NumPy aware dynamic Python compiler using LLVM
Python C
Pull request Compare This branch is 1 commit ahead, 9743 commits behind numba:master.
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Failed to load latest commit information.


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 byte-code to
machine code especially for use in the NumPy run-time and SciPy

Not all Python syntax is supported, currently.  And long-term,
the best that will be done with some Python constructs is to 
eliminate the "interpreter".  Numba is going to work well first with 
NumPy arrays that are large arrays of typed information.

If you are looking for a full Python compiler to handle all Python syntax,
look at PyPy, ShedSkin, Nutika, or other projects.

Numba is also not a tracing jit.  It *compiles* your code before it gets
run using type information you provide in the decorator.


  * LLVM 3.1
  * llvm-py (from llvmpy/llvmpy fork)
  * numpy
  * Meta (from numba/Meta fork)

* Compile LLVM 3.1: 

tar zxvf llvm-3.1.src.tar.gz
./configure --enable-optimized
# Be sure your compiler architecture is same as version of Python you will use
#  e.g. -arch i386 or -arch x86_64.  It might be best to be explicit about this.
make install

* Clone LLVM-py from github
git clone
python install

* Clone Meta from github
git clone
python install

* Be sure to initialize the minivect submodule (in numba top-level dir)
git submodule init
git submodule update

* Build Numba
python install

* Follow Numba
Join the numba mailinglist

Some old archives are at

* See if our sponsor can help you (which can help this project)