Contributing¶
Contributions are welcome, and they are greatly appreciated! Every little bit helps, and credit will always be given.
You can contribute in many ways:
Types of Contributions¶
Report Bugs¶
Report bugs at https://github.com/mtllr/md_planning/issues.
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.
Detailed steps to reproduce the bug.
Fix Bugs¶
Look through the GitHub issues for bugs. Anything tagged with “bug” and “help wanted” is open to whoever wants to implement it.
Implement Features¶
Look through the GitHub issues for features. Anything tagged with “enhancement” and “help wanted” is open to whoever wants to implement it.
Here are some example features, bugs, etc:
version 0.4.0
TODO: (feature) critical_color implementation
TODO: (bugfix) E17FB6 v0.2 error message shows what csv task and what is the offensive entry
BUG: if there is not at least one dependency between tasks then python-gantt does NOT create the svg
TODO: (feature) assert that task names in a multiproject definition are unique for the whole definition file
TODO: (refactor) data structure and project classes so the Resource class has methods: get_price, get_unit
TODO: (refactor) data structure and project classes so the Task class has method: get_usage
TODO: (refactor) data structure and project classes so the Project class has methods: get_unit, get_price, get_usage, get_cost
TODO: (feature) when user makes task depend on milestone, KeyError is raised but it is difficult to find in which task the error was made
TODO: (bug) nested definition implementation supposes that the CP of a project is the SUM of CPs of all it’s milestones. This is not true if a “small” task in a milestone depends on a long running task outside of the current milestone. The only way to solve this now is to build the full CP between milestones.
TODO: (refactor) add get_dependencies and get_resources to the main code
Write Documentation¶
md-planning could always use more documentation, whether as part of the official md-planning docs, in docstrings, or even on the web in blog posts, articles, and such.
Submit Feedback¶
The best way to send feedback is to file an issue at https://github.com/mtllr/md_planning/issues.
If you are proposing a feature:
Explain in detail how it would work.
Keep the scope as narrow as possible, to make it easier to implement.
Remember that this is a volunteer-driven project, and that contributions are welcome :)
Get Started!¶
Ready to contribute? Here’s how to set up md_planning for local development.
Fork the md_planning repo on GitHub.
Clone your fork locally:
$ git clone git@github.com:your_name_here/md_planning.git
Install your local copy into a virtualenv. Assuming you have virtualenvwrapper installed, this is how you set up your fork for local development:
$ mkvirtualenv md_planning $ cd md_planning/ $ python setup.py developCreate a branch for local development:
$ git checkout -b name-of-your-bugfix-or-feature
Now you can make your changes locally.
When you’re done making changes, check that your changes pass flake8 and the tests, including testing other Python versions with tox:
$ flake8 md_planning tests $ python setup.py test or pytest $ toxTo get flake8 and tox, just pip install them into your virtualenv.
Commit your changes and push your branch to GitHub:
$ git add . $ git commit -m "Your detailed description of your changes." $ git push origin name-of-your-bugfix-or-featureSubmit a pull request through the GitHub website.
Pull Request Guidelines¶
Before you submit a pull request, check that it meets these guidelines:
The pull request should include tests.
If the pull request adds functionality, the docs should be updated. Put your new functionality into a function with a docstring, and add the feature to the list in README.rst.
The pull request should work for Python 3.5, 3.6, 3.7 and 3.8, and for PyPy. Check https://travis-ci.com/mtllr/md_planning/pull_requests and make sure that the tests pass for all supported Python versions.
Tips¶
To run a subset of tests:
$ pytest tests.test_md_planning
Deploying¶
A reminder for the maintainers on how to deploy. Make sure all your changes are committed (including an entry in HISTORY.rst). Then run:
$ bump2version patch # possible: major / minor / patch
$ git push
$ git push --tags
Travis will then deploy to PyPI if tests pass.