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/AaronBlare/pydnameth/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.

Write Documentation¶

pydnameth could always use more documentation, whether as part of the official pydnameth 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/AaronBlare/pydnameth/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 pydnameth for local development.

Environment¶

We use Anaconda Python distribution and PyCharm IDE

You can use any other Python distributions and IDEs.

GitHub Init¶

Fork the pydnameth repo on GitHub.
Travis CI and AppVeyor are continuous integration tools. Login using your Github credentials. It may take a few minutes for Travis CI and AppVeyor to load up a list of all your GitHub repos. Turn on testing your origin repository on Travis CI and AppVeyor. To do this, log into your personal account, synchronize the repositories with GitHub and add pydnameth project.

Local¶

Clone your fork locally:

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

Create a virtual environment for your project and activate it:
```
$ conda create --name your-env-name python=x.x
$ activate your-env-name
```
where your-env-name is the name you want to call your environment, and replace x.x with the Python version you wish to use (for example 3.7)
Go to the root of pydnameth project and install project in ‘editable’ or ‘develop’ mode while you are working on it:
```
$ pip install --editable .
```
. refers to the current working directory. This allows the project to be both installed and editable in project form.

Install all libs in requirements_dev.txt:

$ pip install -r requirements_dev.txt

If with some package err-pkg error occurs, try:

$ conda install err-pkg --channel=conda-forge

If you want to save figures locally as .pdf and .png run the command:

$ conda install -c plotly plotly-orca psutil

And repeat command:

$ pip install -r requirements_dev.txt

If requirements_dev.txt file was updated, you should repeat the command:
```
$ pip install -r requirements_dev.txt
```
If you update requirements_dev.txt file, you should recreate environment for tox (only locally):
```
$ tox --recreate -e env
```
Where env is name for tox environment.

Git Pipeline¶

master branch is always in production, tested and complete.
development is the branch closest to master but has changes that should be merged to master. Anyone who starts working on a new feature or bug fixing should always branch out from development.
Branch out from development with new branch for bug or feature:
```
$ 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:
```
$ tox
```

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.
The pull request should work for Python 3.7, 3.6 and 3.5. Check https://travis-ci.org/AaronBlare/pydnameth/pull_requests and make sure that the tests pass for all supported Python versions.

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:

$ git add HISTORY.rst
$ git commit -m "Changelog for upcoming release x.x.x."
$ bumpversion patch # possible: major / minor / patch
$ git push
$ git push --tags

Travis will then deploy to PyPI if tests pass.