- update to 1.4.0:
  * 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.
- drop avoid-deprecated-ast.patch (upstream)

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- Add patch avoid-deprecated-ast.patch:
  * Avoid deprecated ast classes.
- Add patch also-filter-new-fork-warning.patch:
  * Filter DeprecationWarning due to calling fork() with multiprocessing.
- Switch to pyproject macros.

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- update to 1.3.2:
  * FIX treat n_jobs=None as if left to its default value
  * FIX Init logger parent class in Parallel
  * MNT remove unnecessary .bck file
  * MTN adjust test regex for Python 3.12 improved error message
  * DOC add public documentation for parallel_backend
  * FIX flake8 new E721: type comparison
  * Ensure native byte order for memmap.
  * Drop runtime dependency on `distutils`
  * Add environment variable to change default parallel backend
  * Fix memmapping_reducer when 'os' has no attribute 'statvfs'
  * Move the metadata into `pyproject.toml`
  * TST Close client in test_pickle_in_socket
  * Do not swallow PicklingError
  * FIX Avoid collisions when caching nested functions
  * FIX heisenfailure in doc/memory.rst
  * MAINT Explicit support for Python 3.11
  * MNT Use faulthandler rather than custom autokill logic
  * BENCH add benchmark script for n_jobs=1
  * TST Fix test_nested_parallel_warnings_parent_backend for
    Python nogil
  * TST Fix test_memmapping for Python nogil
  * MAINT Clean deprecations
  * ENH make temp resource cleanup safer
  * MAINT Simplify warning in `_persist_input`
  * MNT Use full flake8 rather than flake8_diff.sh
  * Update Dask backend
  * FIX upload to codecov
  * MTN vendor loky 3.4.0
  * MTN skip thread_bomb mitigation test on PyPy for now

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- Update to 1.2.0 (CVE-2022-21797, bsc#1204232)
  * Fix a security issue where eval(pre_dispatch) could potentially
    run arbitrary code. Now only basic numerics are supported.
    #1327
  * Make sure that joblib works even when multiprocessing is not
    available, for instance with Pyodide #1256
  * Avoid unnecessary warnings when workers and main process delete
    the temporary memmap folder contents concurrently. #1263
  * Vendor loky 3.1.0 with several fixes to more robustly forcibly
    terminate worker processes in case of a crash. #1269
  * 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 platform specific assembly. #1254
  * Vendor cloudpickle 2.2.0 which adds support for PyPy 3.8+.
  * Vendor loky 3.3.0 which fixes a bug with leaking processes in
    case of nested loky parallel calls and more reliability spawn
    the correct number of reusable workers.
- Drop support-setuptools-62.patch

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- Add patch support-setuptools-62.patch:
  * Support setuptools >= 62 by handling more than one warning in a test
    case.

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Automatic submission by obs-autosubmit

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- update to 0.16.0
  - Fix a problem in the constructors of of Parallel backends classes that
    inherit from the `AutoBatchingMixin` that prevented the dask backend to
    properly batch short tasks.
    https://github.com/joblib/joblib/pull/1062
  - Fix a problem in the way the joblib dask backend batches calls that would
    badly interact with the dask callable pickling cache and lead to wrong
    results or errors.
    https://github.com/joblib/joblib/pull/1055
  - Prevent a dask.distributed bug from surfacing in joblib's dask backend
    during nested Parallel calls (due to joblib's auto-scattering feature)
    https://github.com/joblib/joblib/pull/1061
  - Workaround for a race condition after Parallel calls with the dask backend
    that would cause low level warnings from asyncio coroutines:
    https://github.com/joblib/joblib/pull/1078

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- update to 0.15.1:
  - Make joblib work on Python 3 installation that do not ship with the lzma
    package in their standard library.
  - Drop support for Python 2 and Python 3.5. All objects in
    ``joblib.my_exceptions`` and ``joblib.format_stack`` are now deprecated and
    will be removed in joblib 0.16. Note that no deprecation warning will be
    raised for these objects Python < 3.7.
    https://github.com/joblib/joblib/pull/1018
  - Fix many bugs related to the temporary files and folder generated when
    automatically memory mapping large numpy arrays for efficient inter-process
    communication. In particular, this would cause `PermissionError` exceptions
    to be raised under Windows and large leaked files in `/dev/shm` under Linux
    in case of crash.
    https://github.com/joblib/joblib/pull/966
  - Make the dask backend collect results as soon as they complete
    leading to a performance improvement:
    https://github.com/joblib/joblib/pull/1025
  - Fix the number of jobs reported by ``effective_n_jobs`` when ``n_jobs=None``
    called in a parallel backend context.
    https://github.com/joblib/joblib/pull/985
  - Upgraded vendored cloupickle to 1.4.1 and loky to 2.8.0. This allows for
    Parallel calls of dynamically defined functions with type annotations
    in particular.

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- Switch to %pytest
- Add patch to work well with new numpy:
  * numpy16.patch

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- Update to 0.13.2:
  * Upgrade to cloudpickle 0.8.0
  * Add a non-regression test related to joblib issues #836 and #833, reporting that cloudpickle versions between 0.5.4 and 0.7 introduced a bug where global variables changes in a parent process between two calls to joblib.Parallel would not be propagated into the workers

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