[python] Start move to {obs/var} specific arguments for get_anndata

api/python/cellxgene_census/src/cellxgene_census/_get_anndata.py

@@ -8,6 +8,7 @@
 """
 
 from typing import Literal, Optional, Sequence
+from warnings import warn
 
 import anndata
 import pandas as pd
@@ -38,6 +39,8 @@ def get_anndata(
     column_names: Optional[soma.AxisColumnNames] = None,
     obs_embeddings: Optional[Sequence[str]] = (),
     var_embeddings: Optional[Sequence[str]] = (),
+    obs_column_names: Optional[Sequence[str]] = None,
+    var_column_names: Optional[Sequence[str]] = None,
 ) -> anndata.AnnData:
     """Convenience wrapper around :class:`tiledbsoma.Experiment` query, to build and execute a query,
     and return it as an :class:`anndata.AnnData` object.
@@ -65,8 +68,6 @@ def get_anndata(
         var_coords:
             Coordinates for the ``var`` axis, which is indexed by the ``soma_joinid`` value.
             May be an ``int``, a list of ``int``, or a slice. The default, ``None``, selects all.
-        column_names:
-            Columns to fetch for ``obs`` and ``var`` dataframes.
         obsm_layers:
             Additional obsm layers to read and return in the ``obsm`` slot.
         obsp_layers:
@@ -83,6 +84,10 @@ def get_anndata(
             Additional embeddings to be returned as part of the ``varm`` slot.
             Use :func:`get_all_available_embeddings` to retrieve available embeddings
             for this Census version and organism.
+        obs_column_names:
+            Columns to fetch for ``obs`` dataframe.
+        var_column_names:
+            Columns to fetch for ``var`` dataframe.
 
     Returns:
         An :class:`anndata.AnnData` object containing the census slice.
@@ -93,7 +98,7 @@ def get_anndata(
     Examples:
         >>> get_anndata(census, "Mus musculus", obs_value_filter="tissue_general in ['brain', 'lung']")
 
-        >>> get_anndata(census, "Homo sapiens", column_names={"obs": ["tissue"]})
+        >>> get_anndata(census, "Homo sapiens", obs_column_names=["tissue"])
 
         >>> get_anndata(census, "Homo sapiens", obs_coords=slice(0, 1000))
     """
@@ -107,14 +112,31 @@ def get_anndata(
     if varm_layers and var_embeddings and set(varm_layers) & set(var_embeddings):
         raise ValueError("Cannot request both `varm_layers` and `var_embeddings` for the same embedding name")
 
+    # Backwards compat for old column_names argument
+    if column_names is not None:
+        if obs_column_names is not None or var_column_names is not None:
+            raise ValueError(
+                "Both the deprecated 'column_names' argument and it's replacements were used. Please use 'obs_column_names' and 'var_column_names' only."
+            )
+        else:
+            warn(
+                "The argument `column_names` is deprecated and will be removed in a future release. Please use `obs_column_names` and `var_column_names` instead.",
+                FutureWarning,
+                stacklevel=2,
+            )
+        if "obs" in column_names:
+            obs_column_names = column_names["obs"]
+        if "var" in column_names:
+            var_column_names = column_names["var"]
+
     with exp.axis_query(
         measurement_name,
         obs_query=soma.AxisQuery(value_filter=obs_value_filter, coords=obs_coords),
         var_query=soma.AxisQuery(value_filter=var_value_filter, coords=var_coords),
     ) as query:
         adata = query.to_anndata(
             X_name=X_name,
-            column_names=column_names,
+            column_names={"obs": obs_column_names, "var": var_column_names},
             X_layers=X_layers,
             obsm_layers=obsm_layers,
             varm_layers=varm_layers,

api/python/cellxgene_census/tests/test_get_anndata.py

@@ -26,16 +26,14 @@ def test_get_anndata_value_filter(census: soma.Collection) -> None:
             organism="Mus musculus",
             obs_value_filter="tissue_general == 'vasculature'",
             var_value_filter="feature_name in ['Gm53058', '0610010K14Rik']",
-            column_names={
-                "obs": [
-                    "soma_joinid",
-                    "cell_type",
-                    "tissue",
-                    "tissue_general",
-                    "assay",
-                ],
-                "var": ["soma_joinid", "feature_id", "feature_name", "feature_length"],
-            },
+            obs_column_names=[
+                "soma_joinid",
+                "cell_type",
+                "tissue",
+                "tissue_general",
+                "assay",
+            ],
+            var_column_names=["soma_joinid", "feature_id", "feature_name", "feature_length"],
         )
 
     assert ad is not None
@@ -267,6 +265,66 @@ def test_get_anndata_obsm_layers_and_add_obs_embedding_fails(lts_census: soma.Co
             )
 
 
+@pytest.mark.live_corpus
+def test_deprecated_column_api(census: soma.Collection) -> None:
+    """Testing for previous `column_names` argument.
+
+    See: https://github.com/chanzuckerberg/cellxgene-census/issues/1035
+    """
+    ad_curr = cellxgene_census.get_anndata(
+        census,
+        organism="Mus musculus",
+        obs_value_filter="tissue_general == 'vasculature'",
+        var_value_filter="feature_name in ['Gm53058', '0610010K14Rik']",
+        obs_column_names=[
+            "soma_joinid",
+            "cell_type",
+            "tissue",
+            "tissue_general",
+            "assay",
+        ],
+        var_column_names=["soma_joinid", "feature_id", "feature_name", "feature_length"],
+    )
+    with pytest.warns(FutureWarning):
+        ad_prev = cellxgene_census.get_anndata(
+            census,
+            organism="Mus musculus",
+            obs_value_filter="tissue_general == 'vasculature'",
+            var_value_filter="feature_name in ['Gm53058', '0610010K14Rik']",
+            column_names={
+                "obs": [
+                    "soma_joinid",
+                    "cell_type",
+                    "tissue",
+                    "tissue_general",
+                    "assay",
+                ],
+                "var": ["soma_joinid", "feature_id", "feature_name", "feature_length"],
+            },
+        )
+    with pytest.raises(
+        ValueError, match=r"Both the deprecated 'column_names' argument and it's replacements were used."
+    ):
+        cellxgene_census.get_anndata(
+            census,
+            organism="Mus musculus",
+            obs_value_filter="tissue_general == 'vasculature'",
+            var_value_filter="feature_name in ['Gm53058', '0610010K14Rik']",
+            obs_column_names=[
+                "soma_joinid",
+                "cell_type",
+            ],
+            column_names={
+                "obs": [
+                    "soma_joinid",
+                    "cell_type",
+                ],
+            },
+        )
+    pd.testing.assert_frame_equal(ad_curr.obs, ad_prev.obs)
+    pd.testing.assert_frame_equal(ad_curr.var, ad_prev.var)
+
+
 def _map_to_get_anndata_args(query: Dict[str, Any], axis: Literal["obs", "var"]) -> Dict[str, Any]:
     """Helper to map arguments of get_obs/ get_var to get_anndata."""
     result = {}

api/python/notebooks/api_demo/census_access_maintained_embeddings.ipynb

@@ -181,7 +181,7 @@
     "    organism=\"homo_sapiens\",\n",
     "    measurement_name=\"RNA\",\n",
     "    obs_value_filter=\"tissue_general == 'central nervous system'\",\n",
-    "    column_names={\"obs\": [\"cell_type\"]},\n",
+    "    obs_column_names=[\"cell_type\"],\n",
     "    obs_embeddings=emb_names,\n",
     ")\n",
     "\n",

api/python/notebooks/api_demo/census_citation_generation.ipynb

@@ -259,7 +259,7 @@
     "    measurement_name=\"RNA\",\n",
     "    obs_value_filter=\"tissue == 'cardiac atrium'\",\n",
     "    var_value_filter=\"feature_name == 'MYBPC3'\",\n",
-    "    column_names={\"obs\": [\"dataset_id\", \"cell_type\"]},\n",
+    "    obs_column_names=[\"dataset_id\", \"cell_type\"],\n",
     ")\n",
     "\n",
     "# Get a citation string for the slice\n",

api/python/notebooks/api_demo/census_embedding.ipynb

@@ -243,7 +243,7 @@
     "        organism=EXPERIMENT_NAME,\n",
     "        measurement_name=MEASUREMENT_NAME,\n",
     "        obs_value_filter=\"tissue_general == 'central nervous system'\",\n",
-    "        column_names={\"obs\": [\"cell_type\", \"soma_joinid\"]},\n",
+    "        obs_column_names=[\"cell_type\", \"soma_joinid\"],\n",
     "        obs_embeddings=[\"scgpt\"],\n",
     "    )"
    ]

api/python/notebooks/api_demo/census_query_extract.ipynb

@@ -65,7 +65,7 @@
     "\n",
     "The method will return an `anndata.AnnData` object, it takes as an input a census object, the string for an organism, and for both cell and gene metadata we can specify filters and column selection as described above but with the following arguments:\n",
     "\n",
-    "- `column_names` — a dictionary with two keys `obs` and `var` whose values are lists of strings indicating the columns to select for cell and gene metadata respectively.\n",
+    "- `obs_column_names` and `var_column_names` — a pair of arguments whose values are lists of strings indicating the columns to select for cell (`obs`) and gene (`var`) metadata respectively.\n",
     "- `obs_value_filter` —  python expression with selection conditions to fetch **cells** meeting a criteria. For full details see [tiledb.QueryCondition](https://tiledb-inc-tiledb.readthedocs-hosted.com/projects/tiledb-py/en/stable/python-api.html#query-condition).\n",
     "- `var_value_filter` —  python expression with selection conditions to fetch **genes** meeting a criteria. Details as above.  For full details see [tiledb.QueryCondition](https://tiledb-inc-tiledb.readthedocs-hosted.com/projects/tiledb-py/en/stable/python-api.html#query-condition).\n",
     "\n",
@@ -95,7 +95,7 @@
     "    organism=\"Homo sapiens\",\n",
     "    var_value_filter=\"feature_id in ['ENSG00000161798', 'ENSG00000188229']\",\n",
     "    obs_value_filter=\"cell_type == 'B cell' and tissue_general == 'lung' and disease == 'COVID-19' and is_primary_data == True\",\n",
-    "    column_names={\"obs\": [\"sex\"]},\n",
+    "    obs_column_names=[\"sex\"],\n",
     ")"
    ]
   },

tools/census_contrib_qc/embeddings_qc_2023-12-15.ipynb

@@ -488,7 +488,7 @@
     "    organism=\"homo_sapiens\",\n",
     "    measurement_name=\"RNA\",\n",
     "    obs_value_filter=\"tissue_general == 'central nervous system' and is_primary_data == True\",\n",
-    "    column_names={\"obs\": [\"cell_type\", \"assay\", \"soma_joinid\"]},\n",
+    "    obs_column_names=[\"cell_type\", \"assay\", \"soma_joinid\"],\n",
     "    obsm_layers=maintained_embs_human,\n",
     ")"
    ]
@@ -663,7 +663,7 @@
     "    organism=\"homo_sapiens\",\n",
     "    measurement_name=\"RNA\",\n",
     "    obs_value_filter=\"tissue_general == 'pancreas' and is_primary_data == True\",\n",
-    "    column_names={\"obs\": [\"cell_type\", \"assay\", \"soma_joinid\", \"dataset_id\", \"is_primary_data\"]},\n",
+    "    obs_column_names=[\"cell_type\", \"assay\", \"soma_joinid\", \"dataset_id\", \"is_primary_data\"],\n",
     "    obsm_layers=maintained_embs_human,\n",
     ")"
    ]
@@ -862,7 +862,7 @@
     "    organism=\"mus_musculus\",\n",
     "    measurement_name=\"RNA\",\n",
     "    obs_value_filter=\"tissue_general == 'heart' and is_primary_data == True\",\n",
-    "    column_names={\"obs\": [\"cell_type\", \"assay\", \"soma_joinid\"]},\n",
+    "    obs_column_names=[\"cell_type\", \"assay\", \"soma_joinid\"],\n",
     "    obsm_layers=maintained_embs_mouse,\n",
     ")"
    ]
@@ -1014,7 +1014,7 @@
     "    organism=\"mus_musculus\",\n",
     "    measurement_name=\"RNA\",\n",
     "    obs_value_filter=\"tissue_general == 'pancreas'\",\n",
-    "    column_names={\"obs\": [\"cell_type\", \"assay\", \"soma_joinid\"]},\n",
+    "    obs_column_names=[\"cell_type\", \"assay\", \"soma_joinid\"],\n",
     "    obsm_layers=maintained_embs_mouse,\n",
     ")"
    ]