CODEWITHSUNDEEP
pythonpython-3.xnumpylow-memory
abukaj
abukaj

Reputation: 2712

How can I save a big `numpy` as '*.npz' array with limited filesystem capacity?

I have a numpy array which saved as an uncompressed '*npz' file is about 26 GiB as it is numpy.float32 and numpy.savez() ends with:

OSError: Failed to write to /tmp/tmpl9v3xsmf-numpy.npy: 6998400000 requested and 3456146404 written

I suppose saving it compressed may save the day, but with numpy.savez_compressed() I have also:

OSError: Failed to write to /tmp/tmp591cum2r-numpy.npy: 6998400000 requested and 3456157668 written

as numpy.savez_compressed() saves the array uncompressed first.

The obvious "use additional storage" I do not consider an answer. ;)

[EDIT]

The tag low-memory refers to disk memory, not RAM.

Upvotes: 0

Views: 5359

Answers (2)

Charles Duffy
Charles Duffy

Reputation: 295363

With the addition of ZipFile.open(..., mode='w') in Python 3.6, you can do better:

import numpy as np
import zipfile
import io

def saveCompressed(fh, **namedict):
     with zipfile.ZipFile(fh, mode="w", compression=zipfile.ZIP_DEFLATED,
                          allowZip64=True) as zf:
         for k, v in namedict.items():
             with zf.open(k + '.npy', 'w', force_zip64=True) as buf:
                 np.lib.npyio.format.write_array(buf,
                                                 np.asanyarray(v),
                                                 allow_pickle=False)

Upvotes: 1

abukaj
abukaj

Reputation: 2712

Note: I would be more than happy to accept a more RAM-efficient solution.

I have browsed the numpy.savez_compressed() code and decided to reimplement part of its functionality:

import numpy as np
import zipfile
import io

def saveCompressed(fh, **namedict):
     with zipfile.ZipFile(fh,
                          mode="w",
                          compression=zipfile.ZIP_DEFLATED,
                          allowZip64=True) as zf:
         for k, v in namedict.items():
             buf = io.BytesIO()
             np.lib.npyio.format.write_array(buf,
                                             np.asanyarray(v),
                                             allow_pickle=False)
             zf.writestr(k + '.npy',
                         buf.getvalue())

It causes my system to swap, but at least I am able to store my data (sham data used in the example):

>>> A = np.ones(12 * 6 * 6 * 1 * 6 * 6 * 10000* 5* 9, dtype=np.float32)
>>> saveCompressed(open('test.npz', 'wb'), A=A)
>>> A = np.load('test.npz')['A']
>>> A.shape
(6998400000,)
>>> (A == 1).all()
True

Upvotes: 1

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