These are general instructions for installing packages in the SciPy ecosystem.
Scientific Python distributions¶
For many users, especially on Windows, the easiest way to begin is to download one of these Python distributions, which include all the key packages:
- Anaconda: A free distribution of Python with scientific packages. Supports Linux, Windows and Mac.
- Enthought Canopy: The free and commercial versions include the core scientific packages. Supports Linux, Windows and Mac.
- Python(x,y): A free distribution including scientific packages, based around the Spyder IDE. Windows and Ubuntu; Py2 only.
- WinPython: Another free distribution including scientific packages and the Spyder IDE. Windows only, but more actively maintained and supports the latest Python 3 versions.
- Pyzo: A free distribution based on Anaconda and the IEP interactive development environment. Supports Linux, Windows and Mac.
Installing via pip¶
Note that you need to have Python and pip already installed on your system.
You can install packages via commands such as:
python -m pip install --user numpy scipy matplotlib ipython jupyter pandas sympy nose
We recommend using an user install, using the
--user flag to pip
(note: do not use
sudo pip, which can cause problems). This
installs packages for your local user, and does not write to the
Install system-wide via a Linux package manager¶
Users on Linux can install packages from repositories provided by the distributions. These installations will be system-wide, and may have older package versions than those available using pip.
Ubuntu & Debian
sudo apt-get install python-numpy python-scipy python-matplotlib ipython ipython-notebook python-pandas python-sympy python-nose
Users might also want to add the NeuroDebian repository for extra SciPy packages.
Fedora 22 and later:
sudo dnf install numpy scipy python-matplotlib ipython python-pandas sympy python-nose atlas-devel
Install system-wide via a Mac package manager¶
Macs don’t have a preinstalled package manager, but there are a couple of popular package managers you can install.
For Python 3.5 with Macports execute this command in a terminal:
sudo port install py35-numpy py35-scipy py35-matplotlib py35-ipython +notebook py35-pandas py35-sympy py35-nose
Homebrew no longer packages NumPy or other packages of the scientific Python stack. If you’re a Homebrew user, install Python3 with Homebrew and the rest with pip:
python -m pip install numpy scipy matplotlib
Official binary and source packages for most projects are available
pip as explained above.
Binary packages are also available from third parties, such as the Python distributions above. For Windows, Christoph Gohlke provides pre-built Windows installers for many packages.
You can build any of the 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.