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¶

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.

Write Documentation¶

stacklog could always use more documentation, whether as part of the official stacklog 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 the GitHub Issues page.

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 stacklog for local development.

Fork the stacklog repo on GitHub.

Clone your fork locally:

$ git clone git@github.com:your_name_here/stacklog.git

Install your local copy into a virtualenv of choice. Assuming you have virtualenvwrapper installed, this is how you set up your fork for local development:
```
$ poetry install --with dev
```
Create a branch for local development:
```
$ git checkout -b name-of-your-bugfix-or-feature
```
Try to use the naming scheme of prefixing your branch with gh-X where X is the associated issue, such as gh-3-fix-foo-bug. And if you are not developing on your own fork, further prefix the branch with your GitHub username, like githubusername/gh-3-fix-foo-bug.

Now you can make your changes locally.
While hacking your changes, make sure to cover all your developments with the required unit tests, and that none of the old tests fail as a consequence of your changes. For this, make sure to run the tests suite and check the code coverage:
```
$ make lint       # Check code styling
$ make test       # Run the tests
$ make coverage   # Get the coverage report
```
When you’re done making changes, check that your changes pass all the styling checks and tests, including other Python supported versions, using:
```
$ make test-all
```
Make also sure to include the necessary documentation in the code as docstrings following the Google docstrings style. If you want to view how your documentation will look like when it is published, you can generate and view the docs with this command:
```
$ make view-docs
```

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-feature

Submit a pull request through the GitHub website.

Pull Request Guidelines¶

Before you submit a pull request, check that it meets these guidelines:

It resolves an open GitHub Issue and contains its reference in the title or the comment. If there is no associated issue, feel free to create one.
Whenever possible, it resolves only one issue. If your PR resolves more than one issue, try to split it in more than one pull request.
The pull request should include unit tests that cover all the changed code
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 documentation in an appropriate place.
The pull request should work for all the supported Python versions.

Unit Testing Guidelines¶

All the Unit Tests should comply with the following requirements:

Unit Tests should be based only in unittest and pytest modules.
The tests that cover a module called stacklog/path/to/a_module.py should be implemented in a separated module called tests/stacklog/path/to/test_a_module.py. Note that the module name has the test_ prefix and is located in a path similar to the one of the tested module, just inside the tests folder.
Each method of the tested module should have at least one associated test method, and each test method should cover only one use case or scenario.
Test case methods should start with the test_ prefix and have descriptive names that indicate which scenario they cover. Names such as test_some_methed_input_none, test_some_method_value_error or test_some_method_timeout are right, but names like test_some_method_1, some_method or test_error are not.
Each test should validate only what the code of the method being tested does, and not cover the behavior of any third party package or tool being used, which is assumed to work properly as far as it is being passed the right values.
Any third party tool that may have any kind of random behavior, such as some Machine Learning models, databases or Web APIs, will be mocked using the mock library or pytest monkeypatch fixture, and the only thing that will be tested is that our code passes the right values to them.
Unit tests should not use anything from outside the test and the code being tested. This includes not reading or writing to any file system or database, which will be properly mocked.

Tips¶

To run a subset of tests:

$ python -m pytest tests.test_stacklog
$ python -m pytest -k 'foo'

Release Workflow¶

Update the HISTORY.md file describing the new release.

Update the version in pyproject.toml stacklog/__init__.py and elsewhere, and create a new git tag pointing at the corresponding commit in master branch:

poetry self add poetry-bumpversion
poetry version <type>
git add -u
git commit -m "Release $(poetry version -s)"
git tag "v$(poetry version -s)"

Push to GitHub and ensure that tests pass:
```
git push --tags origin master
```
Create a new release on PyPI:
```
poetry publish
```