./math/py-numba, NumPy aware dynamic Python compiler using LLVM

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Branch: CURRENT, Version: 0.55.0, Package name: py39-numba-0.55.0, Maintainer: pkgsrc-users

Numba is an Open Source NumPy-aware optimizing compiler for Python
sponsored by Continuum Analytics, Inc. It uses the
remarkable LLVM compiler infrastructure to compile Python syntax to
machine code.

It is aware of NumPy arrays as typed memory regions and so can speed-up
code using NumPy arrays. Other, less well-typed code will be translated
to Python C-API calls effectively removing the "interpreter" but not removing
the dynamic indirection.

Numba is also not a tracing JIT. It *compiles* your code before it gets
run either using run-time type information or type information you provide
in the decorator.

Numba is a mechanism for producing machine code from Python syntax and typed
data structures such as those that exist in NumPy.

Required to run:
[devel/py-setuptools] [math/py-numpy] [devel/py-llvmlite] [lang/python37]

Required to build:

Master sites:

Filesize: 2246.66 KB

Version history: (Expand)

CVS history: (Expand)

   2022-01-14 20:52:24 by Adam Ciarcinski | Files touched by this commit (5) | Package updated
Log message:
py-numba: updated to 0.55.0

Version 0.55.0

This release includes a significant number important dependency upgrades along \ 
with a number of new features and bug fixes.

Version 0.54.1

This is a bugfix release for 0.54.0. It fixes a regression in structured array \ 
type handling, a potential leak on initialization failure in the CUDA target, a \ 
regression caused by Numba’s vendored cloudpickle module resetting dynamic \ 
classes and a few minor testing/infrastructure related problems.

Version 0.53.1

This is a bugfix release for 0.53.0. It contains the following four \ 
pull-requests which fix two critical regressions and two build failures reported \ 
by the openSuSe team:

* Fix regression on gufunc serialization
* Fix regression in CUDA: Set stream in mapped and managed array device_setup
* Ignore warnings from packaging module when testing import behaviour.
* set non-reported llvm timing values to 0.0

Version 0.53.0

This release continues to add new features, bug fixes and stability improvements \ 
to Numba.

Highlights of core changes:

Support for Python 3.9
Function sub-typing
Initial support for dynamic gufuncs
Parallel Accelerator (@njit(parallel=True) now supports Fortran ordered arrays

Version 0.52.0

This release focuses on performance improvements, but also adds some new \ 
features and contains numerous bug fixes and stability improvements.
   2022-01-05 21:47:37 by Thomas Klausner | Files touched by this commit (26)
Log message:
*: set USE_PKG_RESOURCES for more packages
   2022-01-04 21:55:40 by Thomas Klausner | Files touched by this commit (1595)
Log message:
*: bump PKGREVISION for egg.mk users

They now have a tool dependency on py-setuptools instead of a DEPENDS
   2021-12-30 14:05:42 by Adam Ciarcinski | Files touched by this commit (125)
Log message:
Forget about Python 3.6
   2021-10-26 12:56:13 by Nia Alarie | Files touched by this commit (458)
Log message:
math: Replace RMD160 checksums with BLAKE2s checksums

All checksums have been double-checked against existing RMD160 and
SHA512 hashes
   2021-10-07 16:28:36 by Nia Alarie | Files touched by this commit (458)
Log message:
math: Remove SHA1 hashes for distfiles
   2021-06-29 10:42:02 by Nia Alarie | Files touched by this commit (28)
Log message:
py-numpy: "Python version >= 3.7 required."
   2021-06-23 17:36:26 by Dr. Thomas Orgis | Files touched by this commit (1)
Log message:
math/py-numba: fix typo in PLIST.Linux (hotfix, need to settle PLIST entry)

The omppool file is both in PLIST and PLIST.Linux. One needs to go. This hotfix
just removes the typo. Do we remove PLIST.Linux and assume every platform
of interest has working OpenMP? Add Darwin dep for parallel/openmp?