Setting up Matplotlib for development

Creating a dedicated environment

You should set up a dedicated environment to decouple your Matplotlib development from other Python and Matplotlib installations on your system. Here we use python's virtual environment venv, but you may also use others such as conda.

A new environment can be set up with

python -m venv <file folder location>

and activated with one of the following:

source <file folder location>/bin/activate  # Linux/macOS
<file folder location>\Scripts\activate.bat  # Windows cmd.exe
<file folder location>\Scripts\Activate.ps1  # Windows PowerShell

Whenever you plan to work on Matplotlib, remember to activate the development environment in your shell.

Retrieving the latest version of the code

Matplotlib is hosted at

You can retrieve the latest sources with the command (see Set up your fork for more details):

git clone

This will place the sources in a directory matplotlib below your current working directory.

If you have the proper privileges, you can use git@ instead of https://, which works through the ssh protocol and might be easier to use if you are using 2-factor authentication.

Installing Matplotlib in editable mode

Install Matplotlib in editable mode from the matplotlib directory using the command

python -m pip install -ve .

The 'editable/develop mode', builds everything and places links in your Python environment so that Python will be able to import Matplotlib from your development source directory. This allows you to import your modified version of Matplotlib without re-installing after every change. Note that this is only true for *.py files. If you change the C-extension source (which might also happen if you change branches) you will have to re-run python -m pip install -ve .

Installing additional dependencies for development

See Additional dependencies for development.