Log message:
py-joblib: updated to 1.5.3

1.5.3

The Memory object won't overwrite an already existing .gitignore file in its \ 
cache directory anymore.
Harden the safety checks in eval_expr(pre_dispatch) to prevent excessive memory \ 
allocation and potential crashes by limiting the allowed length of the \ 
expression and the maximum numeric value of sub-expressions and not evaluating \ 
expressions with non-numeric literals.
Vendor cloudpickle 3.1.2 to fix a pickling problem with interactively defined \ 
abstract base classes and type annotations in Python 3.14+.

Log message:
py-joblib: updated to 1.5.2

1.5.2
Vendor loky3.5.6 fixing the resource tracker for python 3.13.7+

Log message:
py-joblib: updated to 1.5.1

1.5.1

Fix backend hints causing errors when no multiprocessing is present.
Vendor loky3.5.5 fixing the resource_tracker clean up with earlier Python versions.

Log message:
py-joblib: updated to 1.5.0

1.5.0

Memory:

Enforce age_limit is a positive timedelta for Memory.reduce_size, to avoid \ 
silently ignoring it.
Remove deprecated bytes_limit argument for Memory, which should be passed \ 
directly to Memory.reduce_size.
Extend functionality of the check_call_in_cache method to now also check against \ 
cache validity. Before, it would only check for a given call if it is in cache \ 
memory.
The Memory object now automatically creates a .gitignore file in its cache \ 
directory, instructing git to ignore the entire folder.

Parallel:

Fixed a bug that caused the timeout parameter in joblib.Parallel to be \ 
ineffective when used along with return_as='generator_unordered'.
Pretty printing of Parallel execution progress when the number of tasks is known.
Make it possible to pass extra arguments to the LokyBackend and \ 
MultiprocessingBackend, enabling the use of initializer.
Refactor and document the custom parallel backend API.

Maintenance:

Drop support for Python 3.8.
Support for Python 3.13 free-threaded has been added.
Drop support for PyPy.
Fixed an issue affecting joblib.load calls with non-null mmap_mode parameter \ 
when loading compressed python objects. It wrongly attempted to load with \ 
np.memmap anyway, resulting in python exceptions or corrupted data. The result \ 
now properly use in-memory np.array arrays, in accordance with the warnings that \ 
are emitted in this case.
Fix a regression in 1.3 and 1.4 that caused large big endian arrays to trigger a \ 
serialization error.
Added a ensure_native_byte_order parameter to joblib.load. When True and \ 
mmap_mode is None, loaded arrays are automatically coerced to a byte order that \ 
matches the endianness of the host system. This behavior has been the default \ 
since joblib==1.3, and can now be disabled if the parameter is set to False \ 
instead. Note that setting it to True will raise an error if mmap_mode is not \ 
null. The default value 'auto' is equivalent to always setting True if mmap_mode \ 
is None, else always False.
Fix support for python 3.14 in hashing, with the addition of an extra argument \ 
in Pickler._batch_setitems.
Fix tests on platforms with only one CPU core.
Bump vendored cloudpickle to 3.1.1 to support Python 3.14 (dev) and various \ 
other fixes.
Bump vendored loky to 3.5.3 to support recent Python versions without raising \ 
the warning on calls to os.fork and fix various sources of crashes and \ 
deadlocks.
Use pickle protocol 5 for pickling numpy arrays with object type.

Log message:
Fix PLIST after py-setuptools update; bump depends and revision

Log message:
py-*: remove unused tool dependency

py-setuptools includes the py-wheel functionality nowadays

Log message:
py-joblib: updated to 1.4.2

Release 1.4.2 -- 2024/05/02

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 consistency.
  https://github.com/joblib/joblib/pull/1576

Log message:
py-joblib: updated to 1.4.0

Release 1.4.0 -- 2024/04/08

- Allow caching co-routines with `Memory.cache`.

- 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.

- Ensure that errors in the task generator given to Parallel's call
  are raised in the results consumming thread.

- Adjust codebase to NumPy 2.0 by changing ``np.NaN`` to ``np.nan``
  and importing ``byte_bounds`` from ``np.lib.array_utils``.

- 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 submission.

- dask backend now supports ``return_as=generator`` and
  ``return_as=generator_unordered``.

- Vendor cloudpickle 3.0.0 and end support for Python 3.7 which has
  reached end of life.