Metadata-Version: 2.1
Name: llvmlite
Version: 0.41.1
Summary: lightweight wrapper around basic LLVM functionality
Home-page: http://llvmlite.readthedocs.io
License: BSD
Project-URL: Source, https://github.com/numba/llvmlite
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Software Development :: Code Generators
Classifier: Topic :: Software Development :: Compilers
Requires-Python: >=3.8
License-File: LICENSE

========
llvmlite
========

.. image:: https://dev.azure.com/numba/numba/_apis/build/status/numba.llvmlite?branchName=main
   :target: https://dev.azure.com/numba/numba/_build/latest?definitionId=2&branchName=main
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A Lightweight LLVM Python Binding for Writing JIT Compilers
-----------------------------------------------------------

.. _llvmpy: https://github.com/llvmpy/llvmpy

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).

Compatibility
=============

llvmlite works with Python 3.8 and greater. We attempt to test with the latest
Python version, this can be checked by looking at the public CI builds.

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 - ...       14.x.x
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    11.x.x
0.34.0 - 0.36.0    10.0.x (9.0.x for  ``aarch64`` only)
0.33.0             9.0.x
0.29.0 - 0.32.0    7.0.x, 7.1.x, 8.0.x
0.27.0 - 0.28.0    7.0.x
0.23.0 - 0.26.0    6.0.x
0.21.0 - 0.22.0    5.0.x
0.17.0 - 0.20.0    4.0.x
0.16.0 - 0.17.0    3.9.x
0.13.0 - 0.15.0    3.8.x
0.9.0 - 0.12.1     3.7.x
0.6.0 - 0.8.0      3.6.x
0.1.0 - 0.5.1      3.5.x
=================  ========================

Documentation
=============

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 <https://anaconda.org/numba>`_.  For example::

   $ conda install --channel=numba llvmlite

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

.. _Numba: http://numba.pydata.org/
.. _Conda: http://conda.pydata.org/
.. _Anaconda: http://docs.continuum.io/anaconda/index.html


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