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# numpy.savez_compressed

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

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

  If keyword arguments are given, then filenames are taken from the keywords. If arguments are passed in with no keywords, then stored file names are arr_0, arr_1, etc.

  Parameters: | file : str or file Either the file name (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 file name if it is not already there. args : Arguments, optional Arrays to save to the file. Since it is not possible for Python to know the names of the arrays outside `savez`, the arrays will be saved with names “arr_0”, “arr_1”, and so on. These arguments can be any expression. kwds : Keyword arguments, optional Arrays to save to the file. Arrays will be saved in the file with the keyword names.
  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` or the NumPy Enhancement Proposal http://docs.scipy.org/doc/numpy/neps/npy-format.html

  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