Function read_feather

python/pyarrow/feather.py:198–227

Read a pandas.DataFrame from Feather format. To read as pyarrow.Table use feather.read_table. Parameters ---------- source : str file path, or file-like object You can use MemoryMappedFile as source, for explicitly use memory map. columns : sequence, optional

(source, columns=None, use_threads=True,
                 memory_map=False, **kwargs)

def read_feather(source, columns=None, use_threads=True,
                 memory_map=False, **kwargs):
    """
    Read a pandas.DataFrame from Feather format. To read as pyarrow.Table use
    feather.read_table.

    Parameters
    ----------
    source : str file path, or file-like object
        You can use MemoryMappedFile as source, for explicitly use memory map.
    columns : sequence, optional
        Only read a specific set of columns. If not provided, all columns are
        read.
    use_threads : bool, default True
        Whether to parallelize reading using multiple threads. If false the
        restriction is used in the conversion to Pandas as well as in the
        reading from Feather format.
    memory_map : boolean, default False
        Use memory mapping when opening file on disk, when source is a str.
    **kwargs
        Additional keyword arguments passed on to `pyarrow.Table.to_pandas`.

    Returns
    -------
    df : pandas.DataFrame
        The contents of the Feather file as a pandas.DataFrame
    """
    return (read_table(
        source, columns=columns, memory_map=memory_map,
        use_threads=use_threads).to_pandas(use_threads=use_threads, **kwargs))


def read_table(source, columns=None, memory_map=False, use_threads=True):