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

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Branch: CURRENT, Version: 0.50.1, Package name: py37-numba-0.50.1, 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:
[pkgtools/cwrappers]

Master sites:

SHA1: 0965f268b851f3c9a61eec9dba10c1f5e5403468
RMD160: 8ce054c9332282dbd1fead6a9b7e575a138e3082
Filesize: 1958.812 KB

Version history: (Expand)


CVS history: (Expand)


   2020-07-07 22:08:46 by Adam Ciarcinski | Files touched by this commit (2) | Package updated
Log message:
py-numba: updated to 0.50.1

Version 0.50.1:

This is a bugfix release for 0.50.0, it fixes a critical bug in error reporting
and a number of other smaller issues:

* Added except for possible Windows get_terminal_size exception
* Improve undefined variable error message
* Update the deprecation notices for 0.50.1
* Fixes literally not forcing re-dispatch for inline='always'
* Fix bad attr access on certain typing templates breaking exceptions.
* Fix cuda test
   2020-06-16 19:07:47 by Adam Ciarcinski | Files touched by this commit (3) | Package updated
Log message:
py-numba: updated to 0.50.0

Version 0.50.0:

This is a more usual release in comparison to the others that have been made in \ 
the last six months. It comprises the result of a number of maintenance tasks \ 
along with some new features and a lot of bug fixes.

Highlights of core feature changes include:

The compilation chain is now based on LLVM 9.
The error handling and reporting system has been improved to reduce the size of \ 
error messages, and also improve quality and specificity.
The CUDA target has more stream constructors available and a new function for \ 
compiling to PTX without linking and loading the code to a device. Further, the \ 
macro-based system for describing CUDA threads and blocks has been replaced with \ 
standard typing and lowering implementations, for improved debugging and \ 
extensibility.
   2020-05-31 22:48:22 by Joerg Sonnenberger | Files touched by this commit (2)
Log message:
Don't use non-portable alloca.h
   2020-05-12 10:11:36 by Adam Ciarcinski | Files touched by this commit (3) | Package updated
Log message:
py-numba: updated to 0.49.1

Version 0.49.1:

This is a bugfix release for 0.49.0, it fixes some residual issues with SSA \ 
form, a critical bug in the branch pruning logic and a number of other smaller \ 
issues:

* Fixed Threading Implementation Typos
* Fixes Remove references to cffi_support from docs and examples
* Fix invalid type in resolve for comparison expr in parfors.
* Fix erroneous rewrite of predicate to bit const on prune.
* Fixes SSA local def scan based on invalid equality assumption.
* Fixes naming error in array_exprs
* Fix. Incorrect race variable detection due to SSA naming.
* Make literal_unroll function work as a freevar.
* Unset the memory manager after EMM Plugin tests
* Fix some SSA issues
* Pin to sphinx=2.4.4 to avoid problem with C declaration
* Fix unifying undefined first class function types issue
* Update example in 5m guide WRT SSA type stability.
* Restore numba.types as public API
   2020-04-30 11:21:27 by Thomas Klausner | Files touched by this commit (1)
Log message:
py-numba: remove patch that was removed from distinfo
   2020-04-18 10:14:09 by Adam Ciarcinski | Files touched by this commit (3) | Package updated
Log message:
py-numba: updated to 0.49.0

Version 0.49.0:

This release is very large in terms of code changes. Large scale removal of \ 
unsupported Python and NumPy versions has taken place along with a significant \ 
amount of refactoring to simplify the Numba code base to make it easier for \ 
contributors. Numba’s intermediate representation has also undergone some \ 
important changes to solve a number of long standing issues. In addition some \ 
new features have been added and a large number of bugs have been fixed!

IMPORTANT: In this release Numba’s internals have moved about a lot. A \ 
backwards compatibility “shim” is provided for this release so as to not \ 
immediately break projects using Numba’s internals. If a module is imported \ 
from a moved location the shim will issue a deprecation warning and suggest how \ 
to update the import statement for the new location. The shim will be removed in \ 
0.50.0!

Highlights of core feature changes include:

Removal of all Python 2 related code and also updating the minimum supported \ 
Python version to 3.6, the minimum supported NumPy version to 1.15 and the \ 
minimum supported SciPy version to 1.0.
Refactoring of the Numba code base. The code is now organised into submodules by \ 
functionality. This cleans up Numba’s top level namespace.
Introduction of an ir.Del free static single assignment form for Numba’s \ 
intermediate representation
An OpenMP-like thread masking API has been added for use with code using the \ 
parallel CPU backends
For the CUDA target, all kernel launches now require a configuration, this \ 
preventing accidental launches of kernels with the old default of a single \ 
thread in a single block. The hard-coded autotuner is also now removed, such \ 
tuning is deferred to CUDA API calls that provide the same functionality
The CUDA target also gained an External Memory Management plugin interface to \ 
allow Numba to use another CUDA-aware library for all memory allocations and \ 
deallocations
The Numba Typed List container gained support for construction from iterables
Experimental support was added for first-class function types
   2020-02-01 22:03:58 by Adam Ciarcinski | Files touched by this commit (3) | Package updated
Log message:
py-numba: updated to 0.48.0

Version 0.48.0

This release is particularly small as it was present to catch anything that \ 
missed the 0.47.0 deadline (the deadline deliberately coincided with the end of \ 
support for Python 2.7). The next release will be considerably larger.

The core changes in this release are dominated by the start of the clean up \ 
needed for the end of Python 2.7 support, improvements to the CUDA target and \ 
support for numerous additional unicode string methods.

Enhancements from user contributed PRs (with thanks!):

Brian Wignall fixed more spelling typos in.
Denis Smirnov added support for string methods capitalize, casefold, swapcase , \ 
rsplit , partition  and splitlines .
Elena Totmenina extended support for string methods startswith  and added endswith .
Eric Wieser made type_callable return the decorated function itself in
Ethan Pronovost added support for np.argwhere in
Graham Markall contributed a large number of CUDA enhancements and fixes, namely:
* Remove Python 3.4 backports from utils
* Make device_array_like create contiguous arrays
* Don’t launch ForAll kernels with 0 elements
* Fix various issues in CUDA library search
* Enable use of records and bools for shared memory, remove ddt, add additional \ 
transpose tests
* Fix: Add more appropriate typing for CUDA device arrays
* test_consuming_strides: Keep dev array alive
* State that CUDA Toolkit 8.0 required in docs
James Bourbeau added the Python 3.8 classifier to setup.py in.
John Kirkham added a clarification to the __cuda_array_interface__ documentation in.
Leo Fang Fixed an indexing problem in dummyarray in.
Marcel Bargull fixed a build and test issue for Python 3.8 in.
Maria Rubtsov added support for string methods isdecimal , isdigit , isnumeric  \ 
and replace .

General Enhancements:
* Make type_callable return the decorated function
* merge string prs

This merge PR included the following:
* Implement str.capitalize() based on CPython
* Implement str.casefold() based on CPython
* Implement str.swapcase() based on CPython
* Implement str.rsplit() based on CPython
* Implement str.isdecimal
* Implement str.isdigit
* Implement str.isnumeric
* Implement str.partition() based on CPython
* Implement str.splitlines() based on CPython
* Implement str.replace
* Functionality extension str.startswith() based on CPython
* Add functionality for str.endswith()
* Disable help messages.
* Add coverage for np.argwhere

Fixes:
* Only use lives (and not aliases) to create post parfor live set.
* Fix more spelling typos
* Propagate semantic constants ahead of static rewrites.
* Add Python 3.8 classifier to setup.py
* Update setup.py and buildscripts for dependency requirements
* Convert from arrays to names in define() and don’t invalidate for multiple \ 
consistent defines.
* Permit mixed int types in wrap_index
* Catch the use of global typed-list in JITed functions
* Fix, bug in bytecode analysis.

CUDA Enhancements/Fixes:
* Fix: Add more appropriate typing for CUDA device arrays
* Make device_array_like create contiguous arrays
* State that CUDA Toolkit 8.0 required in docs
* test_consuming_strides: Keep dev array alive
* Fix IndexError when accessing the “-1” element of dummyarray
* Enable use of records and bools for shared memory, remove ddt, add additional \ 
transpose tests
* Fix various issues in CUDA library search
* Don’t launch ForAll kernels with 0 elements
* Remove Python 3.4 backports from utils
Documentation Updates:

* Clarify what dictionary means
* Update docs for updated version requirements
* Update deprecation notices for 0.48.0
CI updates:

* Install optional dependencies for Python 3.8 tests
* Drop Py2.7 and Py3.5 from public CI
* Fix CI py38
   2020-01-26 18:32:28 by Roland Illig | Files touched by this commit (981)
Log message:
all: migrate homepages from http to https

pkglint -r --network --only "migrate"

As a side-effect of migrating the homepages, pkglint also fixed a few
indentations in unrelated lines. These and the new homepages have been
checked manually.