refactor: typing module re-organization

Type safe types are no longer called strict, but type_safe; typing namespace free of type files, but submodules, and the type files are now in the loading submodule.

pydantic_numpy/__init__.py

@@ -1,4 +1,3 @@
 from pydantic_numpy.helper.annotation import np_array_pydantic_annotated_typing
-from pydantic_numpy.typing.n_dimensional import *
 
 __all__ = ["np_array_pydantic_annotated_typing", "model", "typing"]

pydantic_numpy/helper/annotation.py

@@ -1,6 +1,6 @@
 from collections.abc import Sequence
 from pathlib import Path
-from typing import Any, Callable, ClassVar, Iterable, Optional, Union
+from typing import Any, Callable, ClassVar, Iterable, Optional, Union, cast
 
 import numpy as np
 import numpy.typing as npt
@@ -55,12 +55,12 @@ def pd_np_native_numpy_array_to_data_dict_serializer(array_like: npt.ArrayLike)
     """
     array = np.array(array_like)
 
-    if issubclass(array.dtype.type, np.timedelta64) or issubclass(array.dtype.type, np.datetime64):
-        data = array.astype(int).tolist()
-    else:
-        data = array.astype(float).tolist()
+    data = array.astype(
+        int if issubclass(array.dtype.type, np.timedelta64) or issubclass(array.dtype.type, np.datetime64) else float
+    ).tolist()
+    cast_data = cast(list, data)
 
-    return NumpyArrayTypeData(data_type=str(array.dtype), data=data)
+    return NumpyArrayTypeData(data_type=str(array.dtype), data=cast_data)
 
 
 def pd_np_native_numpy_array_json_schema_from_type_data(

pydantic_numpy/typing/__init__.py

@@ -1,8 +1,4 @@
-from pydantic_numpy.typing.i_dimensional import *
-from pydantic_numpy.typing.ii_dimensional import *
-from pydantic_numpy.typing.iii_dimensional import *
-from pydantic_numpy.typing.n_dimensional import *
-from pydantic_numpy.typing.strict_data_type.i_dimensional import *
-from pydantic_numpy.typing.strict_data_type.ii_dimensional import *
-from pydantic_numpy.typing.strict_data_type.iii_dimensional import *
-from pydantic_numpy.typing.strict_data_type.n_dimensional import *
+from pydantic_numpy.typing.type_safe.i_dimensional import *
+from pydantic_numpy.typing.type_safe.ii_dimensional import *
+from pydantic_numpy.typing.type_safe.iii_dimensional import *
+from pydantic_numpy.typing.type_safe.n_dimensional import *

pydantic_numpy/typing/strict_data_type/i_dimensional.py → pydantic_numpy/typing/type_safe/i_dimensional.py

@@ -1,116 +1,122 @@
-from typing import Annotated
+from typing import Annotated, Any, TypeAlias
 
 import numpy as np
 
 from pydantic_numpy.helper.annotation import NpArrayPydanticAnnotation
 
-NpStrict1DArrayInt64 = Annotated[
+Np1DArray: TypeAlias = Annotated[
+    np.ndarray[tuple[int], np.dtype[Any]],
+    NpArrayPydanticAnnotation.factory(data_type=None, dimensions=1, strict_data_typing=False),
+]
+
+Np1DArrayInt64: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.int64]],
     NpArrayPydanticAnnotation.factory(data_type=np.int64, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayInt32 = Annotated[
+Np1DArrayInt32: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.int32]],
     NpArrayPydanticAnnotation.factory(data_type=np.int32, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayInt16 = Annotated[
+Np1DArrayInt16: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.int16]],
     NpArrayPydanticAnnotation.factory(data_type=np.int16, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayInt8 = Annotated[
+Np1DArrayInt8: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.int8]],
     NpArrayPydanticAnnotation.factory(data_type=np.int8, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayUint64 = Annotated[
+Np1DArrayUint64: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.uint64]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint64, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayUint32 = Annotated[
+Np1DArrayUint32: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.uint32]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint32, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayUint16 = Annotated[
+Np1DArrayUint16: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.uint16]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint16, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayUint8 = Annotated[
+Np1DArrayUint8: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.uint8]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint8, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayFpLongDouble = Annotated[
+Np1DArrayFpLongDouble: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.longdouble]],
     NpArrayPydanticAnnotation.factory(data_type=np.longdouble, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayFp64 = Annotated[
+Np1DArrayFp64: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.float64]],
     NpArrayPydanticAnnotation.factory(data_type=np.float64, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayFp32 = Annotated[
+Np1DArrayFp32: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.float32]],
     NpArrayPydanticAnnotation.factory(data_type=np.float32, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayFp16 = Annotated[
+Np1DArrayFp16: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.float16]],
     NpArrayPydanticAnnotation.factory(data_type=np.float16, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayComplexLongDouble = Annotated[
+Np1DArrayComplexLongDouble: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.clongdouble]],
     NpArrayPydanticAnnotation.factory(data_type=np.clongdouble, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayComplex128 = Annotated[
+Np1DArrayComplex128: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.complex128]],
     NpArrayPydanticAnnotation.factory(data_type=np.complex128, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayComplex64 = Annotated[
+Np1DArrayComplex64: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.complex64]],
     NpArrayPydanticAnnotation.factory(data_type=np.complex64, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayBool = Annotated[
+Np1DArrayBool: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.bool_]],
     NpArrayPydanticAnnotation.factory(data_type=np.bool_, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayDatetime64 = Annotated[
+Np1DArrayDatetime64: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.datetime64]],
     NpArrayPydanticAnnotation.factory(data_type=np.datetime64, dimensions=1, strict_data_typing=True),
 ]
 
-NpStrict1DArrayTimedelta64 = Annotated[
+Np1DArrayTimedelta64: TypeAlias = Annotated[
     np.ndarray[tuple[int], np.dtype[np.timedelta64]],
     NpArrayPydanticAnnotation.factory(data_type=np.timedelta64, dimensions=1, strict_data_typing=True),
 ]
 
 __all__ = [
-    "NpStrict1DArrayInt64",
-    "NpStrict1DArrayInt32",
-    "NpStrict1DArrayInt16",
-    "NpStrict1DArrayInt8",
-    "NpStrict1DArrayUint64",
-    "NpStrict1DArrayUint32",
-    "NpStrict1DArrayUint16",
-    "NpStrict1DArrayUint8",
-    "NpStrict1DArrayFpLongDouble",
-    "NpStrict1DArrayFp64",
-    "NpStrict1DArrayFp32",
-    "NpStrict1DArrayFp16",
-    "NpStrict1DArrayComplexLongDouble",
-    "NpStrict1DArrayComplex128",
-    "NpStrict1DArrayComplex64",
-    "NpStrict1DArrayBool",
-    "NpStrict1DArrayDatetime64",
-    "NpStrict1DArrayTimedelta64",
+    "Np1DArray",
+    "Np1DArrayInt64",
+    "Np1DArrayInt32",
+    "Np1DArrayInt16",
+    "Np1DArrayInt8",
+    "Np1DArrayUint64",
+    "Np1DArrayUint32",
+    "Np1DArrayUint16",
+    "Np1DArrayUint8",
+    "Np1DArrayFpLongDouble",
+    "Np1DArrayFp64",
+    "Np1DArrayFp32",
+    "Np1DArrayFp16",
+    "Np1DArrayComplexLongDouble",
+    "Np1DArrayComplex128",
+    "Np1DArrayComplex64",
+    "Np1DArrayBool",
+    "Np1DArrayDatetime64",
+    "Np1DArrayTimedelta64",
 ]

pydantic_numpy/typing/strict_data_type/ii_dimensional.py → pydantic_numpy/typing/type_safe/ii_dimensional.py

@@ -1,116 +1,122 @@
-from typing import Annotated
+from typing import Annotated, Any, TypeAlias
 
 import numpy as np
 
 from pydantic_numpy.helper.annotation import NpArrayPydanticAnnotation
 
-NpStrict2DArrayInt64 = Annotated[
+Np2DArray: TypeAlias = Annotated[
+    np.ndarray[tuple[int, int], np.dtype[Any]],
+    NpArrayPydanticAnnotation.factory(data_type=None, dimensions=2, strict_data_typing=False),
+]
+
+Np2DArrayInt64: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.int64]],
     NpArrayPydanticAnnotation.factory(data_type=np.int64, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayInt32 = Annotated[
+Np2DArrayInt32: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.int32]],
     NpArrayPydanticAnnotation.factory(data_type=np.int32, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayInt16 = Annotated[
+Np2DArrayInt16: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.int16]],
     NpArrayPydanticAnnotation.factory(data_type=np.int16, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayInt8 = Annotated[
+Np2DArrayInt8: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.int8]],
     NpArrayPydanticAnnotation.factory(data_type=np.int8, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayUint64 = Annotated[
+Np2DArrayUint64: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.uint64]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint64, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayUint32 = Annotated[
+Np2DArrayUint32: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.uint32]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint32, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayUint16 = Annotated[
+Np2DArrayUint16: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.uint16]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint16, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayUint8 = Annotated[
+Np2DArrayUint8: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.uint8]],
     NpArrayPydanticAnnotation.factory(data_type=np.uint8, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayFpLongDouble = Annotated[
+Np2DArrayFpLongDouble: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.longdouble]],
     NpArrayPydanticAnnotation.factory(data_type=np.longdouble, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayFp64 = Annotated[
+Np2DArrayFp64: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.float64]],
     NpArrayPydanticAnnotation.factory(data_type=np.float64, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayFp32 = Annotated[
+Np2DArrayFp32: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.float32]],
     NpArrayPydanticAnnotation.factory(data_type=np.float32, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayFp16 = Annotated[
+Np2DArrayFp16: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.float16]],
     NpArrayPydanticAnnotation.factory(data_type=np.float16, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayComplexLongDouble = Annotated[
+Np2DArrayComplexLongDouble: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.clongdouble]],
     NpArrayPydanticAnnotation.factory(data_type=np.clongdouble, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayComplex128 = Annotated[
+Np2DArrayComplex128: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.complex128]],
     NpArrayPydanticAnnotation.factory(data_type=np.complex128, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayComplex64 = Annotated[
+Np2DArrayComplex64: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.complex64]],
     NpArrayPydanticAnnotation.factory(data_type=np.complex64, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayBool = Annotated[
+Np2DArrayBool: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.bool_]],
     NpArrayPydanticAnnotation.factory(data_type=np.bool_, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayDatetime64 = Annotated[
+Np2DArrayDatetime64: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.datetime64]],
     NpArrayPydanticAnnotation.factory(data_type=np.datetime64, dimensions=2, strict_data_typing=True),
 ]
 
-NpStrict2DArrayTimedelta64 = Annotated[
+Np2DArrayTimedelta64: TypeAlias = Annotated[
     np.ndarray[tuple[int, int], np.dtype[np.timedelta64]],
     NpArrayPydanticAnnotation.factory(data_type=np.timedelta64, dimensions=2, strict_data_typing=True),
 ]
 
 __all__ = [
-    "NpStrict2DArrayInt64",
-    "NpStrict2DArrayInt32",
-    "NpStrict2DArrayInt16",
-    "NpStrict2DArrayInt8",
-    "NpStrict2DArrayUint64",
-    "NpStrict2DArrayUint32",
-    "NpStrict2DArrayUint16",
-    "NpStrict2DArrayUint8",
-    "NpStrict2DArrayFpLongDouble",
-    "NpStrict2DArrayFp64",
-    "NpStrict2DArrayFp32",
-    "NpStrict2DArrayFp16",
-    "NpStrict2DArrayComplexLongDouble",
-    "NpStrict2DArrayComplex128",
-    "NpStrict2DArrayComplex64",
-    "NpStrict2DArrayBool",
-    "NpStrict2DArrayDatetime64",
-    "NpStrict2DArrayTimedelta64",
+    "Np2DArray",
+    "Np2DArrayInt64",
+    "Np2DArrayInt32",
+    "Np2DArrayInt16",
+    "Np2DArrayInt8",
+    "Np2DArrayUint64",
+    "Np2DArrayUint32",
+    "Np2DArrayUint16",
+    "Np2DArrayUint8",
+    "Np2DArrayFpLongDouble",
+    "Np2DArrayFp64",
+    "Np2DArrayFp32",
+    "Np2DArrayFp16",
+    "Np2DArrayComplexLongDouble",
+    "Np2DArrayComplex128",
+    "Np2DArrayComplex64",
+    "Np2DArrayBool",
+    "Np2DArrayDatetime64",
+    "Np2DArrayTimedelta64",
 ]