How to contribute to r5py#

Contributions of any kind to r5py 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 a bug report. In addition, we warmly welcome ideas of new features that could be added to the r5py, or ideas on how to improve the existing codebase.

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 r5py transparent.

If you decide to contribute to the codebase, ensure that you are using an up-to-date main branch. The latest development version will always be there, including the documentation (powered by sphinx).

Seven Steps for Contributing#

There are seven basic steps to contributing to r5py:

  1. Fork the r5py git repository

  2. Create a development environment with r5py dependencies

  3. Make a development build of r5py

  4. Make changes to the code and add tests

  5. Update the documentation

  6. Format and lint the code

  7. Submit a Pull Request

Each of the steps is detailed below.

1. Fork the r5py 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 or PyCharm. However, if you want to use command line, you can fork the r5py repository using following:

git clone r5py-yourname
cd r5py-yourname
git remote add upstream git://

This creates the directory r5py-yourname and connects your repository to the upstream (main project) r5py repository.

Then simply create a new branch of main branch.

2. Create a development environment#

A development environment is a virtual space where you can keep an independent installation of r5py. 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 r5py development environment is as follows:

Tell mamba to create a new environment from a YAML file inside ci directory, by running:

mamba env create -f ci/python_311_dev.yaml

This will create a new environment called r5py, and not touch any of your existing environments, nor existing python installations. The environment includes all necessary dependencies for r5py, as well as optional packages for running tests and building docs. With this environment, you can directly start working with r5py.

To work in this environment, you should activate it as follows:

conda activate r5py

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.

3. Make a development build#

Once dependencies are in place, make an in-place build by navigating to the git clone of the r5py repository and run:

pip install .

This will install r5py from the source into your environment.

4. Make changes and write tests#

r5py 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.

r5py uses the pytest testing system.

Write 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.

Run the test suite#

The tests can then be run directly inside your Git clone without having to install r5py. Run the tests by typing (v means verbose):

pytest -v

5. Update the documentation and user guide#

r5py documentation resides in the docs folder. Changes to the docs are make by modifying the appropriate file within docs. r5py docs uses Myst notebooks, a format for executable notebooks using a syntax based on Markdown. 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 (comes with r5py environment if installed from the YAML file). To do so, you can navigate to the docs folder and type:

python -m sphinx . _build

The resulting html pages will be located in docs/_build/html/.

6. Format the code#

Python (PEP8 / black)#

r5py 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::

black src

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

Import order, import of submodules#

R5py uses jpype, with the help of which Java classes can be imported using normal import statements. As a consequence, the order of import statements at the beginning of source files plays a crucial role.

By convention, in r5py source files, the import statements should be grouped in the following order:

  1. Imports of modules of the Python Standard Library

  2. Imports of third-party Python modules

  3. Relative imports of other r5py modules

  4. Imports of Java classes

The modules of each group should be sorted alphabetically, the groups be separated by an empty line.

The import of submodules (from ... import ...), as well as the use of aliases for imported modules (import ... as ...) are discouraged. An exception to this rule, assets from other modules from within r5py should always be imported as submodules (from . import TravelTimeMatrixComputer).

7. Submit 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 r5py code base.

You can find a pull request (or PR) tutorial in the GitHub’s Help Docs.


These contribution guidelines are largely based on pyrosm and momepy -libraries.