experimental/cuda-ubi9/: llvmlite-0.42.0 metadata and description

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lightweight wrapper around basic LLVM functionality

  • Development Status :: 4 - Beta
  • Intended Audience :: Developers
  • Operating System :: OS Independent
  • Programming Language :: Python
  • Programming Language :: Python :: 3
  • Programming Language :: Python :: 3.9
  • Programming Language :: Python :: 3.10
  • Programming Language :: Python :: 3.11
  • Programming Language :: Python :: 3.12
  • Topic :: Software Development :: Code Generators
  • Topic :: Software Development :: Compilers
license BSD
  • Source, https://github.com/numba/llvmlite
requires_python >=3.9
File Tox results History
42 MB
Python Wheel
Azure Pipelines Code Climate Coveralls.io Readthedocs.io

A Lightweight LLVM Python Binding for Writing JIT Compilers

llvmlite is a project originally tailored for Numba’s needs, using the following approach:

  • A small C wrapper around the parts of the LLVM C++ API we need that are not already exposed by the LLVM C API.

  • A ctypes Python wrapper around the C API.

  • A pure Python implementation of the subset of the LLVM IR builder that we need for Numba.

Why llvmlite

The old llvmpy binding exposes a lot of LLVM APIs but the mapping of C++-style memory management to Python is error prone. Numba and many JIT compilers do not need a full LLVM API. Only the IR builder, optimizer, and JIT compiler APIs are necessary.

Key Benefits

  • The IR builder is pure Python code and decoupled from LLVM’s frequently-changing C++ APIs.

  • Materializing a LLVM module calls LLVM’s IR parser which provides better error messages than step-by-step IR building through the C++ API (no more segfaults or process aborts).

  • Most of llvmlite uses the LLVM C API which is small but very stable (low maintenance when changing LLVM version).

  • The binding is not a Python C-extension, but a plain DLL accessed using ctypes (no need to wrestle with Python’s compiler requirements and C++ 11 compatibility).

  • The Python binding layer has sane memory management.

  • llvmlite is faster than llvmpy thanks to a much simpler architecture (the Numba test suite is twice faster than it was).


llvmlite has been tested with Python 3.9 – 3.12 and is likely to work with greater versions.

As of version 0.41.0, llvmlite requires LLVM 14.x.x on all architectures

Historical compatibility table:

llvmlite versions

compatible LLVM versions

0.41.0 - …


0.40.0 - 0.40.1

11.x.x and 14.x.x (12.x.x and 13.x.x untested but may work)

0.37.0 - 0.39.1


0.34.0 - 0.36.0

10.0.x (9.0.x for aarch64 only)



0.29.0 - 0.32.0

7.0.x, 7.1.x, 8.0.x

0.27.0 - 0.28.0


0.23.0 - 0.26.0


0.21.0 - 0.22.0


0.17.0 - 0.20.0


0.16.0 - 0.17.0


0.13.0 - 0.15.0


0.9.0 - 0.12.1


0.6.0 - 0.8.0


0.1.0 - 0.5.1



You’ll find the documentation at http://llvmlite.pydata.org

Pre-built binaries

We recommend you use the binaries provided by the Numba team for the Conda package manager. You can find them in Numba’s anaconda.org channel. For example:

$ conda install --channel=numba llvmlite

(or, simply, the official llvmlite package provided in the Anaconda distribution)

Other build methods

If you don’t want to use our pre-built packages, you can compile and install llvmlite yourself. The documentation will teach you how: http://llvmlite.pydata.org/en/latest/install/index.html