ENH: Improve api.types

pandas-stubs/_libs/lib.pyi

@@ -1,3 +1,9 @@
-no_default = None
-
 def infer_dtype(value: object, skipna: bool = ...) -> str: ...
+def is_iterator(obj: object) -> bool: ...
+def is_scalar(val: object) -> bool: ...
+def is_list_like(obj: object, allow_sets: bool = ...) -> bool: ...
+def is_interval(val: object) -> bool: ...
+def is_complex(val: object) -> bool: ...
+def is_bool(val: object) -> bool: ...
+def is_integer(val: object) -> bool: ...
+def is_float(val: object) -> bool: ...

pandas-stubs/api/extensions/__init__.pyi

@@ -8,8 +8,6 @@ from pandas.core.arrays import (
     ExtensionScalarOpsMixin as ExtensionScalarOpsMixin,
 )
 
-from pandas._libs.lib import no_default as no_default
-
 from pandas.core.dtypes.dtypes import (
     ExtensionDtype as ExtensionDtype,
     register_extension_dtype as register_extension_dtype,

pandas-stubs/api/types/__init__.pyi

@@ -4,7 +4,6 @@ from pandas.core.dtypes.api import (
     is_array_like as is_array_like,
     is_bool as is_bool,
     is_bool_dtype as is_bool_dtype,
-    is_categorical as is_categorical,
     is_categorical_dtype as is_categorical_dtype,
     is_complex as is_complex,
     is_complex_dtype as is_complex_dtype,
@@ -15,7 +14,6 @@ from pandas.core.dtypes.api import (
     is_dict_like as is_dict_like,
     is_dtype_equal as is_dtype_equal,
     is_extension_array_dtype as is_extension_array_dtype,
-    is_extension_type as is_extension_type,
     is_file_like as is_file_like,
     is_float as is_float,
     is_float_dtype as is_float_dtype,

pandas-stubs/core/arrays/sparse/__init__.pyi

@@ -2,9 +2,5 @@ from .accessor import (
     SparseAccessor as SparseAccessor,
     SparseFrameAccessor as SparseFrameAccessor,
 )
-from .array import (
-    BlockIndex as BlockIndex,
-    IntIndex as IntIndex,
-    SparseArray as SparseArray,
-)
+from .array import SparseArray as SparseArray
 from .dtype import SparseDtype as SparseDtype

pandas-stubs/core/arrays/sparse/accessor.pyi

@@ -1,11 +1,4 @@
-from pandas.core.accessor import (
-    PandasDelegate as PandasDelegate,
-    delegate_names as delegate_names,
-)
-from pandas.core.arrays.sparse.array import SparseArray as SparseArray
-from pandas.core.arrays.sparse.dtype import SparseDtype as SparseDtype
-
-from pandas.core.dtypes.cast import find_common_type as find_common_type
+from pandas.core.accessor import PandasDelegate
 
 class BaseAccessor:
     def __init__(self, data=...) -> None: ...

pandas-stubs/core/arrays/sparse/array.pyi

@@ -1,44 +1,9 @@
 import numpy as np
 from pandas.core.arrays import (
-    ExtensionArray as ExtensionArray,
+    ExtensionArray,
     ExtensionOpsMixin,
 )
-from pandas.core.arrays.sparse.dtype import SparseDtype as SparseDtype
 from pandas.core.base import PandasObject as PandasObject
-from pandas.core.construction import sanitize_array as sanitize_array
-from pandas.core.indexers import check_array_indexer as check_array_indexer
-from pandas.core.missing import interpolate_2d as interpolate_2d
-
-from pandas._libs.sparse import (
-    BlockIndex as BlockIndex,
-    IntIndex as IntIndex,
-    SparseIndex as SparseIndex,
-)
-from pandas._libs.tslibs import NaT as NaT
-from pandas.errors import PerformanceWarning as PerformanceWarning
-
-from pandas.core.dtypes.cast import (
-    astype_nansafe as astype_nansafe,
-    construct_1d_arraylike_from_scalar as construct_1d_arraylike_from_scalar,
-    find_common_type as find_common_type,
-)
-from pandas.core.dtypes.common import (
-    is_array_like as is_array_like,
-    is_bool_dtype as is_bool_dtype,
-    is_datetime64_any_dtype as is_datetime64_any_dtype,
-    is_dtype_equal as is_dtype_equal,
-    is_integer as is_integer,
-    is_object_dtype as is_object_dtype,
-    is_scalar as is_scalar,
-    is_string_dtype as is_string_dtype,
-    pandas_dtype as pandas_dtype,
-)
-from pandas.core.dtypes.generic import ABCSeries as ABCSeries
-from pandas.core.dtypes.missing import (
-    isna as isna,
-    na_value_for_dtype as na_value_for_dtype,
-    notna as notna,
-)
 
 class SparseArray(PandasObject, ExtensionArray, ExtensionOpsMixin):
     def __init__(

pandas-stubs/core/arrays/sparse/dtype.pyi

@@ -3,22 +3,10 @@ from pandas._typing import (
     Scalar,
 )
 
-from pandas.core.dtypes.base import ExtensionDtype as ExtensionDtype
-from pandas.core.dtypes.cast import astype_nansafe as astype_nansafe
-from pandas.core.dtypes.common import (
-    is_bool_dtype as is_bool_dtype,
-    is_object_dtype as is_object_dtype,
-    is_scalar as is_scalar,
-    is_string_dtype as is_string_dtype,
-    pandas_dtype as pandas_dtype,
-)
+from pandas.core.dtypes.base import ExtensionDtype
 from pandas.core.dtypes.dtypes import (
     register_extension_dtype as register_extension_dtype,
 )
-from pandas.core.dtypes.missing import (
-    isna as isna,
-    na_value_for_dtype as na_value_for_dtype,
-)
 
 # merged types from pylance
 

pandas-stubs/core/dtypes/api.pyi

@@ -2,7 +2,6 @@ from pandas.core.dtypes.common import (
     is_array_like as is_array_like,
     is_bool as is_bool,
     is_bool_dtype as is_bool_dtype,
-    is_categorical as is_categorical,
     is_categorical_dtype as is_categorical_dtype,
     is_complex as is_complex,
     is_complex_dtype as is_complex_dtype,
@@ -13,7 +12,6 @@ from pandas.core.dtypes.common import (
     is_dict_like as is_dict_like,
     is_dtype_equal as is_dtype_equal,
     is_extension_array_dtype as is_extension_array_dtype,
-    is_extension_type as is_extension_type,
     is_file_like as is_file_like,
     is_float as is_float,
     is_float_dtype as is_float_dtype,

pandas-stubs/core/dtypes/cast.pyi

@@ -1,28 +0,0 @@
-import numpy as np
-
-from pandas._typing import Dtype
-
-def is_nested_object(obj) -> bool: ...
-def infer_dtype_from(val, pandas_dtype: bool = ...): ...
-def infer_dtype_from_scalar(val, pandas_dtype: bool = ...): ...
-def infer_dtype_from_array(arr, pandas_dtype: bool = ...): ...
-def invalidate_string_dtypes(dtype_set) -> None: ...
-def coerce_indexer_dtype(indexer, categories): ...
-def astype_nansafe(arr, dtype, copy: bool = ..., skipna: bool = ...): ...
-def soft_convert_objects(
-    values: np.ndarray,
-    datetime: bool = ...,
-    numeric: bool = ...,
-    timedelta: bool = ...,
-    coerce: bool = ...,
-    copy: bool = ...,
-): ...
-def convert_dtypes(
-    input_array,
-    convert_string: bool = ...,
-    convert_integer: bool = ...,
-    convert_boolean: bool = ...,
-) -> Dtype: ...
-def find_common_type(types): ...
-def construct_1d_arraylike_from_scalar(value, length: int, dtype): ...
-def construct_1d_object_array_from_listlike(values): ...

pandas-stubs/core/dtypes/common.pyi

@@ -1,6 +1,13 @@
-from typing import Callable
+from typing import Union
 
 import numpy as np
+import pandas as pd
+
+from pandas._typing import (
+    ArrayLike,
+    DtypeObj,
+    npt,
+)
 
 from pandas.core.dtypes.inference import (
     is_array_like as is_array_like,
@@ -21,37 +28,28 @@ from pandas.core.dtypes.inference import (
     is_scalar as is_scalar,
 )
 
-def classes(*klasses) -> Callable: ...
-def classes_and_not_datetimelike(*klasses) -> Callable: ...
-def is_object_dtype(arr_or_dtype) -> bool: ...
-def is_sparse(arr) -> bool: ...
-def is_scipy_sparse(arr) -> bool: ...
-def is_categorical(arr) -> bool: ...
-def is_datetime64_dtype(arr_or_dtype) -> bool: ...
-def is_datetime64tz_dtype(arr_or_dtype) -> bool: ...
-def is_timedelta64_dtype(arr_or_dtype) -> bool: ...
-def is_period_dtype(arr_or_dtype) -> bool: ...
-def is_interval_dtype(arr_or_dtype) -> bool: ...
-def is_categorical_dtype(arr_or_dtype) -> bool: ...
-def is_string_dtype(arr_or_dtype) -> bool: ...
+_ArrayOrDtype = Union[ArrayLike, npt.DTypeLike, pd.Series, pd.DataFrame]
+
+def is_object_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
+def is_sparse(arr: ArrayLike | pd.Series | pd.DataFrame) -> bool: ...
+def is_datetime64_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
+def is_datetime64tz_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
+def is_timedelta64_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
+def is_period_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
 def is_dtype_equal(source, target) -> bool: ...
-def is_any_int_dtype(arr_or_dtype) -> bool: ...
-def is_integer_dtype(arr_or_dtype) -> bool: ...
-def is_signed_integer_dtype(arr_or_dtype) -> bool: ...
-def is_unsigned_integer_dtype(arr_or_dtype) -> bool: ...
-def is_int64_dtype(arr_or_dtype) -> bool: ...
-def is_datetime64_any_dtype(arr_or_dtype) -> bool: ...
-def is_datetime64_ns_dtype(arr_or_dtype) -> bool: ...
-def is_timedelta64_ns_dtype(arr_or_dtype) -> bool: ...
-def is_datetime_or_timedelta_dtype(arr_or_dtype) -> bool: ...
-def is_numeric_v_string_like(a, b): ...
-def is_datetimelike_v_numeric(a, b): ...
-def needs_i8_conversion(arr_or_dtype) -> bool: ...
-def is_numeric_dtype(arr_or_dtype) -> bool: ...
-def is_float_dtype(arr_or_dtype) -> bool: ...
-def is_bool_dtype(arr_or_dtype) -> bool: ...
-def is_extension_type(arr) -> bool: ...
-def is_extension_array_dtype(arr_or_dtype) -> bool: ...
-def is_complex_dtype(arr_or_dtype) -> bool: ...
-def infer_dtype_from_object(dtype): ...
-def pandas_dtype(dtype): ...
+def is_interval_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
+def is_categorical_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
+def is_string_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
+def is_integer_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
+def is_signed_integer_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
+def is_unsigned_integer_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
+def is_int64_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
+def is_datetime64_any_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
+def is_datetime64_ns_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
+def is_timedelta64_ns_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
+def is_numeric_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
+def is_float_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
+def is_bool_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
+def is_extension_array_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
+def is_complex_dtype(arr_or_dtype: _ArrayOrDtype) -> bool: ...
+def pandas_dtype(dtype: object) -> DtypeObj: ...

pandas-stubs/core/dtypes/concat.pyi

@@ -1,4 +1,16 @@
-def concat_compat(to_concat, axis: int = ...): ...
+from typing import (
+    TypeVar,
+    Union,
+)
+
+from pandas import (
+    Categorical,
+    CategoricalIndex,
+    Series,
+)
+
+_CatT = TypeVar("_CatT", bound=Union[Categorical, CategoricalIndex, Series])
+
 def union_categoricals(
-    to_union, sort_categories: bool = ..., ignore_order: bool = ...
-): ...
+    to_union: list[_CatT], sort_categories: bool = ..., ignore_order: bool = ...
+) -> Categorical: ...

pandas-stubs/core/dtypes/dtypes.pyi

@@ -6,7 +6,6 @@ from typing import (
 from pandas.core.indexes.base import Index
 
 from pandas._libs.tslibs import (  # , timezones as timezones
-    NaT as NaT,
     Period as Period,
     Timestamp,
 )

pandas-stubs/core/dtypes/generic.pyi

@@ -1,15 +1,5 @@
-from pandas import (
-    DataFrame,
-    Index,
-    Series,
-)
+from pandas import Series
 from pandas.core.arrays import ExtensionArray
-from pandas.core.generic import NDFrame
 
-ABCIndex = type[Index]
-
-ABCNDFrame = type[NDFrame]
 ABCSeries = type[Series]
-ABCDataFrame = type[DataFrame]
-
 ABCExtensionArray = type[ExtensionArray]

pandas-stubs/core/dtypes/inference.pyi

@@ -1,19 +1,19 @@
-def is_bool(obj) -> bool: ...
-def is_integer(obj) -> bool: ...
-def is_float(obj) -> bool: ...
-def is_complex(obj) -> bool: ...
-def is_scalar(obj) -> bool: ...
-def is_decimal(obj) -> bool: ...
-def is_interval(obj) -> bool: ...
-def is_list_like(obj) -> bool: ...
-def is_number(obj) -> bool: ...
-def is_iterator(obj) -> bool: ...
-def is_file_like(obj) -> bool: ...
-def is_re(obj) -> bool: ...
-def is_re_compilable(obj) -> bool: ...
-def is_array_like(obj) -> bool: ...
-def is_nested_list_like(obj) -> bool: ...
-def is_dict_like(obj) -> bool: ...
-def is_named_tuple(obj) -> bool: ...
-def is_hashable(obj) -> bool: ...
-def is_sequence(obj) -> bool: ...
+from pandas._libs import lib
+
+is_bool = lib.is_bool
+is_integer = lib.is_integer
+is_float = lib.is_float
+is_complex = lib.is_complex
+is_scalar = lib.is_scalar
+is_interval = lib.is_interval
+is_list_like = lib.is_list_like
+is_iterator = lib.is_iterator
+
+def is_number(obj: object) -> bool: ...
+def is_file_like(obj: object) -> bool: ...
+def is_re(obj: object) -> bool: ...
+def is_array_like(obj: object) -> bool: ...
+def is_re_compilable(obj: object) -> bool: ...
+def is_dict_like(obj: object) -> bool: ...
+def is_named_tuple(obj: object) -> bool: ...
+def is_hashable(obj: object) -> bool: ...

pandas-stubs/core/dtypes/missing.pyi

@@ -36,7 +36,3 @@ def notna(obj: Index | list | ArrayLike) -> np.ndarray: ...
 def notna(obj: Scalar) -> bool: ...
 
 notnull = notna
-
-def array_equivalent(left, right, strict_nan: bool = ...) -> bool: ...
-def na_value_for_dtype(dtype, compat: bool = ...): ...
-def remove_na_arraylike(arr): ...

pandas-stubs/core/ops/dispatch.pyi

@@ -1,8 +1,5 @@
 import numpy as np
 
-from pandas.core.dtypes.generic import (
-    ABCExtensionArray as ABCExtensionArray,
-    ABCSeries,
-)
+from pandas.core.dtypes.generic import ABCSeries
 
 def should_extension_dispatch(left: ABCSeries, right) -> bool: ...

tests/__init__.py

@@ -11,7 +11,6 @@
 
 
 def check(actual: T, klass: type, dtype: type | None = None, attr: str = "left") -> T:
-
     if not isinstance(actual, klass):
         raise RuntimeError(f"Expected type '{klass}' but got '{type(actual)}'")
     if dtype is None: