- numpy.savez(file, *args, **kwds)¶
Save several arrays into a single file in uncompressed .npz format.
If arguments are passed in with no keywords, the corresponding variable names, in the .npz file, are ‘arr_0’, ‘arr_1’, etc. If keyword arguments are given, the corresponding variable names, in the .npz file will match the keyword names.
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, 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.
The .npz file format is a zipped archive of files named after the variables they contain. The archive is not compressed 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.
>>> from tempfile import TemporaryFile >>> outfile = TemporaryFile() >>> x = np.arange(10) >>> y = np.sin(x)
Using savez with *args, the arrays are saved with default names.
>>> np.savez(outfile, x, y) >>> outfile.seek(0) # Only needed here to simulate closing & reopening file >>> npzfile = np.load(outfile) >>> npzfile.files ['arr_1', 'arr_0'] >>> npzfile['arr_0'] array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
Using savez with **kwds, the arrays are saved with the keyword names.
>>> outfile = TemporaryFile() >>> np.savez(outfile, x=x, y=y) >>> outfile.seek(0) >>> npzfile = np.load(outfile) >>> npzfile.files ['y', 'x'] >>> npzfile['x'] array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])