fix 4ea83c7

Author: cmp0xff

pandas-stubs/_typing.pyi

@@ -317,6 +317,10 @@ BuiltinFloatDtypeArg: TypeAlias = type[float] | Literal["float"]
 PandasFloatDtypeArg: TypeAlias = (
     pd.Float32Dtype | pd.Float64Dtype | Literal["Float32", "Float64"]
 )
+PandasAstypeFloatDtypeArg: TypeAlias = (
+    Literal["float_"]  # noqa: PYI030
+    | Literal["f16", "float128", "longdouble", "longfloat"]
+)
 # Numpy float types and their string aliases
 NumpyFloatDtypeArg: TypeAlias = (
     # NOTE: Alias np.float16 only on Linux x86_64, use np.half instead
@@ -328,10 +332,10 @@ NumpyFloatDtypeArg: TypeAlias = (
     | Literal["f", "f4", "float32", "single"]
     # https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.double
     | type[np.double]
-    | Literal["d", "f8", "float64", "double", "float_"]
+    | Literal["d", "f8", "float64", "double"]
     # https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.longdouble
     | type[np.longdouble]
-    | Literal["g", "f16", "float128", "longdouble", "longfloat"]
+    | Literal["g"]  # "float128"
 )
 # PyArrow floating point types and their string aliases
 PyArrowFloatDtypeArg: TypeAlias = Literal[
@@ -344,38 +348,41 @@ PyArrowFloatDtypeArg: TypeAlias = Literal[
 FloatDtypeArg: TypeAlias = (
     BuiltinFloatDtypeArg
     | PandasFloatDtypeArg
+    | PandasAstypeFloatDtypeArg
     | NumpyFloatDtypeArg
     | PyArrowFloatDtypeArg
 )
 # Builtin complex type and its string alias
 BuiltinComplexDtypeArg: TypeAlias = type[complex] | Literal["complex"]
+PandasAstypeComplexDtypeArg: TypeAlias = (
+    Literal["singlecomplex"]  # noqa: PYI030
+    | Literal["cfloat", "complex_"]
+    | Literal["c32", "complex256", "clongfloat", "longcomplex"]
+)
 # Numpy complex types and their aliases
 NumpyComplexDtypeArg: TypeAlias = (
     # https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.csingle
     type[np.csingle]  # noqa: PYI030
-    | Literal["F", "c8", "complex64", "csingle", "singlecomplex"]
+    | Literal["F", "c8", "complex64", "csingle"]
     # https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.cdouble
     | type[np.cdouble]
-    | Literal["D", "c16", "complex128", "cdouble", "cfloat", "complex_"]
+    | Literal["D", "c16", "complex128", "cdouble"]
     #  https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.clongdouble
     # NOTE: Alias np.complex256 only on Linux x86_64, use np.clongdouble instead
     | type[np.clongdouble]
-    | Literal["G", "c32", "complex256", "clongdouble", "clongfloat", "longcomplex"]
+    | Literal["G", "clongdouble"]
 )
-ComplexDtypeArg: TypeAlias = BuiltinComplexDtypeArg | NumpyComplexDtypeArg
-# Refer to https://numpy.org/doc/stable/reference/arrays.datetime.html#datetime-units
-NumpyTimedeltaDtypeArg: TypeAlias = Literal[
+ComplexDtypeArg: TypeAlias = (
+    BuiltinComplexDtypeArg | PandasAstypeComplexDtypeArg | NumpyComplexDtypeArg
+)
+PandasAstypeTimedeltaDtypeArg: TypeAlias = Literal[
     "timedelta64[Y]",
     "timedelta64[M]",
     "timedelta64[W]",
     "timedelta64[D]",
     "timedelta64[h]",
     "timedelta64[m]",
-    "timedelta64[s]",
-    "timedelta64[ms]",
-    "timedelta64[us]",
     "timedelta64[μs]",
-    "timedelta64[ns]",
     "timedelta64[ps]",
     "timedelta64[fs]",
     "timedelta64[as]",
@@ -386,11 +393,7 @@ NumpyTimedeltaDtypeArg: TypeAlias = Literal[
     "m8[D]",
     "m8[h]",
     "m8[m]",
-    "m8[s]",
-    "m8[ms]",
-    "m8[us]",
     "m8[μs]",
-    "m8[ns]",
     "m8[ps]",
     "m8[fs]",
     "m8[as]",
@@ -401,50 +404,69 @@ NumpyTimedeltaDtypeArg: TypeAlias = Literal[
     "<m8[D]",
     "<m8[h]",
     "<m8[m]",
-    "<m8[s]",
-    "<m8[ms]",
-    "<m8[us]",
     "<m8[μs]",
-    "<m8[ns]",
     "<m8[ps]",
     "<m8[fs]",
     "<m8[as]",
 ]
+# Refer to https://numpy.org/doc/stable/reference/arrays.datetime.html#datetime-units
+NumpyTimedeltaDtypeArg: TypeAlias = Literal[
+    "timedelta64[s]",
+    "timedelta64[ms]",
+    "timedelta64[us]",
+    "timedelta64[ns]",
+    # numpy type codes
+    "m8[s]",
+    "m8[ms]",
+    "m8[us]",
+    "m8[ns]",
+    # little endian
+    "<m8[s]",
+    "<m8[ms]",
+    "<m8[us]",
+    "<m8[ns]",
+]
 # PyArrow duration type and its string alias
 PyArrowTimedeltaDtypeArg: TypeAlias = Literal[
     "duration[s][pyarrow]",
     "duration[ms][pyarrow]",
     "duration[us][pyarrow]",
     "duration[ns][pyarrow]",
 ]
-TimedeltaDtypeArg: TypeAlias = NumpyTimedeltaDtypeArg | PyArrowTimedeltaDtypeArg
-NumpyTimestampDtypeArg: TypeAlias = Literal[
+TimedeltaDtypeArg: TypeAlias = (
+    PandasAstypeTimedeltaDtypeArg | NumpyTimedeltaDtypeArg | PyArrowTimedeltaDtypeArg
+)
+# Pandas timestamp type and its string alias
+# Not comprehensive
+PandasTimestampDtypeArg: TypeAlias = (
+    pd.DatetimeTZDtype
+    | Literal[
+        "datetime64[s, UTC]",
+        "datetime64[ms, UTC]",
+        "datetime64[us, UTC]",
+        "datetime64[ns, UTC]",
+    ]
+)
+PandasAstypeTimestampDtypeArg: TypeAlias = Literal[
+    # numpy datetime64
     "datetime64[Y]",
     "datetime64[M]",
     "datetime64[W]",
     "datetime64[D]",
     "datetime64[h]",
     "datetime64[m]",
-    "datetime64[s]",
-    "datetime64[ms]",
-    "datetime64[us]",
     "datetime64[μs]",
-    "datetime64[ns]",
     "datetime64[ps]",
     "datetime64[fs]",
     "datetime64[as]",
-    # numpy type codes
+    # numpy datetime64 type codes
     "M8[Y]",
     "M8[M]",
     "M8[W]",
     "M8[D]",
     "M8[h]",
     "M8[m]",
-    "M8[s]",
-    "M8[ms]",
-    "M8[us]",
     "M8[μs]",
-    "M8[ns]",
     "M8[ps]",
     "M8[fs]",
     "M8[as]",
@@ -455,26 +477,28 @@ NumpyTimestampDtypeArg: TypeAlias = Literal[
     "<M8[D]",
     "<M8[h]",
     "<M8[m]",
-    "<M8[s]",
-    "<M8[ms]",
-    "<M8[us]",
     "<M8[μs]",
-    "<M8[ns]",
     "<M8[ps]",
     "<M8[fs]",
     "<M8[as]",
 ]
-# Pandas timestamp type and its string alias
-# Not comprehensive
-PandasTimestampDtypeArg: TypeAlias = (
-    pd.DatetimeTZDtype
-    | Literal[
-        "datetime64[s, UTC]",
-        "datetime64[ms, UTC]",
-        "datetime64[us, UTC]",
-        "datetime64[ns, UTC]",
-    ]
-)
+# Numpy timestamp type and its string alias
+NumpyTimestampDtypeArg: TypeAlias = Literal[
+    "datetime64[s]",
+    "datetime64[ms]",
+    "datetime64[us]",
+    "datetime64[ns]",
+    # numpy type codes
+    "M8[s]",
+    "M8[ms]",
+    "M8[us]",
+    "M8[ns]",
+    # little endian
+    "<M8[s]",
+    "<M8[ms]",
+    "<M8[us]",
+    "<M8[ns]",
+]
 # PyArrow timestamp type and its string alias
 PyArrowTimestampDtypeArg: TypeAlias = Literal[
     "date32[pyarrow]",
@@ -485,17 +509,18 @@ PyArrowTimestampDtypeArg: TypeAlias = Literal[
     "timestamp[ns][pyarrow]",
 ]
 TimestampDtypeArg: TypeAlias = (
-    PandasTimestampDtypeArg | NumpyTimestampDtypeArg | PyArrowTimestampDtypeArg
+    PandasTimestampDtypeArg
+    | PandasAstypeTimestampDtypeArg
+    | NumpyTimestampDtypeArg
+    | PyArrowTimestampDtypeArg
 )
 # Builtin str type and its string alias
 BuiltinStrDtypeArg: TypeAlias = type[str] | Literal["str"]
 # Pandas nullable string type and its string alias
 PandasStrDtypeArg: TypeAlias = pd.StringDtype | Literal["string"]
 # Numpy string type and its string alias
 # https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.str_
-NumpyStrDtypeArg: TypeAlias = (
-    type[np.str_] | Literal["U", "str_", "str0", "unicode", "unicode_"]
-)
+NumpyStrDtypeArg: TypeAlias = type[np.str_] | Literal["U", "str_", "unicode"]
 # PyArrow string type and its string alias
 PyArrowStrDtypeArg: TypeAlias = Literal["string[pyarrow]"]
 StrDtypeArg: TypeAlias = (
@@ -505,9 +530,7 @@ StrDtypeArg: TypeAlias = (
 BuiltinBytesDtypeArg: TypeAlias = type[bytes] | Literal["bytes"]
 # Numpy bytes type and its string alias
 # https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.bytes_
-NumpyBytesDtypeArg: TypeAlias = (
-    type[np.bytes_] | Literal["S", "bytes_", "bytes0", "string_"]
-)
+NumpyBytesDtypeArg: TypeAlias = type[np.bytes_] | Literal["S", "bytes_"]
 # PyArrow binary type and its string alias
 PyArrowBytesDtypeArg: TypeAlias = Literal["binary[pyarrow]"]
 BytesDtypeArg: TypeAlias = (
@@ -526,7 +549,7 @@ ObjectDtypeArg: TypeAlias = BuiltinObjectDtypeArg | NumpyObjectDtypeArg
 
 # Numpy void type and its string alias
 # https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.void
-NumpyVoidDtypeArg: TypeAlias = type[np.void] | Literal["V", "void", "void0"]
+NumpyVoidDtypeArg: TypeAlias = type[np.void] | Literal["V", "void"]
 VoidDtypeArg: TypeAlias = NumpyVoidDtypeArg
 
 # DtypeArg specifies all allowable dtypes in a functions its dtype argument
@@ -859,14 +882,21 @@ SliceType: TypeAlias = Hashable | None
 ## All types below this point are only used in pandas-stubs
 ######
 
-NumpyDtypeArg: TypeAlias = (
+BuiltinDtypeArg: TypeAlias = (
+    BuiltinBooleanDtypeArg
+    | BuiltinIntDtypeArg
+    | BuiltinFloatDtypeArg
+    | BuiltinComplexDtypeArg
+    | BuiltinStrDtypeArg
+    | BuiltinBytesDtypeArg
+    | BuiltinObjectDtypeArg
+)
+NumpyNotTimeDtypeArg: TypeAlias = (
     NumpyBooleanDtypeArg
     | NumpyIntDtypeArg
     | NumpyUIntDtypeArg
     | NumpyFloatDtypeArg
     | NumpyComplexDtypeArg
-    | NumpyTimedeltaDtypeArg
-    | NumpyTimestampDtypeArg
     | NumpyStrDtypeArg
     | NumpyBytesDtypeArg
     | NumpyObjectDtypeArg