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numba package

numba 0.56.4+dfsg-2 source package in Ubuntu

Changelog

numba (0.56.4+dfsg-2) unstable; urgency=medium

  [ Diane Trout ]
  * Backport patches from https://github.com/numba/numba/pull/8590 into
    patches/python3.11/
    0054-Apply-suggestions-from-code-review.patch
    0055-Fix-arrayexprs-for-py3.11.patch
    0056-Fix-LOAD_GLOBAL-arg-use-in-test_parfors-for-py3.11.patch
    0057-Move-_fix_LOAD_GLOBAL-arg-to-bytecode-module-and-use-it-in-_compute_used_globals.patch
    0058-Fix-text_flow_control-for-py3.11.patch
    0059-Not-a-py311-change-stop-printing-source-code.patch
    0060-Attempt-to-fix-cellvars.patch
    0061-Fix-CodeType-usage.patch
    0062-Remove-duplicated-handling-of-CodeType.patch
    0063-Flake8-fixes.patch
    0064-More-flake8-fixes.patch
    0065-Enable-list_to_tuple-peephole-for-py3.11.patch
    0067-Update-numba-core-byteflow.py.patch
    0068-Get-rid-of-custom-copy_code_type.-Use-CodeType.Replace-instead.patch
  * Add Origin header for the 8545 pull request for the earlier patches
  * Backport patches from https://github.com/numba/numba/pull/8639
      201-Update-string-bytes-hash-algs-to-siphash13-for-Python.patch
      202-Fix-flake8.patch
      203-Attempt-to-fix-closures.patch
      204-Enable-more-peephole-rewrites-in-3.11.patch
      205-Fix-test_dump_bytecode.patch
      206-Fix-f-string-const-name-interp.patch
      207-Rewrite-_jump_if_none-to-match-pre-py3.11.patch
      208-Fix-near-and-far-jump-target-ordering.patch
      209-Add-more-new-op-code-handling.patch
      210-Fix-issue-with-EXTENDED_ARG-test-and-update-test.patch
      211-Add-pop-NULL-to-CALL_FUNCTION_EX-byteflow-analysis.patch
      212-Fix-out-of-bounds-loop-index-in-test.patch
      213-Accommodate-multiple-bytecodes-at-block-start-with-no.patch
      214-Fix-parfors-prange-test-generator-LOAD_GLOBAL-args.patch
      215-Update-assertion-for-Python-3.11-style-error-messages.patch
      216-Fix-bytecode-iteration-to-handle-EXTENDED_ARG-as-jump.patch
      217-Fix-rebase-error-in-op_LOAD_DEREF.patch
      218-Respond-to-feedback-RE-use-of-_is_null_temp_reg-in.patch
      219-Fix-binop-names-to-be-legal-variable-names.patch
      220-Update-test_extended_arg-to-use-CodeType.replace.patch
  * Backport pull request https://github.com/numba/numba/pull/8644
      301-Fix-bare-reraise-support.patch
  * Try to implement nocheck test skipping
  * Mark known problmatic tests with expectedFailure("python3.11")
    tests-failing-python3.patch

 -- Diane Trout <email address hidden>  Sun, 05 Feb 2023 20:51:25 -0800

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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

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numba_0.56.4+dfsg-2.dsc 2.3 KiB 3c8ea88c0c924a658efd0254aa27f502bb429bc350377909061cb8581c3c9977
numba_0.56.4+dfsg.orig.tar.xz 1.7 MiB 2139831b84371aeb3ecbaf64f8ecc50c683768742f4c1bdadbd6768853c26987
numba_0.56.4+dfsg-2.debian.tar.xz 67.6 KiB 465f941b70ef3e48b3d74ece75581da91ba491a810414f2ab4f4f96a1f3a62da

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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