ENH: Improve dtypes

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

@@ -1,8 +1,12 @@
 import numpy as np
 import pyarrow as pa
 
+from pandas._libs.missing import NAType
+
 from pandas.core.dtypes.base import StorageExtensionDtype
 
 class ArrowDtype(StorageExtensionDtype):
     pyarrow_dtype: pa.DataType
     def __init__(self, pyarrow_dtype: pa.DataType) -> None: ...
+    @property
+    def na_value(self) -> NAType: ...

pandas-stubs/core/arrays/boolean.pyi

@@ -1,9 +1,7 @@
 import numpy as np
 
-from pandas._typing import (
-    Scalar,
-    type_t,
-)
+from pandas._libs.missing import NAType
+from pandas._typing import type_t
 
 from pandas.core.dtypes.base import ExtensionDtype as ExtensionDtype
 
@@ -12,11 +10,7 @@ from .masked import BaseMaskedArray as BaseMaskedArray
 class BooleanDtype(ExtensionDtype):
     name: str = ...
     @property
-    def na_value(self) -> Scalar: ...
-    @property
-    def type(self) -> type_t: ...
-    @property
-    def kind(self) -> str: ...
+    def na_value(self) -> NAType: ...
     @classmethod
     def construct_array_type(cls) -> type_t[BooleanArray]: ...
     def __from_arrow__(self, array): ...

pandas-stubs/core/arrays/integer.pyi

@@ -1,26 +1,27 @@
+import numpy as np
+
+from pandas._libs.missing import NAType
+
 from pandas.core.dtypes.base import ExtensionDtype as ExtensionDtype
 
 from .masked import BaseMaskedArray
 
-_type = type
-
 class _IntegerDtype(ExtensionDtype):
-    name: str
-    base = ...
-    type: _type
-    na_value = ...
-    def is_signed_integer(self): ...
-    def is_unsigned_integer(self): ...
-    def numpy_dtype(self): ...
-    def kind(self): ...
-    def itemsize(self): ...
+    base: None
+    @property
+    def na_value(self) -> NAType: ...
+    @property
+    def is_signed_integer(self) -> bool: ...
+    @property
+    def is_unsigned_integer(self) -> bool: ...
+    @property
+    def numpy_dtype(self) -> np.dtype: ...
+    @property
+    def itemsize(self) -> int: ...
     @classmethod
-    def construct_array_type(cls): ...
+    def construct_array_type(cls) -> type[IntegerArray]: ...
     def __from_arrow__(self, array): ...
 
-def safe_cast(values, dtype, copy): ...
-def coerce_to_array(values, dtype, mask=..., copy: bool = ...): ...
-
 class IntegerArray(BaseMaskedArray):
     def dtype(self): ...
     def __init__(self, values, mask, copy: bool = ...) -> None: ...

pandas-stubs/core/arrays/numpy_.pyi

@@ -5,24 +5,16 @@ from pandas.core.arrays.base import (
     ExtensionOpsMixin,
 )
 
+from pandas._typing import npt
+
 from pandas.core.dtypes.dtypes import ExtensionDtype
 
 class PandasDtype(ExtensionDtype):
-    def __init__(self, dtype) -> None: ...
-    @property
-    def numpy_dtype(self): ...
-    @property
-    def name(self): ...
-    @property
-    def type(self): ...
-    @classmethod
-    def construct_from_string(cls, string): ...
-    @classmethod
-    def construct_array_type(cls): ...
+    def __init__(self, dtype: npt.DTypeLike) -> None: ...
     @property
-    def kind(self): ...
+    def numpy_dtype(self) -> np.dtype: ...
     @property
-    def itemsize(self): ...
+    def itemsize(self) -> int: ...
 
 class PandasArray(ExtensionArray, ExtensionOpsMixin, NDArrayOperatorsMixin):
     def __array_ufunc__(self, ufunc, method, *inputs, **kwargs): ...

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

@@ -1,33 +1,22 @@
+import numpy as np
+
 from pandas._typing import (
     Dtype,
     Scalar,
+    npt,
 )
 
 from pandas.core.dtypes.base import ExtensionDtype
 from pandas.core.dtypes.dtypes import (
     register_extension_dtype as register_extension_dtype,
 )
 
-# merged types from pylance
-
 class SparseDtype(ExtensionDtype):
-    def __init__(self, dtype: Dtype = ..., fill_value: Scalar | None = ...) -> None: ...
-    def __hash__(self): ...
-    def __eq__(self, other) -> bool: ...
-    @property
-    def fill_value(self): ...
-    @property
-    def kind(self): ...
-    @property
-    def type(self): ...
+    def __init__(
+        self, dtype: Dtype | npt.DTypeLike = ..., fill_value: Scalar | None = ...
+    ) -> None: ...
     @property
-    def subtype(self): ...
+    def fill_value(self) -> Scalar | None: ...
     @property
-    def name(self): ...
-    @classmethod
-    def construct_array_type(cls): ...
-    @classmethod
-    def construct_from_string(cls, string): ...
-    @classmethod
-    def is_dtype(cls, dtype): ...
-    def update_dtype(self, dtype): ...
+    def subtype(self) -> Dtype: ...
+    def update_dtype(self, dtype: SparseDtype | npt.DTypeLike) -> SparseDtype: ...

pandas-stubs/core/arrays/string_.pyi

@@ -1,17 +1,18 @@
+from typing import Literal
+
+import numpy as np
+import pandas as pd
 from pandas.core.arrays import PandasArray
 
-from pandas._typing import type_t
+from pandas._libs.missing import NAType
 
 from pandas.core.dtypes.base import ExtensionDtype
 
 class StringDtype(ExtensionDtype):
-    name: str = ...
-    na_value = ...
-    @property
-    def type(self) -> type_t: ...
-    @classmethod
-    def construct_array_type(cls) -> type_t[StringArray]: ...
+    def __init__(self, storage: Literal["python", "pyarrow"] | None) -> None: ...
     def __from_arrow__(self, array): ...
+    @property
+    def na_value(self) -> NAType: ...
 
 class StringArray(PandasArray):
     def __init__(self, values, copy: bool = ...) -> None: ...

pandas-stubs/core/dtypes/base.pyi

@@ -3,9 +3,6 @@ from pandas.core.arrays import ExtensionArray
 from pandas._typing import type_t
 
 class ExtensionDtype:
-    def __eq__(self, other) -> bool: ...
-    def __hash__(self) -> int: ...
-    def __ne__(self, other) -> bool: ...
     @property
     def na_value(self): ...
     @property
@@ -16,10 +13,11 @@ class ExtensionDtype:
     def name(self) -> str: ...
     @property
     def names(self) -> list[str] | None: ...
+    def empty(self, size: int | tuple[int, ...]) -> type_t[ExtensionArray]: ...
     @classmethod
     def construct_array_type(cls) -> type_t[ExtensionArray]: ...
     @classmethod
-    def construct_from_string(cls, string: str): ...
+    def construct_from_string(cls, string: str) -> ExtensionDtype: ...
     @classmethod
     def is_dtype(cls, dtype) -> bool: ...
 

pandas-stubs/core/dtypes/dtypes.pyi

@@ -1,125 +1,71 @@
+import datetime as dt
 from typing import (
     Any,
-    Sequence,
+    Literal,
 )
 
+import numpy as np
 from pandas.core.indexes.base import Index
+from pandas.core.series import Series
 
-from pandas._libs.tslibs import (  # , timezones as timezones
-    Period as Period,
-    Timestamp,
+from pandas._libs import NaTType
+from pandas._libs.tslibs import BaseOffset
+from pandas._typing import (
+    Ordered,
+    npt,
 )
-from pandas._typing import Ordered
 
 from .base import ExtensionDtype as ExtensionDtype
 
-_str = str
-
 def register_extension_dtype(cls: type[ExtensionDtype]) -> type[ExtensionDtype]: ...
 
 class BaseMaskedDtype(ExtensionDtype): ...
 
 class PandasExtensionDtype(ExtensionDtype):
     subdtype = ...
-    str: _str | None = ...
+    str: str | None = ...
     num: int = ...
     shape: tuple[int, ...] = ...
     itemsize: int = ...
     base = ...
     isbuiltin: int = ...
     isnative: int = ...
-    def __hash__(self) -> int: ...
+
     @classmethod
     def reset_cache(cls) -> None: ...
 
-class CategoricalDtypeType(type): ...
-
 class CategoricalDtype(PandasExtensionDtype, ExtensionDtype):
-    name: _str = ...
-    type: type[CategoricalDtypeType] = ...
-    kind: _str = ...
-    str: _str = ...
-    base = ...
     def __init__(
-        self, categories: Sequence[Any] | None = ..., ordered: Ordered = ...
+        self,
+        categories: Series | Index | list[Any] | None = ...,
+        ordered: Ordered = ...,
     ) -> None: ...
-    @classmethod
-    def construct_from_string(cls, string: _str) -> CategoricalDtype: ...
-    def __hash__(self) -> int: ...
-    def __eq__(self, other) -> bool: ...
-    @classmethod
-    def construct_array_type(cls): ...
-    @staticmethod
-    def validate_ordered(ordered: Ordered) -> None: ...
-    @staticmethod
-    def validate_categories(categories, fastpath: bool = ...): ...
-    def update_dtype(self, dtype: _str | CategoricalDtype) -> CategoricalDtype: ...
     @property
     def categories(self) -> Index: ...
     @property
     def ordered(self) -> Ordered: ...
 
 class DatetimeTZDtype(PandasExtensionDtype):
-    type: type[Timestamp] = ...
-    kind: _str = ...
-    str: _str = ...
-    num: int = ...
-    base = ...
-    na_value = ...
-    def __init__(self, unit: _str = ..., tz=...) -> None: ...
+    def __init__(
+        self, unit: Literal["ns"] = ..., tz: str | int | dt.tzinfo | None = ...
+    ) -> None: ...
     @property
-    def unit(self): ...
+    def unit(self) -> Literal["ns"]: ...
     @property
-    def tz(self): ...
-    @classmethod
-    def construct_array_type(cls): ...
-    @classmethod
-    def construct_from_string(cls, string: _str): ...
+    def tz(self) -> dt.tzinfo: ...
     @property
-    def name(self) -> _str: ...
-    def __hash__(self) -> int: ...
-    def __eq__(self, other) -> bool: ...
+    def na_value(self) -> NaTType: ...
 
 class PeriodDtype(PandasExtensionDtype):
-    type: type[Period] = ...
-    kind: _str = ...
-    str: _str = ...
-    base = ...
-    num: int = ...
-    def __new__(cls, freq=...): ...
-    @property
-    def freq(self): ...
-    @classmethod
-    def construct_from_string(cls, string: _str): ...
+    def __init__(self, freq: str | BaseOffset = ...): ...
     @property
-    def name(self) -> _str: ...
+    def freq(self) -> BaseOffset: ...
     @property
-    def na_value(self): ...
-    def __hash__(self) -> int: ...
-    def __eq__(self, other) -> bool: ...
-    @classmethod
-    def is_dtype(cls, dtype) -> bool: ...
-    @classmethod
-    def construct_array_type(cls): ...
+    def na_value(self) -> NaTType: ...
     def __from_arrow__(self, array): ...
 
 class IntervalDtype(PandasExtensionDtype):
-    name: _str = ...
-    kind: _str = ...
-    str: _str = ...
-    base = ...
-    num: int = ...
-    def __new__(cls, subtype=...): ...
-    @property
-    def subtype(self): ...
-    @classmethod
-    def construct_array_type(cls): ...
-    @classmethod
-    def construct_from_string(cls, string: _str): ...
+    def __init__(self, subtype: str | npt.DTypeLike | None = ...): ...
     @property
-    def type(self): ...
-    def __hash__(self) -> int: ...
-    def __eq__(self, other) -> bool: ...
-    @classmethod
-    def is_dtype(cls, dtype) -> bool: ...
+    def subtype(self) -> np.dtype | None: ...
     def __from_arrow__(self, array): ...