Ubuntu
numba package

numba 0.59.1+dfsg-3 source package in Ubuntu

Changelog

numba (0.59.1+dfsg-3) unstable; urgency=medium

  * In Autopkgtests always cap the number of cores at 16.  We're having
    random failures on amd64 which has a high core count on the CI,
    upstream's comment implies they encountered that on ppc64.

 -- Diane Trout <email address hidden>  Tue, 23 Jul 2024 11:42:33 -0700

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Uploaded by:
Debian Science Team
Uploaded to:
Sid
Original maintainer:
Debian Science Team
Architectures:
any all
Section:
misc
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Oracular proposed universe misc

Downloads

File Size SHA-256 Checksum
numba_0.59.1+dfsg-3.dsc 2.5 KiB 7c37a98e9269e46570804cf8723ff346d5c1a4c5c13a2c34254d027bacf1ea43
numba_0.59.1+dfsg.orig.tar.xz 1.9 MiB c958bf2dfb9f1ab1bbab7e1522d5c9bfda16a339c20bc1c3a9e74c369293114f
numba_0.59.1+dfsg-3.debian.tar.xz 17.1 KiB 160b5d5b3c92d7b3a755daa9a19f67a1f6d151b69cd32bea2da2fa86df016a5c

Available diffs

No changes file available.

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