Load pickled pandas object (or any object) from file.

    .. warning::

       Loading pickled data received from untrusted sources can be
       unsafe. See `here <https://docs.python.org/3/library/pickle.html>`__.

    Parameters
    ----------
    path : str
        File path where the pickled object will be loaded.
    compression : {'infer', 'gzip', 'bz2', 'zip', 'xz', None}, default 'infer'
        For on-the-fly decompression of on-disk data. If 'infer', then use
        gzip, bz2, xz or zip if path ends in '.gz', '.bz2', '.xz',
        or '.zip' respectively, and no decompression otherwise.
        Set to None for no decompression.

        .. versionadded:: 0.20.0

    Returns
    -------
    unpickled : same type as object stored in file

    See Also
    --------
    DataFrame.to_pickle : Pickle (serialize) DataFrame object to file.
    Series.to_pickle : Pickle (serialize) Series object to file.
    read_hdf : Read HDF5 file into a DataFrame.
    read_sql : Read SQL query or database table into a DataFrame.
    read_parquet : Load a parquet object, returning a DataFrame.

    Examples
    --------
    >>> original_df = pd.DataFrame({"foo": range(5), "bar": range(5, 10)})
    >>> original_df
       foo  bar
    0    0    5
    1    1    6
    2    2    7
    3    3    8
    4    4    9
    >>> pd.to_pickle(original_df, "./dummy.pkl")

    >>> unpickled_df = pd.read_pickle("./dummy.pkl")
    >>> unpickled_df
       foo  bar
    0    0    5
    1    1    6
    2    2    7
    3    3    8
    4    4    9

    >>> import os
    >>> os.remove("./dummy.pkl")

def read_pickle(path, compression='infer'):
    """
    Load pickled pandas object (or any object) from file.

    .. warning::

       Loading pickled data received from untrusted sources can be
       unsafe. See `here <https://docs.python.org/3/library/pickle.html>`__.

    Parameters
    ----------
    path : str
        File path where the pickled object will be loaded.
    compression : {'infer', 'gzip', 'bz2', 'zip', 'xz', None}, default 'infer'
        For on-the-fly decompression of on-disk data. If 'infer', then use
        gzip, bz2, xz or zip if path ends in '.gz', '.bz2', '.xz',
        or '.zip' respectively, and no decompression otherwise.
        Set to None for no decompression.

        .. versionadded:: 0.20.0

    Returns
    -------
    unpickled : same type as object stored in file

    See Also
    --------
    DataFrame.to_pickle : Pickle (serialize) DataFrame object to file.
    Series.to_pickle : Pickle (serialize) Series object to file.
    read_hdf : Read HDF5 file into a DataFrame.
    read_sql : Read SQL query or database table into a DataFrame.
    read_parquet : Load a parquet object, returning a DataFrame.

    Examples
    --------
    >>> original_df = pd.DataFrame({"foo": range(5), "bar": range(5, 10)})
    >>> original_df
       foo  bar
    0    0    5
    1    1    6
    2    2    7
    3    3    8
    4    4    9
    >>> pd.to_pickle(original_df, "./dummy.pkl")

    >>> unpickled_df = pd.read_pickle("./dummy.pkl")
    >>> unpickled_df
       foo  bar
    0    0    5
    1    1    6
    2    2    7
    3    3    8
    4    4    9

    >>> import os
    >>> os.remove("./dummy.pkl")
    """
    path = _stringify_path(path)
    f, fh = _get_handle(path, 'rb', compression=compression, is_text=False)

    # 1) try standard libary Pickle
    # 2) try pickle_compat (older pandas version) to handle subclass changes
    # 3) try pickle_compat with latin1 encoding

    try:
        with warnings.catch_warnings(record=True):
            # We want to silence any warnings about, e.g. moved modules.
            warnings.simplefilter("ignore", Warning)
            return pickle.load(f)
    except Exception:  # noqa: E722
        try:
            return pc.load(f, encoding=None)
        except Exception:  # noqa: E722
            return pc.load(f, encoding='latin1')
    finally:
        f.close()
        for _f in fh:
            _f.close()