simplify types

src/summarizedexperiment/utils/combiners.py

@@ -1,12 +1,11 @@
-from typing import Dict, List, Literal, Tuple
+from typing import Any, Dict, List, Literal, Tuple
 
 from biocframe import BiocFrame
 from biocgenerics import rownames
 from numpy import argwhere, find_common_type, ndarray
 from pandas import DataFrame, Index, concat
 from scipy.sparse import lil_matrix
 
-from ..types import ArrayTypes, BiocOrPandasFrame
 from .validators import validate_names, validate_shapes
 
 # from ..SummarizedExperiment import SummarizedExperiment
@@ -16,17 +15,17 @@
 __license__ = "MIT"
 
 
-def impose_common_precision(*x: ArrayTypes) -> List[ArrayTypes]:
+def impose_common_precision(*x: Any) -> List[Any]:
     """Check and transform input arrays into common dtypes.
 
     Args:
-        *x (ArrayTypes): Array like objects.
+        *x (Any): Array like objects.
 
             ``x`` may be either a :py:class:`~scipy.sparse.lil_matrix` or
             a :py:class:`~numpy.ndarray`.
 
     Returns:
-        List[ArrayTypes]: All transformed matrices.
+        List[Any]: All transformed matrices.
     """
     common_dtype = find_common_type([m.dtype for m in x], [])
     return [(m.astype(common_dtype) if m.dtype != common_dtype else m) for m in x]
@@ -62,15 +61,15 @@ def combine_metadata(experiments: List["SummarizedExperiment"]) -> Dict:
 
 
 def combine_frames(
-    x: List[BiocOrPandasFrame],
+    x: List[BiocFrame],
     use_names: bool,
     axis: int,
     remove_duplicate_columns: bool,
 ) -> DataFrame:
     """Combine a series of `DataFrame`-like objects.
 
     Args:
-        x (List[BiocOrPandasFrame]): Input frames.
+        x (List[BiocFrame]): Input frames.
             May be either a :py:class:`~biocframe.BiocFrame.BiocFrame` or
             :py:class:`~pandas.DataFrame`.
 

src/summarizedexperiment/utils/validators.py

@@ -1,17 +1,17 @@
 from typing import List
 
-from ..types import BiocOrPandasFrame
+from biocframe import BiocFrame
 
 __author__ = "keviny2, jkanche"
 __copyright__ = "keviny2"
 __license__ = "MIT"
 
 
-def _validate_single_frame(df: BiocOrPandasFrame) -> bool:
+def _validate_single_frame(df: BiocFrame) -> bool:
     """Validate there are no None or duplicated names.
 
     Args:
-        df (BiocOrPandasFrame): Object to validate.
+        df (BiocFrame): Object to validate.
             ``df`` may be a :py;class:`~biocframe.BiocFrame.BiocFrame` object.
             Alternatively, ``df`` may be a :py:class:`~pandas.DataFrame`.
 
@@ -24,11 +24,11 @@ def _validate_single_frame(df: BiocOrPandasFrame) -> bool:
     return (not any_null) and (not any_duplicates)
 
 
-def validate_names(x: List[BiocOrPandasFrame]) -> bool:
+def validate_names(x: List[BiocFrame]) -> bool:
     """Validate names across experiments.
 
     Args:
-        x (List[BiocOrPandasFrame]): Objects to validate.
+        x (List[BiocFrame]): Objects to validate.
             ``x`` may be a :py;class:`~biocframe.BiocFrame.BiocFrame` object.
             Alternatively, ``x`` may be a :py:class:`~pandas.DataFrame`.
 
@@ -47,11 +47,11 @@ def validate_names(x: List[BiocOrPandasFrame]) -> bool:
     return is_valid_names
 
 
-def validate_shapes(x: List[BiocOrPandasFrame]):
+def validate_shapes(x: List[BiocFrame]):
     """Validate shapes across experiments.
 
     Args:
-        x (List[BiocOrPandasFrame]): Objects to validate.
+        x (List[BiocFrame]): Objects to validate.
             ``x`` may be a :py;class:`~biocframe.BiocFrame.BiocFrame` object.
             Alternatively, ``x`` may be a :py:class:`~pandas.DataFrame`.