Log message:
py-numba: updated to 0.44.1

Version 0.44.1
This patch release addresses some regressions reported in the 0.44.0 release:
- Fix 4164 issue with NUMBAPRO_NVVM.
- Abandon branch pruning if an arg name is redefined.
- Fix 4156. Problem with defining in-loop variables.

Log message:
py-numba: updated to 0.44.0

Version 0.44.0

IMPORTANT: In this release a few significant deprecations (and some less
significant ones) are being made, users are encouraged to read the related
documentation.

General enhancements in this release include:
- Numba is backed by LLVM 8 on all platforms apart from ppc64le, which, due to
  bugs, remains on the LLVM 7.x series.
- Numba's dictionary support now includes type inference for keys and values.
- The .view() method now works for NumPy scalar types.
- Newly supported NumPy functions added: np.delete, np.nanquantile, np.quantile,
  np.repeat, np.shape.

In addition considerable effort has been made to fix some long standing bugs and
a large number of other bugs, the "Fixes" section is very large this time!

Enhancements from user contributed PRs (with thanks!):
- Max Bolingbroke added support for the selective use of fastmath flags in
  3847.
- Rob Ennis made min() and max() work on iterables in 3820 and added
  np.quantile and np.nanquantile in 3899.
- Sergey Shalnov added numerous unicode string related features, zfill in 3978,
  ljust in 4001, rjust and center in 4044 and strip, lstrip and rstrip in
  4048.
- Guilherme Leobas added support for np.delete in 3890
- Christoph Deil exposed the Numba CLI via python -m numba in 4066 and made
  numerous documentation fixes.
- Leo Schwarz wrote the bulk of the code for jitclass default constructor
  arguments in 3852.
- Nick White enhanced the CUDA backend to use min/max PTX instructions where
  possible in 4054.
- Lucio Fernandez-Arjona implemented the unicode string __mul__ function in
  3952.
- Dimitri Vorona wrote the bulk of the code to implement getitem and setitem for
  jitclass in 3861.

General Enhancements:

* Min max on iterables
* Unicode type iteration
* Allow fine-grained control of fastmath flags to partially address 2923
* Add support for np.delete
* Support for np.quantile and np.nanquantile
* Fix 3457 :: Implements np.repeat
* Add .view() method for NumPy scalars
* Update icc_rt clone recipe.
* __mul__ for strings, initial implementation and tests
* Type-inferred dictionary
* Create a view for string slicing to avoid extra allocations
* zfill operation implementation
* ljust operation implementation
* Support dict() and {}
* Support for llvm 8
* Make type.Optional str more representative
* Deprecation warnings
* rjust and center operations implementation
* strip, lstrip and rstrip operations implementation
* Expose numba CLI via python -m numba
* Impl np.shape and support function for asarray.
* Deprecate the use of iternext_impl without RefType

CUDA Enhancements/Fixes:
* Adds .nbytes property to CUDA device array objects.
* Add .inspect_ptx() to cuda device function
* CUDA: Use min/max PTX Instructions
* Update env-vars for CUDA libraries lookup

Documentation Updates:
* Code repository map
* adding Joris' Fosdem 2019 presentation
* order talks on applications of Numba by date
* fix two small typos in vectorize docs
* Fixup jitclass docs
* mention preprint repo in FAQ. Fixes 3981
* Correct runtests command in contributing.rst
* fix typo
* Ambiguous Documentation fix for guvectorize.
* Remove remaining mentions of autojit in docs
* Fix annotate example in docstring
* Add FAQ entry explaining Numba project name
* Add Documentation for atomicity of typed.Dict
* Remove info about CUDA ENVVAR potential replacement

Fixes:
* Resolves issue 3528.  Adds support for slices when not using parallel=True.
* Remove dels for known dead vars.
* Fix mutable flag transmission in .astype
* Fix some minor issues in the C source.
* Correct boolean reinterpretation of data
* Comments out the appveyor badge
* fixes flake8 after merge
* Add assert to ir.py to help enforce correct structuring
* fix preparfor dtype transform for datetime64
* Prevent mutation of objmode fallback IR.
* Updates for llvmlite 0.29
* Use safe_load from pyyaml.
* Add tolerance to network errors by permitting conda to retry
* Fix casting in namedtuple ctor.
* Fix array inliner for multiple array definition.
* Cherrypick 3903 to main
* Raise better error if unsupported jump opcode found.
* Apply flake8 to the numpy related files
* Silence DeprecationWarning
* Better error message for unknown opcode
* Fix typing of ufuncs in parfor conversion
* Return variable renaming dict from inline_closurecall
* Fix bug in alignment computation of Record.make_c_struct
* Fix error with pickling unicode
* Unicode split algo versioning
* Add handler for unknown locale to numba -s
* Permit Optionals in ufunc machinery
* Remove assert in type inference causing poor error message.
* add is_ascii flag to UnicodeType
* Prevent zero division error in np.linalg.cond
* Resolves 4007.
* Add a more specific error message for invalid write to a global.
* Fix handling of titles in record dtype
* Do a check if a call is const before saying that an object is multiply defined.
* Fix issue 4020.  Turn off no_cpython_wrapper flag when compiling for…
* [WIP] Fixing wrong dtype of array inside reflected list 4028
* Change IPython cache dir name to numba_cache
* Delete examples/notebooks/LinearRegr.py
* Catch writes to global typed.Dict and raise.
* Check tuple length
* Fix missing incref on optional return None
* Make the warnings fixer flush work for warning comparing on type.
* Fix function definition finding logic for commented def
* Fix alignment check on 32-bit.
* Use PEP 508 compliant env markers for install deps

Log message:
py-numba: updated to 0.43.1

Version 0.43.1
This is a bugfix release that provides minor changes to fix: a bug in branch
pruning, bugs in `np.interp` functionality, and also fully accommodate the
NumPy 1.16 release series.

* NumPy 1.16 support
* Refactor np.interp
* Rewrite pruned conditionals as their evaluated constants.

Log message:
mathy/py-numba: Add PLIST.Linux to fix install on CentOS 7

Log message:
py-numba: updated to 0.43.0

Version 0.43.0
In this release, the major new features are:
* Initial support for statically typed dictionaries
* Improvements to hash() to match Python 3 behavior
* Support for the heapq module
* Ability to pass C structs to Numba
* More NumPy functions: asarray, trapz, roll, ptp, extract

Log message:
py-numba: updated to 0.42.0

Version 0.42.0
In this release the major features are:
* The capability to launch and attach the GDB debugger from within a jitted function.
* The upgrading of LLVM to version 7.0.0.

Log message:
Use alloca.h only for __sun.

Log message:
py-numba: updated to 0.41.0

Version 0.41.0

This release adds the following major features:
* Diagnostics showing the optimizations done by ParallelAccelerator
* Support for profiling Numba-compiled functions in Intel VTune
* Additional NumPy functions: partition, nancumsum, nancumprod, ediff1d, cov,
  conj, conjugate, tri, tril, triu
* Initial support for Python 3 Unicode strings

General Enhancements:
* armv7 support
* invert mapping b/w binop operators and the operator module
* First attempt at parallel diagnostics
* Adding NUMBA_ENABLE_PROFILING envvar, enabling jit event
* Support for np.partition
* Support for np.nancumsum and np.nancumprod
* Add location information to exceptions.
* Support for np.ediff1d
* Support for np.cov
* Support user pipeline class in with lifting
* string support
* Improve error message for empty imprecise lists.
* Enable overload(operator.getitem)
* Support negative indexing in tuple.
* Refactor Const type
* Optimized usage of alloca out of the loop
* Updates for llvmlite 0.26
* Add support for `np.conj/np.conjugate`.
* np.tri, np.tril, np.triu - default optional args
* Permit dtype argument as sole kwarg in np.eye

CUDA Enhancements:
* Add max_registers Option to cuda.jit

Continuous Integration / Testing:
* CI with Azure Pipelines
* Workaround race condition with apt
* Fix issues with Azure Pipelines
* Fix `RuntimeWarning: 'numba.runtests' found in sys.modules`
* Disable openmp in wheel building
* Azure Pipelines templates
* Fix cuda tests and error reporting in test discovery
* Prevent faulthandler installation on armv7l
* Fix CUDA test that used negative indexing behaviour that's fixed.
* Start Flake8 checking of Numba source

Fixes:
* Fix dispatcher to only consider contiguous-ness.
* Fix 3119, raise for 0d arrays in reductions
* Reduce redundant module linking
* Fix AOT on windows.
* Fix memory management of __cuda_array_interface__ views.
* Fix typo in error name.
* Fix the default unboxing logic
* Allow non-global reference to objmode() context-manager
* Fix global reference in objmode for dynamically created function
* CUDA_ERROR_MISALIGNED_ADDRESS Using Multiple Const Arrays
* Correctly handle very old versions of colorama
* Add 32bit package guard for non-32bit installs
* Fix with-objmode warning
* Fix label offset in call inline after parfor pass
* Fixes raising of user defined exceptions for exec(<string>).
* Fix error due to function naming in CI in py2.7
* Fixed TBB's single thread execution and test added for
* Allow matching non-array objects in find_callname()
* Change getiter and iternext to not be pure.
* Make ir.UndefinedType singleton class.
* Fix np.random.shuffle sideeffect
* Raise unsupported for kwargs given to `print()`
* Remove dead script.
* Fix stencil support for boolean as return type
* Fix handling make_function literals
* Add missing unicode != unicode
* Fix complex math sqrt implementation for large -ve values
* This adds arg an check for the pattern supplied to Parfors.
* Sets list dtor linkage to `linkonce_odr` to fix visibility in AOT

Documentation Updates:
* Update 0.40 changelog with additional PRs
* Tweak spacing to avoid search box wrapping onto second line
* Add note about memory leaks with exceptions to docs.
* Add FAQ on CUDA + fork issue.
* Update docs for argsort, kind kwarg partially supported.
* Added mention of njit in 5minguide.rst
* Fix parallel reduction example in docs.
* Fix broken link and mark up problem.
* Size Numba logo in docs in em units.
* just two typos
* Document string support
* Documentation for parallel diagnostics.

Log message:
math/py-numba: Add ALTERNATIVES

Log message:
py-numba: updated to 0.39.0

Version 0.39.0
Here are the highlights for the Numba 0.39.0 release.

This is the first version that supports Python 3.7.
With help from Intel, we have fixed the issues with SVML support.
List has gained support for containing reference-counted types like NumPy arrays \ 
and list. Note, list still cannot hold heterogeneous types.
We have made a significant change to the internal calling-convention, which \ 
should be transparent to most users, to allow for a future feature that will \ 
permitting jumping back into python-mode from a nopython-mode function. This \ 
also fixes a limitation to print that disabled its use from nopython functions \ 
that were deep in the call-stack.
For CUDA GPU support, we added a __cuda_array_interface__ following the NumPy \ 
array interface specification to allow Numba to consume externally defined \ 
device arrays. We have opened a corresponding pull request to CuPy to test out \ 
the concept and be able to use a CuPy GPU array.
The Numba dispatcher inspect_types() method now supports the kwarg pretty which \ 
if set to True will produce ANSI/HTML output, showing the annotated types, when \ 
invoked from ipython/jupyter-notebook respectively.
The NumPy functions ndarray.dot, np.percentile and np.nanpercentile, and \ 
np.unique are now supported.
Numba now supports the use of a per-project configuration file to permanently \ 
set behaviours typically set via NUMBA_* family environment variables.
Support for the ppc64le architecture has been added.