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CONTRIBUTING.md

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Contributing

Thanks for considering contributing! Please read this document to learn the various ways you can contribute to this project and how to go about doing it.

This Project welcomes contributions, suggestions, and feedback. All contributions, suggestions, and feedback you submitted are accepted under the Project's license. You represent that if you do not own copyright in the code that you have the authority to submit it under the Project's license. All feedback, suggestions, or contributions are not confidential.

Bug reports and feature requests

Did you find a bug?

First, do a quick search to see whether your issue has already been reported. If your issue has already been reported, please comment on the existing issue.

Otherwise, open a new GitHub issue. Be sure to include a clear title and description. The description should include as much relevant information as possible. The description should explain how to reproduce the erroneous behavior as well as the behavior you expect to see. Ideally you would include a code sample or an executable test case demonstrating the expected behavior.

Do you have a suggestion for an enhancement or new feature?

We use GitHub issues to track feature requests. Before you create an feature request:

  • Make sure you have a clear idea of the enhancement you would like. If you have a vague idea, consider discussing it first on a GitHub issue.
  • Check the documentation to make sure your feature does not already exist.
  • Do a quick search to see whether your feature has already been suggested.

When creating your request, please:

  • Provide a clear title and description.
  • Explain why the enhancement would be useful. It may be helpful to highlight the feature in other libraries.
  • Include code examples to demonstrate how the enhancement would be used.

Making a pull request

When you're ready to contribute code to address an open issue, please follow these guidelines to help us be able to review your pull request (PR) quickly.

  1. Initial setup (only do this once)

    Expand details 👇

    If you haven't already done so, please fork this repository on GitHub.

    Then clone your fork locally with

     git clone https://github.com/USERNAME/dodiscover.git
    

    or

     git clone git@github.com:USERNAME/dodiscover.git
    

    At this point the local clone of your fork only knows that it came from your repo, github.com/USERNAME/dodiscover.git, but doesn't know anything the main repo, https://github.com/py-why/dodiscover.git. You can see this by running

     # Note you should be in the "dodiscover" directory. If you're not
     # run "cd ./dodiscover" to change directory into the repo
     git remote -v
    

    which will output something like this:

     origin https://github.com/USERNAME/dodiscover.git (fetch)
     origin https://github.com/USERNAME/dodiscover.git (push)
    

    This means that your local clone can only track changes from your fork, but not from the main repo, and so you won't be able to keep your fork up-to-date with the main repo over time. Therefore you'll need to add another "remote" to your clone that points to https://github.com/py-why/dodiscover.git. To do this, run the following:

     git remote add upstream https://github.com/py-why/dodiscover.git
    

    Now if you do git remote -v again, you'll see

     origin https://github.com/USERNAME/dodiscover.git (fetch)
     origin https://github.com/USERNAME/dodiscover.git (push)
     upstream https://github.com/py-why/dodiscover.git (fetch)
     upstream https://github.com/py-why/dodiscover.git (push)
    

    Finally, you'll need to create a Python 3 virtual environment suitable for working on this project. There a number of tools out there that making working with virtual environments easier. The most direct way is with the venv module in the standard library, but if you're new to Python or you don't already have a recent Python 3 version installed on your machine, we recommend Miniconda.

    On Mac, for example, you can install Miniconda with Homebrew:

     brew install miniconda
    

    Then you can create and activate a new Python environment by running:

     conda create -n dodiscover python=3.9
     conda activate dodiscover
    

    Next, you'll need poetry installed, which is a software dependency manager written in Python. Follow the official instructions to install poetry. Once your virtual environment is activated, you can install your local clone with poetry.

     # the output should show a version of at least 1.2.2 (e.g. "Poetry (version 1.2.2)")
     poetry --version
    
     # next install dodiscover using poetry
     pip install -U pip setuptools wheel
     poetry install --with docs,test,style --extras graph_func
    
     # or you can try installing in editable mode with pip
     pip install -e .
    

    The "editable mode" comes from the -e argument to pip, and essential just creates a symbolic link from the site-packages directory of your virtual environment to the source code in your local clone. That way any changes you make will be immediately reflected in your virtual environment.

  2. Ensure your fork is up-to-date

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    Once you've added an "upstream" remote pointing to https://github.com/allenai/python-package-temlate.git, keeping your fork up-to-date is easy:

     git checkout main  # if not already on main
     git pull --rebase upstream main
     git push
    
  3. Create a new branch to work on your fix or enhancement

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    Committing directly to the main branch of your fork is not recommended. It will be easier to keep your fork clean if you work on a separate branch for each contribution you intend to make.

    You can create a new branch with

     # replace BRANCH with whatever name you want to give it
     git checkout -b BRANCH
     git push -u origin BRANCH
    
  4. Developing and testing your changes

    Expand details 👇

    Our continuous integration (CI) testing runs a number of checks for each pull request on GitHub Actions. You can run most of these tests locally, which is something you should do before opening a PR to help speed up the review process and make it easier for us. Please see our development guide for a comprehensive overview of useful commands leveraging poetry. This will cover aspects of code style checking, unit testing, integration testing, and building the documentation. We try to make it as easy as possible with copy/paste commands leveraging poetry which will guide your development process!

    And finally, please update the CHANGELOG file in the changelog folder with notes on your contribution in the latest version file.

    After all of the above checks have passed, you can now open a new GitHub pull request. Make sure you have a clear description of the problem and the solution, and include a link to relevant issues.

    We look forward to reviewing your PR!

Writing docstrings

We use Sphinx to build our API docs, which automatically parses all docstrings of public classes and methods. All docstrings should adhere to the Numpy styling convention.

Testing Changes Locally With Poetry

With poetry installed, we have included a few convenience functions to check your code. These checks must pass and will be checked by the PR's continuous integration services. You can install the various different developer dependencies with poetry:

poetry install --with style, docs, test

You can verify that your code will pass certain style, formatting and lint checks by running:

poetry run poe verify

verify runs a sequence of tests that can also be run individually. For example, you can check code formatting with black:

poetry run poe format_check

If you would like to automatically black format your changes:

poetry run poe format

You can then check for code style and general linting:

poetry run poe lint

Finally, you should run some mypy type checks:

poetry run poe type_check

Documentation

If you need to build the documentation locally and check for doc errors:

poetry run poe build_docs

Dependency Changes

If you need to add new, or remove old dependencies, then you need to modify the pyproject.toml file and then also update the poetry.lock file, which version-controls all necessary dependencies. If you alter any dependency in the pyproject.toml file, you must run:

poetry update

To update the lock file.


The Project abides by the Organization's code of conduct and trademark policy.


Part of MVG-0.1-beta. Made with love by GitHub. Licensed under the CC-BY 4.0 License.