Contributing to momepy

(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 momepy transparent.

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).

Eight Steps for Contributing

There are seven basic steps to contributing to momepy:

  1. Fork the momepy git repository

  2. Create a development environment

  3. Install momepy dependencies

  4. Make a development build of momepy

  5. Make changes to code and add tests

  6. Update the documentation

  7. Format code

  8. Submit a Pull Request

Each of the steps is detailed below.

1. Fork the momepy git repository

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 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 momepy-yourname
cd momepy-yourname
git remote add upstream 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.

2. Create a development environment

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 miniconda

  • 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:

activate momepy_dev

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.

3. Installing Dependencies

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.

4. Making a development build

Once dependencies are in place, make an in-place build by navigating to the git clone of the momepy repository and running:

python develop

This will install momepy into your environment but allows any further changes without the need of reinstalling new version.

5. Making changes and writing tests

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.

Writing tests

All tests should go into the tests directory. This folder contains many current examples of tests, and we suggest looking to these for inspiration.

Running the test suite

The tests can then be run directly inside your Git clone (without having to install momepy) by typing:


6. Updating the Documentation and User Guide

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:

make html

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. Using conda:

conda env create -f environment.yml
conda activate geopandas_docs
make html

For minor updates, you can skip whole make html part as reStructuredText syntax is usually quite straightforward.

Updating User Guide

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.

7. Formatting the code

Python (PEP8 / black)

momepy follows the PEP8 standard and uses Black to ensure a consistent code format throughout the project.

Travis 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:

black momepy

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

8. Submitting a Pull Request

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.