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 https://github.com/matplotlib/matplotlib.git.
You can retrieve the latest sources with the command (see Set up your fork for more details):
git clone https://github.com/matplotlib/matplotlib.git
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 .