<commit_before>=====
Numba
=====

A compiler for Python array and numerical functions
---------------------------------------------------

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.


Dependencies
============

* llvmlite
* numpy (version 1.7 or higher)
* funcsigs (for Python 2)


Installing
==========<commit_msg>Fix README rendering in pypi Checked with `python setup.py -r`<commit_after>*****
Numba
*****

A compiler for Python array and numerical functions
###################################################

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.


Dependencies
============

* llvmlite
* numpy (version 1.7 or higher)
* funcsigs (for Python 2)


Installing
==========
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