Installing the SciPy Stack¶
Scientific Python distributions¶
For most users, especially on Windows and Mac, the easiest way to install the packages of the SciPy stack is to download one of these Python distributions, which includes all the key packages:
- Anaconda: A free distribution for the SciPy stack. Supports Linux, Windows and Mac.
- Enthought Canopy: The free and commercial versions include the core SciPy stack packages. Supports Linux, Windows and Mac.
- Python(x,y): A free distribution including the SciPy stack, based around the Spyder IDE. Windows only.
- WinPython: A free distribution including the SciPy stack. Windows only.
- Pyzo: A free distribution based on Anaconda and the IEP interactive development environment. Supports Linux, Windows and Mac.
Users on Linux can quickly install the necessary packages from repositories.
Ubuntu & Debian¶
sudo apt-get install python-numpy python-scipy python-matplotlib ipython ipython-notebook python-pandas python-sympy python-nose
The versions in Ubuntu 12.10 and Debian 7.0 meet the current SciPy stack specification. Users might also want to add the NeuroDebian repository for extra SciPy packages.
sudo yum install numpy scipy python-matplotlib ipython python-pandas sympy python-nose
Users of Fedora 17 and earlier should then upgrade IPython using pip:
sudo pip install --upgrade ipython
sudo emerge -aN '>=dev-python/numpy-1.6' '>=sci-libs/scipy-0.10' '>=dev-python/matplotlib-1.1' '>=dev-python/ipython-0.13' '>=dev-python/pandas-0.8' '>=dev-python/sympy-0.7' '>=dev-python/nose-1.1'
You may get some messages saying that keyword changes or USE changes are
necessary in order to proceed, and that you should use
write changes to config files. This is especially likely to happen if you are
running Gentoo Stable rather than Gentoo Testing, as of this writing (February
If this happens, just run the above command with
appended, then run
sudo dispatch-conf (or an alternative) to save the
configuration changes, and finally run the original command again.
Macs (unlike Linux) don’t come with a package manager, but there are a couple of popular package managers you can install.
Individual binary and source packages¶
The maintainers of many of the packages in the SciPy stack provide “official” binary installers for common Windows and OS-X systems that can be used to install the packages one by one. These installers are generally built to be compatible with the Python binaries available from python.org.
For Windows: Christoph Gohlke provides pre-built Windows installers for many Python packages, including all of the core SciPy stack.
You can also build any of the SciPy packages from source, for instance if you want to get involved with development. This is easy for packages written entirely in Python, while others like NumPy require compiling C code. Refer to individual projects for more details.