Class HDFStore

pandas/io/pytables.py:497–2018

Dict-like IO interface for storing pandas objects in PyTables. Either Fixed or Table format. .. warning:: Pandas uses PyTables for reading and writing HDF5 files, which allows serializing object-dtype data with pickle when using the "fixed" format. Loading pickle

@set_module("pandas")
class HDFStore:
    """
    Dict-like IO interface for storing pandas objects in PyTables.

    Either Fixed or Table format.

    .. warning::

       Pandas uses PyTables for reading and writing HDF5 files, which allows
       serializing object-dtype data with pickle when using the "fixed" format.
       Loading pickled data received from untrusted sources can be unsafe.

       See: https://docs.python.org/3/library/pickle.html for more.

    Parameters
    ----------
    path : str
        File path to HDF5 file.
    mode : {'a', 'w', 'r', 'r+'}, default 'a'

        ``'r'``
            Read-only; no data can be modified.
        ``'w'``
            Write; a new file is created (an existing file with the same
            name would be deleted).
        ``'a'``
            Append; an existing file is opened for reading and writing,
            and if the file does not exist it is created.
        ``'r+'``
            It is similar to ``'a'``, but the file must already exist.
    complevel : int, 0-9, default None
        Specifies a compression level for data.
        A value of 0 or None disables compression.
    complib : {'zlib', 'lzo', 'bzip2', 'blosc'}, default 'zlib'
        Specifies the compression library to be used.
        These additional compressors for Blosc are supported
        (default if no compressor specified: 'blosc:blosclz'):
        {'blosc:blosclz', 'blosc:lz4', 'blosc:lz4hc', 'blosc:snappy',
         'blosc:zlib', 'blosc:zstd'}.
        Specifying a compression library which is not available issues
        a ValueError.
    fletcher32 : bool, default False
        If applying compression use the fletcher32 checksum.
    **kwargs
        These parameters will be passed to the PyTables open_file method.

    Examples
    --------
    >>> bar = pd.DataFrame(np.random.randn(10, 4))
    >>> store = pd.HDFStore("test.h5")
    >>> store["foo"] = bar  # write to HDF5
    >>> bar = store["foo"]  # retrieve
    >>> store.close()

    **Create or load HDF5 file in-memory**

    When passing the `driver` option to the PyTables open_file method through
    **kwargs, the HDF5 file is loaded or created in-memory and will only be