Numba translates Python functions to optimized machine code at
runtime using the industry-standard LLVM compiler library.
Numba-compiled numerical algorithms in Python can approach the
speeds of C or FORTRAN.
You don't need to replace the Python interpreter, run a separate
compilation step, or even have a C/C++ compiler installed. Just apply
one of the Numba decorators to your Python function, and Numba does
the rest.
Due to the Python version in Slackware 15.0, the version of numba is
held at 0.60.0 and will not be updated.
This requires: python3-numpy
Maintained by: Christoph Willing
Keywords: high performance,parallel,just in time compiler
ChangeLog: python3-numba
Homepage:
https://numba.readthedocs.io/en/stable
Download SlackBuild:
python3-numba.tar.gz
python3-numba.tar.gz.asc (FAQ)
(the SlackBuild does not include the source)
| Individual Files: |
| README |
| python3-numba.SlackBuild |
| python3-numba.info |
| slack-desc |
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