Refactoring cxg utility classes in preparation for CXG conversion tooling (#1739)

server/data_anndata/anndata_adaptor.py

@@ -1,22 +1,22 @@
 import warnings
-
-import numpy as np
-from pandas.core.dtypes.dtypes import CategoricalDtype
-import anndata
-from scipy import sparse
-from packaging import version
 from datetime import datetime
+
+import anndata
+import numpy as np
+from packaging import version
+from pandas.core.dtypes.dtypes import CategoricalDtype
+from scipy import sparse
 from server_timing import Timing as ServerTiming
 
-from server.data_common.data_adaptor import DataAdaptor
-from server.data_common.fbs.matrix import encode_matrix_fbs
-from server.common.utils import series_to_schema
+import server.compute.diffexp_generic as diffexp_generic
 from server.common.colors import convert_anndata_category_colors_to_cxg_category_colors
 from server.common.constants import Axis, MAX_LAYOUTS
-from server.common.errors import PrepareError, DatasetAccessError, FilterError
-from server.compute.scanpy import scanpy_umap
-import server.compute.diffexp_generic as diffexp_generic
 from server.common.corpora import corpora_get_props_from_anndata
+from server.common.errors import PrepareError, DatasetAccessError, FilterError
+from server.common.utils.type_conversion_utils import get_schema_type_hint_of_array
+from server.compute.scanpy import scanpy_umap
+from server.data_common.data_adaptor import DataAdaptor
+from server.data_common.fbs.matrix import encode_matrix_fbs
 
 anndata_version = version.parse(str(anndata.__version__)).release
 
@@ -137,7 +137,7 @@ class AnndataAdaptor(DataAdaptor):
             curr_axis = getattr(self.data, str(ax))
             for ann in curr_axis:
                 ann_schema = {"name": ann, "writable": False}
-                ann_schema.update(series_to_schema(curr_axis[ann]))
+                ann_schema.update(get_schema_type_hint_of_array(curr_axis[ann]))
                 self.schema["annotations"][ax]["columns"].append(ann_schema)
 
         for layout in self.get_embedding_names():