SciPy Website

Site Navigation

Table Of Contents

Previous topic

Scientific Computing Tools For Python

Next topic

Frequently Asked Questions

Obtaining NumPy & SciPy

Official Source and Binary Releases

For each official release of NumPy and SciPy, we provide source code (tarball) as well as binary packages for several major platforms. Binary packages for other platforms may be available from your operating system vendor.

Project Available packages Download location
NumPy Official source code (all platforms) and binaries for Windows & Mac OS X SourceForge site for NumPy
SciPy Official source code (all platforms) and binaries for Windows & Mac OS X SourceForge site for SciPy

Build instructions are available for linux, windows and Mac OSX.

Bleeding Edge Repository Access

The most recent development versions of NumPy and SciPy are available through the official repositories hosted on Github.

To check out the latest NumPy sources:

git clone git:// numpy

or (if you’re behind a proxy blocking git ports)

git clone numpy

To check out the latest SciPy sources:

git clone git:// scipy


git clone scipy

Software Distributions that include NumPy/SciPy

A number of software distributions exist that bundle NumPy and SciPy along with a variety of other tools, including data file manipulation packages, visualization tools and more general software development tools. Such distributions can be an excellent way to get started with Python for scientific computing.

We present a list of the most prominent such distributions below. They vary in terms of platform/operating system support, license (free/commercial), packages included, and general focus (general/interactive scientific computing vs. mathematics/computer algebra vs. scientific software/GUI development). If you hope to transition to using Python as your every day scientific computing environment, these distributions are well worth investigating.

Enthought Python Distribution

The Enthought Python Distribution (EPD) is a “kitchen-sink-included” distribution of the Python programming language, including over 80 additional tools and libraries. The EPD bundle includes NumPy, SciPy, IPython, 2D and 3D visualization, database adapters, and a lot of other tools right out of the box.

It is currently available as a single-click installer for Windows XP (x86), Mac OS X (a universal binary for OS X 10.4 and above), RedHat 3, 4 and 5, as well as Solaris 10 (x86 and x86_64/amd64).

EPD is free for academic use. An annual subscription including installation support is available for individual and commercial use. You can download a 30-day free trial at the Enthought website.


Python(x,y) is a distribution of free/open source scientific and engineering software for Microsoft Windows XP/Vista (although there is an effort underway to develop an Ubuntu Linux version) based around Qt and Eclipse. It aims to provide an environment for interactive scientific computing as well as more development-oriented features such as integrated GUI design tools for scientific software development. More details as well as downloads are available on at the Python(x,y) website.


Sage is a monolithic distribution of a wide variety of open source mathematical software available in both source and binary forms for a number of operating systems, including Linux (x86/amd64), Mac OS X, Solaris, and Windows (through VMware Player). A bootable Sage LiveCD is also available.

Sage bundles recent versions of both NumPy and SciPy, along with its own Python interpreter. See the Sage Installation Guide for installation instructions.

SciPy Superpack (OS X)

The Superpack provides bleeding edge binaries of NumPy and SciPy from recent Subversion checkouts, maintained by Chris Fonnesbeck. It is available from

The Superpack requires Mac OS X 10.5 Leopard with either Apple’s preinstalled Python 2.5.1, ActivePython 2.5 or Python 2.5 from Note that the Superpack’s version detection may fail with other Python distributions (e.g. Python installed by Fink and MacPorts) and it will refuse to install. If you are using Python provided by Fink or MacPorts it is recommended that you install NumPy/SciPy with the appropriate packages (see Third-Party/Vendor Package Managers below).

NOTE: NumPy is included in the Superpack. For best compatibility, it is recommended that you use the NumPy provided with the Superpack rather than a separately installed version.

Source Python Distribution

Source Python Distribution (SPD) is a Python distribution based on Sage, containing many optional (mainly scientific) packages that build from source. It contains only a small subset of Sage (an approximately 60 MB download compared with Sage’s several hundred megabytes). It bundles recent versions of NumPy and SciPy, and is compatible with Sage’s packages format so that you can selectively install other pieces of software included in Sage but not in SPD. See the SPD website for details.

Third-Party/Vendor Package Managers

Below is a partial list of third-party and operating system vendor package managers containing NumPy and SciPy packages.

These packages are not maintained by the NumPy and SciPy developers; this list is provided only as a convenience. These packages may not always provide the most up to date version of the software, and may be unmaintained.

IMPORTANT: If you experience problems with these packages (especially those related to installation/build errors), please report the problem to the package maintainer first, rather than to the NumPy/SciPy mailing lists.

Distribution NumPy Packages SciPy Packages
Arch Linux python-numpy python-scipy
Debian GNU/Linux python-numpy python-scipy
Ubuntu Linux python-numpy python-scipy
Fedora numpy scipy
Fink scipy-core-py24, scipy-core-py25, scipy-core-py26 scipy-py24, scipy-py25, scipy-py26
FreeBSD Ports ports/math/py-numpy ports/science/py-scipy
Gentoo Linux dev-python/numpy sci-libs/scipy
MacPorts py-numpy, py25-numpy, py26-numpy py-scipy, py25-scipy, py26-scipy
NetBSD (pkgsrc) math/py-numpy math/py-scipy
OpenSUSE python-numpy, python-numpy-devel python-scipy, python-scipy-devel
Slackware Linux numpy ( scipy (