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- 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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- Add %{?sle15_python_module_pythons}

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- Update to 1.2.0 (CVE-2022-21797, bsc#1204232)

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- Update to 1.2.0 (CVE-2022-21797)

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- Update to 1.2.0
  * 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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- update to 1.1.0:
  * 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 the pickle.
  * Fix joblib.Memory bug with the ignore parameter when the cached function is a
    decorated function.
  * Fix joblib.Memory to properly handle caching for functions defined
    interactively in a IPython session or in Jupyter notebook cell.
  * Update vendored loky (from version 2.9 to 3.0) and cloudpickle (from
    version 1.6 to 2.0)

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- Update to 1.0.1
  * dask: avoid redundant scattering of large arguments to make a
    more efficient use of the network resources and avoid crashing
    dask with "OSError: [Errno 55] No buffer space available" or
    "ConnectionResetError: [Errno 104] connection reset by
    peer".
- Changees in 1.0.0
  * Make joblib.hash and joblib.Memory caching system compatible
    with numpy >= 1.20.0. Also make it explicit in the
    documentation that users should now expect to have their joblib.
    Memory cache invalidated when either joblib or a third party
    library involved in the cached values definition is upgraded.
    In particular, users updating joblib to a release that includes
    this fix will see their previous cache invalidated if they
    contained reference to numpy objects.
  * Remove deprecated check_pickle argument in delayed.
- Changes in 0.17.0
  * Fix a spurious invalidation of Memory.cache'd functions called
    with Parallel under Jupyter or IPython.
  * Bump vendored loky to 2.9.0 and cloudpickle to 1.6.0. In
    particular this fixes a problem to add compat for Python 3.9.
- Don't require optional NumPy for python36 tests in TW, because
  NumPy 1.20 dropped support for Python 3.6 (NEP 29)
- Drop joblib-disable-unrelialble-tests.patch, they are already
  used in pytest deselection parameter.
  * Do the same for disable_test_on_big_endian.patch.

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- BuildRequire threadpoolctl for all python3 flavors
  gh#openSUSE/python-rpm-macros#66

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