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

[ CVSweb ] [ Homepage ] [ RSS ] [ Required by ] [ Add to tracker ]


Branch: CURRENT, Version: 0.39.0nb1, Package name: py27-numba-0.39.0nb1, 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] [lang/python27] [devel/py-enum34] [devel/py-singledispatch] [devel/py-funcsigs] [devel/py-llvmlite]

Required to build:
[pkgtools/cwrappers]

Master sites:

SHA1: 4baa3c6d47b45c28e80f2e30bee2cbc7ee1ac2a8
RMD160: ca9d02348334c8ec0d6a48bdb4455d33babedbb1
Filesize: 1375.096 KB

Version history: (Expand)


CVS history: (Expand)


   2018-09-04 01:47:44 by Min Sik Kim | Files touched by this commit (3)
Log message:
math/py-numba: Add ALTERNATIVES
   2018-08-28 14:06:42 by Adam Ciarcinski | Files touched by this commit (3) | Package updated
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.
   2018-05-18 18:08:49 by Min Sik Kim | Files touched by this commit (4) | Package updated
Log message:
math/py-numba: Import version 0.37.0

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.

Packaged by Kamil Rytarowski for pkgsrc-wip and updated by me.