Update dependency joblib to ~=1.4.2

[renovate]

This PR contains the following updates:

Package	Change	Age	Adoption	Passing	Confidence
joblib	~=1.0.1 -> ~=1.4.2

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Release Notes

joblib/joblib (joblib)

v1.4.2

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Due to maintenance issues, 1.4.1 was not valid and we bumped the version to 1.4.2

• Fix a backward incompatible change in MemorizedFunc.call which needs to
  return the metadata. Also make sure that NotMemorizedFunc.call return
  an empty dict for metadata for consistenhttps://github.com/joblib/joblib/pull/1576ull/1576

v1.4.0

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• Allow caching co-routines with Memory.cache.
  https://github.com/joblib/joblib/pull/894/894

• Try to cast n_jobs to int in parallel and raise an error if
  it fails. This means that n_jobs=2.3 will now result in
  effective_n_jobs=2 instead of failing.
  https://github.com/joblib/joblib/pull/15391539

• Ensure that errors in the task generator given to Parallel's call
  are raised in the results consumming threhttps://github.com/joblib/joblib/pull/1491ull/1491

• Adjust codebase to NumPy 2.0 by changing np.NaN to np.nan
  and importing byte_bounds from np.lib.array_utils.
  https://github.com/joblib/joblib/pull/15011501

• The parameter return_as in joblib.Parallel can now be set to
  generator_unordered. In this case the results will be returned in the
  order of task completion rather than the order of submissihttps://github.com/joblib/joblib/pull/1463ull/1463

• dask backend now supports return_as=generator and
  return_as=generator_unordered.
  https://github.com/joblib/joblib/pull/15201520

• Vendor cloudpickle 3.0.0 and end support for Python 3.7 which has
  reached end of lihttps://github.com/joblib/joblib/pull/1487uhttps://github.com/joblib/joblib/pull/1515ib/pull/1515

v1.3.2

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• Fix a regression in joblib.Parallel introduced in 1.3.0 where
  explicitly setting n_jobs=None was not interpreted as "unset".
  https://github.com/joblib/joblib/pull/14751475

• Fix a regression in joblib.Parallel introduced in 1.3.0 where
  joblib.Parallel logging methods exposed from inheritance to
  joblib.Logger didn't work because of missing logger
  initializatihttps://github.com/joblib/joblib/pull/1494ull/1494

• Various maintenance updates to the doc, the ci and the test.
  https://github.com/joblib/joblib/pull/148014https://github.com/joblib/joblib/pull/1481ulhttps://github.com/joblib/joblib/pull/1476ibhttps://github.com/joblib/joblib/pull/1492joblib/pull/1492

v1.3.1

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• Fix compatibility with python 3.7 by vendor loky 3.4.1
  which is compatible with this versihttps://github.com/joblib/joblib/pull/1472ull/1472

v1.3.0

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• Ensure native byte order for memmap arrays in joblib.load.
  https://github.com/joblib/joblib/issues/13531353

• Add ability to change default Parallel backend in tests by setting the
  JOBLIB_TESTS_DEFAULT_PARALLEL_BACKEND environment variable.
  https://github.com/joblib/joblib/pull/13561356

• Fix temporary folder creation in joblib.Parallel on Linux subsystems on Windows
  which do have /dev/shm but don't have the os.statvfs function
  https://github.com/joblib/joblib/issues/13531353

• Drop runtime dependency on distutils. distutils is going away
  in Python 3.12 and is deprecated from Python 3.10 onwards. This import
  was kept around to avoid breaking scikit-learn, however it's now been
  long enough since scikit-learn deployed a fixed (version 1.1 was released
  in May 2022) that it should be safe https://github.com/joblib/joblib/pull/1361lib/joblib/pull/1361

• A warning is raised when a pickling error occurs during caching operations.
  In version 1.5, this warning will be turned into an error. For all other
  errors, a new warning has been introduced: joblib.memory.CacheWarning.
  https://github.com/joblib/joblib/pull/13591359

• Avoid (module, name) collisions when caching nested functions. This fix
  changes the module name of nested functions, invalidating caches from
  previous versions of https://github.com/joblib/joblib/pull/1374ib/pull/1374

• Add cache_validation_callback in :meth:joblib.Memory.cache, to allow
  custom cache invalidation based on the metadata of the function cahttps://github.com/joblib/joblib/pull/1149ull/1149

• Add a return_as parameter for Parallel, that enables consuming
  results asynchronoushttps://github.com/joblib/joblib/pull/1393ulhttps://github.com/joblib/joblib/pull/1458ib/pull/1458

• Improve the behavior of joblib for n_jobs=1, with simplified
  tracebacks and more efficient running tihttps://github.com/joblib/joblib/pull/1393ull/1393

• Add the parallel_config context manager to allow for more fine-grained
  control over the backend configuration. It should be used in place of the
  parallel_backend context manager. In particular, it has the advantage
  of not requiring to set a specific backend in the context managhttps://github.com/joblib/joblib/pull/1392ulhttps://github.com/joblib/joblib/pull/1457ib/pull/1457

• Add items_limit and age_limit in :meth:joblib.Memory.reduce_size
  to make it easy to limit the number of items and remove items that have
  not been accessed for a long time in thehttps://github.com/joblib/joblib/pull/1200ib/pull/1200

• Deprecate bytes_limit in Memory as this is not automatically enforced,
  the limit can be directly passed to :meth:joblib.Memory.reduce_size which
  needs to be called to actually enforce the limhttps://github.com/joblib/joblib/pull/1447ull/1447

• Vendor loky 3.4.0 which includes various fixes.
  https://github.com/joblib/joblib/pull/14221422

• Various updates to the documentation and to benchmarking tools.
  https://github.com/joblib/joblib/pull/134313https://github.com/joblib/joblib/pull/1348ulhttps://github.com/joblib/joblib/pull/1411ibhttps://github.com/joblib/joblib/pull/1451johttps://github.com/joblib/joblib/pull/1427lihttps://github.com/joblib/joblib/pull/1400/BENCH add benchmark script for n_jobs=1 joblib/joblib#1400

• Move project metadata to pyproject.toml.
  https://github.com/joblib/joblib/pull/138213https://github.com/joblib/joblib/pull/1433ull/1433

• Add more tests to improve python nogil support.
  https://github.com/joblib/joblib/pull/139413https://github.com/joblib/joblib/pull/1395ull/1395

v1.2.0

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• Fix a security issue where eval(pre_dispatch) could potentially run
  arbitrary code. Now only basic numerics are supporthttps://github.com/joblib/joblib/pull/1327ull/1327

• Make sure that joblib works even when multiprocessing is not available,
  for instance with Pyodhttps://github.com/joblib/joblib/pull/1256ull/1256

• Avoid unnecessary warnings when workers and main process delete
  the temporary memmap folder contents concurrenthttps://github.com/joblib/joblib/pull/1263ull/1263

• Fix memory alignment bug for pickles containing numpy arrays.
  This is especially important when loading the pickle with
  mmap_mode != None as the resulting numpy.memmap object
  would not be able to correct the misalignment without performing
  a memory copy.
  This bug would cause invalid computation and segmentation faults
  with native code that would directly access the underlying data
  buffer of a numpy array, for instance C/C++/Cython code compiled
  with older GCC versions or some old OpenBLAS written in plathttps://github.com/joblib/joblib/pull/1254thub.com/Make sure arrays are bytes aligned in joblib pickles joblib/joblib#1254

• Vendor cloudpickle 2.2.0 which adds support for PyPy 3.8+.

• Vendor loky 3.3.0 which fixes several bugs including:

  • robustly forcibly terminating worker processes in case of a crash
    https://github.com/joblib/joblib/pull/1269ull/1269);

  • avoiding leaking worker processes in case of nested loky parallel
    calls;

  • reliability spawn the correct number of reusable workers.

v1.1.1

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• Fix a security issue where eval(pre_dispatch) could potentially run
  arbitrary code. Now only basic numerics are supporthttps://github.com/joblib/joblib/pull/1327ull/1327

v1.1.0

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• Fix byte order inconsistency issue during deserialization using joblib.load
  in cross-endian environment: the numpy arrays are now always loaded to
  use the system byte order, independently of the byte order of the system
  that serialized https://github.com/joblib/joblib/pull/1181joblib/pull/1181

• Fix joblib.Memory bug with the ignore parameter when the cached function
  is a decorated functihttps://github.com/joblib/joblib/pull/1165ull/1165

• Fix joblib.Memory to properly handle caching for functions defined
  interactively in a IPython session or in Jupyter notebook cehttps://github.com/joblib/joblib/pull/1214ull/1214

• Update vendored loky (from version 2.9 to 3.0) and cloudpickle (from
  version 1.6 to 2https://github.com/joblib/joblib/pull/1218ull/1218

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