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LICENSE.txt
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__config__.py
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__init__.cython-30.pxd
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__init__.pxd
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__init__.py
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__init__.pyi
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__pycache__
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_distributor_init.py
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_globals.py
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conftest.py
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core
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ctypeslib.py
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ctypeslib.pyi
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distutils
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doc
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dtypes.py
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dtypes.pyi
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exceptions.py
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exceptions.pyi
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f2py
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py.typed
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setup.py
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testing
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version.py
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Editing: dtypes.py
""" DType classes and utility (:mod:`numpy.dtypes`) =============================================== This module is home to specific dtypes related functionality and their classes. For more general information about dtypes, also see `numpy.dtype` and :ref:`arrays.dtypes`. Similar to the builtin ``types`` module, this submodule defines types (classes) that are not widely used directly. .. versionadded:: NumPy 1.25 The dtypes module is new in NumPy 1.25. Previously DType classes were only accessible indirectly. DType classes ------------- The following are the classes of the corresponding NumPy dtype instances and NumPy scalar types. The classes can be used in ``isinstance`` checks and can also be instantiated or used directly. Direct use of these classes is not typical, since their scalar counterparts (e.g. ``np.float64``) or strings like ``"float64"`` can be used. .. list-table:: :header-rows: 1 * - Group - DType class * - Boolean - ``BoolDType`` * - Bit-sized integers - ``Int8DType``, ``UInt8DType``, ``Int16DType``, ``UInt16DType``, ``Int32DType``, ``UInt32DType``, ``Int64DType``, ``UInt64DType`` * - C-named integers (may be aliases) - ``ByteDType``, ``UByteDType``, ``ShortDType``, ``UShortDType``, ``IntDType``, ``UIntDType``, ``LongDType``, ``ULongDType``, ``LongLongDType``, ``ULongLongDType`` * - Floating point - ``Float16DType``, ``Float32DType``, ``Float64DType``, ``LongDoubleDType`` * - Complex - ``Complex64DType``, ``Complex128DType``, ``CLongDoubleDType`` * - Strings - ``BytesDType``, ``BytesDType`` * - Times - ``DateTime64DType``, ``TimeDelta64DType`` * - Others - ``ObjectDType``, ``VoidDType`` """ __all__ = [] def _add_dtype_helper(DType, alias): # Function to add DTypes a bit more conveniently without channeling them # through `numpy.core._multiarray_umath` namespace or similar. from numpy import dtypes setattr(dtypes, DType.__name__, DType) __all__.append(DType.__name__) if alias: alias = alias.removeprefix("numpy.dtypes.") setattr(dtypes, alias, DType) __all__.append(alias)
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