<commit_before>*****************************
Building and installing NumPy
*****************************

Binary installers
=================

In most use cases the best way to install NumPy on your system is by using an
installable binary package for your operating system.

Windows
-------

Good solutions for Windows are, `Enthought Canopy
<https://www.enthought.com/products/canopy/>`_ (which provides binary
installers for Windows, OS X and Linux) and `Python (x, y)
<http://www.pythonxy.com>`_. Both of these packages include Python, NumPy and
many additional packages.

A lightweight alternative is to download the Python
installer from `www.python.org <http://www.python.org>`_ and the NumPy
installer for your Python version from the Sourceforge `download site <http://
sourceforge.net/project/showfiles.php?group_id=1369&package_id=175103>`_

The NumPy installer includes binaries for different CPU's (without SSE
instructions, with SSE2 or with SSE3) and installs the correct one
automatically. If needed, this can be bypassed from the command line with ::

  numpy-<1.y.z>-superpack-win32.exe /arch nosse

or 'sse2' or 'sse3' instead of 'nosse'.

Linux
-----

Most of the major distributions provide packages for NumPy, but these can lag
behind the most recent NumPy release. Pre-built binary packages for Ubuntu are
available on the `scipy ppa
<https://edge.launchpad.net/~scipy/+archive/ppa>`_. Redhat binaries are
available in the `EPD <http://www.enthought.com/products/epd.php>`_.

Mac OS X
--------

A universal binary installer for NumPy is available from the `download site
<http://sourceforge.net/project/showfiles.php?group_id=1369&
package_id=175103>`_. The `EPD <http://www.enthought.com/products/epd.php>`_
provides NumPy binaries.

Building from source
====================
<commit_msg>DOC: replacing old reference from EPD to Canopy<commit_after>*****************************
Building and installing NumPy
*****************************

Binary installers
=================

In most use cases the best way to install NumPy on your system is by using an
installable binary package for your operating system.

Windows
-------

Good solutions for Windows are, `Enthought Canopy
<https://www.enthought.com/products/canopy/>`_ (which provides binary
installers for Windows, OS X and Linux) and `Python (x, y)
<http://www.pythonxy.com>`_. Both of these packages include Python, NumPy and
many additional packages.

A lightweight alternative is to download the Python
installer from `www.python.org <http://www.python.org>`_ and the NumPy
installer for your Python version from the Sourceforge `download site <http://
sourceforge.net/project/showfiles.php?group_id=1369&package_id=175103>`_

The NumPy installer includes binaries for different CPU's (without SSE
instructions, with SSE2 or with SSE3) and installs the correct one
automatically. If needed, this can be bypassed from the command line with ::

  numpy-<1.y.z>-superpack-win32.exe /arch nosse

or 'sse2' or 'sse3' instead of 'nosse'.

Linux
-----

Most of the major distributions provide packages for NumPy, but these can lag
behind the most recent NumPy release. Pre-built binary packages for Ubuntu are
available on the `scipy ppa
<https://edge.launchpad.net/~scipy/+archive/ppa>`_. Redhat binaries are
available in the `Enthought Canopy
<https://www.enthought.com/products/canopy/>`_.

Mac OS X
--------

A universal binary installer for NumPy is available from the `download site
<http://sourceforge.net/project/showfiles.php?group_id=1369&
package_id=175103>`_. The `Enthought Canopy
<https://www.enthought.com/products/canopy/>`_ provides NumPy binaries.

Building from source
====================

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