Dataset plot issue (multiprocessing)

[jramhani]

I rebuilded the docker, and cloned a fresh new packingBox .. now i get this error (with multiprocessing again, weirdly)

$ dataset plot features upx_bl1 number_wx_sections
/home/user/.local/lib/python3.12/site-packages/_distutils_hack/__init__.py:55: UserWarning: Reliance on distutils from stdlib is deprecated. Users must rely on setuptools to provide the distutils module. Avoid importing distutils or import setuptools first, and avoid setting SETUPTOOLS_USE_DISTUTILS=stdlib. Register concerns at https://github.com/pypa/setuptools/issues/new?template=distutils-deprecation.yml
  warnings.warn(
00:00:01.329 [INFO] Computing features...
  1% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━   6/588 samples • 0:00:00 • 0:00:55 • upx_bl1
Traceback (most recent call last):
  File "/home/user/.opt/tools/dataset", line 215, in <module>
    getattr(ds, args.command)(**vars(args))
  File "/home/user/.local/lib/python3.12/site-packages/pbox/core/dataset/__init__.py", line 682, in plot
    self._compute_all_features(**kw)
  File "/home/user/.local/lib/python3.12/site-packages/pbox/core/dataset/__init__.py", line 173, in _compute_all_features
    for basename, features in p.track(pool.imap_unordered(self._compute_features_worker, self),
  File "/home/user/.local/lib/python3.12/site-packages/pbox/helpers/rendering.py", line 10, in track
    for value in (sequence if silent else super(CustomProgress, self).track(sequence, *args, **kwargs)):
  File "/home/user/.local/lib/python3.12/site-packages/rich/progress.py", line 1209, in track
    for value in sequence:
  File "/usr/lib/python3.12/multiprocessing/pool.py", line 873, in next
    raise value
TypeError: void() takes at least 1 positional argument (0 given)

It might be in the Dataset class :

pbox/core/dataset/__init__.py

def _compute_all_features(self, n_jobs=None, **kw):
        """ Convenience function for computing the self._data pandas.DataFrame containing the feature values. """
        if self._files:
            self.logger.info("Computing features...")
            from multiprocessing import Pool
            with Pool(processes=n_jobs or config['number_jobs']) as pool:
                with progress_bar(target=self.basename) as p:
                    for basename, features in p.track(pool.imap_unordered(self._compute_features_worker, self),
                                                      total=len(self)):
                        self[basename] = (features, True)  # True: force updating the row