From 8d8ca8800ef9ff0adf959372c2e448e12ab944b3 Mon Sep 17 00:00:00 2001
From: Alexander Druz <alexandersdruz@gmail.com>
Date: Mon, 5 Feb 2024 10:21:15 +0100
Subject: [PATCH] Ignore lodash vulnerability

---
 package.json                                       | 7 +++++++
 tests/integration/dataset/test_embedding_column.py | 4 +++-
 tests/integration/dataset/test_fancy_indexing.py   | 4 ++--
 3 files changed, 12 insertions(+), 3 deletions(-)

diff --git a/package.json b/package.json
index 1d2792e1..1aabca73 100644
--- a/package.json
+++ b/package.json
@@ -216,5 +216,12 @@
             ".jsx",
             ".tsx"
         ]
+    },
+    "pnpm": {
+        "auditConfig": {
+            "ignoreCves": [
+                "CVE-2020-8203"
+            ]
+        }
     }
 }
diff --git a/tests/integration/dataset/test_embedding_column.py b/tests/integration/dataset/test_embedding_column.py
index c1e5aee6..159d295f 100644
--- a/tests/integration/dataset/test_embedding_column.py
+++ b/tests/integration/dataset/test_embedding_column.py
@@ -1,9 +1,11 @@
+from typing import Tuple
 import numpy as np
 import pytest
 
 from renumics import spotlight
 from renumics.spotlight import dtypes
 from renumics.spotlight.dataset.exceptions import InvalidDTypeError, InvalidShapeError
+from renumics.spotlight.dataset.typing import EmbeddingColumnInputType
 
 
 @pytest.mark.parametrize("length", [1, 2, 8])
@@ -14,7 +16,7 @@ def test_default(empty_dataset: spotlight.Dataset, length: int) -> None:
     empty_dataset.append_embedding_column("embedding")
     assert empty_dataset.get_dtype("embedding") == dtypes.embedding_dtype
 
-    valid_values = (
+    valid_values: Tuple[EmbeddingColumnInputType] = (
         [0] * length,
         range(length),
         tuple(range(length)),
diff --git a/tests/integration/dataset/test_fancy_indexing.py b/tests/integration/dataset/test_fancy_indexing.py
index 30a58772..1c673fc0 100644
--- a/tests/integration/dataset/test_fancy_indexing.py
+++ b/tests/integration/dataset/test_fancy_indexing.py
@@ -3,7 +3,7 @@
 """
 
 import datetime
-from typing import Any, List
+from typing import Any, List, cast
 
 import numpy as np
 import pytest
@@ -300,7 +300,7 @@ def test_setitem(fancy_indexing_dataset: Dataset) -> None:
             )
             target = np.array(fancy_indexing_dataset[column_name])
             target[indices] = values
-            fancy_indexing_dataset[column_name, indices] = values
+            fancy_indexing_dataset[column_name, indices] = cast(np.ndarray, values)
             last_edited_at = last_edited_at_column[last_edited_at_indices]
             if len(last_edited_at_indices) > 0:
                 timestamp_ = _assert_unique_datetime(