(Contribution guidelines are largely based on geopandas.)
Contributions of any kind to momepy are more than welcome. That does not mean
new code only, but also improvements of documentation and user guide, additional
tests (ideally filling the gaps in existing suite) or bug report or idea what
could be added or done better.
All contributions should go through our GitHub repository. Bug reports, ideas or
even questions should be raised by opening an issue on the GitHub tracker.
Suggestions for changes in code or documentation should be submitted as a pull
request. However, if you are not sure what to do, feel free to open an issue.
All discussion will then take place on GitHub to keep the development of
If you decide to contribute to the codebase, ensure that you are using an
up-to-date master branch. The latest development version will always be there,
including the documentation (powered by sphinx).
There are seven basic steps to contributing to momepy:
Fork the momepy git repository
Create a development environment
Install momepy dependencies
Make a development build of momepy
Make changes to code and add tests
Update the documentation
Submit a Pull Request
Each of the steps is detailed below.
Git can be complicated for new users, but you no longer need to use command line
to work with git. If you are not familiar with git, we recommend using tools on
GitHub.org, GitHub Desktop or tools with included git like Atom. However, if you
want to use command line, you can fork momepy repository using following:
git clone firstname.lastname@example.org:your-user-name/momepy.git momepy-yourname
git remote add upstream git://github.com/martinfleis/momepy.git
This creates the directory momepy-yourname and connects your repository to
the upstream (main project) momepy repository.
Then simply create a new branch of master branch.
A development environment is a virtual space where you can keep an independent
installation of momepy. This makes it easy to keep both a stable version of
python in one place you use for work, and a development version (which you may
break while playing with code) in another.
An easy way to create a momepy development environment is as follows:
Install either Anaconda or
Make sure that you have cloned the repository
cd to the momepy source directory
Tell conda to create a new environment, named momepy_dev, or any other name you would like
for this environment, by running:
conda create -n momepy_dev
This will create the new environment, and not touch any of your existing environments,
nor any existing python installation.
To work in this environment, Windows users should activate it as follows:
macOS and Linux users should use:
conda activate momepy_dev
You will then see a confirmation message to indicate you are in the new development environment.
To view your environments:
conda info -e
To return to you home root environment:
See the full conda docs here.
At this point you can easily do a development install, as detailed in the next sections.
To run momepy in an development environment, you must first install
momepy’s dependencies. We suggest doing so using the following commands
(executed after your development environment has been activated)
to ensure compatibility of all dependencies:
conda config --env --add channels conda-forge
conda config --env --set channel_priority strict
conda install geopandas networkx libpysal tqdm pysal mapclassify pytest
This should install all necessary dependencies including optional.
Once dependencies are in place, make an in-place build by navigating to the git
clone of the momepy repository and running:
python setup.py develop
This will install momepy into your environment but allows any further changes
without the need of reinstalling new version.
momepy is serious about testing and strongly encourages contributors to embrace
test-driven development (TDD).
This development process “relies on the repetition of a very short development cycle:
first the developer writes an (initially failing) automated test case that defines a desired
improvement or new function, then produces the minimum amount of code to pass that test.”
So, before actually writing any code, you should write your tests. Often the test can be
taken from the original GitHub issue. However, it is always worth considering additional
use cases and writing corresponding tests.
momepy uses the pytest testing system.
All tests should go into the tests directory. This folder contains many
current examples of tests, and we suggest looking to these for inspiration.
The tests can then be run directly inside your Git clone (without having to
install momepy) by typing:
momepy documentation resides in the docs folder. Changes to the docs are
make by modifying the appropriate file within doc.
momepy docs us reStructuredText syntax, which is explained here
and the docstrings follow the Numpy Docstring standard.
Once you have made your changes, you may try if they render correctly by building the docs using sphinx.
To do so, you can navigate to the doc folder and type:
The resulting html pages will be located in doc/build/html. In case of any errors,
you can try to use make html within a new environment based on environment.yml specification in the doc folder.
conda env create -f environment.yml
conda activate geopandas_docs
For minor updates, you can skip whole make html part as reStructuredText syntax is
usually quite straightforward.
Updating user guide might be slightly more complicated as it
consists of collection of reStructuredText files and Jupyter notebooks.
Changes in reStructuredText are straightforward, changes in notebooks should be done using Jupyter. Make sure that all cells have their correct outputs as notebooks
are not executed by readthedocs.
momepy follows the PEP8 standard
and uses Black to ensure a consistent code format throughout the project.
CI will run black --check and fails if there are files which would be
auto-formatted by black. Therefore, it is helpful before submitting code to
auto-format your code:
Additionally, many editors have plugins that will apply black as you edit files.
If you don’t have black, you can install it using pip:
pip install black
Once you’ve made changes and pushed them to your forked repository, you then
submit a pull request to have them integrated into the momepy code base.
You can find a pull request (or PR) tutorial in the GitHub’s Help Docs.