Skip to content

Latest commit

 

History

History
150 lines (101 loc) · 4.87 KB

CONTRIBUTING.md

File metadata and controls

150 lines (101 loc) · 4.87 KB
Raw

Contributing Guide

Interested in helping build jupyter-forward? Have code from your work that you believe others will find useful? Have a few minutes to tackle an issue?

Contributions are highly welcomed and appreciated. Every little help counts, so do not hesitate!

The following sections cover some general guidelines regarding development in jupyter-forward for maintainers and contributors. Nothing here is set in stone and can't be changed. Feel free to suggest improvements or changes in the workflow.

Feature requests and feedback

We'd also like to hear about your propositions and suggestions. Feel free to submit them as issues on jupyter-forward's GitHub issue tracker and:

  • Explain in detail how they should work.
  • Keep the scope as narrow as possible. This will make it easier to implement.

Report bugs

Report bugs for jupyter-forward in the issue tracker.

If you are reporting a bug, please include:

  • Your operating system name and version.
  • Any details about your local setup that might be helpful in troubleshooting, specifically the Python interpreter version, installed libraries, and jupyter-forward version.
  • Detailed steps to reproduce the bug.

If you can write a demonstration test that currently fails but should pass (xfail), that is a very useful commit to make as well, even if you cannot fix the bug itself.

Fix bugs

Look through the GitHub issues for bugs.

Talk to developers to find out how you can fix specific bugs.

Write documentation

jupyter-forward could always use more documentation. What exactly is needed?

  • More complementary documentation. Have you perhaps found something unclear?
  • Docstrings. There can never be too many of them.
  • Blog posts, articles and such -- they're all very appreciated.

You can also edit documentation files directly in the GitHub web interface, without using a local copy. This can be convenient for small fixes.

Build the documentation locally with the following command:

$ make docs

Preparing Pull Requests

  1. Fork the jupyter-forward GitHub repository.

  2. Clone your fork locally using git, connect your repository to the upstream (main project), and create a branch::

    $ git clone [email protected]:YOUR_GITHUB_USERNAME/jupyter-forward.git
$ cd jupyter-forward
$ git remote add upstream [email protected]:ncar-xdev/jupyter-forward.git

    now, to fix a bug or add feature create your own branch off "master":

    $ git checkout -b your-bugfix-feature-branch-name master

    If you need some help with Git, follow this quick start guide: https://git.wiki.kernel.org/index.php/QuickStart

  3. Install dependencies into a new conda environment::

    $ conda env update -f ci/environment.yml
$ conda activate jupyter-forward-dev

  4. Make an editable install of jupyter-forward by running::

    $ python -m pip install -e .

  5. Install pre-commit <https://pre-commit.com>_ hooks on the jupyter-forward repo::

    $ pre-commit install

    Afterwards pre-commit will run whenever you commit.

    pre-commit is a framework for managing and maintaining multi-language pre-commit hooks to ensure code-style and code formatting is consistent.

    Now you have an environment called jupyter-forward-dev that you can work in. You’ll need to make sure to activate that environment next time you want to use it after closing the terminal or your system.

  6. (Optional) Run all the tests

    Now running tests is as simple as issuing this command::

    $ pytest

    This command will run tests via the pytest tool.

  7. Commit and push once your tests pass and you are happy with your change(s)::

    When committing, pre-commit will re-format the files if necessary.

    $ git commit -a -m "<commit message>"
$ git push -u

  8. Finally, submit a pull request through the GitHub website using this data::

    head-fork: YOUR_GITHUB_USERNAME/jupyter-forward
compare: your-branch-name

base-fork: ncar-xdev/jupyter-forward
base: master # if it's a bugfix or feature
In some cases you may want to create a local virtual machine (VM) to simulate a remote machine. This is not necessary, but it is recommended. You can use the provided [vagrant file](https://www.vagrantup.com/) to create a VM. From the root directory of the jupyter-forward repository, run the following command to create a VM::
   ```bash
   $ vagrant up
   $ vagrant ssh-config > vagrant-ssh
   $ ssh -F vagrant-ssh default
   $ jupyter-forward [email protected]:2222 --identity ./.vagrant/machines/default/virtualbox/private_key