diff --git a/.binder/conda-lock.yml b/.binder/conda-lock.yml
index b70c9223..9827780b 100644
--- a/.binder/conda-lock.yml
+++ b/.binder/conda-lock.yml
@@ -14,9 +14,9 @@ version: 1
 metadata:
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     win-64: 9c2b11234e9280108270839dfdba0da926f1145b309292be8bb66956f29e267e
+    osx-arm64: 9f7f80aae213484ab9ac5d43ff57b4890d5b46a1558528835931afb6fa1696e1
   channels:
   - url: conda-forge
     used_env_vars: []
@@ -40,6 +40,19 @@ package:
     sha256: fe51de6107f9edc7aa4f786a70f4a883943bc9d39b3bb7307c04c41410990726
   category: main
   optional: false
+- name: _openmp_mutex
+  version: '4.5'
+  manager: conda
+  platform: linux-64
+  dependencies:
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+    libgomp: '>=7.5.0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-2_gnu.tar.bz2
+  hash:
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+  category: main
+  optional: false
 - name: _r-mutex
   version: 1.0.1
   manager: conda
@@ -51,5375 +64,5543 @@ package:
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   category: main
   optional: false
-- name: ca-certificates
-  version: 2023.7.22
+- name: _r-mutex
+  version: 1.0.1
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/linux-64/ca-certificates-2023.7.22-hbcca054_0.conda
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-- name: font-ttf-dejavu-sans-mono
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+  version: 1.0.1
   manager: conda
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+  platform: win-64
   dependencies: {}
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+  url: https://conda.anaconda.org/conda-forge/noarch/_r-mutex-1.0.1-anacondar_1.tar.bz2
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-- name: font-ttf-inconsolata
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   platform: linux-64
-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/noarch/font-ttf-inconsolata-3.000-h77eed37_0.tar.bz2
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-  dependencies: {}
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-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/noarch/font-ttf-ubuntu-0.83-hab24e00_0.tar.bz2
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-  url: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.40-h41732ed_0.conda
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-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/noarch/poppler-data-0.4.12-hd8ed1ab_0.conda
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-  url: https://conda.anaconda.org/conda-forge/linux-64/python_abi-3.12-4_cp312.conda
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   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/fonts-conda-forge-1-0.tar.bz2
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+  platform: win-64
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+    python: '>=3.8'
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+  platform: osx-64
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   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-13.2.0-h807b86a_2.conda
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+    python: '>=3.8'
+    sniffio: '>=1.1'
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+  url: https://conda.anaconda.org/conda-forge/noarch/anyio-4.0.0-pyhd8ed1ab_0.conda
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-- name: libnsl
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-- name: libsodium
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-- name: openssl
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-- name: sed
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-- name: tzcode
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-- name: xorg-kbproto
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   manager: conda
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-- name: xorg-libice
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   manager: conda
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-- name: xorg-libxau
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-- name: xorg-libxdmcp
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-- name: xz
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-- name: yaml
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-- name: gcc_impl_linux-64
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-- name: glpk
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-- name: hdf4
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-- name: jq
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-- name: libbrotlidec
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   manager: conda
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+  platform: win-64
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-- name: libbrotlienc
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   manager: conda
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   dependencies:
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-- name: libedit
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   manager: conda
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-- name: libgfortran-ng
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   manager: conda
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-- name: libkml
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-- name: libnghttp2
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   optional: false
-- name: libpng
-  version: 1.6.39
+- name: blosc
+  version: 1.21.5
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    libgcc-ng: '>=12'
+    libcxx: '>=15.0.7'
     libzlib: '>=1.2.13,<1.3.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/libpng-1.6.39-h753d276_0.conda
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+    snappy: '>=1.1.10,<2.0a0'
+    zstd: '>=1.5.5,<1.6.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/blosc-1.21.5-heccf04b_0.conda
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-- name: libprotobuf
-  version: 4.24.4
+- name: blosc
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   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-    libstdcxx-ng: '>=12'
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     libzlib: '>=1.2.13,<1.3.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/libprotobuf-4.24.4-hf27288f_0.conda
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+    snappy: '>=1.1.10,<2.0a0'
+    zstd: '>=1.5.5,<1.6.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/blosc-1.21.5-hc338f07_0.conda
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-- name: librttopo
-  version: 1.1.0
+- name: blosc
+  version: 1.21.5
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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-    libstdcxx-ng: '>=12'
-  url: https://conda.anaconda.org/conda-forge/linux-64/librttopo-1.1.0-hb58d41b_14.conda
+    libzlib: '>=1.2.13,<1.3.0a0'
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+    snappy: '>=1.1.10,<2.0a0'
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+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+    zstd: '>=1.5.5,<1.6.0a0'
+  url: https://conda.anaconda.org/conda-forge/win-64/blosc-1.21.5-hdccc3a2_0.conda
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-- name: libsqlite
-  version: 3.43.2
+- name: bokeh
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   manager: conda
   platform: linux-64
   dependencies:
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-    libzlib: '>=1.2.13,<1.3.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.43.2-h2797004_0.conda
+    contourpy: '>=1'
+    jinja2: '>=2.9'
+    numpy: '>=1.16'
+    packaging: '>=16.8'
+    pandas: '>=1.2'
+    pillow: '>=7.1.0'
+    python: '>=3.9'
+    pyyaml: '>=3.10'
+    tornado: '>=5.1'
+    xyzservices: '>=2021.09.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/bokeh-3.3.4-pyhd8ed1ab_0.conda
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-- name: libssh2
-  version: 1.11.0
+- name: bokeh
+  version: 3.3.4
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    libgcc-ng: '>=12'
-    libzlib: '>=1.2.13,<1.3.0a0'
-    openssl: '>=3.1.1,<4.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/libssh2-1.11.0-h0841786_0.conda
+    python: '>=3.9'
+    numpy: '>=1.16'
+    pyyaml: '>=3.10'
+    pandas: '>=1.2'
+    tornado: '>=5.1'
+    pillow: '>=7.1.0'
+    packaging: '>=16.8'
+    jinja2: '>=2.9'
+    contourpy: '>=1'
+    xyzservices: '>=2021.09.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/bokeh-3.3.4-pyhd8ed1ab_0.conda
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   optional: false
-- name: libudunits2
-  version: 2.2.28
+- name: bokeh
+  version: 3.3.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-    libgcc-ng: '>=12'
-  url: https://conda.anaconda.org/conda-forge/linux-64/libudunits2-2.2.28-h40f5838_3.conda
+    python: '>=3.9'
+    numpy: '>=1.16'
+    pyyaml: '>=3.10'
+    pandas: '>=1.2'
+    tornado: '>=5.1'
+    pillow: '>=7.1.0'
+    packaging: '>=16.8'
+    jinja2: '>=2.9'
+    contourpy: '>=1'
+    xyzservices: '>=2021.09.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/bokeh-3.3.0-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: libxcb
-  version: '1.15'
+- name: bokeh
+  version: 3.3.4
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    libgcc-ng: '>=12'
-    pthread-stubs: ''
-    xorg-libxau: ''
-    xorg-libxdmcp: ''
-  url: https://conda.anaconda.org/conda-forge/linux-64/libxcb-1.15-h0b41bf4_0.conda
+    python: '>=3.9'
+    numpy: '>=1.16'
+    pyyaml: '>=3.10'
+    pandas: '>=1.2'
+    tornado: '>=5.1'
+    pillow: '>=7.1.0'
+    packaging: '>=16.8'
+    jinja2: '>=2.9'
+    contourpy: '>=1'
+    xyzservices: '>=2021.09.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/bokeh-3.3.4-pyhd8ed1ab_0.conda
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-- name: libxml2
-  version: 2.11.5
+- name: branca
+  version: 0.7.1
   manager: conda
   platform: linux-64
   dependencies:
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-    libgcc-ng: '>=12'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libxml2-2.11.5-h232c23b_1.conda
+    jinja2: '>=3'
+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/branca-0.7.1-pyhd8ed1ab_0.conda
   hash:
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   category: main
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-- name: libzip
-  version: 1.10.1
+- name: branca
+  version: 0.7.1
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
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-    libgcc-ng: '>=12'
-    libzlib: '>=1.2.13,<1.3.0a0'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libzip-1.10.1-h2629f0a_3.conda
+    python: '>=3.7'
+    jinja2: '>=3'
+  url: https://conda.anaconda.org/conda-forge/noarch/branca-0.7.1-pyhd8ed1ab_0.conda
   hash:
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   optional: false
-- name: pcre2
-  version: '10.40'
+- name: branca
+  version: 0.6.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-    libgcc-ng: '>=12'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/pcre2-10.40-hc3806b6_0.tar.bz2
+    setuptools: ''
+    jinja2: ''
+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/branca-0.6.0-pyhd8ed1ab_0.tar.bz2
   hash:
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   optional: false
-- name: readline
-  version: '8.2'
+- name: branca
+  version: 0.7.1
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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-    ncurses: '>=6.3,<7.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/readline-8.2-h8228510_1.conda
+    python: '>=3.7'
+    jinja2: '>=3'
+  url: https://conda.anaconda.org/conda-forge/noarch/branca-0.7.1-pyhd8ed1ab_0.conda
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   optional: false
-- name: tk
-  version: 8.6.13
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+  version: 1.1.0
   manager: conda
   platform: linux-64
   dependencies:
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+    libbrotlidec: 1.1.0
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     libgcc-ng: '>=12'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-h2797004_0.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/brotli-1.1.0-hd590300_1.conda
   hash:
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-- name: xorg-libsm
-  version: 1.2.4
+- name: brotli
+  version: 1.1.0
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
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-    libuuid: '>=2.38.1,<3.0a0'
-    xorg-libice: '>=1.1.1,<2.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libsm-1.2.4-h7391055_0.conda
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+    libbrotlidec: 1.1.0
+    libbrotlienc: 1.1.0
+  url: https://conda.anaconda.org/conda-forge/osx-64/brotli-1.1.0-h0dc2134_1.conda
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   optional: false
-- name: zeromq
-  version: 4.3.5
+- name: brotli
+  version: 1.1.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-    libsodium: '>=1.0.18,<1.0.19.0a0'
-    libstdcxx-ng: '>=12'
-  url: https://conda.anaconda.org/conda-forge/linux-64/zeromq-4.3.5-h59595ed_0.conda
+    brotli-bin: 1.1.0
+    libbrotlidec: 1.1.0
+    libbrotlienc: 1.1.0
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/brotli-1.1.0-hb547adb_1.conda
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   optional: false
-- name: zlib
-  version: 1.2.13
+- name: brotli
+  version: 1.1.0
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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-    libzlib: 1.2.13
-  url: https://conda.anaconda.org/conda-forge/linux-64/zlib-1.2.13-hd590300_5.conda
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+    vc: '>=14.2,<15'
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+  url: https://conda.anaconda.org/conda-forge/win-64/brotli-1.1.0-hcfcfb64_1.conda
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   optional: false
-- name: zstd
-  version: 1.5.5
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   manager: conda
   platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.5-hfc55251_0.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/brotli-bin-1.1.0-hd590300_1.conda
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   optional: false
-- name: blosc
-  version: 1.21.5
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+  version: 1.1.0
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
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-    libstdcxx-ng: '>=12'
-    libzlib: '>=1.2.13,<1.3.0a0'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/blosc-1.21.5-h0f2a231_0.conda
+    libbrotlidec: 1.1.0
+    libbrotlienc: 1.1.0
+  url: https://conda.anaconda.org/conda-forge/osx-64/brotli-bin-1.1.0-h0dc2134_1.conda
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   category: main
   optional: false
 - name: brotli-bin
   version: 1.1.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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     libbrotlienc: 1.1.0
-    libgcc-ng: '>=12'
-  url: https://conda.anaconda.org/conda-forge/linux-64/brotli-bin-1.1.0-hd590300_1.conda
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/brotli-bin-1.1.0-hb547adb_1.conda
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   optional: false
-- name: bwidget
-  version: 1.9.14
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+  version: 1.1.0
   manager: conda
-  platform: linux-64
+  platform: win-64
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-- name: freetype
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   manager: conda
   platform: linux-64
   dependencies:
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+    python: '>=3.12.0rc3,<3.13.0a0'
+    python_abi: 3.12.*
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-- name: gfortran_impl_linux-64
-  version: 13.2.0
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   manager: conda
-  platform: linux-64
+  platform: osx-64
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+    python: '>=3.12.0rc3,<3.13.0a0'
+    python_abi: 3.12.*
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-- name: gxx_impl_linux-64
-  version: 13.2.0
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+  version: 1.1.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/linux-64/gxx_impl_linux-64-13.2.0-h338b0a0_2.conda
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+    python: '>=3.12.0rc3,<3.13.0a0'
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-- name: krb5
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   manager: conda
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+  platform: win-64
   dependencies:
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+  url: https://conda.anaconda.org/conda-forge/win-64/brotli-python-1.1.0-py312h53d5487_1.conda
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-- name: libarchive
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   manager: conda
   platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libarchive-3.7.2-h039dbb9_0.conda
+    tk: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/bwidget-1.9.14-ha770c72_1.tar.bz2
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-- name: libglib
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   manager: conda
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libglib-2.78.0-hebfc3b9_0.conda
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+  url: https://conda.anaconda.org/conda-forge/osx-64/bwidget-1.9.14-h694c41f_1.tar.bz2
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-- name: libopenblas
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   manager: conda
   platform: linux-64
   dependencies:
     libgcc-ng: '>=12'
-    libgfortran-ng: ''
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-- name: libtiff
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   manager: conda
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libtiff-4.6.0-ha9c0a0a_2.conda
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-- name: libxslt
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libxslt-1.1.37-h0054252_1.conda
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-- name: minizip
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   manager: conda
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+  platform: win-64
   dependencies:
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+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-hcfcfb64_5.conda
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-- name: nss
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   manager: conda
   platform: linux-64
   dependencies:
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     libgcc-ng: '>=12'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/nss-3.94-h1d7d5a4_0.conda
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-- name: pandoc
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   manager: conda
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-    zlib: ''
-  url: https://conda.anaconda.org/conda-forge/linux-64/pandoc-3.1.3-h32600fe_0.conda
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-- name: python
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   manager: conda
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+  platform: osx-arm64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/c-ares-1.20.1-h93a5062_1.conda
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-- name: sqlite
-  version: 3.43.2
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   manager: conda
   platform: linux-64
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-  url: https://conda.anaconda.org/conda-forge/linux-64/sqlite-3.43.2-h2c6b66d_0.conda
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+  url: https://conda.anaconda.org/conda-forge/linux-64/ca-certificates-2024.2.2-hbcca054_0.conda
   hash:
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-- name: tiledb
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   manager: conda
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   optional: false
-- name: tktable
-  version: '2.10'
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   manager: conda
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-  url: https://conda.anaconda.org/conda-forge/linux-64/tktable-2.10-h0c5db8f_5.conda
+  platform: osx-arm64
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+  url: https://conda.anaconda.org/conda-forge/osx-arm64/ca-certificates-2023.7.22-hf0a4a13_0.conda
   hash:
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-- name: udunits2
-  version: 2.2.28
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+  version: 2024.2.2
+  manager: conda
+  platform: win-64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/win-64/ca-certificates-2024.2.2-h56e8100_0.conda
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   manager: conda
   platform: linux-64
   dependencies:
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+    cached_property: '>=1.5.2,<1.5.3.0a0'
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   category: main
   optional: false
-- name: xorg-libx11
-  version: 1.8.7
+- name: cached-property
+  version: 1.5.2
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    libgcc-ng: '>=12'
-    libxcb: '>=1.15,<1.16.0a0'
-    xorg-kbproto: ''
-    xorg-xextproto: '>=7.3.0,<8.0a0'
-    xorg-xproto: ''
-  url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libx11-1.8.7-h8ee46fc_0.conda
+    cached_property: '>=1.5.2,<1.5.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/cached-property-1.5.2-hd8ed1ab_1.tar.bz2
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   category: main
   optional: false
-- name: affine
-  version: 2.4.0
+- name: cached-property
+  version: 1.5.2
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/affine-2.4.0-pyhd8ed1ab_0.conda
+    cached_property: '>=1.5.2,<1.5.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/cached-property-1.5.2-hd8ed1ab_1.tar.bz2
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   category: main
   optional: false
-- name: alabaster
-  version: 0.7.13
+- name: cached-property
+  version: 1.5.2
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/alabaster-0.7.13-pyhd8ed1ab_0.conda
+    cached_property: '>=1.5.2,<1.5.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/cached-property-1.5.2-hd8ed1ab_1.tar.bz2
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   category: main
   optional: false
-- name: antlr-python-runtime
-  version: 4.11.1
+- name: cached_property
+  version: 1.5.2
   manager: conda
   platform: linux-64
   dependencies:
     python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/antlr-python-runtime-4.11.1-pyhd8ed1ab_0.tar.bz2
+  url: https://conda.anaconda.org/conda-forge/noarch/cached_property-1.5.2-pyha770c72_1.tar.bz2
   hash:
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   category: main
   optional: false
-- name: asciitree
-  version: 0.3.3
+- name: cached_property
+  version: 1.5.2
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    python: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/asciitree-0.3.3-py_2.tar.bz2
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/cached_property-1.5.2-pyha770c72_1.tar.bz2
   hash:
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   category: main
   optional: false
-- name: attrs
-  version: 23.1.0
+- name: cached_property
+  version: 1.5.2
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/attrs-23.1.0-pyh71513ae_1.conda
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/cached_property-1.5.2-pyha770c72_1.tar.bz2
   hash:
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   category: main
   optional: false
-- name: backcall
-  version: 0.2.0
+- name: cached_property
+  version: 1.5.2
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    python: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/backcall-0.2.0-pyh9f0ad1d_0.tar.bz2
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/cached_property-1.5.2-pyha770c72_1.tar.bz2
   hash:
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   category: main
   optional: false
-- name: backports
-  version: '1.0'
+- name: cairo
+  version: 1.18.0
   manager: conda
   platform: linux-64
   dependencies:
-    python: '>=2.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/backports-1.0-pyhd8ed1ab_3.conda
+    fontconfig: '>=2.14.2,<3.0a0'
+    fonts-conda-ecosystem: ''
+    freetype: '>=2.12.1,<3.0a0'
+    icu: '>=73.2,<74.0a0'
+    libgcc-ng: '>=12'
+    libglib: '>=2.78.0,<3.0a0'
+    libpng: '>=1.6.39,<1.7.0a0'
+    libstdcxx-ng: '>=12'
+    libxcb: '>=1.15,<1.16.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    pixman: '>=0.42.2,<1.0a0'
+    xorg-libice: '>=1.1.1,<2.0a0'
+    xorg-libsm: '>=1.2.4,<2.0a0'
+    xorg-libx11: '>=1.8.6,<2.0a0'
+    xorg-libxext: '>=1.3.4,<2.0a0'
+    xorg-libxrender: '>=0.9.11,<0.10.0a0'
+    zlib: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/cairo-1.18.0-h3faef2a_0.conda
   hash:
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-    sha256: 711602276ae39276cb0faaca6fd0ac851fff0ca17151917569174841ef830bbd
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   category: main
   optional: false
-- name: bagit
-  version: 1.8.1
+- name: cairo
+  version: 1.18.0
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    python: '>=3'
-  url: https://conda.anaconda.org/conda-forge/noarch/bagit-1.8.1-pyhd8ed1ab_0.tar.bz2
+    __osx: '>=10.9'
+    fontconfig: '>=2.14.2,<3.0a0'
+    fonts-conda-ecosystem: ''
+    freetype: '>=2.12.1,<3.0a0'
+    icu: '>=73.2,<74.0a0'
+    libcxx: '>=16.0.6'
+    libglib: '>=2.78.0,<3.0a0'
+    libpng: '>=1.6.39,<1.7.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    pixman: '>=0.42.2,<1.0a0'
+    zlib: ''
+  url: https://conda.anaconda.org/conda-forge/osx-64/cairo-1.18.0-h99e66fa_0.conda
   hash:
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   category: main
   optional: false
-- name: brotli
-  version: 1.1.0
+- name: cairo
+  version: 1.18.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    brotli-bin: 1.1.0
-    libbrotlidec: 1.1.0
-    libbrotlienc: 1.1.0
-    libgcc-ng: '>=12'
-  url: https://conda.anaconda.org/conda-forge/linux-64/brotli-1.1.0-hd590300_1.conda
+    __osx: '>=10.9'
+    fontconfig: '>=2.14.2,<3.0a0'
+    fonts-conda-ecosystem: ''
+    freetype: '>=2.12.1,<3.0a0'
+    icu: '>=73.2,<74.0a0'
+    libcxx: '>=16.0.6'
+    libglib: '>=2.78.0,<3.0a0'
+    libpng: '>=1.6.39,<1.7.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    pixman: '>=0.42.2,<1.0a0'
+    zlib: ''
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/cairo-1.18.0-hd1e100b_0.conda
   hash:
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-    sha256: f2d918d351edd06c55a6c2d84b488fe392f85ea018ff227daac07db22b408f6b
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   category: main
   optional: false
-- name: brotli-python
-  version: 1.1.0
+- name: cairo
+  version: 1.18.0
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    libgcc-ng: '>=12'
-    libstdcxx-ng: '>=12'
-    python: '>=3.12.0rc3,<3.13.0a0'
-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/linux-64/brotli-python-1.1.0-py312h30efb56_1.conda
+    fontconfig: '>=2.14.2,<3.0a0'
+    fonts-conda-ecosystem: ''
+    freetype: '>=2.12.1,<3.0a0'
+    icu: '>=73.2,<74.0a0'
+    libglib: '>=2.78.0,<3.0a0'
+    libpng: '>=1.6.39,<1.7.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    pixman: '>=0.42.2,<1.0a0'
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+    zlib: ''
+  url: https://conda.anaconda.org/conda-forge/win-64/cairo-1.18.0-h1fef639_0.conda
   hash:
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   category: main
   optional: false
-- name: cached_property
-  version: 1.5.2
+- name: cartopy
+  version: 0.22.0
   manager: conda
   platform: linux-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/cached_property-1.5.2-pyha770c72_1.tar.bz2
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    matplotlib-base: '>=3.4'
+    numpy: '>=1.26.0,<2.0a0'
+    packaging: '>=20'
+    pyproj: '>=3.1.0'
+    pyshp: '>=2.1'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    shapely: '>=1.7'
+  url: https://conda.anaconda.org/conda-forge/linux-64/cartopy-0.22.0-py312hfb8ada1_1.conda
   hash:
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+    sha256: ce7797a12c0e39ef65ffe8ebdee284de76daac3dce8ea48438a7904df8e5ea45
   category: main
   optional: false
-- name: certifi
-  version: 2023.7.22
+- name: cartopy
+  version: 0.22.0
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/certifi-2023.7.22-pyhd8ed1ab_0.conda
+    __osx: '>=10.9'
+    libcxx: '>=16.0.6'
+    matplotlib-base: '>=3.4'
+    numpy: '>=1.26.0,<2.0a0'
+    packaging: '>=20'
+    pyproj: '>=3.1.0'
+    pyshp: '>=2.1'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    shapely: '>=1.7'
+  url: https://conda.anaconda.org/conda-forge/osx-64/cartopy-0.22.0-py312haf8ecfc_1.conda
   hash:
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   category: main
   optional: false
-- name: cfgv
-  version: 3.3.1
+- name: cartopy
+  version: 0.22.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    python: '>=3.6.1'
-  url: https://conda.anaconda.org/conda-forge/noarch/cfgv-3.3.1-pyhd8ed1ab_0.tar.bz2
+    __osx: '>=10.9'
+    libcxx: '>=16.0.6'
+    matplotlib-base: '>=3.4'
+    numpy: '>=1.26.0,<2.0a0'
+    packaging: '>=20'
+    pyproj: '>=3.1.0'
+    pyshp: '>=2.1'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    shapely: '>=1.7'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/cartopy-0.22.0-py312h9e53831_1.conda
   hash:
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   category: main
   optional: false
-- name: chardet
-  version: 5.2.0
+- name: cartopy
+  version: 0.22.0
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    python: '>=3.12.0rc3,<3.13.0a0'
+    matplotlib-base: '>=3.4'
+    numpy: '>=1.26.0,<2.0a0'
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+    pyproj: '>=3.1.0'
+    pyshp: '>=2.1'
+    python: '>=3.12,<3.13.0a0'
     python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/linux-64/chardet-5.2.0-py312h7900ff3_1.conda
+    shapely: '>=1.7'
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/cartopy-0.22.0-py312h2ab9e98_1.conda
   hash:
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   category: main
   optional: false
-- name: charset-normalizer
-  version: 3.3.1
+- name: cc-plugin-glider
+  version: 2.0.3
   manager: conda
   platform: linux-64
   dependencies:
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/charset-normalizer-3.3.1-pyhd8ed1ab_0.conda
+    compliance-checker: '>=4.3.2'
+    python: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/cc-plugin-glider-2.0.3-pyh9f0ad1d_0.tar.bz2
   hash:
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+    sha256: b7d90c01cfcd87b8741c1c2b5bc7833dbdf0f07ed5ab9204ed0b124f3f5a23b9
   category: main
   optional: false
-- name: click
-  version: 8.1.7
+- name: cc-plugin-glider
+  version: 2.0.3
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    __unix: ''
-    python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/click-8.1.7-unix_pyh707e725_0.conda
+    python: ''
+    compliance-checker: '>=4.3.2'
+  url: https://conda.anaconda.org/conda-forge/noarch/cc-plugin-glider-2.0.3-pyh9f0ad1d_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: colorama
-  version: 0.4.6
+- name: cc-plugin-glider
+  version: 2.0.3
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/colorama-0.4.6-pyhd8ed1ab_0.tar.bz2
+    python: ''
+    compliance-checker: '>=4.3.2'
+  url: https://conda.anaconda.org/conda-forge/noarch/cc-plugin-glider-2.0.3-pyh9f0ad1d_0.tar.bz2
   hash:
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-- name: humanize
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/humanize-4.8.0-pyhd8ed1ab_0.conda
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-- name: hyperframe
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   manager: conda
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+  platform: win-64
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-- name: idna
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   manager: conda
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   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/idna-3.4-pyhd8ed1ab_0.tar.bz2
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-- name: imagesize
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   manager: conda
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/imagesize-1.4.1-pyhd8ed1ab_0.tar.bz2
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-- name: iniconfig
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/iniconfig-2.0.0-pyhd8ed1ab_0.conda
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-- name: ipython_genutils
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   manager: conda
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+  platform: win-64
   dependencies:
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-- name: json5
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-- name: jupyterlab_widgets
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+  platform: osx-arm64
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-  url: https://conda.anaconda.org/conda-forge/noarch/jupyterlab_widgets-3.0.9-pyhd8ed1ab_0.conda
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+  platform: win-64
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-- name: lcms2
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   manager: conda
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-- name: libpq
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   manager: conda
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-- name: libv8
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-- name: lxml
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-- name: markupsafe
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-- name: mistune
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-- name: rfc3986-validator
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+  platform: win-64
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-- name: simplekml
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-- name: soupsieve
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+  platform: win-64
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-- name: sphinxcontrib-jsmath
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-- name: threadpoolctl
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-- name: tomli
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-- name: tornado
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   manager: conda
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   dependencies:
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-    python: '>=3.12.0rc3,<3.13.0a0'
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-- name: traitlets
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-- name: types-python-dateutil
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-- name: typing_extensions
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   manager: conda
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   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.8.0-pyha770c72_0.conda
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-- name: typing_utils
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   dependencies:
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-- name: tzlocal
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   dependencies:
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-- name: uc-micro-py
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-- name: pip
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-- name: postgresql
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-- name: proj
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-- name: protobuf
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-- name: pyct-core
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-- name: pytest
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+  platform: win-64
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-- name: python-dateutil
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-- name: pyviz_comms
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-- name: qtpy
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-- name: rfc3339-validator
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-- name: ruamel.yaml
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-- name: tinycss2
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-- name: tqdm
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-- name: traittypes
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-- name: typing-extensions
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-- name: urllib3
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-- name: xerces-c
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-- name: argon2-cffi-bindings
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-- name: arrow
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+- name: fiona
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   manager: conda
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+  platform: osx-arm64
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-  url: https://conda.anaconda.org/conda-forge/noarch/arrow-1.3.0-pyhd8ed1ab_0.conda
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+    python_abi: 3.12.*
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+    shapely: ''
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-- name: branca
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   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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     setuptools: ''
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   manager: conda
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-- name: geotiff
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   manager: conda
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+  platform: osx-64
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-- name: gitpython
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/gitpython-3.1.40-pyhd8ed1ab_0.conda
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+    pycodestyle: '>=2.11.0,<2.12.0'
+    pyflakes: '>=3.1.0,<3.2.0'
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-- name: gsl
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   manager: conda
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+  platform: win-64
   dependencies:
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-- name: harfbuzz
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   manager: conda
   platform: linux-64
   dependencies:
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+    branca: '>=0.7.0'
+    jinja2: '>=2.9'
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+    python: '>=3.7'
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+  url: https://conda.anaconda.org/conda-forge/noarch/folium-0.15.1-pyhd8ed1ab_0.conda
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-- name: httpcore
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   manager: conda
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/httpcore-0.18.0-pyhd8ed1ab_0.conda
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-- name: importlib_metadata
-  version: 6.8.0
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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+    jinja2: '>=2.9'
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-- name: jsonschema-specifications
-  version: 2023.7.1
+- name: folium
+  version: 0.15.1
   manager: conda
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+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-specifications-2023.7.1-pyhd8ed1ab_0.conda
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+    python: '>=3.7'
+    jinja2: '>=2.9'
+    branca: '>=0.7.0'
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-- name: jupyter_server_terminals
-  version: 0.4.4
+- name: font-ttf-dejavu-sans-mono
+  version: '2.37'
   manager: conda
   platform: linux-64
-  dependencies:
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-    terminado: '>=0.8.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_server_terminals-0.4.4-pyhd8ed1ab_1.conda
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+  url: https://conda.anaconda.org/conda-forge/noarch/font-ttf-dejavu-sans-mono-2.37-hab24e00_0.tar.bz2
   hash:
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-- name: kealib
-  version: 1.5.2
+- name: font-ttf-dejavu-sans-mono
+  version: '2.37'
   manager: conda
-  platform: linux-64
-  dependencies:
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-  url: https://conda.anaconda.org/conda-forge/linux-64/kealib-1.5.2-hcd42e92_1.conda
+  platform: osx-64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/noarch/font-ttf-dejavu-sans-mono-2.37-hab24e00_0.tar.bz2
   hash:
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-- name: libnetcdf
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+- name: font-ttf-dejavu-sans-mono
+  version: '2.37'
   manager: conda
-  platform: linux-64
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-  url: https://conda.anaconda.org/conda-forge/linux-64/libnetcdf-4.9.2-nompi_h80fb2b6_112.conda
+  platform: osx-arm64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/noarch/font-ttf-dejavu-sans-mono-2.37-hab24e00_0.tar.bz2
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-- name: libspatialite
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+- name: font-ttf-dejavu-sans-mono
+  version: '2.37'
   manager: conda
-  platform: linux-64
-  dependencies:
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-    sqlite: ''
-    zlib: ''
-  url: https://conda.anaconda.org/conda-forge/linux-64/libspatialite-5.1.0-h090f1da_0.conda
+  platform: win-64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/noarch/font-ttf-dejavu-sans-mono-2.37-hab24e00_0.tar.bz2
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   optional: false
-- name: markdown
-  version: '3.5'
+- name: font-ttf-inconsolata
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   manager: conda
   platform: linux-64
-  dependencies:
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-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/markdown-3.5-pyhd8ed1ab_0.conda
+  dependencies: {}
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-- name: mdit-py-plugins
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+- name: font-ttf-inconsolata
+  version: '3.000'
   manager: conda
-  platform: linux-64
-  dependencies:
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-    python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/mdit-py-plugins-0.4.0-pyhd8ed1ab_0.conda
+  platform: osx-64
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+  url: https://conda.anaconda.org/conda-forge/noarch/font-ttf-inconsolata-3.000-h77eed37_0.tar.bz2
   hash:
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-- name: numpy
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+  version: '3.000'
   manager: conda
-  platform: linux-64
-  dependencies:
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-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/linux-64/numpy-1.26.0-py312heda63a1_0.conda
+  platform: osx-arm64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/noarch/font-ttf-inconsolata-3.000-h77eed37_0.tar.bz2
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   manager: conda
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   manager: conda
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   manager: conda
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-- name: pygeoif
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   manager: conda
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-- name: pyproj
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   manager: conda
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   manager: conda
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-- name: sqlalchemy
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   manager: conda
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   manager: conda
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-- name: trio
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   dependencies:
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   manager: conda
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+  platform: osx-64
   dependencies:
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   manager: conda
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   dependencies:
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-- name: wsproto
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   manager: conda
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   dependencies:
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-- name: argon2-cffi
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   manager: conda
   platform: linux-64
   dependencies:
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-- name: cftime
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   manager: conda
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   dependencies:
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-- name: contourpy
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   manager: conda
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   dependencies:
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-- name: folium
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   manager: conda
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+  platform: win-64
   dependencies:
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-- name: github3.py
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   manager: conda
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   dependencies:
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+    font-ttf-dejavu-sans-mono: ''
+    font-ttf-inconsolata: ''
+    font-ttf-source-code-pro: ''
+    font-ttf-ubuntu: ''
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-- name: gsw
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   manager: conda
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   dependencies:
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+    font-ttf-source-code-pro: ''
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-- name: httpx
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   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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+    font-ttf-source-code-pro: ''
+    font-ttf-dejavu-sans-mono: ''
+    font-ttf-ubuntu: ''
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-- name: identify
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   manager: conda
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+  platform: win-64
   dependencies:
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-    ukkonen: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/identify-2.5.31-pyhd8ed1ab_0.conda
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+    font-ttf-source-code-pro: ''
+    font-ttf-ubuntu: ''
+    font-ttf-dejavu-sans-mono: ''
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-- name: isoduration
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   manager: conda
   platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/isoduration-20.11.0-pyhd8ed1ab_0.tar.bz2
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-- name: jsonschema
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   manager: conda
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+  platform: osx-64
   dependencies:
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+    brotli: ''
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-- name: jupyter_core
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+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/linux-64/jupyter_core-5.4.0-py312h7900ff3_0.conda
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-- name: libgdal
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+  platform: win-64
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+    brotli: ''
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-- name: netcdf-fortran
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   dependencies:
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-- name: numcodecs
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   manager: conda
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+  platform: osx-64
   dependencies:
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-- name: owslib
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-- name: pandas
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   manager: conda
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+  platform: win-64
   dependencies:
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-    libstdcxx-ng: '>=12'
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-- name: pango
-  version: 1.50.14
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   manager: conda
   platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/linux-64/pango-1.50.14-ha41ecd1_2.conda
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-- name: prompt-toolkit
-  version: 3.0.39
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   manager: conda
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+  platform: osx-64
   dependencies:
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-    wcwidth: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/prompt-toolkit-3.0.39-pyha770c72_0.conda
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-- name: pybtex-docutils
-  version: 1.0.3
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-    pybtex: '>=0.16'
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-- name: pyct
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   manager: conda
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+  platform: win-64
   dependencies:
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-    python: ''
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-- name: pygc
-  version: 1.3.0
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   manager: conda
   platform: linux-64
   dependencies:
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-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/pygc-1.3.0-pyhd8ed1ab_0.tar.bz2
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-- name: pykdtree
-  version: 1.3.9
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   manager: conda
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+  platform: osx-64
   dependencies:
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-- name: pyworms
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-    requests: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/pyworms-0.4.0-pyhd8ed1ab_0.conda
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-- name: scipy
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+- name: freexl
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+  manager: conda
+  platform: win-64
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   manager: conda
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-  url: https://conda.anaconda.org/conda-forge/linux-64/scipy-1.11.3-py312heda63a1_1.conda
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-- name: seawater
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+- name: fribidi
+  version: 1.0.10
+  manager: conda
+  platform: osx-64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-64/fribidi-1.0.10-hbcb3906_0.tar.bz2
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   manager: conda
   platform: linux-64
   dependencies:
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-    python: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/seawater-3.3.4-py_1.tar.bz2
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   optional: false
-- name: shapely
-  version: 2.0.2
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   manager: conda
   platform: linux-64
   dependencies:
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     python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/linux-64/shapely-2.0.2-py312h1cd15a4_0.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/gdal-3.8.4-py312h257dd4b_0.conda
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-- name: snuggs
-  version: 1.4.7
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   manager: conda
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+  platform: osx-64
   dependencies:
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-    pyparsing: '>=2.1.6'
-    python: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/snuggs-1.4.7-py_0.tar.bz2
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+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
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-- name: tempest-remap
-  version: 2.2.0
+- name: gdal
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   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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     hdf5: '>=1.14.2,<1.14.3.0a0'
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+    openssl: '>=3.1.3,<4.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/gdal-3.7.2-py312hb8631af_7.conda
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   category: main
   optional: false
-- name: trio-websocket
-  version: 0.11.1
+- name: geographiclib
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   manager: conda
   platform: linux-64
   dependencies:
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     python: '>=3.7'
-    trio: '>=0.11'
-    wsproto: '>=0.14'
-  url: https://conda.anaconda.org/conda-forge/noarch/trio-websocket-0.11.1-pyhd8ed1ab_0.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/geographiclib-2.0-pyhd8ed1ab_0.tar.bz2
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-- name: virtualenv
-  version: 20.24.6
+- name: geographiclib
+  version: '2.0'
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
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-    filelock: <4,>=3.12.2
-    platformdirs: <4,>=3.9.1
-    python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/virtualenv-20.24.6-pyhd8ed1ab_0.conda
+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/geographiclib-2.0-pyhd8ed1ab_0.tar.bz2
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-- name: bokeh
-  version: 3.3.0
+- name: geographiclib
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   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-    jinja2: '>=2.9'
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-  url: https://conda.anaconda.org/conda-forge/noarch/bokeh-3.3.0-pyhd8ed1ab_0.conda
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/geographiclib-1.52-pyhd8ed1ab_0.tar.bz2
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-- name: cf-units
-  version: 3.2.0
+- name: geographiclib
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   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/linux-64/cf-units-3.2.0-py312hc7c0aa3_4.conda
+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/geographiclib-2.0-pyhd8ed1ab_0.tar.bz2
   hash:
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   optional: false
-- name: colorcet
-  version: 3.0.1
+- name: geojson
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   manager: conda
   platform: linux-64
   dependencies:
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-    python: '>=2.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/colorcet-3.0.1-pyhd8ed1ab_0.tar.bz2
+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/geojson-3.1.0-pyhd8ed1ab_0.conda
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   category: main
   optional: false
-- name: erddapy
-  version: 2.2.0
+- name: geojson
+  version: 3.1.0
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
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-    pandas: <3,>=0.25.2
-    python: '>=3.8'
-    pytz: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/erddapy-2.2.0-pyhd8ed1ab_0.conda
+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/geojson-3.1.0-pyhd8ed1ab_0.conda
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   optional: false
-- name: esmf
-  version: 8.4.2
+- name: geojson
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/linux-64/esmf-8.4.2-nompi_h9e768e6_3.conda
+    python: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/geojson-2.5.0-py_0.tar.bz2
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   optional: false
-- name: gdal
-  version: 3.7.2
+- name: geojson
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   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/linux-64/gdal-3.7.2-py312ha5e4baf_7.conda
+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/geojson-3.1.0-pyhd8ed1ab_0.conda
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 - name: geojsonio
@@ -5436,5533 +5617,5398 @@ package:
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   category: main
   optional: false
-- name: geopandas-base
-  version: 0.14.0
+- name: geojsonio
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   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
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-    pandas: '>=1.4.0'
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-    python: '>=3.9'
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-  url: https://conda.anaconda.org/conda-forge/noarch/geopandas-base-0.14.0-pyha770c72_1.conda
+    python: ''
+    six: ''
+    github3.py: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/geojsonio-0.0.3-py_0.tar.bz2
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   optional: false
-- name: jsonschema-with-format-nongpl
-  version: 4.19.1
+- name: geojsonio
+  version: 0.0.3
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-    idna: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-with-format-nongpl-4.19.1-pyhd8ed1ab_0.conda
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   optional: false
-- name: jupyter_client
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+  version: 0.0.3
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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-    traitlets: '>=5.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_client-8.5.0-pyhd8ed1ab_0.conda
+    python: ''
+    six: ''
+    github3.py: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/geojsonio-0.0.3-py_0.tar.bz2
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   category: main
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-- name: matplotlib-base
-  version: 3.8.0
+- name: geolinks
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   manager: conda
   platform: linux-64
   dependencies:
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-    contourpy: '>=1.0.1'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/matplotlib-base-3.8.0-py312he5832f3_2.conda
+    click: ''
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/geolinks-0.2.3-pyhd8ed1ab_0.conda
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-- name: nbformat
-  version: 5.9.2
+- name: geolinks
+  version: 0.2.3
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
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-    traitlets: '>=5.1'
-  url: https://conda.anaconda.org/conda-forge/noarch/nbformat-5.9.2-pyhd8ed1ab_0.conda
+    click: ''
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/geolinks-0.2.3-pyhd8ed1ab_0.conda
   hash:
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   optional: false
-- name: netcdf4
-  version: 1.6.5
+- name: geolinks
+  version: 0.2.3
   manager: conda
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+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/linux-64/netcdf4-1.6.5-nompi_py312h26027e0_100.conda
+    click: ''
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/geolinks-0.2.3-pyhd8ed1ab_0.conda
   hash:
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-- name: patsy
-  version: 0.5.3
+- name: geolinks
+  version: 0.2.3
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    numpy: '>=1.4.0'
+    click: ''
     python: '>=3.6'
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-    six: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/patsy-0.5.3-pyhd8ed1ab_0.tar.bz2
+  url: https://conda.anaconda.org/conda-forge/noarch/geolinks-0.2.3-pyhd8ed1ab_0.conda
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-- name: pre-commit
-  version: 3.5.0
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   manager: conda
   platform: linux-64
   dependencies:
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-    identify: '>=1.0.0'
-    nodeenv: '>=0.11.1'
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-  url: https://conda.anaconda.org/conda-forge/noarch/pre-commit-3.5.0-pyha770c72_0.conda
+    fiona: '>=1.8.21'
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+    mapclassify: '>=2.4.0'
+    matplotlib-base: ''
+    python: '>=3.9'
+    rtree: ''
+    xyzservices: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/geopandas-0.14.3-pyhd8ed1ab_0.conda
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   optional: false
-- name: prompt_toolkit
-  version: 3.0.39
+- name: geopandas
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   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/prompt_toolkit-3.0.39-hd8ed1ab_0.conda
+    matplotlib-base: ''
+    rtree: ''
+    folium: ''
+    xyzservices: ''
+    python: '>=3.9'
+    mapclassify: '>=2.4.0'
+    fiona: '>=1.8.21'
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+  url: https://conda.anaconda.org/conda-forge/noarch/geopandas-0.14.3-pyhd8ed1ab_0.conda
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   optional: false
-- name: pyobis
-  version: 1.3.1
+- name: geopandas
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   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-    python: '>=3.7'
-    requests: '>2.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/pyobis-1.3.1-pyhd8ed1ab_0.conda
+    matplotlib-base: ''
+    rtree: ''
+    folium: ''
+    xyzservices: ''
+    python: '>=3.9'
+    mapclassify: '>=2.4.0'
+    fiona: '>=1.8.21'
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+  url: https://conda.anaconda.org/conda-forge/noarch/geopandas-0.14.0-pyhd8ed1ab_1.conda
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-- name: pyresample
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-    importlib-metadata: ''
-    libgcc-ng: '>=12'
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   category: main
   optional: false
-- name: r-base
-  version: 4.3.1
+- name: geopandas
+  version: 0.14.3
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    _openmp_mutex: '>=4.5'
-    _r-mutex: 1.*
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-    bzip2: '>=1.0.8,<2.0a0'
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-    tk: '>=8.6.13,<8.7.0a0'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/r-base-4.3.1-h93585b2_6.conda
+    matplotlib-base: ''
+    rtree: ''
+    folium: ''
+    xyzservices: ''
+    python: '>=3.9'
+    mapclassify: '>=2.4.0'
+    fiona: '>=1.8.21'
+    geopandas-base: 0.14.3
+  url: https://conda.anaconda.org/conda-forge/noarch/geopandas-0.14.3-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: rasterio
-  version: 1.3.9
+- name: geopandas-base
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   manager: conda
   platform: linux-64
   dependencies:
-    affine: ''
-    attrs: ''
-    certifi: ''
-    click: '>=4'
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-    snuggs: '>=1.4.1'
-  url: https://conda.anaconda.org/conda-forge/linux-64/rasterio-1.3.9-py312hc719454_0.conda
+    packaging: ''
+    pandas: '>=1.4.0'
+    pyproj: '>=3.3.0'
+    python: '>=3.9'
+    shapely: '>=1.8.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/geopandas-base-0.14.3-pyha770c72_0.conda
   hash:
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   optional: false
-- name: scikit-learn
-  version: 1.3.2
+- name: geopandas-base
+  version: 0.14.3
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
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-    joblib: '>=1.1.1'
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-    libstdcxx-ng: '>=12'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/scikit-learn-1.3.2-py312h394d371_1.conda
+    packaging: ''
+    python: '>=3.9'
+    pandas: '>=1.4.0'
+    shapely: '>=1.8.0'
+    pyproj: '>=3.3.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/geopandas-base-0.14.3-pyha770c72_0.conda
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   category: main
   optional: false
-- name: selenium
-  version: 4.14.0
+- name: geopandas-base
+  version: 0.14.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-    python: '>=3.7'
-    selenium-manager: 4.14.*
-    trio: '>=0.17,<1.dev0'
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-    urllib3: '>=1.26,<3'
-  url: https://conda.anaconda.org/conda-forge/noarch/selenium-4.14.0-pyhd8ed1ab_0.conda
+    packaging: ''
+    python: '>=3.9'
+    pandas: '>=1.4.0'
+    shapely: '>=1.8.0'
+    pyproj: '>=3.3.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/geopandas-base-0.14.0-pyha770c72_1.conda
   hash:
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   category: main
   optional: false
-- name: utide
-  version: 0.3.0
+- name: geopandas-base
+  version: 0.14.3
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    numpy: ''
-    python: '>=3.6'
-    scipy: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/utide-0.3.0-pyhd8ed1ab_0.tar.bz2
+    packaging: ''
+    python: '>=3.9'
+    pandas: '>=1.4.0'
+    shapely: '>=1.8.0'
+    pyproj: '>=3.3.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/geopandas-base-0.14.3-pyha770c72_0.conda
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   category: main
   optional: false
-- name: xarray
-  version: 2023.10.1
+- name: geoplot
+  version: 0.5.1
   manager: conda
   platform: linux-64
   dependencies:
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-    packaging: '>=21.3'
-    pandas: '>=1.4'
-    python: '>=3.9'
-  url: https://conda.anaconda.org/conda-forge/noarch/xarray-2023.10.1-pyhd8ed1ab_0.conda
+    cartopy: ''
+    contextily: '>=1.0.0'
+    geopandas: '>=0.9.0'
+    mapclassify: '>=2.1'
+    matplotlib-base: '>=3.1.2'
+    pandas: ''
+    python: '>=3.7'
+    seaborn-base: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/geoplot-0.5.1-pyhd8ed1ab_0.tar.bz2
   hash:
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   optional: false
-- name: zarr
-  version: 2.16.1
+- name: geoplot
+  version: 0.5.1
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
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-    fasteners: ''
-    numcodecs: '>=0.10.0'
-    numpy: '>=1.20,!=1.21.0'
-    python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/zarr-2.16.1-pyhd8ed1ab_0.conda
+    pandas: ''
+    cartopy: ''
+    seaborn-base: ''
+    python: '>=3.7'
+    geopandas: '>=0.9.0'
+    contextily: '>=1.0.0'
+    mapclassify: '>=2.1'
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+  url: https://conda.anaconda.org/conda-forge/noarch/geoplot-0.5.1-pyhd8ed1ab_0.tar.bz2
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   optional: false
-- name: cartopy
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+- name: geoplot
+  version: 0.5.1
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-    libstdcxx-ng: '>=12'
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-    python_abi: 3.12.*
-    shapely: '>=1.7'
-  url: https://conda.anaconda.org/conda-forge/linux-64/cartopy-0.22.0-py312hfb8ada1_1.conda
+    pandas: ''
+    cartopy: ''
+    seaborn-base: ''
+    python: '>=3.7'
+    geopandas: '>=0.9.0'
+    contextily: '>=1.0.0'
+    mapclassify: '>=2.1'
+    matplotlib-base: '>=3.1.2'
+  url: https://conda.anaconda.org/conda-forge/noarch/geoplot-0.5.1-pyhd8ed1ab_0.tar.bz2
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-- name: cf_xarray
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+- name: geoplot
+  version: 0.5.1
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    python: '>=3.8'
-    xarray: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/cf_xarray-0.8.4-pyhd8ed1ab_0.conda
+    pandas: ''
+    cartopy: ''
+    seaborn-base: ''
+    python: '>=3.7'
+    geopandas: '>=0.9.0'
+    contextily: '>=1.0.0'
+    mapclassify: '>=2.1'
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+  url: https://conda.anaconda.org/conda-forge/noarch/geoplot-0.5.1-pyhd8ed1ab_0.tar.bz2
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   category: main
   optional: false
-- name: cmcrameri
-  version: '1.7'
+- name: geopy
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   manager: conda
   platform: linux-64
   dependencies:
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-    numpy: ''
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/cmcrameri-1.7-pyhd8ed1ab_0.conda
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+  url: https://conda.anaconda.org/conda-forge/noarch/geopy-1.13.0-py_0.tar.bz2
   hash:
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   optional: false
-- name: compliance-checker
-  version: 5.1.0
+- name: geopy
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   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
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-    cftime: '>=1.1.0'
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-    validators: '>=0.14.2'
-  url: https://conda.anaconda.org/conda-forge/noarch/compliance-checker-5.1.0-pyhd8ed1ab_0.conda
+    python: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/geopy-1.13.0-py_0.tar.bz2
   hash:
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   optional: false
-- name: contextily
-  version: 1.4.0
+- name: geopy
+  version: 2.4.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    geopy: ''
-    joblib: ''
-    matplotlib-base: ''
-    mercantile: ''
-    pillow: ''
-    python: '>=3.8'
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-    requests: ''
-    xyzservices: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/contextily-1.4.0-pyhd8ed1ab_0.conda
+    python: '>=3.5'
+    geographiclib: <2,>=1.49
+  url: https://conda.anaconda.org/conda-forge/noarch/geopy-2.4.0-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: descartes
-  version: 1.1.0
+- name: geopy
+  version: 1.13.0
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    matplotlib-base: ''
     python: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/descartes-1.1.0-py_4.tar.bz2
+  url: https://conda.anaconda.org/conda-forge/noarch/geopy-1.13.0-py_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: fiona
-  version: 1.9.5
+- name: geos
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   manager: conda
   platform: linux-64
   dependencies:
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-    click: '>=4.0'
-    click-plugins: '>=1.0'
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     libstdcxx-ng: '>=12'
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-    python_abi: 3.12.*
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-    six: '>=1.7'
-  url: https://conda.anaconda.org/conda-forge/linux-64/fiona-1.9.5-py312hc770a3a_0.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/geos-3.12.1-h59595ed_0.conda
   hash:
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   optional: false
-- name: gridgeo
-  version: 1.5.2
+- name: geos
+  version: 3.12.1
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    docopt: ''
-    netcdf4: ''
-    python: '>=3.6'
-    shapely: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/gridgeo-1.5.2-py_0.tar.bz2
+    __osx: '>=10.9'
+    libcxx: '>=16.0.6'
+  url: https://conda.anaconda.org/conda-forge/osx-64/geos-3.12.1-h93d8f39_0.conda
   hash:
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   optional: false
-- name: ioos_qc
-  version: 1.0.0
+- name: geos
+  version: 3.12.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    geojson: ''
-    netcdf4: ''
-    numpy: '>=1.14'
-    pygc: ''
-    python: ''
-    ruamel.yaml: ''
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-    xarray: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/ioos_qc-1.0.0-pyh9f0ad1d_0.tar.bz2
+    libcxx: '>=15.0.7'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/geos-3.12.0-h13dd4ca_0.conda
   hash:
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   category: main
   optional: false
-- name: ipython
-  version: 8.16.1
+- name: geos
+  version: 3.12.1
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    __linux: ''
-    backcall: ''
-    decorator: ''
-    exceptiongroup: ''
-    jedi: '>=0.16'
-    matplotlib-inline: ''
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-    pygments: '>=2.4.0'
-    python: '>=3.9'
-    stack_data: ''
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-    typing_extensions: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/ipython-8.16.1-pyh0d859eb_0.conda
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/geos-3.12.1-h1537add_0.conda
   hash:
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   optional: false
-- name: jupyter_events
-  version: 0.8.0
+- name: geotiff
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   manager: conda
   platform: linux-64
   dependencies:
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-    python: '>=3.8'
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-    traitlets: '>=5.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_events-0.8.0-pyhd8ed1ab_0.conda
+    libgcc-ng: '>=12'
+    libjpeg-turbo: '>=3.0.0,<4.0a0'
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+    libtiff: '>=4.6.0,<4.7.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    proj: '>=9.3.1,<9.3.2.0a0'
+    zlib: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/geotiff-1.7.1-h6b2125f_15.conda
   hash:
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   optional: false
-- name: mapclassify
-  version: 2.6.1
+- name: geotiff
+  version: 1.7.1
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
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-    numpy: '>=1.23'
-    pandas: '>=1.4,!=1.5.0'
-    python: '>=3.9'
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-    scipy: '>=1.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/mapclassify-2.6.1-pyhd8ed1ab_0.conda
+    __osx: '>=10.9'
+    libcxx: '>=16.0.6'
+    libjpeg-turbo: '>=3.0.0,<4.0a0'
+    libtiff: '>=4.6.0,<4.7.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    proj: '>=9.3.1,<9.3.2.0a0'
+    zlib: ''
+  url: https://conda.anaconda.org/conda-forge/osx-64/geotiff-1.7.1-h509af15_15.conda
   hash:
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   optional: false
-- name: nbclient
-  version: 0.7.4
+- name: geotiff
+  version: 1.7.1
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-    nbformat: '>=5.1'
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-    traitlets: '>=5.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/nbclient-0.7.4-pyhd8ed1ab_0.conda
+    libcxx: '>=15.0.7'
+    libjpeg-turbo: '>=3.0.0,<4.0a0'
+    libtiff: '>=4.6.0,<4.7.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    proj: '>=9.3.0,<9.3.1.0a0'
+    zlib: ''
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/geotiff-1.7.1-h71398c0_14.conda
   hash:
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   category: main
   optional: false
-- name: nc-time-axis
-  version: 1.4.1
+- name: geotiff
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   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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-    matplotlib-base: ''
-    numpy: ''
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/nc-time-axis-1.4.1-pyhd8ed1ab_0.tar.bz2
+    libjpeg-turbo: '>=3.0.0,<4.0a0'
+    libtiff: '>=4.6.0,<4.7.0a0'
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+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+    zlib: ''
+  url: https://conda.anaconda.org/conda-forge/win-64/geotiff-1.7.1-hbf5ca3a_15.conda
   hash:
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   optional: false
-- name: nco
-  version: 5.1.8
+- name: gettext
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   manager: conda
   platform: linux-64
   dependencies:
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-    esmf: ''
-    gsl: '>=2.7,<2.8.0a0'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/nco-5.1.8-h00920e0_1.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/gettext-0.21.1-h27087fc_0.tar.bz2
   hash:
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   optional: false
-- name: odvc
-  version: 1.0.0
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   manager: conda
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+  platform: osx-64
   dependencies:
-    netcdf4: ''
-    numpy: ''
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/odvc-1.0.0-pyhd8ed1ab_0.tar.bz2
+    libiconv: '>=1.17,<2.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/gettext-0.21.1-h8a4c099_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: paegan
-  version: 1.1.4
-  manager: conda
-  platform: linux-64
+- name: gettext
+  version: 0.21.1
+  manager: conda
+  platform: osx-arm64
   dependencies:
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-    numpy: ''
-    python: ''
-    python-dateutil: ''
-    pytz: ''
-    scipy: ''
-    shapely: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/paegan-1.1.4-py_1.tar.bz2
+    libiconv: '>=1.17,<2.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/gettext-0.21.1-h0186832_0.tar.bz2
   hash:
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   optional: false
-- name: pandas-flavor
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-- name: panel
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-- name: pysgrid
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-- name: pyugrid
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   manager: conda
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-  url: https://conda.anaconda.org/conda-forge/noarch/pyugrid-0.3.1-py_2.tar.bz2
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-- name: r-base64enc
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   manager: conda
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+  platform: win-64
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-- name: r-brio
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-- name: r-cli
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-- name: r-clipr
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-- name: r-colorspace
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-- name: r-commonmark
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-- name: r-cpp11
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-- name: r-crayon
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-- name: r-curl
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-- name: r-data.table
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-- name: r-dbi
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+    gmp: '>=6.2.1,<7.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/glpk-5.0-h3cb5acd_0.tar.bz2
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-- name: r-digest
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   manager: conda
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   dependencies:
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     libstdcxx-ng: '>=12'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/r-digest-0.6.33-r43ha503ecb_0.conda
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-- name: r-evaluate
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   manager: conda
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-evaluate-0.22-r43hc72bb7e_0.conda
+    __osx: '>=10.9'
+    libcxx: '>=16.0.6'
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-- name: r-fansi
-  version: 1.0.5
+- name: graphite2
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   manager: conda
   platform: linux-64
   dependencies:
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-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-fansi-1.0.5-r43h57805ef_0.conda
+    libgcc-ng: '>=7.5.0'
+    libstdcxx-ng: '>=7.5.0'
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-- name: r-farver
-  version: 2.1.1
+- name: graphite2
+  version: 1.3.13
   manager: conda
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+  platform: osx-64
   dependencies:
-    libgcc-ng: '>=12'
-    libstdcxx-ng: '>=12'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/r-farver-2.1.1-r43ha503ecb_2.conda
+    libcxx: '>=10.0.1'
+  url: https://conda.anaconda.org/conda-forge/osx-64/graphite2-1.3.13-h2e338ed_1001.tar.bz2
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-- name: r-fastmap
-  version: 1.1.1
+- name: greenlet
+  version: 3.0.3
   manager: conda
   platform: linux-64
   dependencies:
     libgcc-ng: '>=12'
     libstdcxx-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-fastmap-1.1.1-r43ha503ecb_1.conda
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/linux-64/greenlet-3.0.3-py312h30efb56_0.conda
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-- name: r-fs
-  version: 1.6.3
+- name: greenlet
+  version: 3.0.3
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    libgcc-ng: '>=12'
-    libstdcxx-ng: '>=12'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/r-fs-1.6.3-r43ha503ecb_0.conda
+    libcxx: '>=15'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/osx-64/greenlet-3.0.3-py312hede676d_0.conda
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-- name: r-generics
-  version: 0.1.3
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+  version: 3.0.1
   manager: conda
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+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-generics-0.1.3-r43hc72bb7e_2.conda
+    __osx: '>=10.9'
+    libcxx: '>=16.0.6'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/greenlet-3.0.1-py312h650e478_0.conda
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-- name: r-glue
-  version: 1.6.2
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+  version: 3.0.3
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-glue-1.6.2-r43h57805ef_2.conda
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/greenlet-3.0.3-py312h53d5487_0.conda
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-- name: r-httpcode
-  version: 0.3.0
+- name: gridgeo
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   manager: conda
   platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/linux-64/r-httpcode-0.3.0-r43ha770c72_3.conda
+    docopt: ''
+    netcdf4: ''
+    python: '>=3.6'
+    shapely: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/gridgeo-1.5.2-py_0.tar.bz2
   hash:
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   optional: false
-- name: r-isoband
-  version: 0.2.7
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+  version: 1.5.2
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
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-    libstdcxx-ng: '>=12'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/r-isoband-0.2.7-r43ha503ecb_2.conda
+    netcdf4: ''
+    shapely: ''
+    docopt: ''
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/gridgeo-1.5.2-py_0.tar.bz2
   hash:
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-- name: r-jsonlite
-  version: 1.8.7
+- name: gridgeo
+  version: 1.5.2
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-jsonlite-1.8.7-r43h57805ef_0.conda
+    shapely: ''
+    netcdf4: ''
+    docopt: ''
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/gridgeo-1.5.2-py_0.tar.bz2
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-- name: r-kernsmooth
-  version: '2.23_22'
+- name: gridgeo
+  version: 1.5.2
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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-    libgfortran-ng: ''
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-  url: https://conda.anaconda.org/conda-forge/linux-64/r-kernsmooth-2.23_22-r43h13b3f57_0.conda
+    netcdf4: ''
+    shapely: ''
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+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/gridgeo-1.5.2-py_0.tar.bz2
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-- name: r-labeling
-  version: 0.4.3
+- name: gsl
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   manager: conda
   platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-labeling-0.4.3-r43hc72bb7e_0.conda
+    libblas: '>=3.8.0,<4.0a0'
+    libcblas: '>=3.8.0,<4.0a0'
+    libgcc-ng: '>=9.3.0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/gsl-2.7-he838d99_0.tar.bz2
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-- name: r-lattice
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+- name: gsl
+  version: '2.7'
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
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-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-lattice-0.22_5-r43h57805ef_0.conda
+    libblas: '>=3.8.0,<4.0a0'
+    libcblas: '>=3.8.0,<4.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/gsl-2.7-h93259b0_0.tar.bz2
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-- name: r-lazyeval
-  version: 0.2.2
+- name: gsl
+  version: '2.7'
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-lazyeval-0.2.2-r43h57805ef_4.conda
+    libblas: '>=3.9.0,<4.0a0'
+    libcblas: '>=3.9.0,<4.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/gsl-2.7-h6e638da_0.tar.bz2
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-- name: r-magrittr
-  version: 2.0.3
+- name: gsl
+  version: '2.7'
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-magrittr-2.0.3-r43h57805ef_2.conda
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+    libcblas: '>=3.8.0,<4.0a0'
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-- name: r-maps
-  version: 3.4.1
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   manager: conda
   platform: linux-64
   dependencies:
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-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-maps-3.4.1-r43h57805ef_2.conda
+    numpy: '>=1.26.0,<2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/linux-64/gsw-3.6.17-py312hc7c0aa3_1.conda
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-- name: r-mass
-  version: '7.3_60'
+- name: gsw
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   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
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-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-mass-7.3_60-r43h57805ef_1.conda
+    numpy: '>=1.26.0,<2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/osx-64/gsw-3.6.17-py312h3f2338b_1.conda
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   optional: false
-- name: r-mime
-  version: '0.12'
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+  version: 3.6.17
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-mime-0.12-r43h57805ef_2.conda
+    numpy: '>=1.26.0,<2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/gsw-3.6.17-py312hf635c46_1.conda
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-- name: r-ncdf4
-  version: '1.21'
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   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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-- name: r-sys
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-- name: r-utf8
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+    libzlib: '>=1.2.13,<1.3.0a0'
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-- name: r-viridislite
-  version: 0.4.2
+- name: hdf4
+  version: 4.2.15
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-viridislite-0.4.2-r43hc72bb7e_1.conda
+    libcxx: '>=15.0.7'
+    libjpeg-turbo: '>=3.0.0,<4.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/hdf4-4.2.15-h2ee6834_7.conda
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-- name: r-withr
-  version: 2.5.1
+- name: hdf4
+  version: 4.2.15
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-withr-2.5.1-r43hc72bb7e_0.conda
+    libjpeg-turbo: '>=3.0.0,<4.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/hdf4-4.2.15-h5557f11_7.conda
   hash:
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   category: main
   optional: false
-- name: r-xfun
-  version: '0.40'
+- name: hdf5
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   manager: conda
   platform: linux-64
   dependencies:
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+    libcurl: '>=8.4.0,<9.0a0'
     libgcc-ng: '>=12'
+    libgfortran-ng: ''
+    libgfortran5: '>=12.3.0'
     libstdcxx-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-xfun-0.40-r43ha503ecb_0.conda
+    libzlib: '>=1.2.13,<1.3.0a0'
+    openssl: '>=3.2.0,<4.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/hdf5-1.14.3-nompi_h4f84152_100.conda
   hash:
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-- name: r-xml
-  version: 3.99_0.14
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   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
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-    libxml2: '>=2.11.4,<2.12.0a0'
-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-xml-3.99_0.14-r43hc38eee6_2.conda
+    __osx: '>=10.9'
+    libaec: '>=1.1.2,<2.0a0'
+    libcurl: '>=8.4.0,<9.0a0'
+    libcxx: '>=16.0.6'
+    libgfortran: 5.*
+    libgfortran5: '>=13.2.0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    openssl: '>=3.2.0,<4.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/hdf5-1.14.3-nompi_h691f4bf_100.conda
   hash:
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   category: main
   optional: false
-- name: r-xtable
-  version: '1.8_4'
+- name: hdf5
+  version: 1.14.2
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-xtable-1.8_4-r43hc72bb7e_5.conda
+    libaec: '>=1.0.6,<2.0a0'
+    libcurl: '>=8.2.1,<9.0a0'
+    libcxx: '>=15.0.7'
+    libgfortran: 5.*
+    libgfortran5: '>=12.3.0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    openssl: '>=3.1.2,<4.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/hdf5-1.14.2-nompi_h3aba7b3_100.conda
   hash:
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   category: main
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-- name: r-yaml
-  version: 2.3.7
+- name: hdf5
+  version: 1.14.3
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    libgcc-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-yaml-2.3.7-r43h57805ef_1.conda
+    libaec: '>=1.1.2,<2.0a0'
+    libcurl: '>=8.4.0,<9.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    openssl: '>=3.2.0,<4.0a0'
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/hdf5-1.14.3-nompi_h73e8ff5_100.conda
   hash:
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-    sha256: a5a61ffedaaf69da7eee9e2f618f410c69b49fadb2fa98c5d216dc485de2f7b2
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   optional: false
-- name: rpy2
-  version: 3.5.11
+- name: holoviews
+  version: 1.18.3
   manager: conda
   platform: linux-64
   dependencies:
-    cffi: '>=1.10.0,!=1.13.0'
-    jinja2: ''
-    libgcc-ng: '>=12'
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-    python_abi: 3.12.*
-    pytz: ''
-    r-base: '>=4.3,<4.4.0a0'
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-    tzlocal: ''
-  url: https://conda.anaconda.org/conda-forge/linux-64/rpy2-3.5.11-py312r43hc7c0aa3_3.conda
+    bokeh: '>=3.1'
+    colorcet: ''
+    matplotlib-base: '>=3.0'
+    numpy: '>=1.0'
+    packaging: ''
+    pandas: '>=0.20.0'
+    panel: '>=1.0'
+    param: '>=1.12.0,<3.0'
+    python: '>=3.9'
+    pyviz_comms: '>=0.7.4'
+  url: https://conda.anaconda.org/conda-forge/noarch/holoviews-1.18.3-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: seaborn-base
-  version: 0.13.0
+- name: holoviews
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   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    matplotlib-base: '>=3.3,!=3.6.1'
-    numpy: '>=1.20,!=1.24.0'
-    pandas: '>=1.2'
-    python: '>=3.8'
-    scipy: '>=1.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.13.0-pyhd8ed1ab_0.conda
+    packaging: ''
+    colorcet: ''
+    python: '>=3.9'
+    matplotlib-base: '>=3.0'
+    numpy: '>=1.0'
+    pyviz_comms: '>=0.7.4'
+    pandas: '>=0.20.0'
+    param: '>=1.12.0,<3.0'
+    bokeh: '>=3.1'
+    panel: '>=1.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/holoviews-1.18.3-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: siphon
-  version: '0.9'
+- name: holoviews
+  version: 1.18.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-    netcdf4: ''
-    numpy: '>=1.8'
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-    protobuf: '>=3.0.0a3'
-    python: '>=3.6'
-    requests: '>=1.2'
-  url: https://conda.anaconda.org/conda-forge/noarch/siphon-0.9-pyhd8ed1ab_2.tar.bz2
+    packaging: ''
+    colorcet: ''
+    python: '>=3.9'
+    matplotlib-base: '>=3.0'
+    numpy: '>=1.0'
+    pyviz_comms: '>=0.7.4'
+    pandas: '>=0.20.0'
+    bokeh: '>=3.1'
+    panel: '>=1.0'
+    param: '>=1.12.0,<3.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/holoviews-1.18.0-pyhd8ed1ab_0.conda
   hash:
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   optional: false
-- name: statsmodels
-  version: 0.14.0
+- name: holoviews
+  version: 1.18.3
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    libgcc-ng: '>=12'
-    numpy: '>=1.26.0,<2.0a0'
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-    python_abi: 3.12.*
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-  url: https://conda.anaconda.org/conda-forge/linux-64/statsmodels-0.14.0-py312hc7c0aa3_2.conda
+    packaging: ''
+    colorcet: ''
+    python: '>=3.9'
+    matplotlib-base: '>=3.0'
+    numpy: '>=1.0'
+    pyviz_comms: '>=0.7.4'
+    pandas: '>=0.20.0'
+    param: '>=1.12.0,<3.0'
+    bokeh: '>=3.1'
+    panel: '>=1.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/holoviews-1.18.3-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: thredds_crawler
-  version: 1.5.4
+- name: hpack
+  version: 4.0.0
   manager: conda
   platform: linux-64
   dependencies:
-    lxml: ''
-    netcdf4: ''
     python: ''
-    pytz: ''
-    requests: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/thredds_crawler-1.5.4-py_1.tar.bz2
+  url: https://conda.anaconda.org/conda-forge/noarch/hpack-4.0.0-pyh9f0ad1d_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: windrose
-  version: 1.9.0
+- name: hpack
+  version: 4.0.0
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    matplotlib-base: '>=3'
-    numpy: '>=1.21'
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/windrose-1.9.0-pyhd8ed1ab_0.conda
+    python: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/hpack-4.0.0-pyh9f0ad1d_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: cc-plugin-glider
-  version: 2.0.3
+- name: hpack
+  version: 4.0.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    compliance-checker: '>=4.3.2'
     python: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/cc-plugin-glider-2.0.3-pyh9f0ad1d_0.tar.bz2
+  url: https://conda.anaconda.org/conda-forge/noarch/hpack-4.0.0-pyh9f0ad1d_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: cc-plugin-ncei
-  version: 2.0.2
+- name: hpack
+  version: 4.0.0
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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-    isodate: '>=0.5.4'
     python: ''
-    six: '>=1.10.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/cc-plugin-ncei-2.0.2-py_3.tar.bz2
+  url: https://conda.anaconda.org/conda-forge/noarch/hpack-4.0.0-pyh9f0ad1d_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: ctd
-  version: 1.4.4
+- name: httpcore
+  version: 1.0.3
   manager: conda
   platform: linux-64
   dependencies:
-    chardet: ''
-    gsw: '>=3.3.0'
-    matplotlib-base: ''
-    numpy: ''
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-    pandas-flavor: '>=0.1.2'
-    python: '>=3.6'
-    scipy: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/ctd-1.4.4-pyhd8ed1ab_0.conda
+    anyio: '>=3.0,<5.0'
+    certifi: ''
+    h11: '>=0.13,<0.15'
+    h2: '>=3,<5'
+    python: '>=3.8'
+    sniffio: 1.*
+  url: https://conda.anaconda.org/conda-forge/noarch/httpcore-1.0.3-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: geopandas
-  version: 0.14.0
+- name: httpcore
+  version: 1.0.3
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
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-    folium: ''
-    geopandas-base: 0.14.0
-    mapclassify: '>=2.4.0'
-    matplotlib-base: ''
-    python: '>=3.9'
-    rtree: ''
-    xyzservices: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/geopandas-0.14.0-pyhd8ed1ab_1.conda
+    certifi: ''
+    python: '>=3.8'
+    sniffio: 1.*
+    h2: '>=3,<5'
+    anyio: '>=3.0,<5.0'
+    h11: '>=0.13,<0.15'
+  url: https://conda.anaconda.org/conda-forge/noarch/httpcore-1.0.3-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: holoviews
-  version: 1.18.0
+- name: httpcore
+  version: 0.18.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    bokeh: '>=3.1'
-    colorcet: ''
-    matplotlib-base: '>=3.0'
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-    param: '>=1.12.0,<3.0'
-    python: '>=3.9'
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-  url: https://conda.anaconda.org/conda-forge/noarch/holoviews-1.18.0-pyhd8ed1ab_0.conda
+    certifi: ''
+    python: '>=3.8'
+    sniffio: 1.*
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-- name: ipykernel
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+  platform: win-64
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-- name: ipywidgets
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   manager: conda
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+  platform: osx-64
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-- name: nbconvert-core
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+  platform: osx-arm64
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-- name: pyoos
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   manager: conda
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+  platform: win-64
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-- name: r-askpass
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-- name: r-bit64
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   manager: conda
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+  platform: osx-64
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-- name: r-cachem
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   manager: conda
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+  platform: osx-arm64
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   manager: conda
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+  platform: win-64
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-- name: r-colourvalues
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   manager: conda
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+    python: '>=3.8'
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-- name: r-desc
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   manager: conda
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+  platform: osx-64
   dependencies:
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-- name: r-diffobj
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   manager: conda
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   dependencies:
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-- name: r-downloader
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-- name: r-ellipsis
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   dependencies:
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-- name: r-geometries
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   manager: conda
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+  platform: osx-64
   dependencies:
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+    python: '>=3.6'
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-- name: r-googlepolylines
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   manager: conda
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   dependencies:
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-- name: r-highr
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   manager: conda
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+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-highr-0.10-r43hc72bb7e_1.conda
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-- name: r-hoardr
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   manager: conda
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-- name: r-jsonify
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-- name: r-later
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-- name: r-nlme
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   manager: conda
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   manager: conda
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-- name: r-sp
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   manager: conda
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-- name: r-systemfonts
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   manager: conda
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-- name: r-terra
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   manager: conda
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-- name: r-timechange
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-- name: r-tinytex
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-- name: r-triebeard
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-- name: r-tzdb
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-- name: r-units
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-- name: r-v8
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   manager: conda
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+  platform: osx-64
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-  url: https://conda.anaconda.org/conda-forge/linux-64/r-v8-4.4.0-r43h432ea70_0.conda
+    importlib-metadata: '>=7.0.1,<7.0.2.0a0'
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-- name: r-wk
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-    libstdcxx-ng: '>=12'
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+    importlib-metadata: '>=6.8.0,<6.8.1.0a0'
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-- name: r-xml2
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   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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-    libstdcxx-ng: '>=12'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/r-xml2-1.3.5-r43h1ad5fc0_0.conda
+    importlib-metadata: '>=7.0.1,<7.0.2.0a0'
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-- name: r-zoo
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   manager: conda
   platform: linux-64
   dependencies:
-    libgcc-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/r-zoo-1.8_12-r43h57805ef_1.conda
+    python: '>=3.8'
+    zipp: '>=3.1.0'
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   category: main
   optional: false
-- name: seaborn
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+- name: importlib_resources
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   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
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-    statsmodels: '>=0.12'
-  url: https://conda.anaconda.org/conda-forge/noarch/seaborn-0.13.0-hd8ed1ab_0.conda
+    python: '>=3.8'
+    zipp: '>=3.1.0'
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   category: main
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-- name: geoplot
-  version: 0.5.1
+- name: importlib_resources
+  version: 6.1.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-    contextily: '>=1.0.0'
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-    mapclassify: '>=2.1'
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-  url: https://conda.anaconda.org/conda-forge/noarch/geoplot-0.5.1-pyhd8ed1ab_0.tar.bz2
+    python: '>=3.8'
+    zipp: '>=3.1.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/importlib_resources-6.1.0-pyhd8ed1ab_0.conda
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   category: main
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-- name: hvplot
-  version: 0.9.0
+- name: importlib_resources
+  version: 6.1.1
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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     python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/hvplot-0.9.0-pyhd8ed1ab_0.conda
+    zipp: '>=3.1.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/importlib_resources-6.1.1-pyhd8ed1ab_0.conda
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   category: main
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-- name: ipyleaflet
-  version: 0.17.4
+- name: iniconfig
+  version: 2.0.0
   manager: conda
   platform: linux-64
   dependencies:
-    branca: '>=0.5.0'
-    ipywidgets: '>=7.6.0,<9'
     python: '>=3.7'
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-    xyzservices: '>=2021.8.1'
-  url: https://conda.anaconda.org/conda-forge/noarch/ipyleaflet-0.17.4-pyhd8ed1ab_0.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/iniconfig-2.0.0-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: ipyparallel
-  version: 8.6.1
+- name: iniconfig
+  version: 2.0.0
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    decorator: ''
-    entrypoints: ''
-    ipykernel: '>=4.4'
-    ipython: '>=6'
-    jupyter_client: ''
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-    python: '>=3.6'
-    python-dateutil: '>=2.1'
-    pyzmq: '>=18'
-    tornado: '>=5.1'
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-    traitlets: '>=4.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/ipyparallel-8.6.1-pyhd8ed1ab_0.conda
+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/iniconfig-2.0.0-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: jupyter_console
-  version: 6.6.3
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+  version: 2.0.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    ipykernel: '>=6.14'
-    ipython: ''
-    jupyter_client: '>=7.0.0'
-    jupyter_core: '>=4.12,!=5.0.*'
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     python: '>=3.7'
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-    traitlets: '>=5.4'
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_console-6.6.3-pyhd8ed1ab_0.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/iniconfig-2.0.0-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: jupyter_server
-  version: 2.9.1
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+  version: 2.0.0
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    anyio: '>=3.1.0'
-    argon2-cffi: ''
-    jinja2: ''
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-    prometheus_client: ''
-    python: '>=3.8'
-    pyzmq: '>=24'
-    send2trash: '>=1.8.2'
-    terminado: '>=0.8.3'
-    tornado: '>=6.2.0'
-    traitlets: '>=5.6.0'
-    websocket-client: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_server-2.9.1-pyhd8ed1ab_0.conda
+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/iniconfig-2.0.0-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: nbconvert-pandoc
-  version: 7.9.2
+- name: intel-openmp
+  version: 2024.0.0
   manager: conda
-  platform: linux-64
-  dependencies:
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-    pandoc: ''
-    python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.9.2-pyhd8ed1ab_0.conda
+  platform: win-64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/win-64/intel-openmp-2024.0.0-h57928b3_49841.conda
   hash:
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   category: main
   optional: false
-- name: nbval
-  version: 0.10.0
+- name: ioos_qc
+  version: 2.1.0
   manager: conda
   platform: linux-64
   dependencies:
-    coverage: ''
-    ipykernel: ''
-    jupyter_client: ''
-    nbformat: ''
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-    python: '>=3.6'
-    six: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/nbval-0.10.0-pyhd8ed1ab_0.conda
+    bokeh: ''
+    geographiclib: ''
+    geojson: ''
+    h5netcdf: ''
+    jsonschema: ''
+    numba: ''
+    numpy: '>=1.14'
+    pandas: ''
+    pyparsing: ''
+    python: '>=3.7,<4.0'
+    ruamel.yaml: ''
+    scipy: ''
+    shapely: ''
+    xarray: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/ioos_qc-2.1.0-pyhd8ed1ab_0.tar.bz2
   hash:
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-    sha256: 791152066934153e33481172530c343244c20b0c91d6b2a3560cd77ff2f02c94
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   category: main
   optional: false
-- name: oceans
-  version: 1.1.3
+- name: ioos_qc
+  version: 2.1.0
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    cmcrameri: ''
-    contourpy: ''
-    ctd: ''
-    gsw: ''
-    matplotlib-base: '>=3.6.0'
-    netcdf4: ''
-    numpy: '>=1.20'
-    pandas: '>=1.0.1'
-    python: '>=3.8'
+    pandas: ''
     scipy: ''
-    seawater: ''
+    xarray: ''
     shapely: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/oceans-1.1.3-pyhd8ed1ab_0.conda
+    numba: ''
+    jsonschema: ''
+    ruamel.yaml: ''
+    bokeh: ''
+    pyparsing: ''
+    geojson: ''
+    h5netcdf: ''
+    geographiclib: ''
+    python: '>=3.7,<4.0'
+    numpy: '>=1.14'
+  url: https://conda.anaconda.org/conda-forge/noarch/ioos_qc-2.1.0-pyhd8ed1ab_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: qtconsole-base
-  version: 5.4.4
+- name: ioos_qc
+  version: 1.0.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    ipykernel: '>=4.1'
-    ipython_genutils: ''
-    jupyter_client: '>=4.1'
-    jupyter_core: ''
-    packaging: ''
-    pygments: ''
-    python: '>=3.7'
-    qtpy: '>=2.4.0'
-    traitlets: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/qtconsole-base-5.4.4-pyha770c72_0.conda
+    python: ''
+    xarray: ''
+    netcdf4: ''
+    ruamel.yaml: ''
+    geojson: ''
+    simplejson: ''
+    pygc: ''
+    numpy: '>=1.14'
+  url: https://conda.anaconda.org/conda-forge/noarch/ioos_qc-1.0.0-pyh9f0ad1d_0.tar.bz2
   hash:
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   optional: false
-- name: r-callr
-  version: 3.7.3
+- name: ioos_qc
+  version: 2.1.0
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-processx: '>=3.4.0'
-    r-r6: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-callr-3.7.3-r43hc72bb7e_1.conda
+    pandas: ''
+    scipy: ''
+    xarray: ''
+    shapely: ''
+    numba: ''
+    jsonschema: ''
+    ruamel.yaml: ''
+    bokeh: ''
+    pyparsing: ''
+    geojson: ''
+    h5netcdf: ''
+    geographiclib: ''
+    python: '>=3.7,<4.0'
+    numpy: '>=1.14'
+  url: https://conda.anaconda.org/conda-forge/noarch/ioos_qc-2.1.0-pyhd8ed1ab_0.tar.bz2
   hash:
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-    sha256: d5e65c7d149d7485d56cefc164166b251cbfd03a36faebec729f2770c32b2f58
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   optional: false
-- name: r-e1071
-  version: '1.7_13'
+- name: ipykernel
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   manager: conda
   platform: linux-64
   dependencies:
-    libgcc-ng: '>=12'
-    libstdcxx-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
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-    r-proxy: ''
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-e1071-1.7_13-r43ha503ecb_1.conda
+    __linux: ''
+    comm: '>=0.1.1'
+    debugpy: '>=1.6.5'
+    ipython: '>=7.23.1'
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+    jupyter_core: '>=4.12,!=5.0.*'
+    matplotlib-inline: '>=0.1'
+    nest-asyncio: ''
+    packaging: ''
+    psutil: ''
+    python: '>=3.8'
+    pyzmq: '>=24'
+    tornado: '>=6.1'
+    traitlets: '>=5.4.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/ipykernel-6.29.2-pyhd33586a_0.conda
   hash:
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-    sha256: 30c6432ed85ab48afe0c524d8356ec239c329b4fad31bd706c2101fc26f5ed1d
+    md5: c0e0eaceb52b50f1971295fe4546e8ed
+    sha256: 6cd66445c6a287623d02fe5fad0d67f8194ac582a7147ce092920fa20a8e3eec
   category: main
   optional: false
-- name: r-geosphere
-  version: '1.5_18'
+- name: ipykernel
+  version: 6.29.2
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    libgcc-ng: '>=12'
-    libstdcxx-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
-    r-rcpp: ''
-    r-sp: ''
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-geosphere-1.5_18-r43ha503ecb_1.conda
+    packaging: ''
+    psutil: ''
+    nest-asyncio: ''
+    __osx: ''
+    appnope: ''
+    python: '>=3.8'
+    tornado: '>=6.1'
+    jupyter_client: '>=6.1.12'
+    jupyter_core: '>=4.12,!=5.0.*'
+    ipython: '>=7.23.1'
+    matplotlib-inline: '>=0.1'
+    debugpy: '>=1.6.5'
+    comm: '>=0.1.1'
+    traitlets: '>=5.4.0'
+    pyzmq: '>=24'
+  url: https://conda.anaconda.org/conda-forge/noarch/ipykernel-6.29.2-pyh3cd1d5f_0.conda
   hash:
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-    sha256: dcfdd15c6a89a417c4a3fc22f99ae4f2ec70ec880ad148ca0b5c9054ab0e4c4e
+    md5: 70402d8d2b523e33c9b6090f5a9c74ff
+    sha256: bd454a69fe3dc80e4a11078aab370d87ee2bd863f386d619fb2bb051b4d6f82b
   category: main
   optional: false
-- name: r-gtable
-  version: 0.3.4
+- name: ipykernel
+  version: 6.26.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-cli: ''
-    r-glue: ''
-    r-lifecycle: ''
-    r-rlang: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-gtable-0.3.4-r43hc72bb7e_0.conda
+    packaging: ''
+    psutil: ''
+    nest-asyncio: ''
+    __osx: ''
+    appnope: ''
+    python: '>=3.8'
+    tornado: '>=6.1'
+    jupyter_client: '>=6.1.12'
+    ipython: '>=7.23.1'
+    matplotlib-inline: '>=0.1'
+    jupyter_core: '>=4.12,!=5.0.*'
+    debugpy: '>=1.6.5'
+    comm: '>=0.1.1'
+    pyzmq: '>=20'
+    traitlets: '>=5.4.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/ipykernel-6.26.0-pyh3cd1d5f_0.conda
   hash:
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-    sha256: ea93666d1db89f24ffa9988064200fe125f93edaaffc903eb9ef8118adf6e981
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+    sha256: be9927d47fe23cc4d2a09d252e37e1e56ffb137767d2c0577ed882ead16f75fa
   category: main
   optional: false
-- name: r-htmltools
-  version: 0.5.6.1
+- name: ipykernel
+  version: 6.29.2
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    libgcc-ng: '>=12'
-    libstdcxx-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
-    r-base64enc: ''
-    r-digest: ''
-    r-ellipsis: ''
-    r-fastmap: '>=1.1.0'
-    r-rlang: '>=0.4.10'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-htmltools-0.5.6.1-r43ha503ecb_0.conda
+    packaging: ''
+    psutil: ''
+    nest-asyncio: ''
+    __win: ''
+    python: '>=3.8'
+    tornado: '>=6.1'
+    jupyter_client: '>=6.1.12'
+    jupyter_core: '>=4.12,!=5.0.*'
+    ipython: '>=7.23.1'
+    matplotlib-inline: '>=0.1'
+    debugpy: '>=1.6.5'
+    comm: '>=0.1.1'
+    traitlets: '>=5.4.0'
+    pyzmq: '>=24'
+  url: https://conda.anaconda.org/conda-forge/noarch/ipykernel-6.29.2-pyha63f2e9_0.conda
   hash:
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-    sha256: 2f4c95acc67182194c0267d2b48a06e26c0f1f4b79b72e26e2d91a98afdeb9f9
+    md5: 65db5267b7fb095354b72735ddb4e08d
+    sha256: 735982c20a60d7b307b7de7a42cafd95ef37eb61e37db8abb627f2902ee9c32c
   category: main
   optional: false
-- name: r-igraph
-  version: 1.5.1
+- name: ipyleaflet
+  version: 0.18.2
   manager: conda
   platform: linux-64
   dependencies:
-    glpk: '>=5.0,<6.0a0'
-    gmp: '>=6.2.1,<7.0a0'
-    libblas: '>=3.9.0,<4.0a0'
-    libgcc-ng: '>=12'
-    libgfortran-ng: ''
-    libgfortran5: '>=12.3.0'
-    liblapack: '>=3.9.0,<4.0a0'
-    libstdcxx-ng: '>=12'
-    libxml2: '>=2.11.5,<2.12.0a0'
-    r-base: '>=4.3,<4.4.0a0'
-    r-cli: ''
-    r-cpp11: '>=0.2.0'
-    r-magrittr: ''
-    r-matrix: ''
-    r-pkgconfig: '>=2.0.0'
-    r-rlang: ''
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-igraph-1.5.1-r43hbd8eb98_0.conda
+    branca: '>=0.5.0'
+    ipywidgets: '>=7.6.0,<9'
+    python: '>=3.7'
+    traittypes: '>=0.2.1,<0.3.0'
+    xyzservices: '>=2021.8.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/ipyleaflet-0.18.2-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 2423b2d48ec146c784550f243c1d001c49e096046bf9978ddaca59915e6bf218
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+    sha256: 6151e64d06b138fd7e32b087d24eedbeb91c844c6cd3b01894d94d5c7d48db22
   category: main
   optional: false
-- name: r-jsonld
-  version: '2.2'
+- name: ipyleaflet
+  version: 0.18.2
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-curl: '>=2.7'
-    r-jsonlite: ''
-    r-v8: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-jsonld-2.2-r43hc72bb7e_2.conda
+    python: '>=3.7'
+    traittypes: '>=0.2.1,<0.3.0'
+    ipywidgets: '>=7.6.0,<9'
+    xyzservices: '>=2021.8.1'
+    branca: '>=0.5.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/ipyleaflet-0.18.2-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 0e6f705c8ddddc409bd83a24310ed7c150f7163961bbe272dda0000062056dd3
+    md5: fd0b34363a06a30ce7b1caa62de657e1
+    sha256: 6151e64d06b138fd7e32b087d24eedbeb91c844c6cd3b01894d94d5c7d48db22
   category: main
   optional: false
-- name: r-knitr
-  version: '1.44'
+- name: ipyleaflet
+  version: 0.17.4
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-evaluate: '>=0.15'
-    r-highr: ''
-    r-xfun: '>=0.34'
-    r-yaml: '>=2.1.19'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-knitr-1.44-r43hc72bb7e_0.conda
+    python: '>=3.7'
+    traittypes: '>=0.2.1,<0.3.0'
+    ipywidgets: '>=7.6.0,<9'
+    xyzservices: '>=2021.8.1'
+    branca: '>=0.5.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/ipyleaflet-0.17.4-pyhd8ed1ab_0.conda
   hash:
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-    sha256: fe24a1cfcd5b0f9292910aa3f234d48868e103fe9ed9e586d311ed6d5d287ff8
+    md5: f85309d8aa0c749e1f4ec8121e70b000
+    sha256: 958570f95951111e8aa4508d7e48c3b6868cac9ab80af9b483a8baf9852fe97b
   category: main
   optional: false
-- name: r-lubridate
-  version: 1.9.3
+- name: ipyleaflet
+  version: 0.18.2
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    libgcc-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
-    r-generics: ''
-    r-timechange: '>=0.1.1'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-lubridate-1.9.3-r43h57805ef_0.conda
+    python: '>=3.7'
+    traittypes: '>=0.2.1,<0.3.0'
+    ipywidgets: '>=7.6.0,<9'
+    xyzservices: '>=2021.8.1'
+    branca: '>=0.5.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/ipyleaflet-0.18.2-pyhd8ed1ab_0.conda
   hash:
-    md5: 48f220862d7b0ac7d1397f8c6601fb70
-    sha256: 549e7c7b034cf6e66323cd1a02af57bbade1478bcaf5744e03d56b2ddad9e9a7
+    md5: fd0b34363a06a30ce7b1caa62de657e1
+    sha256: 6151e64d06b138fd7e32b087d24eedbeb91c844c6cd3b01894d94d5c7d48db22
   category: main
   optional: false
-- name: r-memoise
-  version: 2.0.1
+- name: ipyparallel
+  version: 8.6.1
   manager: conda
   platform: linux-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-cachem: ''
-    r-rlang: '>=0.4.10'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-memoise-2.0.1-r43hc72bb7e_2.conda
+    decorator: ''
+    entrypoints: ''
+    ipykernel: '>=4.4'
+    ipython: '>=6'
+    jupyter_client: ''
+    psutil: ''
+    python: '>=3.6'
+    python-dateutil: '>=2.1'
+    pyzmq: '>=18'
+    tornado: '>=5.1'
+    tqdm: ''
+    traitlets: '>=4.3'
+  url: https://conda.anaconda.org/conda-forge/noarch/ipyparallel-8.6.1-pyhd8ed1ab_0.conda
   hash:
-    md5: 6520452e207d8f9bab9f21492f88c48b
-    sha256: a563bd856ffac75d634eed2d28a9ad5b13c55379a2afd054390d76b2910ef03c
+    md5: 42eba197eb58b18703767c60103f0712
+    sha256: ba71fa050152858c5d1a9be8a7be473141604f0077019b6fbd322f0bd6dd9135
   category: main
   optional: false
-- name: r-mgcv
-  version: '1.9_0'
+- name: ipyparallel
+  version: 8.6.1
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    _openmp_mutex: '>=4.5'
-    libblas: '>=3.9.0,<4.0a0'
-    libgcc-ng: '>=12'
-    liblapack: '>=3.9.0,<4.0a0'
-    r-base: '>=4.3,<4.4.0a0'
-    r-matrix: ''
-    r-nlme: '>=3.1_64'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-mgcv-1.9_0-r43h316c678_0.conda
+    tqdm: ''
+    psutil: ''
+    decorator: ''
+    jupyter_client: ''
+    entrypoints: ''
+    python: '>=3.6'
+    tornado: '>=5.1'
+    python-dateutil: '>=2.1'
+    ipykernel: '>=4.4'
+    ipython: '>=6'
+    pyzmq: '>=18'
+    traitlets: '>=4.3'
+  url: https://conda.anaconda.org/conda-forge/noarch/ipyparallel-8.6.1-pyhd8ed1ab_0.conda
   hash:
-    md5: 457861cc31161e3295ea4a33a341e59c
-    sha256: 29a315d4f46a74e1c4f4cf1b86918e2af7c576cd10d8ed3ec7bdf00877fb33af
+    md5: 42eba197eb58b18703767c60103f0712
+    sha256: ba71fa050152858c5d1a9be8a7be473141604f0077019b6fbd322f0bd6dd9135
   category: main
   optional: false
-- name: r-openssl
-  version: 2.1.1
+- name: ipyparallel
+  version: 8.6.1
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    libgcc-ng: '>=12'
-    openssl: '>=3.1.3,<4.0a0'
-    r-askpass: ''
-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-openssl-2.1.1-r43hb353fa6_0.conda
+    tqdm: ''
+    psutil: ''
+    decorator: ''
+    jupyter_client: ''
+    entrypoints: ''
+    python: '>=3.6'
+    tornado: '>=5.1'
+    python-dateutil: '>=2.1'
+    ipykernel: '>=4.4'
+    ipython: '>=6'
+    pyzmq: '>=18'
+    traitlets: '>=4.3'
+  url: https://conda.anaconda.org/conda-forge/noarch/ipyparallel-8.6.1-pyhd8ed1ab_0.conda
   hash:
-    md5: d034eaa40df595f8e77dfe6d716b36b4
-    sha256: 5d3c25bd9b2d121f2dd1aebdfaf1485794665c1c725e7e4535af647b8c85b764
+    md5: 42eba197eb58b18703767c60103f0712
+    sha256: ba71fa050152858c5d1a9be8a7be473141604f0077019b6fbd322f0bd6dd9135
   category: main
   optional: false
-- name: r-promises
-  version: 1.2.1
+- name: ipyparallel
+  version: 8.6.1
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    libgcc-ng: '>=12'
-    libstdcxx-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
-    r-fastmap: '>=1.1.0'
-    r-later: ''
-    r-magrittr: '>=1.5'
-    r-r6: ''
-    r-rcpp: ''
-    r-rlang: ''
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-promises-1.2.1-r43ha503ecb_0.conda
+    tqdm: ''
+    psutil: ''
+    decorator: ''
+    jupyter_client: ''
+    entrypoints: ''
+    python: '>=3.6'
+    tornado: '>=5.1'
+    python-dateutil: '>=2.1'
+    ipykernel: '>=4.4'
+    ipython: '>=6'
+    pyzmq: '>=18'
+    traitlets: '>=4.3'
+  url: https://conda.anaconda.org/conda-forge/noarch/ipyparallel-8.6.1-pyhd8ed1ab_0.conda
   hash:
-    md5: 2f0bf831cac8b04d72b7e1d27c3a7da7
-    sha256: 4149d9d297654be1aa47c757b1355ac901fd454d6770e0dc2e3b06c9889f6a69
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+    sha256: ba71fa050152858c5d1a9be8a7be473141604f0077019b6fbd322f0bd6dd9135
   category: main
   optional: false
-- name: r-raster
-  version: '3.6_26'
+- name: ipython
+  version: 8.21.0
   manager: conda
   platform: linux-64
   dependencies:
-    libgcc-ng: '>=12'
-    libstdcxx-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
-    r-rcpp: ''
-    r-sp: '>=1.4.5'
-    r-terra: '>=1.6-41'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-raster-3.6_26-r43ha503ecb_0.conda
+    __unix: ''
+    decorator: ''
+    exceptiongroup: ''
+    jedi: '>=0.16'
+    matplotlib-inline: ''
+    pexpect: '>4.3'
+    pickleshare: ''
+    prompt-toolkit: '>=3.0.41,<3.1.0'
+    pygments: '>=2.4.0'
+    python: '>=3.10'
+    stack_data: ''
+    traitlets: '>=5'
+    typing_extensions: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/ipython-8.21.0-pyh707e725_0.conda
   hash:
-    md5: ca448851bd1448a6ccb3f6881e1afde3
-    sha256: eeaee84491d55196bd3e0325b1dc2e214a81a0c52712a14b47cbf7fb335f0608
+    md5: 371344fdbdf9c70cfe9adb512a8cbca6
+    sha256: 521291dd15bf09fbb3ecea1c27536742d8e434c2e539b06776e734ee729bdead
   category: main
   optional: false
-- name: r-rgdal
-  version: '1.6_7'
+- name: ipython
+  version: 8.21.0
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    __glibc: '>=2.17,<3.0.a0'
-    libgcc-ng: '>=12'
-    libgdal: '>=3.7.2,<3.8.0a0'
-    libstdcxx-ng: '>=12'
-    proj: '>=9.3.0,<9.3.1.0a0'
-    r-base: '>=4.3,<4.4.0a0'
-    r-sp: '>=1.1_0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-rgdal-1.6_7-r43haac4566_0.conda
+    typing_extensions: ''
+    __unix: ''
+    decorator: ''
+    exceptiongroup: ''
+    stack_data: ''
+    matplotlib-inline: ''
+    pickleshare: ''
+    python: '>=3.10'
+    pygments: '>=2.4.0'
+    traitlets: '>=5'
+    jedi: '>=0.16'
+    pexpect: '>4.3'
+    prompt-toolkit: '>=3.0.41,<3.1.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/ipython-8.21.0-pyh707e725_0.conda
   hash:
-    md5: c3534af127f798b242ea5cf28a94d6c8
-    sha256: f152ae1aa23b252a8de4eb1e6e2057e17f18740a0f5fe0cae645bc23b516c930
+    md5: 371344fdbdf9c70cfe9adb512a8cbca6
+    sha256: 521291dd15bf09fbb3ecea1c27536742d8e434c2e539b06776e734ee729bdead
   category: main
   optional: false
-- name: r-rgeos
-  version: '0.6_4'
+- name: ipython
+  version: 8.16.1
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    geos: '>=3.12.0,<3.12.1.0a0'
-    libgcc-ng: '>=12'
-    libstdcxx-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
-    r-sp: '>=1.1_0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-rgeos-0.6_4-r43hb9af077_0.conda
+    typing_extensions: ''
+    decorator: ''
+    exceptiongroup: ''
+    __osx: ''
+    stack_data: ''
+    matplotlib-inline: ''
+    backcall: ''
+    appnope: ''
+    pickleshare: ''
+    python: '>=3.9'
+    pygments: '>=2.4.0'
+    traitlets: '>=5'
+    jedi: '>=0.16'
+    pexpect: '>4.3'
+    prompt_toolkit: '>=3.0.30,<3.1.0,!=3.0.37'
+  url: https://conda.anaconda.org/conda-forge/noarch/ipython-8.16.1-pyh31c8845_0.conda
   hash:
-    md5: 748d15d814dcfa91b5b6bbda97639f75
-    sha256: 652cf542ae1eccafc3939aaeed615376b194db466f745cf0c1ea1b6027d54749
+    md5: 531bac092414642fdead7a511357485a
+    sha256: 77cfbc15ee2ad8976009a6880bb1f7c716db44e23594fba7c9c382135e02eb03
   category: main
   optional: false
-- name: r-s2
-  version: 1.1.4
+- name: ipython
+  version: 8.21.0
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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-    r-base: '>=4.3,<4.4.0a0'
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-    r-wk: ''
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-s2-1.1.4-r43h5eac2b3_1.conda
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+    colorama: ''
+    decorator: ''
+    __win: ''
+    exceptiongroup: ''
+    stack_data: ''
+    matplotlib-inline: ''
+    pickleshare: ''
+    python: '>=3.10'
+    pygments: '>=2.4.0'
+    traitlets: '>=5'
+    jedi: '>=0.16'
+    prompt-toolkit: '>=3.0.41,<3.1.0'
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-- name: r-scales
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   platform: linux-64
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-scales-1.2.1-r43hc72bb7e_2.conda
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+  url: https://conda.anaconda.org/conda-forge/noarch/ipython_genutils-0.2.0-py_1.tar.bz2
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-- name: r-sfheaders
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   manager: conda
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+  platform: osx-64
   dependencies:
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-    libstdcxx-ng: '>=12'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/r-sfheaders-0.4.3-r43ha503ecb_0.conda
+    python: ''
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-- name: r-svglite
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   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-    libpng: '>=1.6.39,<1.7.0a0'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/r-svglite-2.1.2-r43h329214f_0.conda
+    python: ''
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-- name: r-urltools
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+- name: ipython_genutils
+  version: 0.2.0
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    libgcc-ng: '>=12'
-    libstdcxx-ng: '>=12'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/r-urltools-1.7.3-r43ha503ecb_4.conda
+    python: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/ipython_genutils-0.2.0-py_1.tar.bz2
   hash:
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   category: main
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-- name: r-vctrs
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   manager: conda
   platform: linux-64
   dependencies:
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-    libstdcxx-ng: '>=12'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/r-vctrs-0.6.4-r43ha503ecb_0.conda
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+    ipython: '>=6.1.0'
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+    python: '>=3.7'
+    traitlets: '>=4.3.1'
+    widgetsnbextension: '>=4.0.10,<4.1.0'
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-- name: r-xts
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   manager: conda
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+  platform: osx-64
   dependencies:
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-    r-base: '>=4.3,<4.4.0a0'
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-  url: https://conda.anaconda.org/conda-forge/linux-64/r-xts-0.13.1-r43h57805ef_1.conda
+    python: '>=3.7'
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+    widgetsnbextension: '>=4.0.10,<4.1.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/ipywidgets-8.1.2-pyhd8ed1ab_0.conda
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-- name: sensorml2iso
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-    jinja2: ''
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-    python: ''
-    shapely: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/sensorml2iso-1.0.5-py_0.tar.bz2
+    python: '>=3.7'
+    traitlets: '>=4.3.1'
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+    comm: '>=0.1.3'
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+    widgetsnbextension: '>=4.0.9,<4.1.0'
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-- name: jupyter-lsp
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   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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   category: main
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-- name: jupyter-server-mathjax
-  version: 0.2.6
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   manager: conda
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-server-mathjax-0.2.6-pyh5bfe37b_1.conda
+    libcxx: '>=14.0.6'
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   optional: false
-- name: jupyterlab_server
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   manager: conda
   platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/jupyterlab_server-2.25.0-pyhd8ed1ab_0.conda
+    python: '>=3.6'
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-- name: metakernel
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   manager: conda
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+  platform: osx-64
   dependencies:
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+    six: ''
+    python: '>=3.6'
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-- name: nbconvert
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+- name: isodate
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   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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   optional: false
-- name: notebook-shim
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+  platform: win-64
+  dependencies:
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+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/isodate-0.6.1-pyhd8ed1ab_0.tar.bz2
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   platform: linux-64
   dependencies:
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     python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/notebook-shim-0.2.3-pyhd8ed1ab_0.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/isoduration-20.11.0-pyhd8ed1ab_0.tar.bz2
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   optional: false
-- name: r-classint
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   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
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-    libgfortran-ng: ''
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-  url: https://conda.anaconda.org/conda-forge/linux-64/r-classint-0.4_10-r43h61816a4_0.conda
+    python: '>=3.7'
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   optional: false
-- name: r-crosstalk
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   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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+    python: '>=3.7'
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-- name: r-crul
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   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-crul-1.4.0-r43h785f33e_1.conda
+    python: '>=3.7'
+    arrow: '>=0.15.0'
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-- name: r-emld
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   manager: conda
   platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-emld-0.5.1-r43hc72bb7e_2.conda
+    parso: '>=0.8.3,<0.9.0'
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/jedi-0.19.1-pyhd8ed1ab_0.conda
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-- name: r-fontawesome
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   manager: conda
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+  platform: osx-64
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+    parso: '>=0.8.3,<0.9.0'
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-- name: r-geojsonsf
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   manager: conda
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+  platform: osx-arm64
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+    parso: '>=0.8.3,<0.9.0'
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-- name: r-gridextra
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   manager: conda
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+  platform: win-64
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+    parso: '>=0.8.3,<0.9.0'
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-- name: r-hms
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-- name: r-httpuv
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+  platform: osx-64
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+    python: '>=3.7'
+    markupsafe: '>=2.0'
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-- name: r-httr
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+  platform: osx-arm64
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-- name: r-influencer
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+  platform: win-64
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-- name: r-jquerylib
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   manager: conda
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   dependencies:
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-- name: r-leaflet.providers
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   manager: conda
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+  platform: osx-64
   dependencies:
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-- name: r-pillar
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   manager: conda
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+    setuptools: ''
+    python: '>=3.7'
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-- name: r-pkgbuild
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   manager: conda
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+  platform: win-64
   dependencies:
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-- name: r-purrr
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-- name: r-sass
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   manager: conda
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+  platform: osx-64
   dependencies:
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+    oniguruma: '>=6.9.9,<6.10.0a0'
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-- name: r-satellite
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   manager: conda
   platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/linux-64/r-satellite-1.0.4-r43ha503ecb_2.conda
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-- name: r-stringr
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   manager: conda
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-- name: r-tidyselect
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+  url: https://conda.anaconda.org/conda-forge/osx-arm64/json-c-0.17-h40ed0f5_0.conda
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+    python: '>=3.7,<4.0'
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-- name: r-webshot
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   dependencies:
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+    python: '>=3.7,<4.0'
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-- name: jupyterlab
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   manager: conda
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+  platform: osx-arm64
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+    python: '>=3.7,<4.0'
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   optional: false
-- name: nbclassic
-  version: 1.0.0
+- name: json5
+  version: 0.9.14
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    argon2-cffi: ''
-    ipykernel: ''
-    ipython_genutils: ''
-    jinja2: ''
-    jupyter_client: '>=6.1.1'
-    jupyter_core: '>=4.6.1'
-    jupyter_server: '>=1.8'
-    nbconvert: '>=5'
-    nbformat: ''
-    nest-asyncio: '>=1.5'
-    notebook-shim: '>=0.2.3'
-    prometheus_client: ''
-    python: '>=3.7'
-    pyzmq: '>=17'
-    send2trash: '>=1.8.0'
-    terminado: '>=0.8.3'
-    tornado: '>=6.1'
-    traitlets: '>=4.2.1'
-  url: https://conda.anaconda.org/conda-forge/noarch/nbclassic-1.0.0-pyhb4ecaf3_1.conda
+    python: '>=3.7,<4.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/json5-0.9.14-pyhd8ed1ab_0.conda
   hash:
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-    sha256: fc2b2e606ccbd0aaa2cdecdd33fc39e2c4bd7b5b96a64b89b3e6ad9ce20eec2f
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+    sha256: 41514104208c092959bef0713cbd795e72c535f2f939b7903d8c97809f2adaa7
   category: main
   optional: false
-- name: nbdime
-  version: 3.2.1
+- name: jsonpointer
+  version: '2.4'
   manager: conda
   platform: linux-64
   dependencies:
-    colorama: ''
-    gitpython: '!=2.1.4,!=2.1.5,!=2.1.6'
-    jinja2: '>=2.9'
-    jupyter-server-mathjax: '>=0.2.2'
-    jupyter_server: ''
-    nbformat: ''
-    pygments: ''
-    python: '>=3.6'
-    requests: ''
-    tornado: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/nbdime-3.2.1-pyhd8ed1ab_0.conda
+    python: '>=3.12.0rc3,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/linux-64/jsonpointer-2.4-py312h7900ff3_3.conda
   hash:
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-    sha256: ffd7d26af9174e1f4580f2aa2efaee6c7e8e26fa37d9804396f0852aaa49110c
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+    sha256: c211a79cff8aa001a6e14e923c37278231dca7f0970d8db155c4b9e48ac87a5a
   category: main
   optional: false
-- name: octave_kernel
-  version: 0.35.1
+- name: jsonpointer
+  version: '2.4'
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    ipykernel: ''
-    jupyter_client: '>=4.3.0'
-    metakernel: '>=0.24.0'
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/octave_kernel-0.35.1-pyhd8ed1ab_0.conda
+    python: '>=3.12.0rc3,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/osx-64/jsonpointer-2.4-py312hb401068_3.conda
   hash:
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-    sha256: 016e83d410fda3fb94fa0f6d7e693ae6bbc1a52906dfd626256729d426295865
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+    sha256: 883f6d635e58f49359f393e853e4e0043731fb0ce671283a2024db02a1ebc8f6
   category: main
   optional: false
-- name: r-bslib
-  version: 0.5.1
+- name: jsonpointer
+  version: '2.4'
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-base64enc: ''
-    r-cachem: ''
-    r-htmltools: '>=0.5.4'
-    r-jquerylib: '>=0.1.3'
-    r-jsonlite: ''
-    r-memoise: '>=2.0.1'
-    r-mime: ''
-    r-rlang: ''
-    r-sass: '>=0.4.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-bslib-0.5.1-r43hc72bb7e_0.conda
+    python: '>=3.12.0rc3,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/jsonpointer-2.4-py312h81bd7bf_3.conda
   hash:
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-    sha256: fd88ef751adbe4bce1b0e56168c2d5cf18c7bbec1a59cb8e0deb166062dad267
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+    sha256: 6cb2d17da9083e05f5ead7902a5cd6ec9567cd3da972c65c03f090515c9fa176
   category: main
   optional: false
-- name: r-httpcache
-  version: 1.2.0
+- name: jsonpointer
+  version: '2.4'
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-digest: ''
-    r-httr: '>=1.0.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-httpcache-1.2.0-r43hc72bb7e_2.conda
+    python: '>=3.12.0rc3,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/win-64/jsonpointer-2.4-py312h2e8e312_3.conda
   hash:
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-    sha256: f68408ae0818ed3d44df59b2b1e6c80a9067c630c508e3829c5ee062416f706a
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+    sha256: 98d86d5ccb3a95da2cd96b394c157aa6fef0d4908b8878c3e2b5931f6bc5fd57
   category: main
   optional: false
-- name: r-pkgload
-  version: 1.3.3
+- name: jsonschema
+  version: 4.21.1
   manager: conda
   platform: linux-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-cli: '>=3.3.0'
-    r-crayon: ''
-    r-desc: ''
-    r-fs: ''
-    r-glue: ''
-    r-pkgbuild: ''
-    r-rlang: '>=1.1.1'
-    r-rprojroot: ''
-    r-withr: '>=2.4.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-pkgload-1.3.3-r43hc72bb7e_0.conda
+    attrs: '>=22.2.0'
+    importlib_resources: '>=1.4.0'
+    jsonschema-specifications: '>=2023.03.6'
+    pkgutil-resolve-name: '>=1.3.10'
+    python: '>=3.8'
+    referencing: '>=0.28.4'
+    rpds-py: '>=0.7.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-4.21.1-pyhd8ed1ab_0.conda
   hash:
-    md5: 5a210114c5aa973b48328947fca2441c
-    sha256: 3f708853da1889fbb5c4c05137ef0575be53e0b39f46340cf37f1563d2e3feaf
+    md5: 8a3a3d01629da20befa340919e3dd2c4
+    sha256: c5c1b4e08e91fdd697289015be1a176409b4e63942899a43b276f1f250be8129
   category: main
   optional: false
-- name: r-progress
-  version: 1.2.2
+- name: jsonschema
+  version: 4.21.1
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-crayon: ''
-    r-hms: ''
-    r-prettyunits: ''
-    r-r6: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-progress-1.2.2-r43hc72bb7e_4.conda
+    python: '>=3.8'
+    attrs: '>=22.2.0'
+    importlib_resources: '>=1.4.0'
+    pkgutil-resolve-name: '>=1.3.10'
+    jsonschema-specifications: '>=2023.03.6'
+    referencing: '>=0.28.4'
+    rpds-py: '>=0.7.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-4.21.1-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 53c72eea6207dc3c002f1602af26a92def0b6c601742af606c983df4ec52d513
+    md5: 8a3a3d01629da20befa340919e3dd2c4
+    sha256: c5c1b4e08e91fdd697289015be1a176409b4e63942899a43b276f1f250be8129
   category: main
   optional: false
-- name: r-repr
-  version: 1.1.6
+- name: jsonschema
+  version: 4.19.1
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-base64enc: ''
-    r-htmltools: ''
-    r-jsonlite: ''
-    r-pillar: '>=1.4.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-repr-1.1.6-r43h785f33e_1.conda
+    python: '>=3.8'
+    attrs: '>=22.2.0'
+    importlib_resources: '>=1.4.0'
+    pkgutil-resolve-name: '>=1.3.10'
+    jsonschema-specifications: '>=2023.03.6'
+    referencing: '>=0.28.4'
+    rpds-py: '>=0.7.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-4.19.1-pyhd8ed1ab_0.conda
   hash:
-    md5: 6783aca202b4458c27666b4144a0816a
-    sha256: 36d8c6d25a27b36a98a52718d2cb199410ad03709e5544de35b4eb65a24d47ab
+    md5: 78aff5d2af74e6537c1ca73017f01f4f
+    sha256: b4e50e1d53b984a467e79b7ba69cc408d14e3a2002cad4eaf7798e20268cff2d
   category: main
   optional: false
-- name: r-reshape2
-  version: 1.4.4
+- name: jsonschema
+  version: 4.21.1
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    libgcc-ng: '>=12'
-    libstdcxx-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
-    r-plyr: '>=1.8.1'
-    r-rcpp: ''
-    r-stringr: ''
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-reshape2-1.4.4-r43ha503ecb_3.conda
+    python: '>=3.8'
+    attrs: '>=22.2.0'
+    importlib_resources: '>=1.4.0'
+    pkgutil-resolve-name: '>=1.3.10'
+    jsonschema-specifications: '>=2023.03.6'
+    referencing: '>=0.28.4'
+    rpds-py: '>=0.7.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-4.21.1-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 618e090cad662d610d9d0e8b351f5d6584413a37251f85582d5962c9a01607c4
+    md5: 8a3a3d01629da20befa340919e3dd2c4
+    sha256: c5c1b4e08e91fdd697289015be1a176409b4e63942899a43b276f1f250be8129
   category: main
   optional: false
-- name: r-servr
-  version: '0.27'
+- name: jsonschema-specifications
+  version: 2023.12.1
   manager: conda
   platform: linux-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-httpuv: '>=1.5.2'
-    r-jsonlite: ''
-    r-mime: '>=0.2'
-    r-xfun: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-servr-0.27-r43hc72bb7e_1.conda
+    importlib_resources: '>=1.4.0'
+    python: '>=3.8'
+    referencing: '>=0.31.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-specifications-2023.12.1-pyhd8ed1ab_0.conda
   hash:
-    md5: eecb9dd79c702267af7dc8df4756ec67
-    sha256: a5361e3440fee84782739a6a8b4b638575e746f859daf8af9185d5ad967b0a70
+    md5: a0e4efb5f35786a05af4809a2fb1f855
+    sha256: a9630556ddc3121c0be32f4cbf792dd9102bd380d5cd81d57759d172cf0c2da2
   category: main
   optional: false
-- name: r-sf
-  version: '1.0_14'
+- name: jsonschema-specifications
+  version: 2023.12.1
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    __glibc: '>=2.17,<3.0.a0'
-    geos: '>=3.12.0,<3.12.1.0a0'
-    libgcc-ng: '>=12'
-    libgdal: '>=3.7.2,<3.8.0a0'
-    libstdcxx-ng: '>=12'
-    proj: '>=9.3.0,<9.3.1.0a0'
-    r-base: '>=4.3,<4.4.0a0'
-    r-classint: '>=0.4_1'
-    r-dbi: '>=0.8'
-    r-magrittr: ''
-    r-rcpp: '>=0.12.18'
-    r-s2: '>=1.1.0'
-    r-units: '>=0.7_0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-sf-1.0_14-r43h85a8d9e_1.conda
+    python: '>=3.8'
+    importlib_resources: '>=1.4.0'
+    referencing: '>=0.31.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-specifications-2023.12.1-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 07c1a6be271373781ace9e6ee7aab82cc571ce1e8cd06269e38910de42d7e3ab
+    md5: a0e4efb5f35786a05af4809a2fb1f855
+    sha256: a9630556ddc3121c0be32f4cbf792dd9102bd380d5cd81d57759d172cf0c2da2
   category: main
   optional: false
-- name: r-spatialwidget
-  version: 0.2.3
+- name: jsonschema-specifications
+  version: 2023.7.1
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    libgcc-ng: '>=12'
-    libstdcxx-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
-    r-colourvalues: '>=0.3.4'
-    r-geojsonsf: '>=1.3.3'
-    r-geometries: ''
-    r-jsonify: '>=1.1.1'
-    r-rapidjsonr: ''
-    r-rcpp: ''
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-spatialwidget-0.2.3-r43ha503ecb_2.conda
+    python: '>=3.8'
+    importlib_resources: '>=1.4.0'
+    referencing: '>=0.25.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-specifications-2023.7.1-pyhd8ed1ab_0.conda
   hash:
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-    sha256: f78f931240494d34f0e4555b2ee79f3598e8551ff70fae07ae55368b37dad354
+    md5: 7c27ea1bdbe520bb830dcadd59f55cbf
+    sha256: 7b0061e106674f27cc718f79a095e90a5667a3635ec6626dd23b3be0fd2bfbdc
   category: main
   optional: false
-- name: r-tibble
-  version: 3.2.1
+- name: jsonschema-specifications
+  version: 2023.12.1
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    libgcc-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
-    r-fansi: '>=0.4.0'
-    r-lifecycle: '>=1.0.0'
-    r-magrittr: ''
-    r-pillar: '>=1.8.1'
-    r-pkgconfig: ''
-    r-rlang: '>=1.0.2'
-    r-vctrs: '>=0.4.2'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-tibble-3.2.1-r43h57805ef_2.conda
+    python: '>=3.8'
+    importlib_resources: '>=1.4.0'
+    referencing: '>=0.31.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-specifications-2023.12.1-pyhd8ed1ab_0.conda
   hash:
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-    sha256: ecb1c7a1fd41f5a8fc4d89bdaef49b986507dd2186f4c94c574ef192a9fdee17
+    md5: a0e4efb5f35786a05af4809a2fb1f855
+    sha256: a9630556ddc3121c0be32f4cbf792dd9102bd380d5cd81d57759d172cf0c2da2
   category: main
   optional: false
-- name: notebook
-  version: 7.0.6
+- name: jsonschema-with-format-nongpl
+  version: 4.21.1
   manager: conda
   platform: linux-64
   dependencies:
-    jupyter_server: '>=2.4.0,<3'
-    jupyterlab: '>=4.0.7,<5'
-    jupyterlab_server: '>=2.22.1,<3'
-    notebook-shim: '>=0.2,<0.3'
-    python: '>=3.8'
-    tornado: '>=6.2.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/notebook-7.0.6-pyhd8ed1ab_0.conda
+    fqdn: ''
+    idna: ''
+    isoduration: ''
+    jsonpointer: '>1.13'
+    jsonschema: '>=4.21.1,<4.21.2.0a0'
+    python: ''
+    rfc3339-validator: ''
+    rfc3986-validator: '>0.1.0'
+    uri-template: ''
+    webcolors: '>=1.11'
+  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-with-format-nongpl-4.21.1-pyhd8ed1ab_0.conda
   hash:
-    md5: d60881c78a54cbf8042ae719f1f77a50
-    sha256: 5259ad2fb47300407dafa6ea5e78085a2c8de8dcdbfbaa58592bf2677d7187a9
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+    sha256: 6e458c325c097956ac4605ef386f0d67bad5223041cedd66819892988b72f83a
   category: main
   optional: false
-- name: oct2py
-  version: 5.6.0
+- name: jsonschema-with-format-nongpl
+  version: 4.21.1
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    ipython: ''
-    numpy: ''
-    octave_kernel: '>=0.34.0'
-    python: '>=3.6'
-    scipy: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/oct2py-5.6.0-pyha21a80b_0.conda
+    python: ''
+    idna: ''
+    rfc3339-validator: ''
+    uri-template: ''
+    fqdn: ''
+    isoduration: ''
+    jsonpointer: '>1.13'
+    webcolors: '>=1.11'
+    rfc3986-validator: '>0.1.0'
+    jsonschema: '>=4.21.1,<4.21.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-with-format-nongpl-4.21.1-pyhd8ed1ab_0.conda
   hash:
-    md5: 682521ad6e1a2eb81b03a2ffa35a8cd5
-    sha256: 3db5174adf49ebb88829634bd0a0b37fe441e6e73c3369f65497cac35fd5d04d
+    md5: 26bce4b5405738c09304d4f4796b2c2a
+    sha256: 6e458c325c097956ac4605ef386f0d67bad5223041cedd66819892988b72f83a
   category: main
   optional: false
-- name: r-dplyr
-  version: 1.1.3
+- name: jsonschema-with-format-nongpl
+  version: 4.19.1
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    libgcc-ng: '>=12'
-    libstdcxx-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
-    r-ellipsis: ''
-    r-generics: ''
-    r-glue: '>=1.3.2'
-    r-lifecycle: '>=1.0.0'
-    r-magrittr: '>=1.5'
-    r-pillar: '>=1.5.1'
-    r-r6: ''
-    r-rlang: '>=0.4.10'
-    r-tibble: '>=2.1.3'
-    r-tidyselect: '>=1.1.0'
-    r-vctrs: '>=0.3.5'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-dplyr-1.1.3-r43ha503ecb_0.conda
+    python: ''
+    idna: ''
+    rfc3339-validator: ''
+    uri-template: ''
+    fqdn: ''
+    isoduration: ''
+    jsonpointer: '>1.13'
+    webcolors: '>=1.11'
+    rfc3986-validator: '>0.1.0'
+    jsonschema: '>=4.19.1,<4.19.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-with-format-nongpl-4.19.1-pyhd8ed1ab_0.conda
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   category: main
   optional: false
-- name: r-ggplot2
-  version: 3.4.4
+- name: jsonschema-with-format-nongpl
+  version: 4.21.1
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-ggplot2-3.4.4-r43hc72bb7e_0.conda
+    python: ''
+    idna: ''
+    rfc3339-validator: ''
+    uri-template: ''
+    fqdn: ''
+    isoduration: ''
+    jsonpointer: '>1.13'
+    webcolors: '>=1.11'
+    rfc3986-validator: '>0.1.0'
+    jsonschema: '>=4.21.1,<4.21.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-with-format-nongpl-4.21.1-pyhd8ed1ab_0.conda
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   category: main
   optional: false
-- name: r-irdisplay
-  version: '1.1'
+- name: jupyter
+  version: 1.0.0
   manager: conda
   platform: linux-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-repr: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-irdisplay-1.1-r43hd8ed1ab_2.conda
+    ipykernel: ''
+    ipywidgets: ''
+    jupyter_console: ''
+    nbconvert: ''
+    notebook: ''
+    python: '>=3.6'
+    qtconsole-base: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-1.0.0-pyhd8ed1ab_10.conda
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   category: main
   optional: false
-- name: r-rematch2
-  version: 2.1.2
+- name: jupyter
+  version: 1.0.0
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-tibble: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-rematch2-2.1.2-r43hc72bb7e_3.conda
+    ipywidgets: ''
+    notebook: ''
+    nbconvert: ''
+    ipykernel: ''
+    qtconsole-base: ''
+    jupyter_console: ''
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-1.0.0-pyhd8ed1ab_10.conda
   hash:
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   category: main
   optional: false
-- name: r-rgexf
-  version: 0.16.2
+- name: jupyter
+  version: 1.0.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-igraph: ''
-    r-servr: ''
-    r-xml: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-rgexf-0.16.2-r43hc72bb7e_2.conda
+    ipywidgets: ''
+    notebook: ''
+    ipykernel: ''
+    nbconvert: ''
+    jupyter_console: ''
+    qtconsole-base: ''
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-1.0.0-pyhd8ed1ab_10.conda
   hash:
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   category: main
   optional: false
-- name: r-rmarkdown
-  version: '2.25'
+- name: jupyter
+  version: 1.0.0
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    pandoc: '>=1.14'
-    r-base: '>=4.3,<4.4.0a0'
-    r-bslib: '>=0.2.5.1'
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-    r-tinytex: '>=0.31'
-    r-xfun: '>=0.36'
-    r-yaml: '>=2.1.19'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-rmarkdown-2.25-r43hc72bb7e_0.conda
+    ipywidgets: ''
+    notebook: ''
+    nbconvert: ''
+    ipykernel: ''
+    qtconsole-base: ''
+    jupyter_console: ''
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-1.0.0-pyhd8ed1ab_10.conda
   hash:
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   category: main
   optional: false
-- name: r-shiny
-  version: 1.7.5.1
+- name: jupyter-book
+  version: 0.15.1
   manager: conda
   platform: linux-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-bslib: '>=0.3.0'
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-    r-fontawesome: '>=0.2.1'
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-    r-htmltools: '>=0.5.2'
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-    r-jsonlite: '>=0.9.16'
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-    r-mime: '>=0.3'
-    r-promises: '>=1.1.0'
-    r-r6: '>=2.0'
-    r-rlang: '>=0.4.10'
-    r-sourcetools: ''
-    r-withr: ''
-    r-xtable: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-shiny-1.7.5.1-r43h785f33e_0.conda
+    click: '>=7.1,<9'
+    docutils: '>=0.15,<0.19'
+    jinja2: ''
+    jsonschema: <5
+    linkify-it-py: '>=2.0.0,<2.1.0'
+    myst-nb: '>=0.17.1,<0.18.0'
+    python: '>=3.7'
+    pyyaml: ''
+    sphinx: '>=4,<6'
+    sphinx-book-theme: '>=1.0.0,<1.1.0'
+    sphinx-comments: ''
+    sphinx-copybutton: ''
+    sphinx-design: '>=0.3.0,<0.4.0'
+    sphinx-external-toc: '>=0.3.1,<0.4.0'
+    sphinx-jupyterbook-latex: '>=0.5.2,<0.6.0'
+    sphinx-multitoc-numbering: '>=0.1.3,<0.2.0'
+    sphinx-thebe: '>=0.2.0,<0.3.0'
+    sphinx-togglebutton: ''
+    sphinxcontrib-bibtex: '>=2.2.0,<=2.5.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-book-0.15.1-pyhd8ed1ab_0.conda
   hash:
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-    sha256: d3545b97b2149b47435bcf2c88d0cce8bd7b1ccfb26dd165f185adf9111798a9
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   category: main
   optional: false
-- name: r-vroom
-  version: 1.6.4
+- name: jupyter-book
+  version: 0.15.1
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    libgcc-ng: '>=12'
-    libstdcxx-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
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-    r-crayon: ''
-    r-glue: ''
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-    r-progress: '>=1.2.1'
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-    r-tidyselect: ''
-    r-tzdb: '>=0.1.1'
-    r-vctrs: '>=0.2.0'
-    r-withr: ''
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-vroom-1.6.4-r43ha503ecb_0.conda
+    pyyaml: ''
+    jinja2: ''
+    sphinx-copybutton: ''
+    sphinx-togglebutton: ''
+    sphinx-comments: ''
+    python: '>=3.7'
+    click: '>=7.1,<9'
+    sphinx: '>=4,<6'
+    sphinx-multitoc-numbering: '>=0.1.3,<0.2.0'
+    sphinxcontrib-bibtex: '>=2.2.0,<=2.5.0'
+    docutils: '>=0.15,<0.19'
+    jsonschema: <5
+    linkify-it-py: '>=2.0.0,<2.1.0'
+    sphinx-external-toc: '>=0.3.1,<0.4.0'
+    sphinx-jupyterbook-latex: '>=0.5.2,<0.6.0'
+    myst-nb: '>=0.17.1,<0.18.0'
+    sphinx-book-theme: '>=1.0.0,<1.1.0'
+    sphinx-design: '>=0.3.0,<0.4.0'
+    sphinx-thebe: '>=0.2.0,<0.3.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-book-0.15.1-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: r-worrms
-  version: 0.4.3
+- name: jupyter-book
+  version: 0.15.1
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-crul: '>=0.6.0'
-    r-data.table: ''
-    r-jsonlite: '>=1.1'
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-worrms-0.4.3-r43h785f33e_0.conda
+    pyyaml: ''
+    jinja2: ''
+    sphinx-copybutton: ''
+    sphinx-togglebutton: ''
+    sphinx-comments: ''
+    python: '>=3.7'
+    click: '>=7.1,<9'
+    sphinx: '>=4,<6'
+    sphinx-multitoc-numbering: '>=0.1.3,<0.2.0'
+    sphinxcontrib-bibtex: '>=2.2.0,<=2.5.0'
+    docutils: '>=0.15,<0.19'
+    jsonschema: <5
+    linkify-it-py: '>=2.0.0,<2.1.0'
+    sphinx-external-toc: '>=0.3.1,<0.4.0'
+    sphinx-jupyterbook-latex: '>=0.5.2,<0.6.0'
+    myst-nb: '>=0.17.1,<0.18.0'
+    sphinx-book-theme: '>=1.0.0,<1.1.0'
+    sphinx-design: '>=0.3.0,<0.4.0'
+    sphinx-thebe: '>=0.2.0,<0.3.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-book-0.15.1-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: jupyter
-  version: 1.0.0
+- name: jupyter-book
+  version: 0.15.1
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    ipykernel: ''
-    ipywidgets: ''
-    jupyter_console: ''
-    nbconvert: ''
-    notebook: ''
-    python: '>=3.6'
-    qtconsole-base: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-1.0.0-pyhd8ed1ab_10.conda
+    pyyaml: ''
+    jinja2: ''
+    sphinx-copybutton: ''
+    sphinx-togglebutton: ''
+    sphinx-comments: ''
+    python: '>=3.7'
+    click: '>=7.1,<9'
+    sphinx: '>=4,<6'
+    sphinx-multitoc-numbering: '>=0.1.3,<0.2.0'
+    sphinxcontrib-bibtex: '>=2.2.0,<=2.5.0'
+    docutils: '>=0.15,<0.19'
+    jsonschema: <5
+    linkify-it-py: '>=2.0.0,<2.1.0'
+    sphinx-external-toc: '>=0.3.1,<0.4.0'
+    sphinx-jupyterbook-latex: '>=0.5.2,<0.6.0'
+    myst-nb: '>=0.17.1,<0.18.0'
+    sphinx-book-theme: '>=1.0.0,<1.1.0'
+    sphinx-design: '>=0.3.0,<0.4.0'
+    sphinx-thebe: '>=0.2.0,<0.3.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-book-0.15.1-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: r-cowplot
-  version: 1.1.1
+- name: jupyter-cache
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   manager: conda
   platform: linux-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-ggplot2: '>2.2.1'
-    r-gtable: ''
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-    r-scales: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-cowplot-1.1.1-r43hc72bb7e_2.conda
+    attrs: ''
+    click: ''
+    importlib-metadata: ''
+    nbclient: '>=0.2,<0.8'
+    nbformat: ''
+    python: '>=3.8'
+    pyyaml: ''
+    sqlalchemy: '>=1.3.12,<3'
+    tabulate: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-cache-0.6.1-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: r-eml
-  version: 2.0.6.1
+- name: jupyter-cache
+  version: 0.6.1
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-digest: ''
-    r-dplyr: ''
-    r-emld: '>=0.0.0.9900'
-    r-jqr: ''
-    r-jsonlite: ''
-    r-rmarkdown: ''
-    r-uuid: ''
-    r-xml2: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-eml-2.0.6.1-r43hc72bb7e_2.conda
+    pyyaml: ''
+    click: ''
+    importlib-metadata: ''
+    tabulate: ''
+    attrs: ''
+    nbformat: ''
+    python: '>=3.8'
+    sqlalchemy: '>=1.3.12,<3'
+    nbclient: '>=0.2,<0.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-cache-0.6.1-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: r-htmlwidgets
-  version: 1.6.2
+- name: jupyter-cache
+  version: 0.6.1
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-htmltools: '>=0.5.4'
-    r-jsonlite: '>=0.9.16'
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-    r-yaml: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-htmlwidgets-1.6.2-r43hc72bb7e_1.conda
+    pyyaml: ''
+    click: ''
+    importlib-metadata: ''
+    tabulate: ''
+    nbformat: ''
+    attrs: ''
+    python: '>=3.8'
+    nbclient: '>=0.2,<0.8'
+    sqlalchemy: '>=1.3.12,<3'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-cache-0.6.1-pyhd8ed1ab_0.conda
   hash:
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-    sha256: f4d1c8082e3aa9a65cc2351a99cc21c7b99c5c4f32bf99a22614c36d58ba231f
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   category: main
   optional: false
-- name: r-irkernel
-  version: 1.3.2
+- name: jupyter-cache
+  version: 0.6.1
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-crayon: ''
-    r-digest: ''
-    r-evaluate: '>=0.10'
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-    r-jsonlite: '>=0.9.6'
-    r-pbdzmq: '>=0.2_1'
-    r-repr: '>=0.4.99'
-    r-uuid: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-irkernel-1.3.2-r43h785f33e_1.conda
+    pyyaml: ''
+    click: ''
+    importlib-metadata: ''
+    tabulate: ''
+    attrs: ''
+    nbformat: ''
+    python: '>=3.8'
+    sqlalchemy: '>=1.3.12,<3'
+    nbclient: '>=0.2,<0.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-cache-0.6.1-pyhd8ed1ab_0.conda
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   optional: false
-- name: r-miniui
-  version: 0.1.1.1
+- name: jupyter-lsp
+  version: 2.2.2
   manager: conda
   platform: linux-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-htmltools: '>=0.3'
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-miniui-0.1.1.1-r43hc72bb7e_1004.conda
+    importlib-metadata: '>=4.8.3'
+    jupyter_server: '>=1.1.2'
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-lsp-2.2.2-pyhd8ed1ab_0.conda
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-    sha256: d3efd6a925a135384992cfc356f4d1e6ff93aa916643245ee9a0d9f9bb06801a
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+    sha256: d8ab253be3df67be1b31fe040a8386e071ff065ef4442b94a722a45fa3562fbe
   category: main
   optional: false
-- name: r-readr
-  version: 2.1.4
+- name: jupyter-lsp
+  version: 2.2.2
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    libgcc-ng: '>=12'
-    libstdcxx-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
-    r-cli: ''
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-    r-crayon: ''
-    r-hms: '>=0.4.1'
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-    r-rlang: ''
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-    r-vroom: '>=1.5.4'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-readr-2.1.4-r43ha503ecb_1.conda
+    python: '>=3.8'
+    importlib-metadata: '>=4.8.3'
+    jupyter_server: '>=1.1.2'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-lsp-2.2.2-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 57b6f066e343a8ab1ed918b9abf1a376e132c31f6f1541ab72371a2686026832
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+    sha256: d8ab253be3df67be1b31fe040a8386e071ff065ef4442b94a722a45fa3562fbe
   category: main
   optional: false
-- name: r-rerddap
-  version: 1.0.4
+- name: jupyter-lsp
+  version: 2.2.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
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-    r-crul: '>=0.7.4'
-    r-data.table: '>=1.12.0'
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-    r-jsonlite: '>=1.6'
-    r-ncdf4: '>=1.16'
-    r-tibble: ''
-    r-xml2: '>=1.2.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-rerddap-1.0.4-r43hc72bb7e_0.conda
+    python: '>=3.8'
+    importlib-metadata: '>=4.8.3'
+    jupyter_server: '>=1.1.2'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-lsp-2.2.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: c6058dc86181c686613d516ee65b012c6b94d7ec98b31f93f42b240f574f6908
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+    sha256: 16fc7b40024adece716ba7227e5c123a2deccc13f946a10d9a3270493908d11c
   category: main
   optional: false
-- name: r-tidyr
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+- name: jupyter-lsp
+  version: 2.2.2
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    libgcc-ng: '>=12'
-    libstdcxx-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
-    r-cli: '>=3.4.1'
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-    r-magrittr: ''
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-    r-rlang: '>=1.0.4'
-    r-stringr: '>=1.5.0'
-    r-tibble: '>=2.1.1'
-    r-tidyselect: '>=1.2.0'
-    r-vctrs: '>=0.5.2'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-tidyr-1.3.0-r43ha503ecb_1.conda
+    python: '>=3.8'
+    importlib-metadata: '>=4.8.3'
+    jupyter_server: '>=1.1.2'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-lsp-2.2.2-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 8b1cee365a703efd3af8ceaebad88d6a9e30c0cb795b9b64a61e2fc061e5fde9
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+    sha256: d8ab253be3df67be1b31fe040a8386e071ff065ef4442b94a722a45fa3562fbe
   category: main
   optional: false
-- name: r-viridis
-  version: 0.6.4
+- name: jupyter-server-mathjax
+  version: 0.2.6
   manager: conda
   platform: linux-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-ggplot2: '>=1.0.1'
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-viridis-0.6.4-r43hc72bb7e_0.conda
+    jupyter_server: '>=1.1,<3'
+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-server-mathjax-0.2.6-pyh5bfe37b_1.conda
   hash:
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-    sha256: 95c4ced3a2f770f8183a2288b8b402e50344de151c799c9bd6c16a0076a1b4eb
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+    sha256: 46f6c3b76d9f03e8eb31e1c178083efb7de94447b8b14d378493073666a791a1
   category: main
   optional: false
-- name: r-waldo
-  version: 0.5.1
+- name: jupyter-server-mathjax
+  version: 0.2.6
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-cli: ''
-    r-diffobj: '>=0.3.4'
-    r-fansi: ''
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-    r-rematch2: ''
-    r-rlang: '>=1.0.0'
-    r-tibble: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-waldo-0.5.1-r43hc72bb7e_1.conda
+    python: '>=3.7'
+    jupyter_server: '>=1.1,<3'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-server-mathjax-0.2.6-pyh5bfe37b_1.conda
   hash:
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-    sha256: 62565d34d7a17008da4ff5daef22a717dde06e1b69e27c9e48cb25c3536ac489
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   category: main
   optional: false
-- name: r-dt
-  version: '0.28'
+- name: jupyter-server-mathjax
+  version: 0.2.6
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-crosstalk: ''
-    r-htmltools: '>=0.3.6'
-    r-htmlwidgets: '>=1.3'
-    r-jquerylib: ''
-    r-jsonlite: '>=0.9.16'
-    r-magrittr: ''
-    r-promises: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-dt-0.28-r43hc72bb7e_1.conda
+    python: '>=3.7'
+    jupyter_server: '>=1.1,<3'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-server-mathjax-0.2.6-pyh5bfe37b_1.conda
   hash:
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-    sha256: a4d698593a6b6d40a9df81802ebfd6d750782521407bb35a5ef16247a722a598
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   category: main
   optional: false
-- name: r-finch
-  version: 0.4.0
+- name: jupyter-server-mathjax
+  version: 0.2.6
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
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-    r-data.table: '>=1.10.0'
-    r-digest: ''
-    r-eml: '>=2.0.0'
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-    r-rappdirs: ''
-    r-xml2: '>=1.0.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-finch-0.4.0-r43hc72bb7e_2.conda
+    python: '>=3.7'
+    jupyter_server: '>=1.1,<3'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-server-mathjax-0.2.6-pyh5bfe37b_1.conda
   hash:
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-    sha256: 2b36e651c20305fe714c9204bdc603c57202c684ffd444bf52f1b191eac2f48a
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+    sha256: 46f6c3b76d9f03e8eb31e1c178083efb7de94447b8b14d378493073666a791a1
   category: main
   optional: false
-- name: r-ggfortify
-  version: 0.4.16
+- name: jupyter_client
+  version: 8.6.0
   manager: conda
   platform: linux-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-dplyr: '>=0.3'
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-    r-scales: ''
-    r-stringr: ''
-    r-tibble: ''
-    r-tidyr: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-ggfortify-0.4.16-r43hc72bb7e_1.conda
+    importlib_metadata: '>=4.8.3'
+    jupyter_core: '>=4.12,!=5.0.*'
+    python: '>=3.8'
+    python-dateutil: '>=2.8.2'
+    pyzmq: '>=23.0'
+    tornado: '>=6.2'
+    traitlets: '>=5.3'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_client-8.6.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 31c76b95be21937675c4f523b90350621d9aa2d04a64bd9606e7b282d71195b6
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+    sha256: 86cbb9070862cf23a245451efce539ca214e610849d0950bb8ac90c545bd158d
   category: main
   optional: false
-- name: r-leaflet
-  version: 2.2.0
+- name: jupyter_client
+  version: 8.6.0
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-base64enc: ''
-    r-crosstalk: ''
-    r-htmltools: ''
-    r-htmlwidgets: ''
-    r-leaflet.providers: '>=1.8.0'
-    r-magrittr: ''
-    r-markdown: ''
-    r-png: ''
-    r-raster: ''
-    r-rcolorbrewer: ''
-    r-scales: '>=1.0.0'
-    r-sp: ''
-    r-viridis: '>=0.5.1'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-leaflet-2.2.0-r43hc72bb7e_0.conda
+    python: '>=3.8'
+    python-dateutil: '>=2.8.2'
+    jupyter_core: '>=4.12,!=5.0.*'
+    importlib_metadata: '>=4.8.3'
+    traitlets: '>=5.3'
+    pyzmq: '>=23.0'
+    tornado: '>=6.2'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_client-8.6.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: d6c25e6a9b8f9bdc5fa5c5fec04384907408b6eba25baa89809b8b5ab3a0ebd0
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+    sha256: 86cbb9070862cf23a245451efce539ca214e610849d0950bb8ac90c545bd158d
   category: main
   optional: false
-- name: r-leafpop
-  version: 0.1.0
+- name: jupyter_client
+  version: 8.5.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    libgcc-ng: '>=12'
-    libstdcxx-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
-    r-base64enc: ''
-    r-brew: ''
-    r-htmltools: ''
-    r-htmlwidgets: ''
-    r-sf: ''
-    r-svglite: ''
-    r-uuid: ''
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-leafpop-0.1.0-r43ha503ecb_2.conda
+    python: '>=3.8'
+    python-dateutil: '>=2.8.2'
+    jupyter_core: '>=4.12,!=5.0.*'
+    traitlets: '>=5.3'
+    pyzmq: '>=23.0'
+    importlib_metadata: '>=4.8.3'
+    tornado: '>=6.2'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_client-8.5.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 5fe3fbba4431ac9bcd75b98a2118cbd2e41b1f684c59d3052ba0806a871f6dea
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+    sha256: e4478e137e0975ce94ef4ee6e4a6736afaf4a00e99bc8007a275bcb39fe728d9
   category: main
   optional: false
-- name: r-mapdeck
-  version: 0.3.4
+- name: jupyter_client
+  version: 8.6.0
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    libgcc-ng: '>=12'
-    libstdcxx-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
-    r-colourvalues: '>=0.3.4'
-    r-geojsonsf: '>=1.3.3'
-    r-geometries: ''
-    r-googlepolylines: '>=0.7.2'
-    r-htmlwidgets: ''
-    r-jsonify: '>=1.1.1'
-    r-magrittr: ''
-    r-rapidjsonr: ''
-    r-rcpp: ''
-    r-sfheaders: '>=0.2.2'
-    r-shiny: ''
-    r-spatialwidget: '>=0.2.3'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-mapdeck-0.3.4-r43ha503ecb_3.conda
+    python: '>=3.8'
+    python-dateutil: '>=2.8.2'
+    jupyter_core: '>=4.12,!=5.0.*'
+    importlib_metadata: '>=4.8.3'
+    traitlets: '>=5.3'
+    pyzmq: '>=23.0'
+    tornado: '>=6.2'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_client-8.6.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: c2d8e4f294d831b7736d5f84a78adb0f673017d12fcfe344d54795c4b70774d8
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+    sha256: 86cbb9070862cf23a245451efce539ca214e610849d0950bb8ac90c545bd158d
   category: main
   optional: false
-- name: r-testthat
-  version: 3.2.0
+- name: jupyter_console
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   manager: conda
   platform: linux-64
   dependencies:
-    libgcc-ng: '>=12'
-    libstdcxx-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
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-    r-evaluate: ''
-    r-jsonlite: ''
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-    r-pkgload: ''
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-    r-processx: ''
-    r-ps: '>=1.3.4'
-    r-r6: '>=2.2.0'
-    r-rlang: '>=0.4.1'
-    r-waldo: '>=0.2.1'
-    r-withr: '>=2.0.0'
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-testthat-3.2.0-r43ha503ecb_0.conda
+    ipykernel: '>=6.14'
+    ipython: ''
+    jupyter_client: '>=7.0.0'
+    jupyter_core: '>=4.12,!=5.0.*'
+    prompt_toolkit: '>=3.0.30'
+    pygments: ''
+    python: '>=3.7'
+    pyzmq: '>=17'
+    traitlets: '>=5.4'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_console-6.6.3-pyhd8ed1ab_0.conda
   hash:
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-    sha256: f0b7a9d7df1135474803465748011a6ed2ac3734185bdb2f56d778a1f6f6de20
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   category: main
   optional: false
-- name: r-visnetwork
-  version: 2.1.2
+- name: jupyter_console
+  version: 6.6.3
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-htmltools: ''
-    r-htmlwidgets: ''
-    r-jsonlite: ''
-    r-magrittr: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-visnetwork-2.1.2-r43hc72bb7e_2.conda
+    ipython: ''
+    pygments: ''
+    python: '>=3.7'
+    pyzmq: '>=17'
+    jupyter_core: '>=4.12,!=5.0.*'
+    jupyter_client: '>=7.0.0'
+    ipykernel: '>=6.14'
+    traitlets: '>=5.4'
+    prompt_toolkit: '>=3.0.30'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_console-6.6.3-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 1a21d3b5e6ce5c5efcf9c8fb206abe13c6459c33b104d52751bc220479bc13d5
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+    sha256: 4e51764d5fe2f6e43d83bcfbcf8b4da6569721bf82eaf4d647be8717cd6be75a
   category: main
   optional: false
-- name: r-xtractomatic
-  version: 3.4.2
+- name: jupyter_console
+  version: 6.6.3
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-dplyr: ''
-    r-httr: ''
-    r-ncdf4: ''
-    r-readr: ''
-    r-sp: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-xtractomatic-3.4.2-r43h785f33e_4.conda
+    ipython: ''
+    pygments: ''
+    python: '>=3.7'
+    pyzmq: '>=17'
+    jupyter_core: '>=4.12,!=5.0.*'
+    jupyter_client: '>=7.0.0'
+    ipykernel: '>=6.14'
+    traitlets: '>=5.4'
+    prompt_toolkit: '>=3.0.30'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_console-6.6.3-pyhd8ed1ab_0.conda
   hash:
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-    sha256: f1ed42e7d058af28ad1a6126d22c8a7ed5b2e60f50b430f1ea371d1803798593
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+    sha256: 4e51764d5fe2f6e43d83bcfbcf8b4da6569721bf82eaf4d647be8717cd6be75a
   category: main
   optional: false
-- name: r-diagrammer
-  version: 1.0.10
+- name: jupyter_console
+  version: 6.6.3
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-downloader: '>=0.4'
-    r-dplyr: '>=0.7.4'
-    r-glue: '>=1.2.0'
-    r-htmltools: '>=0.3.6'
-    r-htmlwidgets: '>=1.0'
-    r-igraph: '>=1.1.2'
-    r-influencer: '>=0.1.0'
-    r-magrittr: '>=1.5'
-    r-purrr: '>=0.2.4'
-    r-rcolorbrewer: '>=1.1_2'
-    r-readr: '>=1.1.1'
-    r-rgexf: '>=0.15.3'
-    r-rlang: '>=0.2.0'
-    r-rstudioapi: '>=0.7'
-    r-scales: '>=0.5.0'
-    r-stringr: '>=1.3.0'
-    r-tibble: '>=1.4.2'
-    r-tidyr: '>=0.8.0'
-    r-viridis: '>=0.5.0'
-    r-visnetwork: '>=2.0.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-diagrammer-1.0.10-r43hc72bb7e_1.conda
+    ipython: ''
+    pygments: ''
+    python: '>=3.7'
+    pyzmq: '>=17'
+    jupyter_core: '>=4.12,!=5.0.*'
+    jupyter_client: '>=7.0.0'
+    ipykernel: '>=6.14'
+    traitlets: '>=5.4'
+    prompt_toolkit: '>=3.0.30'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_console-6.6.3-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 572cf485eab05b354c60bcb01fc110db0723a51525f12dfbd51a0fee47d45b32
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+    sha256: 4e51764d5fe2f6e43d83bcfbcf8b4da6569721bf82eaf4d647be8717cd6be75a
   category: main
   optional: false
-- name: r-gsw
-  version: '1.1_1'
+- name: jupyter_core
+  version: 5.7.1
   manager: conda
   platform: linux-64
   dependencies:
-    libgcc-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
-    r-testthat: ''
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-gsw-1.1_1-r43hd590300_1.conda
+    platformdirs: '>=2.5'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    traitlets: '>=5.3'
+  url: https://conda.anaconda.org/conda-forge/linux-64/jupyter_core-5.7.1-py312h7900ff3_0.conda
   hash:
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-    sha256: 67a3adf1886cc90073298f97074467045fd05dc5d24f0cb5c3291df3e99b2566
+    md5: a26a2c80b748744dafb642a9a729e119
+    sha256: ce667e4829f934ace4437474ad4775bbd5ac53a597529afebfd8533dec1e697c
   category: main
   optional: false
-- name: r-leafem
-  version: 0.2.3
+- name: jupyter_core
+  version: 5.7.1
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-base64enc: ''
-    r-htmltools: '>=0.3'
-    r-htmlwidgets: ''
-    r-leaflet: '>=2.0.1'
-    r-mapdeck: ''
-    r-png: ''
-    r-raster: ''
-    r-scales: '>=1.0.0'
-    r-sf: ''
-    r-sp: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-leafem-0.2.3-r43h785f33e_0.conda
+    platformdirs: '>=2.5'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    traitlets: '>=5.3'
+  url: https://conda.anaconda.org/conda-forge/osx-64/jupyter_core-5.7.1-py312hb401068_0.conda
   hash:
-    md5: 0030f30227c17da9a268ecc00c0279c2
-    sha256: f2a0b21e95a893511c91940cd89c588278ef3bf863e2ddc4046e0daba47dd9a4
+    md5: 5db7505ee6fbb00f060782a8d93f974a
+    sha256: 410f57e7812dbf9122d416b4a9fc8d3833836fe40929ef845e221d4c8de0edbc
   category: main
   optional: false
-- name: r-leaflet.extras
-  version: 1.0.0
+- name: jupyter_core
+  version: 5.4.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-htmltools: ''
-    r-htmlwidgets: ''
-    r-leaflet: '>=2.0.0'
-    r-magrittr: ''
-    r-stringr: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-leaflet.extras-1.0.0-r43hc72bb7e_1006.conda
+    platformdirs: '>=2.5'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    traitlets: '>=5.3'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/jupyter_core-5.4.0-py312h81bd7bf_0.conda
   hash:
-    md5: 826d3aa9e550171ec11454400efd01cd
-    sha256: 21a42eead7e8de7b16cf59912a41e6761a71afa76c1a1084d3fae104be5dce81
+    md5: 5379051cda42f293221d6243e604d49a
+    sha256: 57d70af504df16f748b1d4dbee4bac440b8d9bc257f5151b996af005cf0caaab
   category: main
   optional: false
-- name: r-leafpm
-  version: 0.1.0
+- name: jupyter_core
+  version: 5.7.1
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-dplyr: ''
-    r-htmltools: '>=0.3'
-    r-htmlwidgets: ''
-    r-jsonlite: ''
-    r-leaflet: '>=2.0.1'
-    r-sf: '>=0.5_2'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-leafpm-0.1.0-r43hc72bb7e_5.conda
+    platformdirs: '>=2.5'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    pywin32: '>=300'
+    traitlets: '>=5.3'
+  url: https://conda.anaconda.org/conda-forge/win-64/jupyter_core-5.7.1-py312h2e8e312_0.conda
   hash:
-    md5: c2a38841b618b575ebb2a4d6f89370f0
-    sha256: ed12aaf41d7f42cf5aa3bc8a1ca15378b3f82afea75828dee50c3cce0ca0e180
+    md5: 4169f425045de1e7e7ddc19fba8eaf71
+    sha256: d4ad01e013ad873c08fb8118c339695d9f289a908d59a9ffc1e68833ad61405b
   category: main
   optional: false
-- name: r-data.tree
-  version: 1.0.0
+- name: jupyter_events
+  version: 0.9.0
   manager: conda
   platform: linux-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-diagrammer: '>=1.0.0'
-    r-r6: ''
-    r-stringr: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-data.tree-1.0.0-r43hd8ed1ab_2.conda
+    jsonschema-with-format-nongpl: '>=4.18.0'
+    python: '>=3.8'
+    python-json-logger: '>=2.0.4'
+    pyyaml: '>=5.3'
+    referencing: ''
+    rfc3339-validator: ''
+    rfc3986-validator: '>=0.1.1'
+    traitlets: '>=5.3'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_events-0.9.0-pyhd8ed1ab_0.conda
   hash:
-    md5: beca08a9458356627a8a9778bce1bb0f
-    sha256: cef6294cbf191e8132701a922508e436b2f88858b72f8e6b14a7c03602402c66
+    md5: 00ba25993f0dba38cf72a7224e33289f
+    sha256: 713f0cc927a862862a6d35bfb29c4114f987e4f59e2a8a14f71f23fcd7edfec3
   category: main
   optional: false
-- name: r-mapview
-  version: 2.11.2
+- name: jupyter_events
+  version: 0.9.0
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-base64enc: ''
-    r-htmltools: ''
-    r-htmlwidgets: ''
-    r-lattice: ''
-    r-leafem: ''
-    r-leaflet: '>=2.0.0'
-    r-leafpop: ''
-    r-png: ''
-    r-raster: ''
-    r-satellite: ''
-    r-scales: '>=0.2.5'
-    r-servr: ''
-    r-sf: ''
-    r-sp: ''
-    r-webshot: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-mapview-2.11.2-r43hc72bb7e_0.conda
+    rfc3339-validator: ''
+    referencing: ''
+    python: '>=3.8'
+    pyyaml: '>=5.3'
+    rfc3986-validator: '>=0.1.1'
+    traitlets: '>=5.3'
+    python-json-logger: '>=2.0.4'
+    jsonschema-with-format-nongpl: '>=4.18.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_events-0.9.0-pyhd8ed1ab_0.conda
   hash:
-    md5: 21d49cc1e6ee48f0593e1c644f5b81c5
-    sha256: 01b16fc2dfea68386bbce456042d9b68b760022dc92401a8bfd70d9703c2481c
+    md5: 00ba25993f0dba38cf72a7224e33289f
+    sha256: 713f0cc927a862862a6d35bfb29c4114f987e4f59e2a8a14f71f23fcd7edfec3
   category: main
   optional: false
-- name: r-oce
-  version: '1.8_1'
+- name: jupyter_events
+  version: 0.8.0
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    libgcc-ng: '>=12'
-    libgfortran-ng: ''
-    libgfortran5: '>=12.3.0'
-    libstdcxx-ng: '>=12'
-    r-base: '>=4.3,<4.4.0a0'
-    r-gsw: ''
-    r-rcpp: ''
-    r-sf: ''
-    r-testthat: ''
-  url: https://conda.anaconda.org/conda-forge/linux-64/r-oce-1.8_1-r43h9bbc0ff_0.conda
+    rfc3339-validator: ''
+    referencing: ''
+    python: '>=3.8'
+    pyyaml: '>=5.3'
+    rfc3986-validator: '>=0.1.1'
+    traitlets: '>=5.3'
+    python-json-logger: '>=2.0.4'
+    jsonschema-with-format-nongpl: '>=4.18.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_events-0.8.0-pyhd8ed1ab_0.conda
   hash:
-    md5: b2e4ff42847f00358c60934b58c8e353
-    sha256: 6bee4b8d6b98f63386a84f70fdebe93c5166e241039f5ffbfda53efe1a061af0
+    md5: 04272d87d3e06c2e26af5e2d4b0e0ad8
+    sha256: 44742f7b6453774fbbdf7cec20282f88c7362707990790116fec23270b81b447
   category: main
   optional: false
-- name: r-mapedit
-  version: 0.6.0
+- name: jupyter_events
+  version: 0.9.0
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-dplyr: ''
-    r-htmltools: '>=0.3'
-    r-htmlwidgets: ''
-    r-jsonlite: ''
-    r-leaflet: '>=2.0.1'
-    r-leaflet.extras: '>=1.0'
-    r-leafpm: ''
-    r-mapview: ''
-    r-miniui: ''
-    r-sf: '>=0.5_2'
-    r-shiny: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-mapedit-0.6.0-r43h785f33e_3.conda
+    rfc3339-validator: ''
+    referencing: ''
+    python: '>=3.8'
+    pyyaml: '>=5.3'
+    rfc3986-validator: '>=0.1.1'
+    traitlets: '>=5.3'
+    python-json-logger: '>=2.0.4'
+    jsonschema-with-format-nongpl: '>=4.18.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_events-0.9.0-pyhd8ed1ab_0.conda
   hash:
-    md5: 97f605947c9f6c10373222c37dab1093
-    sha256: ef59918cfb0499985d411778827bdf6abb3d45b9505961273bb04ae32613eaf2
+    md5: 00ba25993f0dba38cf72a7224e33289f
+    sha256: 713f0cc927a862862a6d35bfb29c4114f987e4f59e2a8a14f71f23fcd7edfec3
   category: main
   optional: false
-- name: r-obistools
-  version: 0.0.10
+- name: jupyter_server
+  version: 2.12.5
   manager: conda
   platform: linux-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-cowplot: ''
-    r-data.tree: ''
-    r-digest: ''
-    r-dplyr: ''
-    r-geosphere: ''
-    r-ggplot2: ''
-    r-httr: ''
-    r-jsonlite: ''
-    r-knitr: ''
-    r-leaflet: ''
-    r-maps: ''
-    r-rappdirs: ''
-    r-raster: ''
-    r-rgdal: ''
-    r-rgeos: ''
-    r-rmarkdown: ''
-    r-sf: ''
-    r-sp: ''
-    r-stringr: ''
-    r-tidyr: ''
-    r-worrms: ''
-    r-xml2: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-obistools-0.0.10-r43hd8ed1ab_3.conda
+    anyio: '>=3.1.0'
+    argon2-cffi: ''
+    jinja2: ''
+    jupyter_client: '>=7.4.4'
+    jupyter_core: '>=4.12,!=5.0.*'
+    jupyter_events: '>=0.9.0'
+    jupyter_server_terminals: ''
+    nbconvert-core: '>=6.4.4'
+    nbformat: '>=5.3.0'
+    overrides: ''
+    packaging: ''
+    prometheus_client: ''
+    python: '>=3.8'
+    pyzmq: '>=24'
+    send2trash: '>=1.8.2'
+    terminado: '>=0.8.3'
+    tornado: '>=6.2.0'
+    traitlets: '>=5.6.0'
+    websocket-client: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_server-2.12.5-pyhd8ed1ab_0.conda
   hash:
-    md5: ef04359609828a700aa0763f37cb7412
-    sha256: 0f05bccb2baa3fb8e401eeef9fea09371fb710e8ffd8fc1f96e89f6bff5e1542
+    md5: 755177a956fa6dd90d5cfcbbb5084de2
+    sha256: 43dcd238c656c7ecf3228be8735def530cad5181f990c042ba202b9e383d2b1f
   category: main
   optional: false
-- name: r-robis
-  version: 2.11.3
+- name: jupyter_server
+  version: 2.12.5
   manager: conda
-  platform: linux-64
+  platform: osx-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-curl: ''
-    r-data.table: ''
-    r-dplyr: ''
-    r-ggplot2: ''
-    r-httpcache: ''
-    r-httr: ''
-    r-jsonlite: ''
-    r-leaflet: ''
-    r-mapedit: ''
-    r-purrr: ''
-    r-rlang: ''
-    r-sf: ''
-    r-stringr: ''
-    r-tibble: ''
-    r-tidyr: ''
-    r-tidyselect: ''
-    r-xml2: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/r-robis-2.11.3-r43hc72bb7e_2.conda
+    packaging: ''
+    jinja2: ''
+    prometheus_client: ''
+    websocket-client: ''
+    argon2-cffi: ''
+    overrides: ''
+    jupyter_server_terminals: ''
+    python: '>=3.8'
+    terminado: '>=0.8.3'
+    jupyter_core: '>=4.12,!=5.0.*'
+    tornado: '>=6.2.0'
+    nbconvert-core: '>=6.4.4'
+    pyzmq: '>=24'
+    jupyter_client: '>=7.4.4'
+    nbformat: '>=5.3.0'
+    traitlets: '>=5.6.0'
+    anyio: '>=3.1.0'
+    send2trash: '>=1.8.2'
+    jupyter_events: '>=0.9.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_server-2.12.5-pyhd8ed1ab_0.conda
   hash:
-    md5: 6f1997c44ffd450521cb67bb2069ef7d
-    sha256: 98c0b0e34ed4e5fdd862d98fdbae3f5ffe0a362ddf4f47ef7477cf5515beb4d0
+    md5: 755177a956fa6dd90d5cfcbbb5084de2
+    sha256: 43dcd238c656c7ecf3228be8735def530cad5181f990c042ba202b9e383d2b1f
   category: main
   optional: false
-- name: myst-parser
-  version: 0.18.1
+- name: jupyter_server
+  version: 2.9.1
   manager: conda
-  platform: linux-64
+  platform: osx-arm64
   dependencies:
-    docutils: '>=0.15,<0.20'
+    packaging: ''
     jinja2: ''
-    markdown-it-py: '>=1.0.0,<3.0.0'
-    mdit-py-plugins: '>=0.3.1,<1'
-    python: '>=3.7'
-    pyyaml: ''
-    sphinx: '>=4,<6'
-    typing-extensions: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/myst-parser-0.18.1-pyhd8ed1ab_0.tar.bz2
+    prometheus_client: ''
+    websocket-client: ''
+    argon2-cffi: ''
+    overrides: ''
+    jupyter_server_terminals: ''
+    python: '>=3.8'
+    terminado: '>=0.8.3'
+    jupyter_core: '>=4.12,!=5.0.*'
+    nbconvert-core: '>=6.4.4'
+    tornado: '>=6.2.0'
+    jupyter_client: '>=7.4.4'
+    nbformat: '>=5.3.0'
+    pyzmq: '>=24'
+    traitlets: '>=5.6.0'
+    jupyter_events: '>=0.6.0'
+    anyio: '>=3.1.0'
+    send2trash: '>=1.8.2'
+  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_server-2.9.1-pyhd8ed1ab_0.conda
   hash:
-    md5: bcfdf5c7d8bf5c6f6be7b4c66fff2eca
-    sha256: 260812a430adee3598103d75704c1c855a9816a3895971ca0190d0f5e1e8165a
+    md5: 8e0cfa69e5b0062b829a9dbb14645def
+    sha256: bb9a60ff41085031a28204add4e6120990437cfad341db297519f0a0f0df8e18
   category: main
   optional: false
-- name: myst-nb
-  version: 0.17.2
+- name: jupyter_server
+  version: 2.12.5
   manager: conda
-  platform: linux-64
+  platform: win-64
   dependencies:
-    importlib-metadata: ''
-    ipykernel: ''
-    ipython: ''
-    jupyter-cache: '>=0.5.0,<0.7.0'
-    myst-parser: '>=0.18.0,<0.19.0'
-    nbclient: ''
-    nbformat: '>=5.0,<6'
-    python: '>=3.7'
-    pyyaml: ''
-    sphinx: '>=4,<6'
-    typing_extensions: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/myst-nb-0.17.2-pyhd8ed1ab_0.conda
+    packaging: ''
+    jinja2: ''
+    prometheus_client: ''
+    websocket-client: ''
+    argon2-cffi: ''
+    overrides: ''
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-- name: sphinx-book-theme
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+  platform: osx-64
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-- name: sphinx-comments
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   manager: conda
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   dependencies:
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-- name: sphinx-copybutton
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   manager: conda
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+  platform: win-64
   dependencies:
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-- name: sphinx-design
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   platform: linux-64
   dependencies:
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-- name: sphinx-external-toc
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-- name: sphinx-jupyterbook-latex
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   manager: conda
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+  platform: osx-arm64
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-- name: sphinx-multitoc-numbering
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   manager: conda
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   dependencies:
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-- name: sphinx-thebe
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   platform: linux-64
   dependencies:
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-- name: sphinx-togglebutton
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   manager: conda
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   dependencies:
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-- name: sphinxcontrib-applehelp
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   manager: conda
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   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-applehelp-1.0.7-pyhd8ed1ab_0.conda
+    python: '>=3.7'
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-- name: sphinxcontrib-bibtex
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   manager: conda
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+  platform: win-64
   dependencies:
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+    python: '>=3.7'
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-- name: jupyter-book
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   platform: linux-64
   dependencies:
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-- name: sphinxcontrib-devhelp
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   manager: conda
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   dependencies:
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-- name: sphinxcontrib-htmlhelp
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   manager: conda
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   dependencies:
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-- name: sphinxcontrib-qthelp
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   manager: conda
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   dependencies:
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   manager: conda
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-- name: make
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-  url: https://conda.anaconda.org/conda-forge/osx-64/phantomjs-2.1.1-h694c41f_1.conda
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-- name: tzcode
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-- name: xorg-libxdmcp
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-- name: xz
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   manager: conda
   platform: osx-64
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-- name: libxml2
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   manager: conda
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-- name: lz4-c
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   manager: conda
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-- name: openssl
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   manager: conda
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+  platform: linux-64
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-- name: pandoc
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-- name: pcre2
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   manager: conda
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+  platform: linux-64
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-- name: pixman
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-- name: readline
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   manager: conda
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-- name: snappy
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+  platform: win-64
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-- name: tapi
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-- name: tk
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-- name: uriparser
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-- name: zstd
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-- name: blosc
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-- name: brotli-bin
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-- name: fonts-conda-ecosystem
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   manager: conda
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   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/fonts-conda-ecosystem-1-0.tar.bz2
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   category: main
   optional: false
-- name: freetype
-  version: 2.12.1
+- name: libev
+  version: '4.33'
   manager: conda
   platform: osx-64
-  dependencies:
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-    libzlib: '>=1.2.13,<1.3.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/freetype-2.12.1-h60636b9_2.conda
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-64/libev-4.33-h10d778d_2.conda
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   category: main
   optional: false
-- name: glpk
-  version: '5.0'
+- name: libev
+  version: '4.33'
   manager: conda
-  platform: osx-64
-  dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-64/glpk-5.0-h3cb5acd_0.tar.bz2
+  platform: osx-arm64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/libev-4.33-h642e427_1.tar.bz2
   hash:
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   category: main
   optional: false
-- name: krb5
-  version: 1.21.2
+- name: libexpat
+  version: 2.5.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    libcxx: '>=15.0.7'
-    libedit: '>=3.1.20191231,<4.0a0'
-    openssl: '>=3.1.2,<4.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/krb5-1.21.2-hb884880_0.conda
+    libgcc-ng: '>=12'
+  url: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.5.0-hcb278e6_1.conda
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   category: main
   optional: false
-- name: libarchive
-  version: 3.7.2
+- name: libexpat
+  version: 2.5.0
   manager: conda
   platform: osx-64
-  dependencies:
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-    libiconv: '>=1.17,<2.0a0'
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-    zstd: '>=1.5.5,<1.6.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/libarchive-3.7.2-h0b5dc4a_0.conda
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-64/libexpat-2.5.0-hf0c8a7f_1.conda
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   category: main
   optional: false
-- name: libgfortran
-  version: 5.0.0
+- name: libexpat
+  version: 2.5.0
   manager: conda
-  platform: osx-64
-  dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-64/libgfortran-5.0.0-13_2_0_h97931a8_1.conda
+  platform: osx-arm64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.5.0-hb7217d7_1.conda
   hash:
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   category: main
   optional: false
-- name: libglib
-  version: 2.78.0
+- name: libexpat
+  version: 2.5.0
   manager: conda
-  platform: osx-64
-  dependencies:
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-    libcxx: '>=15.0.7'
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-    libzlib: '>=1.2.13,<1.3.0a0'
-    pcre2: '>=10.40,<10.41.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/libglib-2.78.0-hc62aa5d_0.conda
+  platform: win-64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/win-64/libexpat-2.5.0-h63175ca_1.conda
   hash:
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   category: main
   optional: false
-- name: libkml
-  version: 1.3.0
+- name: libffi
+  version: 3.4.2
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    libboost-headers: ''
-    libcxx: '>=15.0.7'
-    libexpat: '>=2.5.0,<3.0a0'
-    libzlib: '>=1.2.13,<1.3.0a0'
-    uriparser: '>=0.9.7,<1.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/libkml-1.3.0-hab3ca0e_1018.conda
+    libgcc-ng: '>=9.4.0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.4.2-h7f98852_5.tar.bz2
   hash:
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   category: main
   optional: false
-- name: libllvm16
-  version: 16.0.6
+- name: libffi
+  version: 3.4.2
   manager: conda
   platform: osx-64
-  dependencies:
-    libcxx: '>=15'
-    libxml2: '>=2.11.4,<2.12.0a0'
-    libzlib: '>=1.2.13,<1.3.0a0'
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-  url: https://conda.anaconda.org/conda-forge/osx-64/libllvm16-16.0.6-he4b1e75_2.conda
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-64/libffi-3.4.2-h0d85af4_5.tar.bz2
   hash:
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   category: main
   optional: false
-- name: libnghttp2
-  version: 1.55.1
+- name: libffi
+  version: 3.4.2
   manager: conda
-  platform: osx-64
-  dependencies:
-    __osx: '>=10.9'
-    c-ares: '>=1.20.1,<2.0a0'
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-    openssl: '>=3.1.4,<4.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/libnghttp2-1.55.1-hc0a10c5_0.conda
+  platform: osx-arm64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.4.2-h3422bc3_5.tar.bz2
   hash:
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   category: main
   optional: false
-- name: libprotobuf
-  version: 4.24.4
+- name: libffi
+  version: 3.4.2
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    __osx: '>=10.9'
-    libabseil: '>=20230802.1,<20230803.0a0'
-    libcxx: '>=16.0.6'
-    libzlib: '>=1.2.13,<1.3.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/libprotobuf-4.24.4-h0ee05dc_0.conda
+    vc: '>=14.1,<15.0a0'
+    vs2015_runtime: '>=14.16.27012'
+  url: https://conda.anaconda.org/conda-forge/win-64/libffi-3.4.2-h8ffe710_5.tar.bz2
   hash:
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   category: main
   optional: false
-- name: librttopo
-  version: 1.1.0
+- name: libgcc-devel_linux-64
+  version: 13.2.0
   manager: conda
-  platform: osx-64
-  dependencies:
-    geos: '>=3.12.0,<3.12.1.0a0'
-    libcxx: '>=15.0.7'
-  url: https://conda.anaconda.org/conda-forge/osx-64/librttopo-1.1.0-h23f359d_14.conda
+  platform: linux-64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/noarch/libgcc-devel_linux-64-13.2.0-ha9c7c90_105.conda
   hash:
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   category: main
   optional: false
-- name: libssh2
-  version: 1.11.0
+- name: libgcc-ng
+  version: 13.2.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    libzlib: '>=1.2.13,<1.3.0a0'
-    openssl: '>=3.1.1,<4.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/libssh2-1.11.0-hd019ec5_0.conda
+    _libgcc_mutex: '0.1'
+    _openmp_mutex: '>=4.5'
+  url: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-13.2.0-h807b86a_5.conda
   hash:
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   category: main
   optional: false
-- name: libtiff
-  version: 4.6.0
+- name: libgdal
+  version: 3.8.4
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    lerc: '>=4.0.0,<5.0a0'
-    libcxx: '>=15.0.7'
-    libdeflate: '>=1.19,<1.20.0a0'
-    libjpeg-turbo: '>=3.0.0,<4.0a0'
-    libwebp-base: '>=1.3.2,<2.0a0'
+    __glibc: '>=2.17,<3.0.a0'
+    blosc: '>=1.21.5,<2.0a0'
+    cfitsio: '>=4.3.1,<4.3.2.0a0'
+    freexl: '>=2.0.0,<3.0a0'
+    geos: '>=3.12.1,<3.12.2.0a0'
+    geotiff: '>=1.7.1,<1.8.0a0'
+    giflib: '>=5.2.1,<5.3.0a0'
+    hdf4: '>=4.2.15,<4.2.16.0a0'
+    hdf5: '>=1.14.3,<1.14.4.0a0'
+    json-c: '>=0.17,<0.18.0a0'
+    kealib: '>=1.5.3,<1.6.0a0'
+    lerc: '>=4.0.0,<5.0a0'
+    libaec: '>=1.1.2,<2.0a0'
+    libarchive: '>=3.7.2,<3.8.0a0'
+    libcurl: '>=8.5.0,<9.0a0'
+    libdeflate: '>=1.19,<1.20.0a0'
+    libexpat: '>=2.5.0,<3.0a0'
+    libgcc-ng: '>=12'
+    libiconv: '>=1.17,<2.0a0'
+    libjpeg-turbo: '>=3.0.0,<4.0a0'
+    libkml: '>=1.3.0,<1.4.0a0'
+    libnetcdf: '>=4.9.2,<4.9.3.0a0'
+    libpng: '>=1.6.42,<1.7.0a0'
+    libpq: '>=16.2,<17.0a0'
+    libspatialite: '>=5.1.0,<5.2.0a0'
+    libsqlite: '>=3.45.1,<4.0a0'
+    libstdcxx-ng: '>=12'
+    libtiff: '>=4.6.0,<4.7.0a0'
+    libuuid: '>=2.38.1,<3.0a0'
+    libwebp-base: '>=1.3.2,<2.0a0'
+    libxml2: '>=2.12.5,<3.0a0'
     libzlib: '>=1.2.13,<1.3.0a0'
+    lz4-c: '>=1.9.3,<1.10.0a0'
+    openjpeg: '>=2.5.0,<3.0a0'
+    openssl: '>=3.2.1,<4.0a0'
+    pcre2: '>=10.42,<10.43.0a0'
+    poppler: '>=24.2.0,<24.3.0a0'
+    postgresql: ''
+    proj: '>=9.3.1,<9.3.2.0a0'
+    tiledb: '>=2.20.0,<2.21.0a0'
+    xerces-c: '>=3.2.5,<3.3.0a0'
     xz: '>=5.2.6,<6.0a0'
     zstd: '>=1.5.5,<1.6.0a0'
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-  hash:
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-    sha256: 1ef5bd7295f4316b111f70ad21356fb9f0de50b85a341cac9e3a61ac6487fdf1
-  category: main
-  optional: false
-- name: libxslt
-  version: 1.1.37
-  manager: conda
-  platform: osx-64
-  dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-64/libxslt-1.1.37-h20bfa82_1.conda
+  url: https://conda.anaconda.org/conda-forge/linux-64/libgdal-3.8.4-h9323651_0.conda
   hash:
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+    sha256: af88738b2eda7d388daad5bd7dd8fe66efbaba300921ecb6fb03d9c5823a950d
   category: main
   optional: false
-- name: libzip
-  version: 1.10.1
+- name: libgdal
+  version: 3.8.4
   manager: conda
   platform: osx-64
   dependencies:
-    bzip2: '>=1.0.8,<2.0a0'
+    blosc: '>=1.21.5,<2.0a0'
+    cfitsio: '>=4.3.1,<4.3.2.0a0'
+    freexl: '>=2.0.0,<3.0a0'
+    geos: '>=3.12.1,<3.12.2.0a0'
+    geotiff: '>=1.7.1,<1.8.0a0'
+    giflib: '>=5.2.1,<5.3.0a0'
+    hdf4: '>=4.2.15,<4.2.16.0a0'
+    hdf5: '>=1.14.3,<1.14.4.0a0'
+    json-c: '>=0.17,<0.18.0a0'
+    kealib: '>=1.5.3,<1.6.0a0'
+    lerc: '>=4.0.0,<5.0a0'
+    libaec: '>=1.1.2,<2.0a0'
+    libarchive: '>=3.7.2,<3.8.0a0'
+    libcurl: '>=8.5.0,<9.0a0'
+    libcxx: '>=16'
+    libdeflate: '>=1.19,<1.20.0a0'
+    libexpat: '>=2.5.0,<3.0a0'
+    libiconv: '>=1.17,<2.0a0'
+    libjpeg-turbo: '>=3.0.0,<4.0a0'
+    libkml: '>=1.3.0,<1.4.0a0'
+    libnetcdf: '>=4.9.2,<4.9.3.0a0'
+    libpng: '>=1.6.42,<1.7.0a0'
+    libpq: '>=16.2,<17.0a0'
+    libspatialite: '>=5.1.0,<5.2.0a0'
+    libsqlite: '>=3.45.1,<4.0a0'
+    libtiff: '>=4.6.0,<4.7.0a0'
+    libwebp-base: '>=1.3.2,<2.0a0'
+    libxml2: '>=2.12.5,<3.0a0'
     libzlib: '>=1.2.13,<1.3.0a0'
-    openssl: '>=3.1.2,<4.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/libzip-1.10.1-hc158999_3.conda
+    lz4-c: '>=1.9.3,<1.10.0a0'
+    openjpeg: '>=2.5.0,<3.0a0'
+    openssl: '>=3.2.1,<4.0a0'
+    pcre2: '>=10.42,<10.43.0a0'
+    poppler: '>=24.2.0,<24.3.0a0'
+    postgresql: ''
+    proj: '>=9.3.1,<9.3.2.0a0'
+    tiledb: '>=2.20.0,<2.21.0a0'
+    xerces-c: '>=3.2.5,<3.3.0a0'
+    xz: '>=5.2.6,<6.0a0'
+    zstd: '>=1.5.5,<1.6.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/libgdal-3.8.4-h46636ed_0.conda
   hash:
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   category: main
   optional: false
-- name: minizip
-  version: 4.0.2
+- name: libgdal
+  version: 3.7.2
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
     __osx: '>=10.9'
-    bzip2: '>=1.0.8,<2.0a0'
+    blosc: '>=1.21.5,<2.0a0'
+    cfitsio: '>=4.3.0,<4.3.1.0a0'
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+    lerc: '>=4.0.0,<5.0a0'
+    libarchive: '>=3.7.2,<3.8.0a0'
+    libcurl: '>=8.4.0,<9.0a0'
     libcxx: '>=16.0.6'
+    libdeflate: '>=1.19,<1.20.0a0'
+    libexpat: '>=2.5.0,<3.0a0'
     libiconv: '>=1.17,<2.0a0'
+    libjpeg-turbo: '>=3.0.0,<4.0a0'
+    libkml: '>=1.3.0,<1.4.0a0'
+    libnetcdf: '>=4.9.2,<4.9.3.0a0'
+    libpng: '>=1.6.39,<1.7.0a0'
+    libpq: '>=16.0,<17.0a0'
+    libspatialite: '>=5.1.0,<5.2.0a0'
+    libsqlite: '>=3.43.2,<4.0a0'
+    libtiff: '>=4.6.0,<4.7.0a0'
+    libwebp-base: '>=1.3.2,<2.0a0'
+    libxml2: '>=2.11.5,<2.12.0a0'
     libzlib: '>=1.2.13,<1.3.0a0'
-    openssl: '>=3.1.4,<4.0a0'
+    lz4-c: '>=1.9.3,<1.10.0a0'
+    openjpeg: '>=2.5.0,<3.0a0'
+    openssl: '>=3.1.3,<4.0a0'
+    pcre2: '>=10.40,<10.41.0a0'
+    poppler: '>=23.10.0,<23.11.0a0'
+    postgresql: ''
+    proj: '>=9.3.0,<9.3.1.0a0'
+    tiledb: '>=2.16,<2.17.0a0'
+    xerces-c: '>=3.2.4,<3.3.0a0'
     xz: '>=5.2.6,<6.0a0'
     zstd: '>=1.5.5,<1.6.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/minizip-4.0.2-h23f18a7_0.conda
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/libgdal-3.7.2-h116f65a_7.conda
   hash:
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   category: main
   optional: false
-- name: mpfr
-  version: 4.2.1
+- name: libgdal
+  version: 3.8.1
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-64/mpfr-4.2.1-h0c69b56_0.conda
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+    geotiff: '>=1.7.1,<1.8.0a0'
+    hdf4: '>=4.2.15,<4.2.16.0a0'
+    hdf5: '>=1.14.3,<1.14.4.0a0'
+    kealib: '>=1.5.2,<1.6.0a0'
+    lerc: '>=4.0.0,<5.0a0'
+    libaec: '>=1.1.2,<2.0a0'
+    libarchive: '>=3.7.2,<3.8.0a0'
+    libcurl: '>=8.5.0,<9.0a0'
+    libdeflate: '>=1.19,<1.20.0a0'
+    libexpat: '>=2.5.0,<3.0a0'
+    libiconv: '>=1.17,<2.0a0'
+    libjpeg-turbo: '>=3.0.0,<4.0a0'
+    libkml: '>=1.3.0,<1.4.0a0'
+    libnetcdf: '>=4.9.2,<4.9.3.0a0'
+    libpng: '>=1.6.39,<1.7.0a0'
+    libpq: '>=16.1,<17.0a0'
+    libspatialite: '>=5.1.0,<5.2.0a0'
+    libsqlite: '>=3.44.2,<4.0a0'
+    libtiff: '>=4.6.0,<4.7.0a0'
+    libwebp-base: '>=1.3.2,<2.0a0'
+    libxml2: '>=2.12.2,<3.0.0a0'
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+    openjpeg: '>=2.5.0,<3.0a0'
+    openssl: '>=3.2.0,<4.0a0'
+    pcre2: '>=10.42,<10.43.0a0'
+    poppler: '>=23.12.0,<23.13.0a0'
+    postgresql: ''
+    proj: '>=9.3.1,<9.3.2.0a0'
+    tiledb: '>=2.18.2,<2.19.0a0'
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+    xerces-c: '>=3.2.4,<3.3.0a0'
+    xz: '>=5.2.6,<6.0a0'
+    zstd: '>=1.5.5,<1.6.0a0'
+  url: https://conda.anaconda.org/conda-forge/win-64/libgdal-3.8.1-h70e2fc3_4.conda
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   category: main
   optional: false
-- name: nss
-  version: '3.94'
+- name: libgfortran
+  version: 5.0.0
   manager: conda
   platform: osx-64
   dependencies:
-    libcxx: '>=15.0.7'
-    libsqlite: '>=3.43.0,<4.0a0'
-    libzlib: '>=1.2.13,<1.3.0a0'
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-  url: https://conda.anaconda.org/conda-forge/osx-64/nss-3.94-hd6ac835_0.conda
+    libgfortran5: 13.2.0
+  url: https://conda.anaconda.org/conda-forge/osx-64/libgfortran-5.0.0-13_2_0_h97931a8_3.conda
   hash:
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   category: main
   optional: false
-- name: python
-  version: 3.12.0
+- name: libgfortran
+  version: 5.0.0
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    bzip2: '>=1.0.8,<2.0a0'
-    libexpat: '>=2.5.0,<3.0a0'
-    libffi: '>=3.4,<4.0a0'
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-    tk: '>=8.6.13,<8.7.0a0'
-    tzdata: ''
-    xz: '>=5.2.6,<6.0a0'
-    pip: ''
-  url: https://conda.anaconda.org/conda-forge/osx-64/python-3.12.0-h30d4d87_0_cpython.conda
+    libgfortran5: 13.2.0
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/libgfortran-5.0.0-13_2_0_hd922786_1.conda
   hash:
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+    sha256: bc8750e7893e693fa380bf2f342d4a5ce44995467cbdf72e56a00e5106b4892d
   category: main
   optional: false
-- name: sigtool
-  version: 0.1.3
+- name: libgfortran-devel_osx-64
+  version: 12.3.0
   manager: conda
   platform: osx-64
-  dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-64/sigtool-0.1.3-h88f4db0_0.tar.bz2
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/noarch/libgfortran-devel_osx-64-12.3.0-h0b6f5ec_3.conda
   hash:
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+    sha256: 2d81f8e94d030185f676e85f69b6258e8910d5e7338ed3db397e4ed2d5a50432
   category: main
   optional: false
-- name: sqlite
-  version: 3.43.2
+- name: libgfortran-ng
+  version: 13.2.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    libsqlite: 3.43.2
-    libzlib: '>=1.2.13,<1.3.0a0'
-    ncurses: '>=6.4,<7.0a0'
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-  url: https://conda.anaconda.org/conda-forge/osx-64/sqlite-3.43.2-h7461747_0.conda
+    libgfortran5: 13.2.0
+  url: https://conda.anaconda.org/conda-forge/linux-64/libgfortran-ng-13.2.0-h69a702a_5.conda
   hash:
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+    sha256: 238c16c84124d58307376715839aa152bd4a1bf5a043052938ad6c3137d30245
   category: main
   optional: false
-- name: tiledb
-  version: 2.16.3
+- name: libgfortran5
+  version: 13.2.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    bzip2: '>=1.0.8,<2.0a0'
-    libcxx: '>=15.0.7'
-    libxml2: '>=2.11.5,<2.12.0a0'
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-    openssl: '>=3.1.2,<4.0a0'
-    zstd: '>=1.5.5,<1.6.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/tiledb-2.16.3-h9b026fb_3.conda
+    libgcc-ng: '>=13.2.0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-13.2.0-ha4646dd_5.conda
   hash:
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+    sha256: ba8d94e8493222ce155bb264d9de4200e41498a458e866fedf444de809bde8b6
   category: main
   optional: false
-- name: tktable
-  version: '2.10'
+- name: libgfortran5
+  version: 13.2.0
   manager: conda
   platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-64/tktable-2.10-ha166976_5.conda
+    llvm-openmp: '>=8.0.0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/libgfortran5-13.2.0-h2873a65_3.conda
   hash:
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   category: main
   optional: false
-- name: udunits2
-  version: 2.2.28
+- name: libgfortran5
+  version: 13.2.0
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
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-    libudunits2: 2.2.28
-  url: https://conda.anaconda.org/conda-forge/osx-64/udunits2-2.2.28-h516ac8c_3.conda
+    llvm-openmp: '>=8.0.0'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/libgfortran5-13.2.0-hf226fd6_1.conda
   hash:
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   category: main
   optional: false
-- name: affine
-  version: 2.4.0
+- name: libglib
+  version: 2.78.4
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/affine-2.4.0-pyhd8ed1ab_0.conda
+    gettext: '>=0.21.1,<1.0a0'
+    libffi: '>=3.4,<4.0a0'
+    libgcc-ng: '>=12'
+    libiconv: '>=1.17,<2.0a0'
+    libstdcxx-ng: '>=12'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    pcre2: '>=10.42,<10.43.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/libglib-2.78.4-h783c2da_0.conda
   hash:
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   category: main
   optional: false
-- name: alabaster
-  version: 0.7.13
+- name: libglib
+  version: 2.78.4
   manager: conda
   platform: osx-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/alabaster-0.7.13-pyhd8ed1ab_0.conda
+    gettext: '>=0.21.1,<1.0a0'
+    libcxx: '>=16'
+    libffi: '>=3.4,<4.0a0'
+    libiconv: '>=1.17,<2.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    pcre2: '>=10.42,<10.43.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/libglib-2.78.4-hab64008_0.conda
   hash:
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   category: main
   optional: false
-- name: antlr-python-runtime
-  version: 4.11.1
+- name: libglib
+  version: 2.78.0
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/antlr-python-runtime-4.11.1-pyhd8ed1ab_0.tar.bz2
+    gettext: '>=0.21.1,<1.0a0'
+    libcxx: '>=15.0.7'
+    libffi: '>=3.4,<4.0a0'
+    libiconv: '>=1.17,<2.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    pcre2: '>=10.40,<10.41.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/libglib-2.78.0-h24e9cb9_0.conda
   hash:
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   category: main
   optional: false
-- name: appnope
-  version: 0.1.3
+- name: libglib
+  version: 2.78.4
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    python: '>=2.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/appnope-0.1.3-pyhd8ed1ab_0.tar.bz2
+    gettext: '>=0.21.1,<1.0a0'
+    libffi: '>=3.4,<4.0a0'
+    libiconv: '>=1.17,<2.0a0'
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+    pcre2: '>=10.42,<10.43.0a0'
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/libglib-2.78.4-h16e383f_0.conda
   hash:
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+    sha256: d4350c4c8d7947b4f1b13918e04f07a35d2eb88cc1b6bccefe12eb92bd1aa660
   category: main
   optional: false
-- name: asciitree
-  version: 0.3.3
+- name: libgomp
+  version: 13.2.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/asciitree-0.3.3-py_2.tar.bz2
+    _libgcc_mutex: '0.1'
+  url: https://conda.anaconda.org/conda-forge/linux-64/libgomp-13.2.0-h807b86a_5.conda
   hash:
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   category: main
   optional: false
-- name: attrs
-  version: 23.1.0
+- name: libgoogle-cloud
+  version: 2.12.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/attrs-23.1.0-pyh71513ae_1.conda
+    libabseil: '>=20230802.1,<20230803.0a0'
+    libcrc32c: '>=1.1.2,<1.2.0a0'
+    libcurl: '>=8.5.0,<9.0a0'
+    libgcc-ng: '>=12'
+    libgrpc: '>=1.60.0,<1.61.0a0'
+    libprotobuf: '>=4.25.1,<4.25.2.0a0'
+    libstdcxx-ng: '>=12'
+    openssl: '>=3.2.0,<4.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/libgoogle-cloud-2.12.0-hef10d8f_5.conda
   hash:
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-- name: backcall
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   dependencies:
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-- name: backports
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   manager: conda
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+  platform: linux-64
   dependencies:
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-- name: bagit
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   dependencies:
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-- name: brotli
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   manager: conda
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+  platform: win-64
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-- name: brotli-python
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   manager: conda
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+  platform: linux-64
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-- name: cached_property
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   manager: conda
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-- name: certifi
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-  url: https://conda.anaconda.org/conda-forge/noarch/certifi-2023.7.22-pyhd8ed1ab_0.conda
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-- name: cfgv
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   manager: conda
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+  platform: win-64
   dependencies:
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-- name: chardet
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   manager: conda
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+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-64/chardet-5.2.0-py312hb401068_1.conda
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-- name: charset-normalizer
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-- name: click
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   manager: conda
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-  url: https://conda.anaconda.org/conda-forge/noarch/click-8.1.7-unix_pyh707e725_0.conda
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-- name: colorama
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   manager: conda
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+  platform: win-64
   dependencies:
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-- name: cycler
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   manager: conda
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+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/cycler-0.12.1-pyhd8ed1ab_0.conda
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-- name: cython
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   manager: conda
   platform: osx-64
   dependencies:
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-    libcxx: '>=16.0.6'
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-- name: dataclasses
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-- name: debugpy
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   manager: conda
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   dependencies:
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-- name: decorator
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   manager: conda
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   dependencies:
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-- name: defusedxml
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   manager: conda
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   dependencies:
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-- name: distlib
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   manager: conda
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   dependencies:
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-- name: docopt
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   manager: conda
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   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/docopt-0.6.2-py_1.tar.bz2
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   category: main
   optional: false
-- name: docutils
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   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: '>=3.12.0rc3,<3.13.0a0'
-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-64/docutils-0.17.1-py312hb401068_4.conda
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    libzlib: '>=1.2.13,<1.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/libllvm14-14.0.6-hcd5def8_4.conda
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   category: main
   optional: false
-- name: entrypoints
-  version: '0.4'
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   manager: conda
   platform: osx-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/entrypoints-0.4-pyhd8ed1ab_0.tar.bz2
+    libcxx: '>=15'
+    libzlib: '>=1.2.13,<1.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/libllvm14-14.0.6-hc8e404f_4.conda
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   category: main
   optional: false
-- name: exceptiongroup
-  version: 1.1.3
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+  version: 17.0.6
   manager: conda
   platform: osx-64
   dependencies:
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/exceptiongroup-1.1.3-pyhd8ed1ab_0.conda
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+    libxml2: '>=2.12.1,<3.0.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    zstd: '>=1.5.5,<1.6.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/libllvm17-17.0.6-hbedff68_1.conda
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   category: main
   optional: false
-- name: executing
-  version: 2.0.1
+- name: libnetcdf
+  version: 4.9.2
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: '>=2.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/executing-2.0.1-pyhd8ed1ab_0.conda
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+    libcurl: '>=8.5.0,<9.0a0'
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+    libstdcxx-ng: '>=12'
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+    libzlib: '>=1.2.13,<1.3.0a0'
+    openssl: '>=3.2.0,<4.0a0'
+    zlib: ''
+    zstd: '>=1.5.5,<1.6.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/libnetcdf-4.9.2-nompi_h9612171_113.conda
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   category: main
   optional: false
-- name: fasteners
-  version: 0.17.3
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+  version: 4.9.2
   manager: conda
   platform: osx-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/fasteners-0.17.3-pyhd8ed1ab_0.tar.bz2
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+    libaec: '>=1.1.2,<2.0a0'
+    libcurl: '>=8.5.0,<9.0a0'
+    libcxx: '>=16.0.6'
+    libxml2: '>=2.12.2,<3.0.0a0'
+    libzip: '>=1.10.1,<2.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    openssl: '>=3.2.0,<4.0a0'
+    zlib: ''
+    zstd: '>=1.5.5,<1.6.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/libnetcdf-4.9.2-nompi_h7760872_113.conda
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   category: main
   optional: false
-- name: filelock
-  version: 3.13.0
+- name: libnetcdf
+  version: 4.9.2
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/filelock-3.13.0-pyhd8ed1ab_0.conda
+    blosc: '>=1.21.4,<2.0a0'
+    bzip2: '>=1.0.8,<2.0a0'
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+    libaec: '>=1.0.6,<2.0a0'
+    libcurl: '>=8.2.1,<9.0a0'
+    libcxx: '>=15.0.7'
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+    libzip: '>=1.10.1,<2.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    openssl: '>=3.1.2,<4.0a0'
+    zlib: ''
+    zstd: '>=1.5.5,<1.6.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/libnetcdf-4.9.2-nompi_hb2fb864_112.conda
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   category: main
   optional: false
-- name: fontconfig
-  version: 2.14.2
+- name: libnetcdf
+  version: 4.9.2
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    expat: '>=2.5.0,<3.0a0'
-    freetype: '>=2.12.1,<3.0a0'
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+    bzip2: '>=1.0.8,<2.0a0'
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+    libcurl: '>=8.5.0,<9.0a0'
+    libxml2: '>=2.12.2,<3.0.0a0'
+    libzip: '>=1.10.1,<2.0a0'
     libzlib: '>=1.2.13,<1.3.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/fontconfig-2.14.2-h5bb23bf_0.conda
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+    zlib: ''
+    zstd: '>=1.5.5,<1.6.0a0'
+  url: https://conda.anaconda.org/conda-forge/win-64/libnetcdf-4.9.2-nompi_h07c049d_113.conda
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   category: main
   optional: false
-- name: freexl
-  version: 2.0.0
+- name: libnghttp2
+  version: 1.58.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    libexpat: '>=2.5.0,<3.0a0'
-    libiconv: '>=1.17,<2.0a0'
-    minizip: '>=4.0.1,<5.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/freexl-2.0.0-h3ec172f_0.conda
+    c-ares: '>=1.23.0,<2.0a0'
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+    libstdcxx-ng: '>=12'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    openssl: '>=3.2.0,<4.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/libnghttp2-1.58.0-h47da74e_1.conda
   hash:
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   category: main
   optional: false
-- name: geographiclib
-  version: '1.52'
+- name: libnghttp2
+  version: 1.58.0
   manager: conda
   platform: osx-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/geographiclib-1.52-pyhd8ed1ab_0.tar.bz2
+    __osx: '>=10.9'
+    c-ares: '>=1.23.0,<2.0a0'
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+    libzlib: '>=1.2.13,<1.3.0a0'
+    openssl: '>=3.2.0,<4.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/libnghttp2-1.58.0-h64cf6d3_1.conda
   hash:
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   category: main
   optional: false
-- name: geojson
-  version: 2.5.0
+- name: libnghttp2
+  version: 1.55.1
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    python: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/geojson-2.5.0-py_0.tar.bz2
+    __osx: '>=10.9'
+    c-ares: '>=1.20.1,<2.0a0'
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+    libev: '>=4.33,<4.34.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    openssl: '>=3.1.4,<4.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/libnghttp2-1.55.1-h2b02ca0_0.conda
   hash:
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   category: main
   optional: false
-- name: greenlet
-  version: 3.0.1
+- name: libnsl
+  version: 2.0.1
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    __osx: '>=10.9'
-    libcxx: '>=16.0.6'
-    python: '>=3.12,<3.13.0a0'
-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-64/greenlet-3.0.1-py312h444b7ae_0.conda
+    libgcc-ng: '>=12'
+  url: https://conda.anaconda.org/conda-forge/linux-64/libnsl-2.0.1-hd590300_0.conda
   hash:
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   category: main
   optional: false
-- name: hpack
-  version: 4.0.0
+- name: libopenblas
+  version: 0.3.26
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/hpack-4.0.0-pyh9f0ad1d_0.tar.bz2
+    libgcc-ng: '>=12'
+    libgfortran-ng: ''
+    libgfortran5: '>=12.3.0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/libopenblas-0.3.26-pthreads_h413a1c8_0.conda
   hash:
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   category: main
   optional: false
-- name: humanize
-  version: 4.8.0
+- name: libopenblas
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   manager: conda
   platform: osx-64
   dependencies:
-    python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/humanize-4.8.0-pyhd8ed1ab_0.conda
+    libgfortran: 5.*
+    libgfortran5: '>=12.3.0'
+    llvm-openmp: '>=16.0.6'
+  url: https://conda.anaconda.org/conda-forge/osx-64/libopenblas-0.3.26-openmp_hfef2a42_0.conda
   hash:
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   category: main
   optional: false
-- name: hyperframe
-  version: 6.0.1
+- name: libopenblas
+  version: 0.3.24
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/hyperframe-6.0.1-pyhd8ed1ab_0.tar.bz2
+    libgfortran: 5.*
+    libgfortran5: '>=12.3.0'
+    llvm-openmp: '>=15.0.7'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/libopenblas-0.3.24-openmp_hd76b1f2_0.conda
   hash:
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   category: main
   optional: false
-- name: idna
-  version: '3.4'
+- name: libpng
+  version: 1.6.42
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/idna-3.4-pyhd8ed1ab_0.tar.bz2
+    libgcc-ng: '>=12'
+    libzlib: '>=1.2.13,<1.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/libpng-1.6.42-h2797004_0.conda
   hash:
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   category: main
   optional: false
-- name: imagesize
-  version: 1.4.1
+- name: libpng
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   manager: conda
   platform: osx-64
   dependencies:
-    python: '>=3.4'
-  url: https://conda.anaconda.org/conda-forge/noarch/imagesize-1.4.1-pyhd8ed1ab_0.tar.bz2
+    libzlib: '>=1.2.13,<1.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/libpng-1.6.42-h92b6c6a_0.conda
   hash:
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   category: main
   optional: false
-- name: iniconfig
-  version: 2.0.0
+- name: libpng
+  version: 1.6.39
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/iniconfig-2.0.0-pyhd8ed1ab_0.conda
+    libzlib: '>=1.2.13,<1.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/libpng-1.6.39-h76d750c_0.conda
   hash:
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   category: main
   optional: false
-- name: ipython_genutils
-  version: 0.2.0
+- name: libpng
+  version: 1.6.42
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    python: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/ipython_genutils-0.2.0-py_1.tar.bz2
+    libzlib: '>=1.2.13,<1.3.0a0'
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/libpng-1.6.42-h19919ed_0.conda
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-- name: json5
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   manager: conda
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+  platform: linux-64
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-- name: jsonpointer
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   manager: conda
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+    openssl: '>=3.2.1,<4.0a0'
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-- name: jupyterlab_widgets
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   manager: conda
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+  platform: osx-arm64
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-- name: kiwisolver
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   manager: conda
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-- name: lcms2
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-- name: ld64_osx-64
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   manager: conda
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-- name: libclang-cpp16
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+  platform: osx-arm64
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-- name: libcurl
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-- name: libopenblas
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   manager: conda
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-- name: libpq
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-- name: libv8
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   manager: conda
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-- name: llvm-tools
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-- name: lxml
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-- name: markupsafe
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-- name: mccabe
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   manager: conda
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   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/mccabe-0.7.0-pyhd8ed1ab_0.tar.bz2
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-- name: mdurl
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   dependencies:
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-- name: mpc
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-- name: mpmath
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   category: main
   optional: false
-- name: msgpack-python
-  version: 1.0.6
+- name: libspatialindex
+  version: 1.9.3
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    libcxx: '>=15.0.7'
-    python: '>=3.12.0rc3,<3.13.0a0'
-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-64/msgpack-python-1.0.6-py312h49ebfd2_0.conda
+    libgcc-ng: '>=9.3.0'
+    libstdcxx-ng: '>=9.3.0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/libspatialindex-1.9.3-h9c3ff4c_4.tar.bz2
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   category: main
   optional: false
-- name: munch
-  version: 4.0.0
+- name: libspatialindex
+  version: 1.9.3
   manager: conda
   platform: osx-64
   dependencies:
-    python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/munch-4.0.0-pyhd8ed1ab_0.conda
+    libcxx: '>=11.1.0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/libspatialindex-1.9.3-he49afe7_4.tar.bz2
   hash:
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   category: main
   optional: false
-- name: munkres
-  version: 1.1.4
+- name: libspatialindex
+  version: 1.9.3
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    python: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/munkres-1.1.4-pyh9f0ad1d_0.tar.bz2
+    libcxx: '>=11.1.0'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/libspatialindex-1.9.3-hbdafb3b_4.tar.bz2
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   category: main
   optional: false
-- name: nest-asyncio
-  version: 1.5.8
+- name: libspatialindex
+  version: 1.9.3
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    python: '>=3.5'
-  url: https://conda.anaconda.org/conda-forge/noarch/nest-asyncio-1.5.8-pyhd8ed1ab_0.conda
+    vc: '>=14.1,<15.0a0'
+    vs2015_runtime: '>=14.16.27012'
+  url: https://conda.anaconda.org/conda-forge/win-64/libspatialindex-1.9.3-h39d44d4_4.tar.bz2
   hash:
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   category: main
   optional: false
-- name: networkx
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+- name: libspatialite
+  version: 5.1.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: '>=3.9'
-  url: https://conda.anaconda.org/conda-forge/noarch/networkx-3.2.1-pyhd8ed1ab_0.conda
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+    geos: '>=3.12.1,<3.12.2.0a0'
+    libgcc-ng: '>=12'
+    librttopo: '>=1.1.0,<1.2.0a0'
+    libsqlite: '>=3.44.2,<4.0a0'
+    libstdcxx-ng: '>=12'
+    libxml2: '>=2.12.2,<3.0.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    proj: '>=9.3.1,<9.3.2.0a0'
+    sqlite: ''
+    zlib: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/libspatialite-5.1.0-h7bd4643_4.conda
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   category: main
   optional: false
-- name: openjpeg
-  version: 2.5.0
+- name: libspatialite
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   manager: conda
   platform: osx-64
   dependencies:
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-    libpng: '>=1.6.39,<1.7.0a0'
-    libtiff: '>=4.6.0,<4.7.0a0'
+    __osx: '>=10.9'
+    freexl: '>=2.0.0,<3.0a0'
+    geos: '>=3.12.1,<3.12.2.0a0'
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+    libiconv: '>=1.17,<2.0a0'
+    librttopo: '>=1.1.0,<1.2.0a0'
+    libsqlite: '>=3.44.2,<4.0a0'
+    libxml2: '>=2.12.2,<3.0.0a0'
     libzlib: '>=1.2.13,<1.3.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/openjpeg-2.5.0-ha4da562_3.conda
+    proj: '>=9.3.1,<9.3.2.0a0'
+    sqlite: ''
+    zlib: ''
+  url: https://conda.anaconda.org/conda-forge/osx-64/libspatialite-5.1.0-hebe6af1_4.conda
   hash:
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   category: main
   optional: false
-- name: packaging
-  version: '23.2'
+- name: libspatialite
+  version: 5.1.0
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/packaging-23.2-pyhd8ed1ab_0.conda
+    freexl: '>=2.0.0,<3.0a0'
+    geos: '>=3.12.0,<3.12.1.0a0'
+    libcxx: '>=15.0.7'
+    libiconv: '>=1.17,<2.0a0'
+    librttopo: '>=1.1.0,<1.2.0a0'
+    libsqlite: '>=3.43.0,<4.0a0'
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+    libzlib: '>=1.2.13,<1.3.0a0'
+    proj: '>=9.3.0,<9.3.1.0a0'
+    sqlite: ''
+    zlib: ''
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/libspatialite-5.1.0-h32510b6_0.conda
   hash:
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   optional: false
-- name: palettable
-  version: 3.3.3
+- name: libspatialite
+  version: 5.1.0
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/palettable-3.3.3-pyhd8ed1ab_0.conda
+    freexl: '>=2.0.0,<3.0a0'
+    geos: '>=3.12.1,<3.12.2.0a0'
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+    libzlib: '>=1.2.13,<1.3.0a0'
+    proj: '>=9.3.1,<9.3.2.0a0'
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+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+    zlib: ''
+  url: https://conda.anaconda.org/conda-forge/win-64/libspatialite-5.1.0-hf2f0abc_4.conda
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-- name: pandocfilters
-  version: 1.5.0
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   manager: conda
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+  platform: linux-64
   dependencies:
-    python: '!=3.0,!=3.1,!=3.2,!=3.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/pandocfilters-1.5.0-pyhd8ed1ab_0.tar.bz2
+    libgcc-ng: '>=12'
+    libzlib: '>=1.2.13,<1.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.45.1-h2797004_0.conda
   hash:
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   optional: false
-- name: param
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   manager: conda
   platform: osx-64
   dependencies:
-    python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/param-2.0.0-pyhca7485f_0.conda
+    libzlib: '>=1.2.13,<1.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/libsqlite-3.45.1-h92b6c6a_0.conda
   hash:
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   optional: false
-- name: parso
-  version: 0.8.3
+- name: libsqlite
+  version: 3.43.2
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/parso-0.8.3-pyhd8ed1ab_0.tar.bz2
+    libzlib: '>=1.2.13,<1.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/libsqlite-3.43.2-h091b4b1_0.conda
   hash:
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   optional: false
-- name: pickleshare
-  version: 0.7.5
+- name: libsqlite
+  version: 3.45.1
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    python: '>=3'
-  url: https://conda.anaconda.org/conda-forge/noarch/pickleshare-0.7.5-py_1003.tar.bz2
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/libsqlite-3.45.1-hcfcfb64_0.conda
   hash:
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   category: main
   optional: false
-- name: pkgutil-resolve-name
-  version: 1.3.10
+- name: libssh2
+  version: 1.11.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/pkgutil-resolve-name-1.3.10-pyhd8ed1ab_1.conda
+    libgcc-ng: '>=12'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    openssl: '>=3.1.1,<4.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/libssh2-1.11.0-h0841786_0.conda
   hash:
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   category: main
   optional: false
-- name: pluggy
-  version: 1.3.0
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   manager: conda
   platform: osx-64
   dependencies:
-    python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/pluggy-1.3.0-pyhd8ed1ab_0.conda
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+    openssl: '>=3.1.1,<4.0a0'
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   hash:
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   category: main
   optional: false
-- name: portalocker
-  version: 2.8.2
+- name: libssh2
+  version: 1.11.0
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    python: '>=3.12.0rc3,<3.13.0a0'
-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-64/portalocker-2.8.2-py312hb401068_1.conda
+    libzlib: '>=1.2.13,<1.3.0a0'
+    openssl: '>=3.1.1,<4.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/libssh2-1.11.0-h7a5bd25_0.conda
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   optional: false
-- name: prometheus_client
-  version: 0.17.1
+- name: libssh2
+  version: 1.11.0
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/prometheus_client-0.17.1-pyhd8ed1ab_0.conda
+    libzlib: '>=1.2.13,<1.3.0a0'
+    openssl: '>=3.1.1,<4.0a0'
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/libssh2-1.11.0-h7dfc565_0.conda
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   category: main
   optional: false
-- name: psutil
-  version: 5.9.5
+- name: libstdcxx-devel_linux-64
+  version: 13.2.0
   manager: conda
-  platform: osx-64
-  dependencies:
-    python: '>=3.12.0rc3,<3.13.0a0'
-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-64/psutil-5.9.5-py312h104f124_1.conda
+  platform: linux-64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/noarch/libstdcxx-devel_linux-64-13.2.0-ha9c7c90_105.conda
   hash:
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   optional: false
-- name: ptyprocess
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   manager: conda
-  platform: osx-64
-  dependencies:
-    python: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/ptyprocess-0.7.0-pyhd3deb0d_0.tar.bz2
+  platform: linux-64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-13.2.0-h7e041cc_5.conda
   hash:
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   optional: false
-- name: pure_eval
-  version: 0.2.2
+- name: libtiff
+  version: 4.6.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: '>=3.5'
-  url: https://conda.anaconda.org/conda-forge/noarch/pure_eval-0.2.2-pyhd8ed1ab_0.tar.bz2
+    lerc: '>=4.0.0,<5.0a0'
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+    libjpeg-turbo: '>=3.0.0,<4.0a0'
+    libstdcxx-ng: '>=12'
+    libwebp-base: '>=1.3.2,<2.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    xz: '>=5.2.6,<6.0a0'
+    zstd: '>=1.5.5,<1.6.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/libtiff-4.6.0-ha9c0a0a_2.conda
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-- name: pysocks
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-- name: python-tzdata
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-  url: https://conda.anaconda.org/conda-forge/noarch/python-tzdata-2023.3-pyhd8ed1ab_0.conda
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-- name: pytz
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-- name: pytzdata
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-- name: pyyaml
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-- name: pyzmq
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   manager: conda
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   dependencies:
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-- name: regex
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   manager: conda
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   dependencies:
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-- name: rfc3986-validator
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   manager: conda
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+  platform: osx-arm64
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-- name: rpds-py
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   manager: conda
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   dependencies:
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-- name: rtree
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   dependencies:
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-- name: ruamel.yaml.clib
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-- name: tornado
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-- name: types-python-dateutil
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-- name: tzlocal
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-- name: uri-template
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-- name: uritemplate
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   manager: conda
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+  platform: linux-64
   dependencies:
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-- name: webcolors
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-- name: websocket-client
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-- name: xmltodict
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-- name: xyzservices
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-- name: zipp
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-- name: accessible-pygments
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-- name: anyio
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-- name: asttokens
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-- name: async-lru
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   manager: conda
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-- name: babel
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-- name: beautifulsoup4
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-- name: bleach
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-- name: cached-property
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+  version: 1.3.1
   manager: conda
-  platform: osx-64
+  platform: win-64
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+    m2w64-libogg: ''
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-- name: cairo
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   manager: conda
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+  platform: win-64
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-- name: cctools_osx-64
-  version: 973.0.1
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   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-64/cctools_osx-64-973.0.1-ha1c5b94_15.conda
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+    m2w64-gcc-libs-core: ''
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-- name: cffi
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   manager: conda
-  platform: osx-64
+  platform: win-64
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-- name: cfitsio
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   manager: conda
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+  platform: win-64
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-- name: clang-16
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   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
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-- name: click-plugins
-  version: 1.1.1
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   manager: conda
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+  platform: win-64
   dependencies:
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-    click: '>=3.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/click-plugins-1.1.1-py_0.tar.bz2
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-- name: cligj
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   manager: conda
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+  platform: win-64
   dependencies:
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-    click: '>=4.0'
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-- name: comm
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   manager: conda
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+  platform: win-64
   dependencies:
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-    traitlets: '>=5.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/comm-0.1.4-pyhd8ed1ab_0.conda
+    msys2-conda-epoch: '20160418'
+  url: https://conda.anaconda.org/conda-forge/win-64/m2w64-libiconv-1.14-6.tar.bz2
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-- name: configobj
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   manager: conda
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+  platform: win-64
   dependencies:
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-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/configobj-5.0.8-pyhd8ed1ab_0.conda
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+    msys2-conda-epoch: '20160418'
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-- name: coverage
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+  version: 1.3.2
   manager: conda
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+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-64/coverage-7.3.2-py312h104f124_0.conda
+    msys2-conda-epoch: '20160418'
+  url: https://conda.anaconda.org/conda-forge/win-64/m2w64-libogg-1.3.2-3.tar.bz2
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-- name: curl
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+- name: m2w64-libpng
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   manager: conda
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+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-64/curl-8.4.0-h726d00d_0.conda
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+    m2w64-zlib: ''
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-- name: easyargs
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   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
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-    six: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/easyargs-0.9.4-py_0.tar.bz2
+    m2w64-flac: ''
+    m2w64-libvorbis: ''
+    m2w64-speex: ''
+    msys2-conda-epoch: '20160418'
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-- name: flake8
-  version: 6.1.0
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   manager: conda
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+  platform: win-64
   dependencies:
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+  url: https://conda.anaconda.org/conda-forge/win-64/m2w64-libtiff-4.0.6-2.tar.bz2
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-- name: fonttools
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   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
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-    munkres: ''
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-  url: https://conda.anaconda.org/conda-forge/osx-64/fonttools-4.43.1-py312h41838bb_0.conda
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+    m2w64-libogg: ''
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-- name: geolinks
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   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/geolinks-0.2.3-pyhd8ed1ab_0.conda
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+  url: https://conda.anaconda.org/conda-forge/win-64/m2w64-libwinpthread-git-5.0.0.4634.697f757-2.tar.bz2
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   optional: false
-- name: geopy
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+  version: 2.9.3
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
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-    geographiclib: <2,>=1.49
-  url: https://conda.anaconda.org/conda-forge/noarch/geopy-2.4.0-pyhd8ed1ab_0.conda
+    m2w64-gcc-libs: ''
+    m2w64-gettext: ''
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-- name: gfortran_impl_osx-64
-  version: 12.3.0
+- name: m2w64-mpfr
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   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-64/gfortran_impl_osx-64-12.3.0-h54fd467_1.conda
+    m2w64-gmp: ''
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-- name: gitdb
-  version: 4.0.11
+- name: m2w64-pcre2
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   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
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-- name: rfc3339-validator
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-- name: ruamel.yaml
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-- name: sympy
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-- name: tinycss2
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   manager: conda
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   manager: conda
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-- name: markdown
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   manager: conda
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-- name: mdit-py-plugins
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-- name: pendulum
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   manager: conda
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-- name: platformdirs
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   manager: conda
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   dependencies:
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-- name: poppler
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   manager: conda
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+    tbb: 2021.*
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-- name: pybtex
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   manager: conda
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-- name: pygeoif
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-- name: pyobjc-framework-cocoa
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   manager: conda
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+  platform: linux-64
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-- name: pyproj
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   dependencies:
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-- name: requests
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   manager: conda
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   dependencies:
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-- name: sqlalchemy
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   manager: conda
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+  platform: win-64
   dependencies:
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-- name: stack_data
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   manager: conda
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   dependencies:
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-- name: trio
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   manager: conda
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   dependencies:
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-- name: ukkonen
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   manager: conda
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     libcxx: '>=15.0.7'
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     python_abi: 3.12.*
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-- name: wsproto
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   manager: conda
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+  platform: win-64
   dependencies:
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-- name: argon2-cffi
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   manager: conda
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-- name: clangxx
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   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-64/clangxx-16.0.6-default_h762fdd7_1.conda
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/munch-4.0.0-pyhd8ed1ab_0.conda
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   category: main
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-- name: github3.py
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   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
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-    python-dateutil: '>=2.6.0'
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-  url: https://conda.anaconda.org/conda-forge/noarch/github3.py-4.0.1-pyhd8ed1ab_0.conda
+    python: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/munkres-1.1.4-pyh9f0ad1d_0.tar.bz2
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   category: main
   optional: false
-- name: gsl
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   manager: conda
   platform: osx-64
   dependencies:
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+    python: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/munkres-1.1.4-pyh9f0ad1d_0.tar.bz2
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-- name: httpx
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   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
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-    idna: ''
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-    httpcore: '>=0.18.0,<0.19.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/httpx-0.25.0-pyhd8ed1ab_0.conda
+    python: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/munkres-1.1.4-pyh9f0ad1d_0.tar.bz2
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-- name: identify
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+- name: munkres
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   manager: conda
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+  platform: win-64
   dependencies:
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-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/identify-2.5.31-pyhd8ed1ab_0.conda
+    python: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/munkres-1.1.4-pyh9f0ad1d_0.tar.bz2
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-- name: isoduration
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   manager: conda
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+  platform: linux-64
   dependencies:
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     python: '>=3.7'
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-  url: https://conda.anaconda.org/conda-forge/noarch/isoduration-20.11.0-pyhd8ed1ab_0.tar.bz2
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-  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-4.19.1-pyhd8ed1ab_0.conda
+    pyyaml: ''
+    sphinx: '>=4,<6'
+    typing_extensions: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/myst-nb-0.17.2-pyhd8ed1ab_0.conda
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-- name: jupyter_core
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   manager: conda
   platform: osx-64
   dependencies:
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-    python: '>=3.12,<3.13.0a0'
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-  url: https://conda.anaconda.org/conda-forge/osx-64/jupyter_core-5.4.0-py312hb401068_0.conda
+    pyyaml: ''
+    typing_extensions: ''
+    ipython: ''
+    importlib-metadata: ''
+    ipykernel: ''
+    nbclient: ''
+    python: '>=3.7'
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+    sphinx: '>=4,<6'
+    myst-parser: '>=0.18.0,<0.19.0'
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-- name: libgdal
-  version: 3.7.2
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   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-64/libgdal-3.7.2-h926149b_7.conda
+    pyyaml: ''
+    typing_extensions: ''
+    ipython: ''
+    importlib-metadata: ''
+    ipykernel: ''
+    nbclient: ''
+    python: '>=3.7'
+    nbformat: '>=5.0,<6'
+    sphinx: '>=4,<6'
+    myst-parser: '>=0.18.0,<0.19.0'
+    jupyter-cache: '>=0.5.0,<0.7.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/myst-nb-0.17.2-pyhd8ed1ab_0.conda
   hash:
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   optional: false
-- name: netcdf-fortran
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+- name: myst-nb
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   manager: conda
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+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-64/netcdf-fortran-4.6.1-nompi_ha9164e6_102.conda
+    pyyaml: ''
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+    importlib-metadata: ''
+    ipykernel: ''
+    nbclient: ''
+    python: '>=3.7'
+    nbformat: '>=5.0,<6'
+    sphinx: '>=4,<6'
+    myst-parser: '>=0.18.0,<0.19.0'
+    jupyter-cache: '>=0.5.0,<0.7.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/myst-nb-0.17.2-pyhd8ed1ab_0.conda
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   category: main
   optional: false
-- name: numpy
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+- name: myst-parser
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   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
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-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-64/numpy-1.26.0-py312h5df92dc_0.conda
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+    markdown-it-py: '>=1.0.0,<3.0.0'
+    mdit-py-plugins: '>=0.3.1,<1'
+    python: '>=3.7'
+    pyyaml: ''
+    sphinx: '>=4,<6'
+    typing-extensions: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/myst-parser-0.18.1-pyhd8ed1ab_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: owslib
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+- name: myst-parser
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   manager: conda
   platform: osx-64
   dependencies:
     pyyaml: ''
-    lxml: ''
-    pytz: ''
-    dataclasses: ''
+    typing-extensions: ''
+    jinja2: ''
     python: '>=3.7'
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-    requests: '>=1.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/owslib-0.29.2-pyhd8ed1ab_0.conda
+    markdown-it-py: '>=1.0.0,<3.0.0'
+    sphinx: '>=4,<6'
+    docutils: '>=0.15,<0.20'
+    mdit-py-plugins: '>=0.3.1,<1'
+  url: https://conda.anaconda.org/conda-forge/noarch/myst-parser-0.18.1-pyhd8ed1ab_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: pango
-  version: 1.50.14
+- name: myst-parser
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   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
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+    pyyaml: ''
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+    python: '>=3.7'
+    markdown-it-py: '>=1.0.0,<3.0.0'
+    sphinx: '>=4,<6'
+    docutils: '>=0.15,<0.20'
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+  url: https://conda.anaconda.org/conda-forge/noarch/myst-parser-0.18.1-pyhd8ed1ab_0.tar.bz2
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   optional: false
-- name: prompt-toolkit
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   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
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     python: '>=3.7'
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+    markdown-it-py: '>=1.0.0,<3.0.0'
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+  url: https://conda.anaconda.org/conda-forge/noarch/myst-parser-0.18.1-pyhd8ed1ab_0.tar.bz2
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   optional: false
-- name: pybtex-docutils
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   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
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-    pybtex: '>=0.16'
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-  url: https://conda.anaconda.org/conda-forge/osx-64/pybtex-docutils-1.0.3-py312hb401068_1.conda
+    argon2-cffi: ''
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+    jupyter_server: '>=1.8'
+    nbconvert: '>=5'
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+    nest-asyncio: '>=1.5'
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+    prometheus_client: ''
+    python: '>=3.7'
+    pyzmq: '>=17'
+    send2trash: '>=1.8.0'
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+    tornado: '>=6.1'
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   hash:
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   category: main
   optional: false
-- name: pyct
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+- name: nbclassic
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   manager: conda
   platform: osx-64
   dependencies:
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-    pyyaml: ''
-    pyct-core: 0.4.6.*
-  url: https://conda.anaconda.org/conda-forge/noarch/pyct-0.4.6-py_0.tar.bz2
+    jinja2: ''
+    nbformat: ''
+    prometheus_client: ''
+    ipykernel: ''
+    ipython_genutils: ''
+    argon2-cffi: ''
+    python: '>=3.7'
+    tornado: '>=6.1'
+    pyzmq: '>=17'
+    terminado: '>=0.8.3'
+    jupyter_client: '>=6.1.1'
+    jupyter_core: '>=4.6.1'
+    nest-asyncio: '>=1.5'
+    traitlets: '>=4.2.1'
+    send2trash: '>=1.8.0'
+    nbconvert: '>=5'
+    jupyter_server: '>=1.8'
+    notebook-shim: '>=0.2.3'
+  url: https://conda.anaconda.org/conda-forge/noarch/nbclassic-1.0.0-pyhb4ecaf3_1.conda
   hash:
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-    sha256: 50af51619db6a35c36e65e8f50c83c722c3358f1f4b5527e87799b8f9935ace0
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+    sha256: fc2b2e606ccbd0aaa2cdecdd33fc39e2c4bd7b5b96a64b89b3e6ad9ce20eec2f
   category: main
   optional: false
-- name: pyworms
-  version: 0.4.0
+- name: nbclassic
+  version: 1.0.0
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    requests: ''
-    backports.functools_lru_cache: ''
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/pyworms-0.4.0-pyhd8ed1ab_0.conda
+    jinja2: ''
+    nbformat: ''
+    prometheus_client: ''
+    ipykernel: ''
+    ipython_genutils: ''
+    argon2-cffi: ''
+    python: '>=3.7'
+    tornado: '>=6.1'
+    pyzmq: '>=17'
+    terminado: '>=0.8.3'
+    jupyter_client: '>=6.1.1'
+    jupyter_core: '>=4.6.1'
+    nest-asyncio: '>=1.5'
+    traitlets: '>=4.2.1'
+    send2trash: '>=1.8.0'
+    nbconvert: '>=5'
+    jupyter_server: '>=1.8'
+    notebook-shim: '>=0.2.3'
+  url: https://conda.anaconda.org/conda-forge/noarch/nbclassic-1.0.0-pyhb4ecaf3_1.conda
   hash:
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+    sha256: fc2b2e606ccbd0aaa2cdecdd33fc39e2c4bd7b5b96a64b89b3e6ad9ce20eec2f
   category: main
   optional: false
-- name: send2trash
-  version: 1.8.2
+- name: nbclassic
+  version: 1.0.0
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    __osx: ''
-    pyobjc-framework-cocoa: ''
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/send2trash-1.8.2-pyhd1c38e8_0.conda
+    jinja2: ''
+    nbformat: ''
+    prometheus_client: ''
+    ipykernel: ''
+    ipython_genutils: ''
+    argon2-cffi: ''
+    python: '>=3.7'
+    tornado: '>=6.1'
+    pyzmq: '>=17'
+    terminado: '>=0.8.3'
+    jupyter_client: '>=6.1.1'
+    jupyter_core: '>=4.6.1'
+    nest-asyncio: '>=1.5'
+    traitlets: '>=4.2.1'
+    send2trash: '>=1.8.0'
+    nbconvert: '>=5'
+    jupyter_server: '>=1.8'
+    notebook-shim: '>=0.2.3'
+  url: https://conda.anaconda.org/conda-forge/noarch/nbclassic-1.0.0-pyhb4ecaf3_1.conda
   hash:
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   category: main
   optional: false
-- name: tempest-remap
-  version: 2.2.0
+- name: nbclient
+  version: 0.7.4
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    hdf5: '>=1.14.2,<1.14.3.0a0'
-    libblas: '>=3.9.0,<4.0a0'
-    libcxx: '>=15.0.7'
-    liblapack: '>=3.9.0,<4.0a0'
-    libnetcdf: '>=4.9.2,<4.9.3.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/tempest-remap-2.2.0-h8893032_2.conda
+    jupyter_client: '>=6.1.12'
+    jupyter_core: '>=4.12,!=5.0.*'
+    nbformat: '>=5.1'
+    python: '>=3.7'
+    traitlets: '>=5.3'
+  url: https://conda.anaconda.org/conda-forge/noarch/nbclient-0.7.4-pyhd8ed1ab_0.conda
   hash:
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+    sha256: f26afcbbdd4bd1245db514c6ebc6ef18cc12067145dcab229b6f88653575d44c
   category: main
   optional: false
-- name: trio-websocket
-  version: 0.11.1
+- name: nbclient
+  version: 0.7.4
   manager: conda
   platform: osx-64
   dependencies:
-    exceptiongroup: ''
     python: '>=3.7'
-    trio: '>=0.11'
-    wsproto: '>=0.14'
-  url: https://conda.anaconda.org/conda-forge/noarch/trio-websocket-0.11.1-pyhd8ed1ab_0.conda
+    jupyter_client: '>=6.1.12'
+    jupyter_core: '>=4.12,!=5.0.*'
+    nbformat: '>=5.1'
+    traitlets: '>=5.3'
+  url: https://conda.anaconda.org/conda-forge/noarch/nbclient-0.7.4-pyhd8ed1ab_0.conda
   hash:
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-    sha256: c6f4453ee5116a584c347c40e60a61fac645ce203c8bea245bb72c3a865b04cf
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+    sha256: f26afcbbdd4bd1245db514c6ebc6ef18cc12067145dcab229b6f88653575d44c
   category: main
   optional: false
-- name: virtualenv
-  version: 20.24.6
+- name: nbclient
+  version: 0.7.4
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    python: '>=3.8'
-    distlib: <1,>=0.3.7
-    filelock: <4,>=3.12.2
-    platformdirs: <4,>=3.9.1
-  url: https://conda.anaconda.org/conda-forge/noarch/virtualenv-20.24.6-pyhd8ed1ab_0.conda
+    python: '>=3.7'
+    jupyter_client: '>=6.1.12'
+    jupyter_core: '>=4.12,!=5.0.*'
+    nbformat: '>=5.1'
+    traitlets: '>=5.3'
+  url: https://conda.anaconda.org/conda-forge/noarch/nbclient-0.7.4-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: cftime
-  version: 1.6.2
+- name: nbclient
+  version: 0.7.4
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    numpy: '>=1.26.0,<2.0a0'
-    python: '>=3.12.0rc3,<3.13.0a0'
-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-64/cftime-1.6.2-py312h5d6a8aa_2.conda
+    python: '>=3.7'
+    jupyter_client: '>=6.1.12'
+    jupyter_core: '>=4.12,!=5.0.*'
+    nbformat: '>=5.1'
+    traitlets: '>=5.3'
+  url: https://conda.anaconda.org/conda-forge/noarch/nbclient-0.7.4-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 1a567c5346e0d94c07d937c0e752d5b0d760198597fbcbdfa3f5da101d072e95
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+    sha256: f26afcbbdd4bd1245db514c6ebc6ef18cc12067145dcab229b6f88653575d44c
   category: main
   optional: false
-- name: colorcet
-  version: 3.0.1
+- name: nbconvert
+  version: 7.16.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: '>=2.7'
-    pyct: '>=0.4.4'
-  url: https://conda.anaconda.org/conda-forge/noarch/colorcet-3.0.1-pyhd8ed1ab_0.tar.bz2
+    nbconvert-core: 7.16.0
+    nbconvert-pandoc: 7.16.0
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.16.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 4e68730cc38236a736c8f1c6837c6460807cc0f0a5fd2166b3359d481e6f129f
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+    sha256: b1e9941abc76be0dc2666f86791445a114fafd8e680c668c53e4a93b8bef9ea3
   category: main
   optional: false
-- name: compiler-rt_osx-64
-  version: 16.0.6
+- name: nbconvert
+  version: 7.16.0
   manager: conda
   platform: osx-64
   dependencies:
-    clang: 16.0.6.*
-    clangxx: 16.0.6.*
-  url: https://conda.anaconda.org/conda-forge/noarch/compiler-rt_osx-64-16.0.6-he1888fc_1.conda
+    python: '>=3.8'
+    nbconvert-core: 7.16.0
+    nbconvert-pandoc: 7.16.0
+  url: https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.16.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: aa9cf69307986dbd8ccefdf7dc4362b39956d47193c71e4e11b092cee83ec6d7
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+    sha256: b1e9941abc76be0dc2666f86791445a114fafd8e680c668c53e4a93b8bef9ea3
   category: main
   optional: false
-- name: contourpy
-  version: 1.1.1
+- name: nbconvert
+  version: 7.9.2
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    libcxx: '>=15.0.7'
-    numpy: '>=1.16'
-    python: '>=3.12.0rc3,<3.13.0a0'
-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-64/contourpy-1.1.1-py312h49ebfd2_1.conda
+    python: '>=3.8'
+    nbconvert-core: 7.9.2
+    nbconvert-pandoc: 7.9.2
+  url: https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.9.2-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 37369a6903a1c9c1746ce5272a7a113d099037f7b0a4c0777211638cc8e70b9a
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+    sha256: d7402466864e0b76d26be95235dd68dae5814bd6d25b8d5827e368b9f952961f
   category: main
   optional: false
-- name: esmf
-  version: 8.4.2
+- name: nbconvert
+  version: 7.16.0
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    hdf5: '>=1.14.2,<1.14.3.0a0'
-    libcxx: '>=15.0.7'
-    libgfortran: 5.*
-    libgfortran5: '>=12.3.0'
-    libnetcdf: '>=4.9.2,<4.9.3.0a0'
-    netcdf-fortran: '>=4.6.1,<4.7.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/esmf-8.4.2-nompi_h5ec6942_3.conda
+    python: '>=3.8'
+    nbconvert-core: 7.16.0
+    nbconvert-pandoc: 7.16.0
+  url: https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.16.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 7e8a9aac0a158b29e018186c91174d9e38aad6629cee4c14924cb5a8d52c12d9
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+    sha256: b1e9941abc76be0dc2666f86791445a114fafd8e680c668c53e4a93b8bef9ea3
   category: main
   optional: false
-- name: folium
-  version: 0.14.0
+- name: nbconvert-core
+  version: 7.16.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    numpy: ''
-    requests: ''
-    python: '>=3.6'
-    jinja2: '>=2.9'
-    branca: '>=0.6.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/folium-0.14.0-pyhd8ed1ab_0.conda
+    beautifulsoup4: ''
+    bleach: ''
+    defusedxml: ''
+    entrypoints: '>=0.2.2'
+    jinja2: '>=3.0'
+    jupyter_core: '>=4.7'
+    jupyterlab_pygments: ''
+    markupsafe: '>=2.0'
+    mistune: '>=2.0.3,<4'
+    nbclient: '>=0.5.0'
+    nbformat: '>=5.1'
+    packaging: ''
+    pandocfilters: '>=1.4.1'
+    pygments: '>=2.4.1'
+    python: '>=3.8'
+    tinycss2: ''
+    traitlets: '>=5.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/nbconvert-core-7.16.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 60c51dacc4edb33ba02a7224ddec9d938200f89588eb34b0ccdffc96155795fe
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+    sha256: 8ff53ffc16dd13dc6288ddb4d36f055e782b8f7599d832c20dec182f609d37a5
   category: main
   optional: false
-- name: gdal
-  version: 3.7.2
+- name: nbconvert-core
+  version: 7.16.0
   manager: conda
   platform: osx-64
   dependencies:
-    __osx: '>=10.9'
-    hdf5: '>=1.14.2,<1.14.3.0a0'
-    libcxx: '>=16.0.6'
-    libgdal: 3.7.2
-    libxml2: '>=2.11.5,<2.12.0a0'
-    numpy: '>=1.26.0,<2.0a0'
-    openssl: '>=3.1.3,<4.0a0'
-    python: '>=3.12,<3.13.0a0'
-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-64/gdal-3.7.2-py312hffe8f62_7.conda
+    packaging: ''
+    beautifulsoup4: ''
+    defusedxml: ''
+    bleach: ''
+    tinycss2: ''
+    jupyterlab_pygments: ''
+    python: '>=3.8'
+    jinja2: '>=3.0'
+    entrypoints: '>=0.2.2'
+    jupyter_core: '>=4.7'
+    traitlets: '>=5.0'
+    markupsafe: '>=2.0'
+    pandocfilters: '>=1.4.1'
+    nbformat: '>=5.1'
+    pygments: '>=2.4.1'
+    nbclient: '>=0.5.0'
+    mistune: '>=2.0.3,<4'
+  url: https://conda.anaconda.org/conda-forge/noarch/nbconvert-core-7.16.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 1ff718e324f203d1befdc88e6ebc94e1b9857962013d8e08ef2e12388e026a65
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+    sha256: 8ff53ffc16dd13dc6288ddb4d36f055e782b8f7599d832c20dec182f609d37a5
   category: main
   optional: false
-- name: geojsonio
-  version: 0.0.3
+- name: nbconvert-core
+  version: 7.9.2
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    python: ''
-    six: ''
-    github3.py: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/geojsonio-0.0.3-py_0.tar.bz2
+    packaging: ''
+    beautifulsoup4: ''
+    defusedxml: ''
+    bleach: ''
+    tinycss2: ''
+    jupyterlab_pygments: ''
+    python: '>=3.8'
+    jinja2: '>=3.0'
+    entrypoints: '>=0.2.2'
+    traitlets: '>=5.0'
+    markupsafe: '>=2.0'
+    pandocfilters: '>=1.4.1'
+    jupyter_core: '>=4.7'
+    nbformat: '>=5.1'
+    pygments: '>=2.4.1'
+    nbclient: '>=0.5.0'
+    mistune: '>=2.0.3,<4'
+  url: https://conda.anaconda.org/conda-forge/noarch/nbconvert-core-7.9.2-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 2f032b8fa1790a3d807d2ee5a47bab90269ff327aaa6a7aa3d1439e9300b134b
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+    sha256: 2c85cf290cffb72b1fe7d24c22ad6bf89873bf0f562c9c51907dfb6c00f2d4dd
   category: main
   optional: false
-- name: gsw
-  version: 3.6.17
+- name: nbconvert-core
+  version: 7.16.0
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    numpy: '>=1.26.0,<2.0a0'
-    python: '>=3.12,<3.13.0a0'
-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-64/gsw-3.6.17-py312h3f2338b_1.conda
+    packaging: ''
+    beautifulsoup4: ''
+    defusedxml: ''
+    bleach: ''
+    tinycss2: ''
+    jupyterlab_pygments: ''
+    python: '>=3.8'
+    jinja2: '>=3.0'
+    entrypoints: '>=0.2.2'
+    jupyter_core: '>=4.7'
+    traitlets: '>=5.0'
+    markupsafe: '>=2.0'
+    pandocfilters: '>=1.4.1'
+    nbformat: '>=5.1'
+    pygments: '>=2.4.1'
+    nbclient: '>=0.5.0'
+    mistune: '>=2.0.3,<4'
+  url: https://conda.anaconda.org/conda-forge/noarch/nbconvert-core-7.16.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 1c469a934febc944754ca42330c6a7786b1d2dbc4435dc3f12f5b7e84db834d4
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+    sha256: 8ff53ffc16dd13dc6288ddb4d36f055e782b8f7599d832c20dec182f609d37a5
   category: main
   optional: false
-- name: jsonschema-with-format-nongpl
-  version: 4.19.1
+- name: nbconvert-pandoc
+  version: 7.16.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: ''
-    idna: ''
-    rfc3339-validator: ''
-    uri-template: ''
-    fqdn: ''
-    isoduration: ''
-    jsonpointer: '>1.13'
-    webcolors: '>=1.11'
-    rfc3986-validator: '>0.1.0'
-    jsonschema: '>=4.19.1,<4.19.2.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-with-format-nongpl-4.19.1-pyhd8ed1ab_0.conda
+    nbconvert-core: 7.16.0
+    pandoc: ''
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.16.0-pyhd8ed1ab_0.conda
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-- name: compiler-rt
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+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/nc-time-axis-1.4.1-pyhd8ed1ab_0.tar.bz2
   hash:
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-    sha256: d0b11dbbe52a6257d87b0d98eb3a320e564f95900fe3c6615aec9dfa36d77217
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   category: main
   optional: false
-- name: geopandas-base
-  version: 0.14.0
+- name: nc-time-axis
+  version: 1.4.1
   manager: conda
   platform: osx-64
   dependencies:
-    packaging: ''
-    python: '>=3.9'
-    pandas: '>=1.4.0'
-    shapely: '>=1.8.0'
-    pyproj: '>=3.3.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/geopandas-base-0.14.0-pyha770c72_1.conda
+    numpy: ''
+    matplotlib-base: ''
+    python: '>=3.7'
+    cftime: '>=1.5'
+  url: https://conda.anaconda.org/conda-forge/noarch/nc-time-axis-1.4.1-pyhd8ed1ab_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: ipython
-  version: 8.16.1
+- name: nc-time-axis
+  version: 1.4.1
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    typing_extensions: ''
-    decorator: ''
-    exceptiongroup: ''
-    __osx: ''
-    stack_data: ''
-    matplotlib-inline: ''
-    backcall: ''
-    appnope: ''
-    pickleshare: ''
-    python: '>=3.9'
-    pygments: '>=2.4.0'
-    traitlets: '>=5'
-    jedi: '>=0.16'
-    pexpect: '>4.3'
-    prompt_toolkit: '>=3.0.30,<3.1.0,!=3.0.37'
-  url: https://conda.anaconda.org/conda-forge/noarch/ipython-8.16.1-pyh31c8845_0.conda
+    numpy: ''
+    matplotlib-base: ''
+    python: '>=3.7'
+    cftime: '>=1.5'
+  url: https://conda.anaconda.org/conda-forge/noarch/nc-time-axis-1.4.1-pyhd8ed1ab_0.tar.bz2
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   category: main
   optional: false
-- name: jupyter_events
-  version: 0.8.0
+- name: nc-time-axis
+  version: 1.4.1
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    rfc3339-validator: ''
-    referencing: ''
-    python: '>=3.8'
-    pyyaml: '>=5.3'
-    rfc3986-validator: '>=0.1.1'
-    traitlets: '>=5.3'
-    python-json-logger: '>=2.0.4'
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-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_events-0.8.0-pyhd8ed1ab_0.conda
+    numpy: ''
+    matplotlib-base: ''
+    python: '>=3.7'
+    cftime: '>=1.5'
+  url: https://conda.anaconda.org/conda-forge/noarch/nc-time-axis-1.4.1-pyhd8ed1ab_0.tar.bz2
   hash:
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-    sha256: 44742f7b6453774fbbdf7cec20282f88c7362707990790116fec23270b81b447
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+    sha256: 345d51b39f603a6717e43a998adaac35764467a4cf2bfec8f1963b9a7ced2a36
   category: main
   optional: false
-- name: matplotlib-base
-  version: 3.8.0
+- name: nco
+  version: 5.2.1
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    __osx: '>=10.9'
-    certifi: '>=2020.06.20'
-    contourpy: '>=1.0.1'
-    cycler: '>=0.10'
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-    pillow: '>=6.2.0'
-    pyparsing: '>=2.3.1'
-    python: '>=3.12,<3.13.0a0'
-    python-dateutil: '>=2.7'
-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-64/matplotlib-base-3.8.0-py312h1fe5000_2.conda
+    _openmp_mutex: '>=4.5'
+    esmf: ''
+    gsl: '>=2.7,<2.8.0a0'
+    hdf5: '>=1.14.3,<1.14.4.0a0'
+    krb5: '>=1.21.2,<1.22.0a0'
+    libblas: '>=3.9.0,<4.0a0'
+    libcblas: '>=3.9.0,<4.0a0'
+    libexpat: '>=2.5.0,<3.0a0'
+    libgcc-ng: '>=12'
+    libnetcdf: '>=4.9.2,<4.9.3.0a0'
+    libstdcxx-ng: '>=12'
+    libudunits2: '>=2.2.28,<3.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    tempest-remap: '!=2.1.2,!=2.1.3'
+  url: https://conda.anaconda.org/conda-forge/linux-64/nco-5.2.1-he646072_0.conda
   hash:
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-    sha256: 4e66d0404e1e99243c99ef9aff09f1a0df75c57a0a28a1eb2712a4e11382f24f
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+    sha256: 1b6117489ce08ca488aabd3063c525bef7b316bb4fdd8ee825216b94ccdeaed5
   category: main
   optional: false
-- name: nbclient
-  version: 0.7.4
+- name: nco
+  version: 5.2.1
   manager: conda
   platform: osx-64
   dependencies:
-    python: '>=3.7'
-    jupyter_client: '>=6.1.12'
-    jupyter_core: '>=4.12,!=5.0.*'
-    nbformat: '>=5.1'
-    traitlets: '>=5.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/nbclient-0.7.4-pyhd8ed1ab_0.conda
+    esmf: ''
+    gsl: '>=2.7,<2.8.0a0'
+    hdf5: '>=1.14.3,<1.14.4.0a0'
+    krb5: '>=1.21.2,<1.22.0a0'
+    libblas: '>=3.9.0,<4.0a0'
+    libcblas: '>=3.9.0,<4.0a0'
+    libcxx: '>=16'
+    libexpat: '>=2.5.0,<3.0a0'
+    libnetcdf: '>=4.9.2,<4.9.3.0a0'
+    libudunits2: '>=2.2.28,<3.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    llvm-openmp: '>=16.0.6'
+    tempest-remap: '!=2.1.2,!=2.1.3'
+  url: https://conda.anaconda.org/conda-forge/osx-64/nco-5.2.1-hfcf1594_0.conda
   hash:
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-    sha256: f26afcbbdd4bd1245db514c6ebc6ef18cc12067145dcab229b6f88653575d44c
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   category: main
   optional: false
 - name: nco
   version: 5.1.8
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
     __osx: '>=10.9'
     esmf: ''
@@ -15796,4381 +16202,3894 @@ package:
     libzlib: '>=1.2.13,<1.3.0a0'
     llvm-openmp: '>=16.0.6'
     tempest-remap: '!=2.1.2,!=2.1.3'
-  url: https://conda.anaconda.org/conda-forge/osx-64/nco-5.1.8-h36ae7ab_1.conda
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/nco-5.1.8-h91bca93_1.conda
   hash:
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-    sha256: b4372e41f13e16c42b9eef33fafedef50ea0eafc036ff04865105b64cdd45994
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   category: main
   optional: false
-- name: netcdf4
-  version: 1.6.5
+- name: nco
+  version: 5.2.1
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    certifi: ''
-    cftime: ''
-    hdf5: '>=1.14.2,<1.14.3.0a0'
+    gsl: '>=2.7,<2.8.0a0'
+    hdf5: '>=1.14.3,<1.14.4.0a0'
+    libblas: '>=3.9.0,<4.0a0'
+    libcblas: '>=3.9.0,<4.0a0'
+    libexpat: '>=2.5.0,<3.0a0'
     libnetcdf: '>=4.9.2,<4.9.3.0a0'
+    libudunits2: '>=2.2.28,<3.0a0'
     libzlib: '>=1.2.13,<1.3.0a0'
-    numpy: '>=1.26.0,<2.0a0'
-    python: '>=3.12,<3.13.0a0'
-    python_abi: 3.12.*
-    setuptools: ''
-  url: https://conda.anaconda.org/conda-forge/osx-64/netcdf4-1.6.5-nompi_py312hd4beaa4_100.conda
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/nco-5.2.1-h871a938_0.conda
   hash:
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-    sha256: a1bd1a258d1cce8200c63898339e0dd162df4e97ff7df779e76d8d226fde219a
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+    sha256: 20ce8f973c107d4f80b566e256e18d3079633f1aaf71f63742ff501746bd557c
   category: main
   optional: false
-- name: patsy
-  version: 0.5.3
+- name: ncurses
+  version: '6.4'
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    scipy: ''
-    six: ''
-    python: '>=3.6'
-    numpy: '>=1.4.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/patsy-0.5.3-pyhd8ed1ab_0.tar.bz2
+    libgcc-ng: '>=12'
+  url: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.4-h59595ed_2.conda
   hash:
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-    sha256: 9d232f9cda05ce1833a7e5b16db4486ddfb71318635047fb64de119d364e0259
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+    sha256: 91cc03f14caf96243cead96c76fe91ab5925a695d892e83285461fb927dece5e
   category: main
   optional: false
-- name: pyobis
-  version: 1.3.1
+- name: ncurses
+  version: '6.4'
   manager: conda
   platform: osx-64
   dependencies:
-    pandas: ''
-    python: '>=3.7'
-    requests: '>2.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/pyobis-1.3.1-pyhd8ed1ab_0.conda
+    __osx: '>=10.9'
+  url: https://conda.anaconda.org/conda-forge/osx-64/ncurses-6.4-h93d8f39_2.conda
   hash:
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-    sha256: 3b494cb0f7cc6b4bb177d4141ff3810f6bf069701592191fb3fd5add77503dfe
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+    sha256: ea0fca66bbb52a1ef0687d466518fe120b5f279684effd6fd336a7b0dddc423a
   category: main
   optional: false
-- name: pyresample
-  version: 1.27.1
+- name: ncurses
+  version: '6.4'
   manager: conda
-  platform: osx-64
-  dependencies:
-    __osx: '>=10.9'
-    configobj: ''
-    importlib-metadata: ''
-    libcxx: '>=16.0.6'
-    numpy: '>=1.26.0,<2.0a0'
-    pykdtree: '>=1.3.1'
-    pyproj: '>=3.0'
-    python: '>=3.12,<3.13.0a0'
-    python_abi: 3.12.*
-    pyyaml: ''
-    setuptools: '>=3.2'
-    shapely: ''
-  url: https://conda.anaconda.org/conda-forge/osx-64/pyresample-1.27.1-py312haf8ecfc_2.conda
+  platform: osx-arm64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/ncurses-6.4-h7ea286d_0.conda
   hash:
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-    sha256: bb91f7073380974ed5b446e087fcf117b9f36eff5b595d223b53c0d9bfdc2e27
+    md5: 318337fb9d0c53ba635efb7888242373
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   category: main
   optional: false
-- name: rasterio
-  version: 1.3.9
+- name: nest-asyncio
+  version: 1.6.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    affine: ''
-    attrs: ''
-    certifi: ''
-    click: '>=4'
-    click-plugins: ''
-    cligj: '>=0.5'
-    libgdal: '>=3.7.2,<3.8.0a0'
-    numpy: '>=1.26.0,<2.0a0'
-    proj: '>=9.3.0,<9.3.1.0a0'
-    python: '>=3.12,<3.13.0a0'
-    python_abi: 3.12.*
-    setuptools: '>=0.9.8'
-    snuggs: '>=1.4.1'
-  url: https://conda.anaconda.org/conda-forge/osx-64/rasterio-1.3.9-py312h6d3d842_0.conda
+    python: '>=3.5'
+  url: https://conda.anaconda.org/conda-forge/noarch/nest-asyncio-1.6.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: f4705722ff2505ba4d538b90d5c3df62f3cf02409bfbfa603178948acb8fbccf
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+    sha256: 30db21d1f7e59b3408b831a7e0417b83b53ee6223afae56482c5f26da3ceb49a
   category: main
   optional: false
-- name: scikit-learn
-  version: 1.3.2
+- name: nest-asyncio
+  version: 1.6.0
   manager: conda
   platform: osx-64
   dependencies:
-    __osx: '>=10.9'
-    joblib: '>=1.1.1'
-    libcxx: '>=16.0.6'
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-    numpy: '>=1.26.0,<2.0a0'
-    python: '>=3.12,<3.13.0a0'
-    python_abi: 3.12.*
-    scipy: ''
-    threadpoolctl: '>=2.0.0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/scikit-learn-1.3.2-py312h5e37b4f_1.conda
+    python: '>=3.5'
+  url: https://conda.anaconda.org/conda-forge/noarch/nest-asyncio-1.6.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 529f7f0d93ea23b378f7e3732ae3488a428ea0fbb49452a88ab791eb30559f9e
+    md5: 6598c056f64dc8800d40add25e4e2c34
+    sha256: 30db21d1f7e59b3408b831a7e0417b83b53ee6223afae56482c5f26da3ceb49a
   category: main
   optional: false
-- name: utide
-  version: 0.3.0
+- name: nest-asyncio
+  version: 1.5.8
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    numpy: ''
-    scipy: ''
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/utide-0.3.0-pyhd8ed1ab_0.tar.bz2
+    python: '>=3.5'
+  url: https://conda.anaconda.org/conda-forge/noarch/nest-asyncio-1.5.8-pyhd8ed1ab_0.conda
   hash:
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-    sha256: fc35c7b890c7521fc780a7e4a4121d2f704d9a11ce18ac4eadff85fd232a0ec2
+    md5: a4f0e4519bc50eee4f53f689be9607f7
+    sha256: d7b795b4e754136841c6da3f9fa1a0f7ec37bc7167e7dd68c5b45e657133e008
   category: main
   optional: false
-- name: xarray
-  version: 2023.10.1
+- name: nest-asyncio
+  version: 1.6.0
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    python: '>=3.9'
-    packaging: '>=21.3'
-    pandas: '>=1.4'
-    numpy: '>=1.22'
-  url: https://conda.anaconda.org/conda-forge/noarch/xarray-2023.10.1-pyhd8ed1ab_0.conda
+    python: '>=3.5'
+  url: https://conda.anaconda.org/conda-forge/noarch/nest-asyncio-1.6.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 6062114745e9c01813506527d7e48c75dbe5eb6017e4c60ce8c98ef9fd757db2
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+    sha256: 30db21d1f7e59b3408b831a7e0417b83b53ee6223afae56482c5f26da3ceb49a
   category: main
   optional: false
-- name: zarr
-  version: 2.16.1
+- name: netcdf-fortran
+  version: 4.6.1
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    fasteners: ''
-    asciitree: ''
-    python: '>=3.8'
-    numcodecs: '>=0.10.0'
-    numpy: '>=1.20,!=1.21.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/zarr-2.16.1-pyhd8ed1ab_0.conda
+    hdf5: '>=1.14.2,<1.14.4.0a0'
+    libgcc-ng: '>=12'
+    libgfortran-ng: ''
+    libgfortran5: '>=12.3.0'
+    libnetcdf: '>=4.9.2,<4.9.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/netcdf-fortran-4.6.1-nompi_hacb5139_103.conda
   hash:
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-    sha256: a320989af085d1700ace9d982e6fdb7a63de11331ab7f8bf4cf4f636e3962b65
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+    sha256: c0353e0a03886717679187e20535ddb7834eaa255bb6d65fccd0bb5dab6efd8a
   category: main
   optional: false
-- name: cartopy
-  version: 0.22.0
+- name: netcdf-fortran
+  version: 4.6.1
   manager: conda
   platform: osx-64
   dependencies:
-    __osx: '>=10.9'
-    libcxx: '>=16.0.6'
-    matplotlib-base: '>=3.4'
-    numpy: '>=1.26.0,<2.0a0'
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-    pyproj: '>=3.1.0'
-    pyshp: '>=2.1'
-    python: '>=3.12,<3.13.0a0'
-    python_abi: 3.12.*
-    shapely: '>=1.7'
-  url: https://conda.anaconda.org/conda-forge/osx-64/cartopy-0.22.0-py312haf8ecfc_1.conda
+    hdf5: '>=1.14.2,<1.14.4.0a0'
+    libgfortran: 5.*
+    libgfortran5: '>=13.2.0'
+    libnetcdf: '>=4.9.2,<4.9.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/netcdf-fortran-4.6.1-nompi_h383bc5a_103.conda
   hash:
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-    sha256: 6eb2bf83cfa27d5d1fac1104c9e44d9484780a84d36484ceb03789d064240433
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+    sha256: defbf640a8a6b7d33c3a80e965bf8b336353d569c8ceea97d24fe53d196a5bd8
   category: main
   optional: false
-- name: cf_xarray
-  version: 0.8.4
+- name: netcdf-fortran
+  version: 4.6.1
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    xarray: ''
-    python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/cf_xarray-0.8.4-pyhd8ed1ab_0.conda
+    hdf5: '>=1.14.2,<1.14.3.0a0'
+    libgfortran: 5.*
+    libgfortran5: '>=12.3.0'
+    libnetcdf: '>=4.9.2,<4.9.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/netcdf-fortran-4.6.1-nompi_h9281076_102.conda
   hash:
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-    sha256: 9be2079a3d668a732eba62a50f5ad7622bafb153ac68502126d6d5102405c88c
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+    sha256: d2b7a4c7c4148174af65ab6b35bc537cd58dd0579eff15514c2eca08b7c74f92
   category: main
   optional: false
-- name: clang_impl_osx-64
-  version: 16.0.6
+- name: netcdf4
+  version: 1.6.5
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    cctools_osx-64: ''
-    clang: 16.0.6.*
-    compiler-rt: 16.0.6.*
-    ld64_osx-64: ''
-    llvm-tools: 16.0.6.*
-  url: https://conda.anaconda.org/conda-forge/osx-64/clang_impl_osx-64-16.0.6-h8787910_6.conda
+    certifi: ''
+    cftime: ''
+    hdf5: '>=1.14.2,<1.14.4.0a0'
+    libgcc-ng: '>=12'
+    libnetcdf: '>=4.9.2,<4.9.3.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    numpy: '>=1.26.0,<2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    setuptools: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/netcdf4-1.6.5-nompi_py312h26027e0_100.conda
   hash:
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-    sha256: 88f9c189387ecd4708e58086e62f3264e611d9de14e5254dead824ce131de030
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+    sha256: 9f15fb8f019e56926504ae1176172f8c7cf39d72c80791669d201a0dc8c20b0d
   category: main
   optional: false
-- name: cmcrameri
-  version: '1.7'
+- name: netcdf4
+  version: 1.6.5
   manager: conda
   platform: osx-64
   dependencies:
-    numpy: ''
-    matplotlib-base: ''
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/cmcrameri-1.7-pyhd8ed1ab_0.conda
+    certifi: ''
+    cftime: ''
+    hdf5: '>=1.14.2,<1.14.4.0a0'
+    libnetcdf: '>=4.9.2,<4.9.3.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    numpy: '>=1.26.0,<2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    setuptools: ''
+  url: https://conda.anaconda.org/conda-forge/osx-64/netcdf4-1.6.5-nompi_py312hd4beaa4_100.conda
   hash:
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-    sha256: 393dbade8ac5f8569a32736bf81a4387e3d4ad83cdb7650e7aa3cf32ba9decaa
+    md5: eee4a0a669a2b538fdf6eec373b09886
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   category: main
   optional: false
-- name: compliance-checker
-  version: 5.1.0
+- name: netcdf4
+  version: 1.6.5
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    python: '>=3.7'
-    isodate: '>=0.5.4'
-    validators: '>=0.14.2'
-    shapely: '>=1.7.1'
-    requests: '>=2.2.1'
-    jinja2: '>=2.7.3'
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-    lxml: '>=3.2.1'
-    owslib: '>=0.8.3'
-    pendulum: '>=1.2.4'
-    pygeoif: '>=0.6'
-    cf-units: '>=2'
-    regex: '>=2017.07.28'
-    setuptools: '>=15.0'
-    cftime: '>=1.1.0'
-    pyproj: '>=2.2.1'
-  url: https://conda.anaconda.org/conda-forge/noarch/compliance-checker-5.1.0-pyhd8ed1ab_0.conda
+    certifi: ''
+    cftime: ''
+    hdf5: '>=1.14.2,<1.14.3.0a0'
+    libnetcdf: '>=4.9.2,<4.9.3.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    numpy: '>=1.26.0,<2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    setuptools: ''
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/netcdf4-1.6.5-nompi_py312h9035142_100.conda
   hash:
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-    sha256: b91a12b72b1a78b072ca970bf5a651a86da561caa1c28bfebb3e3e13af137576
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   category: main
   optional: false
-- name: contextily
-  version: 1.4.0
+- name: netcdf4
+  version: 1.6.5
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    requests: ''
-    matplotlib-base: ''
-    pillow: ''
-    joblib: ''
-    rasterio: ''
-    xyzservices: ''
-    geopy: ''
-    mercantile: ''
-    python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/contextily-1.4.0-pyhd8ed1ab_0.conda
+    certifi: ''
+    cftime: ''
+    hdf5: '>=1.14.2,<1.14.4.0a0'
+    libnetcdf: '>=4.9.2,<4.9.3.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    numpy: '>=1.26.0,<2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    setuptools: ''
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/netcdf4-1.6.5-nompi_py312he4da9c3_100.conda
   hash:
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-    sha256: aa467b146557712f44930eb9e73272e3bf5ad1c7dabb5b7d34ef4872ca017351
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+    sha256: 97ee6744cc4f92b8bb3b290e619c7c457804e6da6b494b5853afd0b6af8865e2
   category: main
   optional: false
-- name: descartes
-  version: 1.1.0
+- name: networkx
+  version: 3.2.1
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: ''
-    matplotlib-base: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/descartes-1.1.0-py_4.tar.bz2
+    python: '>=3.9'
+  url: https://conda.anaconda.org/conda-forge/noarch/networkx-3.2.1-pyhd8ed1ab_0.conda
   hash:
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-    sha256: b0b73c09a69e775f50541861622ea54e8342ae7c4b0ca7713967acb902263c74
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+    sha256: 7629aa4f9f8cdff45ea7a4701fe58dccce5bf2faa01c26eb44cbb27b7e15ca9d
   category: main
   optional: false
-- name: gridgeo
-  version: 1.5.2
+- name: networkx
+  version: 3.2.1
   manager: conda
   platform: osx-64
   dependencies:
-    shapely: ''
-    netcdf4: ''
-    docopt: ''
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/gridgeo-1.5.2-py_0.tar.bz2
+    python: '>=3.9'
+  url: https://conda.anaconda.org/conda-forge/noarch/networkx-3.2.1-pyhd8ed1ab_0.conda
   hash:
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+    sha256: 7629aa4f9f8cdff45ea7a4701fe58dccce5bf2faa01c26eb44cbb27b7e15ca9d
   category: main
   optional: false
-- name: ioos_qc
-  version: 1.0.0
+- name: networkx
+  version: 3.2.1
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    python: ''
-    xarray: ''
-    netcdf4: ''
-    ruamel.yaml: ''
-    geojson: ''
-    simplejson: ''
-    pygc: ''
-    numpy: '>=1.14'
-  url: https://conda.anaconda.org/conda-forge/noarch/ioos_qc-1.0.0-pyh9f0ad1d_0.tar.bz2
+    python: '>=3.9'
+  url: https://conda.anaconda.org/conda-forge/noarch/networkx-3.2.1-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 0a48f0052a28961c3606aacc33c20d30ef87d88a0246d03e1dcc6b77be192045
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+    sha256: 7629aa4f9f8cdff45ea7a4701fe58dccce5bf2faa01c26eb44cbb27b7e15ca9d
   category: main
   optional: false
-- name: ipykernel
-  version: 6.26.0
+- name: networkx
+  version: 3.2.1
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    packaging: ''
-    psutil: ''
-    nest-asyncio: ''
-    __osx: ''
-    appnope: ''
-    python: '>=3.8'
-    tornado: '>=6.1'
-    jupyter_client: '>=6.1.12'
-    ipython: '>=7.23.1'
-    matplotlib-inline: '>=0.1'
-    jupyter_core: '>=4.12,!=5.0.*'
-    debugpy: '>=1.6.5'
-    comm: '>=0.1.1'
-    pyzmq: '>=20'
-    traitlets: '>=5.4.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/ipykernel-6.26.0-pyh3cd1d5f_0.conda
+    python: '>=3.9'
+  url: https://conda.anaconda.org/conda-forge/noarch/networkx-3.2.1-pyhd8ed1ab_0.conda
   hash:
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-    sha256: be9927d47fe23cc4d2a09d252e37e1e56ffb137767d2c0577ed882ead16f75fa
+    md5: 425fce3b531bed6ec3c74fab3e5f0a1c
+    sha256: 7629aa4f9f8cdff45ea7a4701fe58dccce5bf2faa01c26eb44cbb27b7e15ca9d
   category: main
   optional: false
-- name: ipywidgets
-  version: 8.1.1
+- name: nodeenv
+  version: 1.8.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: '>=3.7'
-    traitlets: '>=4.3.1'
-    ipython: '>=6.1.0'
-    comm: '>=0.1.3'
-    jupyterlab_widgets: '>=3.0.9,<3.1.0'
-    widgetsnbextension: '>=4.0.9,<4.1.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/ipywidgets-8.1.1-pyhd8ed1ab_0.conda
+    python: 2.7|>=3.7
+    setuptools: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/nodeenv-1.8.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 8136defec115396ba992273a77f814d74eeafd9cc099f5430d109c60785a7f02
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+    sha256: 1320306234552717149f36f825ddc7e27ea295f24829e9db4cc6ceaff0b032bd
   category: main
   optional: false
-- name: jupyter-cache
-  version: 0.6.1
+- name: nodeenv
+  version: 1.8.0
   manager: conda
   platform: osx-64
   dependencies:
-    pyyaml: ''
-    click: ''
-    importlib-metadata: ''
-    tabulate: ''
-    nbformat: ''
-    attrs: ''
-    python: '>=3.8'
-    nbclient: '>=0.2,<0.8'
-    sqlalchemy: '>=1.3.12,<3'
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-cache-0.6.1-pyhd8ed1ab_0.conda
+    setuptools: ''
+    python: 2.7|>=3.7
+  url: https://conda.anaconda.org/conda-forge/noarch/nodeenv-1.8.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: b22ba507904f33fcc7b218cc2a3ed8d39027524d0f223f3696b8344b7c5a1e1f
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+    sha256: 1320306234552717149f36f825ddc7e27ea295f24829e9db4cc6ceaff0b032bd
   category: main
   optional: false
-- name: mapclassify
-  version: 2.6.1
+- name: nodeenv
+  version: 1.8.0
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    python: '>=3.9'
-    scikit-learn: '>=1.0'
-    scipy: '>=1.8'
-    numpy: '>=1.23'
-    networkx: '>=2.7'
-    pandas: '>=1.4,!=1.5.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/mapclassify-2.6.1-pyhd8ed1ab_0.conda
+    setuptools: ''
+    python: 2.7|>=3.7
+  url: https://conda.anaconda.org/conda-forge/noarch/nodeenv-1.8.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 204ab8b242229d422b33cfec07ea61cefa8bd22375a16658afbabaafce031d64
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+    sha256: 1320306234552717149f36f825ddc7e27ea295f24829e9db4cc6ceaff0b032bd
   category: main
   optional: false
-- name: nbconvert-core
-  version: 7.9.2
+- name: nodeenv
+  version: 1.8.0
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    packaging: ''
-    beautifulsoup4: ''
-    defusedxml: ''
-    bleach: ''
-    tinycss2: ''
-    jupyterlab_pygments: ''
-    python: '>=3.8'
-    jinja2: '>=3.0'
-    entrypoints: '>=0.2.2'
-    traitlets: '>=5.0'
-    markupsafe: '>=2.0'
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-    jupyter_core: '>=4.7'
-    nbformat: '>=5.1'
-    pygments: '>=2.4.1'
-    nbclient: '>=0.5.0'
-    mistune: '>=2.0.3,<4'
-  url: https://conda.anaconda.org/conda-forge/noarch/nbconvert-core-7.9.2-pyhd8ed1ab_0.conda
+    setuptools: ''
+    python: 2.7|>=3.7
+  url: https://conda.anaconda.org/conda-forge/noarch/nodeenv-1.8.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 2c85cf290cffb72b1fe7d24c22ad6bf89873bf0f562c9c51907dfb6c00f2d4dd
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+    sha256: 1320306234552717149f36f825ddc7e27ea295f24829e9db4cc6ceaff0b032bd
   category: main
   optional: false
-- name: nc-time-axis
-  version: 1.4.1
+- name: notebook
+  version: 7.1.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    numpy: ''
-    matplotlib-base: ''
-    python: '>=3.7'
-    cftime: '>=1.5'
-  url: https://conda.anaconda.org/conda-forge/noarch/nc-time-axis-1.4.1-pyhd8ed1ab_0.tar.bz2
+    jupyter_server: '>=2.4.0,<3'
+    jupyterlab: '>=4.1.1,<4.2.0'
+    jupyterlab_server: '>=2.22.1,<3'
+    notebook-shim: '>=0.2,<0.3'
+    python: '>=3.8'
+    tornado: '>=6.2.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/notebook-7.1.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 345d51b39f603a6717e43a998adaac35764467a4cf2bfec8f1963b9a7ced2a36
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+    sha256: 426ae293064364aeb2a77612ddb7a6bb6ebed60a67a522fef18172ececedddde
   category: main
   optional: false
-- name: odvc
-  version: 1.0.0
+- name: notebook
+  version: 7.1.0
   manager: conda
   platform: osx-64
   dependencies:
-    numpy: ''
-    netcdf4: ''
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/odvc-1.0.0-pyhd8ed1ab_0.tar.bz2
+    python: '>=3.8'
+    tornado: '>=6.2.0'
+    jupyter_server: '>=2.4.0,<3'
+    jupyterlab_server: '>=2.22.1,<3'
+    notebook-shim: '>=0.2,<0.3'
+    jupyterlab: '>=4.1.1,<4.2.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/notebook-7.1.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 6c3e360bfee859423b08a100e7f8ce65dd1b11eff920bb0e112af0ef0ec257cc
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+    sha256: 426ae293064364aeb2a77612ddb7a6bb6ebed60a67a522fef18172ececedddde
   category: main
   optional: false
-- name: paegan
-  version: 1.1.4
+- name: notebook
+  version: 7.0.6
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    python: ''
-    numpy: ''
-    scipy: ''
-    python-dateutil: ''
-    pytz: ''
-    shapely: ''
-    netcdf4: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/paegan-1.1.4-py_1.tar.bz2
+    python: '>=3.8'
+    tornado: '>=6.2.0'
+    jupyter_server: '>=2.4.0,<3'
+    jupyterlab_server: '>=2.22.1,<3'
+    notebook-shim: '>=0.2,<0.3'
+    jupyterlab: '>=4.0.7,<5'
+  url: https://conda.anaconda.org/conda-forge/noarch/notebook-7.0.6-pyhd8ed1ab_0.conda
   hash:
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-    sha256: bc3f17c0b310c828b4b36af5b253280fb27cb0e8d14b3776fc9fe13794b54dda
+    md5: d60881c78a54cbf8042ae719f1f77a50
+    sha256: 5259ad2fb47300407dafa6ea5e78085a2c8de8dcdbfbaa58592bf2677d7187a9
   category: main
   optional: false
-- name: pandas-flavor
-  version: 0.2.0
+- name: notebook
+  version: 7.1.0
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    python: ''
-    pandas: ''
-    xarray: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/pandas-flavor-0.2.0-py_0.tar.bz2
+    python: '>=3.8'
+    tornado: '>=6.2.0'
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+    notebook-shim: '>=0.2,<0.3'
+    jupyterlab: '>=4.1.1,<4.2.0'
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-- name: panel
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+  version: 0.2.4
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    requests: ''
-    typing_extensions: ''
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-    markdown: ''
-    bleach: ''
-    mdit-py-plugins: ''
-    markdown-it-py: ''
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-    param: '>=2.0.0,<3'
-  url: https://conda.anaconda.org/conda-forge/noarch/panel-1.3.0-pyhd8ed1ab_0.conda
+    jupyter_server: '>=1.8,<3'
+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/notebook-shim-0.2.4-pyhd8ed1ab_0.conda
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-- name: pocean-core
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+- name: notebook-shim
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   manager: conda
   platform: osx-64
   dependencies:
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-    pytz: ''
-    netcdf4: ''
-    simplejson: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/pocean-core-3.1.0-pyhd8ed1ab_0.conda
+    python: '>=3.7'
+    jupyter_server: '>=1.8,<3'
+  url: https://conda.anaconda.org/conda-forge/noarch/notebook-shim-0.2.4-pyhd8ed1ab_0.conda
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-- name: pysgrid
-  version: 0.3.5
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+  version: 0.2.3
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
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-    numpy: ''
-    netcdf4: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/pysgrid-0.3.5-py_0.tar.bz2
+    python: '>=3.7'
+    jupyter_server: '>=1.8,<3'
+  url: https://conda.anaconda.org/conda-forge/noarch/notebook-shim-0.2.3-pyhd8ed1ab_0.conda
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-- name: pyugrid
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+- name: notebook-shim
+  version: 0.2.4
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    python: ''
-    numpy: ''
-    netcdf4: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/pyugrid-0.3.1-py_2.tar.bz2
+    python: '>=3.7'
+    jupyter_server: '>=1.8,<3'
+  url: https://conda.anaconda.org/conda-forge/noarch/notebook-shim-0.2.4-pyhd8ed1ab_0.conda
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-- name: seaborn-base
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+- name: nspr
+  version: '4.35'
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: '>=3.8'
-    pandas: '>=1.2'
-    scipy: '>=1.3'
-    matplotlib-base: '>=3.3,!=3.6.1'
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-  url: https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.13.0-pyhd8ed1ab_0.conda
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+  url: https://conda.anaconda.org/conda-forge/linux-64/nspr-4.35-h27087fc_0.conda
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   category: main
   optional: false
-- name: siphon
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+- name: nspr
+  version: '4.35'
   manager: conda
   platform: osx-64
   dependencies:
-    pandas: ''
-    netcdf4: ''
-    python: '>=3.6'
-    numpy: '>=1.8'
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-    protobuf: '>=3.0.0a3'
-    beautifulsoup4: '>=4.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/siphon-0.9-pyhd8ed1ab_2.tar.bz2
+    libcxx: '>=14.0.6'
+  url: https://conda.anaconda.org/conda-forge/osx-64/nspr-4.35-hea0b92c_0.conda
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   optional: false
-- name: statsmodels
-  version: 0.14.0
+- name: nspr
+  version: '4.35'
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
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-    pandas: '>=1.0'
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-  url: https://conda.anaconda.org/conda-forge/osx-64/statsmodels-0.14.0-py312h3f2338b_2.conda
+    libcxx: '>=14.0.6'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/nspr-4.35-hb7217d7_0.conda
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   optional: false
-- name: thredds_crawler
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+- name: nss
+  version: '3.98'
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: ''
-    requests: ''
-    lxml: ''
-    pytz: ''
-    netcdf4: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/thredds_crawler-1.5.4-py_1.tar.bz2
+    __glibc: '>=2.17,<3.0.a0'
+    libgcc-ng: '>=12'
+    libsqlite: '>=3.45.1,<4.0a0'
+    libstdcxx-ng: '>=12'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    nspr: '>=4.35,<5.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/nss-3.98-h1d7d5a4_0.conda
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   category: main
   optional: false
-- name: windrose
-  version: 1.9.0
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   manager: conda
   platform: osx-64
   dependencies:
-    python: '>=3.6'
-    numpy: '>=1.21'
-    matplotlib-base: '>=3'
-  url: https://conda.anaconda.org/conda-forge/noarch/windrose-1.9.0-pyhd8ed1ab_0.conda
+    libcxx: '>=16'
+    libsqlite: '>=3.45.1,<4.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    nspr: '>=4.35,<5.0a0'
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   category: main
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-- name: cc-plugin-glider
-  version: 2.0.3
+- name: nss
+  version: '3.94'
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    python: ''
-    compliance-checker: '>=4.3.2'
-  url: https://conda.anaconda.org/conda-forge/noarch/cc-plugin-glider-2.0.3-pyh9f0ad1d_0.tar.bz2
+    libcxx: '>=15.0.7'
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+    libzlib: '>=1.2.13,<1.3.0a0'
+    nspr: '>=4.35,<5.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/nss-3.94-hc6b9969_0.conda
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-- name: cc-plugin-ncei
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+- name: numba
+  version: 0.59.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: ''
-    six: '>=1.10.0'
-    isodate: '>=0.5.4'
-    compliance-checker: '>=2.2.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/cc-plugin-ncei-2.0.2-py_3.tar.bz2
+    _openmp_mutex: '>=4.5'
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    llvmlite: '>=0.42.0,<0.43.0a0'
+    numpy: '>=1.26.3,<2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/linux-64/numba-0.59.0-py312hacefee8_1.conda
   hash:
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   category: main
   optional: false
-- name: clang_osx-64
-  version: 16.0.6
+- name: numba
+  version: 0.59.0
   manager: conda
   platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-64/clang_osx-64-16.0.6-hb91bd55_6.conda
+    libcxx: '>=16'
+    llvm-openmp: '>=17.0.6'
+    llvmlite: '>=0.42.0,<0.43.0a0'
+    numpy: '>=1.26.3,<2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/osx-64/numba-0.59.0-py312h04e34b5_1.conda
   hash:
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   category: main
   optional: false
-- name: ctd
-  version: 1.4.4
+- name: numba
+  version: 0.59.0
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    numpy: ''
-    scipy: ''
-    matplotlib-base: ''
-    chardet: ''
-    python: '>=3.6'
-    pandas: '>=0.24.0'
-    pandas-flavor: '>=0.1.2'
-    gsw: '>=3.3.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/ctd-1.4.4-pyhd8ed1ab_0.conda
+    llvmlite: '>=0.42.0,<0.43.0a0'
+    numpy: '>=1.26.3,<2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/numba-0.59.0-py312h115d327_1.conda
   hash:
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   category: main
   optional: false
-- name: geopandas
-  version: 0.14.0
+- name: numcodecs
+  version: 0.12.1
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    matplotlib-base: ''
-    rtree: ''
-    folium: ''
-    xyzservices: ''
-    python: '>=3.9'
-    mapclassify: '>=2.4.0'
-    fiona: '>=1.8.21'
-    geopandas-base: 0.14.0
-  url: https://conda.anaconda.org/conda-forge/noarch/geopandas-0.14.0-pyhd8ed1ab_1.conda
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    msgpack-python: ''
+    numpy: '>=1.7'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/linux-64/numcodecs-0.12.1-py312h30efb56_0.conda
   hash:
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   category: main
   optional: false
-- name: holoviews
-  version: 1.18.0
+- name: numcodecs
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   manager: conda
   platform: osx-64
   dependencies:
-    packaging: ''
-    colorcet: ''
-    python: '>=3.9'
-    matplotlib-base: '>=3.0'
-    numpy: '>=1.0'
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-    pandas: '>=0.20.0'
-    bokeh: '>=3.1'
-    panel: '>=1.0'
-    param: '>=1.12.0,<3.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/holoviews-1.18.0-pyhd8ed1ab_0.conda
+    __osx: '>=10.9'
+    libcxx: '>=16.0.6'
+    msgpack-python: ''
+    numpy: '>=1.7'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/osx-64/numcodecs-0.12.1-py312h444b7ae_0.conda
   hash:
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   category: main
   optional: false
-- name: ipyleaflet
-  version: 0.17.4
+- name: numcodecs
+  version: 0.12.1
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    python: '>=3.7'
-    traittypes: '>=0.2.1,<0.3.0'
-    ipywidgets: '>=7.6.0,<9'
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-    branca: '>=0.5.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/ipyleaflet-0.17.4-pyhd8ed1ab_0.conda
+    __osx: '>=10.9'
+    libcxx: '>=16.0.6'
+    msgpack-python: ''
+    numpy: '>=1.7'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/numcodecs-0.12.1-py312h650e478_0.conda
   hash:
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   category: main
   optional: false
-- name: ipyparallel
-  version: 8.6.1
+- name: numcodecs
+  version: 0.12.1
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    tqdm: ''
-    psutil: ''
-    decorator: ''
-    jupyter_client: ''
-    entrypoints: ''
-    python: '>=3.6'
-    tornado: '>=5.1'
-    python-dateutil: '>=2.1'
-    ipykernel: '>=4.4'
-    ipython: '>=6'
-    pyzmq: '>=18'
-    traitlets: '>=4.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/ipyparallel-8.6.1-pyhd8ed1ab_0.conda
+    msgpack-python: ''
+    numpy: '>=1.7'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/numcodecs-0.12.1-py312h53d5487_0.conda
   hash:
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-    sha256: ba71fa050152858c5d1a9be8a7be473141604f0077019b6fbd322f0bd6dd9135
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+    sha256: ff7e6666caa980d48f5fd9e667c462073be98d10d1e5842b51b964d71774dfbd
   category: main
   optional: false
-- name: jupyter_console
-  version: 6.6.3
+- name: numpy
+  version: 1.26.4
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    ipython: ''
-    pygments: ''
-    python: '>=3.7'
-    pyzmq: '>=17'
-    jupyter_core: '>=4.12,!=5.0.*'
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-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_console-6.6.3-pyhd8ed1ab_0.conda
+    libblas: '>=3.9.0,<4.0a0'
+    libcblas: '>=3.9.0,<4.0a0'
+    libgcc-ng: '>=12'
+    liblapack: '>=3.9.0,<4.0a0'
+    libstdcxx-ng: '>=12'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/linux-64/numpy-1.26.4-py312heda63a1_0.conda
   hash:
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-    sha256: 4e51764d5fe2f6e43d83bcfbcf8b4da6569721bf82eaf4d647be8717cd6be75a
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   category: main
   optional: false
-- name: jupyter_server
-  version: 2.9.1
+- name: numpy
+  version: 1.26.4
   manager: conda
   platform: osx-64
   dependencies:
-    packaging: ''
-    jinja2: ''
-    prometheus_client: ''
-    websocket-client: ''
-    argon2-cffi: ''
-    overrides: ''
-    jupyter_server_terminals: ''
-    python: '>=3.8'
-    terminado: '>=0.8.3'
-    jupyter_core: '>=4.12,!=5.0.*'
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-    tornado: '>=6.2.0'
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-    pyzmq: '>=24'
-    traitlets: '>=5.6.0'
-    jupyter_events: '>=0.6.0'
-    anyio: '>=3.1.0'
-    send2trash: '>=1.8.2'
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_server-2.9.1-pyhd8ed1ab_0.conda
+    libblas: '>=3.9.0,<4.0a0'
+    libcblas: '>=3.9.0,<4.0a0'
+    libcxx: '>=16'
+    liblapack: '>=3.9.0,<4.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/osx-64/numpy-1.26.4-py312he3a82b2_0.conda
   hash:
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-    sha256: bb9a60ff41085031a28204add4e6120990437cfad341db297519f0a0f0df8e18
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+    sha256: 6152b73fba3e227afa4952df8753128fc9669bbaf142ee8f9972bf9df3bf8856
   category: main
   optional: false
-- name: nbconvert-pandoc
-  version: 7.9.2
+- name: numpy
+  version: 1.26.0
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    pandoc: ''
-    python: '>=3.8'
-    nbconvert-core: 7.9.2
-  url: https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.9.2-pyhd8ed1ab_0.conda
+    libblas: '>=3.9.0,<4.0a0'
+    libcblas: '>=3.9.0,<4.0a0'
+    libcxx: '>=15.0.7'
+    liblapack: '>=3.9.0,<4.0a0'
+    python: '>=3.12.0rc3,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/numpy-1.26.0-py312h696b312_0.conda
   hash:
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-    sha256: 30e0a60a81fa70a10ba4cf1f9a2585f19bfe54c88bb53f0367aaf67a5c56bf37
+    md5: 6281cf23af141e1bc06f6c705e4cc281
+    sha256: 3cdffc4a7775a0159f4e259814dfc86e80590ddd13114468e1abe5b0bcada96a
   category: main
   optional: false
-- name: nbval
-  version: 0.10.0
+- name: numpy
+  version: 1.26.4
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    six: ''
-    pytest: ''
-    nbformat: ''
-    ipykernel: ''
-    jupyter_client: ''
-    coverage: ''
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/nbval-0.10.0-pyhd8ed1ab_0.conda
+    libblas: '>=3.9.0,<4.0a0'
+    libcblas: '>=3.9.0,<4.0a0'
+    liblapack: '>=3.9.0,<4.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/numpy-1.26.4-py312h8753938_0.conda
   hash:
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-    sha256: 791152066934153e33481172530c343244c20b0c91d6b2a3560cd77ff2f02c94
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+    sha256: 73570817a5109d396b4ebbe5124a89525959269fd33fa33fd413700289fbe0ef
   category: main
   optional: false
-- name: pyoos
-  version: 0.8.4
+- name: oceans
+  version: 1.1.3
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: ''
-    numpy: ''
-    requests: ''
-    lxml: ''
-    beautifulsoup4: ''
-    fiona: ''
-    owslib: ''
-    paegan: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/pyoos-0.8.4-py_1.tar.bz2
+    cmcrameri: ''
+    contourpy: ''
+    ctd: ''
+    gsw: ''
+    matplotlib-base: '>=3.6.0'
+    netcdf4: ''
+    numpy: '>=1.20'
+    pandas: '>=1.0.1'
+    python: '>=3.8'
+    scipy: ''
+    seawater: ''
+    shapely: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/oceans-1.1.3-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 8da49879c4de97824398f124cbe22727ecc5b4e9cd1f233cdc47e103510d7f2d
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+    sha256: 4a68d942d1112c0608a41fb8951daa76583a415b98bd478e3633b0cc98ddea42
   category: main
   optional: false
-- name: qtconsole-base
-  version: 5.4.4
+- name: oceans
+  version: 1.1.3
   manager: conda
   platform: osx-64
   dependencies:
-    packaging: ''
-    pygments: ''
-    traitlets: ''
-    jupyter_core: ''
-    ipython_genutils: ''
-    python: '>=3.7'
-    ipykernel: '>=4.1'
-    jupyter_client: '>=4.1'
-    qtpy: '>=2.4.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/qtconsole-base-5.4.4-pyha770c72_0.conda
+    scipy: ''
+    netcdf4: ''
+    shapely: ''
+    gsw: ''
+    seawater: ''
+    ctd: ''
+    cmcrameri: ''
+    contourpy: ''
+    python: '>=3.8'
+    numpy: '>=1.20'
+    pandas: '>=1.0.1'
+    matplotlib-base: '>=3.6.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/oceans-1.1.3-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 86a7705d335558b08219868069293603f4bb225ee5ca02e229dcf5f9b38da7a4
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+    sha256: 4a68d942d1112c0608a41fb8951daa76583a415b98bd478e3633b0cc98ddea42
   category: main
   optional: false
-- name: seaborn
-  version: 0.13.0
+- name: oceans
+  version: 1.1.3
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    statsmodels: '>=0.12'
-    seaborn-base: '>=0.13.0,<0.13.1.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/seaborn-0.13.0-hd8ed1ab_0.conda
+    scipy: ''
+    shapely: ''
+    netcdf4: ''
+    gsw: ''
+    seawater: ''
+    ctd: ''
+    cmcrameri: ''
+    contourpy: ''
+    python: '>=3.8'
+    numpy: '>=1.20'
+    pandas: '>=1.0.1'
+    matplotlib-base: '>=3.6.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/oceans-1.1.3-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 8b6bd68c99fa5f58c4c247daf16a3b28dcef6ffb237c5b382b4750186d9ce54d
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+    sha256: 4a68d942d1112c0608a41fb8951daa76583a415b98bd478e3633b0cc98ddea42
   category: main
   optional: false
-- name: clangxx_impl_osx-64
-  version: 16.0.6
+- name: oceans
+  version: 1.1.3
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    __osx: '>=10.9'
-    clang_osx-64: 16.0.6
-    clangxx: 16.0.6.*
-    libcxx: '>=16.0.6'
-    libllvm16: '>=16.0.6,<16.1.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/clangxx_impl_osx-64-16.0.6-h1b7723c_6.conda
+    scipy: ''
+    netcdf4: ''
+    shapely: ''
+    gsw: ''
+    seawater: ''
+    ctd: ''
+    cmcrameri: ''
+    contourpy: ''
+    python: '>=3.8'
+    numpy: '>=1.20'
+    pandas: '>=1.0.1'
+    matplotlib-base: '>=3.6.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/oceans-1.1.3-pyhd8ed1ab_0.conda
   hash:
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-    sha256: e57434abc85524613d8b2b2d93416b9d2f459c50b86abe3aaecce3a9cb8b7553
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+    sha256: 4a68d942d1112c0608a41fb8951daa76583a415b98bd478e3633b0cc98ddea42
   category: main
   optional: false
-- name: geoplot
-  version: 0.5.1
+- name: oct2py
+  version: 5.6.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    pandas: ''
-    cartopy: ''
-    seaborn-base: ''
-    python: '>=3.7'
-    geopandas: '>=0.9.0'
-    contextily: '>=1.0.0'
-    mapclassify: '>=2.1'
-    matplotlib-base: '>=3.1.2'
-  url: https://conda.anaconda.org/conda-forge/noarch/geoplot-0.5.1-pyhd8ed1ab_0.tar.bz2
+    ipython: ''
+    numpy: ''
+    octave_kernel: '>=0.34.0'
+    python: '>=3.6'
+    scipy: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/oct2py-5.6.0-pyha21a80b_0.conda
   hash:
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-    sha256: dae0c82a86de293a0d6dbb97082f34d6a12fb442005667271a85eba9f9cfc040
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   category: main
   optional: false
-- name: gfortran_osx-64
-  version: 12.3.0
+- name: oct2py
+  version: 5.6.0
   manager: conda
   platform: osx-64
   dependencies:
-    cctools_osx-64: ''
-    clang: ''
-    clang_osx-64: ''
-    gfortran_impl_osx-64: 12.3.0
-    ld64_osx-64: ''
-    libgfortran: 5.*
-    libgfortran-devel_osx-64: 12.3.0
-    libgfortran5: '>=12.3.0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/gfortran_osx-64-12.3.0-h18f7dce_1.conda
+    numpy: ''
+    scipy: ''
+    ipython: ''
+    python: '>=3.6'
+    octave_kernel: '>=0.34.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/oct2py-5.6.0-pyha21a80b_0.conda
   hash:
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-    sha256: 527c03edaa1f1faec95476d5045c67c8b1a792dc2ce80cdd22f3db0f0b8a867d
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+    sha256: 3db5174adf49ebb88829634bd0a0b37fe441e6e73c3369f65497cac35fd5d04d
   category: main
   optional: false
-- name: hvplot
-  version: 0.9.0
+- name: oct2py
+  version: 5.6.0
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    pandas: ''
-    packaging: ''
-    python: '>=3.8'
-    numpy: '>=1.15'
-    bokeh: '>=1.0.0'
-    holoviews: '>=1.11.0'
-    colorcet: '>=2'
-    panel: '>=0.11.0'
-    param: '>=1.9.0,<3.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/hvplot-0.9.0-pyhd8ed1ab_0.conda
+    numpy: ''
+    scipy: ''
+    ipython: ''
+    python: '>=3.6'
+    octave_kernel: '>=0.34.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/oct2py-5.6.0-pyha21a80b_0.conda
   hash:
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   category: main
   optional: false
-- name: jupyter-lsp
-  version: 2.2.0
+- name: oct2py
+  version: 5.6.0
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    python: '>=3.8'
-    importlib-metadata: '>=4.8.3'
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-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-lsp-2.2.0-pyhd8ed1ab_0.conda
+    numpy: ''
+    scipy: ''
+    ipython: ''
+    python: '>=3.6'
+    octave_kernel: '>=0.34.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/oct2py-5.6.0-pyha21a80b_0.conda
   hash:
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-    sha256: 16fc7b40024adece716ba7227e5c123a2deccc13f946a10d9a3270493908d11c
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+    sha256: 3db5174adf49ebb88829634bd0a0b37fe441e6e73c3369f65497cac35fd5d04d
   category: main
   optional: false
-- name: jupyter-server-mathjax
-  version: 0.2.6
-  manager: conda
-  platform: osx-64
-  dependencies:
-    python: '>=3.7'
-    jupyter_server: '>=1.1,<3'
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-server-mathjax-0.2.6-pyh5bfe37b_1.conda
-  hash:
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-  category: main
-  optional: false
-- name: jupyterlab_server
-  version: 2.25.0
+- name: octave_kernel
+  version: 0.35.1
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: '>=3.8'
-    packaging: '>=21.3'
-    jinja2: '>=3.0.3'
-    importlib-metadata: '>=4.8.3'
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-    babel: '>=2.10'
-    json5: '>=0.9.0'
-    requests: '>=2.31'
-    jsonschema: '>=4.18'
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyterlab_server-2.25.0-pyhd8ed1ab_0.conda
+    ipykernel: ''
+    jupyter_client: '>=4.3.0'
+    metakernel: '>=0.24.0'
+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/octave_kernel-0.35.1-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: metakernel
-  version: 0.30.1
+- name: octave_kernel
+  version: 0.35.1
   manager: conda
   platform: osx-64
   dependencies:
-    portalocker: ''
-    ipyparallel: ''
+    ipykernel: ''
     python: '>=3.7'
-    jupyter_core: '>=4.9.2'
-    pexpect: '>=4.8'
-    jedi: '>=0.18'
-    ipykernel: '>5.5.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/metakernel-0.30.1-pyhd8ed1ab_0.conda
+    jupyter_client: '>=4.3.0'
+    metakernel: '>=0.24.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/octave_kernel-0.35.1-pyhd8ed1ab_0.conda
   hash:
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-    sha256: c6eeae97c77e263a3f0dd21293e398e89d40054d5ed77e060a84a6cd90148274
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   category: main
   optional: false
-- name: nbconvert
-  version: 7.9.2
+- name: octave_kernel
+  version: 0.35.1
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    python: '>=3.8'
-    nbconvert-core: 7.9.2
-    nbconvert-pandoc: 7.9.2
-  url: https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.9.2-pyhd8ed1ab_0.conda
+    ipykernel: ''
+    python: '>=3.7'
+    jupyter_client: '>=4.3.0'
+    metakernel: '>=0.24.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/octave_kernel-0.35.1-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: notebook-shim
-  version: 0.2.3
+- name: octave_kernel
+  version: 0.35.1
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
+    ipykernel: ''
     python: '>=3.7'
-    jupyter_server: '>=1.8,<3'
-  url: https://conda.anaconda.org/conda-forge/noarch/notebook-shim-0.2.3-pyhd8ed1ab_0.conda
+    jupyter_client: '>=4.3.0'
+    metakernel: '>=0.24.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/octave_kernel-0.35.1-pyhd8ed1ab_0.conda
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-    sha256: f028d7ad1f2175cde307db08b60d07e371b9d6f035cfae6c81ea94b4c408c538
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   category: main
   optional: false
-- name: oceans
-  version: 1.1.3
+- name: odvc
+  version: 1.0.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    scipy: ''
-    shapely: ''
     netcdf4: ''
-    gsw: ''
-    seawater: ''
-    ctd: ''
-    cmcrameri: ''
-    contourpy: ''
-    python: '>=3.8'
-    numpy: '>=1.20'
-    pandas: '>=1.0.1'
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-  url: https://conda.anaconda.org/conda-forge/noarch/oceans-1.1.3-pyhd8ed1ab_0.conda
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-- name: sensorml2iso
-  version: 1.0.5
-  manager: conda
-  platform: osx-64
-  dependencies:
-    python: ''
     numpy: ''
-    pandas: ''
-    jinja2: ''
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-    shapely: ''
-    geopandas: ''
-    owslib: ''
-    pyoos: '>=0.8.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/sensorml2iso-1.0.5-py_0.tar.bz2
+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/odvc-1.0.0-pyhd8ed1ab_0.tar.bz2
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   category: main
   optional: false
-- name: clangxx_osx-64
-  version: 16.0.6
+- name: odvc
+  version: 1.0.0
   manager: conda
   platform: osx-64
   dependencies:
-    clang_osx-64: 16.0.6
-    clangxx_impl_osx-64: 16.0.6
-  url: https://conda.anaconda.org/conda-forge/osx-64/clangxx_osx-64-16.0.6-h2fff7d5_6.conda
+    numpy: ''
+    netcdf4: ''
+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/odvc-1.0.0-pyhd8ed1ab_0.tar.bz2
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   category: main
   optional: false
-- name: jupyterlab
-  version: 4.0.7
+- name: odvc
+  version: 1.0.0
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    packaging: ''
-    traitlets: ''
-    tomli: ''
-    ipykernel: ''
-    jupyter_core: ''
-    python: '>=3.8'
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-  url: https://conda.anaconda.org/conda-forge/noarch/jupyterlab-4.0.7-pyhd8ed1ab_0.conda
+    numpy: ''
+    netcdf4: ''
+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/odvc-1.0.0-pyhd8ed1ab_0.tar.bz2
   hash:
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-    sha256: 1d841546fd239d7edefbf00edd3bad4680b12c3eb2549026d6aa70a301f23295
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   category: main
   optional: false
-- name: nbclassic
+- name: odvc
   version: 1.0.0
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    jinja2: ''
-    nbformat: ''
-    prometheus_client: ''
-    ipykernel: ''
-    ipython_genutils: ''
-    argon2-cffi: ''
+    numpy: ''
+    netcdf4: ''
     python: '>=3.7'
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-    pyzmq: '>=17'
-    terminado: '>=0.8.3'
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-  url: https://conda.anaconda.org/conda-forge/noarch/nbclassic-1.0.0-pyhb4ecaf3_1.conda
+  url: https://conda.anaconda.org/conda-forge/noarch/odvc-1.0.0-pyhd8ed1ab_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: nbdime
-  version: 3.2.1
+- name: oniguruma
+  version: 6.9.9
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    requests: ''
-    pygments: ''
-    colorama: ''
-    nbformat: ''
-    tornado: ''
-    jupyter_server: ''
-    python: '>=3.6'
-    jinja2: '>=2.9'
-    gitpython: '!=2.1.4,!=2.1.5,!=2.1.6'
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-  url: https://conda.anaconda.org/conda-forge/noarch/nbdime-3.2.1-pyhd8ed1ab_0.conda
+    libgcc-ng: '>=12'
+  url: https://conda.anaconda.org/conda-forge/linux-64/oniguruma-6.9.9-hd590300_0.conda
   hash:
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   category: main
   optional: false
-- name: octave_kernel
-  version: 0.35.1
+- name: oniguruma
+  version: 6.9.9
   manager: conda
   platform: osx-64
-  dependencies:
-    ipykernel: ''
-    python: '>=3.7'
-    jupyter_client: '>=4.3.0'
-    metakernel: '>=0.24.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/octave_kernel-0.35.1-pyhd8ed1ab_0.conda
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-64/oniguruma-6.9.9-h10d778d_0.conda
   hash:
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   category: main
   optional: false
-- name: notebook
-  version: 7.0.6
+- name: openjpeg
+  version: 2.5.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    python: '>=3.8'
-    tornado: '>=6.2.0'
-    jupyter_server: '>=2.4.0,<3'
-    jupyterlab_server: '>=2.22.1,<3'
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-  url: https://conda.anaconda.org/conda-forge/noarch/notebook-7.0.6-pyhd8ed1ab_0.conda
+    libgcc-ng: '>=12'
+    libpng: '>=1.6.39,<1.7.0a0'
+    libstdcxx-ng: '>=12'
+    libtiff: '>=4.6.0,<4.7.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/openjpeg-2.5.0-h488ebb8_3.conda
   hash:
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   category: main
   optional: false
-- name: oct2py
-  version: 5.6.0
+- name: openjpeg
+  version: 2.5.0
   manager: conda
   platform: osx-64
   dependencies:
-    numpy: ''
-    scipy: ''
-    ipython: ''
-    python: '>=3.6'
-    octave_kernel: '>=0.34.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/oct2py-5.6.0-pyha21a80b_0.conda
+    libcxx: '>=15.0.7'
+    libpng: '>=1.6.39,<1.7.0a0'
+    libtiff: '>=4.6.0,<4.7.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/openjpeg-2.5.0-ha4da562_3.conda
   hash:
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   category: main
   optional: false
-- name: r-base
-  version: 4.3.1
+- name: openjpeg
+  version: 2.5.0
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    _r-mutex: 1.*
-    bwidget: ''
-    bzip2: '>=1.0.8,<2.0a0'
-    cairo: '>=1.16.0,<2.0a0'
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-    clangxx_osx-64: '>=15'
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     libtiff: '>=4.6.0,<4.7.0a0'
     libzlib: '>=1.2.13,<1.3.0a0'
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-    readline: '>=8.2,<9.0a0'
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-  url: https://conda.anaconda.org/conda-forge/osx-64/r-base-4.3.1-h0ff45fa_6.conda
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/openjpeg-2.5.0-h4c1507b_3.conda
   hash:
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   category: main
   optional: false
-- name: jupyter
-  version: 1.0.0
+- name: openjpeg
+  version: 2.5.0
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    ipywidgets: ''
-    notebook: ''
-    ipykernel: ''
-    nbconvert: ''
-    jupyter_console: ''
-    qtconsole-base: ''
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-1.0.0-pyhd8ed1ab_10.conda
+    libpng: '>=1.6.39,<1.7.0a0'
+    libtiff: '>=4.6.0,<4.7.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/openjpeg-2.5.0-h3d672ee_3.conda
   hash:
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   category: main
   optional: false
-- name: r-assertthat
-  version: 0.2.1
+- name: openssl
+  version: 3.2.1
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-assertthat-0.2.1-r43hc72bb7e_4.conda
+    ca-certificates: ''
+    libgcc-ng: '>=12'
+  url: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.2.1-hd590300_0.conda
   hash:
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   category: main
   optional: false
-- name: r-base64enc
-  version: '0.1_3'
+- name: openssl
+  version: 3.2.1
   manager: conda
   platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-64/r-base64enc-0.1_3-r43h6dc245f_1006.conda
+    ca-certificates: ''
+  url: https://conda.anaconda.org/conda-forge/osx-64/openssl-3.2.1-hd75f5a5_0.conda
   hash:
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   category: main
   optional: false
-- name: r-bit
-  version: 4.0.5
+- name: openssl
+  version: 3.1.4
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-64/r-bit-4.0.5-r43h6dc245f_1.conda
+    ca-certificates: ''
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/openssl-3.1.4-h0d3ecfb_0.conda
   hash:
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   category: main
   optional: false
-- name: r-brew
-  version: '1.0_8'
+- name: openssl
+  version: 3.2.1
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-brew-1.0_8-r43hc72bb7e_2.conda
+    ca-certificates: ''
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/openssl-3.2.1-hcfcfb64_0.conda
   hash:
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   optional: false
-- name: r-brio
-  version: 1.1.3
+- name: outcome
+  version: 1.3.0.post0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/r-brio-1.1.3-r43h6dc245f_2.conda
+    attrs: '>=19.2.0'
+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/outcome-1.3.0.post0-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: r-cli
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   manager: conda
   platform: osx-64
   dependencies:
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-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/r-cli-3.6.1-r43hac7d2d5_1.conda
+    python: '>=3.7'
+    attrs: '>=19.2.0'
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-- name: r-rprojroot
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   manager: conda
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-- name: r-stringi
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-- name: r-utf8
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-- name: r-uuid
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-- name: r-xfun
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-- name: r-xml
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-- name: r-xtable
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+  platform: win-64
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-- name: r-yaml
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-- name: rpy2
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-- name: r-askpass
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-- name: r-bit64
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-- name: r-cachem
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   manager: conda
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   dependencies:
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-- name: r-class
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-- name: r-colourvalues
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   manager: conda
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   dependencies:
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-- name: r-desc
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   manager: conda
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   manager: conda
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-- name: r-downloader
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-- name: r-ellipsis
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-- name: r-geometries
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+  platform: win-64
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-- name: r-googlepolylines
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   manager: conda
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+  platform: linux-64
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+    python: '>=3.7'
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-- name: r-highr
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-- name: r-hoardr
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+  platform: osx-arm64
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-- name: r-jqr
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   manager: conda
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+  platform: win-64
   dependencies:
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-- name: r-jsonify
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   manager: conda
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+  url: https://conda.anaconda.org/conda-forge/linux-64/phantomjs-2.1.1-ha770c72_1.conda
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-- name: r-lifecycle
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-- name: r-mapdata
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-- name: r-markdown
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   manager: conda
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+  platform: linux-64
   dependencies:
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-    r-mime: '>=0.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-markdown-1.11-r43hc72bb7e_0.conda
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-- name: r-matrix
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   manager: conda
   platform: osx-64
   dependencies:
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+    python: '>=3'
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-- name: r-munsell
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-munsell-0.5.0-r43hc72bb7e_1006.conda
+    python: '>=3'
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-- name: r-nlme
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   manager: conda
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+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-64/r-nlme-3.1_163-r43hfe07776_0.conda
+    python: '>=3'
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-- name: r-plyr
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+- name: pillow
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   manager: conda
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   dependencies:
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+  url: https://conda.anaconda.org/conda-forge/linux-64/pillow-10.2.0-py312hf3581a9_0.conda
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-- name: r-prettyunits
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+- name: pillow
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   manager: conda
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   dependencies:
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+    python: '>=3.12,<3.13.0a0'
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-- name: r-processx
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   manager: conda
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   dependencies:
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-- name: r-systemfonts
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-- name: r-terra
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-- name: r-tinytex
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-- name: r-units
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-- name: r-xml2
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-- name: r-zoo
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-- name: r-callr
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-- name: r-e1071
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-- name: r-geosphere
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-- name: r-gtable
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-- name: r-htmltools
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-- name: r-igraph
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-  url: https://conda.anaconda.org/conda-forge/osx-64/r-igraph-1.5.1-r43hedd5883_0.conda
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/pluggy-1.4.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 19593e72d710b07b27cc2d15f8b6d7add0f0d29465876c7a884916db1b41b037
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+    sha256: 6edfd2c41938ea772096c674809bfcf2ebb9bef7e82de6c7ea0b966b86bfb4d0
   category: main
   optional: false
-- name: r-jsonld
-  version: '2.2'
+- name: pluggy
+  version: 1.4.0
   manager: conda
   platform: osx-64
   dependencies:
-    r-jsonlite: ''
-    r-v8: ''
-    r-base: '>=4.3,<4.4.0a0'
-    r-curl: '>=2.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-jsonld-2.2-r43hc72bb7e_2.conda
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/pluggy-1.4.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 0e6f705c8ddddc409bd83a24310ed7c150f7163961bbe272dda0000062056dd3
+    md5: 139e9feb65187e916162917bb2484976
+    sha256: 6edfd2c41938ea772096c674809bfcf2ebb9bef7e82de6c7ea0b966b86bfb4d0
   category: main
   optional: false
-- name: r-knitr
-  version: '1.44'
+- name: pluggy
+  version: 1.3.0
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    r-highr: ''
-    r-base: '>=4.3,<4.4.0a0'
-    r-yaml: '>=2.1.19'
-    r-evaluate: '>=0.15'
-    r-xfun: '>=0.34'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-knitr-1.44-r43hc72bb7e_0.conda
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/pluggy-1.3.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: fe24a1cfcd5b0f9292910aa3f234d48868e103fe9ed9e586d311ed6d5d287ff8
+    md5: 2390bd10bed1f3fdc7a537fb5a447d8d
+    sha256: 7bf2ad9d747e71f1e93d0863c2c8061dd0f2fe1e582f28d292abfb40264a2eb5
   category: main
   optional: false
-- name: r-lubridate
-  version: 1.9.3
+- name: pluggy
+  version: 1.4.0
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-generics: ''
-    r-timechange: '>=0.1.1'
-  url: https://conda.anaconda.org/conda-forge/osx-64/r-lubridate-1.9.3-r43h6dc245f_0.conda
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/pluggy-1.4.0-pyhd8ed1ab_0.conda
   hash:
-    md5: ca8d466be4a8903ff8143fac3abf11b7
-    sha256: 4e0a36edd55aa2bf3b59738f7a18c990e38bd397e0997a8c0b15ec7d748eb003
+    md5: 139e9feb65187e916162917bb2484976
+    sha256: 6edfd2c41938ea772096c674809bfcf2ebb9bef7e82de6c7ea0b966b86bfb4d0
   category: main
   optional: false
-- name: r-memoise
-  version: 2.0.1
+- name: pocean-core
+  version: 3.1.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    r-cachem: ''
-    r-base: '>=4.3,<4.4.0a0'
-    r-rlang: '>=0.4.10'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-memoise-2.0.1-r43hc72bb7e_2.conda
+    cftime: '>=1.2.1'
+    netcdf4: ''
+    numpy: '>=1.20'
+    pandas: '>=1.0.5'
+    python: '>=3.7,<4.0'
+    python-dateutil: ''
+    pytz: ''
+    shapely: '>=1.8'
+    simplejson: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/pocean-core-3.1.0-pyhd8ed1ab_0.conda
   hash:
-    md5: 6520452e207d8f9bab9f21492f88c48b
-    sha256: a563bd856ffac75d634eed2d28a9ad5b13c55379a2afd054390d76b2910ef03c
+    md5: ef77ed3dfbfed4ceb8ee883738706675
+    sha256: e7113cd9fdc5b3891b47a9c68cd3fbc04fa3d98704af2e1a23ada1f5d86b5be1
   category: main
   optional: false
-- name: r-mgcv
-  version: '1.9_0'
+- name: pocean-core
+  version: 3.1.0
   manager: conda
   platform: osx-64
   dependencies:
-    libblas: '>=3.9.0,<4.0a0'
-    liblapack: '>=3.9.0,<4.0a0'
-    llvm-openmp: '>=15.0.7'
-    r-base: '>=4.3,<4.4.0a0'
-    r-matrix: ''
-    r-nlme: '>=3.1_64'
-  url: https://conda.anaconda.org/conda-forge/osx-64/r-mgcv-1.9_0-r43h9c380c6_0.conda
+    python-dateutil: ''
+    pytz: ''
+    netcdf4: ''
+    simplejson: ''
+    python: '>=3.7,<4.0'
+    numpy: '>=1.20'
+    pandas: '>=1.0.5'
+    shapely: '>=1.8'
+    cftime: '>=1.2.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/pocean-core-3.1.0-pyhd8ed1ab_0.conda
   hash:
-    md5: 32645f355db86b38d6d440d52b8ad2c9
-    sha256: d33f8e0e17f824058dacd3b7c726bd5ab006500582779ef01d509a4f09b6ef9a
+    md5: ef77ed3dfbfed4ceb8ee883738706675
+    sha256: e7113cd9fdc5b3891b47a9c68cd3fbc04fa3d98704af2e1a23ada1f5d86b5be1
   category: main
   optional: false
-- name: r-openssl
-  version: 2.1.1
+- name: pocean-core
+  version: 3.1.0
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    openssl: '>=3.1.3,<4.0a0'
-    r-askpass: ''
-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/r-openssl-2.1.1-r43hc61a7e2_0.conda
+    python-dateutil: ''
+    pytz: ''
+    netcdf4: ''
+    simplejson: ''
+    python: '>=3.7,<4.0'
+    numpy: '>=1.20'
+    pandas: '>=1.0.5'
+    shapely: '>=1.8'
+    cftime: '>=1.2.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/pocean-core-3.1.0-pyhd8ed1ab_0.conda
   hash:
-    md5: 3db86666c5b26a54e5976ab755a6fa8a
-    sha256: 4e6afb88f3a31b796bc9db53f00da9b3a4e6a5816ff3629f15b8e9d7f995a0a3
+    md5: ef77ed3dfbfed4ceb8ee883738706675
+    sha256: e7113cd9fdc5b3891b47a9c68cd3fbc04fa3d98704af2e1a23ada1f5d86b5be1
   category: main
   optional: false
-- name: r-promises
-  version: 1.2.1
+- name: pocean-core
+  version: 3.1.0
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    libcxx: '>=15.0.7'
-    r-base: '>=4.3,<4.4.0a0'
-    r-fastmap: '>=1.1.0'
-    r-later: ''
-    r-magrittr: '>=1.5'
-    r-r6: ''
-    r-rcpp: ''
-    r-rlang: ''
-  url: https://conda.anaconda.org/conda-forge/osx-64/r-promises-1.2.1-r43hac7d2d5_0.conda
+    python-dateutil: ''
+    pytz: ''
+    netcdf4: ''
+    simplejson: ''
+    python: '>=3.7,<4.0'
+    numpy: '>=1.20'
+    pandas: '>=1.0.5'
+    shapely: '>=1.8'
+    cftime: '>=1.2.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/pocean-core-3.1.0-pyhd8ed1ab_0.conda
   hash:
-    md5: fc9cc111fa54190ffea58e8eb04573b0
-    sha256: a75b26a5496065c7b028476989324540ab31715d9a3d2c7c2db1e2bf3e71cfc8
+    md5: ef77ed3dfbfed4ceb8ee883738706675
+    sha256: e7113cd9fdc5b3891b47a9c68cd3fbc04fa3d98704af2e1a23ada1f5d86b5be1
   category: main
   optional: false
-- name: r-raster
-  version: '3.6_26'
+- name: poppler
+  version: 24.02.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    __osx: '>=10.9'
-    libcxx: '>=16.0.6'
-    r-base: '>=4.3,<4.4.0a0'
-    r-rcpp: ''
-    r-sp: '>=1.4.5'
-    r-terra: '>=1.6-41'
-  url: https://conda.anaconda.org/conda-forge/osx-64/r-raster-3.6_26-r43h64b2c41_0.conda
+    cairo: '>=1.18.0,<2.0a0'
+    fontconfig: '>=2.14.2,<3.0a0'
+    fonts-conda-ecosystem: ''
+    freetype: '>=2.12.1,<3.0a0'
+    lcms2: '>=2.16,<3.0a0'
+    libcurl: '>=8.5.0,<9.0a0'
+    libgcc-ng: '>=12'
+    libglib: '>=2.78.3,<3.0a0'
+    libiconv: '>=1.17,<2.0a0'
+    libjpeg-turbo: '>=3.0.0,<4.0a0'
+    libpng: '>=1.6.42,<1.7.0a0'
+    libstdcxx-ng: '>=12'
+    libtiff: '>=4.6.0,<4.7.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    nspr: '>=4.35,<5.0a0'
+    nss: '>=3.97,<4.0a0'
+    openjpeg: '>=2.5.0,<3.0a0'
+    poppler-data: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/poppler-24.02.0-h590f24d_0.conda
   hash:
-    md5: c0871225139cc47a7af1b704904fad9b
-    sha256: 900e2c9f9e0ec22bfb54f5dd4bff00b80c824379730bf0e4c11b6e3c054e25e1
+    md5: 7e715c1572de09d6106c5a31fa70ffca
+    sha256: 55bb2deb67c76bd9f5592bf9765cc879cf11e555c4f8879292cbd5544e88887e
   category: main
   optional: false
-- name: r-rgdal
-  version: '1.6_7'
+- name: poppler
+  version: 24.02.0
   manager: conda
   platform: osx-64
   dependencies:
-    __osx: '>=10.9'
-    libcxx: '>=16.0.6'
-    libgdal: '>=3.7.2,<3.8.0a0'
-    proj: '>=9.3.0,<9.3.1.0a0'
-    r-base: '>=4.3,<4.4.0a0'
-    r-sp: '>=1.1_0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/r-rgdal-1.6_7-r43h3e0c24d_0.conda
+    cairo: '>=1.18.0,<2.0a0'
+    fontconfig: '>=2.14.2,<3.0a0'
+    fonts-conda-ecosystem: ''
+    freetype: '>=2.12.1,<3.0a0'
+    gettext: '>=0.21.1,<1.0a0'
+    lcms2: '>=2.16,<3.0a0'
+    libcurl: '>=8.5.0,<9.0a0'
+    libcxx: '>=16'
+    libglib: '>=2.78.3,<3.0a0'
+    libiconv: '>=1.17,<2.0a0'
+    libjpeg-turbo: '>=3.0.0,<4.0a0'
+    libpng: '>=1.6.42,<1.7.0a0'
+    libtiff: '>=4.6.0,<4.7.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    nspr: '>=4.35,<5.0a0'
+    nss: '>=3.97,<4.0a0'
+    openjpeg: '>=2.5.0,<3.0a0'
+    poppler-data: ''
+  url: https://conda.anaconda.org/conda-forge/osx-64/poppler-24.02.0-h0c752f9_0.conda
   hash:
-    md5: a62565a7ad17d5a252e5e89bdd7bef22
-    sha256: 1eefb23e32d778f964a4e31afcc21ab970c5f98ec86ddc7be09f19c04b10c5a0
+    md5: 064e1d83d148b0ff5fa9ddd21141d0b1
+    sha256: 54400c2961eca96f14ecbb9ccdac457ef7f86ee6741e38aa71db47eee22b76b6
   category: main
   optional: false
-- name: r-rgeos
-  version: '0.6_4'
+- name: poppler
+  version: 23.10.0
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    geos: '>=3.12.0,<3.12.1.0a0'
-    libcxx: '>=15.0.7'
-    r-base: '>=4.3,<4.4.0a0'
-    r-sp: '>=1.1_0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/r-rgeos-0.6_4-r43h82bd096_0.conda
+    __osx: '>=10.9'
+    cairo: '>=1.18.0,<2.0a0'
+    fontconfig: '>=2.14.2,<3.0a0'
+    fonts-conda-ecosystem: ''
+    freetype: '>=2.12.1,<3.0a0'
+    gettext: '>=0.21.1,<1.0a0'
+    lcms2: '>=2.15,<3.0a0'
+    libcurl: '>=8.4.0,<9.0a0'
+    libcxx: '>=16.0.6'
+    libglib: '>=2.78.0,<3.0a0'
+    libiconv: '>=1.17,<2.0a0'
+    libjpeg-turbo: '>=3.0.0,<4.0a0'
+    libpng: '>=1.6.39,<1.7.0a0'
+    libtiff: '>=4.6.0,<4.7.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    nspr: '>=4.35,<5.0a0'
+    nss: '>=3.94,<4.0a0'
+    openjpeg: '>=2.5.0,<3.0a0'
+    poppler-data: ''
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/poppler-23.10.0-hcdd998b_0.conda
   hash:
-    md5: f11e4f24f61778803c5be4bea3525890
-    sha256: ca1f11bfdf08cf56784e233361d227b4ade688afa55a9671d154f4d4972c4b6b
+    md5: f09dca383af70b61ff5ead622d2994a1
+    sha256: 53ffe710fc3c2e6af9c7b42f093b39b2626a6029bc7373509a7e054031b6cf95
   category: main
   optional: false
-- name: r-s2
-  version: 1.1.4
+- name: poppler
+  version: 23.12.0
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    libcxx: '>=15.0.7'
-    openssl: '>=3.1.1,<4.0a0'
-    r-base: '>=4.3,<4.4.0a0'
-    r-rcpp: ''
-    r-wk: ''
-  url: https://conda.anaconda.org/conda-forge/osx-64/r-s2-1.1.4-r43hc0060d5_1.conda
+    cairo: '>=1.18.0,<2.0a0'
+    freetype: '>=2.12.1,<3.0a0'
+    lcms2: '>=2.15,<3.0a0'
+    libcurl: '>=8.4.0,<9.0a0'
+    libglib: '>=2.78.1,<3.0a0'
+    libiconv: '>=1.17,<2.0a0'
+    libjpeg-turbo: '>=3.0.0,<4.0a0'
+    libpng: '>=1.6.39,<1.7.0a0'
+    libtiff: '>=4.6.0,<4.7.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    openjpeg: '>=2.5.0,<3.0a0'
+    poppler-data: ''
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/poppler-23.12.0-hc2f3c52_0.conda
   hash:
-    md5: c738308e32491b6284e74dd97d5115f7
-    sha256: b971a003d0a4ed95f870f5350b3a8ca11857b76ef34325fa455624ee44867d63
+    md5: 8c90459ba86f472bec103717d41792a1
+    sha256: 02c9799b474a4be63c1e039723c0f276c7b0f098d51d033796afb7ad9e0517e7
   category: main
   optional: false
-- name: r-scales
-  version: 1.2.1
+- name: poppler-data
+  version: 0.4.12
   manager: conda
-  platform: osx-64
-  dependencies:
-    r-r6: ''
-    r-lifecycle: ''
-    r-rcolorbrewer: ''
-    r-viridislite: ''
-    r-labeling: ''
-    r-base: '>=4.3,<4.4.0a0'
-    r-munsell: '>=0.5'
-    r-farver: '>=2.0.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-scales-1.2.1-r43hc72bb7e_2.conda
+  platform: linux-64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/noarch/poppler-data-0.4.12-hd8ed1ab_0.conda
   hash:
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-    sha256: a57b079cfa4c51f0cc5ba4a32b1b0bc4374bf2d6895e0ae6c645c4a6cbf26206
+    md5: d8d7293c5b37f39b2ac32940621c6592
+    sha256: 2f227e17b3c0346112815faa605502b66c1c4511a856127f2899abf15a98a2cf
   category: main
   optional: false
-- name: r-sfheaders
-  version: 0.4.3
+- name: poppler-data
+  version: 0.4.12
   manager: conda
   platform: osx-64
-  dependencies:
-    libcxx: '>=15.0.7'
-    r-base: '>=4.3,<4.4.0a0'
-    r-geometries: '>=0.2.2'
-    r-rcpp: '>=1.0.10'
-  url: https://conda.anaconda.org/conda-forge/osx-64/r-sfheaders-0.4.3-r43hac7d2d5_0.conda
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/noarch/poppler-data-0.4.12-hd8ed1ab_0.conda
   hash:
-    md5: ed08e63b29d86758069b57c01926acd3
-    sha256: 4be5e3d03244289591e5539a2e30ca35e1812cc57149a3f35caa2e5d6fa82c03
+    md5: d8d7293c5b37f39b2ac32940621c6592
+    sha256: 2f227e17b3c0346112815faa605502b66c1c4511a856127f2899abf15a98a2cf
   category: main
   optional: false
-- name: r-svglite
-  version: 2.1.2
+- name: poppler-data
+  version: 0.4.12
   manager: conda
-  platform: osx-64
-  dependencies:
-    __osx: '>=10.9'
-    libcxx: '>=16.0.6'
-    libpng: '>=1.6.39,<1.7.0a0'
-    r-base: '>=4.3,<4.4.0a0'
-    r-systemfonts: '>=1.0.0'
-  url: https://conda.anaconda.org/conda-forge/osx-64/r-svglite-2.1.2-r43ha588c02_0.conda
+  platform: osx-arm64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/noarch/poppler-data-0.4.12-hd8ed1ab_0.conda
   hash:
-    md5: ba4e1625dd21e7a2c0024db3e881b528
-    sha256: 35a457cb573a470285f8ce70147dc82f9c386f1f76eaad934d6a94b3ae00f461
+    md5: d8d7293c5b37f39b2ac32940621c6592
+    sha256: 2f227e17b3c0346112815faa605502b66c1c4511a856127f2899abf15a98a2cf
   category: main
   optional: false
-- name: r-urltools
-  version: 1.7.3
+- name: poppler-data
+  version: 0.4.12
   manager: conda
-  platform: osx-64
-  dependencies:
-    libcxx: '>=15.0.7'
-    r-base: '>=4.3,<4.4.0a0'
-    r-rcpp: ''
-    r-triebeard: ''
-  url: https://conda.anaconda.org/conda-forge/osx-64/r-urltools-1.7.3-r43hac7d2d5_4.conda
+  platform: win-64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/noarch/poppler-data-0.4.12-hd8ed1ab_0.conda
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   category: main
   optional: false
-- name: r-vctrs
-  version: 0.6.4
+- name: portalocker
+  version: 2.8.2
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    __osx: '>=10.9'
-    libcxx: '>=16.0.6'
-    r-base: '>=4.3,<4.4.0a0'
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-  url: https://conda.anaconda.org/conda-forge/osx-64/r-vctrs-0.6.4-r43h64b2c41_0.conda
+    python: '>=3.12.0rc3,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/linux-64/portalocker-2.8.2-py312h7900ff3_1.conda
   hash:
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   category: main
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-- name: r-xts
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+- name: portalocker
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   manager: conda
   platform: osx-64
   dependencies:
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-    r-zoo: '>=1.7_12'
-  url: https://conda.anaconda.org/conda-forge/osx-64/r-xts-0.13.1-r43h6dc245f_1.conda
+    python: '>=3.12.0rc3,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/osx-64/portalocker-2.8.2-py312hb401068_1.conda
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   category: main
   optional: false
-- name: r-classint
-  version: '0.4_10'
+- name: portalocker
+  version: 2.8.2
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
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-    libgfortran5: '>=12.3.0'
-    r-base: '>=4.3,<4.4.0a0'
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-    r-kernsmooth: ''
-  url: https://conda.anaconda.org/conda-forge/osx-64/r-classint-0.4_10-r43hfe07776_0.conda
+    python: '>=3.12.0rc3,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/portalocker-2.8.2-py312h81bd7bf_1.conda
   hash:
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   category: main
   optional: false
-- name: r-crosstalk
-  version: 1.2.0
+- name: portalocker
+  version: 2.8.2
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    r-jsonlite: ''
-    r-r6: ''
-    r-lazyeval: ''
-    r-base: '>=4.3,<4.4.0a0'
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-crosstalk-1.2.0-r43hc72bb7e_2.conda
+    python: '>=3.12.0rc3,<3.13.0a0'
+    python_abi: 3.12.*
+    pywin32: ''
+  url: https://conda.anaconda.org/conda-forge/win-64/portalocker-2.8.2-py312h2e8e312_1.conda
   hash:
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   category: main
   optional: false
-- name: r-crul
-  version: 1.4.0
+- name: postgresql
+  version: '16.2'
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    r-jsonlite: ''
-    r-mime: ''
-    r-base: '>=4.3,<4.4.0a0'
-    r-r6: '>=2.2.0'
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-    r-curl: '>=3.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-crul-1.4.0-r43h785f33e_1.conda
+    krb5: '>=1.21.2,<1.22.0a0'
+    libgcc-ng: '>=12'
+    libpq: '16.2'
+    libxml2: '>=2.12.5,<3.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    openssl: '>=3.2.1,<4.0a0'
+    readline: '>=8.2,<9.0a0'
+    tzcode: ''
+    tzdata: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/postgresql-16.2-h7387d8b_0.conda
   hash:
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   category: main
   optional: false
-- name: r-emld
-  version: 0.5.1
+- name: postgresql
+  version: '16.2'
   manager: conda
   platform: osx-64
   dependencies:
-    r-jsonlite: ''
-    r-xml2: ''
-    r-yaml: ''
-    r-jsonld: ''
-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-emld-0.5.1-r43hc72bb7e_2.conda
+    krb5: '>=1.21.2,<1.22.0a0'
+    libpq: '16.2'
+    libxml2: '>=2.12.5,<3.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    openssl: '>=3.2.1,<4.0a0'
+    readline: '>=8.2,<9.0a0'
+    tzcode: ''
+    tzdata: ''
+  url: https://conda.anaconda.org/conda-forge/osx-64/postgresql-16.2-hbd19fd8_0.conda
   hash:
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   category: main
   optional: false
-- name: r-fontawesome
-  version: 0.5.2
+- name: postgresql
+  version: '16.0'
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    r-base: '>=4.3,<4.4.0a0'
-    r-rlang: '>=0.4.10'
-    r-htmltools: '>=0.5.1.1'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-fontawesome-0.5.2-r43hc72bb7e_0.conda
+    krb5: '>=1.21.2,<1.22.0a0'
+    libpq: '16.0'
+    libxml2: '>=2.11.5,<2.12.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    openssl: '>=3.1.3,<4.0a0'
+    readline: '>=8.2,<9.0a0'
+    tzcode: ''
+    tzdata: ''
+    zlib: ''
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/postgresql-16.0-h00cd704_1.conda
   hash:
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   category: main
   optional: false
-- name: r-geojsonsf
-  version: 2.0.3
+- name: postgresql
+  version: '16.2'
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    libcxx: '>=15.0.7'
-    r-base: '>=4.3,<4.4.0a0'
-    r-geometries: ''
-    r-jsonify: '>=1.1.1'
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-  url: https://conda.anaconda.org/conda-forge/osx-64/r-geojsonsf-2.0.3-r43hac7d2d5_2.conda
+    krb5: '>=1.21.2,<1.22.0a0'
+    libpq: '16.2'
+    libxml2: '>=2.12.5,<3.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    openssl: '>=3.2.1,<4.0a0'
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/postgresql-16.2-h1beaf6b_0.conda
   hash:
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   category: main
   optional: false
-- name: r-gridextra
-  version: '2.3'
+- name: pre-commit
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   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    r-gtable: ''
-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-gridextra-2.3-r43hc72bb7e_1005.conda
+    cfgv: '>=2.0.0'
+    identify: '>=1.0.0'
+    nodeenv: '>=0.11.1'
+    python: '>=3.9'
+    pyyaml: '>=5.1'
+    virtualenv: '>=20.10.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/pre-commit-3.6.2-pyha770c72_0.conda
   hash:
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   category: main
   optional: false
-- name: r-hms
-  version: 1.1.3
+- name: pre-commit
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   manager: conda
   platform: osx-64
   dependencies:
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-    r-lifecycle: ''
-    r-ellipsis: ''
-    r-pkgconfig: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-hms-1.1.3-r43hc72bb7e_1.conda
+    python: '>=3.9'
+    pyyaml: '>=5.1'
+    identify: '>=1.0.0'
+    nodeenv: '>=0.11.1'
+    cfgv: '>=2.0.0'
+    virtualenv: '>=20.10.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/pre-commit-3.6.2-pyha770c72_0.conda
   hash:
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   category: main
   optional: false
-- name: r-httpuv
-  version: 1.6.12
+- name: pre-commit
+  version: 3.5.0
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
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-    libcxx: '>=16.0.6'
-    r-base: '>=4.3,<4.4.0a0'
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-  url: https://conda.anaconda.org/conda-forge/osx-64/r-httpuv-1.6.12-r43h64b2c41_0.conda
+    python: '>=3.8'
+    pyyaml: '>=5.1'
+    identify: '>=1.0.0'
+    nodeenv: '>=0.11.1'
+    cfgv: '>=2.0.0'
+    virtualenv: '>=20.10.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/pre-commit-3.5.0-pyha770c72_0.conda
   hash:
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   category: main
   optional: false
-- name: r-httr
-  version: 1.4.7
+- name: pre-commit
+  version: 3.6.2
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    r-jsonlite: ''
-    r-r6: ''
-    r-mime: ''
-    r-base: '>=4.3,<4.4.0a0'
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-httr-1.4.7-r43hc72bb7e_0.conda
+    python: '>=3.9'
+    pyyaml: '>=5.1'
+    identify: '>=1.0.0'
+    nodeenv: '>=0.11.1'
+    cfgv: '>=2.0.0'
+    virtualenv: '>=20.10.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/pre-commit-3.6.2-pyha770c72_0.conda
   hash:
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   category: main
   optional: false
-- name: r-influencer
-  version: 0.1.5
+- name: proj
+  version: 9.3.1
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    llvm-openmp: '>=16.0.5'
-    r-base: '>=4.3,<4.4.0a0'
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-  url: https://conda.anaconda.org/conda-forge/osx-64/r-influencer-0.1.5-r43hc72ff8c_1.conda
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+    libstdcxx-ng: '>=12'
+    libtiff: '>=4.6.0,<4.7.0a0'
+    sqlite: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/proj-9.3.1-h1d62c97_0.conda
   hash:
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   optional: false
-- name: r-jquerylib
-  version: 0.1.4
+- name: proj
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   manager: conda
   platform: osx-64
   dependencies:
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-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-jquerylib-0.1.4-r43hc72bb7e_2.conda
+    __osx: '>=10.9'
+    libcurl: '>=8.4.0,<9.0a0'
+    libcxx: '>=16.0.6'
+    libsqlite: '>=3.44.2,<4.0a0'
+    libtiff: '>=4.6.0,<4.7.0a0'
+    sqlite: ''
+  url: https://conda.anaconda.org/conda-forge/osx-64/proj-9.3.1-h81faed2_0.conda
   hash:
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   category: main
   optional: false
-- name: r-leaflet.providers
-  version: 2.0.0
+- name: proj
+  version: 9.3.0
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    r-htmltools: ''
-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-leaflet.providers-2.0.0-r43hc72bb7e_0.conda
+    libcurl: '>=8.4.0,<9.0a0'
+    libsqlite: '>=3.43.2,<4.0a0'
+    libtiff: '>=4.6.0,<4.7.0a0'
+    sqlite: ''
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/proj-9.3.0-h52fb9d0_2.conda
   hash:
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   category: main
   optional: false
-- name: r-pillar
-  version: 1.9.0
+- name: proj
+  version: 9.3.1
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    r-cli: ''
-    r-lifecycle: ''
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-    r-fansi: ''
-    r-base: '>=4.3,<4.4.0a0'
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-pillar-1.9.0-r43hc72bb7e_1.conda
+    libcurl: '>=8.4.0,<9.0a0'
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+    libtiff: '>=4.6.0,<4.7.0a0'
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+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/proj-9.3.1-he13c7e8_0.conda
   hash:
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   optional: false
-- name: r-pkgbuild
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-- name: r-sass
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-- name: r-satellite
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-- name: r-bslib
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-- name: r-pkgload
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-- name: r-progress
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-- name: r-reshape2
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   manager: conda
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-- name: r-servr
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-- name: r-spatialwidget
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-- name: r-tibble
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   manager: conda
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   dependencies:
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+    libgcc-ng: '>=12'
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-- name: r-dplyr
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+    python_abi: 3.12.*
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   category: main
   optional: false
-- name: r-ggplot2
-  version: 3.4.4
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   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
-    r-tibble: ''
-    r-mass: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-ggplot2-3.4.4-r43hc72bb7e_0.conda
+    python: '>=3.12.0rc3,<3.13.0a0'
+    python_abi: 3.12.*
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   category: main
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-- name: r-irdisplay
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   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
-    r-repr: ''
-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-irdisplay-1.1-r43hd8ed1ab_2.conda
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/psutil-5.9.8-py312he70551f_0.conda
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-- name: r-rematch2
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+- name: pthread-stubs
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   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    r-tibble: ''
-    r-base: '>=4.3,<4.4.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-rematch2-2.1.2-r43hc72bb7e_3.conda
+    libgcc-ng: '>=7.5.0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/pthread-stubs-0.4-h36c2ea0_1001.tar.bz2
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   category: main
   optional: false
-- name: r-rgexf
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+- name: pthread-stubs
+  version: '0.4'
   manager: conda
   platform: osx-64
-  dependencies:
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-    r-xml: ''
-    r-servr: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-rgexf-0.16.2-r43hc72bb7e_2.conda
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-64/pthread-stubs-0.4-hc929b4f_1001.tar.bz2
   hash:
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-- name: r-rmarkdown
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+- name: pthread-stubs
+  version: '0.4'
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/pthread-stubs-0.4-h27ca646_1001.tar.bz2
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   dependencies:
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-    pandoc: '>=1.14'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-rmarkdown-2.25-r43hc72bb7e_0.conda
+    m2w64-gcc-libs: ''
+  url: https://conda.anaconda.org/conda-forge/win-64/pthread-stubs-0.4-hcd874cb_1001.tar.bz2
   hash:
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-- name: r-shiny
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+- name: pthreads-win32
+  version: 2.9.1
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
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-    r-crayon: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-shiny-1.7.5.1-r43h785f33e_0.conda
+    vc: 14.*
+  url: https://conda.anaconda.org/conda-forge/win-64/pthreads-win32-2.9.1-hfa6e2cd_3.tar.bz2
   hash:
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   optional: false
-- name: r-vroom
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+- name: ptyprocess
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   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    libcxx: '>=15.0.7'
-    r-base: '>=4.3,<4.4.0a0'
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-    r-withr: ''
-  url: https://conda.anaconda.org/conda-forge/osx-64/r-vroom-1.6.4-r43hac7d2d5_0.conda
+    python: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/ptyprocess-0.7.0-pyhd3deb0d_0.tar.bz2
   hash:
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   optional: false
-- name: r-worrms
-  version: 0.4.3
+- name: ptyprocess
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   manager: conda
   platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-worrms-0.4.3-r43h785f33e_0.conda
+    python: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/ptyprocess-0.7.0-pyhd3deb0d_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: r-cowplot
-  version: 1.1.1
+- name: ptyprocess
+  version: 0.7.0
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
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-    r-scales: ''
-    r-gtable: ''
-    r-base: '>=4.3,<4.4.0a0'
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-cowplot-1.1.1-r43hc72bb7e_2.conda
+    python: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/ptyprocess-0.7.0-pyhd3deb0d_0.tar.bz2
   hash:
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   category: main
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-- name: r-eml
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+- name: ptyprocess
+  version: 0.7.0
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
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-    r-jsonlite: ''
-    r-digest: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-eml-2.0.6.1-r43hc72bb7e_2.conda
+    python: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/ptyprocess-0.7.0-pyhd3deb0d_0.tar.bz2
   hash:
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   category: main
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-- name: r-htmlwidgets
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+- name: pure_eval
+  version: 0.2.2
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    r-rmarkdown: ''
-    r-yaml: ''
-    r-base: '>=4.3,<4.4.0a0'
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-htmlwidgets-1.6.2-r43hc72bb7e_1.conda
+    python: '>=3.5'
+  url: https://conda.anaconda.org/conda-forge/noarch/pure_eval-0.2.2-pyhd8ed1ab_0.tar.bz2
   hash:
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   optional: false
-- name: r-irkernel
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+- name: pure_eval
+  version: 0.2.2
   manager: conda
   platform: osx-64
   dependencies:
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-    r-crayon: ''
-    r-uuid: ''
-    r-base: '>=4.3,<4.4.0a0'
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-irkernel-1.3.2-r43h785f33e_1.conda
+    python: '>=3.5'
+  url: https://conda.anaconda.org/conda-forge/noarch/pure_eval-0.2.2-pyhd8ed1ab_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: r-miniui
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+  version: 0.2.2
   manager: conda
-  platform: osx-64
+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-miniui-0.1.1.1-r43hc72bb7e_1004.conda
+    python: '>=3.5'
+  url: https://conda.anaconda.org/conda-forge/noarch/pure_eval-0.2.2-pyhd8ed1ab_0.tar.bz2
   hash:
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   optional: false
-- name: r-readr
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+- name: pure_eval
+  version: 0.2.2
   manager: conda
-  platform: osx-64
+  platform: win-64
   dependencies:
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-    r-base: '>=4.3,<4.4.0a0'
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-  url: https://conda.anaconda.org/conda-forge/osx-64/r-readr-2.1.4-r43hac7d2d5_1.conda
+    python: '>=3.5'
+  url: https://conda.anaconda.org/conda-forge/noarch/pure_eval-0.2.2-pyhd8ed1ab_0.tar.bz2
   hash:
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   optional: false
-- name: r-rerddap
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+- name: pybtex
+  version: 0.24.0
   manager: conda
-  platform: osx-64
+  platform: linux-64
   dependencies:
-    r-tibble: ''
-    r-digest: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-rerddap-1.0.4-r43hc72bb7e_0.conda
+    latexcodec: '>=1.0.4'
+    python: '>=3.6'
+    pyyaml: '>=3.01'
+    setuptools: ''
+    six: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/pybtex-0.24.0-pyhd8ed1ab_2.tar.bz2
   hash:
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   optional: false
-- name: r-tidyr
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+- name: pybtex
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   manager: conda
   platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-64/r-tidyr-1.3.0-r43hac7d2d5_1.conda
+    setuptools: ''
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+    python: '>=3.6'
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   optional: false
-- name: libev
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   manager: conda
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-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libev-4.33-h642e427_1.tar.bz2
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+    fiona: ''
+    owslib: ''
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-- name: libexpat
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   manager: conda
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-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.5.0-hb7217d7_1.conda
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-- name: libffi
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   manager: conda
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-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.4.2-h3422bc3_5.tar.bz2
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-- name: libiconv
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   manager: conda
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-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libiconv-1.17-he4db4b2_0.tar.bz2
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-- name: libjpeg-turbo
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   manager: conda
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-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libjpeg-turbo-3.0.0-hb547adb_1.conda
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-- name: libsodium
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   manager: conda
   platform: osx-arm64
-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libsodium-1.0.18-h27ca646_1.tar.bz2
+  dependencies:
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-- name: libwebp-base
-  version: 1.3.2
+- name: pyparsing
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   manager: conda
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-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libwebp-base-1.3.2-hb547adb_0.conda
+  platform: win-64
+  dependencies:
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+  url: https://conda.anaconda.org/conda-forge/noarch/pyparsing-3.1.1-pyhd8ed1ab_0.conda
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   category: main
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-- name: libzlib
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   manager: conda
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-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libzlib-1.2.13-h53f4e23_5.conda
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+    python_abi: 3.12.*
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   hash:
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-- name: llvm-openmp
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   manager: conda
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-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/llvm-openmp-17.0.3-hcd81f8e_0.conda
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   hash:
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-- name: lzo
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   manager: conda
   platform: osx-arm64
-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/lzo-2.10-h642e427_1000.tar.bz2
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   hash:
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-- name: ncurses
-  version: '6.4'
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   manager: conda
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-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/ncurses-6.4-h7ea286d_0.conda
+  platform: win-64
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   optional: false
-- name: pandoc
-  version: 3.1.3
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   manager: conda
-  platform: osx-arm64
-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/pandoc-3.1.3-hce30654_0.conda
+  platform: linux-64
+  dependencies:
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+    numpy: '>=1.26.4,<2.0a0'
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+    python_abi: 3.12.*
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+    setuptools: '>=3.2'
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+  url: https://conda.anaconda.org/conda-forge/linux-64/pyresample-1.28.1-py312hfb8ada1_0.conda
   hash:
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   category: main
   optional: false
-- name: phantomjs
-  version: 2.1.1
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   manager: conda
-  platform: osx-arm64
-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/phantomjs-2.1.1-hce30654_1.conda
+  platform: osx-64
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+    libcxx: '>=16'
+    numpy: '>=1.26.4,<2.0a0'
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+    python_abi: 3.12.*
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+    setuptools: '>=3.2'
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+  url: https://conda.anaconda.org/conda-forge/osx-64/pyresample-1.28.1-py312h83c8a23_0.conda
   hash:
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   category: main
   optional: false
-- name: poppler-data
-  version: 0.4.12
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   manager: conda
   platform: osx-arm64
-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/noarch/poppler-data-0.4.12-hd8ed1ab_0.conda
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+    libcxx: '>=16.0.6'
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+    python_abi: 3.12.*
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+    setuptools: '>=3.2'
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+  url: https://conda.anaconda.org/conda-forge/osx-arm64/pyresample-1.27.1-py312h9e53831_2.conda
   hash:
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   category: main
   optional: false
-- name: pthread-stubs
-  version: '0.4'
+- name: pyresample
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   manager: conda
-  platform: osx-arm64
-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/pthread-stubs-0.4-h27ca646_1001.tar.bz2
+  platform: win-64
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+    python_abi: 3.12.*
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+    vc: '>=14.2,<15'
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+  url: https://conda.anaconda.org/conda-forge/win-64/pyresample-1.28.1-py312h2ab9e98_0.conda
   hash:
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   optional: false
-- name: python_abi
-  version: '3.12'
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   manager: conda
-  platform: osx-arm64
-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/python_abi-3.12-4_cp312.conda
+  platform: linux-64
+  dependencies:
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+    numpy: ''
+    python: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/pysgrid-0.3.5-py_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: selenium-manager
-  version: 4.14.0
+- name: pysgrid
+  version: 0.3.5
   manager: conda
-  platform: osx-arm64
-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/selenium-manager-4.14.0-h5ef7bb8_1.conda
+  platform: osx-64
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+  url: https://conda.anaconda.org/conda-forge/noarch/pysgrid-0.3.5-py_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: tzcode
-  version: 2023c
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   manager: conda
   platform: osx-arm64
-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/tzcode-2023c-h1a8c8d9_0.conda
+  dependencies:
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+  url: https://conda.anaconda.org/conda-forge/noarch/pysgrid-0.3.5-py_0.tar.bz2
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   optional: false
-- name: tzdata
-  version: 2023c
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   manager: conda
-  platform: osx-arm64
-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/noarch/tzdata-2023c-h71feb2d_0.conda
+  platform: win-64
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+  url: https://conda.anaconda.org/conda-forge/noarch/pysgrid-0.3.5-py_0.tar.bz2
   hash:
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   optional: false
-- name: xorg-libxau
-  version: 1.0.11
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   manager: conda
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-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/xorg-libxau-1.0.11-hb547adb_0.conda
+  platform: linux-64
+  dependencies:
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+  url: https://conda.anaconda.org/conda-forge/noarch/pyshp-2.3.1-pyhd8ed1ab_0.tar.bz2
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   optional: false
-- name: xorg-libxdmcp
-  version: 1.1.3
+- name: pyshp
+  version: 2.3.1
   manager: conda
-  platform: osx-arm64
-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/xorg-libxdmcp-1.1.3-h27ca646_0.tar.bz2
+  platform: osx-64
+  dependencies:
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/pyshp-2.3.1-pyhd8ed1ab_0.tar.bz2
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-- name: xz
-  version: 5.2.6
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+  version: 2.3.1
   manager: conda
   platform: osx-arm64
-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/xz-5.2.6-h57fd34a_0.tar.bz2
+  dependencies:
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/pyshp-2.3.1-pyhd8ed1ab_0.tar.bz2
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-- name: yaml
-  version: 0.2.5
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+  version: 2.3.1
   manager: conda
-  platform: osx-arm64
-  dependencies: {}
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/yaml-0.2.5-h3422bc3_2.tar.bz2
+  platform: win-64
+  dependencies:
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/pyshp-2.3.1-pyhd8ed1ab_0.tar.bz2
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-- name: expat
-  version: 2.5.0
+- name: pysocks
+  version: 1.7.1
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/expat-2.5.0-hb7217d7_1.conda
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+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/pysocks-1.7.1-pyha2e5f31_6.tar.bz2
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   category: main
   optional: false
-- name: fonts-conda-forge
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+- name: pysocks
+  version: 1.7.1
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    font-ttf-inconsolata: ''
-    font-ttf-source-code-pro: ''
-    font-ttf-dejavu-sans-mono: ''
-    font-ttf-ubuntu: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/fonts-conda-forge-1-0.tar.bz2
+    __unix: ''
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/pysocks-1.7.1-pyha2e5f31_6.tar.bz2
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-- name: geos
-  version: 3.12.0
+- name: pysocks
+  version: 1.7.1
   manager: conda
   platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/geos-3.12.0-h13dd4ca_0.conda
+    __unix: ''
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/pysocks-1.7.1-pyha2e5f31_6.tar.bz2
   hash:
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-- name: gettext
-  version: 0.21.1
+- name: pysocks
+  version: 1.7.1
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/gettext-0.21.1-h0186832_0.tar.bz2
+    __win: ''
+    win_inet_pton: ''
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/pysocks-1.7.1-pyh0701188_6.tar.bz2
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-- name: hdf4
-  version: 4.2.15
+- name: pytest
+  version: 8.0.0
   manager: conda
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+  platform: linux-64
   dependencies:
-    libcxx: '>=15.0.7'
-    libjpeg-turbo: '>=3.0.0,<4.0a0'
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+    exceptiongroup: '>=1.0.0rc8'
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+    python: '>=3.8'
+    tomli: '>=1.0.0'
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   category: main
   optional: false
-- name: lerc
-  version: 4.0.0
+- name: pytest
+  version: 8.0.0
   manager: conda
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+  platform: osx-64
   dependencies:
-    libcxx: '>=13.0.1'
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/lerc-4.0.0-h9a09cb3_0.tar.bz2
+    packaging: ''
+    colorama: ''
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+    python: '>=3.8'
+    exceptiongroup: '>=1.0.0rc8'
+    tomli: '>=1.0.0'
+    pluggy: <2.0,>=1.4.0
+  url: https://conda.anaconda.org/conda-forge/noarch/pytest-8.0.0-pyhd8ed1ab_0.conda
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   category: main
   optional: false
-- name: libabseil
-  version: '20230802.1'
+- name: pytest
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   manager: conda
   platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libabseil-20230802.1-cxx17_h13dd4ca_0.conda
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+    colorama: ''
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+    python: '>=3.7'
+    exceptiongroup: '>=1.0.0rc8'
+    tomli: '>=1.0.0'
+    pluggy: '>=0.12,<2.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/pytest-7.4.3-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: libaec
-  version: 1.1.2
+- name: pytest
+  version: 8.0.0
   manager: conda
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+  platform: win-64
   dependencies:
-    libcxx: '>=15.0.7'
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libaec-1.1.2-h13dd4ca_1.conda
+    packaging: ''
+    colorama: ''
+    iniconfig: ''
+    python: '>=3.8'
+    exceptiongroup: '>=1.0.0rc8'
+    tomli: '>=1.0.0'
+    pluggy: <2.0,>=1.4.0
+  url: https://conda.anaconda.org/conda-forge/noarch/pytest-8.0.0-pyhd8ed1ab_0.conda
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   category: main
   optional: false
-- name: libbrotlidec
-  version: 1.1.0
+- name: python
+  version: 3.12.2
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    libbrotlicommon: 1.1.0
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libbrotlidec-1.1.0-hb547adb_1.conda
+    bzip2: '>=1.0.8,<2.0a0'
+    ld_impl_linux-64: '>=2.36.1'
+    libexpat: '>=2.5.0,<3.0a0'
+    libffi: '>=3.4,<4.0a0'
+    libgcc-ng: '>=12'
+    libnsl: '>=2.0.1,<2.1.0a0'
+    libsqlite: '>=3.45.1,<4.0a0'
+    libuuid: '>=2.38.1,<3.0a0'
+    libxcrypt: '>=4.4.36'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    ncurses: '>=6.4,<7.0a0'
+    openssl: '>=3.2.1,<4.0a0'
+    readline: '>=8.2,<9.0a0'
+    tk: '>=8.6.13,<8.7.0a0'
+    tzdata: ''
+    xz: '>=5.2.6,<6.0a0'
+    pip: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/python-3.12.2-hab00c5b_0_cpython.conda
   hash:
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   category: main
   optional: false
-- name: libbrotlienc
-  version: 1.1.0
+- name: python
+  version: 3.12.2
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libbrotlienc-1.1.0-hb547adb_1.conda
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+    ncurses: '>=6.4,<7.0a0'
+    openssl: '>=3.2.1,<4.0a0'
+    readline: '>=8.2,<9.0a0'
+    tk: '>=8.6.13,<8.7.0a0'
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+    xz: '>=5.2.6,<6.0a0'
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+  url: https://conda.anaconda.org/conda-forge/osx-64/python-3.12.2-h9f0c242_0_cpython.conda
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   category: main
   optional: false
-- name: libedit
-  version: 3.1.20191231
+- name: python
+  version: 3.12.0
   manager: conda
   platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libedit-3.1.20191231-hc8eb9b7_2.tar.bz2
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-- name: libgfortran5
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-  dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libgfortran5-13.2.0-hf226fd6_1.conda
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+    libsqlite: '>=3.43.0,<4.0a0'
+    libzlib: '>=1.2.13,<1.3.0a0'
+    ncurses: '>=6.4,<7.0a0'
+    openssl: '>=3.1.3,<4.0a0'
+    readline: '>=8.2,<9.0a0'
+    tk: '>=8.6.13,<8.7.0a0'
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+    xz: '>=5.2.6,<6.0a0'
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   category: main
   optional: false
-- name: libpng
-  version: 1.6.39
+- name: python
+  version: 3.12.2
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
+    bzip2: '>=1.0.8,<2.0a0'
+    libexpat: '>=2.5.0,<3.0a0'
+    libffi: '>=3.4,<4.0a0'
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     libzlib: '>=1.2.13,<1.3.0a0'
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+    openssl: '>=3.2.1,<4.0a0'
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+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+    xz: '>=5.2.6,<6.0a0'
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+  url: https://conda.anaconda.org/conda-forge/win-64/python-3.12.2-h2628c8c_0_cpython.conda
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   category: main
   optional: false
-- name: libspatialindex
-  version: 1.9.3
+- name: python-dateutil
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   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libspatialindex-1.9.3-hbdafb3b_4.tar.bz2
+    python: '>=3.6'
+    six: '>=1.5'
+  url: https://conda.anaconda.org/conda-forge/noarch/python-dateutil-2.8.2-pyhd8ed1ab_0.tar.bz2
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   optional: false
-- name: libsqlite
-  version: 3.43.2
+- name: python-dateutil
+  version: 2.8.2
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libsqlite-3.43.2-h091b4b1_0.conda
+    python: '>=3.6'
+    six: '>=1.5'
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   optional: false
-- name: libudunits2
-  version: 2.2.28
+- name: python-dateutil
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   manager: conda
   platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libudunits2-2.2.28-h5f3f34b_3.conda
+    python: '>=3.6'
+    six: '>=1.5'
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   category: main
   optional: false
-- name: libxcb
-  version: '1.15'
+- name: python-dateutil
+  version: 2.8.2
   manager: conda
-  platform: osx-arm64
+  platform: win-64
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   manager: conda
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-- name: dataclasses
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+    readline: '>=8.2,<9.0a0'
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-- name: docopt
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   manager: conda
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+  platform: osx-64
   dependencies:
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+    clangxx_osx-64: '>=16'
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+    fonts-conda-ecosystem: ''
+    gettext: '>=0.21.1,<1.0a0'
+    gfortran_osx-64: 12.*
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-- name: docutils
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   manager: conda
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+  platform: win-64
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-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/docutils-0.17.1-py312h81bd7bf_4.conda
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+    liblapack: '>=3.9.0,<4.0a0'
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+    m2w64-bzip2: ''
+    m2w64-fftw: ''
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    m2w64-gmp: ''
+    m2w64-gsl: ''
+    m2w64-libiconv: ''
+    m2w64-libjpeg-turbo: ''
+    m2w64-libpng: ''
+    m2w64-libsndfile: ''
+    m2w64-libtiff: ''
+    m2w64-libxml2: ''
+    m2w64-mpfr: ''
+    m2w64-pcre2: ''
+    m2w64-tk: ''
+    m2w64-tktable: ''
+    m2w64-xz: ''
+    m2w64-zlib: ''
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-- name: entrypoints
-  version: '0.4'
+- name: r-base64enc
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   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/entrypoints-0.4-pyhd8ed1ab_0.tar.bz2
+    libgcc-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
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-- name: exceptiongroup
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   manager: conda
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/exceptiongroup-1.1.3-pyhd8ed1ab_0.conda
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-- name: executing
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+  version: '0.1_3'
   manager: conda
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+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/executing-2.0.1-pyhd8ed1ab_0.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
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+  url: https://conda.anaconda.org/conda-forge/win-64/r-base64enc-0.1_3-r41h6d2157b_1006.conda
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-- name: fasteners
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   manager: conda
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+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/fasteners-0.17.3-pyhd8ed1ab_0.tar.bz2
+    libgcc-ng: '>=12'
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-- name: filelock
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   manager: conda
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/filelock-3.13.0-pyhd8ed1ab_0.conda
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-- name: fontconfig
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+  version: 4.0.5
   manager: conda
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+  platform: win-64
   dependencies:
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+    m2w64-gcc-libs-core: ''
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-- name: freexl
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   manager: conda
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+  platform: linux-64
   dependencies:
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+    libgcc-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+    r-bit: '>=4.0.0'
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   optional: false
-- name: geographiclib
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   manager: conda
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/geographiclib-1.52-pyhd8ed1ab_0.tar.bz2
+    r-base: '>=4.3,<4.4.0a0'
+    r-bit: '>=4.0.0'
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   optional: false
-- name: geojson
-  version: 2.5.0
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+  version: 4.0.5
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/geojson-2.5.0-py_0.tar.bz2
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-bit: '>=4.0.0'
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   optional: false
-- name: greenlet
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   manager: conda
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+  platform: linux-64
   dependencies:
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-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/greenlet-3.0.1-py312h650e478_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-brew-1.0_10-r43hc72bb7e_0.conda
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   optional: false
-- name: hpack
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   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/hpack-4.0.0-pyh9f0ad1d_0.tar.bz2
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-brew-1.0_10-r43hc72bb7e_0.conda
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   optional: false
-- name: humanize
-  version: 4.8.0
+- name: r-brew
+  version: '1.0_8'
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/humanize-4.8.0-pyhd8ed1ab_0.conda
+    r-base: '>=4.1,<4.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-brew-1.0_8-r41hc72bb7e_1.tar.bz2
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   optional: false
-- name: hyperframe
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+- name: r-brio
+  version: 1.1.4
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/hyperframe-6.0.1-pyhd8ed1ab_0.tar.bz2
+    libgcc-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-brio-1.1.4-r43h57805ef_0.conda
   hash:
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   optional: false
-- name: idna
-  version: '3.4'
+- name: r-brio
+  version: 1.1.4
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/idna-3.4-pyhd8ed1ab_0.tar.bz2
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-brio-1.1.4-r43hb2c329c_0.conda
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   optional: false
-- name: imagesize
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+- name: r-brio
+  version: 1.1.4
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    python: '>=3.4'
-  url: https://conda.anaconda.org/conda-forge/noarch/imagesize-1.4.1-pyhd8ed1ab_0.tar.bz2
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-brio-1.1.4-r41h6d2157b_0.conda
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   optional: false
-- name: iniconfig
-  version: 2.0.0
+- name: r-bslib
+  version: 0.6.1
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/iniconfig-2.0.0-pyhd8ed1ab_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+    r-base64enc: ''
+    r-cachem: ''
+    r-htmltools: '>=0.5.7'
+    r-jquerylib: '>=0.1.3'
+    r-jsonlite: ''
+    r-lifecycle: ''
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   manager: conda
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-- name: jupyterlab_widgets
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-- name: mccabe
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   dependencies:
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-- name: mdurl
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-- name: mpmath
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-- name: msgpack-python
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-- name: munch
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   dependencies:
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-- name: munkres
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   dependencies:
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-- name: nest-asyncio
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+    r-lazyeval: ''
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+    r-htmltools: '>=0.3.6'
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-- name: pyshp
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   manager: conda
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+  platform: win-64
   dependencies:
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-- name: pysocks
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   manager: conda
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+  platform: linux-64
   dependencies:
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-    python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/pysocks-1.7.1-pyha2e5f31_6.tar.bz2
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-- name: python-fastjsonschema
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+  platform: osx-64
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-- name: python-json-logger
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-- name: python-tzdata
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+  platform: win-64
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-- name: pytz
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+  platform: linux-64
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-- name: pytzdata
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-- name: pyyaml
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-- name: pyzmq
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-- name: regex
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-- name: rfc3986-validator
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-- name: rpds-py
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-- name: rtree
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-- name: ruamel.yaml.clib
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-- name: simplejson
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-- name: simplekml
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-- name: six
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   dependencies:
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-- name: smmap
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-- name: sniffio
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   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/sniffio-1.3.0-pyhd8ed1ab_0.tar.bz2
+    r-r6: ''
+    r-cli: ''
+    r-rprojroot: ''
+    r-base: '>=4.1,<4.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-desc-1.4.2-r41hc72bb7e_1.tar.bz2
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   optional: false
-- name: snowballstemmer
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+  version: 1.0.11
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    python: '>=2'
-  url: https://conda.anaconda.org/conda-forge/noarch/snowballstemmer-2.2.0-pyhd8ed1ab_0.tar.bz2
+    r-base: '>=4.3,<4.4.0a0'
+    r-downloader: '>=0.4'
+    r-dplyr: '>=0.7.4'
+    r-glue: '>=1.2.0'
+    r-htmltools: '>=0.3.6'
+    r-htmlwidgets: '>=1.0'
+    r-igraph: '>=1.1.2'
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+    r-rlang: '>=0.2.0'
+    r-rstudioapi: '>=0.7'
+    r-scales: '>=0.5.0'
+    r-stringr: '>=1.3.0'
+    r-tibble: '>=1.4.2'
+    r-tidyr: '>=0.8.0'
+    r-viridis: '>=0.5.0'
+    r-visnetwork: '>=2.0.3'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-diagrammer-1.0.11-r43hc72bb7e_0.conda
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-- name: sortedcontainers
-  version: 2.4.0
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+  version: 1.0.11
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/sortedcontainers-2.4.0-pyhd8ed1ab_0.tar.bz2
+    r-base: '>=4.3,<4.4.0a0'
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+    r-influencer: '>=0.1.0'
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+    r-downloader: '>=0.4'
+    r-igraph: '>=1.1.2'
+    r-viridis: '>=0.5.0'
+    r-visnetwork: '>=2.0.3'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-diagrammer-1.0.11-r43hc72bb7e_0.conda
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-- name: soupsieve
-  version: '2.5'
+- name: r-diagrammer
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   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/soupsieve-2.5-pyhd8ed1ab_1.conda
+    r-base: '>=4.1,<4.2.0a0'
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+    r-dplyr: '>=0.7.4'
+    r-purrr: '>=0.2.4'
+    r-scales: '>=0.5.0'
+    r-tidyr: '>=0.8.0'
+    r-stringr: '>=1.3.0'
+    r-htmlwidgets: '>=1.0'
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+    r-influencer: '>=0.1.0'
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+    r-downloader: '>=0.4'
+    r-igraph: '>=1.1.2'
+    r-viridis: '>=0.5.0'
+    r-visnetwork: '>=2.0.3'
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-- name: sphinxcontrib-jsmath
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   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-jsmath-1.0.1-pyhd8ed1ab_0.conda
+    libgcc-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+    r-crayon: '>=1.3.2'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-diffobj-0.3.5-r43h57805ef_2.conda
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-- name: tabulate
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   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/tabulate-0.9.0-pyhd8ed1ab_1.tar.bz2
+    r-base: '>=4.3,<4.4.0a0'
+    r-crayon: '>=1.3.2'
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-- name: threadpoolctl
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   manager: conda
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+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/threadpoolctl-3.2.0-pyha21a80b_0.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-crayon: '>=1.3.2'
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-- name: tomli
-  version: 2.0.1
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   manager: conda
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+  platform: linux-64
   dependencies:
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/tomli-2.0.1-pyhd8ed1ab_0.tar.bz2
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-digest-0.6.34-r43ha503ecb_0.conda
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-- name: tornado
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   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/tornado-6.3.3-py312h02f2b3b_1.conda
+    libcxx: '>=15'
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-digest-0.6.34-r43h29979af_0.conda
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-- name: traitlets
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+  version: 0.6.34
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/traitlets-5.12.0-pyhd8ed1ab_0.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
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   category: main
   optional: false
-- name: types-python-dateutil
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+- name: r-downloader
+  version: '0.4'
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/types-python-dateutil-2.8.19.14-pyhd8ed1ab_0.conda
+    r-base: '>=4.3,<4.4.0a0'
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   optional: false
-- name: typing_extensions
-  version: 4.8.0
+- name: r-downloader
+  version: '0.4'
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.8.0-pyha770c72_0.conda
+    r-digest: ''
+    r-base: '>=4.3,<4.4.0a0'
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   category: main
   optional: false
-- name: typing_utils
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+  version: '0.4'
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/typing_utils-0.1.0-pyhd8ed1ab_0.tar.bz2
+    r-digest: ''
+    r-base: '>=4.1,<4.2.0a0'
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   optional: false
-- name: uc-micro-py
-  version: 1.0.1
+- name: r-dplyr
+  version: 1.1.4
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/uc-micro-py-1.0.1-pyhd8ed1ab_0.tar.bz2
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
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+    r-glue: '>=1.3.2'
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+    r-tibble: '>=2.1.3'
+    r-tidyselect: '>=1.1.0'
+    r-vctrs: '>=0.3.5'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-dplyr-1.1.4-r43ha503ecb_0.conda
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   category: main
   optional: false
-- name: uri-template
-  version: 1.3.0
+- name: r-dplyr
+  version: 1.1.4
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/uri-template-1.3.0-pyhd8ed1ab_0.conda
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-- name: uritemplate
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-  url: https://conda.anaconda.org/conda-forge/noarch/uritemplate-4.1.1-pyhd8ed1ab_0.tar.bz2
+    __osx: '>=10.9'
+    libcxx: '>=16.0.6'
+    r-base: '>=4.3,<4.4.0a0'
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+    r-rlang: '>=0.4.10'
+    r-tibble: '>=2.1.3'
+    r-tidyselect: '>=1.1.0'
+    r-vctrs: '>=0.3.5'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-dplyr-1.1.4-r43h64b2c41_0.conda
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   optional: false
-- name: validators
-  version: 0.22.0
+- name: r-dplyr
+  version: 1.1.4
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/validators-0.22.0-pyhd8ed1ab_0.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
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+    r-glue: '>=1.3.2'
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+    r-rlang: '>=0.4.10'
+    r-tibble: '>=2.1.3'
+    r-tidyselect: '>=1.1.0'
+    r-vctrs: '>=0.3.5'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-dplyr-1.1.4-r41ha856d6a_0.conda
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   optional: false
-- name: webcolors
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+- name: r-dt
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   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    python: '>=3.5'
-  url: https://conda.anaconda.org/conda-forge/noarch/webcolors-1.13-pyhd8ed1ab_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+    r-crosstalk: ''
+    r-htmltools: '>=0.3.6'
+    r-htmlwidgets: '>=1.3'
+    r-httpuv: ''
+    r-jquerylib: ''
+    r-jsonlite: '>=0.9.16'
+    r-magrittr: ''
+    r-promises: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/r-dt-0.31-r43hc72bb7e_0.conda
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-- name: cfitsio
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-- name: click-plugins
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-- name: cligj
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-- name: comm
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-- name: coverage
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-- name: easyargs
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-- name: fonttools
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-- name: geolinks
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-- name: geopy
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-- name: gitdb
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-- name: h11
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-- name: hdf5
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-- name: importlib-metadata
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-- name: importlib_resources
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-- name: jedi
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-- name: jinja2
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   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/jinja2-3.1.2-pyhd8ed1ab_1.tar.bz2
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
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+    r-rapidjsonr: '>=1.2.0'
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+    r-sfheaders: '>=0.2.2'
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-- name: joblib
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   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/joblib-1.3.2-pyhd8ed1ab_0.conda
+    libcxx: '>=15.0.7'
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+    r-sfheaders: '>=0.2.2'
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-- name: jupyterlab_pygments
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   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
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+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
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+    r-sfheaders: '>=0.2.2'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-geojsonsf-2.0.3-r41ha856d6a_2.conda
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-- name: latexcodec
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   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
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-    six: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/latexcodec-2.0.1-pyh9f0ad1d_0.tar.bz2
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
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+  url: https://conda.anaconda.org/conda-forge/linux-64/r-geometries-0.2.4-r43ha503ecb_0.conda
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   optional: false
-- name: libblas
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   manager: conda
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libblas-3.9.0-19_osxarm64_openblas.conda
+    libcxx: '>=15'
+    r-base: '>=4.3,<4.4.0a0'
+    r-rcpp: ''
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-geometries-0.2.4-r43h29979af_0.conda
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   optional: false
-- name: linkify-it-py
-  version: 2.0.0
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+  version: 0.2.4
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
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-    uc-micro-py: '>=1.0.1,<2.0.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/linkify-it-py-2.0.0-pyhd8ed1ab_0.tar.bz2
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
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+  url: https://conda.anaconda.org/conda-forge/win-64/r-geometries-0.2.4-r41ha856d6a_0.conda
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-- name: markdown-it-py
-  version: 2.2.0
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   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/markdown-it-py-2.2.0-pyhd8ed1ab_0.conda
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
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+    r-sp: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-geosphere-1.5_18-r43ha503ecb_1.conda
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   optional: false
-- name: matplotlib-inline
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   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/matplotlib-inline-0.1.6-pyhd8ed1ab_0.tar.bz2
+    libcxx: '>=15.0.7'
+    r-base: '>=4.3,<4.4.0a0'
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+  url: https://conda.anaconda.org/conda-forge/osx-64/r-geosphere-1.5_18-r43hac7d2d5_1.conda
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   optional: false
-- name: mercantile
-  version: 1.2.1
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+  version: '1.5_18'
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
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-    python: '>=3.6'
-    click: '>=3.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/mercantile-1.2.1-pyhd8ed1ab_0.tar.bz2
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
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+    r-sp: ''
+  url: https://conda.anaconda.org/conda-forge/win-64/r-geosphere-1.5_18-r41ha856d6a_1.conda
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   optional: false
-- name: nodeenv
-  version: 1.8.0
+- name: r-ggfortify
+  version: 0.4.16
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    setuptools: ''
-    python: 2.7|>=3.7
-  url: https://conda.anaconda.org/conda-forge/noarch/nodeenv-1.8.0-pyhd8ed1ab_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+    r-dplyr: '>=0.3'
+    r-ggplot2: '>=2.0.0'
+    r-gridextra: ''
+    r-scales: ''
+    r-stringr: ''
+    r-tibble: ''
+    r-tidyr: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/r-ggfortify-0.4.16-r43hc72bb7e_1.conda
   hash:
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-- name: outcome
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   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-    attrs: '>=19.2.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/outcome-1.3.0.post0-pyhd8ed1ab_0.conda
+    r-tibble: ''
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+    r-stringr: ''
+    r-scales: ''
+    r-gridextra: ''
+    r-base: '>=4.3,<4.4.0a0'
+    r-ggplot2: '>=2.0.0'
+    r-dplyr: '>=0.3'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-ggfortify-0.4.16-r43hc72bb7e_1.conda
   hash:
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   optional: false
-- name: overrides
-  version: 7.4.0
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+  version: 0.4.16
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
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-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/overrides-7.4.0-pyhd8ed1ab_0.conda
+    r-tibble: ''
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+    r-stringr: ''
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+    r-base: '>=4.1,<4.2.0a0'
+    r-ggplot2: '>=2.0.0'
+    r-dplyr: '>=0.3'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-ggfortify-0.4.16-r41hc72bb7e_0.conda
   hash:
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   category: main
   optional: false
-- name: pexpect
-  version: 4.8.0
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+  version: 3.4.4
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    python: ''
-    ptyprocess: '>=0.5'
-  url: https://conda.anaconda.org/conda-forge/noarch/pexpect-4.8.0-pyh1a96a4e_2.tar.bz2
+    r-base: '>=4.3,<4.4.0a0'
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+    r-scales: '>=1.2.0'
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+    r-vctrs: '>=0.5.0'
+    r-withr: '>=2.5.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-ggplot2-3.4.4-r43hc72bb7e_0.conda
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   category: main
   optional: false
-- name: pillow
-  version: 10.1.0
+- name: r-ggplot2
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   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/pillow-10.1.0-py312hac22aec_0.conda
+    r-tibble: ''
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+    r-rlang: '>=1.0.0'
+    r-vctrs: '>=0.5.0'
+    r-scales: '>=1.2.0'
+    r-gtable: '>=0.1.1'
+    r-lifecycle: '>=1.0.1'
+    r-withr: '>=2.5.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-ggplot2-3.4.4-r43hc72bb7e_0.conda
   hash:
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   category: main
   optional: false
-- name: pip
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   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
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-    wheel: ''
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/pip-23.3.1-pyhd8ed1ab_0.conda
+    r-tibble: ''
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+    r-base: '>=4.1,<4.2.0a0'
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+    r-vctrs: '>=0.5.0'
+    r-scales: '>=1.2.0'
+    r-gtable: '>=0.1.1'
+    r-lifecycle: '>=1.0.1'
+    r-withr: '>=2.5.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-ggplot2-3.4.2-r41hc72bb7e_0.conda
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   category: main
   optional: false
-- name: postgresql
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   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
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-    zlib: ''
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/postgresql-16.0-h00cd704_1.conda
+    libgcc-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-glue-1.7.0-r43h57805ef_0.conda
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   category: main
   optional: false
-- name: proj
-  version: 9.3.0
+- name: r-glue
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   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/proj-9.3.0-h52fb9d0_2.conda
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-glue-1.7.0-r43hb2c329c_0.conda
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-- name: protobuf
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-- name: pyct-core
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+  platform: linux-64
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-- name: pyobjc-core
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+  platform: osx-64
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-- name: pytest
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-- name: pyviz_comms
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+  platform: osx-64
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-- name: qtpy
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-- name: referencing
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-- name: rfc3339-validator
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-- name: sympy
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-- name: terminado
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-- name: tinycss2
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-- name: traittypes
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   manager: conda
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-- name: typing-extensions
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-- name: urllib3
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-- name: xerces-c
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-- name: argon2-cffi-bindings
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-- name: arrow
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-- name: branca
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+  platform: osx-64
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-- name: fqdn
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+  platform: win-64
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-- name: geotiff
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+  platform: linux-64
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-- name: gitpython
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   manager: conda
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+  platform: osx-64
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-- name: httpcore
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   manager: conda
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+  platform: win-64
   dependencies:
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-    python: '>=3.8'
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-- name: importlib_metadata
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   manager: conda
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+  platform: linux-64
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-- name: jsonschema-specifications
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   manager: conda
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+  platform: osx-64
   dependencies:
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-- name: jupyter_server_terminals
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   manager: conda
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+  platform: win-64
   dependencies:
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-    terminado: '>=0.8.3'
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-- name: kealib
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   manager: conda
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+  platform: linux-64
   dependencies:
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-- name: libcblas
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+- name: r-httpcache
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   manager: conda
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+  platform: osx-64
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libcblas-3.9.0-19_osxarm64_openblas.conda
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-- name: liblapack
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   manager: conda
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+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/liblapack-3.9.0-19_osxarm64_openblas.conda
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-- name: libnetcdf
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+- name: r-httpcode
+  version: 0.3.0
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
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-- name: libspatialite
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+- name: r-httpcode
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   manager: conda
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+  platform: osx-64
   dependencies:
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+    r-base: '>=4.3,<4.4.0a0'
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-- name: markdown
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   manager: conda
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+  platform: win-64
   dependencies:
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-- name: mdit-py-plugins
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   manager: conda
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+  platform: linux-64
   dependencies:
-    python: '>=3.8'
-    markdown-it-py: '>=1.0.0,<4.0.0'
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-- name: pendulum
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   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-- name: platformdirs
-  version: 3.11.0
+- name: r-httpuv
+  version: 1.6.14
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    python: '>=3.7'
-    typing-extensions: '>=4.6.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/platformdirs-3.11.0-pyhd8ed1ab_0.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-later: '>=0.8.0'
+    r-promises: ''
+    r-r6: ''
+    r-rcpp: '>=1.0.7'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-httpuv-1.6.14-r41ha856d6a_0.conda
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   category: main
   optional: false
-- name: poppler
-  version: 23.10.0
+- name: r-httr
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   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    __osx: '>=10.9'
-    cairo: '>=1.18.0,<2.0a0'
-    fontconfig: '>=2.14.2,<3.0a0'
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-    nss: '>=3.94,<4.0a0'
-    openjpeg: '>=2.5.0,<3.0a0'
-    poppler-data: ''
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/poppler-23.10.0-hcdd998b_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+    r-curl: '>=0.9.1'
+    r-jsonlite: ''
+    r-mime: ''
+    r-openssl: '>=0.8'
+    r-r6: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/r-httr-1.4.7-r43hc72bb7e_0.conda
   hash:
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   category: main
   optional: false
-- name: pybtex
-  version: 0.24.0
+- name: r-httr
+  version: 1.4.7
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    setuptools: ''
-    six: ''
-    python: '>=3.6'
-    latexcodec: '>=1.0.4'
-    pyyaml: '>=3.01'
-  url: https://conda.anaconda.org/conda-forge/noarch/pybtex-0.24.0-pyhd8ed1ab_2.tar.bz2
+    r-jsonlite: ''
+    r-r6: ''
+    r-mime: ''
+    r-base: '>=4.3,<4.4.0a0'
+    r-openssl: '>=0.8'
+    r-curl: '>=0.9.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-httr-1.4.7-r43hc72bb7e_0.conda
   hash:
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   category: main
   optional: false
-- name: pygeoif
-  version: 1.1.1
+- name: r-httr
+  version: 1.4.6
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    typing-extensions: ''
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/pygeoif-1.1.1-pyhd8ed1ab_0.conda
+    r-jsonlite: ''
+    r-r6: ''
+    r-mime: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-openssl: '>=0.8'
+    r-curl: '>=0.9.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-httr-1.4.6-r41hc72bb7e_0.conda
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   category: main
   optional: false
-- name: pyobjc-framework-cocoa
-  version: '10.0'
+- name: r-igraph
+  version: 1.6.0
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    libffi: '>=3.4,<4.0a0'
-    pyobjc-core: 10.0.*
-    python: '>=3.12.0rc3,<3.13.0a0'
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/pyobjc-framework-cocoa-10.0-py312h6168cce_1.conda
+    glpk: '>=5.0,<6.0a0'
+    gmp: '>=6.3.0,<7.0a0'
+    libblas: '>=3.9.0,<4.0a0'
+    libgcc-ng: '>=12'
+    libgfortran-ng: ''
+    libgfortran5: '>=12.3.0'
+    liblapack: '>=3.9.0,<4.0a0'
+    libstdcxx-ng: '>=12'
+    libxml2: '>=2.12.4,<3.0a0'
+    r-base: '>=4.3,<4.4.0a0'
+    r-cli: ''
+    r-cpp11: '>=0.4.7'
+    r-lifecycle: ''
+    r-magrittr: ''
+    r-matrix: ''
+    r-pkgconfig: '>=2.0.0'
+    r-rlang: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-igraph-1.6.0-r43hbec7d4a_0.conda
   hash:
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-    sha256: e0e2d8103a5c8d575fef6dad97bec72a7cb06f3053982dc8328dca95672f6b18
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   category: main
   optional: false
-- name: pyproj
-  version: 3.6.1
+- name: r-igraph
+  version: 1.6.0
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    certifi: ''
-    proj: '>=9.3.0,<9.3.1.0a0'
-    python: '>=3.12,<3.13.0a0'
-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/pyproj-3.6.1-py312h33684bb_3.conda
+    glpk: '>=5.0,<6.0a0'
+    gmp: '>=6.3.0,<7.0a0'
+    libblas: '>=3.9.0,<4.0a0'
+    libcxx: '>=16'
+    libgfortran: 5.*
+    libgfortran5: '>=13.2.0'
+    liblapack: '>=3.9.0,<4.0a0'
+    libxml2: '>=2.12.4,<3.0a0'
+    r-base: '>=4.3,<4.4.0a0'
+    r-cli: ''
+    r-cpp11: '>=0.4.7'
+    r-lifecycle: ''
+    r-magrittr: ''
+    r-matrix: ''
+    r-pkgconfig: '>=2.0.0'
+    r-rlang: ''
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-igraph-1.6.0-r43hf16f1c3_0.conda
   hash:
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   category: main
   optional: false
-- name: requests
-  version: 2.31.0
+- name: r-igraph
+  version: 1.6.0
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    python: '>=3.7'
-    idna: '>=2.5,<4'
-    certifi: '>=2017.4.17'
-    charset-normalizer: '>=2,<4'
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-  url: https://conda.anaconda.org/conda-forge/noarch/requests-2.31.0-pyhd8ed1ab_0.conda
+    libblas: '>=3.9.0,<4.0a0'
+    liblapack: '>=3.9.0,<4.0a0'
+    libxml2: '>=2.12.4,<3.0a0'
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-cli: ''
+    r-cpp11: '>=0.4.7'
+    r-lifecycle: ''
+    r-magrittr: ''
+    r-matrix: ''
+    r-pkgconfig: '>=2.0.0'
+    r-rlang: ''
+  url: https://conda.anaconda.org/conda-forge/win-64/r-igraph-1.6.0-r41hcf554be_0.conda
   hash:
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   category: main
   optional: false
-- name: sqlalchemy
-  version: 2.0.22
+- name: r-influencer
+  version: 0.1.5
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    greenlet: '!=0.4.17'
-    python: '>=3.12,<3.13.0a0'
-    python_abi: 3.12.*
-    typing-extensions: '>=4.2.0'
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/sqlalchemy-2.0.22-py312he37b823_0.conda
+    libgcc-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+    r-igraph: '>=1.0.1'
+    r-matrix: '>=1.1_4'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-influencer-0.1.5-r43h57805ef_1.conda
   hash:
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   category: main
   optional: false
-- name: stack_data
-  version: 0.6.2
+- name: r-influencer
+  version: 0.1.5
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-    executing: ''
-    pure_eval: ''
-    python: '>=3.5'
-  url: https://conda.anaconda.org/conda-forge/noarch/stack_data-0.6.2-pyhd8ed1ab_0.conda
+    llvm-openmp: '>=16.0.5'
+    r-base: '>=4.3,<4.4.0a0'
+    r-igraph: '>=1.0.1'
+    r-matrix: '>=1.1_4'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-influencer-0.1.5-r43hc72ff8c_1.conda
   hash:
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   category: main
   optional: false
-- name: trio
-  version: 0.22.2
+- name: r-influencer
+  version: 0.1.5
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    attrs: '>=20.1.0'
-    idna: ''
-    outcome: ''
-    python: '>=3.12,<3.13.0a0'
-    python_abi: 3.12.*
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-    sortedcontainers: ''
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/trio-0.22.2-py312h81bd7bf_1.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-igraph: '>=1.0.1'
+    r-matrix: '>=1.1_4'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-influencer-0.1.5-r41h6d2157b_1.conda
   hash:
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   category: main
   optional: false
-- name: ukkonen
-  version: 1.0.1
+- name: r-interleave
+  version: 0.1.2
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    cffi: ''
-    libcxx: '>=15.0.7'
-    python: '>=3.12.0rc3,<3.13.0a0'
-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/ukkonen-1.0.1-py312h389731b_4.conda
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+    r-geometries: '>=0.2.4'
+    r-rcpp: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-interleave-0.1.2-r43ha503ecb_0.conda
   hash:
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   category: main
   optional: false
-- name: wcwidth
-  version: 0.2.8
+- name: r-interleave
+  version: 0.1.2
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    backports.functools_lru_cache: ''
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/wcwidth-0.2.8-pyhd8ed1ab_0.conda
+    libcxx: '>=15'
+    r-base: '>=4.3,<4.4.0a0'
+    r-geometries: '>=0.2.4'
+    r-rcpp: ''
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-interleave-0.1.2-r43h29979af_0.conda
   hash:
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   category: main
   optional: false
-- name: wsproto
-  version: 1.2.0
+- name: r-irdisplay
+  version: '1.1'
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    python: '>=3.7'
-    h11: '>=0.9.0,<1.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/wsproto-1.2.0-pyhd8ed1ab_0.tar.bz2
+    r-base: '>=4.3,<4.4.0a0'
+    r-repr: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/r-irdisplay-1.1-r43hd8ed1ab_2.conda
   hash:
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   category: main
   optional: false
-- name: argon2-cffi
-  version: 23.1.0
+- name: r-irdisplay
+  version: '1.1'
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    typing-extensions: ''
-    argon2-cffi-bindings: ''
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/argon2-cffi-23.1.0-pyhd8ed1ab_0.conda
+    r-repr: ''
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-irdisplay-1.1-r43hd8ed1ab_2.conda
   hash:
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   category: main
   optional: false
-- name: github3.py
-  version: 4.0.1
+- name: r-irdisplay
+  version: '1.1'
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    python: '>=3.7'
-    python-dateutil: '>=2.6.0'
-    requests: '>=2.18'
-    uritemplate: '>=3.0.0'
-    pyjwt: '>=2.3.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/github3.py-4.0.1-pyhd8ed1ab_0.conda
+    r-repr: ''
+    r-base: '>=4.1,<4.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-irdisplay-1.1-r41hd8ed1ab_1.tar.bz2
   hash:
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   category: main
   optional: false
-- name: gsl
-  version: '2.7'
+- name: r-irkernel
+  version: 1.3.2
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    libblas: '>=3.9.0,<4.0a0'
-    libcblas: '>=3.9.0,<4.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/gsl-2.7-h6e638da_0.tar.bz2
+    r-base: '>=4.3,<4.4.0a0'
+    r-crayon: ''
+    r-digest: ''
+    r-evaluate: '>=0.10'
+    r-irdisplay: '>=0.3.0.9999'
+    r-jsonlite: '>=0.9.6'
+    r-pbdzmq: '>=0.2_1'
+    r-repr: '>=0.4.99'
+    r-uuid: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/r-irkernel-1.3.2-r43h785f33e_1.conda
   hash:
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   category: main
   optional: false
-- name: httpx
-  version: 0.25.0
+- name: r-irkernel
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   manager: conda
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+    r-crayon: ''
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-- name: identify
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+  version: 1.3.2
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
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-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/identify-2.5.31-pyhd8ed1ab_0.conda
+    r-digest: ''
+    r-crayon: ''
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+    r-pbdzmq: '>=0.2_1'
+    r-repr: '>=0.4.99'
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-- name: isoduration
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   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
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-    arrow: '>=0.15.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/isoduration-20.11.0-pyhd8ed1ab_0.tar.bz2
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-isoband-0.2.7-r43ha503ecb_2.conda
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-- name: jsonschema
-  version: 4.19.1
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   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-4.19.1-pyhd8ed1ab_0.conda
+    libcxx: '>=15.0.7'
+    r-base: '>=4.3,<4.4.0a0'
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-- name: jupyter_core
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+  version: 0.2.7
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
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-    python: '>=3.12,<3.13.0a0'
-    python_abi: 3.12.*
-    traitlets: '>=5.3'
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/jupyter_core-5.4.0-py312h81bd7bf_0.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-isoband-0.2.7-r41ha856d6a_2.conda
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-- name: libgdal
-  version: 3.7.2
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   manager: conda
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+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/libgdal-3.7.2-h116f65a_7.conda
+    jq: ''
+    libgcc-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+    r-lazyeval: ''
+    r-magrittr: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-jqr-1.3.3-r43h57805ef_0.conda
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-- name: netcdf-fortran
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   manager: conda
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/netcdf-fortran-4.6.1-nompi_h9281076_102.conda
+    jq: ''
+    r-base: '>=4.3,<4.4.0a0'
+    r-lazyeval: ''
+    r-magrittr: ''
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-jqr-1.3.3-r43hb2c329c_0.conda
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-- name: numpy
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   manager: conda
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+  platform: win-64
   dependencies:
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-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/numpy-1.26.0-py312h696b312_0.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-lazyeval: ''
+    r-magrittr: ''
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   optional: false
-- name: owslib
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+- name: r-jquerylib
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   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
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-    lxml: ''
-    pytz: ''
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-    python: '>=3.7'
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-  url: https://conda.anaconda.org/conda-forge/noarch/owslib-0.29.2-pyhd8ed1ab_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+    r-htmltools: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/r-jquerylib-0.1.4-r43hc72bb7e_2.conda
   hash:
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-- name: prompt-toolkit
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   manager: conda
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+  platform: osx-64
   dependencies:
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-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/prompt-toolkit-3.0.39-pyha770c72_0.conda
+    r-htmltools: ''
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-jquerylib-0.1.4-r43hc72bb7e_2.conda
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-- name: pybtex-docutils
-  version: 1.0.3
+- name: r-jquerylib
+  version: 0.1.4
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/pybtex-docutils-1.0.3-py312h81bd7bf_1.conda
+    r-htmltools: ''
+    r-base: '>=4.1,<4.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-jquerylib-0.1.4-r41hc72bb7e_1.tar.bz2
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-- name: pyct
-  version: 0.4.6
+- name: r-jsonify
+  version: 1.2.2
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
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-    requests: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/pyct-0.4.6-py_0.tar.bz2
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
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   category: main
   optional: false
-- name: pyworms
-  version: 0.4.0
+- name: r-jsonify
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   manager: conda
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+  platform: osx-64
   dependencies:
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-    backports.functools_lru_cache: ''
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/pyworms-0.4.0-pyhd8ed1ab_0.conda
+    libcxx: '>=15.0.7'
+    r-base: '>=4.3,<4.4.0a0'
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-- name: send2trash
-  version: 1.8.2
+- name: r-jsonify
+  version: 1.2.2
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
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-    pyobjc-framework-cocoa: ''
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/send2trash-1.8.2-pyhd1c38e8_0.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
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-- name: tempest-remap
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+- name: r-jsonld
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   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
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+    r-base: '>=4.3,<4.4.0a0'
+    r-curl: '>=2.7'
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+  url: https://conda.anaconda.org/conda-forge/noarch/r-jsonld-2.2-r43hc72bb7e_2.conda
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-- name: trio-websocket
-  version: 0.11.1
+- name: r-jsonld
+  version: '2.2'
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-    python: '>=3.7'
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-  url: https://conda.anaconda.org/conda-forge/noarch/trio-websocket-0.11.1-pyhd8ed1ab_0.conda
+    r-jsonlite: ''
+    r-v8: ''
+    r-base: '>=4.3,<4.4.0a0'
+    r-curl: '>=2.7'
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   optional: false
-- name: virtualenv
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+    sha256: 368830f1df275a89c1fd3b17ed55b670e6d3d874d85e8bc3da5548f60be2f2da
   category: main
   optional: false
-- name: scipy
-  version: 1.11.3
+- name: r-lattice
+  version: '0.22_5'
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    libblas: '>=3.9.0,<4.0a0'
-    libcblas: '>=3.9.0,<4.0a0'
-    libcxx: '>=15.0.7'
-    libgfortran: 5.*
-    libgfortran5: '>=13.2.0'
-    liblapack: '>=3.9.0,<4.0a0'
-    numpy: '>=1.26.0,<2.0a0'
-    python: '>=3.12,<3.13.0a0'
-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/scipy-1.11.3-py312h44883eb_1.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-lattice-0.22_5-r41h6d2157b_0.conda
   hash:
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-    sha256: a1de458f94a9aecb79620ada349c7530135b4616a378684b1bd423d46170eb10
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+    sha256: 42e47b8c603fcbfeaba14bf463c609386108f159e305681118e3dc57aeccfe9a
   category: main
   optional: false
-- name: seawater
-  version: 3.3.4
+- name: r-lazyeval
+  version: 0.2.2
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    python: ''
-    numpy: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/seawater-3.3.4-py_1.tar.bz2
+    libgcc-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-lazyeval-0.2.2-r43h57805ef_4.conda
   hash:
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-    sha256: 83e6abb3b3dae1d94f659d6c909fa640b67a6f34067939838d31fcd570339ce2
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+    sha256: 03da9e70caf52417daacafae09ccc414cef2f0da23fc38d97eb54003875a58ea
   category: main
   optional: false
-- name: selenium
-  version: 4.14.0
+- name: r-lazyeval
+  version: 0.2.2
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    python: '>=3.7'
-    certifi: '>=2021.10.8'
-    trio: '>=0.17,<1.dev0'
-    trio-websocket: '>=0.9,<1.dev0'
-    urllib3: '>=1.26,<3'
-    selenium-manager: 4.14.*
-  url: https://conda.anaconda.org/conda-forge/noarch/selenium-4.14.0-pyhd8ed1ab_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-lazyeval-0.2.2-r43h6dc245f_4.conda
   hash:
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-    sha256: 237ae7a8fd3ddf405f1618eb8a4ac9f4b152cb6f17e295c8125678373ab8500b
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   category: main
   optional: false
-- name: shapely
-  version: 2.0.2
+- name: r-lazyeval
+  version: 0.2.2
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    geos: '>=3.12.0,<3.12.1.0a0'
-    numpy: '>=1.26.0,<2.0a0'
-    python: '>=3.12,<3.13.0a0'
-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/shapely-2.0.2-py312hf679d78_0.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-lazyeval-0.2.2-r41h6d2157b_4.conda
   hash:
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-    sha256: b32a86631919a3c7cd5c17b74e3f70ad4913efd4aab648519f512f63b62c9229
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+    sha256: 19122e383c6959c378a86f95c38ad87a690f29aebe2158c4a860e1986981fedf
   category: main
   optional: false
-- name: snuggs
-  version: 1.4.7
+- name: r-leafem
+  version: 0.2.3
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    python: ''
-    numpy: ''
-    pyparsing: '>=2.1.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/snuggs-1.4.7-py_0.tar.bz2
+    r-base: '>=4.3,<4.4.0a0'
+    r-base64enc: ''
+    r-htmltools: '>=0.3'
+    r-htmlwidgets: ''
+    r-leaflet: '>=2.0.1'
+    r-mapdeck: ''
+    r-png: ''
+    r-raster: ''
+    r-scales: '>=1.0.0'
+    r-sf: ''
+    r-sp: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/r-leafem-0.2.3-r43h785f33e_0.conda
   hash:
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-    sha256: ebb8f5f9e362f186fb7d732e656f85c969b86309494436eba51cc3b8b96683f7
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+    sha256: f2a0b21e95a893511c91940cd89c588278ef3bf863e2ddc4046e0daba47dd9a4
   category: main
   optional: false
-- name: bokeh
-  version: 3.3.0
+- name: r-leafem
+  version: 0.2.3
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    python: '>=3.9'
-    numpy: '>=1.16'
-    pyyaml: '>=3.10'
-    pandas: '>=1.2'
-    tornado: '>=5.1'
-    pillow: '>=7.1.0'
-    packaging: '>=16.8'
-    jinja2: '>=2.9'
-    contourpy: '>=1'
-    xyzservices: '>=2021.09.1'
-  url: https://conda.anaconda.org/conda-forge/noarch/bokeh-3.3.0-pyhd8ed1ab_0.conda
+    r-base64enc: ''
+    r-htmlwidgets: ''
+    r-sp: ''
+    r-sf: ''
+    r-raster: ''
+    r-png: ''
+    r-mapdeck: ''
+    r-base: '>=4.3,<4.4.0a0'
+    r-scales: '>=1.0.0'
+    r-htmltools: '>=0.3'
+    r-leaflet: '>=2.0.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-leafem-0.2.3-r43h785f33e_0.conda
   hash:
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-    sha256: c007fed947070f21bbb73340cfad70a55e8fb1e48c01a4ac977ff53c636329cb
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+    sha256: f2a0b21e95a893511c91940cd89c588278ef3bf863e2ddc4046e0daba47dd9a4
   category: main
   optional: false
-- name: cf-units
-  version: 3.2.0
+- name: r-leafem
+  version: 0.2.0
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    antlr-python-runtime: 4.11.1.*
-    cftime: '>=1.5.2'
-    jinja2: ''
-    libudunits2: '>=2.2.28,<3.0a0'
-    numpy: '>=1.26.0,<2.0a0'
-    python: '>=3.12,<3.13.0a0'
-    python_abi: 3.12.*
-    udunits2: '>=2.2.28,<2.3.0a0'
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/cf-units-3.2.0-py312hf635c46_4.conda
+    r-base64enc: ''
+    r-htmlwidgets: ''
+    r-sp: ''
+    r-sf: ''
+    r-raster: ''
+    r-png: ''
+    r-mapdeck: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-scales: '>=1.0.0'
+    r-htmltools: '>=0.3'
+    r-leaflet: '>=2.0.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-leafem-0.2.0-r41h785f33e_1.tar.bz2
   hash:
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-    sha256: 1ba424771edeeb740137e0ec49cbb8826bae7c3eb1eea3e4a0289757bcac54e6
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+    sha256: b810008df0f6f15c343a38fd87f368350c68ad4bd46ead528e16c0e6c5e03427
   category: main
   optional: false
-- name: erddapy
-  version: 2.2.0
+- name: r-leaflet
+  version: 2.2.1
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    pytz: ''
-    httpx: ''
-    python: '>=3.8'
-    pandas: <3,>=0.25.2
-  url: https://conda.anaconda.org/conda-forge/noarch/erddapy-2.2.0-pyhd8ed1ab_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+    r-base64enc: ''
+    r-crosstalk: ''
+    r-htmltools: ''
+    r-htmlwidgets: ''
+    r-leaflet.providers: '>=1.8.0'
+    r-magrittr: ''
+    r-markdown: ''
+    r-png: ''
+    r-raster: ''
+    r-rcolorbrewer: ''
+    r-scales: '>=1.0.0'
+    r-sp: ''
+    r-viridis: '>=0.5.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-leaflet-2.2.1-r43hc72bb7e_0.conda
   hash:
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-    sha256: 551059f05aeb9b18f0148da0d406e3a1c19e42aea6357356ec2228d193da146b
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+    sha256: 0ecae1a99bdd57cfed9b0477df330df86650557d4552e4f0df059d180cb76d58
   category: main
   optional: false
-- name: fiona
-  version: 1.9.5
+- name: r-leaflet
+  version: 2.2.1
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    __osx: '>=10.9'
-    attrs: '>=17'
-    click: '>=4.0'
-    click-plugins: '>=1.0'
-    cligj: '>=0.5'
-    gdal: ''
-    importlib-metadata: ''
-    libcxx: '>=16.0.6'
-    libgdal: '>=3.7.2,<3.8.0a0'
-    munch: ''
-    numpy: '>=1.26.0,<2.0a0'
-    python: '>=3.12,<3.13.0a0'
-    python_abi: 3.12.*
-    setuptools: ''
-    shapely: ''
-    six: '>=1.7'
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/fiona-1.9.5-py312h0aea21f_0.conda
+    r-magrittr: ''
+    r-htmltools: ''
+    r-base64enc: ''
+    r-htmlwidgets: ''
+    r-rcolorbrewer: ''
+    r-sp: ''
+    r-raster: ''
+    r-png: ''
+    r-markdown: ''
+    r-crosstalk: ''
+    r-base: '>=4.3,<4.4.0a0'
+    r-scales: '>=1.0.0'
+    r-viridis: '>=0.5.1'
+    r-leaflet.providers: '>=1.8.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-leaflet-2.2.1-r43hc72bb7e_0.conda
   hash:
-    md5: 52cb2f8cf1cf1204a49f49343537053f
-    sha256: e3aaa6f6efb7d765f851586a168022d50298b01748bf61400843d014ffc4d859
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+    sha256: 0ecae1a99bdd57cfed9b0477df330df86650557d4552e4f0df059d180cb76d58
   category: main
   optional: false
-- name: geopandas-base
-  version: 0.14.0
+- name: r-leaflet
+  version: 2.1.2
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    packaging: ''
-    python: '>=3.9'
-    pandas: '>=1.4.0'
-    shapely: '>=1.8.0'
-    pyproj: '>=3.3.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/geopandas-base-0.14.0-pyha770c72_1.conda
+    r-magrittr: ''
+    r-htmltools: ''
+    r-base64enc: ''
+    r-htmlwidgets: ''
+    r-rcolorbrewer: ''
+    r-sp: ''
+    r-raster: ''
+    r-png: ''
+    r-markdown: ''
+    r-crosstalk: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-scales: '>=1.0.0'
+    r-viridis: '>=0.5.1'
+    r-leaflet.providers: '>=1.8.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-leaflet-2.1.2-r41hc72bb7e_0.conda
   hash:
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-    sha256: 97fe438e399d9106998e38fc700fdd6f90f15ea92d1e20cf0a01e74436aa24ba
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+    sha256: 69c820487804c3b44e8fe76880bbbc50fca068178f92941decaa9480c6d46de8
   category: main
   optional: false
-- name: ipython
-  version: 8.16.1
+- name: r-leaflet.extras
+  version: 1.0.0
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    typing_extensions: ''
-    decorator: ''
-    exceptiongroup: ''
-    __osx: ''
-    stack_data: ''
-    matplotlib-inline: ''
-    backcall: ''
-    appnope: ''
-    pickleshare: ''
-    python: '>=3.9'
-    pygments: '>=2.4.0'
-    traitlets: '>=5'
-    jedi: '>=0.16'
-    pexpect: '>4.3'
-    prompt_toolkit: '>=3.0.30,<3.1.0,!=3.0.37'
-  url: https://conda.anaconda.org/conda-forge/noarch/ipython-8.16.1-pyh31c8845_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+    r-htmltools: ''
+    r-htmlwidgets: ''
+    r-leaflet: '>=2.0.0'
+    r-magrittr: ''
+    r-stringr: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/r-leaflet.extras-1.0.0-r43hc72bb7e_1006.conda
   hash:
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-    sha256: 77cfbc15ee2ad8976009a6880bb1f7c716db44e23594fba7c9c382135e02eb03
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+    sha256: 21a42eead7e8de7b16cf59912a41e6761a71afa76c1a1084d3fae104be5dce81
   category: main
   optional: false
-- name: jupyter_events
-  version: 0.8.0
-  manager: conda
-  platform: osx-arm64
+- name: r-leaflet.extras
+  version: 1.0.0
+  manager: conda
+  platform: osx-64
   dependencies:
-    rfc3339-validator: ''
-    referencing: ''
-    python: '>=3.8'
-    pyyaml: '>=5.3'
-    rfc3986-validator: '>=0.1.1'
-    traitlets: '>=5.3'
-    python-json-logger: '>=2.0.4'
-    jsonschema-with-format-nongpl: '>=4.18.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_events-0.8.0-pyhd8ed1ab_0.conda
+    r-magrittr: ''
+    r-stringr: ''
+    r-htmltools: ''
+    r-htmlwidgets: ''
+    r-base: '>=4.3,<4.4.0a0'
+    r-leaflet: '>=2.0.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-leaflet.extras-1.0.0-r43hc72bb7e_1006.conda
   hash:
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-    sha256: 44742f7b6453774fbbdf7cec20282f88c7362707990790116fec23270b81b447
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+    sha256: 21a42eead7e8de7b16cf59912a41e6761a71afa76c1a1084d3fae104be5dce81
   category: main
   optional: false
-- name: matplotlib-base
-  version: 3.8.0
+- name: r-leaflet.extras
+  version: 1.0.0
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    __osx: '>=10.9'
-    certifi: '>=2020.06.20'
-    contourpy: '>=1.0.1'
-    cycler: '>=0.10'
-    fonttools: '>=4.22.0'
-    freetype: '>=2.12.1,<3.0a0'
-    kiwisolver: '>=1.0.1'
-    libcxx: '>=16.0.6'
-    numpy: '>=1.26.0,<2.0a0'
-    packaging: '>=20.0'
-    pillow: '>=6.2.0'
-    pyparsing: '>=2.3.1'
-    python: '>=3.12,<3.13.0a0'
-    python-dateutil: '>=2.7'
-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/matplotlib-base-3.8.0-py312hba9b818_2.conda
+    r-magrittr: ''
+    r-stringr: ''
+    r-htmltools: ''
+    r-htmlwidgets: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-leaflet: '>=2.0.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-leaflet.extras-1.0.0-r41hc72bb7e_1005.tar.bz2
   hash:
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-    sha256: 83ce7b8ec248823a2aa250ce8ea2ebd93907581eb6255d1094bf496b9336b811
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+    sha256: 2f5aa8e220f1535d89b2d916f7302a96f49c2e738b8b374b17ead6e4922ded56
   category: main
   optional: false
-- name: nbclient
-  version: 0.7.4
+- name: r-leaflet.providers
+  version: 2.0.0
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    python: '>=3.7'
-    jupyter_client: '>=6.1.12'
-    jupyter_core: '>=4.12,!=5.0.*'
-    nbformat: '>=5.1'
-    traitlets: '>=5.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/nbclient-0.7.4-pyhd8ed1ab_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+    r-htmltools: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/r-leaflet.providers-2.0.0-r43hc72bb7e_0.conda
   hash:
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-    sha256: f26afcbbdd4bd1245db514c6ebc6ef18cc12067145dcab229b6f88653575d44c
+    md5: d13d08f583d97d05290c089f07ce52ff
+    sha256: 419d2f95203320866de6bf548167b255b571b1b647e4bdbe32afbc57e7b6f14b
   category: main
   optional: false
-- name: nco
-  version: 5.1.8
+- name: r-leaflet.providers
+  version: 2.0.0
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    __osx: '>=10.9'
-    esmf: ''
-    gsl: '>=2.7,<2.8.0a0'
-    hdf5: '>=1.14.2,<1.14.3.0a0'
-    krb5: '>=1.21.2,<1.22.0a0'
-    libblas: '>=3.9.0,<4.0a0'
-    libcblas: '>=3.9.0,<4.0a0'
-    libcxx: '>=16.0.6'
-    libexpat: '>=2.5.0,<3.0a0'
-    libnetcdf: '>=4.9.2,<4.9.3.0a0'
-    libudunits2: '>=2.2.28,<3.0a0'
-    libzlib: '>=1.2.13,<1.3.0a0'
-    llvm-openmp: '>=16.0.6'
-    tempest-remap: '!=2.1.2,!=2.1.3'
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/nco-5.1.8-h91bca93_1.conda
+    r-htmltools: ''
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-leaflet.providers-2.0.0-r43hc72bb7e_0.conda
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   optional: false
-- name: netcdf4
-  version: 1.6.5
+- name: r-leaflet.providers
+  version: 1.9.0
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    certifi: ''
-    cftime: ''
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-    setuptools: ''
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/netcdf4-1.6.5-nompi_py312h9035142_100.conda
+    r-base: '>=4.1,<4.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-leaflet.providers-1.9.0-r41hc72bb7e_2.tar.bz2
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   optional: false
-- name: patsy
-  version: 0.5.3
+- name: r-leafpm
+  version: 0.1.0
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    scipy: ''
-    six: ''
-    python: '>=3.6'
-    numpy: '>=1.4.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/patsy-0.5.3-pyhd8ed1ab_0.tar.bz2
+    r-base: '>=4.3,<4.4.0a0'
+    r-dplyr: ''
+    r-htmltools: '>=0.3'
+    r-htmlwidgets: ''
+    r-jsonlite: ''
+    r-leaflet: '>=2.0.1'
+    r-sf: '>=0.5_2'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-leafpm-0.1.0-r43hc72bb7e_5.conda
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   category: main
   optional: false
-- name: pyobis
-  version: 1.3.1
+- name: r-leafpm
+  version: 0.1.0
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    pandas: ''
-    python: '>=3.7'
-    requests: '>2.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/pyobis-1.3.1-pyhd8ed1ab_0.conda
+    r-dplyr: ''
+    r-jsonlite: ''
+    r-htmlwidgets: ''
+    r-base: '>=4.3,<4.4.0a0'
+    r-htmltools: '>=0.3'
+    r-leaflet: '>=2.0.1'
+    r-sf: '>=0.5_2'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-leafpm-0.1.0-r43hc72bb7e_5.conda
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   optional: false
-- name: pyresample
-  version: 1.27.1
+- name: r-leafpm
+  version: 0.1.0
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    __osx: '>=10.9'
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-    shapely: ''
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/pyresample-1.27.1-py312h9e53831_2.conda
+    r-dplyr: ''
+    r-jsonlite: ''
+    r-htmlwidgets: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-htmltools: '>=0.3'
+    r-leaflet: '>=2.0.1'
+    r-sf: '>=0.5_2'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-leafpm-0.1.0-r41hc72bb7e_4.tar.bz2
   hash:
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   category: main
   optional: false
-- name: rasterio
-  version: 1.3.9
+- name: r-leafpop
+  version: 0.1.0
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    affine: ''
-    attrs: ''
-    certifi: ''
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-    cligj: '>=0.5'
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/rasterio-1.3.9-py312h6499bd6_0.conda
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+    r-base64enc: ''
+    r-brew: ''
+    r-htmltools: ''
+    r-htmlwidgets: ''
+    r-sf: ''
+    r-svglite: ''
+    r-uuid: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-leafpop-0.1.0-r43ha503ecb_2.conda
   hash:
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   optional: false
-- name: scikit-learn
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+  version: 0.1.0
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-    joblib: '>=1.1.1'
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-    llvm-openmp: '>=16.0.6'
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-  url: https://conda.anaconda.org/conda-forge/osx-arm64/scikit-learn-1.3.2-py312h6f466fd_1.conda
+    libcxx: '>=15.0.7'
+    r-base: '>=4.3,<4.4.0a0'
+    r-base64enc: ''
+    r-brew: ''
+    r-htmltools: ''
+    r-htmlwidgets: ''
+    r-sf: ''
+    r-svglite: ''
+    r-uuid: ''
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-leafpop-0.1.0-r43hac7d2d5_2.conda
   hash:
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   optional: false
-- name: utide
-  version: 0.3.0
+- name: r-leafpop
+  version: 0.1.0
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    numpy: ''
-    scipy: ''
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/utide-0.3.0-pyhd8ed1ab_0.tar.bz2
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-base64enc: ''
+    r-brew: ''
+    r-htmltools: ''
+    r-htmlwidgets: ''
+    r-sf: ''
+    r-svglite: ''
+    r-uuid: ''
+  url: https://conda.anaconda.org/conda-forge/win-64/r-leafpop-0.1.0-r41ha856d6a_2.conda
   hash:
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   optional: false
-- name: xarray
-  version: 2023.10.1
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+  version: 1.0.4
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    python: '>=3.9'
-    packaging: '>=21.3'
-    pandas: '>=1.4'
-    numpy: '>=1.22'
-  url: https://conda.anaconda.org/conda-forge/noarch/xarray-2023.10.1-pyhd8ed1ab_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+    r-cli: '>=3.4.0'
+    r-glue: ''
+    r-rlang: '>=1.0.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-lifecycle-1.0.4-r43hc72bb7e_0.conda
   hash:
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   category: main
   optional: false
-- name: zarr
-  version: 2.16.1
+- name: r-lifecycle
+  version: 1.0.4
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-    asciitree: ''
-    python: '>=3.8'
-    numcodecs: '>=0.10.0'
-    numpy: '>=1.20,!=1.21.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/zarr-2.16.1-pyhd8ed1ab_0.conda
+    r-glue: ''
+    r-base: '>=4.3,<4.4.0a0'
+    r-rlang: '>=1.0.6'
+    r-cli: '>=3.4.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-lifecycle-1.0.4-r43hc72bb7e_0.conda
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   optional: false
-- name: cartopy
-  version: 0.22.0
+- name: r-lifecycle
+  version: 1.0.3
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
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-    libcxx: '>=16.0.6'
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-    shapely: '>=1.7'
-  url: https://conda.anaconda.org/conda-forge/osx-arm64/cartopy-0.22.0-py312h9e53831_1.conda
+    r-glue: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-rlang: '>=1.0.6'
+    r-cli: '>=3.4.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-lifecycle-1.0.3-r41hc72bb7e_1.tar.bz2
   hash:
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   category: main
   optional: false
-- name: cf_xarray
-  version: 0.8.4
+- name: r-lubridate
+  version: 1.9.3
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
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-    python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/cf_xarray-0.8.4-pyhd8ed1ab_0.conda
+    libgcc-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+    r-generics: ''
+    r-timechange: '>=0.1.1'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-lubridate-1.9.3-r43h57805ef_0.conda
   hash:
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   category: main
   optional: false
-- name: cmcrameri
-  version: '1.7'
+- name: r-lubridate
+  version: 1.9.3
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-    matplotlib-base: ''
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/cmcrameri-1.7-pyhd8ed1ab_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+    r-generics: ''
+    r-timechange: '>=0.1.1'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-lubridate-1.9.3-r43h6dc245f_0.conda
   hash:
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   category: main
   optional: false
-- name: compliance-checker
-  version: 5.1.0
+- name: r-lubridate
+  version: 1.9.3
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/compliance-checker-5.1.0-pyhd8ed1ab_0.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-generics: ''
+    r-timechange: '>=0.1.1'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-lubridate-1.9.3-r41h6d2157b_0.conda
   hash:
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   category: main
   optional: false
-- name: contextily
-  version: 1.4.0
+- name: r-magrittr
+  version: 2.0.3
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    requests: ''
-    matplotlib-base: ''
-    pillow: ''
-    joblib: ''
-    rasterio: ''
-    xyzservices: ''
-    geopy: ''
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-    python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/contextily-1.4.0-pyhd8ed1ab_0.conda
+    libgcc-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-magrittr-2.0.3-r43h57805ef_2.conda
   hash:
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   optional: false
-- name: descartes
-  version: 1.1.0
+- name: r-magrittr
+  version: 2.0.3
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    python: ''
-    matplotlib-base: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/descartes-1.1.0-py_4.tar.bz2
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-magrittr-2.0.3-r43h6dc245f_2.conda
   hash:
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   category: main
   optional: false
-- name: gridgeo
-  version: 1.5.2
+- name: r-magrittr
+  version: 2.0.3
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    shapely: ''
-    netcdf4: ''
-    docopt: ''
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/gridgeo-1.5.2-py_0.tar.bz2
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-magrittr-2.0.3-r41h6d2157b_2.conda
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+    sha256: 869f89d97cbf7989a095a5db1fbf2e3a9eb49ff99246c576f793cc58ab85fbf2
   category: main
   optional: false
-- name: ioos_qc
-  version: 1.0.0
+- name: r-mapdata
+  version: 2.3.1
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    python: ''
-    xarray: ''
-    netcdf4: ''
-    ruamel.yaml: ''
-    geojson: ''
-    simplejson: ''
-    pygc: ''
-    numpy: '>=1.14'
-  url: https://conda.anaconda.org/conda-forge/noarch/ioos_qc-1.0.0-pyh9f0ad1d_0.tar.bz2
+    libgcc-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+    r-maps: '>=2.0_7'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-mapdata-2.3.1-r43h57805ef_1.conda
   hash:
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-    sha256: 0a48f0052a28961c3606aacc33c20d30ef87d88a0246d03e1dcc6b77be192045
+    md5: 09ea46dd78404313b6d800cbd7c99e0e
+    sha256: 7266b623fa024f312c3a5b0c7f25e8380b1d78dc197a97daf2ebe1d286488138
   category: main
   optional: false
-- name: ipykernel
-  version: 6.26.0
+- name: r-mapdata
+  version: 2.3.1
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    packaging: ''
-    psutil: ''
-    nest-asyncio: ''
-    __osx: ''
-    appnope: ''
-    python: '>=3.8'
-    tornado: '>=6.1'
-    jupyter_client: '>=6.1.12'
-    ipython: '>=7.23.1'
-    matplotlib-inline: '>=0.1'
-    jupyter_core: '>=4.12,!=5.0.*'
-    debugpy: '>=1.6.5'
-    comm: '>=0.1.1'
-    pyzmq: '>=20'
-    traitlets: '>=5.4.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/ipykernel-6.26.0-pyh3cd1d5f_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+    r-maps: '>=2.0_7'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-mapdata-2.3.1-r43h6dc245f_1.conda
   hash:
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-    sha256: be9927d47fe23cc4d2a09d252e37e1e56ffb137767d2c0577ed882ead16f75fa
+    md5: 9c3c73aa9eb74e90a4a560f6ec324bd0
+    sha256: c69e81cf0f3afa73c9136e2477b36ff4b363e91069c1485bbc6389df1192dc77
   category: main
   optional: false
-- name: ipywidgets
-  version: 8.1.1
+- name: r-mapdata
+  version: 2.3.1
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    python: '>=3.7'
-    traitlets: '>=4.3.1'
-    ipython: '>=6.1.0'
-    comm: '>=0.1.3'
-    jupyterlab_widgets: '>=3.0.9,<3.1.0'
-    widgetsnbextension: '>=4.0.9,<4.1.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/ipywidgets-8.1.1-pyhd8ed1ab_0.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-maps: '>=2.0_7'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-mapdata-2.3.1-r41h6d2157b_1.conda
   hash:
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-    sha256: 8136defec115396ba992273a77f814d74eeafd9cc099f5430d109c60785a7f02
+    md5: fafe313180101247f53a870871848c40
+    sha256: 41625367522224788dd59f2e0a61a584e8c24e77ed9fbbded5d1de99a44d28a4
   category: main
   optional: false
-- name: jupyter-cache
-  version: 0.6.1
+- name: r-mapdeck
+  version: 0.3.4
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    pyyaml: ''
-    click: ''
-    importlib-metadata: ''
-    tabulate: ''
-    nbformat: ''
-    attrs: ''
-    python: '>=3.8'
-    nbclient: '>=0.2,<0.8'
-    sqlalchemy: '>=1.3.12,<3'
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-cache-0.6.1-pyhd8ed1ab_0.conda
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+    r-colourvalues: '>=0.3.4'
+    r-geojsonsf: '>=1.3.3'
+    r-geometries: ''
+    r-googlepolylines: '>=0.7.2'
+    r-htmlwidgets: ''
+    r-jsonify: '>=1.1.1'
+    r-magrittr: ''
+    r-rapidjsonr: ''
+    r-rcpp: ''
+    r-sfheaders: '>=0.2.2'
+    r-shiny: ''
+    r-spatialwidget: '>=0.2.3'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-mapdeck-0.3.4-r43ha503ecb_3.conda
   hash:
-    md5: 2e360820ae68e3d28e1a5a9d2714ca5c
-    sha256: b22ba507904f33fcc7b218cc2a3ed8d39027524d0f223f3696b8344b7c5a1e1f
+    md5: 6ca03dc184c8269b5681b14d9a0c0911
+    sha256: c2d8e4f294d831b7736d5f84a78adb0f673017d12fcfe344d54795c4b70774d8
   category: main
   optional: false
-- name: mapclassify
-  version: 2.6.1
+- name: r-mapdeck
+  version: 0.3.4
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    python: '>=3.9'
-    scikit-learn: '>=1.0'
-    scipy: '>=1.8'
-    numpy: '>=1.23'
-    networkx: '>=2.7'
-    pandas: '>=1.4,!=1.5.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/mapclassify-2.6.1-pyhd8ed1ab_0.conda
+    libcxx: '>=15.0.7'
+    r-base: '>=4.3,<4.4.0a0'
+    r-colourvalues: '>=0.3.4'
+    r-geojsonsf: '>=1.3.3'
+    r-geometries: ''
+    r-googlepolylines: '>=0.7.2'
+    r-htmlwidgets: ''
+    r-jsonify: '>=1.1.1'
+    r-magrittr: ''
+    r-rapidjsonr: ''
+    r-rcpp: ''
+    r-sfheaders: '>=0.2.2'
+    r-shiny: ''
+    r-spatialwidget: '>=0.2.3'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-mapdeck-0.3.4-r43hac7d2d5_3.conda
   hash:
-    md5: 6aceae1ad4f16cf7b73ee04189947f98
-    sha256: 204ab8b242229d422b33cfec07ea61cefa8bd22375a16658afbabaafce031d64
+    md5: bbdac97f0caefca55c99e227897e9d19
+    sha256: 1c76a2163a8144416decd846872f9c808a15f251e6e4c360dcfa726fb419ff1f
   category: main
   optional: false
-- name: nbconvert-core
-  version: 7.9.2
+- name: r-mapdeck
+  version: 0.3.4
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    packaging: ''
-    beautifulsoup4: ''
-    defusedxml: ''
-    bleach: ''
-    tinycss2: ''
-    jupyterlab_pygments: ''
-    python: '>=3.8'
-    jinja2: '>=3.0'
-    entrypoints: '>=0.2.2'
-    traitlets: '>=5.0'
-    markupsafe: '>=2.0'
-    pandocfilters: '>=1.4.1'
-    jupyter_core: '>=4.7'
-    nbformat: '>=5.1'
-    pygments: '>=2.4.1'
-    nbclient: '>=0.5.0'
-    mistune: '>=2.0.3,<4'
-  url: https://conda.anaconda.org/conda-forge/noarch/nbconvert-core-7.9.2-pyhd8ed1ab_0.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-colourvalues: '>=0.3.4'
+    r-geojsonsf: '>=1.3.3'
+    r-geometries: ''
+    r-googlepolylines: '>=0.7.2'
+    r-htmlwidgets: ''
+    r-jsonify: '>=1.1.1'
+    r-magrittr: ''
+    r-rapidjsonr: ''
+    r-rcpp: ''
+    r-sfheaders: '>=0.2.2'
+    r-shiny: ''
+    r-spatialwidget: '>=0.2.3'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-mapdeck-0.3.4-r41ha856d6a_3.conda
   hash:
-    md5: 01e4314c780ca73759c694ce3ece281f
-    sha256: 2c85cf290cffb72b1fe7d24c22ad6bf89873bf0f562c9c51907dfb6c00f2d4dd
+    md5: 8ff79ac82f2a1a3cb7ec40461f3ba32a
+    sha256: 6f1d78109307f4334f9673f3f302fccf2574274066fccb58c6a8c702deb7d076
   category: main
   optional: false
-- name: nc-time-axis
-  version: 1.4.1
+- name: r-mapedit
+  version: 0.6.0
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    numpy: ''
-    matplotlib-base: ''
-    python: '>=3.7'
-    cftime: '>=1.5'
-  url: https://conda.anaconda.org/conda-forge/noarch/nc-time-axis-1.4.1-pyhd8ed1ab_0.tar.bz2
+    r-base: '>=4.3,<4.4.0a0'
+    r-dplyr: ''
+    r-htmltools: '>=0.3'
+    r-htmlwidgets: ''
+    r-jsonlite: ''
+    r-leaflet: '>=2.0.1'
+    r-leaflet.extras: '>=1.0'
+    r-leafpm: ''
+    r-mapview: ''
+    r-miniui: ''
+    r-sf: '>=0.5_2'
+    r-shiny: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/r-mapedit-0.6.0-r43h785f33e_3.conda
   hash:
-    md5: 281b58948bf60a2582de9e548bcc5369
-    sha256: 345d51b39f603a6717e43a998adaac35764467a4cf2bfec8f1963b9a7ced2a36
+    md5: 97f605947c9f6c10373222c37dab1093
+    sha256: ef59918cfb0499985d411778827bdf6abb3d45b9505961273bb04ae32613eaf2
   category: main
   optional: false
-- name: odvc
-  version: 1.0.0
+- name: r-mapedit
+  version: 0.6.0
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    numpy: ''
-    netcdf4: ''
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/odvc-1.0.0-pyhd8ed1ab_0.tar.bz2
+    r-dplyr: ''
+    r-jsonlite: ''
+    r-shiny: ''
+    r-htmlwidgets: ''
+    r-miniui: ''
+    r-mapview: ''
+    r-leafpm: ''
+    r-base: '>=4.3,<4.4.0a0'
+    r-htmltools: '>=0.3'
+    r-leaflet: '>=2.0.1'
+    r-sf: '>=0.5_2'
+    r-leaflet.extras: '>=1.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-mapedit-0.6.0-r43h785f33e_3.conda
   hash:
-    md5: 6363fc57e5b7782bf6e528f76a6b8e04
-    sha256: 6c3e360bfee859423b08a100e7f8ce65dd1b11eff920bb0e112af0ef0ec257cc
+    md5: 97f605947c9f6c10373222c37dab1093
+    sha256: ef59918cfb0499985d411778827bdf6abb3d45b9505961273bb04ae32613eaf2
   category: main
   optional: false
-- name: paegan
-  version: 1.1.4
+- name: r-mapedit
+  version: 0.6.0
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    python: ''
-    numpy: ''
-    scipy: ''
-    python-dateutil: ''
-    pytz: ''
-    shapely: ''
-    netcdf4: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/paegan-1.1.4-py_1.tar.bz2
+    r-dplyr: ''
+    r-jsonlite: ''
+    r-shiny: ''
+    r-htmlwidgets: ''
+    r-miniui: ''
+    r-mapview: ''
+    r-leafpm: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-htmltools: '>=0.3'
+    r-leaflet: '>=2.0.1'
+    r-sf: '>=0.5_2'
+    r-leaflet.extras: '>=1.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-mapedit-0.6.0-r41h785f33e_2.tar.bz2
   hash:
-    md5: 50677bb3024eb10e2823021bb9cfae93
-    sha256: bc3f17c0b310c828b4b36af5b253280fb27cb0e8d14b3776fc9fe13794b54dda
+    md5: 91753ccc055efe4bdc59d4e1a984cc7d
+    sha256: 2227bc56fa23c73f42a72a61557197a0a3df2daf267e7e5bf3d62a3a533770b6
   category: main
   optional: false
-- name: pandas-flavor
-  version: 0.2.0
+- name: r-maps
+  version: 3.4.2
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    python: ''
-    pandas: ''
-    xarray: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/pandas-flavor-0.2.0-py_0.tar.bz2
+    libgcc-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-maps-3.4.2-r43h57805ef_0.conda
   hash:
-    md5: 4e7641376dbfc2ca5abff209273ed37c
-    sha256: fc2c14956e5ef0dc855b70a157f95d259c2d877bd8f3afa7ac28a922fa7a6d37
+    md5: a8a9f2a4fc6692046eebb1d89860b94a
+    sha256: 7a9e523e7cd1af092bc77920b3e847025ea09315ad0ec8c1d3a20421fe5321d2
   category: main
   optional: false
-- name: panel
-  version: 1.3.0
+- name: r-maps
+  version: 3.4.2
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    requests: ''
-    typing_extensions: ''
-    packaging: ''
-    markdown: ''
-    bleach: ''
-    mdit-py-plugins: ''
-    markdown-it-py: ''
-    linkify-it-py: ''
-    python: '>=3.9'
-    tqdm: '>=4.48.0'
-    pyviz_comms: '>=0.7.4'
-    bokeh: '>=3.2.0,<3.4'
-    param: '>=2.0.0,<3'
-  url: https://conda.anaconda.org/conda-forge/noarch/panel-1.3.0-pyhd8ed1ab_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-maps-3.4.2-r43hb2c329c_0.conda
   hash:
-    md5: 2caee6ff4ab76e1b4f2e151cf7d18ccb
-    sha256: 831a7a22455cb7aab66e948fe0cd943b4976271dc9632ff89f05765d617bacfd
+    md5: a51957778bb8c9515465ba98384f57b6
+    sha256: ddc47504d7dae66a5e7082a4a701e1be46f1222b9fadb6fab966a4c3e484f28a
   category: main
   optional: false
-- name: pocean-core
-  version: 3.1.0
+- name: r-maps
+  version: 3.4.2
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    python-dateutil: ''
-    pytz: ''
-    netcdf4: ''
-    simplejson: ''
-    python: '>=3.7,<4.0'
-    numpy: '>=1.20'
-    pandas: '>=1.0.5'
-    shapely: '>=1.8'
-    cftime: '>=1.2.1'
-  url: https://conda.anaconda.org/conda-forge/noarch/pocean-core-3.1.0-pyhd8ed1ab_0.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-maps-3.4.2-r41h6d2157b_0.conda
   hash:
-    md5: ef77ed3dfbfed4ceb8ee883738706675
-    sha256: e7113cd9fdc5b3891b47a9c68cd3fbc04fa3d98704af2e1a23ada1f5d86b5be1
+    md5: 6459e91318c56027d56df38aca6d570a
+    sha256: 34b06e0069091edfe7820934564646dceabefde8760e089c5d396290b6274ebf
   category: main
   optional: false
-- name: pysgrid
-  version: 0.3.5
+- name: r-mapview
+  version: 2.11.2
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    python: ''
-    numpy: ''
-    netcdf4: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/pysgrid-0.3.5-py_0.tar.bz2
+    r-base: '>=4.3,<4.4.0a0'
+    r-base64enc: ''
+    r-htmltools: ''
+    r-htmlwidgets: ''
+    r-lattice: ''
+    r-leafem: ''
+    r-leaflet: '>=2.0.0'
+    r-leafpop: ''
+    r-png: ''
+    r-raster: ''
+    r-satellite: ''
+    r-scales: '>=0.2.5'
+    r-servr: ''
+    r-sf: ''
+    r-sp: ''
+    r-webshot: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/r-mapview-2.11.2-r43hc72bb7e_0.conda
   hash:
-    md5: 11eb6973e57bdf0f704955c9b706fd26
-    sha256: 8f5433af6e7e2bf740c1ed978860cd41c2e2814df05570883e7069256849fd4a
+    md5: 21d49cc1e6ee48f0593e1c644f5b81c5
+    sha256: 01b16fc2dfea68386bbce456042d9b68b760022dc92401a8bfd70d9703c2481c
   category: main
   optional: false
-- name: pyugrid
-  version: 0.3.1
+- name: r-mapview
+  version: 2.11.2
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    python: ''
-    numpy: ''
-    netcdf4: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/pyugrid-0.3.1-py_2.tar.bz2
+    r-htmltools: ''
+    r-base64enc: ''
+    r-lattice: ''
+    r-htmlwidgets: ''
+    r-sp: ''
+    r-sf: ''
+    r-raster: ''
+    r-png: ''
+    r-webshot: ''
+    r-servr: ''
+    r-leafem: ''
+    r-leafpop: ''
+    r-satellite: ''
+    r-base: '>=4.3,<4.4.0a0'
+    r-scales: '>=0.2.5'
+    r-leaflet: '>=2.0.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-mapview-2.11.2-r43hc72bb7e_0.conda
   hash:
-    md5: 7d7361886fbcf2be663fd185bf6d244d
-    sha256: c4a06b1efb1d91e01fbd2471bc5345e36fe24a5883250166ba48a0a7b21eaa2f
+    md5: 21d49cc1e6ee48f0593e1c644f5b81c5
+    sha256: 01b16fc2dfea68386bbce456042d9b68b760022dc92401a8bfd70d9703c2481c
   category: main
   optional: false
-- name: seaborn-base
-  version: 0.13.0
+- name: r-mapview
+  version: 2.11.0
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    python: '>=3.8'
-    pandas: '>=1.2'
-    scipy: '>=1.3'
-    matplotlib-base: '>=3.3,!=3.6.1'
-    numpy: '>=1.20,!=1.24.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.13.0-pyhd8ed1ab_0.conda
+    r-htmltools: ''
+    r-base64enc: ''
+    r-lattice: ''
+    r-htmlwidgets: ''
+    r-sp: ''
+    r-sf: ''
+    r-raster: ''
+    r-png: ''
+    r-webshot: ''
+    r-servr: ''
+    r-leafem: ''
+    r-leafpop: ''
+    r-satellite: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-scales: '>=0.2.5'
+    r-leaflet: '>=2.0.0'
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-- name: siphon
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   manager: conda
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+  platform: linux-64
   dependencies:
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+    r-mime: '>=0.3'
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-- name: statsmodels
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   manager: conda
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+  platform: osx-64
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-- name: thredds_crawler
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   manager: conda
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+  platform: win-64
   dependencies:
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+    r-mime: '>=0.3'
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-- name: windrose
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   manager: conda
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+  platform: linux-64
   dependencies:
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-- name: cc-plugin-glider
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   manager: conda
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+  platform: osx-64
   dependencies:
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-- name: cc-plugin-ncei
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   manager: conda
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+  platform: win-64
   dependencies:
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+    m2w64-gcc-libs-core: ''
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-- name: ctd
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   manager: conda
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+  platform: linux-64
   dependencies:
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+    liblapack: '>=3.9.0,<4.0a0'
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-- name: geopandas
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   manager: conda
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+  platform: osx-64
   dependencies:
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-    rtree: ''
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-    python: '>=3.9'
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+    libblas: '>=3.9.0,<4.0a0'
+    liblapack: '>=3.9.0,<4.0a0'
+    r-base: '>=4.3,<4.4.0a0'
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-- name: holoviews
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   manager: conda
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+  platform: win-64
   dependencies:
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-    colorcet: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/holoviews-1.18.0-pyhd8ed1ab_0.conda
+    libblas: '>=3.9.0,<4.0a0'
+    liblapack: '>=3.9.0,<4.0a0'
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-lattice: ''
+  url: https://conda.anaconda.org/conda-forge/win-64/r-matrix-1.6_5-r41hb9981e2_0.conda
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-- name: ipyleaflet
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   manager: conda
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+  platform: linux-64
   dependencies:
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-    traittypes: '>=0.2.1,<0.3.0'
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-    branca: '>=0.5.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/ipyleaflet-0.17.4-pyhd8ed1ab_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+    r-cachem: ''
+    r-rlang: '>=0.4.10'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-memoise-2.0.1-r43hc72bb7e_2.conda
   hash:
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-- name: ipyparallel
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+- name: r-memoise
+  version: 2.0.1
   manager: conda
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+  platform: osx-64
   dependencies:
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-    psutil: ''
-    decorator: ''
-    jupyter_client: ''
-    entrypoints: ''
-    python: '>=3.6'
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-  url: https://conda.anaconda.org/conda-forge/noarch/ipyparallel-8.6.1-pyhd8ed1ab_0.conda
+    r-cachem: ''
+    r-base: '>=4.3,<4.4.0a0'
+    r-rlang: '>=0.4.10'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-memoise-2.0.1-r43hc72bb7e_2.conda
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-- name: jupyter_console
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+  version: 2.0.1
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
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-    pygments: ''
-    python: '>=3.7'
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-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_console-6.6.3-pyhd8ed1ab_0.conda
+    r-cachem: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-rlang: '>=0.4.10'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-memoise-2.0.1-r41hc72bb7e_1.tar.bz2
   hash:
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   optional: false
-- name: jupyter_server
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+  version: '1.9_1'
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
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-    jinja2: ''
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-    argon2-cffi: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_server-2.9.1-pyhd8ed1ab_0.conda
+    _openmp_mutex: '>=4.5'
+    libblas: '>=3.9.0,<4.0a0'
+    libgcc-ng: '>=12'
+    liblapack: '>=3.9.0,<4.0a0'
+    r-base: '>=4.3,<4.4.0a0'
+    r-matrix: ''
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+  url: https://conda.anaconda.org/conda-forge/linux-64/r-mgcv-1.9_1-r43h316c678_0.conda
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   optional: false
-- name: nbconvert-pandoc
-  version: 7.9.2
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+  version: '1.9_1'
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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-    python: '>=3.8'
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-  url: https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.9.2-pyhd8ed1ab_0.conda
+    libblas: '>=3.9.0,<4.0a0'
+    liblapack: '>=3.9.0,<4.0a0'
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+    r-base: '>=4.3,<4.4.0a0'
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+  url: https://conda.anaconda.org/conda-forge/osx-64/r-mgcv-1.9_1-r43hc8b66e8_0.conda
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   optional: false
-- name: nbval
-  version: 0.10.0
+- name: r-mgcv
+  version: '1.9_1'
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
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-    pytest: ''
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-    coverage: ''
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/nbval-0.10.0-pyhd8ed1ab_0.conda
+    libblas: '>=3.9.0,<4.0a0'
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+    r-base: '>=4.1,<4.2.0a0'
+    r-matrix: ''
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+  url: https://conda.anaconda.org/conda-forge/win-64/r-mgcv-1.9_1-r41hb9981e2_0.conda
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-- name: pyoos
-  version: 0.8.4
+- name: r-mime
+  version: '0.12'
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    python: ''
-    numpy: ''
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-    fiona: ''
-    owslib: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/pyoos-0.8.4-py_1.tar.bz2
+    libgcc-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
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-- name: qtconsole-base
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   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
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+    zeromq: '>=4.3.5,<4.4.0a0'
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+  optional: false
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+  platform: osx-64
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+    r-base: '>=4.3,<4.4.0a0'
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+  platform: win-64
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+    zeromq: '>=4.3.5,<4.3.6.0a0'
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+    r-ellipsis: ''
+    r-fansi: ''
+    r-lifecycle: ''
+    r-rlang: '>=0.3.0'
+    r-utf8: '>=1.1.0'
+    r-vctrs: '>=0.2.0'
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+    r-lifecycle: ''
+    r-ellipsis: ''
+    r-fansi: ''
+    r-base: '>=4.3,<4.4.0a0'
+    r-rlang: '>=0.3.0'
+    r-crayon: '>=1.3.4'
+    r-vctrs: '>=0.2.0'
+    r-utf8: '>=1.1.0'
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+- name: r-pillar
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+  platform: win-64
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+    r-lifecycle: ''
+    r-ellipsis: ''
+    r-fansi: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-rlang: '>=0.3.0'
+    r-crayon: '>=1.3.4'
+    r-vctrs: '>=0.2.0'
+    r-utf8: '>=1.1.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-pillar-1.9.0-r41hc72bb7e_0.conda
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+    r-crayon: ''
+    r-desc: ''
+    r-prettyunits: ''
+    r-r6: ''
+    r-rprojroot: ''
+    r-withr: '>=2.1.2'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-pkgbuild-1.4.2-r43hc72bb7e_0.conda
+  hash:
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+    sha256: 7046454840937404ab519ee55c21cc19ae32fae7aad801b31e0e3abddc0163bf
+  category: main
+  optional: false
+- name: r-pkgbuild
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+  manager: conda
+  platform: osx-64
+  dependencies:
+    r-r6: ''
+    r-crayon: ''
+    r-cli: ''
+    r-desc: ''
+    r-rprojroot: ''
+    r-prettyunits: ''
+    r-base: '>=4.3,<4.4.0a0'
+    r-withr: '>=2.1.2'
+    r-callr: '>=3.2.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-pkgbuild-1.4.2-r43hc72bb7e_0.conda
+  hash:
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+  category: main
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+  manager: conda
+  platform: linux-64
+  dependencies:
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-pkgconfig-2.0.3-r43hc72bb7e_3.conda
+  hash:
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+    sha256: 1386c1a64451fd3220333f7cdad77c8baa797800cec3d9819e8c4b715559c979
+  category: main
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+- name: r-pkgconfig
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+  manager: conda
+  platform: osx-64
   dependencies:
-    python: '>=3.8'
-    nbconvert-core: 7.9.2
-    nbconvert-pandoc: 7.9.2
-  url: https://conda.anaconda.org/conda-forge/noarch/nbconvert-7.9.2-pyhd8ed1ab_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-pkgconfig-2.0.3-r43hc72bb7e_3.conda
   hash:
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   category: main
   optional: false
-- name: notebook-shim
-  version: 0.2.3
+- name: r-pkgconfig
+  version: 2.0.3
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    python: '>=3.7'
-    jupyter_server: '>=1.8,<3'
-  url: https://conda.anaconda.org/conda-forge/noarch/notebook-shim-0.2.3-pyhd8ed1ab_0.conda
+    r-base: '>=4.1,<4.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-pkgconfig-2.0.3-r41hc72bb7e_2.tar.bz2
   hash:
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-    sha256: f028d7ad1f2175cde307db08b60d07e371b9d6f035cfae6c81ea94b4c408c538
+    md5: fceb80e453285589b08efe53174ebe22
+    sha256: 73cea1b810690932495dc9ba057336f1360bc2947bd929019226e015e737215b
   category: main
   optional: false
-- name: oceans
-  version: 1.1.3
+- name: r-pkgload
+  version: 1.3.4
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    scipy: ''
-    shapely: ''
-    netcdf4: ''
-    gsw: ''
-    seawater: ''
-    ctd: ''
-    cmcrameri: ''
-    contourpy: ''
-    python: '>=3.8'
-    numpy: '>=1.20'
-    pandas: '>=1.0.1'
-    matplotlib-base: '>=3.6.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/oceans-1.1.3-pyhd8ed1ab_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+    r-cli: '>=3.3.0'
+    r-crayon: ''
+    r-desc: ''
+    r-fs: ''
+    r-glue: ''
+    r-pkgbuild: ''
+    r-rlang: '>=1.1.1'
+    r-rprojroot: ''
+    r-withr: '>=2.4.3'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-pkgload-1.3.4-r43hc72bb7e_0.conda
   hash:
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-    sha256: 4a68d942d1112c0608a41fb8951daa76583a415b98bd478e3633b0cc98ddea42
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+    sha256: 07bc29faf92c5ef3fc22ccd50377ec6c58202c2258bff5e1b6530bb33a361650
   category: main
   optional: false
-- name: sensorml2iso
-  version: 1.0.5
+- name: r-pkgload
+  version: 1.3.4
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    python: ''
-    numpy: ''
-    pandas: ''
-    jinja2: ''
-    lxml: ''
-    shapely: ''
-    geopandas: ''
-    owslib: ''
-    pyoos: '>=0.8.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/sensorml2iso-1.0.5-py_0.tar.bz2
+    r-glue: ''
+    r-crayon: ''
+    r-desc: ''
+    r-fs: ''
+    r-rprojroot: ''
+    r-pkgbuild: ''
+    r-base: '>=4.3,<4.4.0a0'
+    r-cli: '>=3.3.0'
+    r-withr: '>=2.4.3'
+    r-rlang: '>=1.1.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-pkgload-1.3.4-r43hc72bb7e_0.conda
   hash:
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-    sha256: 02a3e0ef2393fd9730b123ff85fef4ec0b12f3d33eaace9e7b736c2e8d9a5f05
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+    sha256: 07bc29faf92c5ef3fc22ccd50377ec6c58202c2258bff5e1b6530bb33a361650
   category: main
   optional: false
-- name: jupyterlab
-  version: 4.0.7
+- name: r-pkgload
+  version: 1.3.2
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    packaging: ''
-    traitlets: ''
-    tomli: ''
-    ipykernel: ''
-    jupyter_core: ''
-    python: '>=3.8'
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-    tornado: '>=6.2.0'
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-    notebook-shim: '>=0.2'
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyterlab-4.0.7-pyhd8ed1ab_0.conda
+    r-glue: ''
+    r-crayon: ''
+    r-desc: ''
+    r-fs: ''
+    r-rprojroot: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-rlang: '>=1.0.3'
+    r-cli: '>=3.3.0'
+    r-withr: '>=2.4.3'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-pkgload-1.3.2-r41hc72bb7e_0.tar.bz2
   hash:
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-    sha256: 1d841546fd239d7edefbf00edd3bad4680b12c3eb2549026d6aa70a301f23295
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   category: main
   optional: false
-- name: nbclassic
-  version: 1.0.0
+- name: r-plyr
+  version: 1.8.9
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    jinja2: ''
-    nbformat: ''
-    prometheus_client: ''
-    ipykernel: ''
-    ipython_genutils: ''
-    argon2-cffi: ''
-    python: '>=3.7'
-    tornado: '>=6.1'
-    pyzmq: '>=17'
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-  url: https://conda.anaconda.org/conda-forge/noarch/nbclassic-1.0.0-pyhb4ecaf3_1.conda
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+    r-rcpp: '>=0.11.0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-plyr-1.8.9-r43ha503ecb_0.conda
   hash:
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-    sha256: fc2b2e606ccbd0aaa2cdecdd33fc39e2c4bd7b5b96a64b89b3e6ad9ce20eec2f
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+    sha256: d86127a64226390cb9c106d38add3a69ec28de52748388dcbd4275f7bdcf4407
   category: main
   optional: false
-- name: nbdime
-  version: 3.2.1
+- name: r-plyr
+  version: 1.8.9
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    requests: ''
-    pygments: ''
-    colorama: ''
-    nbformat: ''
-    tornado: ''
-    jupyter_server: ''
-    python: '>=3.6'
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-  url: https://conda.anaconda.org/conda-forge/noarch/nbdime-3.2.1-pyhd8ed1ab_0.conda
+    libcxx: '>=15.0.7'
+    r-base: '>=4.3,<4.4.0a0'
+    r-rcpp: '>=0.11.0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-plyr-1.8.9-r43hac7d2d5_0.conda
   hash:
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-    sha256: ffd7d26af9174e1f4580f2aa2efaee6c7e8e26fa37d9804396f0852aaa49110c
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   category: main
   optional: false
-- name: octave_kernel
-  version: 0.35.1
+- name: r-plyr
+  version: 1.8.9
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    ipykernel: ''
-    python: '>=3.7'
-    jupyter_client: '>=4.3.0'
-    metakernel: '>=0.24.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/octave_kernel-0.35.1-pyhd8ed1ab_0.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-rcpp: '>=0.11.0'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-plyr-1.8.9-r41ha856d6a_0.conda
   hash:
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-    sha256: 016e83d410fda3fb94fa0f6d7e693ae6bbc1a52906dfd626256729d426295865
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   category: main
   optional: false
-- name: notebook
-  version: 7.0.6
+- name: r-png
+  version: '0.1_8'
   manager: conda
-  platform: osx-arm64
+  platform: linux-64
   dependencies:
-    python: '>=3.8'
-    tornado: '>=6.2.0'
-    jupyter_server: '>=2.4.0,<3'
-    jupyterlab_server: '>=2.22.1,<3'
-    notebook-shim: '>=0.2,<0.3'
-    jupyterlab: '>=4.0.7,<5'
-  url: https://conda.anaconda.org/conda-forge/noarch/notebook-7.0.6-pyhd8ed1ab_0.conda
+    libgcc-ng: '>=12'
+    libpng: '>=1.6.39,<1.7.0a0'
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-png-0.1_8-r43h81d01c5_1.conda
   hash:
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+    sha256: 1e51d61591c01dd134d4324d1db2aa5a45d7190b43d316a47c05dadf38efd47a
   category: main
   optional: false
-- name: oct2py
-  version: 5.6.0
+- name: r-png
+  version: '0.1_8'
   manager: conda
-  platform: osx-arm64
+  platform: osx-64
   dependencies:
-    numpy: ''
-    scipy: ''
-    ipython: ''
-    python: '>=3.6'
-    octave_kernel: '>=0.34.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/oct2py-5.6.0-pyha21a80b_0.conda
+    libpng: '>=1.6.39,<1.7.0a0'
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-png-0.1_8-r43h9ae9e50_1.conda
   hash:
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+    sha256: e31f80d1c1f1c0053c9956bf050762eb8d6ba5d0f2b9fa012e739ab02ccec77b
   category: main
   optional: false
-- name: jupyter
-  version: 1.0.0
+- name: r-png
+  version: '0.1_8'
   manager: conda
-  platform: osx-arm64
+  platform: win-64
   dependencies:
-    ipywidgets: ''
-    notebook: ''
-    ipykernel: ''
-    nbconvert: ''
-    jupyter_console: ''
-    qtconsole-base: ''
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-1.0.0-pyhd8ed1ab_10.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-png-0.1_8-r41h6d2157b_1.conda
   hash:
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   category: main
   optional: false
-- name: myst-parser
-  version: 0.18.1
+- name: r-praise
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-- name: font-ttf-inconsolata
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-- name: font-ttf-ubuntu
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-- name: msys2-conda-epoch
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-- name: phantomjs
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-- name: python_abi
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   manager: conda
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-  url: https://conda.anaconda.org/conda-forge/win-64/python_abi-3.12-4_cp312.conda
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-- name: tzdata
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   manager: conda
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-- name: ucrt
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-- name: winpty
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   manager: conda
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-- name: expat
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   manager: conda
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   dependencies:
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-- name: fonts-conda-forge
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   manager: conda
   platform: win-64
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-    font-ttf-ubuntu: ''
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-- name: m2w64-expat
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+  platform: linux-64
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-- name: m2w64-gmp
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+  platform: osx-64
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-- name: m2w64-gsl
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-- name: m2w64-libiconv
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-  url: https://conda.anaconda.org/conda-forge/win-64/m2w64-libiconv-1.14-6.tar.bz2
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-- name: m2w64-libogg
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+  platform: osx-64
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-- name: m2w64-libwinpthread-git
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   platform: win-64
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+  platform: linux-64
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-- name: vc14_runtime
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   manager: conda
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+  platform: osx-64
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-- name: fonts-conda-ecosystem
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   dependencies:
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-- name: m2w64-gcc-libs-core
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   manager: conda
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+  platform: linux-64
   dependencies:
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-- name: m2w64-mpfr
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+  platform: osx-64
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-- name: vc
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-- name: vs2015_runtime
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   manager: conda
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+  platform: linux-64
   dependencies:
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   manager: conda
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-- name: geos
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-- name: icu
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   manager: conda
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-- name: lerc
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   manager: conda
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-- name: libabseil
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-  url: https://conda.anaconda.org/conda-forge/win-64/libabseil-20230802.1-cxx17_h63175ca_0.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-plyr: '>=1.8.1'
+    r-rcpp: ''
+    r-stringr: ''
+  url: https://conda.anaconda.org/conda-forge/win-64/r-reshape2-1.4.4-r41ha856d6a_3.conda
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   optional: false
-- name: libaec
-  version: 1.1.2
+- name: r-rgdal
+  version: '1.6_7'
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-    vc: '>=14.2,<15'
-    vc14_runtime: '>=14.29.30139'
-  url: https://conda.anaconda.org/conda-forge/win-64/libaec-1.1.2-h63175ca_1.conda
+    __glibc: '>=2.17,<3.0.a0'
+    libgcc-ng: '>=12'
+    libgdal: '>=3.8.2,<3.9.0a0'
+    libstdcxx-ng: '>=12'
+    proj: '>=9.3.1,<9.3.2.0a0'
+    r-base: '>=4.3,<4.4.0a0'
+    r-sp: '>=1.1_0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-rgdal-1.6_7-r43h786f0a0_2.conda
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   category: main
   optional: false
-- name: libbrotlicommon
-  version: 1.1.0
+- name: r-rgdal
+  version: '1.6_7'
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-    vc: '>=14.2,<15'
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-  url: https://conda.anaconda.org/conda-forge/win-64/libbrotlicommon-1.1.0-hcfcfb64_1.conda
+    libcxx: '>=15'
+    libgdal: '>=3.8.2,<3.9.0a0'
+    proj: '>=9.3.1,<9.3.2.0a0'
+    r-base: '>=4.3,<4.4.0a0'
+    r-sp: '>=1.1_0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-rgdal-1.6_7-r43ha7a5594_2.conda
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   category: main
   optional: false
-- name: libdeflate
-  version: '1.19'
+- name: r-rgdal
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   manager: conda
   platform: win-64
   dependencies:
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-    vc: '>=14.2,<15'
-    vc14_runtime: '>=14.29.30139'
-  url: https://conda.anaconda.org/conda-forge/win-64/libdeflate-1.19-hcfcfb64_0.conda
+    r-base: '>=4.1,<4.2.0a0'
+    r-sp: '>=1.1_0'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-rgdal-1.6_6-r41h57928b3_6.conda
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   category: main
   optional: false
-- name: libffi
-  version: 3.4.2
+- name: r-rgeos
+  version: '0.6_4'
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    vc: '>=14.1,<15.0a0'
-    vs2015_runtime: '>=14.16.27012'
-  url: https://conda.anaconda.org/conda-forge/win-64/libffi-3.4.2-h8ffe710_5.tar.bz2
+    geos: '>=3.12.1,<3.12.2.0a0'
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+    r-sp: '>=1.1_0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-rgeos-0.6_4-r43h72d82f6_1.conda
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   category: main
   optional: false
-- name: libiconv
-  version: '1.17'
+- name: r-rgeos
+  version: '0.6_4'
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-    vs2015_runtime: '>=14.16.27033'
-  url: https://conda.anaconda.org/conda-forge/win-64/libiconv-1.17-h8ffe710_0.tar.bz2
+    __osx: '>=10.9'
+    geos: '>=3.12.1,<3.12.2.0a0'
+    libcxx: '>=16.0.6'
+    r-base: '>=4.3,<4.4.0a0'
+    r-sp: '>=1.1_0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-rgeos-0.6_4-r43h1f347b3_1.conda
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   optional: false
-- name: libjpeg-turbo
-  version: 3.0.0
+- name: r-rgeos
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   manager: conda
   platform: win-64
   dependencies:
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-    vc: '>=14.2,<15'
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-  url: https://conda.anaconda.org/conda-forge/win-64/libjpeg-turbo-3.0.0-hcfcfb64_1.conda
+    geos: '>=3.12.1,<3.12.2.0a0'
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-sp: '>=1.1_0'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-rgeos-0.6_4-r41hc4d305a_1.conda
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   category: main
   optional: false
-- name: libsodium
-  version: 1.0.18
+- name: r-rgexf
+  version: 0.16.2
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    vc: '>=14.1,<15.0a0'
-    vs2015_runtime: '>=14.16.27012'
-  url: https://conda.anaconda.org/conda-forge/win-64/libsodium-1.0.18-h8d14728_1.tar.bz2
+    r-base: '>=4.3,<4.4.0a0'
+    r-igraph: ''
+    r-servr: ''
+    r-xml: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/r-rgexf-0.16.2-r43hc72bb7e_2.conda
   hash:
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   optional: false
-- name: libspatialindex
-  version: 1.9.3
+- name: r-rgexf
+  version: 0.16.2
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/libspatialindex-1.9.3-h39d44d4_4.tar.bz2
+    r-igraph: ''
+    r-xml: ''
+    r-servr: ''
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-rgexf-0.16.2-r43hc72bb7e_2.conda
   hash:
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   optional: false
-- name: libsqlite
-  version: 3.43.2
+- name: r-rgexf
+  version: 0.16.2
   manager: conda
   platform: win-64
   dependencies:
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-    vc: '>=14.2,<15'
-    vc14_runtime: '>=14.29.30139'
-  url: https://conda.anaconda.org/conda-forge/win-64/libsqlite-3.43.2-hcfcfb64_0.conda
+    r-igraph: ''
+    r-xml: ''
+    r-servr: ''
+    r-base: '>=4.1,<4.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-rgexf-0.16.2-r41hc72bb7e_1.tar.bz2
   hash:
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   category: main
   optional: false
-- name: libudunits2
-  version: 2.2.28
+- name: r-rlang
+  version: 1.1.3
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    libexpat: '>=2.5.0,<3.0a0'
-    ucrt: '>=10.0.20348.0'
-    vc: '>=14.2,<15'
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-  url: https://conda.anaconda.org/conda-forge/win-64/libudunits2-2.2.28-hfda9870_3.conda
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-rlang-1.1.3-r43ha503ecb_0.conda
   hash:
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   category: main
   optional: false
-- name: libwebp-base
-  version: 1.3.2
+- name: r-rlang
+  version: 1.1.3
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-    vc: '>=14.2,<15'
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-  url: https://conda.anaconda.org/conda-forge/win-64/libwebp-base-1.3.2-hcfcfb64_0.conda
+    libcxx: '>=15'
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-rlang-1.1.3-r43h29979af_0.conda
   hash:
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   category: main
   optional: false
-- name: libzlib
-  version: 1.2.13
+- name: r-rlang
+  version: 1.1.3
   manager: conda
   platform: win-64
   dependencies:
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-    vc: '>=14.2,<15'
-    vc14_runtime: '>=14.29.30139'
-  url: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.2.13-hcfcfb64_5.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-rlang-1.1.3-r41ha856d6a_0.conda
   hash:
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+    sha256: 2be7fe93c31bd780425e8cf488679fd452371c2d3457b709f65fa0228bf6df9e
   category: main
   optional: false
-- name: lz4-c
-  version: 1.9.4
+- name: r-rmarkdown
+  version: '2.25'
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    ucrt: '>=10.0.20348.0'
-    vc: '>=14.2,<15'
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-  url: https://conda.anaconda.org/conda-forge/win-64/lz4-c-1.9.4-hcfcfb64_0.conda
+    pandoc: '>=1.14'
+    r-base: '>=4.3,<4.4.0a0'
+    r-bslib: '>=0.2.5.1'
+    r-evaluate: '>=0.13'
+    r-fontawesome: '>=0.5.0'
+    r-htmltools: '>=0.5.1'
+    r-jquerylib: ''
+    r-jsonlite: ''
+    r-knitr: '>=1.22'
+    r-stringr: '>=1.2.0'
+    r-tinytex: '>=0.31'
+    r-xfun: '>=0.36'
+    r-yaml: '>=2.1.19'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-rmarkdown-2.25-r43hc72bb7e_0.conda
   hash:
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   category: main
   optional: false
-- name: lzo
-  version: '2.10'
+- name: r-rmarkdown
+  version: '2.25'
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    vc: '>=14.1,<15.0a0'
-    vs2015_runtime: '>=14.16.27012'
-  url: https://conda.anaconda.org/conda-forge/win-64/lzo-2.10-he774522_1000.tar.bz2
+    r-jsonlite: ''
+    r-jquerylib: ''
+    r-base: '>=4.3,<4.4.0a0'
+    r-yaml: '>=2.1.19'
+    r-knitr: '>=1.22'
+    r-stringr: '>=1.2.0'
+    r-evaluate: '>=0.13'
+    r-htmltools: '>=0.5.1'
+    r-tinytex: '>=0.31'
+    r-bslib: '>=0.2.5.1'
+    r-fontawesome: '>=0.5.0'
+    r-xfun: '>=0.36'
+    pandoc: '>=1.14'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-rmarkdown-2.25-r43hc72bb7e_0.conda
   hash:
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   category: main
   optional: false
-- name: m2w64-gcc-libgfortran
-  version: 5.3.0
+- name: r-rmarkdown
+  version: '2.22'
   manager: conda
   platform: win-64
   dependencies:
-    m2w64-gcc-libs-core: ''
-    msys2-conda-epoch: '20160418'
-  url: https://conda.anaconda.org/conda-forge/win-64/m2w64-gcc-libgfortran-5.3.0-6.tar.bz2
+    r-jsonlite: ''
+    r-jquerylib: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-yaml: '>=2.1.19'
+    r-knitr: '>=1.22'
+    r-stringr: '>=1.2.0'
+    r-evaluate: '>=0.13'
+    r-htmltools: '>=0.5.1'
+    r-tinytex: '>=0.31'
+    r-bslib: '>=0.2.5.1'
+    pandoc: '>=1.14,<3.0'
+    r-fontawesome: '>=0.5.0'
+    r-xfun: '>=0.36'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-rmarkdown-2.22-r41hc72bb7e_0.conda
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   category: main
   optional: false
-- name: openssl
-  version: 3.1.4
+- name: r-robis
+  version: 2.11.3
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    ca-certificates: ''
-    ucrt: '>=10.0.20348.0'
-    vc: '>=14.2,<15'
-    vc14_runtime: '>=14.29.30139'
-  url: https://conda.anaconda.org/conda-forge/win-64/openssl-3.1.4-hcfcfb64_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+    r-curl: ''
+    r-data.table: ''
+    r-dplyr: ''
+    r-ggplot2: ''
+    r-httpcache: ''
+    r-httr: ''
+    r-jsonlite: ''
+    r-leaflet: ''
+    r-mapedit: ''
+    r-purrr: ''
+    r-rlang: ''
+    r-sf: ''
+    r-stringr: ''
+    r-tibble: ''
+    r-tidyr: ''
+    r-tidyselect: ''
+    r-xml2: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/r-robis-2.11.3-r43hc72bb7e_2.conda
   hash:
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   category: main
   optional: false
-- name: pixman
-  version: 0.42.2
+- name: r-robis
+  version: 2.11.3
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    ucrt: '>=10.0.20348.0'
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-  url: https://conda.anaconda.org/conda-forge/win-64/pixman-0.42.2-h63175ca_0.conda
+    r-rlang: ''
+    r-ggplot2: ''
+    r-dplyr: ''
+    r-tibble: ''
+    r-jsonlite: ''
+    r-purrr: ''
+    r-tidyr: ''
+    r-stringr: ''
+    r-data.table: ''
+    r-httr: ''
+    r-xml2: ''
+    r-tidyselect: ''
+    r-curl: ''
+    r-sf: ''
+    r-leaflet: ''
+    r-mapedit: ''
+    r-httpcache: ''
+    r-base: '>=4.3,<4.4.0a0'
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-- name: pthreads-win32
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   manager: conda
   platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/pthreads-win32-2.9.1-hfa6e2cd_3.tar.bz2
+    r-rlang: ''
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+    r-jsonlite: ''
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+    r-sf: ''
+    r-leaflet: ''
+    r-mapedit: ''
+    r-httpcache: ''
+    r-base: '>=4.1,<4.2.0a0'
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-- name: selenium-manager
-  version: 4.14.0
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   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/selenium-manager-4.14.0-h975169c_1.conda
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-rprojroot-2.0.4-r43hc72bb7e_0.conda
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-- name: snappy
-  version: 1.1.10
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   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/snappy-1.1.10-hfb803bf_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-rprojroot-2.0.4-r43hc72bb7e_0.conda
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-- name: tk
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   manager: conda
   platform: win-64
   dependencies:
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-    vc: '>=14.2,<15'
-    vc14_runtime: '>=14.29.30139'
-  url: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-hcfcfb64_0.conda
+    r-backports: ''
+    r-base: '>=4.1,<4.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-rprojroot-2.0.3-r41hc72bb7e_1.tar.bz2
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-- name: uriparser
-  version: 0.9.7
+- name: r-rstudioapi
+  version: 0.15.0
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/uriparser-0.9.7-h1537add_1.conda
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-rstudioapi-0.15.0-r43hc72bb7e_0.conda
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-- name: xerces-c
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+  version: 0.15.0
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/xerces-c-3.2.4-h63175ca_3.conda
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-rstudioapi-0.15.0-r43hc72bb7e_0.conda
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-- name: xz
-  version: 5.2.6
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   manager: conda
   platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/xz-5.2.6-h8d14728_0.tar.bz2
+    r-base: '>=4.1,<4.2.0a0'
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-- name: yaml
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+  version: 1.1.6
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    vc: '>=14.1,<15.0a0'
-    vs2015_runtime: '>=14.16.27012'
-  url: https://conda.anaconda.org/conda-forge/win-64/yaml-0.2.5-h8ffe710_2.tar.bz2
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    openssl: '>=3.2.0,<4.0a0'
+    r-base: '>=4.3,<4.4.0a0'
+    r-rcpp: ''
+    r-wk: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-s2-1.1.6-r43h5eac2b3_0.conda
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-- name: gettext
-  version: 0.21.1
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+  version: 1.1.6
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/gettext-0.21.1-h5728263_0.tar.bz2
+    libcxx: '>=15'
+    openssl: '>=3.2.0,<4.0a0'
+    r-base: '>=4.3,<4.4.0a0'
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+    r-wk: ''
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-s2-1.1.6-r43hf967310_0.conda
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   category: main
   optional: false
-- name: hdf4
-  version: 4.2.15
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   manager: conda
   platform: win-64
   dependencies:
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-    libzlib: '>=1.2.13,<1.3.0a0'
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-  url: https://conda.anaconda.org/conda-forge/win-64/hdf4-4.2.15-h5557f11_7.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    openssl: '>=3.2.0,<4.0a0'
+    r-base: '>=4.1,<4.2.0a0'
+    r-rcpp: ''
+    r-wk: ''
+  url: https://conda.anaconda.org/conda-forge/win-64/r-s2-1.1.6-r41h9b1ec75_0.conda
   hash:
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   category: main
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-- name: krb5
-  version: 1.21.2
+- name: r-sass
+  version: 0.4.8
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-    vc: '>=14.2,<15'
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-  url: https://conda.anaconda.org/conda-forge/win-64/krb5-1.21.2-heb0366b_0.conda
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+    r-digest: ''
+    r-fs: ''
+    r-htmltools: ''
+    r-r6: ''
+    r-rappdirs: ''
+    r-rlang: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-sass-0.4.8-r43ha503ecb_0.conda
   hash:
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   category: main
   optional: false
-- name: libbrotlidec
-  version: 1.1.0
+- name: r-sass
+  version: 0.4.8
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-    vc: '>=14.2,<15'
-    vc14_runtime: '>=14.29.30139'
-  url: https://conda.anaconda.org/conda-forge/win-64/libbrotlidec-1.1.0-hcfcfb64_1.conda
+    __osx: '>=10.9'
+    libcxx: '>=16.0.6'
+    r-base: '>=4.3,<4.4.0a0'
+    r-digest: ''
+    r-fs: ''
+    r-htmltools: ''
+    r-r6: ''
+    r-rappdirs: ''
+    r-rlang: ''
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-sass-0.4.8-r43h64b2c41_0.conda
   hash:
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   optional: false
-- name: libbrotlienc
-  version: 1.1.0
+- name: r-sass
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   manager: conda
   platform: win-64
   dependencies:
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-    ucrt: '>=10.0.20348.0'
-    vc: '>=14.2,<15'
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-  url: https://conda.anaconda.org/conda-forge/win-64/libbrotlienc-1.1.0-hcfcfb64_1.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-digest: ''
+    r-fs: ''
+    r-htmltools: ''
+    r-r6: ''
+    r-rappdirs: ''
+    r-rlang: ''
+  url: https://conda.anaconda.org/conda-forge/win-64/r-sass-0.4.8-r41ha856d6a_0.conda
   hash:
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   optional: false
-- name: libkml
-  version: 1.3.0
+- name: r-satellite
+  version: 1.0.5
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-    libexpat: '>=2.5.0,<3.0a0'
-    libzlib: '>=1.2.13,<1.3.0a0'
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-  url: https://conda.anaconda.org/conda-forge/win-64/libkml-1.3.0-haf3e7a6_1018.conda
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+    r-plyr: ''
+    r-raster: ''
+    r-rcpp: '>=0.10.3'
+    r-terra: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-satellite-1.0.5-r43ha503ecb_0.conda
   hash:
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   optional: false
-- name: libpng
-  version: 1.6.39
+- name: r-satellite
+  version: 1.0.5
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-    vc: '>=14.2,<15'
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-  url: https://conda.anaconda.org/conda-forge/win-64/libpng-1.6.39-h19919ed_0.conda
+    libcxx: '>=16'
+    r-base: '>=4.3,<4.4.0a0'
+    r-plyr: ''
+    r-raster: ''
+    r-rcpp: '>=0.10.3'
+    r-terra: ''
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-satellite-1.0.5-r43h29979af_0.conda
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   category: main
   optional: false
-- name: libprotobuf
-  version: 4.24.4
+- name: r-satellite
+  version: 1.0.5
   manager: conda
   platform: win-64
   dependencies:
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-    libzlib: '>=1.2.13,<1.3.0a0'
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-    vc14_runtime: '>=14.29.30139'
-  url: https://conda.anaconda.org/conda-forge/win-64/libprotobuf-4.24.4-hb8276f3_0.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-plyr: ''
+    r-raster: ''
+    r-rcpp: '>=0.10.3'
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+  url: https://conda.anaconda.org/conda-forge/win-64/r-satellite-1.0.5-r41ha856d6a_0.conda
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   optional: false
-- name: librttopo
-  version: 1.1.0
+- name: r-scales
+  version: 1.3.0
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/librttopo-1.1.0-h92c5fdb_14.conda
+    r-base: '>=4.3,<4.4.0a0'
+    r-farver: '>=2.0.0'
+    r-labeling: ''
+    r-lifecycle: ''
+    r-munsell: '>=0.5'
+    r-r6: ''
+    r-rcolorbrewer: ''
+    r-viridislite: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/r-scales-1.3.0-r43hc72bb7e_0.conda
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-- name: libssh2
-  version: 1.11.0
+- name: r-scales
+  version: 1.3.0
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/libssh2-1.11.0-h7dfc565_0.conda
+    r-r6: ''
+    r-lifecycle: ''
+    r-rcolorbrewer: ''
+    r-viridislite: ''
+    r-labeling: ''
+    r-base: '>=4.3,<4.4.0a0'
+    r-munsell: '>=0.5'
+    r-farver: '>=2.0.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-scales-1.3.0-r43hc72bb7e_0.conda
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   category: main
   optional: false
-- name: libxml2
-  version: 2.11.5
+- name: r-scales
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   manager: conda
   platform: win-64
   dependencies:
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-    libzlib: '>=1.2.13,<1.3.0a0'
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-  url: https://conda.anaconda.org/conda-forge/win-64/libxml2-2.11.5-hc3477c8_1.conda
+    r-r6: ''
+    r-lifecycle: ''
+    r-rcolorbrewer: ''
+    r-viridislite: ''
+    r-labeling: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-munsell: '>=0.5'
+    r-farver: '>=2.0.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-scales-1.2.1-r41hc72bb7e_1.tar.bz2
   hash:
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   category: main
   optional: false
-- name: libzip
-  version: 1.10.1
+- name: r-servr
+  version: '0.29'
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    bzip2: '>=1.0.8,<2.0a0'
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-    vc14_runtime: '>=14.29.30139'
-  url: https://conda.anaconda.org/conda-forge/win-64/libzip-1.10.1-h1d365fa_3.conda
+    r-base: '>=4.3,<4.4.0a0'
+    r-httpuv: '>=1.5.2'
+    r-jsonlite: ''
+    r-mime: '>=0.2'
+    r-xfun: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/r-servr-0.29-r43hc72bb7e_0.conda
   hash:
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-    sha256: 221698b52dd7a3dcfc67ff9460e9c8649fc6c86506a2a2ab6f57b97e7489bb9f
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   category: main
   optional: false
-- name: m2w64-gcc-libs
-  version: 5.3.0
+- name: r-servr
+  version: '0.29'
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    m2w64-gcc-libgfortran: ''
-    m2w64-gcc-libs-core: ''
-    m2w64-gmp: ''
-    m2w64-libwinpthread-git: ''
-    msys2-conda-epoch: '20160418'
-  url: https://conda.anaconda.org/conda-forge/win-64/m2w64-gcc-libs-5.3.0-7.tar.bz2
+    r-jsonlite: ''
+    r-xfun: ''
+    r-base: '>=4.3,<4.4.0a0'
+    r-httpuv: '>=1.5.2'
+    r-mime: '>=0.2'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-servr-0.29-r43hc72bb7e_0.conda
   hash:
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   category: main
   optional: false
-- name: pcre2
-  version: '10.40'
+- name: r-servr
+  version: '0.27'
   manager: conda
   platform: win-64
   dependencies:
-    bzip2: '>=1.0.8,<2.0a0'
-    libzlib: '>=1.2.12,<1.3.0a0'
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-  url: https://conda.anaconda.org/conda-forge/win-64/pcre2-10.40-h17e33f8_0.tar.bz2
+    r-jsonlite: ''
+    r-xfun: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-httpuv: '>=1.5.2'
+    r-mime: '>=0.2'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-servr-0.27-r41hc72bb7e_0.conda
   hash:
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   category: main
   optional: false
-- name: python
-  version: 3.12.0
+- name: r-sf
+  version: '1.0_15'
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    bzip2: '>=1.0.8,<2.0a0'
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-    vc: '>=14.2,<15'
-    vc14_runtime: '>=14.29.30139'
-    xz: '>=5.2.6,<6.0a0'
-    pip: ''
-  url: https://conda.anaconda.org/conda-forge/win-64/python-3.12.0-h2628c8c_0_cpython.conda
+    __glibc: '>=2.17,<3.0.a0'
+    geos: '>=3.12.1,<3.12.2.0a0'
+    libgcc-ng: '>=12'
+    libgdal: '>=3.8.2,<3.9.0a0'
+    libstdcxx-ng: '>=12'
+    proj: '>=9.3.1,<9.3.2.0a0'
+    r-base: '>=4.3,<4.4.0a0'
+    r-classint: '>=0.4_1'
+    r-dbi: '>=0.8'
+    r-magrittr: ''
+    r-rcpp: '>=0.12.18'
+    r-s2: '>=1.1.0'
+    r-units: '>=0.7_0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-sf-1.0_15-r43h538aadf_1.conda
   hash:
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   category: main
   optional: false
-- name: sqlite
-  version: 3.43.2
+- name: r-sf
+  version: '1.0_15'
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-    ucrt: '>=10.0.20348.0'
-    vc: '>=14.2,<15'
-    vc14_runtime: '>=14.29.30139'
-  url: https://conda.anaconda.org/conda-forge/win-64/sqlite-3.43.2-hcfcfb64_0.conda
+    geos: '>=3.12.1,<3.12.2.0a0'
+    libcxx: '>=15'
+    libgdal: '>=3.8.2,<3.9.0a0'
+    proj: '>=9.3.1,<9.3.2.0a0'
+    r-base: '>=4.3,<4.4.0a0'
+    r-classint: '>=0.4_1'
+    r-dbi: '>=0.8'
+    r-magrittr: ''
+    r-rcpp: '>=0.12.18'
+    r-s2: '>=1.1.0'
+    r-units: '>=0.7_0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-sf-1.0_15-r43ha6c789f_1.conda
   hash:
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   category: main
   optional: false
-- name: udunits2
-  version: 2.2.28
+- name: r-sf
+  version: '1.0_7'
   manager: conda
   platform: win-64
   dependencies:
-    libexpat: '>=2.5.0,<3.0a0'
-    libudunits2: 2.2.28
-    ucrt: '>=10.0.20348.0'
-    vc: '>=14.2,<15'
-    vc14_runtime: '>=14.29.30139'
-  url: https://conda.anaconda.org/conda-forge/win-64/udunits2-2.2.28-hfda9870_3.conda
+    m2w64-gcc-libs: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-classint: '>=0.4_1'
+    r-dbi: '>=0.8'
+    r-magrittr: ''
+    r-rcpp: '>=0.12.18'
+    r-s2: ''
+    r-units: '>=0.6_0'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-sf-1.0_7-r41ha856d6a_6.conda
   hash:
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   category: main
   optional: false
-- name: zeromq
-  version: 4.3.5
+- name: r-sfheaders
+  version: 0.4.4
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    libsodium: '>=1.0.18,<1.0.19.0a0'
-    ucrt: '>=10.0.20348.0'
-    vc: '>=14.2,<15'
-    vc14_runtime: '>=14.29.30139'
-  url: https://conda.anaconda.org/conda-forge/win-64/zeromq-4.3.5-h63175ca_0.conda
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+    r-geometries: '>=0.2.2'
+    r-rcpp: '>=1.0.10'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-sfheaders-0.4.4-r43ha503ecb_0.conda
   hash:
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-    sha256: f8377793c36e19da17bbb8cf517f1a969b89e1cc7cb9622dc6d60c3d1383c919
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   category: main
   optional: false
-- name: zlib
-  version: 1.2.13
+- name: r-sfheaders
+  version: 0.4.4
   manager: conda
-  platform: win-64
-  dependencies:
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-    ucrt: '>=10.0.20348.0'
-    vc: '>=14.2,<15'
-    vc14_runtime: '>=14.29.30139'
-  url: https://conda.anaconda.org/conda-forge/win-64/zlib-1.2.13-hcfcfb64_5.conda
+  platform: osx-64
+  dependencies:
+    libcxx: '>=15'
+    r-base: '>=4.3,<4.4.0a0'
+    r-geometries: '>=0.2.2'
+    r-rcpp: '>=1.0.10'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-sfheaders-0.4.4-r43h29979af_0.conda
   hash:
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+    sha256: 07117aecd75268647f5962192607be6188a018f552b6bd2aecb9e1d4092b2222
   category: main
   optional: false
-- name: zstd
-  version: 1.5.5
+- name: r-sfheaders
+  version: 0.4.4
   manager: conda
   platform: win-64
   dependencies:
-    libzlib: '>=1.2.13,<1.3.0a0'
-    ucrt: '>=10.0.20348.0'
-    vc: '>=14.2,<15'
-    vc14_runtime: '>=14.29.30139'
-  url: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.5-h12be248_0.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-geometries: '>=0.2.2'
+    r-rcpp: '>=1.0.10'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-sfheaders-0.4.4-r41ha856d6a_0.conda
   hash:
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   category: main
   optional: false
-- name: affine
-  version: 2.4.0
+- name: r-shiny
+  version: 1.8.0
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/affine-2.4.0-pyhd8ed1ab_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+    r-bslib: '>=0.3.0'
+    r-cachem: ''
+    r-commonmark: '>=1.7'
+    r-crayon: ''
+    r-ellipsis: ''
+    r-fastmap: '>=1.1.0'
+    r-fontawesome: '>=0.2.1'
+    r-glue: '>=1.3.2'
+    r-htmltools: '>=0.5.2'
+    r-httpuv: '>=1.5.2'
+    r-jsonlite: '>=0.9.16'
+    r-later: '>=1.0.0'
+    r-lifecycle: '>=0.2.0'
+    r-mime: '>=0.3'
+    r-promises: '>=1.1.0'
+    r-r6: '>=2.0'
+    r-rlang: '>=0.4.10'
+    r-sourcetools: ''
+    r-withr: ''
+    r-xtable: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/r-shiny-1.8.0-r43h785f33e_0.conda
   hash:
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-    sha256: fbf0288cae7c6e5005280436ff73c95a36c5a4c978ba50175cc8e3eb22abc5f9
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+    sha256: 159c4d2b9f3b119c863d2561ffbb07ebe184da12080ea18e977d75bed3c77c8f
   category: main
   optional: false
-- name: alabaster
-  version: 0.7.13
+- name: r-shiny
+  version: 1.8.0
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/alabaster-0.7.13-pyhd8ed1ab_0.conda
+    r-withr: ''
+    r-crayon: ''
+    r-ellipsis: ''
+    r-xtable: ''
+    r-cachem: ''
+    r-sourcetools: ''
+    r-base: '>=4.3,<4.4.0a0'
+    r-rlang: '>=0.4.10'
+    r-jsonlite: '>=0.9.16'
+    r-lifecycle: '>=0.2.0'
+    r-httpuv: '>=1.5.2'
+    r-commonmark: '>=1.7'
+    r-mime: '>=0.3'
+    r-htmltools: '>=0.5.2'
+    r-promises: '>=1.1.0'
+    r-later: '>=1.0.0'
+    r-glue: '>=1.3.2'
+    r-fastmap: '>=1.1.0'
+    r-r6: '>=2.0'
+    r-bslib: '>=0.3.0'
+    r-fontawesome: '>=0.2.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-shiny-1.8.0-r43h785f33e_0.conda
   hash:
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-    sha256: b2d160a050996950434c6e87a174fc01c4a937cbeffbdd20d1b46126b4478a95
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+    sha256: 159c4d2b9f3b119c863d2561ffbb07ebe184da12080ea18e977d75bed3c77c8f
   category: main
   optional: false
-- name: antlr-python-runtime
-  version: 4.11.1
+- name: r-shiny
+  version: 1.7.4
   manager: conda
   platform: win-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/antlr-python-runtime-4.11.1-pyhd8ed1ab_0.tar.bz2
+    r-withr: ''
+    r-crayon: ''
+    r-ellipsis: ''
+    r-xtable: ''
+    r-cachem: ''
+    r-sourcetools: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-rlang: '>=0.4.10'
+    r-jsonlite: '>=0.9.16'
+    r-lifecycle: '>=0.2.0'
+    r-httpuv: '>=1.5.2'
+    r-commonmark: '>=1.7'
+    r-mime: '>=0.3'
+    r-htmltools: '>=0.5.2'
+    r-promises: '>=1.1.0'
+    r-later: '>=1.0.0'
+    r-glue: '>=1.3.2'
+    r-fastmap: '>=1.1.0'
+    r-r6: '>=2.0'
+    r-bslib: '>=0.3.0'
+    r-fontawesome: '>=0.2.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-shiny-1.7.4-r41h785f33e_0.conda
   hash:
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-    sha256: 1a2b5dabf00acfa8e34211a2c3b29d261f9eae0511facd24febc1f74095bdaaf
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   category: main
   optional: false
-- name: asciitree
-  version: 0.3.3
+- name: r-sourcetools
+  version: 0.1.7_1
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-- name: backcall
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   dependencies:
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-- name: backports
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   manager: conda
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   dependencies:
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-- name: bagit
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   manager: conda
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+  platform: osx-64
   dependencies:
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-- name: blosc
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-- name: brotli-bin
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+  platform: linux-64
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+    r-sfheaders: '>=0.4.4'
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-- name: brotli-python
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-- name: cached_property
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   manager: conda
   platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/cached_property-1.5.2-pyha770c72_1.tar.bz2
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-- name: certifi
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   manager: conda
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+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/certifi-2023.7.22-pyhd8ed1ab_0.conda
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-- name: cfgv
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   manager: conda
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+  platform: osx-64
   dependencies:
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-- name: chardet
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   platform: win-64
   dependencies:
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-- name: charset-normalizer
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   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/charset-normalizer-3.3.1-pyhd8ed1ab_0.conda
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-- name: colorama
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   dependencies:
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-- name: cycler
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   platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/cycler-0.12.1-pyhd8ed1ab_0.conda
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-- name: cython
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   manager: conda
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   dependencies:
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-- name: dataclasses
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   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/dataclasses-0.8-pyhc8e2a94_3.tar.bz2
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-- name: debugpy
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-- name: decorator
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   manager: conda
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   dependencies:
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+    libgcc-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-sys-3.4.2-r43h57805ef_1.conda
   hash:
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   category: main
   optional: false
-- name: defusedxml
-  version: 0.7.1
+- name: r-sys
+  version: 3.4.2
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/defusedxml-0.7.1-pyhd8ed1ab_0.tar.bz2
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-sys-3.4.2-r43h6dc245f_1.conda
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   category: main
   optional: false
-- name: distlib
-  version: 0.3.7
+- name: r-sys
+  version: 3.4.2
   manager: conda
   platform: win-64
   dependencies:
-    python: 2.7|>=3.6
-  url: https://conda.anaconda.org/conda-forge/noarch/distlib-0.3.7-pyhd8ed1ab_0.conda
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-sys-3.4.2-r41h6d2157b_1.conda
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   category: main
   optional: false
-- name: docopt
-  version: 0.6.2
+- name: r-systemfonts
+  version: 1.0.5
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    python: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/docopt-0.6.2-py_1.tar.bz2
+    freetype: '>=2.12.1,<3.0a0'
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+    r-cpp11: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-systemfonts-1.0.5-r43haf97adc_0.conda
   hash:
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-    sha256: 4bbfb8ab343b4711223aedf797a2678955412124e71415dc2fe9816248f0b28d
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   optional: false
-- name: docutils
-  version: 0.17.1
+- name: r-systemfonts
+  version: 1.0.5
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    python: '>=3.12.0rc3,<3.13.0a0'
-    python_abi: 3.12.*
-  url: https://conda.anaconda.org/conda-forge/win-64/docutils-0.17.1-py312h2e8e312_4.conda
+    __osx: '>=10.9'
+    freetype: '>=2.12.1,<3.0a0'
+    libcxx: '>=16.0.6'
+    r-base: '>=4.3,<4.4.0a0'
+    r-cpp11: ''
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-systemfonts-1.0.5-r43hac8360d_0.conda
   hash:
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-    sha256: bf3da9128e684f9d46c01a0bfe2da3520fb14a5f55cc999881fe1266b9ac243f
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   category: main
   optional: false
-- name: entrypoints
-  version: '0.4'
+- name: r-systemfonts
+  version: 1.0.5
   manager: conda
   platform: win-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/entrypoints-0.4-pyhd8ed1ab_0.tar.bz2
+    freetype: '>=2.12.1,<3.0a0'
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-cpp11: ''
+  url: https://conda.anaconda.org/conda-forge/win-64/r-systemfonts-1.0.5-r41h93c4b31_0.conda
   hash:
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+    sha256: 62498a43b60bb4bd62c18a7e7d3a7754268cb0020a910c8d72536e2f98968520
   category: main
   optional: false
-- name: exceptiongroup
-  version: 1.1.3
+- name: r-terra
+  version: '1.7_71'
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/exceptiongroup-1.1.3-pyhd8ed1ab_0.conda
+    geos: '>=3.12.1,<3.12.2.0a0'
+    libgcc-ng: '>=12'
+    libgdal: '>=3.8.3,<3.9.0a0'
+    libstdcxx-ng: '>=12'
+    proj: '>=9.3.1,<9.3.2.0a0'
+    r-base: '>=4.3,<4.4.0a0'
+    r-rcpp: '>=1.0_10'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-terra-1.7_71-r43h81f2993_0.conda
   hash:
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   category: main
   optional: false
-- name: executing
-  version: 2.0.1
+- name: r-terra
+  version: '1.7_71'
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    python: '>=2.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/executing-2.0.1-pyhd8ed1ab_0.conda
+    geos: '>=3.12.1,<3.12.2.0a0'
+    libcxx: '>=15'
+    libgdal: '>=3.8.3,<3.9.0a0'
+    proj: '>=9.3.1,<9.3.2.0a0'
+    r-base: '>=4.3,<4.4.0a0'
+    r-rcpp: '>=1.0_10'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-terra-1.7_71-r43ha6c789f_0.conda
   hash:
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-    sha256: c738804ab1e6376f8ea63372229a04c8d658dc90fd5a218c6273a2eaf02f4057
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+    sha256: 5d491a303feb39464e1e456a983d4d0754d053a012813dfda4baaaf7b9d883f1
   category: main
   optional: false
-- name: fasteners
-  version: 0.17.3
+- name: r-terra
+  version: '1.5_21'
   manager: conda
   platform: win-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/fasteners-0.17.3-pyhd8ed1ab_0.tar.bz2
+    m2w64-gcc-libs: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-rcpp: ''
+  url: https://conda.anaconda.org/conda-forge/win-64/r-terra-1.5_21-r41ha856d6a_8.conda
   hash:
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-    sha256: 42be6ac8478051b26751d778490d6a71de12e5c6443e145ff3eddbc577d9bcda
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+    sha256: 9476f6be70c9abb3985a6e506f0411373ead38acd7852f75ef64401ec2a9099e
   category: main
   optional: false
-- name: filelock
-  version: 3.13.0
+- name: r-testthat
+  version: 3.2.1
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/filelock-3.13.0-pyhd8ed1ab_0.conda
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+    r-brio: ''
+    r-callr: '>=3.5.1'
+    r-cli: ''
+    r-crayon: '>=1.3.4'
+    r-desc: ''
+    r-digest: ''
+    r-ellipsis: '>=0.2.0'
+    r-evaluate: ''
+    r-jsonlite: ''
+    r-lifecycle: ''
+    r-magrittr: ''
+    r-pkgload: ''
+    r-praise: ''
+    r-processx: ''
+    r-ps: '>=1.3.4'
+    r-r6: '>=2.2.0'
+    r-rlang: '>=0.4.1'
+    r-waldo: '>=0.2.1'
+    r-withr: '>=2.0.0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-testthat-3.2.1-r43ha503ecb_0.conda
   hash:
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-    sha256: b26fb8c446773268a7ec8c33bc5e39fc9ff4679b76f214aa44596b4e666569a0
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   category: main
   optional: false
-- name: freetype
-  version: 2.12.1
+- name: r-testthat
+  version: 3.2.1
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    libpng: '>=1.6.39,<1.7.0a0'
-    libzlib: '>=1.2.13,<1.3.0a0'
-    ucrt: '>=10.0.20348.0'
-    vc: '>=14.2,<15'
-    vc14_runtime: '>=14.29.30139'
-  url: https://conda.anaconda.org/conda-forge/win-64/freetype-2.12.1-hdaf720e_2.conda
+    __osx: '>=10.9'
+    libcxx: '>=16.0.6'
+    r-base: '>=4.3,<4.4.0a0'
+    r-brio: ''
+    r-callr: '>=3.5.1'
+    r-cli: ''
+    r-crayon: '>=1.3.4'
+    r-desc: ''
+    r-digest: ''
+    r-ellipsis: '>=0.2.0'
+    r-evaluate: ''
+    r-jsonlite: ''
+    r-lifecycle: ''
+    r-magrittr: ''
+    r-pkgload: ''
+    r-praise: ''
+    r-processx: ''
+    r-ps: '>=1.3.4'
+    r-r6: '>=2.2.0'
+    r-rlang: '>=0.4.1'
+    r-waldo: '>=0.2.1'
+    r-withr: '>=2.0.0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-testthat-3.2.1-r43h64b2c41_0.conda
   hash:
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-    sha256: 2c53ee8879e05e149a9e525481d36adfd660a6abda26fd731376fa64ff03e728
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   category: main
   optional: false
-- name: geographiclib
-  version: '1.52'
+- name: r-testthat
+  version: 3.2.1
   manager: conda
   platform: win-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/geographiclib-1.52-pyhd8ed1ab_0.tar.bz2
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-brio: ''
+    r-callr: '>=3.5.1'
+    r-cli: ''
+    r-crayon: '>=1.3.4'
+    r-desc: ''
+    r-digest: ''
+    r-ellipsis: '>=0.2.0'
+    r-evaluate: ''
+    r-jsonlite: ''
+    r-lifecycle: ''
+    r-magrittr: ''
+    r-pkgload: ''
+    r-praise: ''
+    r-processx: ''
+    r-ps: '>=1.3.4'
+    r-r6: '>=2.2.0'
+    r-rlang: '>=0.4.1'
+    r-waldo: '>=0.2.1'
+    r-withr: '>=2.0.0'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-testthat-3.2.1-r41ha856d6a_0.conda
   hash:
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   category: main
   optional: false
-- name: geojson
-  version: 2.5.0
+- name: r-tibble
+  version: 3.2.1
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    python: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/geojson-2.5.0-py_0.tar.bz2
+    libgcc-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+    r-fansi: '>=0.4.0'
+    r-lifecycle: '>=1.0.0'
+    r-magrittr: ''
+    r-pillar: '>=1.8.1'
+    r-pkgconfig: ''
+    r-rlang: '>=1.0.2'
+    r-vctrs: '>=0.4.2'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-tibble-3.2.1-r43h57805ef_2.conda
   hash:
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-    sha256: d5978675ee8e59b28b0b4fbb78392447d11c030c072cef829dd7c8f9329462ad
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+    sha256: ecb1c7a1fd41f5a8fc4d89bdaef49b986507dd2186f4c94c574ef192a9fdee17
   category: main
   optional: false
-- name: greenlet
-  version: 3.0.1
+- name: r-tibble
+  version: 3.2.1
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    python: '>=3.12,<3.13.0a0'
-    python_abi: 3.12.*
-    ucrt: '>=10.0.20348.0'
-    vc: '>=14.2,<15'
-    vc14_runtime: '>=14.29.30139'
-  url: https://conda.anaconda.org/conda-forge/win-64/greenlet-3.0.1-py312h53d5487_0.conda
+    r-base: '>=4.3,<4.4.0a0'
+    r-fansi: '>=0.4.0'
+    r-lifecycle: '>=1.0.0'
+    r-magrittr: ''
+    r-pillar: '>=1.8.1'
+    r-pkgconfig: ''
+    r-rlang: '>=1.0.2'
+    r-vctrs: '>=0.4.2'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-tibble-3.2.1-r43h6dc245f_2.conda
   hash:
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-    sha256: efe469288e72c59c848a417f75477c204aa864bce117a748a6109bc3071bdb5a
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   category: main
   optional: false
-- name: hpack
-  version: 4.0.0
+- name: r-tibble
+  version: 3.2.1
   manager: conda
   platform: win-64
   dependencies:
-    python: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/hpack-4.0.0-pyh9f0ad1d_0.tar.bz2
+    m2w64-gcc-libs: ''
+    m2w64-gcc-libs-core: ''
+    r-base: '>=4.1,<4.2.0a0'
+    r-fansi: '>=0.4.0'
+    r-lifecycle: '>=1.0.0'
+    r-magrittr: ''
+    r-pillar: '>=1.8.1'
+    r-pkgconfig: ''
+    r-rlang: '>=1.0.2'
+    r-vctrs: '>=0.4.2'
+  url: https://conda.anaconda.org/conda-forge/win-64/r-tibble-3.2.1-r41h6d2157b_2.conda
   hash:
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   category: main
   optional: false
-- name: humanize
-  version: 4.8.0
+- name: r-tidyr
+  version: 1.3.1
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/humanize-4.8.0-pyhd8ed1ab_0.conda
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+    r-cli: '>=3.4.1'
+    r-dplyr: '>=1.0.10'
+    r-glue: ''
+    r-lifecycle: '>=1.0.3'
+    r-magrittr: ''
+    r-purrr: '>=1.0.1'
+    r-rlang: '>=1.0.4'
+    r-stringr: '>=1.5.0'
+    r-tibble: '>=2.1.1'
+    r-tidyselect: '>=1.2.0'
+    r-vctrs: '>=0.5.2'
+  url: https://conda.anaconda.org/conda-forge/linux-64/r-tidyr-1.3.1-r43ha503ecb_0.conda
   hash:
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+    sha256: f6c61bfb64c666c70b353bb4fbad1c50604befdcd922176177d50d74273f1336
   category: main
   optional: false
-- name: hyperframe
-  version: 6.0.1
+- name: r-tidyr
+  version: 1.3.1
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/hyperframe-6.0.1-pyhd8ed1ab_0.tar.bz2
+    libcxx: '>=15'
+    r-base: '>=4.3,<4.4.0a0'
+    r-cli: '>=3.4.1'
+    r-dplyr: '>=1.0.10'
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+    r-lifecycle: '>=1.0.3'
+    r-magrittr: ''
+    r-purrr: '>=1.0.1'
+    r-rlang: '>=1.0.4'
+    r-stringr: '>=1.5.0'
+    r-tibble: '>=2.1.1'
+    r-tidyselect: '>=1.2.0'
+    r-vctrs: '>=0.5.2'
+  url: https://conda.anaconda.org/conda-forge/osx-64/r-tidyr-1.3.1-r43h29979af_0.conda
   hash:
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-- name: iniconfig
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-- name: jsonpointer
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   manager: conda
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-- name: jupyterlab_widgets
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   manager: conda
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-- name: libarchive
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   manager: conda
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-- name: libcurl
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-- name: libhwloc
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-- name: libpq
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-- name: libtiff
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-- name: libxslt
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-- name: m2w64-bzip2
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   dependencies:
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-- name: m2w64-fftw
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   manager: conda
-  platform: win-64
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   dependencies:
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   manager: conda
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-- name: msgpack-python
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-- name: munkres
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-- name: nest-asyncio
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-- name: networkx
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-- name: packaging
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-- name: palettable
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-- name: pandocfilters
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   platform: win-64
   dependencies:
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+    r-ggplot2: '>=1.0.1'
+    r-viridislite: '>=0.4.0'
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-- name: param
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   manager: conda
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+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/param-2.0.0-pyhca7485f_0.conda
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-- name: parso
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   manager: conda
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/parso-0.8.3-pyhd8ed1ab_0.tar.bz2
+    r-base: '>=4.3,<4.4.0a0'
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-- name: pickleshare
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   manager: conda
   platform: win-64
   dependencies:
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-- name: pkgutil-resolve-name
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   manager: conda
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+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/pkgutil-resolve-name-1.3.10-pyhd8ed1ab_1.conda
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+    r-htmltools: ''
+    r-htmlwidgets: ''
+    r-jsonlite: ''
+    r-magrittr: ''
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-- name: pluggy
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   manager: conda
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/pluggy-1.3.0-pyhd8ed1ab_0.conda
+    r-magrittr: ''
+    r-jsonlite: ''
+    r-htmltools: ''
+    r-htmlwidgets: ''
+    r-base: '>=4.3,<4.4.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/r-visnetwork-2.1.2-r43hc72bb7e_2.conda
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-- name: prometheus_client
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   manager: conda
   platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/prometheus_client-0.17.1-pyhd8ed1ab_0.conda
+    r-magrittr: ''
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+    r-htmltools: ''
+    r-htmlwidgets: ''
+    r-base: '>=4.1,<4.2.0a0'
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-- name: psutil
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   manager: conda
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+  platform: linux-64
   dependencies:
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-    python_abi: 3.12.*
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-  url: https://conda.anaconda.org/conda-forge/win-64/psutil-5.9.5-py312he70551f_1.conda
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
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+    r-tzdb: '>=0.1.1'
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-- name: pthread-stubs
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/pthread-stubs-0.4-hcd874cb_1001.tar.bz2
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+    r-tzdb: '>=0.1.1'
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-- name: ptyprocess
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   manager: conda
   platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/ptyprocess-0.7.0-pyhd3deb0d_0.tar.bz2
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-- name: pure_eval
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   manager: conda
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+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/pure_eval-0.2.2-pyhd8ed1ab_0.tar.bz2
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-- name: pycodestyle
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-  url: https://conda.anaconda.org/conda-forge/noarch/pycodestyle-2.11.1-pyhd8ed1ab_0.conda
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-- name: pycparser
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   manager: conda
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   dependencies:
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-- name: pyflakes
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   manager: conda
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+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/pyflakes-3.1.0-pyhd8ed1ab_0.conda
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-- name: pygments
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   dependencies:
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-- name: pyjwt
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   platform: win-64
   dependencies:
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-- name: pyparsing
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   manager: conda
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+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/pyparsing-3.1.1-pyhd8ed1ab_0.conda
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-- name: pyshp
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   manager: conda
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   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/pyshp-2.3.1-pyhd8ed1ab_0.tar.bz2
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-- name: python-fastjsonschema
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   platform: win-64
   dependencies:
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-- name: python-tzdata
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-- name: rfc3986-validator
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-- name: simplekml
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-- name: sniffio
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-- name: snowballstemmer
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-- name: sortedcontainers
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   manager: conda
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+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/sortedcontainers-2.4.0-pyhd8ed1ab_0.tar.bz2
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-- name: soupsieve
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   manager: conda
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/soupsieve-2.5-pyhd8ed1ab_1.conda
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-- name: sphinxcontrib-jsmath
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   platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-jsmath-1.0.1-pyhd8ed1ab_0.conda
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-- name: tabulate
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   manager: conda
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+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/tabulate-0.9.0-pyhd8ed1ab_1.tar.bz2
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-- name: threadpoolctl
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   manager: conda
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/threadpoolctl-3.2.0-pyha21a80b_0.conda
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-- name: tiledb
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-  url: https://conda.anaconda.org/conda-forge/win-64/tiledb-2.16.3-h1ffc264_3.conda
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+    m2w64-gcc-libs-core: ''
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-- name: tomli
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   manager: conda
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+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/tomli-2.0.1-pyhd8ed1ab_0.tar.bz2
+    libgcc-ng: '>=12'
+    r-base: '>=4.3,<4.4.0a0'
+    r-lattice: '>=0.20_27'
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-- name: tornado
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   manager: conda
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/tornado-6.3.3-py312he70551f_1.conda
+    r-base: '>=4.3,<4.4.0a0'
+    r-lattice: '>=0.20_27'
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-- name: traitlets
-  version: 5.12.0
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   manager: conda
   platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/traitlets-5.12.0-pyhd8ed1ab_0.conda
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+    m2w64-gcc-libs-core: ''
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+    r-lattice: '>=0.20_27'
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-- name: types-python-dateutil
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   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/types-python-dateutil-2.8.19.14-pyhd8ed1ab_0.conda
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+    libgdal: '>=3.8.1,<3.9.0a0'
+    libstdcxx-ng: '>=12'
+    numpy: '>=1.26.2,<2.0a0'
+    proj: '>=9.3.1,<9.3.2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    setuptools: '>=0.9.8'
+    snuggs: '>=1.4.1'
+  url: https://conda.anaconda.org/conda-forge/linux-64/rasterio-1.3.9-py312h26ef92c_2.conda
   hash:
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-- name: typing_extensions
-  version: 4.8.0
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   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.8.0-pyha770c72_0.conda
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+    proj: '>=9.3.1,<9.3.2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    setuptools: '>=0.9.8'
+    snuggs: '>=1.4.1'
+  url: https://conda.anaconda.org/conda-forge/osx-64/rasterio-1.3.9-py312h2bf6802_2.conda
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   optional: false
-- name: typing_utils
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/typing_utils-0.1.0-pyhd8ed1ab_0.tar.bz2
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+    cligj: '>=0.5'
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+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    setuptools: '>=0.9.8'
+    snuggs: '>=1.4.1'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/rasterio-1.3.9-py312h6499bd6_0.conda
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   optional: false
-- name: uc-micro-py
-  version: 1.0.1
+- name: rasterio
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   manager: conda
   platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/uc-micro-py-1.0.1-pyhd8ed1ab_0.tar.bz2
+    affine: ''
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+    click: '>=4'
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+    cligj: '>=0.5'
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+    proj: '>=9.3.1,<9.3.2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    setuptools: '>=0.9.8'
+    snuggs: '>=1.4.1'
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/rasterio-1.3.9-py312hc028deb_2.conda
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   optional: false
-- name: uri-template
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+  version: 2023.06.02
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/uri-template-1.3.0-pyhd8ed1ab_0.conda
+    libre2-11: 2023.06.02
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   optional: false
-- name: uritemplate
-  version: 4.1.1
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+  version: 2023.06.02
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/uritemplate-4.1.1-pyhd8ed1ab_0.tar.bz2
+    libre2-11: 2023.06.02
+  url: https://conda.anaconda.org/conda-forge/osx-64/re2-2023.06.02-hd34609a_0.conda
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   optional: false
-- name: validators
-  version: 0.22.0
+- name: readline
+  version: '8.2'
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    python: '>=3.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/validators-0.22.0-pyhd8ed1ab_0.conda
+    libgcc-ng: '>=12'
+    ncurses: '>=6.3,<7.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/readline-8.2-h8228510_1.conda
   hash:
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   optional: false
-- name: webcolors
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   manager: conda
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+  platform: osx-64
   dependencies:
-    python: '>=3.5'
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-- name: importlib_resources
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-- name: jedi
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+- name: ruamel.yaml.clib
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   manager: conda
   platform: win-64
   dependencies:
-    python: '>=3.6'
-    parso: '>=0.8.3,<0.9.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/jedi-0.19.1-pyhd8ed1ab_0.conda
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+    python_abi: 3.12.*
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+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/ruamel.yaml.clib-0.2.8-py312he70551f_0.conda
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-- name: jinja2
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+- name: scikit-learn
+  version: 1.4.1.post1
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    python: '>=3.7'
-    markupsafe: '>=2.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/jinja2-3.1.2-pyhd8ed1ab_1.tar.bz2
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+    joblib: '>=1.2.0'
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    numpy: '>=1.26.4,<2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    scipy: ''
+    threadpoolctl: '>=2.0.0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/scikit-learn-1.4.1.post1-py312h394d371_0.conda
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   optional: false
-- name: joblib
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+- name: scikit-learn
+  version: 1.4.1.post1
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/joblib-1.3.2-pyhd8ed1ab_0.conda
+    joblib: '>=1.2.0'
+    libcxx: '>=16'
+    llvm-openmp: '>=17.0.6'
+    numpy: '>=1.26.4,<2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    scipy: ''
+    threadpoolctl: '>=2.0.0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/scikit-learn-1.4.1.post1-py312h7167a34_0.conda
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   category: main
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-- name: jupyterlab_pygments
-  version: 0.2.2
+- name: scikit-learn
+  version: 1.3.2
   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
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-    pygments: '>=2.4.1,<3'
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyterlab_pygments-0.2.2-pyhd8ed1ab_0.tar.bz2
+    __osx: '>=10.9'
+    joblib: '>=1.1.1'
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+    llvm-openmp: '>=16.0.6'
+    numpy: '>=1.26.0,<2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+    scipy: ''
+    threadpoolctl: '>=2.0.0'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/scikit-learn-1.3.2-py312h6f466fd_1.conda
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   category: main
   optional: false
-- name: latexcodec
-  version: 2.0.1
+- name: scikit-learn
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   manager: conda
   platform: win-64
   dependencies:
-    python: ''
-    six: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/latexcodec-2.0.1-pyh9f0ad1d_0.tar.bz2
+    joblib: '>=1.2.0'
+    numpy: '>=1.26.4,<2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
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+    threadpoolctl: '>=2.0.0'
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/scikit-learn-1.4.1.post1-py312hcacafb1_0.conda
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   category: main
   optional: false
-- name: lcms2
-  version: '2.15'
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   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/lcms2-2.15-h67d730c_3.conda
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+    libcblas: '>=3.9.0,<4.0a0'
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+    liblapack: '>=3.9.0,<4.0a0'
+    libstdcxx-ng: '>=12'
+    numpy: '>=1.26.3,<2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/linux-64/scipy-1.12.0-py312heda63a1_2.conda
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   optional: false
-- name: libxcb
-  version: '1.15'
+- name: scipy
+  version: 1.12.0
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    m2w64-gcc-libs: ''
-    m2w64-gcc-libs-core: ''
-    pthread-stubs: ''
-    xorg-libxau: ''
-    xorg-libxdmcp: ''
-  url: https://conda.anaconda.org/conda-forge/win-64/libxcb-1.15-hcd874cb_0.conda
+    libblas: '>=3.9.0,<4.0a0'
+    libcblas: '>=3.9.0,<4.0a0'
+    libcxx: '>=15'
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+    numpy: '>=1.26.3,<2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/osx-64/scipy-1.12.0-py312h8adb940_2.conda
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   category: main
   optional: false
-- name: linkify-it-py
-  version: 2.0.0
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   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
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-    uc-micro-py: '>=1.0.1,<2.0.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/linkify-it-py-2.0.0-pyhd8ed1ab_0.tar.bz2
+    libblas: '>=3.9.0,<4.0a0'
+    libcblas: '>=3.9.0,<4.0a0'
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+    liblapack: '>=3.9.0,<4.0a0'
+    numpy: '>=1.26.0,<2.0a0'
+    python: '>=3.12,<3.13.0a0'
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/scipy-1.11.3-py312h44883eb_1.conda
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   optional: false
-- name: lxml
-  version: 4.9.3
+- name: scipy
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   manager: conda
   platform: win-64
   dependencies:
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+    libblas: '>=3.9.0,<4.0a0'
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     python_abi: 3.12.*
     ucrt: '>=10.0.20348.0'
     vc: '>=14.2,<15'
     vc14_runtime: '>=14.29.30139'
-  url: https://conda.anaconda.org/conda-forge/win-64/lxml-4.9.3-py312h2f4f5e2_1.conda
+  url: https://conda.anaconda.org/conda-forge/win-64/scipy-1.12.0-py312h8753938_2.conda
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   optional: false
-- name: m2w64-speex
-  version: 1.2rc2
+- name: seaborn
+  version: 0.13.2
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-    m2w64-speexdsp: ''
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-  url: https://conda.anaconda.org/conda-forge/win-64/m2w64-speex-1.2rc2-3.tar.bz2
+    seaborn-base: 0.13.2
+    statsmodels: '>=0.12'
+  url: https://conda.anaconda.org/conda-forge/noarch/seaborn-0.13.2-hd8ed1ab_0.conda
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   optional: false
-- name: m2w64-xz
-  version: 5.2.2
+- name: seaborn
+  version: 0.13.2
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-    m2w64-gettext: ''
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-  url: https://conda.anaconda.org/conda-forge/win-64/m2w64-xz-5.2.2-2.tar.bz2
+    statsmodels: '>=0.12'
+    seaborn-base: 0.13.2
+  url: https://conda.anaconda.org/conda-forge/noarch/seaborn-0.13.2-hd8ed1ab_0.conda
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-- name: m2w64-zlib
-  version: 1.2.8
+- name: seaborn
+  version: 0.13.0
   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
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-    msys2-conda-epoch: '20160418'
-  url: https://conda.anaconda.org/conda-forge/win-64/m2w64-zlib-1.2.8-10.tar.bz2
+    statsmodels: '>=0.12'
+    seaborn-base: '>=0.13.0,<0.13.1.0a0'
+  url: https://conda.anaconda.org/conda-forge/noarch/seaborn-0.13.0-hd8ed1ab_0.conda
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-- name: markdown-it-py
-  version: 2.2.0
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   manager: conda
   platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/markdown-it-py-2.2.0-pyhd8ed1ab_0.conda
+    statsmodels: '>=0.12'
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+  url: https://conda.anaconda.org/conda-forge/noarch/seaborn-0.13.2-hd8ed1ab_0.conda
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   optional: false
-- name: matplotlib-inline
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+- name: seaborn-base
+  version: 0.13.2
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/matplotlib-inline-0.1.6-pyhd8ed1ab_0.tar.bz2
+    matplotlib-base: '>=3.4,!=3.6.1'
+    numpy: '>=1.20,!=1.24.0'
+    pandas: '>=1.2'
+    python: '>=3.8'
+    scipy: '>=1.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.13.2-pyhd8ed1ab_0.conda
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   optional: false
-- name: nodeenv
-  version: 1.8.0
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+  version: 0.13.2
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-    python: 2.7|>=3.7
-  url: https://conda.anaconda.org/conda-forge/noarch/nodeenv-1.8.0-pyhd8ed1ab_0.conda
+    python: '>=3.8'
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+    scipy: '>=1.7'
+    numpy: '>=1.20,!=1.24.0'
+    matplotlib-base: '>=3.4,!=3.6.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.13.2-pyhd8ed1ab_0.conda
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-- name: openjpeg
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-  url: https://conda.anaconda.org/conda-forge/win-64/openjpeg-2.5.0-h3d672ee_3.conda
+- name: seaborn-base
+  version: 0.13.0
+  manager: conda
+  platform: osx-arm64
+  dependencies:
+    python: '>=3.8'
+    pandas: '>=1.2'
+    scipy: '>=1.3'
+    matplotlib-base: '>=3.3,!=3.6.1'
+    numpy: '>=1.20,!=1.24.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.13.0-pyhd8ed1ab_0.conda
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   optional: false
-- name: outcome
-  version: 1.3.0.post0
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+  version: 0.13.2
   manager: conda
   platform: win-64
   dependencies:
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-    attrs: '>=19.2.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/outcome-1.3.0.post0-pyhd8ed1ab_0.conda
+    python: '>=3.8'
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+    scipy: '>=1.7'
+    numpy: '>=1.20,!=1.24.0'
+    matplotlib-base: '>=3.4,!=3.6.1'
+  url: https://conda.anaconda.org/conda-forge/noarch/seaborn-base-0.13.2-pyhd8ed1ab_0.conda
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-- name: overrides
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   manager: conda
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+  platform: linux-64
   dependencies:
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-- name: pexpect
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   manager: conda
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+  platform: osx-64
   dependencies:
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-- name: pip
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+  platform: osx-arm64
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-    wheel: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/pip-23.3.1-pyhd8ed1ab_0.conda
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-- name: portalocker
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-- name: postgresql
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   manager: conda
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+  platform: linux-64
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-- name: proj
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+  platform: linux-64
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+  platform: osx-64
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-- name: pyct-core
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   manager: conda
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+  platform: osx-arm64
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     python: '>=3.8'
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   manager: conda
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+  platform: linux-64
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   dependencies:
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-- name: referencing
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   manager: conda
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+  platform: linux-64
   dependencies:
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-- name: rfc3339-validator
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   manager: conda
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+  platform: osx-64
   dependencies:
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+    __osx: ''
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-- name: ruamel.yaml
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   manager: conda
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   dependencies:
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   category: main
   optional: false
-- name: sympy
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+  platform: linux-64
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-    mpmath: '>=0.19'
-  url: https://conda.anaconda.org/conda-forge/noarch/sympy-1.12-pyh04b8f61_3.conda
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   optional: false
-- name: tbb
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   manager: conda
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-- name: terminado
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   manager: conda
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-- name: fonttools
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-- name: jupyter_server_terminals
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   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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+    python: '>=3.6'
+    requests: '>=1.2'
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-- name: kealib
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   manager: conda
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+  platform: osx-64
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+    numpy: '>=1.8'
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+    protobuf: '>=3.0.0a3'
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-- name: libnetcdf
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+- name: siphon
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   manager: conda
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+  platform: osx-arm64
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+    python: '>=3.6'
+    numpy: '>=1.8'
+    requests: '>=1.2'
+    protobuf: '>=3.0.0a3'
+    beautifulsoup4: '>=4.6'
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-- name: libspatialite
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   manager: conda
   platform: win-64
   dependencies:
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+    python: '>=3.6'
+    numpy: '>=1.8'
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-- name: m2w64-libpng
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   manager: conda
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+  platform: linux-64
   dependencies:
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-- name: m2w64-libsndfile
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+  platform: osx-64
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-- name: m2w64-libtiff
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+  platform: osx-arm64
   dependencies:
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-- name: m2w64-libxml2
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   dependencies:
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-- name: m2w64-pcre2
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+  platform: linux-64
   dependencies:
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-- name: m2w64-tcl
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+  platform: osx-64
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-- name: markdown
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-- name: mdit-py-plugins
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   dependencies:
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-- name: mercantile
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   manager: conda
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+  platform: linux-64
   dependencies:
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-- name: mkl
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   manager: conda
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+  platform: osx-64
   dependencies:
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-- name: pendulum
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-- name: pillow
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-- name: platformdirs
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   manager: conda
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+  platform: linux-64
   dependencies:
     python: '>=3.7'
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-- name: pybtex
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-    pyyaml: '>=3.01'
-  url: https://conda.anaconda.org/conda-forge/noarch/pybtex-0.24.0-pyhd8ed1ab_2.tar.bz2
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-- name: pygeoif
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   manager: conda
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+  platform: osx-64
   dependencies:
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     python: '>=3.7'
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-- name: pyproj
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-  url: https://conda.anaconda.org/conda-forge/win-64/pyproj-3.6.1-py312hb4fa1d0_3.conda
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-- name: sqlalchemy
-  version: 2.0.22
+- name: sniffio
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   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
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-    python: '>=3.12,<3.13.0a0'
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-  url: https://conda.anaconda.org/conda-forge/win-64/sqlalchemy-2.0.22-py312he70551f_0.conda
+    python: '>=3.7'
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-- name: stack_data
-  version: 0.6.2
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   manager: conda
   platform: win-64
   dependencies:
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-    executing: ''
-    pure_eval: ''
-    python: '>=3.5'
-  url: https://conda.anaconda.org/conda-forge/noarch/stack_data-0.6.2-pyhd8ed1ab_0.conda
+    python: '>=3.7'
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-- name: trio
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+- name: snowballstemmer
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   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-    cffi: '>=1.14'
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-  url: https://conda.anaconda.org/conda-forge/win-64/trio-0.22.2-py312h2e8e312_1.conda
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-- name: ukkonen
-  version: 1.0.1
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   manager: conda
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+  platform: osx-64
   dependencies:
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-    python: '>=3.12.0rc3,<3.13.0a0'
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-  url: https://conda.anaconda.org/conda-forge/win-64/ukkonen-1.0.1-py312h0d7def4_4.conda
+    python: '>=2'
+  url: https://conda.anaconda.org/conda-forge/noarch/snowballstemmer-2.2.0-pyhd8ed1ab_0.tar.bz2
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-- name: urllib3
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+  version: 2.2.0
   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
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-    brotli-python: '>=1.0.9'
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-  url: https://conda.anaconda.org/conda-forge/noarch/urllib3-2.0.7-pyhd8ed1ab_0.conda
+    python: '>=2'
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-- name: wcwidth
-  version: 0.2.8
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   manager: conda
   platform: win-64
   dependencies:
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-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/wcwidth-0.2.8-pyhd8ed1ab_0.conda
+    python: '>=2'
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-- name: wsproto
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   manager: conda
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+  platform: linux-64
   dependencies:
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-    h11: '>=0.9.0,<1.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/wsproto-1.2.0-pyhd8ed1ab_0.tar.bz2
+    numpy: ''
+    pyparsing: '>=2.1.6'
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-- name: argon2-cffi
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   manager: conda
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+  platform: osx-64
   dependencies:
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-    argon2-cffi-bindings: ''
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+    pyparsing: '>=2.1.6'
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-- name: httpx
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/httpx-0.25.0-pyhd8ed1ab_0.conda
+    python: ''
+    numpy: ''
+    pyparsing: '>=2.1.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/snuggs-1.4.7-py_0.tar.bz2
   hash:
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-- name: identify
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   manager: conda
   platform: win-64
   dependencies:
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-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/identify-2.5.31-pyhd8ed1ab_0.conda
+    python: ''
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+    pyparsing: '>=2.1.6'
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   hash:
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-- name: isoduration
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   manager: conda
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+  platform: linux-64
   dependencies:
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-    arrow: '>=0.15.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/isoduration-20.11.0-pyhd8ed1ab_0.tar.bz2
+    python: '>=2.7'
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-- name: jsonschema
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   manager: conda
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-4.19.1-pyhd8ed1ab_0.conda
+    python: '>=2.7'
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-- name: jupyter_core
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-    python: '>=3.12,<3.13.0a0'
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-  url: https://conda.anaconda.org/conda-forge/win-64/jupyter_core-5.4.0-py312h2e8e312_0.conda
+    python: '>=2.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/sortedcontainers-2.4.0-pyhd8ed1ab_0.tar.bz2
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-- name: libblas
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   manager: conda
   platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/libblas-3.9.0-19_win64_mkl.conda
+    python: '>=2.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/sortedcontainers-2.4.0-pyhd8ed1ab_0.tar.bz2
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-- name: m2w64-tk
-  version: 8.6.5
+- name: soupsieve
+  version: '2.5'
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-    msys2-conda-epoch: '20160418'
-  url: https://conda.anaconda.org/conda-forge/win-64/m2w64-tk-8.6.5-3.tar.bz2
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/soupsieve-2.5-pyhd8ed1ab_1.conda
   hash:
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-- name: poppler
-  version: 23.10.0
+- name: soupsieve
+  version: '2.5'
   manager: conda
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/poppler-23.10.0-hc2f3c52_0.conda
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/soupsieve-2.5-pyhd8ed1ab_1.conda
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   optional: false
-- name: prompt-toolkit
-  version: 3.0.39
+- name: soupsieve
+  version: '2.5'
   manager: conda
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+  platform: osx-arm64
   dependencies:
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-    python: '>=3.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/prompt-toolkit-3.0.39-pyha770c72_0.conda
+    python: '>=3.8'
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-- name: pybtex-docutils
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   manager: conda
   platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/pybtex-docutils-1.0.3-py312h2e8e312_1.conda
+    python: '>=3.8'
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-- name: requests
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+- name: sphinx
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   manager: conda
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+  platform: linux-64
   dependencies:
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-    idna: '>=2.5,<4'
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-- name: trio-websocket
-  version: 0.11.1
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   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-    wsproto: '>=0.14'
-  url: https://conda.anaconda.org/conda-forge/noarch/trio-websocket-0.11.1-pyhd8ed1ab_0.conda
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+    sphinxcontrib-jsmath: ''
+    sphinxcontrib-applehelp: ''
+    sphinxcontrib-devhelp: ''
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+    python: '>=3.6'
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+    pygments: '>=2.0'
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-- name: virtualenv
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   manager: conda
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+  platform: osx-arm64
   dependencies:
-    python: '>=3.8'
-    distlib: <1,>=0.3.7
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-  url: https://conda.anaconda.org/conda-forge/noarch/virtualenv-20.24.6-pyhd8ed1ab_0.conda
+    packaging: ''
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+    sphinxcontrib-devhelp: ''
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+    imagesize: ''
+    python: '>=3.6'
+    pygments: '>=2.0'
+    alabaster: '>=0.7,<0.8'
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+    sphinxcontrib-serializinghtml: '>=1.1.5'
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-- name: github3.py
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   manager: conda
   platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/github3.py-4.0.1-pyhd8ed1ab_0.conda
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+    sphinxcontrib-applehelp: ''
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+    sphinxcontrib-qthelp: ''
+    imagesize: ''
+    python: '>=3.6'
+    importlib-metadata: '>=4.4'
+    pygments: '>=2.0'
+    alabaster: '>=0.7,<0.8'
+    requests: '>=2.5.0'
+    jinja2: '>=2.3'
+    snowballstemmer: '>=1.1'
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+    sphinxcontrib-serializinghtml: '>=1.1.5'
+    colorama: '>=0.3.5'
+    docutils: '>=0.14,<0.19'
+  url: https://conda.anaconda.org/conda-forge/noarch/sphinx-5.0.2-pyh6c4a22f_0.tar.bz2
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   category: main
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-- name: jsonschema-with-format-nongpl
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+- name: sphinx-book-theme
+  version: 1.0.1
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    python: ''
-    idna: ''
-    rfc3339-validator: ''
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-    fqdn: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/jsonschema-with-format-nongpl-4.19.1-pyhd8ed1ab_0.conda
+    pydata-sphinx-theme: '>=0.13.3'
+    python: '>=3.7'
+    sphinx: '>=4,<7'
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-- name: jupyter_client
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+  version: 1.0.1
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-    python-dateutil: '>=2.8.2'
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+    python: '>=3.7'
+    sphinx: '>=4,<7'
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-- name: libcblas
-  version: 3.9.0
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+  version: 1.0.1
   manager: conda
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+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/libcblas-3.9.0-19_win64_mkl.conda
+    python: '>=3.7'
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-- name: libgdal
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   manager: conda
   platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/libgdal-3.7.2-h3217549_7.conda
+    python: '>=3.7'
+    sphinx: '>=4,<7'
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-- name: liblapack
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   manager: conda
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+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/liblapack-3.9.0-19_win64_mkl.conda
+    python: ''
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   hash:
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-- name: m2w64-bwidget
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   manager: conda
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/m2w64-bwidget-1.9.10-2.tar.bz2
+    python: ''
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-- name: m2w64-tktable
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-    msys2-conda-epoch: '20160418'
-  url: https://conda.anaconda.org/conda-forge/win-64/m2w64-tktable-2.10-5.tar.bz2
+    python: ''
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-- name: nbformat
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   manager: conda
   platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/nbformat-5.9.2-pyhd8ed1ab_0.conda
+    python: ''
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+  url: https://conda.anaconda.org/conda-forge/noarch/sphinx-comments-0.0.3-pyh9f0ad1d_0.tar.bz2
   hash:
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-- name: owslib
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   manager: conda
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+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/owslib-0.29.2-pyhd8ed1ab_0.conda
+    python: '>=3'
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-- name: pre-commit
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   manager: conda
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   dependencies:
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+    python: '>=3'
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-- name: prompt_toolkit
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   manager: conda
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   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/prompt_toolkit-3.0.39-hd8ed1ab_0.conda
+    python: '>=3'
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-- name: pyct
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   manager: conda
   platform: win-64
   dependencies:
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-    pyct-core: 0.4.6.*
-  url: https://conda.anaconda.org/conda-forge/noarch/pyct-0.4.6-py_0.tar.bz2
+    python: '>=3'
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-- name: pyworms
-  version: 0.4.0
+- name: sphinx-design
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   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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     python: '>=3.6'
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-- name: selenium
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-- name: colorcet
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-- name: geojsonio
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   platform: win-64
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-- name: jupyter_events
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-- name: nbclient
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+  platform: osx-64
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-- name: cftime
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-- name: ipywidgets
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-- name: jupyter-cache
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-- name: r-commonmark
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-- name: r-isoband
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-- name: r-lattice
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-- name: r-lazyeval
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-- name: r-leaflet.providers
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-- name: r-magrittr
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   manager: conda
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-- name: r-maps
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   manager: conda
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-- name: r-mass
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-- name: r-mime
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+  platform: linux-64
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-- name: r-ncdf4
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+  platform: osx-64
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-- name: r-pbdzmq
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   manager: conda
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+  platform: osx-arm64
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-- name: r-pkgconfig
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-- name: r-png
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   manager: conda
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+  platform: linux-64
   dependencies:
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-- name: r-praise
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   manager: conda
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+  platform: osx-64
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-- name: r-proxy
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-- name: r-ps
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   manager: conda
   platform: win-64
   dependencies:
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-- name: r-r6
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   manager: conda
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+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-r6-2.5.1-r41hc72bb7e_1.tar.bz2
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+    python: '>=3.8'
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-- name: r-rapidjsonr
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   manager: conda
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+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-rapidjsonr-1.2.0-r41hc72bb7e_2.tar.bz2
+    python: '>=3.8'
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-- name: r-rappdirs
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-- name: r-rcolorbrewer
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   manager: conda
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-- name: r-rcpp
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   manager: conda
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+  platform: linux-64
   dependencies:
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-- name: r-rlang
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   manager: conda
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+  platform: linux-64
   dependencies:
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+    python: '>=3.7'
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-- name: r-rstudioapi
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   manager: conda
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+  platform: osx-64
   dependencies:
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+    python: '>=3.7'
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-- name: r-sourcetools
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   manager: conda
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-- name: r-stringi
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   manager: conda
   platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/r-stringi-1.7.12-r41ha856d6a_3.conda
+    python: '>=3.7'
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-- name: r-sys
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   manager: conda
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+  platform: osx-64
   dependencies:
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-- name: r-utf8
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   manager: conda
   platform: win-64
   dependencies:
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-- name: r-uuid
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   manager: conda
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+  platform: linux-64
   dependencies:
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+    libnetcdf: '>=4.9.2,<4.9.3.0a0'
+    libstdcxx-ng: '>=12'
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-- name: r-viridislite
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+  version: 2.2.0
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-viridislite-0.4.1-r41hc72bb7e_1.tar.bz2
+    hdf5: '>=1.14.3,<1.14.4.0a0'
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-- name: r-withr
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-- name: r-xfun
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   manager: conda
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+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/r-xfun-0.40-r41ha856d6a_0.conda
+    __linux: ''
+    ptyprocess: ''
+    python: '>=3.8'
+    tornado: '>=6.1.0'
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-- name: r-xml
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   manager: conda
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+  platform: osx-64
   dependencies:
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+    __osx: ''
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-- name: r-xtable
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-xtable-1.8_4-r41hc72bb7e_4.tar.bz2
+    __osx: ''
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+    python: '>=3.7'
+    tornado: '>=6.1.0'
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-- name: r-yaml
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   manager: conda
   platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/r-yaml-2.3.7-r41h6d2157b_1.conda
+    __win: ''
+    python: '>=3.8'
+    tornado: '>=6.1.0'
+    pywinpty: '>=1.1.0'
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-- name: rpy2
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+- name: threadpoolctl
+  version: 3.3.0
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-    m2w64-gcc-libs: ''
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-    tzlocal: ''
-  url: https://conda.anaconda.org/conda-forge/win-64/rpy2-3.5.11-py312r41hd0f9d78_3.conda
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/threadpoolctl-3.3.0-pyhc1e730c_0.conda
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-- name: scipy
-  version: 1.11.3
+- name: threadpoolctl
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   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/scipy-1.11.3-py312h8753938_1.conda
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/threadpoolctl-3.3.0-pyhc1e730c_0.conda
   hash:
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   category: main
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-- name: seawater
-  version: 3.3.4
+- name: threadpoolctl
+  version: 3.2.0
   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
-    python: ''
-    numpy: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/seawater-3.3.4-py_1.tar.bz2
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/threadpoolctl-3.2.0-pyha21a80b_0.conda
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   category: main
   optional: false
-- name: shapely
-  version: 2.0.2
+- name: threadpoolctl
+  version: 3.3.0
   manager: conda
   platform: win-64
   dependencies:
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-    numpy: '>=1.26.0,<2.0a0'
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-  url: https://conda.anaconda.org/conda-forge/win-64/shapely-2.0.2-py312h92c3dd1_0.conda
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/threadpoolctl-3.3.0-pyhc1e730c_0.conda
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   category: main
   optional: false
-- name: snuggs
-  version: 1.4.7
+- name: thredds_crawler
+  version: 1.5.4
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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+    netcdf4: ''
     python: ''
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-    pyparsing: '>=2.1.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/snuggs-1.4.7-py_0.tar.bz2
+    pytz: ''
+    requests: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/thredds_crawler-1.5.4-py_1.tar.bz2
   hash:
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   optional: false
-- name: bokeh
-  version: 3.3.0
+- name: thredds_crawler
+  version: 1.5.4
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-    numpy: '>=1.16'
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-    xyzservices: '>=2021.09.1'
-  url: https://conda.anaconda.org/conda-forge/noarch/bokeh-3.3.0-pyhd8ed1ab_0.conda
+    python: ''
+    requests: ''
+    lxml: ''
+    pytz: ''
+    netcdf4: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/thredds_crawler-1.5.4-py_1.tar.bz2
   hash:
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   optional: false
-- name: cf-units
-  version: 3.2.0
+- name: thredds_crawler
+  version: 1.5.4
   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/cf-units-3.2.0-py312ha90f08f_4.conda
+    python: ''
+    requests: ''
+    lxml: ''
+    pytz: ''
+    netcdf4: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/thredds_crawler-1.5.4-py_1.tar.bz2
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   category: main
   optional: false
-- name: erddapy
-  version: 2.2.0
+- name: thredds_crawler
+  version: 1.5.4
   manager: conda
   platform: win-64
   dependencies:
+    python: ''
+    requests: ''
+    lxml: ''
     pytz: ''
-    httpx: ''
-    python: '>=3.8'
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-  url: https://conda.anaconda.org/conda-forge/noarch/erddapy-2.2.0-pyhd8ed1ab_0.conda
+    netcdf4: ''
+  url: https://conda.anaconda.org/conda-forge/noarch/thredds_crawler-1.5.4-py_1.tar.bz2
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   category: main
   optional: false
-- name: fiona
-  version: 1.9.5
+- name: tiledb
+  version: 2.20.0
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-    click: '>=4.0'
-    click-plugins: '>=1.0'
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-  url: https://conda.anaconda.org/conda-forge/win-64/fiona-1.9.5-py312he9aeaab_0.conda
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+    azure-storage-blobs-cpp: '>=12.10.0,<13.0a0'
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+    openssl: '>=3.2.1,<4.0a0'
+    zstd: '>=1.5.5,<1.6.0a0'
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   category: main
   optional: false
-- name: geopandas-base
-  version: 0.14.0
+- name: tiledb
+  version: 2.20.0
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    packaging: ''
-    python: '>=3.9'
-    pandas: '>=1.4.0'
-    shapely: '>=1.8.0'
-    pyproj: '>=3.3.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/geopandas-base-0.14.0-pyha770c72_1.conda
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+    azure-core-cpp: '>=1.10.3,<1.11.0a0'
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+    openssl: '>=3.2.1,<4.0a0'
+    zstd: '>=1.5.5,<1.6.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/tiledb-2.20.0-h8fd0293_0.conda
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   category: main
   optional: false
-- name: ipyleaflet
-  version: 0.17.4
+- name: tiledb
+  version: 2.16.3
   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
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-    traittypes: '>=0.2.1,<0.3.0'
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-  url: https://conda.anaconda.org/conda-forge/noarch/ipyleaflet-0.17.4-pyhd8ed1ab_0.conda
+    bzip2: '>=1.0.8,<2.0a0'
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+    libxml2: '>=2.11.5,<2.12.0a0'
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+    openssl: '>=3.1.2,<4.0a0'
+    zstd: '>=1.5.5,<1.6.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/tiledb-2.16.3-hc77a09f_3.conda
   hash:
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   category: main
   optional: false
-- name: ipyparallel
-  version: 8.6.1
+- name: tiledb
+  version: 2.18.2
   manager: conda
   platform: win-64
   dependencies:
-    tqdm: ''
-    psutil: ''
-    decorator: ''
-    jupyter_client: ''
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-    python: '>=3.6'
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-    traitlets: '>=4.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/ipyparallel-8.6.1-pyhd8ed1ab_0.conda
+    bzip2: '>=1.0.8,<2.0a0'
+    libxml2: '>=2.12.1,<3.0.0a0'
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+    openssl: '>=3.2.0,<4.0a0'
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+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+    zstd: '>=1.5.5,<1.6.0a0'
+  url: https://conda.anaconda.org/conda-forge/win-64/tiledb-2.18.2-hc200977_1.conda
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   category: main
   optional: false
-- name: jupyter_console
-  version: 6.6.3
+- name: time-machine
+  version: 2.13.0
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    ipython: ''
-    pygments: ''
-    python: '>=3.7'
-    pyzmq: '>=17'
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-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_console-6.6.3-pyhd8ed1ab_0.conda
+    libgcc-ng: '>=12'
+    python: '>=3.12.0rc3,<3.13.0a0'
+    python-dateutil: ''
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/linux-64/time-machine-2.13.0-py312h98912ed_1.conda
   hash:
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   category: main
   optional: false
-- name: jupyter_server
-  version: 2.9.1
+- name: time-machine
+  version: 2.13.0
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    packaging: ''
-    jinja2: ''
-    prometheus_client: ''
-    websocket-client: ''
-    argon2-cffi: ''
-    overrides: ''
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-    python: '>=3.8'
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-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter_server-2.9.1-pyhd8ed1ab_0.conda
+    python: '>=3.12,<3.13.0a0'
+    python-dateutil: ''
+    python_abi: 3.12.*
+  url: https://conda.anaconda.org/conda-forge/osx-64/time-machine-2.13.0-py312h41838bb_1.conda
   hash:
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   category: main
   optional: false
-- name: matplotlib-base
-  version: 3.8.0
+- name: time-machine
+  version: 2.13.0
   manager: conda
   platform: win-64
   dependencies:
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-    contourpy: '>=1.0.1'
-    cycler: '>=0.10'
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-    pyparsing: '>=2.3.1'
-    python: '>=3.12,<3.13.0a0'
-    python-dateutil: '>=2.7'
+    python: '>=3.12.0rc3,<3.13.0a0'
+    python-dateutil: ''
     python_abi: 3.12.*
     ucrt: '>=10.0.20348.0'
     vc: '>=14.2,<15'
     vc14_runtime: '>=14.29.30139'
-  url: https://conda.anaconda.org/conda-forge/win-64/matplotlib-base-3.8.0-py312h26ecaf7_2.conda
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-- name: nbconvert-pandoc
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-  platform: win-64
-  dependencies:
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-    python: '>=3.8'
-    nbconvert-core: 7.9.2
-  url: https://conda.anaconda.org/conda-forge/noarch/nbconvert-pandoc-7.9.2-pyhd8ed1ab_0.conda
+  url: https://conda.anaconda.org/conda-forge/win-64/time-machine-2.13.0-py312he70551f_1.conda
   hash:
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   category: main
   optional: false
-- name: nbval
-  version: 0.10.0
+- name: tinycss2
+  version: 1.2.1
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    six: ''
-    pytest: ''
-    nbformat: ''
-    ipykernel: ''
-    jupyter_client: ''
-    coverage: ''
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/nbval-0.10.0-pyhd8ed1ab_0.conda
+    python: '>=3.5'
+    webencodings: '>=0.4'
+  url: https://conda.anaconda.org/conda-forge/noarch/tinycss2-1.2.1-pyhd8ed1ab_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: netcdf4
-  version: 1.6.5
+- name: tinycss2
+  version: 1.2.1
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-    cftime: ''
-    hdf5: '>=1.14.2,<1.14.3.0a0'
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-  url: https://conda.anaconda.org/conda-forge/win-64/netcdf4-1.6.5-nompi_py312he4da9c3_100.conda
+    python: '>=3.5'
+    webencodings: '>=0.4'
+  url: https://conda.anaconda.org/conda-forge/noarch/tinycss2-1.2.1-pyhd8ed1ab_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: patsy
-  version: 0.5.3
+- name: tinycss2
+  version: 1.2.1
   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
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-    six: ''
-    python: '>=3.6'
-    numpy: '>=1.4.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/patsy-0.5.3-pyhd8ed1ab_0.tar.bz2
+    python: '>=3.5'
+    webencodings: '>=0.4'
+  url: https://conda.anaconda.org/conda-forge/noarch/tinycss2-1.2.1-pyhd8ed1ab_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: pyobis
-  version: 1.3.1
+- name: tinycss2
+  version: 1.2.1
   manager: conda
   platform: win-64
   dependencies:
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-    python: '>=3.7'
-    requests: '>2.7'
-  url: https://conda.anaconda.org/conda-forge/noarch/pyobis-1.3.1-pyhd8ed1ab_0.conda
+    python: '>=3.5'
+    webencodings: '>=0.4'
+  url: https://conda.anaconda.org/conda-forge/noarch/tinycss2-1.2.1-pyhd8ed1ab_0.tar.bz2
   hash:
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   category: main
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-- name: pyresample
-  version: 1.27.1
+- name: tk
+  version: 8.6.13
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/pyresample-1.27.1-py312h2ab9e98_2.conda
+    libgcc-ng: '>=12'
+    libzlib: '>=1.2.13,<1.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_h4845f30_101.conda
   hash:
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   category: main
   optional: false
-- name: qtconsole-base
-  version: 5.4.4
+- name: tk
+  version: 8.6.13
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    packaging: ''
-    pygments: ''
-    traitlets: ''
-    jupyter_core: ''
-    ipython_genutils: ''
-    python: '>=3.7'
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-  url: https://conda.anaconda.org/conda-forge/noarch/qtconsole-base-5.4.4-pyha770c72_0.conda
+    libzlib: '>=1.2.13,<1.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/tk-8.6.13-h1abcd95_1.conda
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   optional: false
-- name: r-askpass
-  version: 1.2.0
+- name: tk
+  version: 8.6.13
   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
-    m2w64-gcc-libs: ''
-    m2w64-gcc-libs-core: ''
-    r-base: '>=4.1,<4.2.0a0'
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-  url: https://conda.anaconda.org/conda-forge/win-64/r-askpass-1.2.0-r41h6d2157b_0.conda
+    libzlib: '>=1.2.13,<1.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/tk-8.6.13-hb31c410_0.conda
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-- name: r-processx
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-- name: r-rprojroot
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-- name: r-systemfonts
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-- name: r-terra
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-- name: r-tinytex
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-- name: r-triebeard
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-- name: r-tzdb
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-- name: r-units
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   manager: conda
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   dependencies:
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-- name: r-v8
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   manager: conda
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+  platform: osx-64
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-- name: r-wk
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   dependencies:
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-- name: r-xml2
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   dependencies:
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-- name: r-zoo
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   manager: conda
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   dependencies:
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-- name: rasterio
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   manager: conda
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   dependencies:
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-- name: scikit-learn
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   manager: conda
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-- name: pandas-flavor
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+  platform: osx-arm64
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-- name: panel
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   manager: conda
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-- name: r-callr
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-- name: r-htmltools
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-- name: r-igraph
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   manager: conda
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   dependencies:
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-- name: r-jsonld
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   manager: conda
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   dependencies:
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-- name: r-knitr
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   manager: conda
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-- name: r-lubridate
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   dependencies:
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-- name: r-memoise
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   manager: conda
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-- name: r-mgcv
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   manager: conda
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   dependencies:
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-- name: r-openssl
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   dependencies:
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-- name: siphon
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-- name: statsmodels
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-- name: thredds_crawler
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-  url: https://conda.anaconda.org/conda-forge/noarch/ctd-1.4.4-pyhd8ed1ab_0.conda
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+  url: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.38.33130-h82b7239_18.conda
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   optional: false
-- name: geopandas
-  version: 0.14.0
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+  version: 20.25.0
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    matplotlib-base: ''
-    rtree: ''
-    folium: ''
-    xyzservices: ''
-    python: '>=3.9'
-    mapclassify: '>=2.4.0'
-    fiona: '>=1.8.21'
-    geopandas-base: 0.14.0
-  url: https://conda.anaconda.org/conda-forge/noarch/geopandas-0.14.0-pyhd8ed1ab_1.conda
+    distlib: <1,>=0.3.7
+    filelock: <4,>=3.12.2
+    platformdirs: <5,>=3.9.1
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/virtualenv-20.25.0-pyhd8ed1ab_0.conda
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   category: main
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-- name: holoviews
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-    python: '>=3.9'
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-  url: https://conda.anaconda.org/conda-forge/noarch/holoviews-1.18.0-pyhd8ed1ab_0.conda
+  optional: false
+- name: virtualenv
+  version: 20.25.0
+  manager: conda
+  platform: osx-64
+  dependencies:
+    python: '>=3.8'
+    distlib: <1,>=0.3.7
+    filelock: <4,>=3.12.2
+    platformdirs: <5,>=3.9.1
+  url: https://conda.anaconda.org/conda-forge/noarch/virtualenv-20.25.0-pyhd8ed1ab_0.conda
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   category: main
   optional: false
-- name: jupyterlab
-  version: 4.0.7
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   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
-    packaging: ''
-    traitlets: ''
-    tomli: ''
-    ipykernel: ''
-    jupyter_core: ''
     python: '>=3.8'
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-  url: https://conda.anaconda.org/conda-forge/noarch/jupyterlab-4.0.7-pyhd8ed1ab_0.conda
+    distlib: <1,>=0.3.7
+    filelock: <4,>=3.12.2
+    platformdirs: <4,>=3.9.1
+  url: https://conda.anaconda.org/conda-forge/noarch/virtualenv-20.24.6-pyhd8ed1ab_0.conda
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   category: main
   optional: false
-- name: nbclassic
-  version: 1.0.0
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   manager: conda
   platform: win-64
   dependencies:
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-    nbformat: ''
-    prometheus_client: ''
-    ipykernel: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/nbclassic-1.0.0-pyhb4ecaf3_1.conda
+    python: '>=3.8'
+    distlib: <1,>=0.3.7
+    filelock: <4,>=3.12.2
+    platformdirs: <5,>=3.9.1
+  url: https://conda.anaconda.org/conda-forge/noarch/virtualenv-20.25.0-pyhd8ed1ab_0.conda
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-- name: nbdime
-  version: 3.2.1
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   manager: conda
   platform: win-64
   dependencies:
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-    pygments: ''
-    colorama: ''
-    nbformat: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/nbdime-3.2.1-pyhd8ed1ab_0.conda
+    vc14_runtime: '>=14.38.33130'
+  url: https://conda.anaconda.org/conda-forge/win-64/vs2015_runtime-14.38.33130-hcb4865c_18.conda
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-- name: octave_kernel
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   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-    python: '>=3.7'
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-    metakernel: '>=0.24.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/octave_kernel-0.35.1-pyhd8ed1ab_0.conda
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/wcwidth-0.2.13-pyhd8ed1ab_0.conda
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   category: main
   optional: false
-- name: pyoos
-  version: 0.8.4
+- name: wcwidth
+  version: 0.2.13
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    python: ''
-    numpy: ''
-    requests: ''
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-    beautifulsoup4: ''
-    fiona: ''
-    owslib: ''
-    paegan: ''
-  url: https://conda.anaconda.org/conda-forge/noarch/pyoos-0.8.4-py_1.tar.bz2
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/wcwidth-0.2.13-pyhd8ed1ab_0.conda
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   optional: false
-- name: r-classint
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+- name: wcwidth
+  version: 0.2.8
   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
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-    m2w64-gcc-libs-core: ''
-    r-base: '>=4.1,<4.2.0a0'
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-  url: https://conda.anaconda.org/conda-forge/win-64/r-classint-0.4_10-r41he816bda_0.conda
+    backports.functools_lru_cache: ''
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/wcwidth-0.2.8-pyhd8ed1ab_0.conda
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   optional: false
-- name: r-crosstalk
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   manager: conda
   platform: win-64
   dependencies:
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+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/wcwidth-0.2.13-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: r-crul
-  version: 1.4.0
+- name: webcolors
+  version: '1.13'
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-    r-mime: ''
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-    r-curl: '>=3.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-crul-1.4.0-r41h785f33e_0.conda
+    python: '>=3.5'
+  url: https://conda.anaconda.org/conda-forge/noarch/webcolors-1.13-pyhd8ed1ab_0.conda
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   category: main
   optional: false
-- name: r-emld
-  version: 0.5.1
+- name: webcolors
+  version: '1.13'
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-    r-xml2: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-emld-0.5.1-r41hc72bb7e_1.tar.bz2
+    python: '>=3.5'
+  url: https://conda.anaconda.org/conda-forge/noarch/webcolors-1.13-pyhd8ed1ab_0.conda
   hash:
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   optional: false
-- name: r-fontawesome
-  version: 0.5.1
+- name: webcolors
+  version: '1.13'
   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-fontawesome-0.5.1-r41hc72bb7e_0.conda
+    python: '>=3.5'
+  url: https://conda.anaconda.org/conda-forge/noarch/webcolors-1.13-pyhd8ed1ab_0.conda
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   category: main
   optional: false
-- name: r-geojsonsf
-  version: 2.0.3
+- name: webcolors
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   manager: conda
   platform: win-64
   dependencies:
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-    m2w64-gcc-libs-core: ''
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-  url: https://conda.anaconda.org/conda-forge/win-64/r-geojsonsf-2.0.3-r41ha856d6a_2.conda
+    python: '>=3.5'
+  url: https://conda.anaconda.org/conda-forge/noarch/webcolors-1.13-pyhd8ed1ab_0.conda
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   category: main
   optional: false
-- name: r-gridextra
-  version: '2.3'
+- name: webencodings
+  version: 0.5.1
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    r-gtable: ''
-    r-base: '>=4.1,<4.2.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-gridextra-2.3-r41hc72bb7e_1004.tar.bz2
+    python: '>=2.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/webencodings-0.5.1-pyhd8ed1ab_2.conda
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   category: main
   optional: false
-- name: r-hms
-  version: 1.1.3
+- name: webencodings
+  version: 0.5.1
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    r-rlang: ''
-    r-lifecycle: ''
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-    r-pkgconfig: ''
-    r-base: '>=4.1,<4.2.0a0'
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-hms-1.1.3-r41hc72bb7e_0.conda
+    python: '>=2.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/webencodings-0.5.1-pyhd8ed1ab_2.conda
   hash:
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   category: main
   optional: false
-- name: r-httpuv
-  version: 1.6.12
+- name: webencodings
+  version: 0.5.1
   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
-    m2w64-gcc-libs: ''
-    m2w64-gcc-libs-core: ''
-    r-base: '>=4.1,<4.2.0a0'
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-  url: https://conda.anaconda.org/conda-forge/win-64/r-httpuv-1.6.12-r41ha856d6a_0.conda
+    python: '>=2.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/webencodings-0.5.1-pyhd8ed1ab_2.conda
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   optional: false
-- name: r-httr
-  version: 1.4.6
+- name: webencodings
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   manager: conda
   platform: win-64
   dependencies:
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-    r-r6: ''
-    r-mime: ''
-    r-base: '>=4.1,<4.2.0a0'
-    r-openssl: '>=0.8'
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-httr-1.4.6-r41hc72bb7e_0.conda
+    python: '>=2.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/webencodings-0.5.1-pyhd8ed1ab_2.conda
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   category: main
   optional: false
-- name: r-influencer
-  version: 0.1.5
+- name: websocket-client
+  version: 1.7.0
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    m2w64-gcc-libs: ''
-    m2w64-gcc-libs-core: ''
-    r-base: '>=4.1,<4.2.0a0'
-    r-igraph: '>=1.0.1'
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-  url: https://conda.anaconda.org/conda-forge/win-64/r-influencer-0.1.5-r41h6d2157b_1.conda
+    python: '>=3.8'
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-- name: r-jquerylib
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+  version: 1.7.0
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-    r-base: '>=4.1,<4.2.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-jquerylib-0.1.4-r41hc72bb7e_1.tar.bz2
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/websocket-client-1.7.0-pyhd8ed1ab_0.conda
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-- name: r-pillar
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   manager: conda
-  platform: win-64
+  platform: osx-arm64
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-pillar-1.9.0-r41hc72bb7e_0.conda
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/websocket-client-1.6.4-pyhd8ed1ab_0.conda
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-- name: r-pkgload
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   manager: conda
   platform: win-64
   dependencies:
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+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/websocket-client-1.7.0-pyhd8ed1ab_0.conda
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-- name: r-purrr
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   manager: conda
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+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/r-purrr-1.0.2-r41h6d2157b_0.conda
+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/wheel-0.42.0-pyhd8ed1ab_0.conda
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-- name: r-sass
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   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/r-sass-0.4.7-r41ha856d6a_0.conda
+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/wheel-0.42.0-pyhd8ed1ab_0.conda
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-- name: r-satellite
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/r-satellite-1.0.4-r41ha856d6a_2.conda
+    python: '>=3.7'
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-- name: r-stringr
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   manager: conda
   platform: win-64
   dependencies:
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+    python: '>=3.7'
+  url: https://conda.anaconda.org/conda-forge/noarch/wheel-0.42.0-pyhd8ed1ab_0.conda
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-- name: r-tidyselect
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   manager: conda
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+  platform: linux-64
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-  url: https://conda.anaconda.org/conda-forge/win-64/r-tidyselect-1.2.0-r41h6addd8b_1.conda
+    python: '>=3.7'
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-- name: r-webshot
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   manager: conda
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+  platform: osx-64
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+    python: '>=3.7'
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-- name: seaborn
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/seaborn-0.13.0-hd8ed1ab_0.conda
+    python: '>=3.7'
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-- name: geoplot
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   manager: conda
   platform: win-64
   dependencies:
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     python: '>=3.7'
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-  url: https://conda.anaconda.org/conda-forge/noarch/geoplot-0.5.1-pyhd8ed1ab_0.tar.bz2
+  url: https://conda.anaconda.org/conda-forge/noarch/widgetsnbextension-4.0.10-pyhd8ed1ab_0.conda
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-- name: hvplot
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   manager: conda
   platform: win-64
   dependencies:
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-    python: '>=3.8'
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-  url: https://conda.anaconda.org/conda-forge/noarch/hvplot-0.9.0-pyhd8ed1ab_0.conda
+    __win: ''
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/win_inet_pton-1.1.0-pyhd8ed1ab_6.tar.bz2
   hash:
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-- name: notebook
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   manager: conda
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+  platform: linux-64
   dependencies:
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+    matplotlib-base: '>=3'
+    numpy: '>=1.21'
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/windrose-1.9.0-pyhd8ed1ab_0.conda
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+  dependencies:
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+    numpy: '>=1.21'
+    matplotlib-base: '>=3'
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   optional: false
-- name: oceans
-  version: 1.1.3
+- name: windrose
+  version: 1.9.0
   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
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-    shapely: ''
-    netcdf4: ''
-    gsw: ''
-    seawater: ''
-    ctd: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/oceans-1.1.3-pyhd8ed1ab_0.conda
+    python: '>=3.6'
+    numpy: '>=1.21'
+    matplotlib-base: '>=3'
+  url: https://conda.anaconda.org/conda-forge/noarch/windrose-1.9.0-pyhd8ed1ab_0.conda
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   optional: false
-- name: oct2py
-  version: 5.6.0
+- name: windrose
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   manager: conda
   platform: win-64
   dependencies:
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-    ipython: ''
     python: '>=3.6'
-    octave_kernel: '>=0.34.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/oct2py-5.6.0-pyha21a80b_0.conda
+    numpy: '>=1.21'
+    matplotlib-base: '>=3'
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   optional: false
-- name: r-bslib
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+- name: winpty
+  version: 0.4.3
   manager: conda
   platform: win-64
-  dependencies:
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-    r-jsonlite: ''
-    r-base64enc: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-bslib-0.5.0-r41hc72bb7e_0.conda
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/win-64/winpty-0.4.3-4.tar.bz2
   hash:
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   optional: false
-- name: r-httpcache
+- name: wsproto
   version: 1.2.0
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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+    h11: '>=0.9.0,<1.0'
+    python: '>=3.7'
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   optional: false
-- name: r-progress
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   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-    r-crayon: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-progress-1.2.2-r41hc72bb7e_3.tar.bz2
+    python: '>=3.7'
+    h11: '>=0.9.0,<1.0'
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-- name: r-repr
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+  version: 1.2.0
   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
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-    r-htmltools: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-repr-1.1.6-r41h785f33e_0.conda
+    python: '>=3.7'
+    h11: '>=0.9.0,<1.0'
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-- name: r-reshape2
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   manager: conda
   platform: win-64
   dependencies:
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-    r-stringr: ''
-  url: https://conda.anaconda.org/conda-forge/win-64/r-reshape2-1.4.4-r41ha856d6a_3.conda
+    python: '>=3.7'
+    h11: '>=0.9.0,<1.0'
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   category: main
   optional: false
-- name: r-servr
-  version: '0.27'
+- name: xarray
+  version: 2024.2.0
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-    r-xfun: ''
-    r-base: '>=4.1,<4.2.0a0'
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-servr-0.27-r41hc72bb7e_0.conda
+    numpy: '>=1.23'
+    packaging: '>=22'
+    pandas: '>=1.5'
+    python: '>=3.9'
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   category: main
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-- name: r-sf
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   manager: conda
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+  platform: osx-64
   dependencies:
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-    r-base: '>=4.1,<4.2.0a0'
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-  url: https://conda.anaconda.org/conda-forge/win-64/r-sf-1.0_7-r41ha856d6a_6.conda
+    python: '>=3.9'
+    numpy: '>=1.23'
+    packaging: '>=22'
+    pandas: '>=1.5'
+  url: https://conda.anaconda.org/conda-forge/noarch/xarray-2024.2.0-pyhd8ed1ab_0.conda
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-- name: r-spatialwidget
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   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/r-spatialwidget-0.2.3-r41ha856d6a_2.conda
+    python: '>=3.9'
+    packaging: '>=21.3'
+    pandas: '>=1.4'
+    numpy: '>=1.22'
+  url: https://conda.anaconda.org/conda-forge/noarch/xarray-2023.10.1-pyhd8ed1ab_0.conda
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-- name: r-tibble
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   manager: conda
   platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/r-tibble-3.2.1-r41h6d2157b_2.conda
+    python: '>=3.9'
+    numpy: '>=1.23'
+    packaging: '>=22'
+    pandas: '>=1.5'
+  url: https://conda.anaconda.org/conda-forge/noarch/xarray-2024.2.0-pyhd8ed1ab_0.conda
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-- name: sensorml2iso
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+- name: xerces-c
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   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    python: ''
-    numpy: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/sensorml2iso-1.0.5-py_0.tar.bz2
+    icu: '>=73.2,<74.0a0'
+    libcurl: '>=8.5.0,<9.0a0'
+    libgcc-ng: '>=12'
+    libnsl: '>=2.0.1,<2.1.0a0'
+    libstdcxx-ng: '>=12'
+  url: https://conda.anaconda.org/conda-forge/linux-64/xerces-c-3.2.5-hac6953d_0.conda
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-- name: jupyter
-  version: 1.0.0
+- name: xerces-c
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   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-    notebook: ''
-    ipykernel: ''
-    nbconvert: ''
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-    qtconsole-base: ''
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-1.0.0-pyhd8ed1ab_10.conda
+    icu: '>=73.2,<74.0a0'
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+    libcxx: '>=15'
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-- name: r-dplyr
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   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/win-64/r-dplyr-1.1.3-r41ha856d6a_0.conda
+    icu: '>=73.2,<74.0a0'
+    libcurl: '>=8.2.1,<9.0a0'
+    libcxx: '>=15.0.7'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/xerces-c-3.2.4-hd886eac_3.conda
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   optional: false
-- name: r-ggplot2
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   manager: conda
   platform: win-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-ggplot2-3.4.2-r41hc72bb7e_0.conda
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/xerces-c-3.2.5-h63175ca_0.conda
   hash:
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   optional: false
-- name: r-irdisplay
-  version: '1.1'
+- name: xlrd
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   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    r-repr: ''
-    r-base: '>=4.1,<4.2.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-irdisplay-1.1-r41hd8ed1ab_1.tar.bz2
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/xlrd-2.0.1-pyhd8ed1ab_3.tar.bz2
   hash:
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   optional: false
-- name: r-rematch2
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+  version: 2.0.1
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-    r-base: '>=4.1,<4.2.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-rematch2-2.1.2-r41hc72bb7e_2.tar.bz2
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/xlrd-2.0.1-pyhd8ed1ab_3.tar.bz2
   hash:
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-- name: r-rgexf
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+- name: xlrd
+  version: 2.0.1
   manager: conda
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+  platform: osx-arm64
   dependencies:
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-    r-xml: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-rgexf-0.16.2-r41hc72bb7e_1.tar.bz2
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/xlrd-2.0.1-pyhd8ed1ab_3.tar.bz2
   hash:
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   optional: false
-- name: r-rmarkdown
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+- name: xlrd
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   manager: conda
   platform: win-64
   dependencies:
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-    r-xfun: '>=0.36'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-rmarkdown-2.22-r41hc72bb7e_0.conda
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/xlrd-2.0.1-pyhd8ed1ab_3.tar.bz2
   hash:
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   optional: false
-- name: r-shiny
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+- name: xmltodict
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   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-shiny-1.7.4-r41h785f33e_0.conda
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/xmltodict-0.13.0-pyhd8ed1ab_0.tar.bz2
   hash:
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   optional: false
-- name: r-vroom
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   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
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-    m2w64-gcc-libs-core: ''
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-  url: https://conda.anaconda.org/conda-forge/win-64/r-vroom-1.6.4-r41ha856d6a_0.conda
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/xmltodict-0.13.0-pyhd8ed1ab_0.tar.bz2
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   optional: false
-- name: r-worrms
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   manager: conda
-  platform: win-64
+  platform: osx-arm64
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-worrms-0.4.2-r41h785f33e_1.tar.bz2
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/xmltodict-0.13.0-pyhd8ed1ab_0.tar.bz2
   hash:
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   optional: false
-- name: r-cowplot
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+- name: xmltodict
+  version: 0.13.0
   manager: conda
   platform: win-64
   dependencies:
-    r-rlang: ''
-    r-scales: ''
-    r-gtable: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-cowplot-1.1.1-r41hc72bb7e_1.tar.bz2
+    python: '>=3.6'
+  url: https://conda.anaconda.org/conda-forge/noarch/xmltodict-0.13.0-pyhd8ed1ab_0.tar.bz2
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   category: main
   optional: false
-- name: r-eml
-  version: 2.0.6.1
+- name: xorg-kbproto
+  version: 1.0.7
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    r-dplyr: ''
-    r-jsonlite: ''
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-    r-xml2: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-eml-2.0.6.1-r41hc72bb7e_1.tar.bz2
+    libgcc-ng: '>=9.3.0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/xorg-kbproto-1.0.7-h7f98852_1002.tar.bz2
   hash:
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-- name: r-htmlwidgets
-  version: 1.6.2
+- name: xorg-libice
+  version: 1.1.1
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    r-rmarkdown: ''
-    r-yaml: ''
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-    r-jsonlite: '>=0.9.16'
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-htmlwidgets-1.6.2-r41hc72bb7e_0.conda
+    libgcc-ng: '>=12'
+  url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libice-1.1.1-hd590300_0.conda
   hash:
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   category: main
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-- name: r-irkernel
-  version: 1.3.2
+- name: xorg-libsm
+  version: 1.2.4
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    r-digest: ''
-    r-crayon: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-irkernel-1.3.2-r41h785f33e_0.conda
+    libgcc-ng: '>=12'
+    libuuid: '>=2.38.1,<3.0a0'
+    xorg-libice: '>=1.1.1,<2.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libsm-1.2.4-h7391055_0.conda
   hash:
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-- name: r-miniui
-  version: 0.1.1.1
+- name: xorg-libx11
+  version: 1.8.7
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
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-    r-htmltools: '>=0.3'
-    r-shiny: '>=0.13'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-miniui-0.1.1.1-r41hc72bb7e_1003.tar.bz2
+    libgcc-ng: '>=12'
+    libxcb: '>=1.15,<1.16.0a0'
+    xorg-kbproto: ''
+    xorg-xextproto: '>=7.3.0,<8.0a0'
+    xorg-xproto: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libx11-1.8.7-h8ee46fc_0.conda
   hash:
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   optional: false
-- name: r-readr
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+- name: xorg-libxau
+  version: 1.0.11
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    m2w64-gcc-libs: ''
-    m2w64-gcc-libs-core: ''
-    r-base: '>=4.1,<4.2.0a0'
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-  url: https://conda.anaconda.org/conda-forge/win-64/r-readr-2.1.4-r41ha856d6a_1.conda
+    libgcc-ng: '>=12'
+  url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxau-1.0.11-hd590300_0.conda
   hash:
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   optional: false
-- name: r-rerddap
-  version: 1.0.2
+- name: xorg-libxau
+  version: 1.0.11
   manager: conda
-  platform: win-64
-  dependencies:
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-    r-digest: ''
-    r-base: '>=4.1,<4.2.0a0'
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-rerddap-1.0.2-r41hc72bb7e_0.conda
+  platform: osx-64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-64/xorg-libxau-1.0.11-h0dc2134_0.conda
   hash:
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   optional: false
-- name: r-tidyr
-  version: 1.3.0
+- name: xorg-libxau
+  version: 1.0.11
+  manager: conda
+  platform: osx-arm64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/xorg-libxau-1.0.11-hb547adb_0.conda
+  hash:
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+  optional: false
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   manager: conda
   platform: win-64
   dependencies:
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     m2w64-gcc-libs-core: ''
-    r-base: '>=4.1,<4.2.0a0'
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-  url: https://conda.anaconda.org/conda-forge/win-64/r-tidyr-1.3.0-r41ha856d6a_1.conda
+  url: https://conda.anaconda.org/conda-forge/win-64/xorg-libxau-1.0.11-hcd874cb_0.conda
   hash:
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   optional: false
-- name: r-viridis
-  version: 0.6.3
+- name: xorg-libxdmcp
+  version: 1.1.3
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    r-gridextra: ''
-    r-base: '>=4.1,<4.2.0a0'
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-viridis-0.6.3-r41hc72bb7e_0.conda
+    libgcc-ng: '>=9.3.0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxdmcp-1.1.3-h7f98852_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: r-waldo
-  version: 0.5.1
+- name: xorg-libxdmcp
+  version: 1.1.3
   manager: conda
-  platform: win-64
-  dependencies:
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-    r-glue: ''
-    r-cli: ''
-    r-fansi: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-waldo-0.5.1-r41hc72bb7e_0.conda
+  platform: osx-64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-64/xorg-libxdmcp-1.1.3-h35c211d_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: r-dt
-  version: '0.28'
+- name: xorg-libxdmcp
+  version: 1.1.3
   manager: conda
-  platform: win-64
-  dependencies:
-    r-magrittr: ''
-    r-crosstalk: ''
-    r-promises: ''
-    r-jquerylib: ''
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-    r-htmlwidgets: '>=1.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-dt-0.28-r41hc72bb7e_0.conda
+  platform: osx-arm64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/xorg-libxdmcp-1.1.3-h27ca646_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: r-finch
-  version: 0.4.0
+- name: xorg-libxdmcp
+  version: 1.1.3
   manager: conda
   platform: win-64
   dependencies:
-    r-digest: ''
-    r-plyr: ''
-    r-rappdirs: ''
-    r-base: '>=4.1,<4.2.0a0'
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-  url: https://conda.anaconda.org/conda-forge/noarch/r-finch-0.4.0-r41hc72bb7e_1.tar.bz2
+    m2w64-gcc-libs: ''
+  url: https://conda.anaconda.org/conda-forge/win-64/xorg-libxdmcp-1.1.3-hcd874cb_0.tar.bz2
   hash:
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   optional: false
-- name: r-ggfortify
-  version: 0.4.16
+- name: xorg-libxext
+  version: 1.3.4
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    r-tibble: ''
-    r-tidyr: ''
-    r-stringr: ''
-    r-scales: ''
-    r-gridextra: ''
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-    r-dplyr: '>=0.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-ggfortify-0.4.16-r41hc72bb7e_0.conda
+    libgcc-ng: '>=12'
+    xorg-libx11: '>=1.7.2,<2.0a0'
+    xorg-xextproto: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxext-1.3.4-h0b41bf4_2.conda
   hash:
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   optional: false
-- name: r-leaflet
-  version: 2.1.2
+- name: xorg-libxrender
+  version: 0.9.11
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    r-magrittr: ''
-    r-htmltools: ''
-    r-base64enc: ''
-    r-htmlwidgets: ''
-    r-rcolorbrewer: ''
-    r-sp: ''
-    r-raster: ''
-    r-png: ''
-    r-markdown: ''
-    r-crosstalk: ''
-    r-base: '>=4.1,<4.2.0a0'
-    r-scales: '>=1.0.0'
-    r-viridis: '>=0.5.1'
-    r-leaflet.providers: '>=1.8.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-leaflet-2.1.2-r41hc72bb7e_0.conda
+    libgcc-ng: '>=12'
+    xorg-libx11: '>=1.8.6,<2.0a0'
+    xorg-renderproto: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxrender-0.9.11-hd590300_0.conda
   hash:
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   category: main
   optional: false
-- name: r-leafpop
-  version: 0.1.0
+- name: xorg-libxt
+  version: 1.3.0
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    m2w64-gcc-libs: ''
-    m2w64-gcc-libs-core: ''
-    r-base: '>=4.1,<4.2.0a0'
-    r-base64enc: ''
-    r-brew: ''
-    r-htmltools: ''
-    r-htmlwidgets: ''
-    r-sf: ''
-    r-svglite: ''
-    r-uuid: ''
-  url: https://conda.anaconda.org/conda-forge/win-64/r-leafpop-0.1.0-r41ha856d6a_2.conda
+    libgcc-ng: '>=12'
+    xorg-kbproto: ''
+    xorg-libice: '>=1.1.1,<2.0a0'
+    xorg-libsm: '>=1.2.4,<2.0a0'
+    xorg-libx11: '>=1.8.6,<2.0a0'
+    xorg-xproto: ''
+  url: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxt-1.3.0-hd590300_1.conda
   hash:
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   category: main
   optional: false
-- name: r-mapdeck
-  version: 0.3.4
+- name: xorg-renderproto
+  version: 0.11.1
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    m2w64-gcc-libs: ''
-    m2w64-gcc-libs-core: ''
-    r-base: '>=4.1,<4.2.0a0'
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-    r-geojsonsf: '>=1.3.3'
-    r-geometries: ''
-    r-googlepolylines: '>=0.7.2'
-    r-htmlwidgets: ''
-    r-jsonify: '>=1.1.1'
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-    r-rapidjsonr: ''
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-    r-sfheaders: '>=0.2.2'
-    r-shiny: ''
-    r-spatialwidget: '>=0.2.3'
-  url: https://conda.anaconda.org/conda-forge/win-64/r-mapdeck-0.3.4-r41ha856d6a_3.conda
+    libgcc-ng: '>=9.3.0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/xorg-renderproto-0.11.1-h7f98852_1002.tar.bz2
   hash:
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-    sha256: 6f1d78109307f4334f9673f3f302fccf2574274066fccb58c6a8c702deb7d076
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   category: main
   optional: false
-- name: r-testthat
-  version: 3.2.0
+- name: xorg-xextproto
+  version: 7.3.0
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    m2w64-gcc-libs: ''
-    m2w64-gcc-libs-core: ''
-    r-base: '>=4.1,<4.2.0a0'
-    r-brio: ''
-    r-callr: '>=3.5.1'
-    r-cli: ''
-    r-crayon: '>=1.3.4'
-    r-desc: ''
-    r-digest: ''
-    r-ellipsis: '>=0.2.0'
-    r-evaluate: ''
-    r-jsonlite: ''
-    r-lifecycle: ''
-    r-magrittr: ''
-    r-pkgload: ''
-    r-praise: ''
-    r-processx: ''
-    r-ps: '>=1.3.4'
-    r-r6: '>=2.2.0'
-    r-rlang: '>=0.4.1'
-    r-waldo: '>=0.2.1'
-    r-withr: '>=2.0.0'
-  url: https://conda.anaconda.org/conda-forge/win-64/r-testthat-3.2.0-r41ha856d6a_0.conda
+    libgcc-ng: '>=12'
+  url: https://conda.anaconda.org/conda-forge/linux-64/xorg-xextproto-7.3.0-h0b41bf4_1003.conda
   hash:
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-    sha256: 2a17ec95003549cacb993ec92adc8727390fc564ef4d911503c6e0ff4a0c57f5
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+    sha256: b8dda3b560e8a7830fe23be1c58cc41f407b2e20ae2f3b6901eb5842ba62b743
   category: main
   optional: false
-- name: r-visnetwork
-  version: 2.1.2
+- name: xorg-xproto
+  version: 7.0.31
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    r-magrittr: ''
-    r-jsonlite: ''
-    r-htmltools: ''
-    r-htmlwidgets: ''
-    r-base: '>=4.1,<4.2.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-visnetwork-2.1.2-r41hc72bb7e_1.tar.bz2
+    libgcc-ng: '>=9.3.0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/xorg-xproto-7.0.31-h7f98852_1007.tar.bz2
   hash:
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-    sha256: b9e8ec60f9c56a6c0e3c38e21042496a23ccb584602b1c9a2d637305cddbfa28
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   category: main
   optional: false
-- name: r-xtractomatic
-  version: 3.4.2
+- name: xyzservices
+  version: 2023.10.1
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    r-dplyr: ''
-    r-httr: ''
-    r-sp: ''
-    r-readr: ''
-    r-ncdf4: ''
-    r-base: '>=4.1,<4.2.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-xtractomatic-3.4.2-r41h785f33e_3.tar.bz2
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/xyzservices-2023.10.1-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 2e7311258a795231490df9c279e47d032f3bcfb8730df9667b032137b48e0ed4
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+    sha256: da655e2e0a742fddefeeaf2dd828b62a1820a3755d13341e1a555a10fcb9cf81
   category: main
   optional: false
-- name: r-diagrammer
-  version: 1.0.10
+- name: xyzservices
+  version: 2023.10.1
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    r-base: '>=4.1,<4.2.0a0'
-    r-magrittr: '>=1.5'
-    r-rlang: '>=0.2.0'
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-    r-rstudioapi: '>=0.7'
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-    r-dplyr: '>=0.7.4'
-    r-purrr: '>=0.2.4'
-    r-scales: '>=0.5.0'
-    r-tidyr: '>=0.8.0'
-    r-stringr: '>=1.3.0'
-    r-htmlwidgets: '>=1.0'
-    r-rcolorbrewer: '>=1.1_2'
-    r-influencer: '>=0.1.0'
-    r-rgexf: '>=0.15.3'
-    r-downloader: '>=0.4'
-    r-igraph: '>=1.1.2'
-    r-viridis: '>=0.5.0'
-    r-visnetwork: '>=2.0.3'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-diagrammer-1.0.10-r41hc72bb7e_0.conda
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/xyzservices-2023.10.1-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 70bbe1f82c808b48679fb01b470bb13089e021e15844a23c193adfc793aa60cd
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+    sha256: da655e2e0a742fddefeeaf2dd828b62a1820a3755d13341e1a555a10fcb9cf81
   category: main
   optional: false
-- name: r-gsw
-  version: '1.1_1'
+- name: xyzservices
+  version: 2023.10.1
   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
-    m2w64-gcc-libs: ''
-    m2w64-gcc-libs-core: ''
-    r-base: '>=4.1,<4.2.0a0'
-    r-testthat: ''
-  url: https://conda.anaconda.org/conda-forge/win-64/r-gsw-1.1_1-r41hcd874cb_1.conda
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/xyzservices-2023.10.1-pyhd8ed1ab_0.conda
   hash:
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+    sha256: da655e2e0a742fddefeeaf2dd828b62a1820a3755d13341e1a555a10fcb9cf81
   category: main
   optional: false
-- name: r-leafem
-  version: 0.2.0
+- name: xyzservices
+  version: 2023.10.1
   manager: conda
   platform: win-64
   dependencies:
-    r-base64enc: ''
-    r-htmlwidgets: ''
-    r-sp: ''
-    r-raster: ''
-    r-sf: ''
-    r-png: ''
-    r-mapdeck: ''
-    r-base: '>=4.1,<4.2.0a0'
-    r-scales: '>=1.0.0'
-    r-htmltools: '>=0.3'
-    r-leaflet: '>=2.0.1'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-leafem-0.2.0-r41h785f33e_1.tar.bz2
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/xyzservices-2023.10.1-pyhd8ed1ab_0.conda
   hash:
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+    sha256: da655e2e0a742fddefeeaf2dd828b62a1820a3755d13341e1a555a10fcb9cf81
   category: main
   optional: false
-- name: r-leaflet.extras
-  version: 1.0.0
+- name: xz
+  version: 5.2.6
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    r-magrittr: ''
-    r-stringr: ''
-    r-htmltools: ''
-    r-htmlwidgets: ''
-    r-base: '>=4.1,<4.2.0a0'
-    r-leaflet: '>=2.0.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-leaflet.extras-1.0.0-r41hc72bb7e_1005.tar.bz2
+    libgcc-ng: '>=12'
+  url: https://conda.anaconda.org/conda-forge/linux-64/xz-5.2.6-h166bdaf_0.tar.bz2
   hash:
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+    sha256: 03a6d28ded42af8a347345f82f3eebdd6807a08526d47899a42d62d319609162
   category: main
   optional: false
-- name: r-leafpm
-  version: 0.1.0
+- name: xz
+  version: 5.2.6
   manager: conda
-  platform: win-64
-  dependencies:
-    r-dplyr: ''
-    r-jsonlite: ''
-    r-htmlwidgets: ''
-    r-base: '>=4.1,<4.2.0a0'
-    r-htmltools: '>=0.3'
-    r-leaflet: '>=2.0.1'
-    r-sf: '>=0.5_2'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-leafpm-0.1.0-r41hc72bb7e_4.tar.bz2
+  platform: osx-64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-64/xz-5.2.6-h775f41a_0.tar.bz2
   hash:
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+    sha256: eb09823f34cc2dd663c0ec4ab13f246f45dcd52e5b8c47b9864361de5204a1c8
   category: main
   optional: false
-- name: r-data.tree
-  version: 1.0.0
+- name: xz
+  version: 5.2.6
   manager: conda
-  platform: win-64
-  dependencies:
-    r-stringr: ''
-    r-r6: ''
-    r-base: '>=4.1,<4.2.0a0'
-    r-diagrammer: '>=1.0.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-data.tree-1.0.0-r41hd8ed1ab_1.tar.bz2
+  platform: osx-arm64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/xz-5.2.6-h57fd34a_0.tar.bz2
   hash:
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   category: main
   optional: false
-- name: r-mapview
-  version: 2.11.0
+- name: xz
+  version: 5.2.6
   manager: conda
   platform: win-64
   dependencies:
-    r-htmltools: ''
-    r-base64enc: ''
-    r-htmlwidgets: ''
-    r-lattice: ''
-    r-sp: ''
-    r-raster: ''
-    r-sf: ''
-    r-png: ''
-    r-webshot: ''
-    r-servr: ''
-    r-leafem: ''
-    r-leafpop: ''
-    r-satellite: ''
-    r-base: '>=4.1,<4.2.0a0'
-    r-scales: '>=0.2.5'
-    r-leaflet: '>=2.0.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-mapview-2.11.0-r41hc72bb7e_1.tar.bz2
+    vc: '>=14.1,<15'
+    vs2015_runtime: '>=14.16.27033'
+  url: https://conda.anaconda.org/conda-forge/win-64/xz-5.2.6-h8d14728_0.tar.bz2
   hash:
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-    sha256: 009b17cc70c50282489cb19cc4e3a005e76e58ab5ae7fa354ba97dcc0557f127
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+    sha256: 54d9778f75a02723784dc63aff4126ff6e6749ba21d11a6d03c1f4775f269fe0
   category: main
   optional: false
-- name: r-oce
-  version: '1.8_1'
+- name: yaml
+  version: 0.2.5
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    m2w64-gcc-libs: ''
-    m2w64-gcc-libs-core: ''
-    r-base: '>=4.1,<4.2.0a0'
-    r-gsw: ''
-    r-rcpp: ''
-    r-sf: ''
-    r-testthat: ''
-  url: https://conda.anaconda.org/conda-forge/win-64/r-oce-1.8_1-r41h644b939_0.conda
+    libgcc-ng: '>=9.4.0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/yaml-0.2.5-h7f98852_2.tar.bz2
   hash:
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-    sha256: 7428fc2b71fe88202a305480428d8acbd7cd60d9ca394b83ec4b21bcf7e5c18b
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+    sha256: a4e34c710eeb26945bdbdaba82d3d74f60a78f54a874ec10d373811a5d217535
   category: main
   optional: false
-- name: r-mapedit
-  version: 0.6.0
+- name: yaml
+  version: 0.2.5
   manager: conda
-  platform: win-64
-  dependencies:
-    r-dplyr: ''
-    r-jsonlite: ''
-    r-shiny: ''
-    r-htmlwidgets: ''
-    r-miniui: ''
-    r-mapview: ''
-    r-leafpm: ''
-    r-base: '>=4.1,<4.2.0a0'
-    r-htmltools: '>=0.3'
-    r-leaflet: '>=2.0.1'
-    r-sf: '>=0.5_2'
-    r-leaflet.extras: '>=1.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-mapedit-0.6.0-r41h785f33e_2.tar.bz2
+  platform: osx-64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-64/yaml-0.2.5-h0d85af4_2.tar.bz2
   hash:
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-    sha256: 2227bc56fa23c73f42a72a61557197a0a3df2daf267e7e5bf3d62a3a533770b6
+    md5: d7e08fcf8259d742156188e8762b4d20
+    sha256: 5301417e2c8dea45b401ffee8df3957d2447d4ce80c83c5ff151fc6bfe1c4148
   category: main
   optional: false
-- name: r-obistools
-  version: 0.0.10
+- name: yaml
+  version: 0.2.5
   manager: conda
-  platform: win-64
-  dependencies:
-    r-ggplot2: ''
-    r-dplyr: ''
-    r-jsonlite: ''
-    r-tidyr: ''
-    r-stringr: ''
-    r-digest: ''
-    r-httr: ''
-    r-xml2: ''
-    r-knitr: ''
-    r-rmarkdown: ''
-    r-sp: ''
-    r-rappdirs: ''
-    r-raster: ''
-    r-sf: ''
-    r-maps: ''
-    r-cowplot: ''
-    r-rgdal: ''
-    r-rgeos: ''
-    r-leaflet: ''
-    r-data.tree: ''
-    r-geosphere: ''
-    r-worrms: ''
-    r-base: '>=4.1,<4.2.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-obistools-0.0.10-r41hd8ed1ab_2.conda
+  platform: osx-arm64
+  dependencies: {}
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/yaml-0.2.5-h3422bc3_2.tar.bz2
   hash:
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-    sha256: b70c60b68e5ccb1e830c9c95772cc49edb68b7f8ae6291a278c734d95a7be65f
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+    sha256: 93181a04ba8cfecfdfb162fc958436d868cc37db504c58078eab4c1a3e57fbb7
   category: main
   optional: false
-- name: r-robis
-  version: 2.11.3
+- name: yaml
+  version: 0.2.5
   manager: conda
   platform: win-64
   dependencies:
-    r-rlang: ''
-    r-ggplot2: ''
-    r-dplyr: ''
-    r-tibble: ''
-    r-purrr: ''
-    r-jsonlite: ''
-    r-tidyr: ''
-    r-stringr: ''
-    r-data.table: ''
-    r-httr: ''
-    r-xml2: ''
-    r-tidyselect: ''
-    r-curl: ''
-    r-sf: ''
-    r-leaflet: ''
-    r-mapedit: ''
-    r-httpcache: ''
-    r-base: '>=4.1,<4.2.0a0'
-  url: https://conda.anaconda.org/conda-forge/noarch/r-robis-2.11.3-r41hc72bb7e_1.tar.bz2
+    vc: '>=14.1,<15.0a0'
+    vs2015_runtime: '>=14.16.27012'
+  url: https://conda.anaconda.org/conda-forge/win-64/yaml-0.2.5-h8ffe710_2.tar.bz2
   hash:
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-    sha256: 480eb4253bb87f6e9064ddcc38c227ddb37210a30f27e1640b2d18d98d79ed76
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+    sha256: 4e2246383003acbad9682c7c63178e2e715ad0eb84f03a8df1fbfba455dfedc5
   category: main
   optional: false
-- name: myst-parser
-  version: 0.18.1
+- name: zarr
+  version: 2.17.0
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    pyyaml: ''
-    typing-extensions: ''
-    jinja2: ''
-    python: '>=3.7'
-    markdown-it-py: '>=1.0.0,<3.0.0'
-    sphinx: '>=4,<6'
-    docutils: '>=0.15,<0.20'
-    mdit-py-plugins: '>=0.3.1,<1'
-  url: https://conda.anaconda.org/conda-forge/noarch/myst-parser-0.18.1-pyhd8ed1ab_0.tar.bz2
+    asciitree: ''
+    fasteners: ''
+    numcodecs: '>=0.10.0'
+    numpy: '>=1.20,!=1.21.0'
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/zarr-2.17.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 260812a430adee3598103d75704c1c855a9816a3895971ca0190d0f5e1e8165a
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+    sha256: 50793d7e1b9e1f3bc5ef9460f04289189def7e202ee9ea8cfc16574d4780abad
   category: main
   optional: false
-- name: myst-nb
-  version: 0.17.2
+- name: zarr
+  version: 2.17.0
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    pyyaml: ''
-    typing_extensions: ''
-    ipython: ''
-    importlib-metadata: ''
-    ipykernel: ''
-    nbclient: ''
-    python: '>=3.7'
-    nbformat: '>=5.0,<6'
-    sphinx: '>=4,<6'
-    myst-parser: '>=0.18.0,<0.19.0'
-    jupyter-cache: '>=0.5.0,<0.7.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/myst-nb-0.17.2-pyhd8ed1ab_0.conda
+    fasteners: ''
+    asciitree: ''
+    python: '>=3.8'
+    numcodecs: '>=0.10.0'
+    numpy: '>=1.20,!=1.21.0'
+  url: https://conda.anaconda.org/conda-forge/noarch/zarr-2.17.0-pyhd8ed1ab_0.conda
   hash:
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-- name: pydata-sphinx-theme
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   manager: conda
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+  platform: osx-arm64
   dependencies:
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-    beautifulsoup4: ''
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     python: '>=3.8'
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-  url: https://conda.anaconda.org/conda-forge/noarch/pydata-sphinx-theme-0.14.2-pyhd8ed1ab_0.conda
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-- name: sphinx-book-theme
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   manager: conda
   platform: win-64
   dependencies:
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+    numcodecs: '>=0.10.0'
+    numpy: '>=1.20,!=1.21.0'
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   optional: false
-- name: sphinx-comments
-  version: 0.0.3
+- name: zeromq
+  version: 4.3.5
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    python: ''
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-  url: https://conda.anaconda.org/conda-forge/noarch/sphinx-comments-0.0.3-pyh9f0ad1d_0.tar.bz2
+    libgcc-ng: '>=12'
+    libsodium: '>=1.0.18,<1.0.19.0a0'
+    libstdcxx-ng: '>=12'
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-- name: sphinx-copybutton
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+  version: 4.3.5
   manager: conda
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+  platform: osx-64
   dependencies:
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-    sphinx: '>=1.8'
-  url: https://conda.anaconda.org/conda-forge/noarch/sphinx-copybutton-0.5.2-pyhd8ed1ab_0.conda
+    __osx: '>=10.9'
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-- name: sphinx-design
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+- name: zeromq
+  version: 4.3.5
   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
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-    sphinx: '>=4,<6'
-  url: https://conda.anaconda.org/conda-forge/noarch/sphinx-design-0.3.0-pyhd8ed1ab_0.tar.bz2
+    __osx: '>=10.9'
+    libcxx: '>=16.0.6'
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+  url: https://conda.anaconda.org/conda-forge/osx-arm64/zeromq-4.3.5-h965bd2d_0.conda
   hash:
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-- name: sphinx-external-toc
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+  version: 4.3.5
   manager: conda
   platform: win-64
   dependencies:
-    pyyaml: ''
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-    click: '>=7.1,<9'
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-  url: https://conda.anaconda.org/conda-forge/noarch/sphinx-external-toc-0.3.1-pyhd8ed1ab_1.conda
+    libsodium: '>=1.0.18,<1.0.19.0a0'
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+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
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   hash:
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   category: main
   optional: false
-- name: sphinx-jupyterbook-latex
-  version: 0.5.2
+- name: zipp
+  version: 3.17.0
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    importlib_resources: ''
-    python: '>=3.6'
-    sphinx: '>=3,<5.1'
-  url: https://conda.anaconda.org/conda-forge/noarch/sphinx-jupyterbook-latex-0.5.2-pyhd8ed1ab_0.tar.bz2
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/zipp-3.17.0-pyhd8ed1ab_0.conda
   hash:
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-- name: sphinx-multitoc-numbering
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+- name: zipp
+  version: 3.17.0
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    python: '>=3.6'
-    sphinx: '>=3'
-  url: https://conda.anaconda.org/conda-forge/noarch/sphinx-multitoc-numbering-0.1.3-pyhd8ed1ab_0.tar.bz2
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/zipp-3.17.0-pyhd8ed1ab_0.conda
   hash:
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   category: main
   optional: false
-- name: sphinx-thebe
-  version: 0.2.1
+- name: zipp
+  version: 3.17.0
   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
-    python: '>=3.6'
-    sphinx: '>=4,<7'
-  url: https://conda.anaconda.org/conda-forge/noarch/sphinx-thebe-0.2.1-pyhd8ed1ab_0.conda
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/zipp-3.17.0-pyhd8ed1ab_0.conda
   hash:
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+    sha256: bced1423fdbf77bca0a735187d05d9b9812d2163f60ab426fc10f11f92ecbe26
   category: main
   optional: false
-- name: sphinx-togglebutton
-  version: 0.3.2
+- name: zipp
+  version: 3.17.0
   manager: conda
   platform: win-64
   dependencies:
-    sphinx: ''
-    docutils: ''
-    python: '>=3.6'
-  url: https://conda.anaconda.org/conda-forge/noarch/sphinx-togglebutton-0.3.2-pyhd8ed1ab_0.tar.bz2
+    python: '>=3.8'
+  url: https://conda.anaconda.org/conda-forge/noarch/zipp-3.17.0-pyhd8ed1ab_0.conda
   hash:
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-    sha256: 0dcee238aae6337fae5eaf1f9a29b0c51ed9834ae501fccb2cde0fed8dae1a88
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+    sha256: bced1423fdbf77bca0a735187d05d9b9812d2163f60ab426fc10f11f92ecbe26
   category: main
   optional: false
-- name: sphinxcontrib-applehelp
-  version: 1.0.7
+- name: zlib
+  version: 1.2.13
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    python: '>=3.9'
-    sphinx: '>=5'
-  url: https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-applehelp-1.0.7-pyhd8ed1ab_0.conda
+    libgcc-ng: '>=12'
+    libzlib: 1.2.13
+  url: https://conda.anaconda.org/conda-forge/linux-64/zlib-1.2.13-hd590300_5.conda
   hash:
-    md5: aebfabcb60c33a89c1f9290cab49bc93
-    sha256: 67e2b386c7b3c858ead88fa71fe4fa5eb1f4f59d7994d167b3910a744db392d3
+    md5: 68c34ec6149623be41a1933ab996a209
+    sha256: 9887a04d7e7cb14bd2b52fa01858f05a6d7f002c890f618d9fcd864adbfecb1b
   category: main
   optional: false
-- name: sphinxcontrib-bibtex
-  version: 2.5.0
+- name: zlib
+  version: 1.2.13
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    dataclasses: ''
-    python: '>=3.6'
-    pybtex: '>=0.24'
-    importlib_metadata: '>=3.6'
-    docutils: '>=0.8'
-    pybtex-docutils: '>=1'
-    sphinx: '>=2.1'
-  url: https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-bibtex-2.5.0-pyhd8ed1ab_0.tar.bz2
+    libzlib: 1.2.13
+  url: https://conda.anaconda.org/conda-forge/osx-64/zlib-1.2.13-h8a1eda9_5.conda
   hash:
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-    sha256: d5b02d285909b4501a469857b1a88a91a849d5f28bbe64b9e6c3e86d2388d345
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+    sha256: d1f4c82fd7bd240a78ce8905e931e68dca5f523c7da237b6b63c87d5625c5b35
   category: main
   optional: false
-- name: jupyter-book
-  version: 0.15.1
+- name: zlib
+  version: 1.2.13
   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
-    pyyaml: ''
-    jinja2: ''
-    sphinx-copybutton: ''
-    sphinx-togglebutton: ''
-    sphinx-comments: ''
-    python: '>=3.7'
-    click: '>=7.1,<9'
-    sphinx: '>=4,<6'
-    sphinx-multitoc-numbering: '>=0.1.3,<0.2.0'
-    sphinxcontrib-bibtex: '>=2.2.0,<=2.5.0'
-    docutils: '>=0.15,<0.19'
-    jsonschema: <5
-    linkify-it-py: '>=2.0.0,<2.1.0'
-    sphinx-external-toc: '>=0.3.1,<0.4.0'
-    sphinx-jupyterbook-latex: '>=0.5.2,<0.6.0'
-    myst-nb: '>=0.17.1,<0.18.0'
-    sphinx-book-theme: '>=1.0.0,<1.1.0'
-    sphinx-design: '>=0.3.0,<0.4.0'
-    sphinx-thebe: '>=0.2.0,<0.3.0'
-  url: https://conda.anaconda.org/conda-forge/noarch/jupyter-book-0.15.1-pyhd8ed1ab_0.conda
+    libzlib: 1.2.13
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/zlib-1.2.13-h53f4e23_5.conda
   hash:
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-    sha256: b50732cd6ab656781f13aa43b8ce420266508235a1fb4ec7d49ca677dbe2a3d0
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+    sha256: de0ee1e24aa6867058d3b852a15c8d7f49f262f5828772700c647186d4a96bbe
   category: main
   optional: false
-- name: sphinxcontrib-devhelp
-  version: 1.0.5
+- name: zlib
+  version: 1.2.13
   manager: conda
   platform: win-64
   dependencies:
-    python: '>=3.9'
-    sphinx: '>=5'
-  url: https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-devhelp-1.0.5-pyhd8ed1ab_0.conda
+    libzlib: 1.2.13
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/zlib-1.2.13-hcfcfb64_5.conda
   hash:
-    md5: ebf08f5184d8eaa486697bc060031953
-    sha256: 770e13ebfef321426c09ec51d95c57755512db160518b2922a4337546ee51672
+    md5: a318e8622e11663f645cc7fa3260f462
+    sha256: 0f91b719c7558046bcd37fdc7ae4b9eb2b7a8e335beb8b59ae7ccb285a46aa46
   category: main
   optional: false
-- name: sphinxcontrib-htmlhelp
-  version: 2.0.4
+- name: zstd
+  version: 1.5.5
   manager: conda
-  platform: win-64
+  platform: linux-64
   dependencies:
-    python: '>=3.9'
-    sphinx: '>=5'
-  url: https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-htmlhelp-2.0.4-pyhd8ed1ab_0.conda
+    libgcc-ng: '>=12'
+    libstdcxx-ng: '>=12'
+    libzlib: '>=1.2.13,<1.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.5-hfc55251_0.conda
   hash:
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-    sha256: 5f09cd4a08a6c194c11999871a8c7cedc2cd7edd9ff7ceb6f0667b6698be4cc5
+    md5: 04b88013080254850d6c01ed54810589
+    sha256: 607cbeb1a533be98ba96cf5cdf0ddbb101c78019f1fda063261871dad6248609
   category: main
   optional: false
-- name: sphinxcontrib-qthelp
-  version: 1.0.6
+- name: zstd
+  version: 1.5.5
   manager: conda
-  platform: win-64
+  platform: osx-64
   dependencies:
-    python: '>=3.9'
-    sphinx: '>=5'
-  url: https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-qthelp-1.0.6-pyhd8ed1ab_0.conda
+    libzlib: '>=1.2.13,<1.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-64/zstd-1.5.5-h829000d_0.conda
   hash:
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-    sha256: 9ba5cea9cbab64106e8b5a9b19add855dcb52b8fbb1674398c715bccdbc04471
+    md5: 80abc41d0c48b82fe0f04e7f42f5cb7e
+    sha256: d54e31d3d8de5e254c0804abd984807b8ae5cd3708d758a8bf1adff1f5df166c
   category: main
   optional: false
-- name: sphinx
-  version: 5.0.2
+- name: zstd
+  version: 1.5.5
   manager: conda
-  platform: win-64
+  platform: osx-arm64
   dependencies:
-    packaging: ''
-    sphinxcontrib-jsmath: ''
-    sphinxcontrib-applehelp: ''
-    sphinxcontrib-devhelp: ''
-    sphinxcontrib-qthelp: ''
-    imagesize: ''
-    python: '>=3.6'
-    pygments: '>=2.0'
-    alabaster: '>=0.7,<0.8'
-    importlib-metadata: '>=4.4'
-    requests: '>=2.5.0'
-    jinja2: '>=2.3'
-    snowballstemmer: '>=1.1'
-    babel: '>=1.3'
-    sphinxcontrib-htmlhelp: '>=2.0.0'
-    sphinxcontrib-serializinghtml: '>=1.1.5'
-    colorama: '>=0.3.5'
-    docutils: '>=0.14,<0.19'
-  url: https://conda.anaconda.org/conda-forge/noarch/sphinx-5.0.2-pyh6c4a22f_0.tar.bz2
+    libzlib: '>=1.2.13,<1.3.0a0'
+  url: https://conda.anaconda.org/conda-forge/osx-arm64/zstd-1.5.5-h4f39d0f_0.conda
   hash:
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-    sha256: 27fc8d942d1cedba71035399f71e2d81fd411b86c5d8717c813c46143b8d74f8
+    md5: 5b212cfb7f9d71d603ad891879dc7933
+    sha256: 7e1fe6057628bbb56849a6741455bbb88705bae6d6646257e57904ac5ee5a481
   category: main
   optional: false
-- name: sphinxcontrib-serializinghtml
-  version: 1.1.9
+- name: zstd
+  version: 1.5.5
   manager: conda
   platform: win-64
   dependencies:
-    python: '>=3.9'
-    sphinx: '>=5'
-  url: https://conda.anaconda.org/conda-forge/noarch/sphinxcontrib-serializinghtml-1.1.9-pyhd8ed1ab_0.conda
+    libzlib: '>=1.2.13,<1.3.0a0'
+    ucrt: '>=10.0.20348.0'
+    vc: '>=14.2,<15'
+    vc14_runtime: '>=14.29.30139'
+  url: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.5-h12be248_0.conda
   hash:
-    md5: 0612e497d7860728f2cda421ea2aec09
-    sha256: c5710ae7bb7465f25a29cc845d9fb6ad0ea561972d796d379fcb48d801e96d6d
+    md5: 792bb5da68bf0a6cac6a6072ecb8dbeb
+    sha256: d540dd56c5ec772b60e4ce7d45f67f01c6614942225885911964ea1e70bb99e3
   category: main
   optional: false
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 85aa4785..a752c57f 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -23,7 +23,7 @@ repos:
         exclude: "_templates/layout.html"
 
   - repo: https://github.com/psf/black
-    rev: 24.1.1
+    rev: 24.2.0
     hooks:
       - id: black
         language_version: python3
@@ -34,7 +34,7 @@ repos:
       - id: add-trailing-comma
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.2.0
+    rev: v0.2.2
     hooks:
       - id: ruff
 
@@ -47,10 +47,7 @@ repos:
       - id: nbqa-check-ast
       - id: nbqa-black
       - id: nbqa-ruff
-        args: [--fix, --extend-ignore=E402]
-        # Skipping b/c These notebooks mix R and Python and
-        # will return false positive for "F821 Undefined name.""
-        exclude: 2017-11-30-rerddap\.ipynb$|2018-02-20-obis.ipynb$
+        args: [--fix]
 
   - repo: https://github.com/bdice/nb-strip-paths
     rev: 'v0.1.0'
diff --git a/jupyterbook/content/code_gallery/data_analysis_and_visualization_notebooks/2016-11-16-CF-UGRID-SGRID-conventions.ipynb b/jupyterbook/content/code_gallery/data_analysis_and_visualization_notebooks/2016-11-16-CF-UGRID-SGRID-conventions.ipynb
index 3f9eb4e7..3ece688b 100644
--- a/jupyterbook/content/code_gallery/data_analysis_and_visualization_notebooks/2016-11-16-CF-UGRID-SGRID-conventions.ipynb
+++ b/jupyterbook/content/code_gallery/data_analysis_and_visualization_notebooks/2016-11-16-CF-UGRID-SGRID-conventions.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {
     "tags": [
      "remove-cell"
@@ -48,7 +48,7 @@
     "\n",
     "Created: 2019-11-16\n",
     "\n",
-    "Updated: 2022-05-25\n",
+    "Updated: 2023-02-19\n",
     "\n",
     "Metadata conventions, like the Climate and Forecast (CF) conventions,\n",
     "can be cumbersome to adhere to but it will be very handy when you or other users manipulate the data later in time.\n",
@@ -67,50 +67,65 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.8.9\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
+       "SGRID:\n",
+       "             CF role:   grid_topology: ['grid']\n",
        "\n",
-       "- CF Roles:   grid_topology: ['grid']\n",
+       "                Axes: * X: ['xi_psi', 'xi_rho', 'xi_u', 'xi_v']\n",
+       "                      * Y: ['eta_psi', 'eta_rho', 'eta_u', 'eta_v']\n",
+       "                      * Z: ['s_rho', 's_w']\n",
        "\n",
        "Coordinates:\n",
-       "- CF Axes: * Z: ['s_rho', 's_w']\n",
-       "           * T: ['ocean_time']\n",
-       "             X, Y: n/a\n",
+       "             CF Axes: * Z: ['s_rho', 's_w']\n",
+       "                      * T: ['ocean_time']\n",
+       "                        X, Y: n/a\n",
        "\n",
-       "- CF Coordinates:   longitude: ['lon_psi', 'lon_rho', 'lon_u', 'lon_v']\n",
-       "                    latitude: ['lat_psi', 'lat_rho', 'lat_u', 'lat_v']\n",
-       "                  * vertical: ['s_rho', 's_w']\n",
-       "                  * time: ['ocean_time']\n",
+       "      CF Coordinates:   longitude: ['lon_psi', 'lon_rho', 'lon_u', 'lon_v']\n",
+       "                        latitude: ['lat_psi', 'lat_rho', 'lat_u', 'lat_v']\n",
+       "                      * vertical: ['s_rho', 's_w']\n",
+       "                      * time: ['ocean_time']\n",
        "\n",
-       "- Cell Measures:   area, volume: n/a\n",
+       "       Cell Measures:   area, volume: n/a\n",
        "\n",
-       "- Standard Names: * forecast_reference_time: ['run']\n",
-       "                    latitude: ['lat_psi', 'lat_rho', 'lat_u', 'lat_v']\n",
-       "                    longitude: ['lon_psi', 'lon_rho', 'lon_u', 'lon_v']\n",
-       "                  * ocean_s_coordinate_g1: ['s_rho', 's_w']\n",
+       "      Standard Names: * forecast_reference_time: ['run']\n",
+       "                        latitude: ['lat_psi', 'lat_rho', 'lat_u', 'lat_v']\n",
+       "                        longitude: ['lon_psi', 'lon_rho', 'lon_u', 'lon_v']\n",
+       "                      * ocean_s_coordinate_g1: ['s_rho', 's_w']\n",
        "\n",
-       "- Bounds:   n/a\n",
+       "              Bounds:   n/a\n",
+       "\n",
+       "       Grid Mappings:   n/a\n",
        "\n",
        "Data Variables:\n",
-       "- Cell Measures:   area, volume: n/a\n",
+       "       Cell Measures:   area, volume: n/a\n",
+       "\n",
+       "      Standard Names:   sea_floor_depth_below_sea_surface: ['h']\n",
+       "                        sea_surface_elevation_anomaly: ['zeta']\n",
+       "                        sea_water_potential_temperature: ['temp']\n",
+       "                        sea_water_practical_salinity: ['salt']\n",
+       "                        sea_water_x_velocity: ['u']\n",
+       "                        sea_water_y_velocity: ['v']\n",
        "\n",
-       "- Standard Names:   sea_floor_depth_below_sea_surface: ['h']\n",
-       "                    sea_surface_elevation_anomaly: ['zeta']\n",
-       "                    sea_water_potential_temperature: ['temp']\n",
-       "                    sea_water_practical_salinity: ['salt']\n",
-       "                    sea_water_x_velocity: ['u']\n",
-       "                    sea_water_y_velocity: ['v']\n",
+       "              Bounds:   n/a\n",
        "\n",
-       "- Bounds:   n/a"
+       "       Grid Mappings:   n/a"
       ]
      },
-     "execution_count": 1,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -137,17 +152,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/filipe/micromamba/envs/IOOS/lib/python3.11/site-packages/cf_xarray/accessor.py:1638: UserWarning: Variables {'', 'time'} not found in object but are referred to in the CF attributes.\n",
-      "  warnings.warn(\n",
-      "/home/filipe/micromamba/envs/IOOS/lib/python3.11/site-packages/cf_xarray/accessor.py:1638: UserWarning: Variables {''} not found in object but are referred to in the CF attributes.\n",
-      "  warnings.warn(\n"
+      "/tmp/ipykernel_26057/1323880464.py:8: UserWarning: Variables {'', 'time'} not found in object but are referred to in the CF attributes.\n",
+      "  eta = ds.cf[\"zeta\"][run, ocean_time, x, y]\n",
+      "/tmp/ipykernel_26057/1323880464.py:9: UserWarning: Variables {''} not found in object but are referred to in the CF attributes.\n",
+      "  depth = ds.cf[\"h\"][x, y]\n"
      ]
     }
    ],
@@ -186,7 +201,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {
     "scrolled": false
    },
@@ -195,8 +210,8 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/filipe/micromamba/envs/IOOS/lib/python3.11/site-packages/cf_xarray/accessor.py:1638: UserWarning: Variables {'', 'time'} not found in object but are referred to in the CF attributes.\n",
-      "  warnings.warn(\n"
+      "/tmp/ipykernel_26057/4185694592.py:1: UserWarning: Variables {'', 'time'} not found in object but are referred to in the CF attributes.\n",
+      "  temp = ds.cf[\"sea_water_potential_temperature\"]\n"
      ]
     },
     {
@@ -566,13 +581,13 @@
        "  fill: currentColor;\n",
        "}\n",
        "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;temp&#x27; (run: 1929, time: 157, s_rho: 36, eta_rho: 82,\n",
-       "                          xi_rho: 130)&gt;\n",
+       "                          xi_rho: 130)&gt; Size: 465GB\n",
        "[116222867280 values with dtype=float32]\n",
        "Coordinates:\n",
-       "  * s_rho    (s_rho) float64 -0.9861 -0.9583 -0.9306 ... -0.04167 -0.01389\n",
-       "  * run      (run) datetime64[ns] 2013-05-18 2013-05-19 ... 2018-09-14\n",
-       "    lat_rho  (eta_rho, xi_rho) float64 33.74 33.79 33.84 ... 42.78 42.82 42.87\n",
-       "    lon_rho  (eta_rho, xi_rho) float64 -75.84 -75.78 -75.71 ... -71.49 -71.43\n",
+       "  * run      (run) datetime64[ns] 15kB 2013-05-18 2013-05-19 ... 2018-09-14\n",
+       "  * s_rho    (s_rho) float64 288B -0.9861 -0.9583 -0.9306 ... -0.04167 -0.01389\n",
+       "    lat_rho  (eta_rho, xi_rho) float64 85kB 33.74 33.79 33.84 ... 42.82 42.87\n",
+       "    lon_rho  (eta_rho, xi_rho) float64 85kB -75.84 -75.78 ... -71.49 -71.43\n",
        "Dimensions without coordinates: time, eta_rho, xi_rho\n",
        "Attributes:\n",
        "    units:          Celsius\n",
@@ -580,21 +595,21 @@
        "    time:           ocean_time\n",
        "    field:          temperature, scalar, series\n",
        "    _ChunkSizes:    [  1  36  82 130]\n",
-       "    standard_name:  sea_water_potential_temperature</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'temp'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>run</span>: 1929</li><li><span>time</span>: 157</li><li><span class='xr-has-index'>s_rho</span>: 36</li><li><span>eta_rho</span>: 82</li><li><span>xi_rho</span>: 130</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-f46888e6-6e6a-4b0d-bbd0-8928802ec23f' class='xr-array-in' type='checkbox' checked><label for='section-f46888e6-6e6a-4b0d-bbd0-8928802ec23f' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[116222867280 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-0bca19c5-52a2-490c-b283-6d875b019e06' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0bca19c5-52a2-490c-b283-6d875b019e06' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>s_rho</span></div><div class='xr-var-dims'>(s_rho)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.9861 -0.9583 ... -0.01389</div><input id='attrs-3fefe0ed-f401-450b-9770-6543f576ae53' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3fefe0ed-f401-450b-9770-6543f576ae53' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d66d0826-7c89-4e78-a6cd-91a7af6dcd31' class='xr-var-data-in' type='checkbox'><label for='data-d66d0826-7c89-4e78-a6cd-91a7af6dcd31' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>S-coordinate at RHO-points</dd><dt><span>valid_min :</span></dt><dd>-1.0</dd><dt><span>valid_max :</span></dt><dd>0.0</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>ocean_s_coordinate_g1</dd><dt><span>formula_terms :</span></dt><dd>s: s_rho C: Cs_r eta: zeta depth: h depth_c: hc</dd><dt><span>field :</span></dt><dd>s_rho, scalar</dd><dt><span>_CoordinateTransformType :</span></dt><dd>Vertical</dd><dt><span>_CoordinateAxisType :</span></dt><dd>GeoZ</dd><dt><span>_CoordinateZisPositive :</span></dt><dd>up</dd><dt><span>_CoordinateAxes :</span></dt><dd>s_rho</dd></dl></div><div class='xr-var-data'><pre>array([-0.986111, -0.958333, -0.930556, -0.902778, -0.875   , -0.847222,\n",
+       "    standard_name:  sea_water_potential_temperature</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'temp'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>run</span>: 1929</li><li><span>time</span>: 157</li><li><span class='xr-has-index'>s_rho</span>: 36</li><li><span>eta_rho</span>: 82</li><li><span>xi_rho</span>: 130</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-4cfcea24-0e3b-4c66-8630-7fc3ae45f40e' class='xr-array-in' type='checkbox' checked><label for='section-4cfcea24-0e3b-4c66-8630-7fc3ae45f40e' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[116222867280 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-f4475a10-02c9-49f1-86c2-34f40f0f63e7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f4475a10-02c9-49f1-86c2-34f40f0f63e7' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>run</span></div><div class='xr-var-dims'>(run)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2013-05-18 ... 2018-09-14</div><input id='attrs-6d3b2271-434b-416a-8e9a-6b1ae60843ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d3b2271-434b-416a-8e9a-6b1ae60843ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5dfe3b9f-b541-4d98-a2cb-752343f616dc' class='xr-var-data-in' type='checkbox'><label for='data-5dfe3b9f-b541-4d98-a2cb-752343f616dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Run time for ForecastModelRunCollection</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd><dt><span>_CoordinateAxisType :</span></dt><dd>RunTime</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2013-05-18T00:00:00.000000000&#x27;, &#x27;2013-05-19T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2013-05-20T00:00:00.000000000&#x27;, ..., &#x27;2018-09-12T00:00:00.000000000&#x27;,\n",
+       "       &#x27;2018-09-13T00:00:00.000000000&#x27;, &#x27;2018-09-14T00:00:00.000000000&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>s_rho</span></div><div class='xr-var-dims'>(s_rho)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.9861 -0.9583 ... -0.01389</div><input id='attrs-d91b0b8e-b5f4-4217-bd0e-65808a169951' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d91b0b8e-b5f4-4217-bd0e-65808a169951' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-09bf646e-c1be-47ce-b1e9-3579a41af539' class='xr-var-data-in' type='checkbox'><label for='data-09bf646e-c1be-47ce-b1e9-3579a41af539' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd></dd><dt><span>long_name :</span></dt><dd>S-coordinate at RHO-points</dd><dt><span>valid_min :</span></dt><dd>-1.0</dd><dt><span>valid_max :</span></dt><dd>0.0</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>ocean_s_coordinate_g1</dd><dt><span>formula_terms :</span></dt><dd>s: s_rho C: Cs_r eta: zeta depth: h depth_c: hc</dd><dt><span>field :</span></dt><dd>s_rho, scalar</dd><dt><span>_CoordinateTransformType :</span></dt><dd>Vertical</dd><dt><span>_CoordinateAxisType :</span></dt><dd>GeoZ</dd><dt><span>_CoordinateZisPositive :</span></dt><dd>up</dd><dt><span>_CoordinateAxes :</span></dt><dd>s_rho</dd></dl></div><div class='xr-var-data'><pre>array([-0.986111, -0.958333, -0.930556, -0.902778, -0.875   , -0.847222,\n",
        "       -0.819444, -0.791667, -0.763889, -0.736111, -0.708333, -0.680556,\n",
        "       -0.652778, -0.625   , -0.597222, -0.569444, -0.541667, -0.513889,\n",
        "       -0.486111, -0.458333, -0.430556, -0.402778, -0.375   , -0.347222,\n",
        "       -0.319444, -0.291667, -0.263889, -0.236111, -0.208333, -0.180556,\n",
-       "       -0.152778, -0.125   , -0.097222, -0.069444, -0.041667, -0.013889])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>run</span></div><div class='xr-var-dims'>(run)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2013-05-18 ... 2018-09-14</div><input id='attrs-a767f81b-bac4-4efb-a880-9f77fa587de0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a767f81b-bac4-4efb-a880-9f77fa587de0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-043f0457-0677-416e-b260-f50bcf249dae' class='xr-var-data-in' type='checkbox'><label for='data-043f0457-0677-416e-b260-f50bcf249dae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Run time for ForecastModelRunCollection</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd><dt><span>_CoordinateAxisType :</span></dt><dd>RunTime</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2013-05-18T00:00:00.000000000&#x27;, &#x27;2013-05-19T00:00:00.000000000&#x27;,\n",
-       "       &#x27;2013-05-20T00:00:00.000000000&#x27;, ..., &#x27;2018-09-12T00:00:00.000000000&#x27;,\n",
-       "       &#x27;2018-09-13T00:00:00.000000000&#x27;, &#x27;2018-09-14T00:00:00.000000000&#x27;],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_rho</span></div><div class='xr-var-dims'>(eta_rho, xi_rho)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>33.74 33.79 33.84 ... 42.82 42.87</div><input id='attrs-63013d8a-4e73-4b86-8a38-7e2eabbeea72' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63013d8a-4e73-4b86-8a38-7e2eabbeea72' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20dd32c2-0c9e-4073-a721-745aa69d1811' class='xr-var-data-in' type='checkbox'><label for='data-20dd32c2-0c9e-4073-a721-745aa69d1811' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude of RHO-points</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>field :</span></dt><dd>lat_rho, scalar</dd><dt><span>_ChunkSizes :</span></dt><dd>[ 82 130]</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd></dl></div><div class='xr-var-data'><pre>array([[33.744605, 33.794267, 33.843908, ..., 39.803658, 39.849137, 39.894587],\n",
+       "       -0.152778, -0.125   , -0.097222, -0.069444, -0.041667, -0.013889])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_rho</span></div><div class='xr-var-dims'>(eta_rho, xi_rho)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>33.74 33.79 33.84 ... 42.82 42.87</div><input id='attrs-e023e94e-2c26-415a-9e02-d25a708abf4d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e023e94e-2c26-415a-9e02-d25a708abf4d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb0cb29e-363a-429e-93ca-9855bcd9cb65' class='xr-var-data-in' type='checkbox'><label for='data-eb0cb29e-363a-429e-93ca-9855bcd9cb65' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude of RHO-points</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>field :</span></dt><dd>lat_rho, scalar</dd><dt><span>_ChunkSizes :</span></dt><dd>[ 82 130]</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lat</dd></dl></div><div class='xr-var-data'><pre>array([[33.744605, 33.794267, 33.843908, ..., 39.803658, 39.849137, 39.894587],\n",
        "       [33.784963, 33.834601, 33.884218, ..., 39.840616, 39.886067, 39.93149 ],\n",
        "       [33.825301, 33.874916, 33.924509, ..., 39.877575, 39.923   , 39.968397],\n",
        "       ...,\n",
        "       [36.874968, 36.922822, 36.970654, ..., 42.708485, 42.752428, 42.796348],\n",
        "       [36.91383 , 36.961662, 37.009472, ..., 42.744764, 42.788691, 42.832595],\n",
-       "       [36.952673, 37.000482, 37.04827 , ..., 42.781022, 42.824933, 42.868822]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_rho</span></div><div class='xr-var-dims'>(eta_rho, xi_rho)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-75.84 -75.78 ... -71.49 -71.43</div><input id='attrs-e7b7615e-d61c-4e59-ad37-e658527ebe6e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7b7615e-d61c-4e59-ad37-e658527ebe6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63a4477e-8edc-4eb4-b5a7-f330497079d9' class='xr-var-data-in' type='checkbox'><label for='data-63a4477e-8edc-4eb4-b5a7-f330497079d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude of RHO-points</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>field :</span></dt><dd>lon_rho, scalar</dd><dt><span>_ChunkSizes :</span></dt><dd>[ 82 130]</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd></dl></div><div class='xr-var-data'><pre>array([[-75.838286, -75.775218, -75.712149, ..., -67.832953, -67.770109,\n",
+       "       [36.952673, 37.000482, 37.04827 , ..., 42.781022, 42.824933, 42.868822]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_rho</span></div><div class='xr-var-dims'>(eta_rho, xi_rho)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-75.84 -75.78 ... -71.49 -71.43</div><input id='attrs-66618d20-4601-4cb5-b884-1fb0408b9539' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-66618d20-4601-4cb5-b884-1fb0408b9539' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-788f0352-4f86-4e58-8b00-ebfc4cd8c8af' class='xr-var-data-in' type='checkbox'><label for='data-788f0352-4f86-4e58-8b00-ebfc4cd8c8af' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude of RHO-points</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>field :</span></dt><dd>lon_rho, scalar</dd><dt><span>_ChunkSizes :</span></dt><dd>[ 82 130]</dd><dt><span>_CoordinateAxisType :</span></dt><dd>Lon</dd></dl></div><div class='xr-var-data'><pre>array([[-75.838286, -75.775218, -75.712149, ..., -67.832953, -67.770109,\n",
        "        -67.707269],\n",
        "       [-75.884579, -75.821508, -75.758437, ..., -67.879134, -67.816286,\n",
        "        -67.753442],\n",
@@ -606,42 +621,36 @@
        "       [-79.542336, -79.47909 , -79.415844, ..., -71.510168, -71.446923,\n",
        "        -71.383677],\n",
        "       [-79.588635, -79.525386, -79.462137, ..., -71.556099, -71.492851,\n",
-       "        -71.429602]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-44427e13-855d-4e6e-bbdd-d22daa3ebe96' class='xr-section-summary-in' type='checkbox'  ><label for='section-44427e13-855d-4e6e-bbdd-d22daa3ebe96' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>s_rho</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-05fc9df6-3ed7-4e36-aade-9e0b716d6bed' class='xr-index-data-in' type='checkbox'/><label for='index-05fc9df6-3ed7-4e36-aade-9e0b716d6bed' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([   -0.986111111111111,   -0.9583333333333333,\n",
-       "                -0.9305555555555555,   -0.9027777777777777,\n",
-       "                             -0.875,   -0.8472222222222222,\n",
-       "                -0.8194444444444444,   -0.7916666666666666,\n",
-       "                -0.7638888888888888,    -0.736111111111111,\n",
-       "                -0.7083333333333333,   -0.6805555555555555,\n",
-       "                -0.6527777777777778,                -0.625,\n",
-       "                -0.5972222222222222,   -0.5694444444444444,\n",
-       "                -0.5416666666666666,   -0.5138888888888888,\n",
-       "                -0.4861111111111111,   -0.4583333333333333,\n",
-       "                -0.4305555555555555,  -0.40277777777777773,\n",
-       "                             -0.375,   -0.3472222222222222,\n",
-       "                -0.3194444444444444,  -0.29166666666666663,\n",
-       "                -0.2638888888888889,   -0.2361111111111111,\n",
-       "               -0.20833333333333331,  -0.18055555555555555,\n",
-       "               -0.15277777777777776,                -0.125,\n",
-       "               -0.09722222222222221,  -0.06944444444444445,\n",
-       "              -0.041666666666666664, -0.013888888888888888],\n",
-       "             dtype=&#x27;float64&#x27;, name=&#x27;s_rho&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>run</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-055af303-3163-4487-ae66-46f3dbca0e3d' class='xr-index-data-in' type='checkbox'/><label for='index-055af303-3163-4487-ae66-46f3dbca0e3d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2013-05-18&#x27;, &#x27;2013-05-19&#x27;, &#x27;2013-05-20&#x27;, &#x27;2013-05-21&#x27;,\n",
+       "        -71.429602]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4dc413a3-3604-4fdd-9528-eb15fdee6422' class='xr-section-summary-in' type='checkbox'  ><label for='section-4dc413a3-3604-4fdd-9528-eb15fdee6422' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>run</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5eaff841-c311-4425-808a-2737185995e4' class='xr-index-data-in' type='checkbox'/><label for='index-5eaff841-c311-4425-808a-2737185995e4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2013-05-18&#x27;, &#x27;2013-05-19&#x27;, &#x27;2013-05-20&#x27;, &#x27;2013-05-21&#x27;,\n",
        "               &#x27;2013-05-22&#x27;, &#x27;2013-05-23&#x27;, &#x27;2013-05-24&#x27;, &#x27;2013-05-25&#x27;,\n",
        "               &#x27;2013-05-26&#x27;, &#x27;2013-05-27&#x27;,\n",
        "               ...\n",
        "               &#x27;2018-09-05&#x27;, &#x27;2018-09-06&#x27;, &#x27;2018-09-07&#x27;, &#x27;2018-09-08&#x27;,\n",
        "               &#x27;2018-09-09&#x27;, &#x27;2018-09-10&#x27;, &#x27;2018-09-11&#x27;, &#x27;2018-09-12&#x27;,\n",
        "               &#x27;2018-09-13&#x27;, &#x27;2018-09-14&#x27;],\n",
-       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;run&#x27;, length=1929, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a6d2faf1-1aa1-42ee-8726-a38fbcadc2df' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a6d2faf1-1aa1-42ee-8726-a38fbcadc2df' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Celsius</dd><dt><span>long_name :</span></dt><dd>potential temperature</dd><dt><span>time :</span></dt><dd>ocean_time</dd><dt><span>field :</span></dt><dd>temperature, scalar, series</dd><dt><span>_ChunkSizes :</span></dt><dd>[  1  36  82 130]</dd><dt><span>standard_name :</span></dt><dd>sea_water_potential_temperature</dd></dl></div></li></ul></div></div>"
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;run&#x27;, length=1929, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>s_rho</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-dc85a4a0-5fe4-43a4-bcb3-7971e5240495' class='xr-index-data-in' type='checkbox'/><label for='index-dc85a4a0-5fe4-43a4-bcb3-7971e5240495' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   -0.986111111111111,   -0.9583333333333333,   -0.9305555555555555,\n",
+       "         -0.9027777777777777,                -0.875,   -0.8472222222222222,\n",
+       "         -0.8194444444444444,   -0.7916666666666666,   -0.7638888888888888,\n",
+       "          -0.736111111111111,   -0.7083333333333333,   -0.6805555555555555,\n",
+       "         -0.6527777777777778,                -0.625,   -0.5972222222222222,\n",
+       "         -0.5694444444444444,   -0.5416666666666666,   -0.5138888888888888,\n",
+       "         -0.4861111111111111,   -0.4583333333333333,   -0.4305555555555555,\n",
+       "        -0.40277777777777773,                -0.375,   -0.3472222222222222,\n",
+       "         -0.3194444444444444,  -0.29166666666666663,   -0.2638888888888889,\n",
+       "         -0.2361111111111111,  -0.20833333333333331,  -0.18055555555555555,\n",
+       "        -0.15277777777777776,                -0.125,  -0.09722222222222221,\n",
+       "        -0.06944444444444445, -0.041666666666666664, -0.013888888888888888],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;s_rho&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-53b41a15-29f5-4a32-880b-c9eedf481aa1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-53b41a15-29f5-4a32-880b-c9eedf481aa1' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Celsius</dd><dt><span>long_name :</span></dt><dd>potential temperature</dd><dt><span>time :</span></dt><dd>ocean_time</dd><dt><span>field :</span></dt><dd>temperature, scalar, series</dd><dt><span>_ChunkSizes :</span></dt><dd>[  1  36  82 130]</dd><dt><span>standard_name :</span></dt><dd>sea_water_potential_temperature</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.DataArray 'temp' (run: 1929, time: 157, s_rho: 36, eta_rho: 82,\n",
-       "                          xi_rho: 130)>\n",
+       "                          xi_rho: 130)> Size: 465GB\n",
        "[116222867280 values with dtype=float32]\n",
        "Coordinates:\n",
-       "  * s_rho    (s_rho) float64 -0.9861 -0.9583 -0.9306 ... -0.04167 -0.01389\n",
-       "  * run      (run) datetime64[ns] 2013-05-18 2013-05-19 ... 2018-09-14\n",
-       "    lat_rho  (eta_rho, xi_rho) float64 33.74 33.79 33.84 ... 42.78 42.82 42.87\n",
-       "    lon_rho  (eta_rho, xi_rho) float64 -75.84 -75.78 -75.71 ... -71.49 -71.43\n",
+       "  * run      (run) datetime64[ns] 15kB 2013-05-18 2013-05-19 ... 2018-09-14\n",
+       "  * s_rho    (s_rho) float64 288B -0.9861 -0.9583 -0.9306 ... -0.04167 -0.01389\n",
+       "    lat_rho  (eta_rho, xi_rho) float64 85kB 33.74 33.79 33.84 ... 42.82 42.87\n",
+       "    lon_rho  (eta_rho, xi_rho) float64 85kB -75.84 -75.78 ... -71.49 -71.43\n",
        "Dimensions without coordinates: time, eta_rho, xi_rho\n",
        "Attributes:\n",
        "    units:          Celsius\n",
@@ -652,7 +661,7 @@
        "    standard_name:  sea_water_potential_temperature"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -665,7 +674,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -678,12 +687,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -698,12 +707,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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HrkJSdKjosoQIdOfJDQYDpk2bhpycHLz11lt23zcajbjtttsQHx+PrVu3or6+HjNnzoQkSVi5cqU7SyOShRf/cwRf7KtAoFKB1+8d5bUPYHQFt4bR4sWLAQBvv/12t9/fuHEjDh8+jLKyMiQlJQEA/vznP2PWrFlYunQpoqL89w9Dvu+f20/ije9PAABevHM4rusfL7gisYSOGW3fvh1Dhw61BhEA3HzzzdDr9di9e3e3P6PX66HT6WxeRN7m60NVWPj5IQDAEzcNwJ1ZyYIrEk9oGFVVVSEhwfbO0piYGAQHB6Oqqqrbn1m+fDnUarX1lZKS4olSiVxm46EqPPLBHkgScM9VKcj7RabokmTB6TBatGgRFArFRV+7du1y+HwKhf19FJIkdfs+ACxYsABardb6Kisrc/YSiISob9LjkQ/24KF3d0PfbkLuwHg8f/vQC/637m+cHjPKy8vD9OnTL3pMenq6Q+dKTEzEjh07bN47c+YM2tra7FpMFiqVCiqVyqHzE8mBJEnYsL8SCz8/hIZmA5QKYM71ffH4+AEIDODdNRZOh5FGo4FGo3HJL8/JycHSpUtRWVmJ3r17AzAPaqtUKmRlZbnkdxCJVKNrxbP/PoiNh6sBAAMSIvDy1BEY4eMr8C+FW2fTSktL0dDQgNLSUhiNRuzduxcAkJmZiYiICEyYMAFDhgzBfffdh5dffhkNDQ148sknMWfOHM6kkVeTJAmfFJZjyReHoGttR6BSgbm5mZiX28/v7qx2lFvD6LnnnsM777xj/frKK68EAGzZsgXjxo1DQEAAvvzyS8ydOxdjx45FaGgoZsyYgRUrVrizLCK3Kj/bgj+sP4DvjtUCAIb2icJLd47AkCT+H+zFKCRJkkQXcTl0Oh3UajW0Wi1bUySUySTh/Z2lWP7Vz2g2GBEcqMRj4/vjoev6+vXYkKOfUbe2jIj8xan6Zjz1yX78dKIBADAqNRovTR2BzF4RgivzHgwjostgNEnI/7EEKzYeRWubCaFBAfjdzQMxc0w6Avxo+w9XYBgRXaLimkb87uP92FN6FgCQ0zcOL945HKlxYWIL81IMIyIntRlNWPv9Cby6uQgGowkRqkD84dbBuOeqFN7AeBkYRkROOFyhw+8/2YeD5eY1keMGxmPZHcP8dtsPV2IYETlA327E374txur/Hke7SYI6NAgLJw3BHVf2YWvIRRhGRD3YW3YWv/94H45VNwEAbr4iAc9PGYpekSGCK/MtDCOiC2htM+KVTcfw5g8nYJKAuPBgLLl9KG4dlsjWkBswjIi6sbOkAU99sh8ldc0AgCkjk/DcpCt89jn3csAwIuqiWd+Ol/5zBO9sPwUASIhSYemUYX7xRFfRGEZEMC/l2PRzNZ7fcBinz7QAAO4enYI/3DbYL5/UIQLDiPxas74dH+8+jfwfS3Cy/hwAoE90KF64c5jf70ntaQwj8kvlZ1vwz20n8cHOUuha2wEAUSGBuPeaNMzLzUS4ih8NT+P/4uRXCkvP4K2tJfjPwSoYTeYNKzI04XhwbDruzEpGWDA/EqLwf3nyee1GE/5zqApvbS2xriMDgDH94jD72gzkDuzlV8+0lyuGEfksbUsbPiwoxTvbTqH8rHlQOjhAickjk/Dg2AxudiYzDCPyOSfrmpH/YwnW7T6NcwYjAPMNi/dek4Z7r0lDfCQf6CBHDCPyCZIk4acTDXhrawm+OVINy/6lAxMiMfvaDEwemYSQIO49LWcMI/Jq+nYjNuyrxFtbS3C4svPpwrkD4zH72r4YmxnHpRtegmFEXqm+SY/3dpTi3Z9OobZRDwAICVLizlHJeGBsBrd79UIMI/Iqx6ob8Y+tJfh0Tzn07SYAQGJUCO4fk4YZV6UiOoxrx7wVw4hkT5IkfHesFm9tLcEPRXXW94cnqzH72gzcOqw3gvz46Ru+gmFEstViMGL9ntPI//EkimvMewkpFcCEIYmYfV0GRqfFcDzIhzCMSHaqda345/aTeH9HKc6cawMARKgCcXd2CmaNSUdKLDe890UMI5KNg+VavLW1BBv2V6DNaJ6bT4kNxawxGbhrdDIiQ7h63pcxjEgoo0nC5p+r8dbWEuwsabC+n50eg9nXZuCmIYl8/pifYBiREE36dnxUUIa3t51EaYN5645ApQK/HN4bD16bgeHJ0WILJI9jGJFHldafwz+3n8SHBWVo1Ju37ogOC8KMq1Jxf046EtXc5N5fMYzI7SRJwo/F9Xh720mbpRp948Px4NgM3DkqGaHBXKrh7xhG5DbnDO1YX1iOd7adRFHH1DwAXD8gHg+MSccNA+K5dQdZMYzI5SxdsY92lVl3UQwPDsDUrGTcPyYd/eK5VIPsMYzIJS7UFUuPC8PMMemYmsWpebo4hhFdlgt1xW4YEI9Z7IqRExhGdEnYFSNXYxiRw9gVI3diGFGP2BUjT2AY0QWVNXTeoMiuGLkbw4hsSJKEbcfrkf8ju2LkWQwjAsCuGInHMPJz7IqRXDCM/BC7YiRHDCM/wq4YyRnDyA+wK0begGHkw7Ydr8M/trIrRt6BYeSDjtc24fkNh/Hfo7XW99gVI7ljGPmQxtY2vPZNEfJ/PIl2k4SgAAWmZ6di1lh2xUj+GEY+wGSS8PHu03jp6yOoazIAAH4xqBeevW0w+jKEyEswjLzc7lNnsPiLQ9h/WgsA6KsJxx8nDUHuwF6CKyNyDsPIS1XrWvHi/x3B+j3lAMwPOXz0xv6YOSYdwYF81DN5H4aRl9G3G/HW1hKs+rYY5wxGKBTAtKxk/O7mQYiPVIkuj+iSMYy8hCRJ2PxzDf705WGcqjc/Z2xUajQWTb6Czxgjn8Aw8gLFNY1Y/MVh/FBUBwDoFanCglsH4fYRfThNTz6DYSRj2pY2vLq5CP/cbp6qDw5QYvZ1GZiXm4kIFf905Fv4X7QMGU0SPtpVhhVfH0V9s3mqfvzgBDx722Cka8IFV0fkHgwjmdl1sgELPz+EQxU6AEBmrwg898shuH5AvODKiNyLYSQTldoWLP/qCD7fVwEAiAwJxGPjB+D+nDQEBXCqnnwfw0iw1jYj/v7DCfxty3G0tJmn6qdnp+CJCQOhieBUPfkPhpEgkiTh60PVWPrVYZQ1tAAARqfFYNHkKzC0j1pwdUSexzAS4Fh1IxZ/cQg/FtcDABKjQrDg1kGYPCIJCgWn6sk/MYw8qFnfjpe/Pop3fzoFo0lCcKAS/+/6vvjNuH4IC+afgvwbPwEeUqNrxYPvFOBguXmWbOIViXjmtsFIiQ0TXBmRPDCMPOBYdSMeyC9A+dkWxIUH46/TR+K6/pyqJ+qKYeRmPxbX4eF3d6NR346+mnDkP5CNtDjeuEh0PoaRG328+zSe/mQ/2k0SstNjsPa+0YgJDxZdFpEsMYzcQJIkvPpNEf66uQgAMGlEEl6eOhwhQQGCKyOSL4aRixnaTfjDpwfw8e7TAIDfjOuH300YyNX1RD1gGLmQrrUNv/nXbvxYXI8ApQLP3z4UM65OFV0WkVdgGLlI+dkWPJC/E8eqmxAWHIC//c8o7kNN5ASGkQscLNfiwbcLUNOoR69IFf4xK5tLOoicxDC6TFuO1GDe+4U4ZzBiYEIk/vFANvpEh4oui8jrMIwuw3s7TuG5zw7BaJJwbaYGq+8dhSg+MprokjCMLoHJJOHFr4/gje9OAACmZiVj2R3D+IggosvAMHJSa5sRT67bhw37KwEA828agN/+IpOr7YkuE8PICWeaDXjo3V0oOHkGQQEKvHjncPxqVLLosoh8AsPIQafqm/FAfgFO1DUjMiQQb9ybhTGZGtFlEfkMhpEDyhrO4Vert6G+2YA+0aHIfyAbAxIiRZdF5FMYRj3Qtxsx7/1C1DcbMLh3FN55IBu9okJEl0Xkczj904NlX/6M/ae1iA4Lwt9njmYQEbmJW8No6dKlGDNmDMLCwhAdHd3tMQqFwu61Zs0ad5blsC/3V+Kd7acAAH+5awRvZiRyI7d20wwGA6ZNm4acnBy89dZbFzwuPz8fEydOtH6tVotfSnGyrhlPfbIfAPDwDf3wi0EJgisi8m1uDaPFixcDAN5+++2LHhcdHY3ExESHzqnX66HX661f63S6S67vQlrbjJj7XiGa9O24Kj0WT04Y4PLfQUS2ZDFmlJeXB41Gg+zsbKxZswYmk+mCxy5fvhxqtdr6SklJcXk9SzYcxuFKHeLCg/HaPVcikE90JXI74Z+y559/HuvWrcPmzZsxffp0PPHEE1i2bNkFj1+wYAG0Wq31VVZW5tJ6Pttbjvd3lEKhAF65eyQS1RywJvIEp7tpixYtsna/LqSgoACjR4926HzPPvus9d8jR44EACxZssTm/a5UKhVUKvc89rm4pgkL1h8AAPw2NxPXD+ATPIg8xekwysvLw/Tp0y96THp6+qXWg2uuuQY6nQ7V1dVISPDcoHGLwYh575m3AsnpG4dHx3OciMiTnA4jjUYDjcZ9yyD27NmDkJCQC94K4C7PfXYQR6sboYlQ4dV7RiKAe1YTeZRbZ9NKS0vR0NCA0tJSGI1G7N27FwCQmZmJiIgIfPHFF6iqqkJOTg5CQ0OxZcsWPPPMM3jooYfc1hXrzrpdZVi3+zSUCuC1e0aiVyTHiYg8za1h9Nxzz+Gdd96xfn3llVcCALZs2YJx48YhKCgIq1evxvz582EymdC3b18sWbIE8+bNc2dZNo5WNeKPnx0EADw+fgDG9OPiVyIRFJIkSaKLuBw6nQ5qtRparRZRUVFO/Wyzvh2TV23F8dpmXD8gHm/PyuYjhYhczNHPqPCpfVEkScIznx7A8dpmJEaF4JW7RjCIiATy2zBat+s0/r23AgFKBVbOuBJxEZ4boyIie34bRn/fat6/ev5NA5CdHiu4GiLyyzA6e86AY9VNAIDp2a5fTkJEzvPLMNp96gwAoG98OLtnRDLhl2FUcNIcRtlp7J4RyYVfhtGukw0AgNHpMYIrISILvwuj1jYj9p/WAgAHrolkxO/C6EC5FgajCZoIFdLiwkSXQ0Qd/C6MCjq6aNnpMXwKLJGM+F0Y7eoYvB7NLhqRrPhVGJlMknXwOpuD10Sy4ldhVFTTBF1rO8KCAzCkt3OLaonIvfwqjCzjRVemRnOTfSKZ8atPpPX+It7sSCQ7fhVG1juvOXhNJDt+E0YVZ1tQfrYFAUoFRqZGiy6HiM7jN2F0sNx813W/+HBEqNy62y4RXQK/CaMMTTgA4ERtM2ob9T0cTUSe5jdh1D8hEiNTotFukrC+8LTocojoPH4TRgBwd8dGah/uKoOXP4eAyOf4VRhNGpGEsOAAnKhttm6wRkTy4FdhFKEKxG3DegMA/regTHA1RNSVX4UR0NlV+3J/JRpb2wRXQ0QWfhdGWWkx6BsfjpY2IzbsrxRdDhF18LswUigUuHt0x0A2u2pEsuF3YQQAvxqVjEClAnvLzuJYdaPocogIfhpG8ZEq3Di4FwC2jojkwi/DCOgcyF5feBr6dqPgaojIb8Po+v7xSIhS4cy5Nmw+XCO6HCK/57dhFBigxNSsZADmO7KJSCy/DSMAuKtjVu2HolqUn20RXA2Rf/PrMEqLC0dO3zhIEvDxLi6eJRLJr8MI6BzIfntbCSq1bB0RieL3YXTrsN64IikKZ8614bfv70Gb0SS6JCK/5PdhFByoxOr/GYXIkEDsOnUGL399VHRJRH7J78MIMI8dvTx1BABg7fcnsPFQleCKiPwPw6jDxKGJmH1tBgDgyXX7UNZwTnBFRP6FYdTF07cMwqjUaOha2zH3vULemU3kQQyjLoIClFg1YxRiwoJwoFyLP234WXRJRH6DYXSepOhQvHL3SADAuz+dwuf7KsQWROQnGEbdGDewF/JyMwEACz7Zj+O1TYIrIvJ9DKMLePymAcjpG4dmgxFz/1WIFgPHj4jciWF0AQFKBV69ZyTiI1U4Wt2IP352UHRJRD6NYXQRvSJD8Nr0K6FUAB/vPo2PuBEbkdswjHqQ0y8OT0wYCAD442cH8XOlTnBFRL6JYeSA39zQD+MGxkPfbsLc9wr5iCMiN2AYOUCpVOCVu0YiSR2CkrpmPP3JAT4em8jFGEYOigkPxsoZoxCoVODLA5X45/ZToksi8ikMIydkpcVgwa2DAQB/+vIw9padFVsQkQ9hGDnpwbHpmHhFItqMEua9V4iGZoPokoh8AsPISQqFAi9NG470uDCUn23BYx/uhdHE8SOiy8UwugRRIUF4/d4shAQp8f2xWqz8tkh0SURej2F0iQb3jsKyO4YBAF79pgj/PcpnrxFdDobRZfjVqGTMuDoVkgQ89uFenD7DDdmILhXD6DI998shGJ6sxtlzbdyQjegyMIwuU0hQAP42YxSiw4Kw/7QWS744LLokIq/EMHKBlNgw/PXukVAogPd2lGJ9IR8ISeQshpGLjBvYC4/8oj8A4A+fHsCRKi6oJXIGw8iFHrmxP67rr0Frmwm/+VchdFxQS+QwhpELBSgVeHX6ldYFtb9bt48LaokcxDBysdjwYKy+NwtBAQp8fagab/5wQnRJRF6BYeQGI1Oi8dykKwAAL/7nKHacqBdcEZH8MYzc5N6rU3HHlX1gNEnI+2APanStoksikjWGkZsoFAosvWMoBiREoLZRj7z396DNaBJdFpFsMYzcKCw4EK/fm4UIVSB2nmzAy18fFV0SkWwxjNysX3wEXp46HACw9vsT+M/BSsEVEckTw8gDbhnWG3OuywAAPLluP6q0HD8iOh/DyEN+P3EQrkiKQpO+HV8fqhJdDpHsMIw8JChAiduG9wYA/FBUJ7gaIvlhGHnQtZkaAMBPJ+rRzpk1IhsMIw+6IkkNdWgQmvTt2HdaK7ocIllhGHlQgFKBsZlxAICt7KoR2WAYedjYjq7aj8UMI6KuGEYedl1mPACgsPQMmvXtgqshkg+GkYelxoUhJTYU7SYJO0q4gJbIgmEkgGVWbWsRw4jIwm1hdPLkScyePRsZGRkIDQ1Fv379sHDhQhgMto+DLi0txaRJkxAeHg6NRoNHHnnE7hhfc21HV43jRkSdAt114iNHjsBkMuGNN95AZmYmDh48iDlz5qC5uRkrVqwAABiNRtx2222Ij4/H1q1bUV9fj5kzZ0KSJKxcudJdpQk3pl8cFArgaHUjanSt6BUVIrokIvEkD3rppZekjIwM69dfffWVpFQqpfLycut7H3zwgaRSqSStVuvQObVarQTA4ePl4pev/SClPbVBWl9YJroUIrdy9DPq0TEjrVaL2NhY69fbt2/H0KFDkZSUZH3v5ptvhl6vx+7du7s9h16vh06ns3l5o7EcNyKy4bEwOn78OFauXImHH37Y+l5VVRUSEhJsjouJiUFwcDCqqrpfTLp8+XKo1WrrKyUlxa11u4t1ELu4lpv2E+ESwmjRokVQKBQXfe3atcvmZyoqKjBx4kRMmzYNv/71r22+p1Ao7H6HJEndvg8ACxYsgFartb7KysqcvQRZGJ0eA1WgEtU6PY7XNokuh0g4pwew8/LyMH369Isek56ebv13RUUFcnNzkZOTg7Vr19ocl5iYiB07dti8d+bMGbS1tdm1mCxUKhVUKpWzZctOSFAAstNjsbW4DluL6pDZK1J0SURCOR1GGo0GGo3GoWPLy8uRm5uLrKws5OfnQ6m0bYjl5ORg6dKlqKysRO/e5u01Nm7cCJVKhaysLGdL8zrX9teYw6i4DrPGZoguh0got03tV1RUYNy4cUhNTcWKFStQW1tr/V5iYiIAYMKECRgyZAjuu+8+vPzyy2hoaMCTTz6JOXPmICoqyl2lyUbnliINaDOaEBTAe1DJf7ktjDZu3Iji4mIUFxcjOTnZ5nuWAduAgAB8+eWXmDt3LsaOHYvQ0FDMmDHDeh+SrxvSOwoxYUE4c64N+0+fRVZabM8/ROSjFJKXT+XodDqo1WpotVqvbE39+p0CbP65BosnX4GZY9JFl0Pkco5+RtkvEKzdZP7/gtDgAMGVEInFMBJM19IGAIgKCRJcCZFYDCPBdK3mPY2iQt02fEfkFRhGgrFlRGTGMBKssaNlpA5lGJF/YxgJZGg3oaXNCIAtIyKGkUCNrW3Wf0eEcMyI/BvDSCDL4HWEKhAByu4XBhP5C4aRQJ2D12wVETGMBNJ1dNOiOHhNxDASSdfScY8RB6+JGEYidbaM2E0jYhgJZJlNY8uIiGEklLWbxjEjIoaRSNZuGmfTiBhGIlmm9iPZTSNiGInEFftEnRhGAnHFPlEnhpFAvOmRqBPDSCDe9EjUiWEkkOU+o0jOphExjESRJAnnOvYyClNxM34ihpEg+nYTLA+JCg1iGBExjARp7WgVAUAIw4iIYSSKZbvZoAAFH2tNBIaRMC0GcxixVURkxjASxNIy4ngRkRnDSBDLmBEfa01kxjASpMVgAsCWEZEFw0gQSzeNY0ZEZgwjQVo5ZkRkg2EkSGfLiH8CIoBhJAwHsIlsMYwE4X1GRLYYRoLwPiMiWwwjQRhGRLYYRoK0GjhmRNQVw0gQ3mdEZIthJEhLG+/AJuqKYSRIC7tpRDYYRoLwDmwiWwwjQVo5ZkRkg2EkSAvvwCaywTAShPcZEdliGAmi75hNCw7kn4AIYBgJY+p4TlGAQiG4EiJ5YBgJYgkjJf8CRAAYRsIYzb00KNkyIgLAMBJGsnTTlAwjIoBhJIzR0k1jFhEBYBgJYzKZw0jBbhoRAIaRMB1ZxNk0og4MI0Gss2kMIyIADCNhjCZO7RN1xY+CIB0NI7aMiDowjAQxcWqfyAbDSBDL1D4bRkRmDCMBJEliN43oPAwjASzT+gCn9oksGEYCWMaLALaMiCwYRgIYuzSNOLVPZMaPggBdGkZsGRF1YBgJYOySRpzaJzJjGAnQdcyIDSMiM4aRACYTB7CJzscwEoBT+0T2GEYCdJ1NYxYRmTGMBJC67PLIzdWIzBhGAhi5lxGRHYaRAJZempLT+kRWDCMBrPtfC66DSE4YRgJYbjPiDY9EnRhGAlhuemQUEXViGAlgmdjnADZRJ4aRANblIMwiIiuGkQDc5ZHIHsNIAIn7XxPZYRgJwDEjIntuC6OTJ09i9uzZyMjIQGhoKPr164eFCxfCYDDYHKdQKOxea9ascVdZssDZNCJ7ge468ZEjR2AymfDGG28gMzMTBw8exJw5c9Dc3IwVK1bYHJufn4+JEydav1ar1e4qSxas49dsGRFZuS2MJk6caBMwffv2xdGjR/H666/bhVF0dDQSExPdVYrsmDhmRGTHo2NGWq0WsbGxdu/n5eVBo9EgOzsba9asgclkuuA59Ho9dDqdzcvbdM6mia2DSE7c1jI63/Hjx7Fy5Ur8+c9/tnn/+eefx4033ojQ0FB88803eOKJJ1BXV4dnn3222/MsX74cixcv9kTJbtN5mxHTiMhKctLChQslmCeELvgqKCiw+Zny8nIpMzNTmj17do/nX7FihRQVFXXB77e2tkpardb6KisrkwBIWq3W2UsRZl/ZGSntqQ1SzrLNokshcjutVuvQZ9TpllFeXh6mT59+0WPS09Ot/66oqEBubi5ycnKwdu3aHs9/zTXXQKfTobq6GgkJCXbfV6lUUKlUzpYtKyYOYBPZcTqMNBoNNBqNQ8eWl5cjNzcXWVlZyM/Ph9KBJxbu2bMHISEhiI6OdrY0ryFxAJvIjtvGjCoqKjBu3DikpqZixYoVqK2ttX7PMnP2xRdfoKqqCjk5OQgNDcWWLVvwzDPP4KGHHvL61s/FdLaMxNZBJCduC6ONGzeiuLgYxcXFSE5OtvmepWUQFBSE1atXY/78+TCZTOjbty+WLFmCefPmuassmeC2s0TnU0hS14ctex+dTge1Wg2tVouoqCjR5Tik4GQDpq3ZjvS4MPz3d7miyyFyK0c/o1ybJgBX7RPZYxgJwP2MiOwxjARgy4jIHsNIAImr9onsMIwE4H5GRPYYRgJw1T6RPYaRANzPiMgew0gAS8uIW4gQdWIYCSBxOQiRHYaRABKXgxDZYRgJYNnIklFE1IlhJIB1MSBbRkRWDCMBJA5gE9lhGAlgaRkxi4g6MYwE6NzpkXFEZMEwEoCL9onsMYwEsHbTmEZEVgwjAfjcNCJ7DCMBLDc9smVE1IlhJACXgxDZYxgJYN1ChN00IiuGkUBsGRF1YhgJwG4akT2GkQBctU9kj2EkgHc/NpPIPRhGAnDbWSJ7DCMBTHxUEZEdhpEAXA5CZI9hJAKfKEtkh2EkgHU5iOA6iOSEYSQA7zMisscwEqBzZp9pRGTBMBKAj7cmsscwEoA7PRLZYxgJYOmmcTaNqBPDSAR204jsMIwE4E2PRPYYRgJwD2wiewwjASSOYBPZYRgJYOJyECI7DCMB+HhrInsMIwEkzqYR2WEYCcQsIurEMBKAOz0S2WMYCcAnyhLZYxgJEBMWjEGJkUhSh4ouhUg2AkUX4I+mjU7BtNEpossgkhW2jIhIFhhGRCQLDCMikgWGERHJAsOIiGSBYUREssAwIiJZYBgRkSwwjIhIFhhGRCQLDCMikgWGERHJAsOIiGSBYUREssAwIiJZYBgRkSwwjIhIFhhGRCQLDCMikgWGERHJAsOIiGTB658OYnlUtE6nE1wJEXXH8tm0fFYvxOvDqLGxEQCQksJH/xDJWWNjI9Rq9QW/r5B6iiuZM5lMOHr0KIYMGYKysjJERUWJLskldDodUlJSeE0y5mvXA7jnmiRJQmNjI5KSkqBUXnhkyOtbRkqlEn369AEAREVF+cx/FBa8JvnztesBXH9NF2sRWXAAm4hkgWFERLLgE2GkUqmwcOFCqFQq0aW4DK9J/nztegCx1+T1A9hE5Bt8omVERN6PYUREssAwIiJZYBgRkSwwjIhIFrwqjL7//ntMmjQJSUlJUCgU+Pe//23z/erqasyaNQtJSUkICwvDxIkTUVRUJKZYByxfvhzZ2dmIjIxEr169MGXKFBw9etTmGEmSsGjRIiQlJSE0NBTjxo3DoUOHBFXcM0euaf369bj55puh0WigUCiwd+9eMcU6qKdramtrw1NPPYVhw4YhPDwcSUlJuP/++1FRUSGw6gtz5G+0aNEiDBo0COHh4YiJicH48eOxY8cOt9blVWHU3NyMESNGYNWqVXbfkyQJU6ZMwYkTJ/DZZ59hz549SEtLw/jx49Hc3Cyg2p599913mDdvHn766Sds2rQJ7e3tmDBhgk29L730Ev7yl79g1apVKCgoQGJiIm666SbrAmG5ceSampubMXbsWLzwwgsCK3VcT9d07tw5FBYW4o9//CMKCwuxfv16HDt2DJMnTxZcefcc+RsNGDAAq1atwoEDB7B161akp6djwoQJqK2tdV9hkpcCIH366afWr48ePSoBkA4ePGh9r729XYqNjZXefPNNARU6r6amRgIgfffdd5IkSZLJZJISExOlF154wXpMa2urpFarpTVr1ogq0ynnX1NXJSUlEgBpz549ni/sMlzsmix27twpAZBOnTrlwcoujSPXo9VqJQDS5s2b3VaHV7WMLkav1wMAQkJCrO8FBAQgODgYW7duFVWWU7RaLQAgNjYWAFBSUoKqqipMmDDBeoxKpcINN9yAbdu2CanRWedfky9w5Jq0Wi0UCgWio6M9VNWl6+l6DAYD1q5dC7VajREjRritDp8Jo0GDBiEtLQ0LFizAmTNnYDAY8MILL6CqqgqVlZWiy+uRJEmYP38+rr32WgwdOhQAUFVVBQBISEiwOTYhIcH6PTnr7pq8nSPX1NraiqeffhozZsyQ/Wr+i13Phg0bEBERgZCQELzyyivYtGkTNBqN22rx+i1ELIKCgvDJJ59g9uzZiI2NRUBAAMaPH49bbrlFdGkOycvLw/79+7ttxSkUCpuvJUmye0+OLnZN3qqna2pra8P06dNhMpmwevVqD1fnvItdT25uLvbu3Yu6ujq8+eabuOuuu7Bjxw706tXLPcW4rQPoZjhvzKirs2fPSjU1NZIkSdJVV10lzZ0714OVOS8vL09KTk6WTpw4YfP+8ePHJQBSYWGhzfuTJ0+W7r//fk+W6LQLXVNX3jZm1NM1GQwGacqUKdLw4cOluro6D1fnPEf+Rl1lZmZKy5Ytc1s9PtNN60qtViM+Ph5FRUXYtWsXbr/9dtEldUuSJOTl5WH9+vX49ttvkZGRYfP9jIwMJCYmYtOmTdb3DAYDvvvuO4wZM8bT5Tqkp2vyRo5cU1tbG+666y4UFRVh8+bNiIuLE1CpYy71byRJknVs1h28qpvW1NSE4uJi69clJSXYu3cvYmNjkZqainXr1iE+Ph6pqak4cOAAHn30UUyZMsVmAFhO5s2bh/fffx+fffYZIiMjreNAarUaoaGhUCgUeOyxx7Bs2TL0798f/fv3x7JlyxAWFoYZM2YIrr57PV0TADQ0NKC0tNR6H47lHpfExEQkJiaKKfwierqm9vZ2TJ06FYWFhdiwYQOMRqP1mNjYWAQHB4ss305P19Pc3IylS5di8uTJ6N27N+rr67F69WqcPn0a06ZNc19hbmtzucGWLVskAHavmTNnSpIkSa+++qqUnJwsBQUFSampqdKzzz4r6fV6sUVfRHfXAkDKz8+3HmMymaSFCxdKiYmJkkqlkq6//nrpwIED4orugSPXlJ+f3+0xCxcuFFb3xfR0TZbuZnevLVu2CK29Oz1dT0tLi3THHXdISUlJUnBwsNS7d29p8uTJ0s6dO91aF/czIiJZ8MkxIyLyPgwjIpIFhhERyQLDiIhkgWFERLLAMCIiWWAYEZEsMIyISBYYRkQkCwwjIpIFhhERycL/B4HiMYoLCsXUAAAAAElFTkSuQmCC",
       "text/plain": [
        "<Figure size 300x700 with 1 Axes>"
       ]
@@ -735,7 +744,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -756,7 +765,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -772,7 +781,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -783,12 +792,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
        "<Figure size 800x600 with 1 Axes>"
       ]
@@ -841,13 +850,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
     "import pysgrid\n",
     "\n",
     "url = \"https://geoport.whoi.edu/thredds/dodsC/coawst_4/use/fmrc/coawst_4_use_best.ncd\"\n",
+    "url = (\n",
+    "    \"http://tds.marine.rutgers.edu/thredds/dodsC/roms/doppio/2017_da/avg/Averages_Best\"\n",
+    ")\n",
     "sgrid = pysgrid.load_grid(url)"
    ]
   },
@@ -860,7 +872,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -871,7 +883,7 @@
        " [GridPadding(mesh_topology_var='grid', face_dim='eta_u', node_dim='eta_psi', padding='both')])"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -882,7 +894,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -891,7 +903,7 @@
        "(1, 0)"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -904,7 +916,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
@@ -913,7 +925,7 @@
        "(0, 1)"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -925,7 +937,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -941,7 +953,7 @@
        "  slice(1, -1, None)))"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -962,7 +974,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1013,7 +1025,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1035,7 +1047,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1069,7 +1081,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1097,7 +1109,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1112,14 +1124,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 22,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
        "<Figure size 900x900 with 1 Axes>"
       ]
@@ -1138,8 +1150,7 @@
     "\n",
     "plt.pcolormesh(x, y, speed, zorder=1, cmap=plt.cm.rainbow)\n",
     "\n",
-    "c = ax.coastlines(\"10m\")\n",
-    "ax.set_extent([-73.5, -62.5, 38, 46])"
+    "c = ax.coastlines(\"10m\")"
    ]
   },
   {
@@ -1166,7 +1177,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.12.2"
   }
  },
  "nbformat": 4,
diff --git a/pyproject.toml b/pyproject.toml
deleted file mode 100644
index 45e9c105..00000000
--- a/pyproject.toml
+++ /dev/null
@@ -1,8 +0,0 @@
-[tool.ruff]
-select = [
-    "F", # flakes
-    "I", # import sorting
-    "U", # upgrade
-]
-target-version = "py37"
-line-length = 120
diff --git a/ruff.toml b/ruff.toml
new file mode 100644
index 00000000..2d267b09
--- /dev/null
+++ b/ruff.toml
@@ -0,0 +1,22 @@
+target-version = "py312"
+line-length = 120
+lint.select = [
+    "F", # flakes
+    "I", # import sorting
+    "U", # upgrade
+]
+
+lint.ignore = [
+    "E402",  # Module level import not at top of file
+    ]
+
+# Skipping b/c These notebooks mix R and Python
+# NB: nbqa-ruff acts on converted .py so we cannot glob .ipynb :-/
+# https://github.com/nbQA-dev/nbQA/issues/823
+[lint.extend-per-file-ignores]
+"jupyterbook/content/code_gallery/data_access_notebooks/2017-11-30-rerddap*" = [
+    "F821",  # Undefined name
+]
+"jupyterbook/content/code_gallery/data_access_notebooks/2018-02-20-obis*" = [
+    "F821",  # Undefined name
+]