油烟在线监测数据爬取
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2023-10-12 ed135d79df12a2466b52dae1a82326941211dcc9 
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    A type representing `numpy.number` precision during static type checking.


 


    Used exclusively for the purpose static type checking, `NBitBase`


    represents the base of a hierarchical set of subclasses.


    Each subsequent subclass is herein used for representing a lower level


    of precision, *e.g.* ``64Bit > 32Bit > 16Bit``.


 


    .. versionadded:: 1.20


 


    Examples


    --------


    Below is a typical usage example: `NBitBase` is herein used for annotating


    a function that takes a float and integer of arbitrary precision


    as arguments and returns a new float of whichever precision is largest


    (*e.g.* ``np.float16 + np.int64 -> np.float64``).


 


    .. code-block:: python


 


        >>> from __future__ import annotations


        >>> from typing import TypeVar, TYPE_CHECKING


        >>> import numpy as np


        >>> import numpy.typing as npt


 


        >>> T1 = TypeVar("T1", bound=npt.NBitBase)


        >>> T2 = TypeVar("T2", bound=npt.NBitBase)


 


        >>> def add(a: np.floating[T1], b: np.integer[T2]) -> np.floating[T1 | T2]:


        ...     return a + b


 


        >>> a = np.float16()


        >>> b = np.int64()


        >>> out = add(a, b)


 


        >>> if TYPE_CHECKING:


        ...     reveal_locals()


        ...     # note: Revealed local types are:


        ...     # note:     a: numpy.floating[numpy.typing._16Bit*]


        ...     # note:     b: numpy.signedinteger[numpy.typing._64Bit*]


        ...     # note:     out: numpy.floating[numpy.typing._64Bit*]


 


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