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1 parent 0b1c666 commit 429d28f64a670d2e033de4c7cd96503861e64aa0 @markflorisson markflorisson committed Apr 4, 2013
Showing with 123 additions and 29 deletions.
  1. +3 −1 conf.py
  2. +84 −28 index.rst
  3. +36 −0 install.rst
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@@ -23,6 +23,8 @@
# If your documentation needs a minimal Sphinx version, state it here.
#needs_sphinx = '1.0'
+html_theme = 'basic'
+
# Add any Sphinx extension module names here, as strings. They can be extensions
# coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
extensions = ['sphinx.ext.mathjax', 'sphinx.ext.ifconfig']
@@ -50,7 +52,7 @@
# The short X.Y version.
version = '0.7'
# The full version, including alpha/beta/rc tags.
-release = '0.7.0'
+release = '0.7.2'
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
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@@ -1,48 +1,104 @@
-numba is a NumPy aware dynamic compiler for Python. It creates LLVM bit-code from Python syntax and then creates a wrapper around that bitcode to call from Python
+********************
+Numba
+********************
+
+Numba is an just-in-time specializing compiler which compiles
+annotated Python and NumPy code to LLVM (through decorators). Its goal
+is to seamlessly integrate with the Python scientific software stack
+and produce optimized native code, as well as integrate with native foreign
+languages.
Example
=======
.. code-block:: python
- from numba import autojit
+ from numba import autojit
+
+ @autojit
+ def sum2d(arr):
+ M, N = arr.shape
+ result = 0.0
+ for i in range(M):
+ for j in range(N):
+ result += arr[i,j]
+ return result
+
+More examples: `examples <http://numba.pydata.org/numba-doc/dev/doc/examples.html>`_.
+
+Documentation
+=============
+
+* http://numba.pydata.org/doc.html
+
+Source and Downloads
+====================
+
+* Github: https://github.com/numba/numba
+
+.. code-block:: bash
+
+ $ git clone git://github.com/numba/numba.git
+
+.. _install_frontpage:
+
+For tarballs see:
+
+.. toctree::
+ :titlesonly:
+ :maxdepth: 2
+
+ download.rst
- @autojit
- def sum2d(arr):
- M, N = arr.shape
- result = 0.0
- for i in range(M):
- for j in range(N):
- result += arr[i,j]
- return result
+.. :ref:`Download Numba <download>`
-QuickStart
+Installing
==========
-The easiest way to get started with Numba is to either:
+The easiest way to install numba and get updates is by using the Anaconda
+Distribution: http://continuum.io/downloads.html
- 1) Download Anaconda (a free Python distribution) from here: http://continuum.io/downloads.html
- 2) Get a Wakari account and interact on-line: http://wakari.io
+If you have anaconda installed already:
-If you want to build things yourself, then this can help get you started:
+.. code-block:: bash
+
+ $ conda install numba
- * Get and install llvmpy at http://www.llvmpy.org
- * Get and install Meta
- * Get and install numba
+or
.. code-block:: bash
- git clone https://github.com/numba/Meta.git
- cd meta
- python setup.py install
- git clone https://github.com/numba/numba.git
- cd numba
- python setup.py install
+ $ conda update numba
-This project is maintained by `Continuum Analytics <http://www.continuum.io>`_
+For custom python environments see:
.. toctree::
- :hidden:
+ :titlesonly:
+ :maxdepth: 1
+
+ install.rst
+
+Mailing Lists
+=============
+
+Join the numba mailing list numba-users@continuum.io :
+
+ * https://groups.google.com/a/continuum.io/d/forum/numba-users
+
+Some old archives are at:
+
+ * http://librelist.com/browser/numba/
+
+Website
+=======
+
+See if our sponsor can help you (which can help this project):
+
+ * http://www.continuum.io
+ * http://numba.pydata.org
+
+Continuous Integration
+======================
+
+* https://travis-ci.org/numba/numba
- doc
- download
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@@ -0,0 +1,36 @@
+.. _custom:
+
+Custom Python Environments
+==========================
+
+If you're not using anaconda, you will need LLVM with RTTI enabled:
+
+* Compile LLVM 3.2
+
+.. code-block:: bash
+
+ $ wget http://llvm.org/releases/3.2/llvm-3.2.src.tar.gz
+ $ tar zxvf llvm-3.2.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
+
+* Installing Numba
+
+.. code-block:: bash
+
+ $ git clone https://github.com/numba/numba.git
+ $ cd numba
+ $ pip install -r requirements.txt
+ $ python setup.py install
+
+or simply
+
+.. code-block:: bash
+
+ $ pip install numba
+
+**NOTE:** Make sure you install *distribute* instead of setuptools. Using setuptools
+ may mean that source files do not get cythonized and may result in an
+ error during installation.

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