Ubuntu
numba package

numba 0.55.1-0ubuntu1 source package in Ubuntu

Changelog

numba (0.55.1-0ubuntu1) jammy; urgency=medium

  * New upstream version
  * Refreshed patchset
  * Add self to d/copyright
  * Bump copyright dates

 -- Erich Eickmeyer <email address hidden>  Mon, 28 Feb 2022 16:50:33 -0800

Upload details

Uploaded by:
Erich Eickmeyer
Uploaded to:
Jammy
Original maintainer:
Ubuntu Developers
Architectures:
any all
Section:
misc
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section

Downloads

File Size SHA-256 Checksum
numba_0.55.1.orig.tar.gz 2.2 MiB a25005aed24de1ff801c307ab4482a0bb4a0564e362addd5913a874a3e97166b
numba_0.55.1-0ubuntu1.debian.tar.xz 14.1 KiB 0e0535fc67e75012f74f23da1167750e0b394fb9ee8f94f91411ba67b529e950
numba_0.55.1-0ubuntu1.dsc 2.1 KiB 05a1e310cea0b67c6ab1584fe7abd369e621fe5d2387ece332b070e6c1b4132f

View changes file

Binary packages built by this source

numba-doc: native machine code compiler for Python (docs)

 Numba compiles native machine code instructions from Python programs at
 runtime using the LLVM compiler infrastructure. Just-in-time compilation with
 Numba could be easily employed by decorating individual computation intensive
 functions in the Python code.
 Numba could significantly speed up the performance of computations, and
 optionally supports compilation to run on GPU processors through Nvidia's
 CUDA platform.
 It integrates well with the Python scientific software stack, and
 especially recognizes Numpy arrays.
 .
 This package contains the documentation and examples.

python3-numba: native machine code compiler for Python 3

 Numba compiles native machine code instructions from Python programs at
 runtime using the LLVM compiler infrastructure. It could be easily employed
 by decorating individual computation intensive functions in the Python code.
 Numba could significantly speed up the performance of computations, and
 optionally supports compilation to run on GPU processors through Nvidia's
 CUDA platform.
 It integrates well with the Python scientific software stack, and
 especially recognizes Numpy arrays.
 .
 This package contains the modules for Python 3.

python3-numba-dbgsym: debug symbols for python3-numba