Contributing to r5py
Contents
Contributing 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 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 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).
Eight Steps for Contributing¶
There are eight basic steps to contributing to r5py:
Fork the r5py git repository
Create a development environment
Install r5py dependencies
Make a development build of r5py
Make changes to code and add tests
Update the documentation
Format code
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.org, GitHub Desktop or tools with included git like Atom or PyCharm. However, if you want to use command line, you can fork r5py repository using following:
git clone git@github.com:your-user-name/r5py.git r5py-yourname
cd r5py-yourname
git remote add upstream git://github.com/r5py/r5py.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 master 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:
Install miniconda
Make sure that you have cloned the repository
cdto the r5py source directory
Tell conda to create a new environment, named r5py, or any other name you would like
for this environment, by running::
conda create -n r5py
This will create the new environment, and not touch any of your existing environments, nor any existing python installation.
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::
deactivate
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 r5py in an development environment, you must first install r5py’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 configargparse geopandas joblib jpype1 pandas psutil requests pytest pytest-cov codecov requests black
This should install all necessary dependencies including optional and packages for running tests.
4. Making a development build¶
Once dependencies are in place, make an in-place build by navigating to the git clone of the r5py repository and running:
pip install .
This will install r5py from the source into your environment.
5. Making changes and writing 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.
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 r5py) by typing::
pytest
6. Updating 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 use a combination of reStructuredText syntax which is explained here,
Jupyter Notebooks (read more 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 docs folder and type::
make html
The resulting html pages will be located in docs/build/html. In case of any errors, you can try to use make html within a new environment based on the libraries in the requirements.txt in the docs folder.
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)¶
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:
Imports of modules of the Python Standard Library
Imports of third-party Python modules
Relative imports of other r5py modules
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).
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 r5py code base.
You can find a pull request (or PR) tutorial in the GitHub’s Help Docs.