- update to 0.59.1:
  * Fixed caching of kernels that use target-specific overloads
  * Fixed a performance regression introduced in Numba 0.59 which
    made ``np.searchsorted`` considerably slower.
  * This patch fixes two issues with ``np.searchsorted``. First,
    a regression is fixed in the support of ``np.datetime64``.
    Second, adopt ``NAT``-aware  comparisons to fix mishandling
    of ``NAT`` value.
  * Allow use of Python 3.12 PEP-695 type parameter syntax

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- update to 0.59.0
  * Python 3.12 support
  * minimum supported version to 3.9
  * Add support for ufunc attributes and reduce
  * Add a config variable to enable / disable the llvmlite memory
    manager
  * see https://numba.readthedocs.io/en/stable/release/0.59.0-notes.html#highlights

  * fix regressions with 0.57.0
    + Support is added for the dict(iterable) constructor.
- Clean up leftover Python 3.8 gubbins, look forward to Python 3.11 support.
  This release focuses on performance improvements, but also adds
  some new features and contains numerous bug fixes and stability
  * Intel kindly sponsored research and development into producing
    a new reference count pruning pass. This pass operates at the
    LLVM level and can prune a number of common reference counting
    patterns. This will improve performance for two primary
    - There will be less pressure on the atomic locks used to do
    - Removal of reference counting operations permits more
      inlining and the optimisation passes can in general do more
  * Intel also sponsored work to improve the performance of the
    numba.typed.List container, particularly in the case of
  * Superword-level parallelism vectorization is now switched on
    and the optimisation pipeline has been lightly analysed and
    tuned so as to be able to vectorize more and more often
  * The inspect_cfg method on the JIT dispatcher object has been
    significantly enhanced and now includes highlighted output and
  * The BSD operating system is now unofficially supported (Stuart
  * Numerous features/functionality improvements to NumPy support,
    - the ndarray allocators, empty, ones and zeros, accepting a

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- update to 0.57.1:
  * fix regressions with 0.57.0 
- remove upper bound on numpy - upstream does not have it either

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- Update to 0.57.0:
  * Support for Python 3.11 (minimum is moved to 3.8)
  * Support for NumPy 1.24 (minimum is moved to 1.21)
  * Python language support enhancements:
    + Exception classes now support arguments that are not compile time
      constant.
    + The built-in functions hasattr and getattr are supported for compile
      time constant attributes.
    + The built-in functions str and repr are now implemented similarly to
      their Python implementations. Custom __str__ and __repr__ functions
      can be associated with types and work as expected.
    + Numba’s unicode functionality in str.startswith now supports kwargs
      start and end.
    + min and max now support boolean types.
    + Support is added for the dict(iterable) constructor. 
- Dropped patches:
  * numba-pr8620-np1.24.patch
  * update-tbb-backend-calls-2021.6.patch
- Rebased existing patch.

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- Clean up leftover Python 3.8 gubbins, look forward to Python 3.11 support. 

- Remove test-py38 flavor from multibuild: Python 3.8 is no longer
  supported.

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- Update to 0.56.2
  This release continues to add new features, bug fixes and stability
  improvements to Numba. Please note that this will be the last release that
  has support for Python 3.7 as the next release series (Numba 0.57) will
  support Python 3.11! Also note that, this will be the last release to support
  linux-32 packages produced by the Numba team.
- Remove fix-max-name-size.patch, it's included in the new version.
- Add update-tbb-backend-calls-2021.6.patch to make it compatible with the
  latest tbb-devel version.
- Add fix-cli-test.patch to disable one test that fails with OBS.

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- Numba <0.55 is not compatible with Python 3.10 or NumPy 1.22
  gh#numba/numba#7557
- Add test skip to numba-pr7483-numpy1_21.patch due to numpy update
  gh#numpy/numpy#20376

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