# numpy.savez_compressed

numpy.savez_compressed(file, *args, **kwds)

  Save several arrays into a single file in compressed `.npz` format.

  Provide arrays as keyword arguments to store them under the corresponding name in the output file: `savez(fn, x=x, y=y)`.

  If arrays are specified as positional arguments, i.e., `savez(fn, x, y)`, their names will be arr_0, arr_1, etc.

  Parameters:
    file str or file

      Either the filename (string) or an open file (file-like object) where the data will be saved. If file is a string or a Path, the `.npz` extension will be appended to the filename if it is not already there.

    args Arguments, optional

      Arrays to save to the file. Please use keyword arguments (see kwds below) to assign names to arrays. Arrays specified as args will be named “arr_0”, “arr_1”, and so on.

    kwds Keyword arguments, optional

      Arrays to save to the file. Each array will be saved to the output file with its corresponding keyword name.

  Returns:
    None

  See also

  `numpy.save`

    Save a single array to a binary file in NumPy format.

  `numpy.savetxt`

    Save an array to a file as plain text.

  `numpy.savez`

    Save several arrays into an uncompressed `.npz` file format

  `numpy.load`

    Load the files created by savez_compressed.

  Notes

  The `.npz` file format is a zipped archive of files named after the variables they contain. The archive is compressed with `zipfile.ZIP_DEFLATED` and each file in the archive contains one variable in `.npy` format. For a description of the `.npy` format, see `numpy.lib.format`.

  When opening the saved `.npz` file with `load` a NpzFile object is returned. This is a dictionary-like object which can be queried for its list of arrays (with the `.files` attribute), and for the arrays themselves.

  Examples

      >>> test_array = np.random.rand(3, 2)
      >>> test_vector = np.random.rand(4)
      >>> np.savez_compressed('/tmp/123', a=test_array, b=test_vector)
      >>> loaded = np.load('/tmp/123.npz')
      >>> print(np.array_equal(test_array, loaded['a']))
      True
      >>> print(np.array_equal(test_vector, loaded['b']))
      True