numpy/numpy · error · ValueError

mode must be one of {all_modes!r} (got {mode!r})

Error message

mode must be one of {all_modes!r} (got {mode!r})

What it means

Error "mode must be one of {all_modes!r} (got {mode!r})" thrown in numpy/numpy.

Source

Thrown at numpy/_core/memmap.py:225

    >>> fpo = np.memmap(filename, dtype=np.float32, mode='r', offset=16)
    >>> fpo
    memmap([  4.,   5.,   6.,   7.,   8.,   9.,  10.,  11.], dtype=float32)

    """

    __array_priority__ = -100.0

    def __new__(cls, filename, dtype=uint8, mode='r+', offset=0,
                shape=None, order='C'):
        # Import here to minimize 'import numpy' overhead
        import mmap
        import os.path
        try:
            mode = mode_equivalents[mode]
        except KeyError as e:
            if mode not in valid_filemodes:
                all_modes = valid_filemodes + list(mode_equivalents.keys())
                raise ValueError(
                    f"mode must be one of {all_modes!r} (got {mode!r})"
                ) from None

        if mode == 'w+' and shape is None:
            raise ValueError("shape must be given if mode == 'w+'")

        if hasattr(filename, 'read'):
            f_ctx = nullcontext(filename)
        else:
            f_ctx = open(
                os.fspath(filename),
                ('r' if mode == 'c' else mode) + 'b'
            )

        with f_ctx as fid:
            fid.seek(0, 2)
            flen = fid.tell()
            descr = dtypedescr(dtype)

View on GitHub (pinned to e117b3ca4e)

Solutions

1. Use one of the valid modes: 'r', 'r+', 'w+', or 'c', e.g. np.memmap('f.dat', dtype='float64', mode='r', shape=(3,4)).

When it happens

Trigger: Passing an invalid mode string such as 'w' or 'a' to np.memmap.

Common situations: Assuming memmap accepts built-in open() modes like 'w' or 'rb'.

AI-assisted analysis of numpy/numpy@e117b3ca4e (2026-08-07). Data as JSON: /api/errors/1d1e9da4bc559577. Report an issue: GitHub.