Metadata-Version: 1.2
Name: llvmlite
Version: 0.33.0rc1
Summary: lightweight wrapper around basic LLVM functionality
Home-page: http://llvmlite.pydata.org
Author: Continuum Analytics, Inc.
Author-email: numba-users@continuum.io
License: BSD
Download-URL: https://github.com/numba/llvmlite
Description: ========
        llvmlite
        ========
        .. image:: https://travis-ci.org/numba/llvmlite.svg?branch=master
           :target: https://travis-ci.org/numba/llvmlite
           :alt: Travis CI
        .. image:: https://codeclimate.com/github/numba/llvmlite/badges/gpa.svg
           :target: https://codeclimate.com/github/numba/llvmlite
           :alt: Code Climate
        .. image:: https://coveralls.io/repos/github/numba/llvmlite/badge.svg
           :target: https://coveralls.io/github/numba/llvmlite
           :alt: Coveralls.io
        .. image:: https://readthedocs.org/projects/llvmlite/badge/
           :target: https://llvmlite.readthedocs.io
           :alt: Readthedocs.io
        
        A lightweight LLVM python binding for writing JIT compilers
        
        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.
        
        .. _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.
        
        
        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 quite faster than llvmpy's thanks to a much simpler architeture
          (the Numba_ test suite is twice faster than it was).
        
        llvmpy Compatibility Layer
        --------------------------
        
        The ``llvmlite.llvmpy`` namespace provides a minimal llvmpy compatibility
        layer.
        
        
        Compatibility
        =============
        
        llvmlite works with Python 3.6 and greater.
        
        As of version 0.33.0, llvmlite requires LLVM 9.0.x.
        
        Historical compatibility table:
        
        =================  ========================
        llvmlite versions  compatible LLVM versions
        =================  ========================
        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
        
Platform: UNKNOWN
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 :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Software Development :: Code Generators
Classifier: Topic :: Software Development :: Compilers
Requires-Python: >=3.6
