update old numpy dtypes, remove them, lint

pyproject.toml

@@ -101,6 +101,10 @@ select = [
     "I",
     # annotations
     "ANN",
+    # perf
+    "PERF",
+    # numpy
+    "NPY",
     ## ----------
     # pydocstyle
     # undocumented public objects

src/numpydantic/dtype.py

@@ -69,9 +69,7 @@ Half = np.half
 Single = np.single
 Double = np.double
 LongDouble = np.longdouble
-LongFloat = np.longfloat
 Float = (
-    np.float_,
     np.float16,
     np.float32,
     np.float64,
@@ -84,32 +82,24 @@ ComplexFloating = np.complexfloating
 Complex64 = np.complex64
 Complex128 = np.complex128
 CSingle = np.csingle
-SingleComplex = np.singlecomplex
 CDouble = np.cdouble
-CFloat = np.cfloat
 CLongDouble = np.clongdouble
-CLongFloat = np.clongfloat
 Complex = (
-    np.complex_,
     np.complexfloating,
     np.complex64,
     np.complex128,
     np.csingle,
-    np.singlecomplex,
     np.cdouble,
-    np.cfloat,
     np.clongdouble,
-    np.clongfloat,
 )
 
-LongComplex = np.longcomplex
 Flexible = np.flexible
 Void = np.void
 Character = np.character
 Bytes = np.bytes_
 Str = np.str_
-String = np.string_
+String = np.str_
-Unicode = np.unicode_
+Unicode = np.str_
 
 Number = tuple(
     [

src/numpydantic/interface/video.py

@@ -144,9 +144,9 @@ class VideoProxy:
         elif isinstance(item, slice):
             # slice of frames
             item = self._complete_slice(item)
-            frames = []
+            frames = [
-            for i in range(item.start, item.stop, item.step):
+                self._get_frame(i) for i in range(item.start, item.stop, item.step)
-                frames.append(self._get_frame(i))
+            ]
             return np.stack(frames)
         else:
             # slices are passed as tuples

src/numpydantic/maps.py

@@ -21,7 +21,7 @@ np_to_python = {
     **{n: int for n in dt.Integer},
     **{n: float for n in dt.Float},
     **{n: complex for n in dt.Complex},
-    **{n: str for n in (np.character, np.str_, np.string_, np.unicode_)},
+    **{n: str for n in (np.character, np.str_, np.bytes_, np.str_)},
 }
 """Map from python types to numpy"""
 

src/numpydantic/ndarray.py

@@ -16,14 +16,6 @@ Extension of nptyping NDArray for pydantic that allows for JSON-Schema serializa
 from typing import TYPE_CHECKING, Any, Tuple
 
 import numpy as np
-from numpydantic.vendor.nptyping.error import InvalidArgumentsError
-from numpydantic.vendor.nptyping.ndarray import NDArrayMeta as _NDArrayMeta
-from numpydantic.vendor.nptyping.nptyping_type import NPTypingType
-from numpydantic.vendor.nptyping.structure import Structure
-from numpydantic.vendor.nptyping.structure_expression import check_type_names
-from numpydantic.vendor.nptyping.typing_ import (
-    dtype_per_name,
-)
 from pydantic import GetJsonSchemaHandler
 from pydantic_core import core_schema
 
@@ -38,6 +30,14 @@ from numpydantic.schema import (
     make_json_schema,
 )
 from numpydantic.types import DtypeType, ShapeType
+from numpydantic.vendor.nptyping.error import InvalidArgumentsError
+from numpydantic.vendor.nptyping.ndarray import NDArrayMeta as _NDArrayMeta
+from numpydantic.vendor.nptyping.nptyping_type import NPTypingType
+from numpydantic.vendor.nptyping.structure import Structure
+from numpydantic.vendor.nptyping.structure_expression import check_type_names
+from numpydantic.vendor.nptyping.typing_ import (
+    dtype_per_name,
+)
 
 if TYPE_CHECKING:  # pragma: no cover
     from nptyping.base_meta_classes import SubscriptableMeta

src/numpydantic/schema.py

@@ -7,7 +7,6 @@ import hashlib
 import json
 from typing import TYPE_CHECKING, Any, Callable, Optional, Union
 
-from numpydantic.vendor.nptyping.structure import StructureMeta
 import numpy as np
 from pydantic import SerializationInfo
 from pydantic_core import CoreSchema, core_schema
@@ -17,6 +16,7 @@ from numpydantic import dtype as dt
 from numpydantic.interface import Interface
 from numpydantic.maps import np_to_python
 from numpydantic.types import DtypeType, NDArrayType, ShapeType
+from numpydantic.vendor.nptyping.structure import StructureMeta
 
 if TYPE_CHECKING:
     from numpydantic import Shape

src/numpydantic/types.py

@@ -8,7 +8,7 @@ Note that these are types as in python typing types, not classes.
 
 from typing import Any, Protocol, Tuple, Union, runtime_checkable
 
-from nptyping import DType
+from numpydantic.vendor.nptyping import DType
 
 ShapeType = Union[Tuple[int, ...], Any]
 DtypeType = Union[str, type, Any, DType]

src/numpydantic/vendor/nptyping/base_meta_classes.py

@@ -23,12 +23,11 @@ SOFTWARE.
 """
 
 from abc import ABCMeta, abstractmethod
-from inspect import FrameInfo, getframeinfo
+from inspect import getframeinfo
 from types import FrameType
 from typing import (
     Any,
     Dict,
-    List,
     Optional,
     Set,
     Tuple,

src/numpydantic/vendor/nptyping/ndarray.py

@@ -27,6 +27,7 @@ from abc import ABC
 from typing import Any, Tuple
 
 import numpy as np
+
 from numpydantic.vendor.nptyping.base_meta_classes import (
     FinalMeta,
     ImmutableMeta,

src/numpydantic/vendor/nptyping/pandas_/dataframe.py

@@ -27,6 +27,7 @@ from abc import ABC
 from typing import Any, Tuple
 
 import numpy as np
+
 from numpydantic.vendor.nptyping import InvalidArgumentsError
 from numpydantic.vendor.nptyping.base_meta_classes import (
     FinalMeta,

src/numpydantic/vendor/nptyping/structure_expression.py

@@ -38,6 +38,7 @@ from typing import (
 )
 
 import numpy as np
+
 from numpydantic.vendor.nptyping.error import InvalidShapeError, InvalidStructureError
 from numpydantic.vendor.nptyping.shape import Shape
 from numpydantic.vendor.nptyping.shape_expression import (

src/numpydantic/vendor/nptyping/typing_.py

@@ -22,7 +22,6 @@ OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 SOFTWARE.
 """
 
-
 from typing import (  # type: ignore[attr-defined,misc] # pylint: disable=unused-import
     Tuple,
     TypeAlias,
@@ -38,10 +37,8 @@ ShapeTuple: TypeAlias = Tuple[int, ...]
 
 Number = np.number
 Bool = np.bool_
-Bool8 = np.bool8
 Obj = np.object_  # Obj is a common abbreviation and should be usable.
 Object = np.object_
-Object0 = np.object0
 Datetime64 = np.datetime64
 Integer = np.integer
 SignedInteger = np.signedinteger
@@ -53,7 +50,6 @@ Byte = np.byte
 Short = np.short
 IntC = np.intc
 IntP = np.intp
-Int0 = np.int0
 Int = np.integer  # Int should translate to the "generic" int type.
 Int_ = np.int_
 LongLong = np.longlong
@@ -67,7 +63,6 @@ UByte = np.ubyte
 UShort = np.ushort
 UIntC = np.uintc
 UIntP = np.uintp
-UInt0 = np.uint0
 UInt = np.uint
 ULongLong = np.ulonglong
 Inexact = np.inexact
@@ -78,38 +73,33 @@ Float64 = np.float64
 Half = np.half
 Single = np.single
 Double = np.double
-Float = np.float_
+Float = np.float64
 LongDouble = np.longdouble
-LongFloat = np.longfloat
+LongFloat = np.longdouble
 ComplexFloating = np.complexfloating
 Complex64 = np.complex64
 Complex128 = np.complex128
 CSingle = np.csingle
-SingleComplex = np.singlecomplex
+SingleComplex = np.complex64
 CDouble = np.cdouble
-Complex = np.complex_
+Complex = np.complex128
-CFloat = np.cfloat
+CFloat = np.complex128
 CLongDouble = np.clongdouble
-CLongFloat = np.clongfloat
+CLongFloat = np.clongdouble
-LongComplex = np.longcomplex
+LongComplex = np.clongdouble
 Flexible = np.flexible
 Void = np.void
-Void0 = np.void0
 Character = np.character
 Bytes = np.bytes_
 Str = np.str_
-String = np.string_
+String = np.str_
-Bytes0 = np.bytes0
+Unicode = np.str_
-Unicode = np.unicode_
-Str0 = np.str0
 
 dtypes = [
     (Number, "Number"),
     (Bool, "Bool"),
-    (Bool8, "Bool8"),
     (Obj, "Obj"),
     (Object, "Object"),
-    (Object0, "Object0"),
     (Datetime64, "Datetime64"),
     (Integer, "Integer"),
     (SignedInteger, "SignedInteger"),
@@ -121,7 +111,6 @@ dtypes = [
     (Short, "Short"),
     (IntC, "IntC"),
     (IntP, "IntP"),
-    (Int0, "Int0"),
     (Int, "Int"),
     (LongLong, "LongLong"),
     (Timedelta64, "Timedelta64"),
@@ -134,7 +123,6 @@ dtypes = [
     (UShort, "UShort"),
     (UIntC, "UIntC"),
     (UIntP, "UIntP"),
-    (UInt0, "UInt0"),
     (UInt, "UInt"),
     (ULongLong, "ULongLong"),
     (Inexact, "Inexact"),
@@ -161,14 +149,11 @@ dtypes = [
     (LongComplex, "LongComplex"),
     (Flexible, "Flexible"),
     (Void, "Void"),
-    (Void0, "Void0"),
     (Character, "Character"),
     (Bytes, "Bytes"),
     (String, "String"),
     (Str, "Str"),
-    (Bytes0, "Bytes0"),
     (Unicode, "Unicode"),
-    (Str0, "Str0"),
 ]
 
 name_per_dtype = dict(dtypes)