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 at https://github.com/scrapinghub/dateparser/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.
Look through the GitHub issues for bugs. Anything tagged with “bug” is open to whoever wants to implement it.
Look through the GitHub issues for features. Anything tagged with “feature” is open to whoever wants to implement it. We encourage you to add new languages to existing stack.
DateParser could always use more documentation, whether as part of the official DateParser docs, in docstrings, or even on the web in blog posts, articles, and such.
The best way to send feedback is to file an issue at https://github.com/scrapinghub/dateparser/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 contributions are welcome :)
Ready to contribute? Here’s how to set up dateparser for local development.
Fork the dateparser repo on GitHub.
Clone your fork locally:
$ git clone email@example.com:your_name_here/dateparser.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 dateparser $ cd dateparser/ $ python setup.py develop
Create 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:
$ pip install -r tests/requirements.txt # install test dependencies $ flake8 dateparser tests $ nosetests $ tox
To get flake8 and tox, just pip install them into your virtualenv. (Note that we use
max-line-length = 100for flake8, this is configured in
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:
- 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.
- Check https://travis-ci.org/scrapinghub/dateparser/pull_requests and make sure that the tests pass for all supported Python versions.
- Follow the core developers’ advice which aim to ensure code’s consistency regardless of variety of approaches used by many contributors.
- In case you are unable to continue working on a PR, please leave a short comment to notify us. We will be pleased to make any changes required to get it done.
Guidelines for Adding New Languages¶
English is the primary language of the dateparser. Dates in all other languages are translated into English equivalents before they are parsed.
The language data required for parsing dates is contained in data/languages.yml file. It contains variable parts that can be used in dates, language by language: month and week names - and their abbreviations, prepositions, conjunctions and frequently used descriptive words and phrases (like “today”).
The chosen data format is YAML because it is readable and simple to edit.
Language data is extracted per language from YAML with
LanguageDataLoader and validated before being put into
Refer to Language Data Template for details about its structure and take a look at already implemented languages for examples. As we deal with the delicate fabric of interwoven languages, tests are essential to keep the functionality across them. Therefore any addition or change should be reflected in tests. However, there is nothing to be afraid of: our tests are highly parameterized and in most cases a test fits in one declarative line of data. Alternatively, you can provide required information and ask the maintainers to create the tests for you.