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Compiling Python code using LLVM

Edit Package python-numba

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.

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Source Files
Filename Size Changed
_link 0000000147 147 Bytes
_multibuild 0000000121 121 Bytes
numba-0.56.4.tar.gz 0002418748 2.31 MB
numba-pr8620-np1.24.patch 0000017905 17.5 KB
python-numba.changes 0000064253 62.7 KB
python-numba.spec 0000006778 6.62 KB
skip-failing-tests.patch 0000002356 2.3 KB
update-tbb-backend-calls-2021.6.patch 0000002209 2.16 KB
Revision 62 (latest revision is 99)
Matej Cepl's avatar Matej Cepl (mcepl) accepted request 1046565 from Benjamin Greiner's avatar Benjamin Greiner (bnavigator) (revision 62) 
- Split out python flavors into testing multibuilds. Depending on
  the obs worker, the test suite can take almost an hour per
  flavor.
- Replace allow-numpy-1.24.patch with an updated
  numba-pr8620-np1.24.patch to also work with still present numpy
  1.23 in Factory (discussed upstream in gh#numba/numba#8620)
- Merge fix-cli-test.patch into skip-failing-tests.patch
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