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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def days_and_sids_for_frames(frames):
 """ Returns the date index and sid columns shared by a list of dataframes, ensuring they all match. Parameters frames : list[pd.DataFrame] A list of dataframes indexed by day, with a column per sid. Returns ------- days : np.array[datetime64[ns]] The days in these dataframes. sids : np.array[int64] The sids in these dataframes. Raises ------ ValueError If the dataframes passed are not all indexed by the same days and sids. """

    if not frames:
        days = np.array([], dtype='datetime64[ns]')
        sids = np.array([], dtype='int64')
        return days, sids

    # Ensure the indices and columns all match.
    check_indexes_all_same(
        [frame.index for frame in frames],
        message='Frames have mistmatched days.',
    )
    check_indexes_all_same(
        [frame.columns for frame in frames],
        message='Frames have mismatched sids.',
    )

    return frames[0].index.values, frames[0].columns.values