shared.py 文件源码

def array(shape, dtype=_np.float64, autolock=False):
    """Factory method for shared memory arrays supporting all numpy dtypes."""
    assert _NP_AVAILABLE, (
        "To use the shared array object, numpy must be available!")
    if not isinstance(dtype, _np.dtype):
        dtype = _np.dtype(dtype)
    # Not bothering to translate the numpy dtypes to ctype types directly,
    # because they're only partially supported. Instead, create a byte ctypes
    # array of the right size and use a view of the appropriate datatype.
    shared_arr = _multiprocessing.Array(
        'b', int(_np.prod(shape) * dtype.alignment), lock=autolock)
    with _warnings.catch_warnings():
        # For more information on why this is necessary, see
        # https://www.reddit.com/r/Python/comments/j3qjb/parformatlabpool_replacement
        _warnings.simplefilter('ignore', RuntimeWarning)
        data = _np.ctypeslib.as_array(shared_arr).view(dtype).reshape(shape)
    return data