Contributing to SHARPy

Bug fixes and features

SHARPy is a collaborative effort, and this means that some coding practices need to be encouraged so that the code is kept tidy and consistent. Any user is welcome to raise issues for bug fixes and feature proposals through Github.

If you are submitting a bug report:

  1. Make sure your SHARPy, xbeam and uvlm local copies are up to date and in the same branch.

  2. Double check that your python distribution is updated by comparing with the utils/environment_*.yml file.

  3. Try to assemble a minimal working example that can be run quickly and easily.

  4. Describe as accurately as possible your setup (OS, path, compilers…) and the problem.

  5. Raise an issue with all this information in the Github repo and label it potential bug.

Please bear in mind that we do not have the resources to provide support for user modifications of the code through Github. If you have doubts about how to modify certain parts of the code, contact us through email and we will help you as much as we can.

If you are fixing a bug:

  1. THANKS!

  2. Please create a pull request from your modified fork, and describe in a few lines which bug you are fixing, a minimal example that triggers the bug and how you are fixing it. We will review it ASAP and hopefully it will be incorporated in the code!

If you have an idea for new functionality but do not know how to implement it:

  1. We welcome tips and suggestions from users, as it allow us to broaden the scope of the code. The more people using it, the better!

  2. Feel free to fill an issue in Github, and tag it as feature proposal. Please understand that the more complete the description of the potential feature, the more likely it is that some of the developers will give it a go.

If you have developed new functionality and you want to share it with the world:

  1. AWESOME! Please follow the same instructions than for the bug fix submission. If you have some peer-reviewed references related to the new code, even better, as it will save us some precious time.

Code formatting

We try to follow the PEP8 standards (with spaces, no tabs please!) and Google Python Style Guide. We do not ask you to freak out over formatting, but please, try to keep it tidy and descriptive. A good tip is to run pylint to make sure there are no obvious formatting problems.


Contributing to SHARPy’s documentation benefits everyone. As a developer, writing documentation helps you better understand what you have done and whether your functions etc make logical sense. As a user, any documentation is better than digging through the code. The more we have documented, the easier the code is to use and the more users we can have.

If you want to contribute by documenting code, you have come to the right place.

SHARPy is documented using Sphinx and it extracts the documentation directly from the source code. It is then sorted into directories automatically and a human readable website generated. The amount of work you need to do is minimal. That said, the recipe for a successfully documented class, function, module is the following:

  1. Your documentation has to be written in ReStructuredText (rst). I know, another language… hence I will leave a few tips:

    • Inline code is written using two backticks ``

    • Inline math is written as :math:`1+\exp^{i\pi} = 0`. Don’t forget the backticks!

    • Math in a single or multiple lines is simple:

          .. math:: 1 + \exp{i\pi} = 0
    • Lists in ReStructuredText are tricky, I must admit. Therefore, I will link to some examples. The key resides in not forgetting the spaces, in particular when you go onto a second line!

    • The definite example list can be found here.

  2. Titles and docstrings, the bare minimum:

    • Start docstrings with r such that they are interpreted raw:

      My docstring
    • All functions, modules and classes should be given a title that goes in the first line of the docstring

    • If you are writing a whole package with an file, even if it’s empty, give it a human readable docstring. This will then be imported into the documentation

    • For modules with several functions, the module docstring has to be at the very top of the file, prior to the import statements.

  3. We use the Google documentation style. A very good set of examples of Google style documentation for functions, modules, classes etc. can be found here.

  4. Function arguments and returns:

    • Function arguments are simple to describe:

      def func(arg1, arg2):
      """Summary line.
      Extended description of function.
        arg1 (int): Description of arg1
        arg2 (str): Description of arg2
        bool: Description of return value
          return True
  5. Solver settings:

    • If your code has a settings dictionary, with defaults and types then make sure that:

      • They are defined as class variables and not instance attributes.

      • Define a settings_types, settings_default and settings_description dictionaries.

      • After all your settings, update the docstring with the automatically generated settings table. You will need to import the sharpy.utils.settings module

        settings_types = dict()
        settings_default = dict()
        settings_description = dict()
        # keep adding settings
        settings_table = sharpy.utils.settings.SettingsTable()
        __doc__ += settings_table.generate(settings_types, settings_default ,settings_description)
  6. See how your docs looks like!

    • Once you are done, run the following SHARPy command:

    sharpy any_string -d
    • If you are making minor updates to docstrings (i.e. you are not documenting a previously undocumented function/class/module) you can simply change directory to sharpy/docs and run

    make html
    • Your documentation will compile and warnings will appear etc. You can check the result by opening


    and navigating to your recently created page.

    • Make sure that before committing any changes in the documentation you update the entire docs directory by running

    sharpy any_string -d

Thank you for reading through this and contributing to make SHARPy a better documented, more user friendly code!

Git branching model

For the development of SHARPy, we try to follow this branching model summarised by the schematic Credit: Vincent Driessen

Therefore, attending to this model our branches have the following versions of the code:

  • master: latest stable release - paired with the appropriate tag.

  • develop: latest stable development build. Features get merged to develop.

  • rc-**: release candidate branch. Prior to releasing tests are performed on this branch.

  • dev_doc: documentation development branch. All work relating to documentation gets done here.

  • fix_**: hotfix branch.

  • dev_**: feature development branch.

If you contribute, please make sure you know what branch to work from. If in doubt please ask!

Commit names are also important since they are the backbone of the code’s change log. Please write concise commit titles and explain the main changes in the body of the commit message. An excellent guide on writing good commit messages can be found here.