Contributor quickstart guide#

After getting the source code from GitHub, there are three steps to start contributing:

  1. Set up a development environment

    Using conda, or some flavor of the many virtual environment management tools, you can make sure the development version of SciPy does not interfere with any other local installations of SciPy on your machine.

  2. Build SciPy

    SciPy uses compiled code for speed, which means you might need extra dependencies to complete this step depending on your system.

  3. Perform development tasks

    These can include any changes you want to make to the source code, running tests, building the documentation, running benchmarks, etc.

Basic workflow#


We strongly recommend using a virtual environment setup, such as venv or conda.

Since SciPy contains parts written in C, C++, and Fortran that need to be compiled before use, make sure you have the necessary compilers and Python development headers installed. If you are using conda, these will be installed automatically. If you are using pip, check which system-level dependencies you might need.

First, fork a copy of the main SciPy repository in GitHub onto your own account and then create your local repository via:

git clone scipy
cd scipy
git submodule update --init
git remote add upstream

Next, set up your development environment.

With conda installed (through Miniforge or Mambaforge, Miniconda or Anaconda), execute the following commands at the terminal from the base directory of your SciPy clone:

# Create an environment with all development dependencies
conda env create -f environment.yml  # works with `mamba` too
# Activate the environment
conda activate scipy-dev

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

Finally, build SciPy for development and run the test suite to make sure your installation is successful. On Linux and OSX, you should use:


This builds SciPy first, so the first time it may take some time.

If you run into a build issue, or need more detailed build documentation including building on Windows, see Building from sources.

Some of the tests in SciPy are very slow and need to be separately enabled. See Running SciPy Tests Locally for details.

Other workflows#

This is only one possible way to set up your development environment out of many. For more detailed instructions, see the SciPy contributor guide.