Welcome to the SpikingAI repository! We're excited you're here and want to contribute.
These guidelines are designed to make it as easy as possible to get involved. If you have any questions that aren't discussed below, please let us know by opening an issue!
Before you start you'll need to set up a free GitHub account and sign in. Here are some instructions.
Already know what you're looking for in this guide? Jump to the following sections:
- Joining the conversation
- Contributing small documentation changes
- Contributing through Github
- Understanding issues, milestones, and project boards
- Installing in editable mode
- Making a change
- Testing your change
- Viewing Documentation Locally
- Structuring contributions
- Recognizing contributors
- Monthly calls and testing guidelines
Don't know where to get started? Read Joining the conversation and pop into Gitter to introduce yourself! Let us know what your interests are and we will help you find an issue to contribute to. Thanks so much!
SpikingAI is a young project maintained by a growing group of enthusiastic developers— and we're excited to have you join!
Most of our discussions will take place on open issues.
We also maintain a gitter chat room for more informal conversations and general project updates.
There is significant cross-talk between these two spaces, and we look forward to hearing from you in either venue!
As a reminder, we expect all contributions to SpikingAI to adhere to our code of conduct.
If you are new to GitHub and just have a small documentation change recommendation, please submit it to our e-mail address and one of our developers will add it to the documentation directly.
git is a really useful tool for version control. GitHub sits on top of git and supports collaborative and distributed working.
You'll use Markdown to chat in issues and pull requests on GitHub.
You can think of Markdown as a few little symbols around your text that will allow GitHub
to render the text with a little bit of formatting.
For example you could write words as bold (**bold**), or in italics (*italics*),
or as a link ([link](https://https://youtu.be/dQw4w9WgXcQ)) to another webpage.
GitHub has a helpful page on getting started with writing and formatting Markdown on GitHub.
Every project on GitHub uses issues, milestones, and project boards slightly differently.
The following outlines how the SpikingAI developers think about these different tools.
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Issues are individual pieces of work that need to be completed to move the project forwards. A general guideline: if you find yourself tempted to write a great big issue that is difficult to describe as one unit of work, please consider splitting it into two or more issues.
Issues are assigned labels which explain how they relate to the overall project's goals and immediate next steps.
Sometimes issues may not produce action items, and conversation will stall after a few months. When this happens, they may be marked stale by stale-bot, and will be closed after a week unless there is more discussion. This helps us keep the issue tracker organized. Any new discussion on the issue will remove the
stalelabel, and prevent it from closing. So, if theres's a discussion you think it not yet resolved, please jump in ! -
Milestones are the link between the issues and the high level strategy for the
SpikingAIproject. Contributors new and old are encouraged to take a look at the milestones to see how we are progressing towardsSpikingAI's shared vision.Issues are assigned to these milestones by the maintainers. If you feel that an issue should be assigned to a specific milestone but the maintainers have not done so, just ask! We might have just missed it, or we might not (yet) see how it aligns with the overall project structure. These conversations are important to have, and we are excited to hear your perspective!
The current list of labels are here and include:
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These issues contain a task that a member of the team has determined we need additional help with.
If you feel that you can contribute to one of these issues, we especially encourage you to do so!
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These issues should not be worked on until the resolution of other issues or Pull Requests.
These are issues that are paused pending resolution of a related issue or Pull Request. Please do not open any Pull Requests to resolve these issues.
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These issues point to problems in the project.
If you find new a bug, please give as much detail as possible in your issue, including steps to recreate the error. If you experience the same bug as one already listed, please add any additional information that you have as a comment.
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These issues are asking for enhancements to be added to the project.
Please try to make sure that your enhancement is distinct from any others that have already been requested or implemented. If you find one that's similar but there are subtle differences please reference the other request in your issue.
We appreciate all contributions to SpikingAI, but those accepted fastest will follow a workflow similar to the following:
1. Comment on an existing issue or open a new issue referencing your addition
This allows other members of the SpikingAI development team to confirm that you aren't overlapping with work that's currently underway and that everyone is on the same page with the goal of the work you're going to carry out.
This blog is a nice explanation of why putting this work in up front is so useful to everyone involved.
2. Fork the SpikingAI repository to your GitHub profile
This is now your own unique and online copy of SpikingAI. Changes here won't affect anyone else's work, so it's a safe space to explore edits to the code!
Remember to clone your fork of SpikingAI to your local machine, which will allow you to make local changes to SpikingAI.
Make sure to always keep your fork up to date with the upstream repository before and after making changes.
To test a change, you may need to set up your local repository to run a SpikingAI workflow.
To do so, run
pip install -e .[all]
from within your local SpikingAI repository. This should ensure all packages are correctly organized and linked on your user profile.
We recommend including the [all] flag when you install SpikingAI so that "extra" requirements necessary for running tests and building the documentation will also be installed.
Once you've run this, your repository should be set for most changes (i.e., you do not have to re-run with every change).
Try to keep the changes focused to the issue. We've found that working on a new branch for each issue makes it easier to keep your changes targeted. Using a new branch allows you to follow the standard GitHub workflow when making changes. This guide provides a useful overview for this workflow. Before making a new branch, make sure your main is up to date with the following commands:
git checkout main
git fetch upstream main
git merge upstream/main
Then, make your new branch.
git checkout -b MYBRANCH
Please make sure to review the SpikingAI style conventions and test your changes.
If you are new to git and would like to work in a graphical user interface (GUI), there are several GUI git clients that you may find helpful, such as
You can run style checks by running the following:
flake8 $SpikingAIDIR/SpikingAI
and unit/integration tests by running pytest (more details below).
If you know a file will test your change, you can run only that test (see "One test file only" below).
Alternatively, running all unit tests is relatively quick and should be fairly comprehensive.
Running all pytest tests will be useful for pre-pushing checks.
Regardless, when you open a Pull Request, we use CircleCI to run all unit and integration tests.
All tests; final checks before pushing
pytest $SpikingAIDIR/SpikingAI/tests
Unit tests and linting only
pytest --skipintegration $SpikingAIDIR/SpikingAI/tests
One test file only
pytest $SpikingAIDIR/SpikingAI/tests/test_file.py
Test one function in a file
pytest -k my_function $SpikingAIDIR/SpikingAI/tests/test_file.py
from within your local SpikingAI repository.
The test run will indicate the number of passes and failures.
Most often, the failures give enough information to determine the cause; if not, you can
refer to the pytest documentation for more details on the failure.
For changes to documentation, we suggest rendering the HTML files locally in order to review the changes before submitting a pull request. This can be done by running
make html
from the docs directory in your local SpikingAI repository. You should then be able to access the rendered files in the docs/_build directory, and view them in your browser.
Most of SpikingAI's documentation is written in restructuredText, rather than Markdown.
Among many other differences, restructuredText allows a great deal of flexibility in how section headings are defined.
For consistency, we have adopted the following standard for our section headings:
#with overline, for parts*with overline, for chapters=, for sections-, for subsections^, for subsubsections", for paragraphs
6. Submit a pull request
When opening the pull request, we ask that you follow some specific conventions. We outline these below.
After you have submitted the pull request, a member of the development team will review your changes to confirm that they can be merged into the main code base. When you have two approving reviewers and all tests are passing, your pull request may be merged.
To push your changes to your remote, use
git push -u origin MYBRANCH
and GitHub will respond by giving you a link to open a pull request to SpikingAI/SpikingAI. Once you have pushed changes to the repository, please do not use commands such as rebase and amend, as they will rewrite your history and make it difficult for developers to work with you on your pull request. You can read more about that here.
To improve understanding pull requests "at a glance", we encourage the use of several standardized tags. When opening a pull request, please use at least one of the following prefixes:
- [BRK] for changes which break existing builds or tests
- [DOC] for new or updated documentation
- [ENH] for enhancements
- [FIX] for bug fixes
- [REF] for refactoring existing code
- [TST] for new or updated tests, and
- [MAINT] for maintenance of code
You can also combine the tags above, for example if you are updating both a test and the documentation: [TST, DOC].
Pull requests should be submitted early and often! If your pull request is not yet ready to be merged, please use draft PRs This tells the development team that your pull request is a "work-in-progress", and that you plan to continue working on it. If no comments or commits occur on an open Pull Request, stale-bot will comment in order to remind both you and the maintainers that the pull request is open. If at this time you are awaiting a developer response, please ping them to remind them. If you are no longer interested in working on the pull request, let us know and we will ask to continue working on your branch. Thanks for contributing!
- Check that all tests are passing ("All tests passsed")
- Make sure you have docstrings for any new functions
- Make sure that docstrings are updated for edited functions
- Make sure you note any issues that will be closed by your PR
- Take a look at the automatically generated readthedocs for your PR (Show all checks -> continuous-documentation/readthedocs -> Details)
For additional, in-depth information on contributing to SpikingAI, please see our Developing Guidelines on readthedocs.
Docstrings should follow numpydoc convention. We encourage extensive documentation.
The python code itself should follow PEP8 convention whenever possible, with at most about 500 lines of code (not including docstrings) per script.
Additionally, we have adopted a purely functional approach in SpikingAI, so we
avoid defining our own classes within the library.
Our documentation is written in ReStructuredText, which we explain in more detail below.
The documentation for SpikingAI is written using ReStructuredText.
Using this markup language allows us to create an online site using the Sphinx
documentation generator.
We then host the generated Sphinx site on ReadTheDocs,
to provide an easily accessible space for accessing SpikingAI documentation.
What this means is that we need to add any updates to the documentation in ReStructuredText,
or rst.
The resulting text looks slightly different from the markdown formatting you'll
use on github, but we're excited to help you get started!
Here's one guide we've found particularly helpful for starting with rst.
And, if you have any questions, please don't hesitate to ask!
We welcome and recognize all contributions from documentation to testing to code development. You can see a list of current contributors in the README (kept up to date by the all contributors bot). You can see here for instructions on how to use the bot. We encourage all contributors to write a brief statement and self-describe how they feel they've contributed, showcased [here][contributions.md]. Thanks to all of our wonderful contributors!
You're awesome. 👋😃
— Based on contributing guidelines from the STEMMRoleModels project.