Development environment quickstart guide using pip on Ubuntu Linux

This is a high-level overview of what is needed to set up a development environment. This is only one possible way out of many. This guide assumes you have a fresh install of Ubuntu Linux 20.04, which only has a python3 executable. We also assume you have already installed git and cloned the SciPy repository.

Installing the system-level dependencies

First, you will also need the compilers for C, C++ and Fortran:

sudo apt install -y gcc g++ gfortran

SciPy also requires BLAS and LAPACK libraries. You can install several variants (ATLAS, OpenBLAS etc), but here we take the simplest option:

sudo apt install -y liblapack-dev

Installing the python-level dependencies

Start with installing pip:

sudo apt install -y python3-pip

All further work should proceed in a virtual environment. Popular options include the standard library venv module or a separate virtualenv package. There are muliple third-party tutorials on how to set up a virtual environment, so we cover only briefly these two options here.

Note

We repeat: all work should happen in a virtual environment. Never use sudo pip.

Using virtualenv

Install the virtualenvwrapper package:

python3 -m pip install virtualenvwrapper --user

Edit the .bashrc file to add some environment variables which are used internally by the virtualenvwrapper:

export WORKON_HOME=$HOME/virtualenvs
export VIRTUALENVWRAPPER_PYTHON=/usr/bin/python3
. $HOME/.local/bin/virtualenvwrapper.sh

Here we store the virtualenvs in a virtualenvs folder in the home directory. (you might need to create the folder manually).

Now open a new terminal window for the changes to the .bashrc to take effect.

Create a new virtual environment and activate it:

mkvirtualenv scipy-dev

Your command prompt now lists the name of your new environment, like so (scipy-dev)$. This means that the environment is active. If it is not, activate it manually with:

workon scipy-dev

Note mkvirtualenv and workon commands come from the virtualwrapper package.

Using the standard-library venv package

Install the venv package:

sudo apt install -y python3-venv

Change the directory to your home folder and create a directory .venvs there. Create the virtualenvironment:

python3 -m venv scipy-dev

To activate the environment, use

source $HOME/.venvs/scipy-dev/bin/activate

Your command prompt now lists the name of your new environment, like so (scipy-dev)$.

(For the official docs for the venv package see https://docs.python.org/3/tutorial/venv.html).

Building SciPy

Inside the scipy-dev environment, install the python-level dependencies:

python -m pip install numpy pytest cython pybind11

Note that when the virtual environment is active, the system-wide names pip3 and python3 are aliased to pip and python, respectively.

Now that you have all needed dependencies, navigate to the directory where you cloned the source code into, and build SciPy (this takes a while):

python setup.py build

Optionally, test it:

python runtests.py