🌍💫 We're excited that you're here and want to contribute. 💫🌍
By joining our efforts, you will be helping to push the frontiers of environmental sciences.
We want to ensure that every user and contributor feels welcome, included and supported to participate in DeepSensor community. Whether you're a seasoned developer, a machine learning researcher, an environmental scientist, or just someone eager to learn and contribute, you are welcome here. We value every contribution, be it big or small, and we appreciate the unique perspectives you bring to the project.
We hope that the information provided in this document will make it as easy as possible for you to get involved. If you find that you have questions that are not discussed below, please let us know through one of the many ways to get in touch.
If you'd like to find out more about DeepSensor, make sure to check out:
- README: For a high-level overview of the project, please refer to our README.
- Documentation: For more detailed information about the project, please refer to our documentation.
- Project Roadmap: Familiarize yourself with our direction and goals by checking out the project's roadmap.
The easiest way to get involved with the active development of DeepSensor is to join our regular community calls. The community calls are currently on a hiatus but if you are interested in participating in the forthcoming community calls, which will start in 2024, you should join our Slack workspace, where conversation about when to hold the community calls in the future will take place.
Slack Workspace: Join our DeepSensor Slack channel for discussions, queries, and community interactions. In order to join, sign up for the Turing Environment & Sustainability stakeholder community. The form includes a question on signing up for the Slack team, where you can find DeepSensor's channel.
Email: If you prefer a more formal communication method or have specific concerns, please reach us at [email protected].
We welcome contributions of all kinds, be it code, documentation, raising issues, or community engagement. We encourage you to read through the following sections to learn more about how you can contribute to
We follow the same instructions for submitting changes to the project as those developed by The Turing Way. In short, there are five steps to adding changes to this repository:
- Fork the Repository: Start by forking the DeepSensor repository.
- Make Changes: Ensure your code adheres to the style guidelines and passes all tests.
- Commit and Push: Use clear commit messages.
- Open a Pull Request: Ensure you describe the changes made and any additional details.
Once you have created a fork of the repository, you now have your own unique local copy of DeepSensor. Changes here won't affect anyone else's work, so it's a safe space to explore edits to the code!
Make sure to keep your fork up to date with the main repository, otherwise, you can end up with lots of dreaded merge conflicts.
If you prefer working with GitHub in the browser, these instructions describe how to sync your fork to the original repository.
Try to keep the changes focused. If you submit a large amount of work all in one go it will be much more work for whoever is reviewing your pull request. Help them help you! 😉
Are you new to Git and GitHub or just want a detailed guide on getting started with version control? Check out our Version Control chapter in The Turing Way Book!
While making your changes, commit often and write good, detailed commit messages. This blog explains how to write a good Git commit message and why it matters. It is also perfectly fine to have a lot of commits - including ones that break code. A good rule of thumb is to push up to GitHub when you do have passing tests then the continuous integration (CI) has a good chance of passing everything. 😸
Please do not re-write history! That is, please do not use the rebase command to edit previous commit messages, combine multiple commits into one, or delete or revert commits that are no longer necessary.
Make sure you're using the developer dependencies.
If you're working locally on the source code, before commiting, please run pip install -r requirements/requirements.dev.txt to install some useful dependencies just for development.
This includes pre-commit and ruff which are used to check and format your code style when you run git commit, so that you don't have to.
Using pre-commit:
- To make this work, just run
pre-commit installand when you commit,ruffwill be run to check the style of the files that you've changed. - Note, you may find that if
ruffneeds to edit your files, you'll have to rungit add ...andgit commit ..again as the pre-commit hook will stop the commit until the changes pass its tests,ruffwill also have slightly edited the files you added, so you'll need to stage and commit again.
Without pre-commit:
- Alternatively, you can run
ruffyourself (without)pre-commitby installingruffas above and just runningruff format.
You should also run pytest and check that your changes don't break any of the existing tests.
If you've made changes to the source code, you may need to add some tests to make sure that they don't get broken in the future.
We encourage you to open a pull request as early in your contributing process as possible. This allows everyone to see what is currently being worked on. It also provides you, the contributor, feedback in real-time from both the community and the continuous integration as you make commits (which will help prevent stuff from breaking).
GitHub has a nice introduction to the pull request workflow, but please get in touch if you have any questions 🎈.
You don't have to write code to contribute to DeepSensor. Another highly valuable way of contributing is helping with DeepSensor's documentation. See below for information on how to do this.
We use the Jupyter Book framework to build our documentation in the docs/ folder.
The documentation is written in
Markdown and Jupyter Notebooks. The documentation is hosted on GitHub Pages and is automatically
built and deployed using GitHub Actions after every commit to the main branch.
DeepSensor requires slightly unique documentation, because demonstrating the package requires both data and trained models. This makes it compute- and data-hungry to run some of the notebooks, and they cannot run on GitHub Actions. Therefore, all the notebooks are run locally - the code cell outputs are saved in the .ipynb files and are rendered when the documentation is built. If DeepSensor is updated, some of the notebooks may become out of date and will need to be re-run.
Some relevant links for Juptyer Book and MyST:
- https://jupyterbook.org/en/stable/intro.html
- https://jupyterbook.org/en/stable/content/myst.html
- https://jupyterbook.org/en/stable/reference/cheatsheet.html
One easy way to contribute to the documentation is to provide feedback in this issue and/or in the DeepSensor Slack channel.
Another way to contribute is to directly edit or add to the documentation and open a PR:
- Follow all the forking instructions above
- Install the documentation requirements:
pip install -r requirements/requirements.docs.txt - Option A: Editing a markdown file
- Simply make your edits!
- Option B: Editing a jupyter notebook file
- This can be more involved... Firstly, reach out on the Slack channel to ask if anyone else is working on the same notebook file locally. Working one-at-a-time can save Jupyter JSON merge conflict headaches later!
- If you are only editing markdown cells, just re-run those cells specifically to compile them
- If you are editing code cells:
- Install
cartopyusingconda install -c conda-forge cartopy - Run the all the code cells that the current cell depends on and any subsequent code cells that depend on the current cell (you may need to rerun the whole notebook)
- Note: Some notebooks require a GPU and some assume that previous notebooks have been run
- Install
- Please be careful about not clearing any code cell outputs that you don't intend to!
- Once your changes have been made, regenerate the docs locally with
jupyter-book build docs --alland check your changes have applied as expected - Push your changes and open a PR (see above)
If you're new to the project, we recommend starting with issues labeled as "good first issue". These are typically simpler tasks that offer a great starting point. Browse these here.
There's also the label "thoughts welcome", which allows for you to contribute with discussion points in the issues, even if you don't want to or cannot contribute to the codebase.
If you feel ready for it, you can also open a new issue. Before you open a new issue, please check if any of our open issues cover your idea already. If you open a new issue, please follow our basic guidelines laid out in our issue templates, which you should be able to see if you open a new issue.
Found a bug? Please open an issue here on GitHub to report it. We have a template for opening issues, so make sure you follow the correct format and ensure you include:
- A clear title.
- A detailed description of the bug.
- Steps to reproduce it.
- Expected versus actual behavior.
We value and recognize every contribution. All contributors will be acknowledged in the contributors section of the README. Notable contributions will also be highlighted in our fortnightly community meetings.
DeepSensor follows the all-contributors specifications. The all-contributors bot usage is described here. You can see a list of current contributors here.
To add yourself or someone else as a contributor, comment on the relevant Issue or Pull Request with the following:
@all-contributors please add username for contribution1, contribution2
You can see the Emoji Key (Contribution Types Reference) for a list of valid types and examples of how this command can be run in this issue. The bot will then create a Pull Request to add the contributor and reply with the pull request details.
PLEASE NOTE: Only one contributor can be added with the bot at a time! Add each contributor in
turn, merge the pull request and delete the branch (all-contributors/add-<username>) before adding
another one. Otherwise, you can end up with
dreaded merge conflicts. Therefore, please
check the open pull requests first to make sure there aren't
any open requests from the bot
before adding another.
What happens if you accidentally run the bot before the previous run was merged and you got those
pesky merge conflicts? (Don't feel bad, we have all done it! 🙈) Simply close the pull request and
delete the branch (all-contributors/add-<username>). If you are unable to do this for any reason,
please let us know on Slack or by opening an issue, and one of our core team members
will be very happy to help!
If you're stuck or need assistance:
- Check our FAQ section first.
- Reach out on Slack or via email for personalized assistance. (See "Get in touch" above for links.)
- Consider pairing up with a another contributor for guidance. You can always find us in the Slack channel and we're happy to chat!
Once again, thank you for considering contributing to DeepSensor! We hope you enjoy your contributing experience.
We aim to make DeepSensor a collaboratively developed project. We, therefore, require that all our members and their contributions adhere to our Code of Conduct. Please familiarize yourself with our Code of Conduct that lists the expected behaviours.
Every contributor is expected to adhere to our Code of Conduct. It outlines our expectations and ensures a safe, respectful environment for everyone.
These Contributing Guidelines have been adapted from the Contributing Guidelines of The Turing Way! (License: CC-BY)