ALFPath class (#162)

one.alf.path.ALFPath class - a pathlib-like object with ALF methods (issue #149)
int-brain-lab · Nov 12, 2024 · ae7a7cc · ae7a7cc
1 parent ce8aa6b
commit ae7a7cc
Show file tree

Hide file tree

Showing 16 changed files with 1,899 additions and 625 deletions.
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -1,13 +1,19 @@
 # Changelog
 ## [Latest](https://github.com/int-brain-lab/ONE/commits/main) [3.0.0]
 This version drops support for python 3.9 and below, and ONE is now in remote mode by default.
+Also adds a new ALFPath class to replace alf path functions.
 
 ### Modified
 
 - supports python >= 3.10 only
 - OneAlyx uses remote mode by default, instead of auto
 - OneAlyx.search now updates the cache tables in remote mode as paginated sessions are accessed
-- Datasets table file_size column nullable by default
+- datasets table file_size column nullable by default
+- one.alf.io.save_metadata now returns the saved filepath
+- paths returned by One methods and functions in one.alf.io are now ALFPath instances
+- bugfix: one.alf.path.full_path_parts didn't always raise when invalid path passed
+- one.alf.path module containing ALFPath class
+- one.alf.exceptions.InvalidALF exception
 
 ### Added
 
@@ -18,6 +24,8 @@ This version drops support for python 3.9 and below, and ONE is now in remote mo
 ### Removed
 
 - setup.py
+- one.alf.files; use one.alf.path instead
+- one.alf.io.remove_uuid_file
 
 ## [2.11.1]
 

diff --git a/docs/notebooks/datasets_and_types.ipynb b/docs/notebooks/datasets_and_types.ipynb
@@ -16,37 +16,43 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
-   "outputs": [],
-   "source": [
-    "from pprint import pprint\n",
-    "from one.alf import spec\n",
-    "from one.alf.files import filename_parts"
-   ],
+   "execution_count": null,
    "metadata": {
     "collapsed": false,
     "pycharm": {
      "name": "#%%\n"
     }
-   }
+   },
+   "outputs": [],
+   "source": [
+    "from pprint import pprint\n",
+    "from one.alf import spec\n",
+    "from one.alf.path import ALFPath"
+   ]
   },
   {
    "cell_type": "markdown",
-   "source": [
-    "## Datasets\n",
-    "\n",
-    "Print information about ALF objects"
-   ],
    "metadata": {
     "collapsed": false,
     "pycharm": {
      "name": "#%% md\n"
     }
-   }
+   },
+   "source": [
+    "## Datasets\n",
+    "\n",
+    "Print information about ALF objects"
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": 14,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -73,83 +79,83 @@
    ],
    "source": [
     "spec.describe('object')"
-   ],
-   "metadata": {
-    "collapsed": false,
-    "pycharm": {
-     "name": "#%%\n"
-    }
-   }
+   ]
   },
   {
    "cell_type": "markdown",
-   "source": [
-    "Check the file name is ALF compliant"
-   ],
    "metadata": {
     "collapsed": false,
     "pycharm": {
      "name": "#%% md\n"
     }
-   }
+   },
+   "source": [
+    "Check the file name is ALF compliant"
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": 15,
-   "outputs": [],
-   "source": [
-    "assert spec.is_valid('spikes.times.npy')"
-   ],
    "metadata": {
     "collapsed": false,
     "pycharm": {
      "name": "#%%\n"
     }
-   }
+   },
+   "outputs": [],
+   "source": [
+    "assert spec.is_valid('spikes.times.npy')"
+   ]
   },
   {
    "cell_type": "markdown",
-   "source": [
-    "Safely construct an ALF dataset using the 'to_alf' function.  This will ensure the correct\n",
-    "case and format"
-   ],
    "metadata": {
     "collapsed": false,
     "pycharm": {
      "name": "#%% md\n"
     }
-   }
+   },
+   "source": [
+    "Safely construct an ALF dataset using the 'to_alf' function.  This will ensure the correct\n",
+    "case and format"
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": 16,
-   "outputs": [],
-   "source": [
-    "filename = spec.to_alf('spikes', 'times', 'npy',\n",
-    "                       namespace='ibl', timescale='ephys clock', extra='raw')"
-   ],
    "metadata": {
     "collapsed": false,
     "pycharm": {
      "name": "#%%\n"
     }
-   }
+   },
+   "outputs": [],
+   "source": [
+    "filename = spec.to_alf('spikes', 'times', 'npy',\n",
+    "                       namespace='ibl', timescale='ephys clock', extra='raw')"
+   ]
   },
   {
    "cell_type": "markdown",
-   "source": [
-    "Parsing a new file into its constituent parts ensures the dataset is correct"
-   ],
    "metadata": {
     "collapsed": false,
     "pycharm": {
      "name": "#%% md\n"
     }
-   }
+   },
+   "source": [
+    "Parsing a new file into its constituent parts ensures the dataset is correct"
+   ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -165,18 +171,18 @@
     }
    ],
    "source": [
-    "parts = filename_parts('_ibl_spikes.times_ephysClock.raw.npy', as_dict=True, assert_valid=True)\n",
+    "parts = ALFPath('_ibl_spikes.times_ephysClock.raw.npy').parse_alf_name()\n",
     "pprint(parts)"
-   ],
+   ]
+  },
+  {
+   "cell_type": "markdown",
    "metadata": {
     "collapsed": false,
     "pycharm": {
-     "name": "#%%\n"
+     "name": "#%% md\n"
     }
-   }
-  },
-  {
-   "cell_type": "markdown",
+   },
    "source": [
     "## Dataset types\n",
     "<div class=\"alert alert-info\">\n",
@@ -197,17 +203,17 @@
     "\n",
     "When registering files they must match exactly 1 dataset type.\n",
     "</div>"
-   ],
-   "metadata": {
-    "collapsed": false,
-    "pycharm": {
-     "name": "#%% md\n"
-    }
-   }
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": 18,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -218,7 +224,13 @@
     },
     {
      "data": {
-      "text/plain": "{'id': '1427b6ba-6535-4f8f-9058-e3df63f0261e',\n 'name': 'spikes.times',\n 'created_by': None,\n 'description': '[nspi]. Times of spikes (seconds, relative to experiment onset). Note this includes spikes from all probes, merged together',\n 'filename_pattern': 'spikes.times*.npy'}"
+      "text/plain": [
+       "{'id': '1427b6ba-6535-4f8f-9058-e3df63f0261e',\n",
+       " 'name': 'spikes.times',\n",
+       " 'created_by': None,\n",
+       " 'description': '[nspi]. Times of spikes (seconds, relative to experiment onset). Note this includes spikes from all probes, merged together',\n",
+       " 'filename_pattern': 'spikes.times*.npy'}"
+      ]
      },
      "execution_count": 18,
      "metadata": {},
@@ -229,29 +241,29 @@
     "from one.api import ONE\n",
     "one = ONE(base_url='https://openalyx.internationalbrainlab.org')\n",
     "one.describe_dataset('spikes.times')  # Requires online version (an Alyx database connection)"
-   ],
-   "metadata": {
-    "collapsed": false,
-    "pycharm": {
-     "name": "#%%\n"
-    }
-   }
+   ]
   },
   {
    "cell_type": "markdown",
-   "source": [
-    "Datasets and their types can be interconverted using the following functions (online mode only):"
-   ],
    "metadata": {
     "collapsed": false,
     "pycharm": {
      "name": "#%% md\n"
     }
-   }
+   },
+   "source": [
+    "Datasets and their types can be interconverted using the following functions (online mode only):"
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": 19,
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -269,13 +281,7 @@
     "\n",
     "dset_list = '\", \"'.join(datasets)\n",
     "print(f'the dataset type \"{dataset_type}\" for {eid} comprises the datasets: \\n\"{dset_list}\"')"
-   ],
-   "metadata": {
-    "collapsed": false,
-    "pycharm": {
-     "name": "#%%\n"
-    }
-   }
+   ]
   }
  ],
  "metadata": {
@@ -299,4 +305,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 0
-}
+}