.. highlight:: shell

============
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/DigitalSlideArchive/HistomicsTK/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"
is open to whoever wants to implement it.

Implement Features
~~~~~~~~~~~~~~~~~~

Look through the GitHub issues for features. Anything tagged with "enhancement"
is open to whoever wants to implement it.

Write Documentation
~~~~~~~~~~~~~~~~~~~

HistomicsTK could always use more documentation, whether as part of the
official HistomicsTK 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/DigitalSlideArchive/HistomicsTK/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 `HistomicsTK` for local development.

1. Fork the `HistomicsTK` repo on GitHub.
2. Clone your fork locally::

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

3. Install your local copy into a virtualenv. Assuming you have virtualenvwrapper installed, this is how you set up your fork for local development::

   $ mkvirtualenv HistomicsTK
   $ cd HistomicsTK/
   $ python -m pip install setuptools-scm Cython>=0.25.2 scikit-build>=0.8.1 cmake>=0.6.0 numpy>=1.12.1
   $ python setup.py develop
    
Of course, any type of virtual python environment will do. These instructions are equally applicable inside `conda` environments.

4. Create a branch for local development::

   $ git checkout -b name-of-your-bugfix-or-feature

   Now you can make your changes locally.

5. 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

7. Submit a pull request through the GitHub website.

Pull Request Guidelines
-----------------------

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

1. The pull request should include unit tests (see notes below).
2. If the pull request adds functionality, the docs should be updated. Put
   your new functionality into a function with a docstring, and make sure
   your feature is reflected in one of the `.rst` files under `./docs/`.
   If an existing module exists and your feature is appended to it,
   then you can ignore this step as Sphinx will render it automatically.
   Otherwise, create a new `.rst` file.
3. **(Optional)** Create a Jupyter Notebook or a detailed documentation `.rst`
   under `./docs/examples/` to explain exactly how the feature should be used.
4. The pull request should work for Python 3.6, 3.7, 3.8, and 3.9. Check that
   the tests pass on the pull request for all supported Python versions.

Unit Testing Notes
----------------------------

There are two 'types` of unit tests on HistomicsTK.

* **Ordinary unit testing:**

  All unit testing uses the ``pytest`` module, and you should avoid using python's
  ``unittest`` module. Unit testing using dependency libraries such as ``numpy``
  or ``pandas`` is allowed. Use the standard ``test_python_file.py``
  naming convention. It is important that you check the
  `pytest naming convention <https://docs.pytest.org/en/latest/goodpractices.html#test-discovery>`_
  to make sure your discovered and actually run. Most of the unit tests are
  going to be stand-alone, and use data files that are small (e.g. csv files)
  that are contained (or added to) this repository.

  You can run your tests using something like::

  $ pytest your_python_file_test.py

* **Server side testing:**

  Sometimes you need to write unit tests for features that use an authenticated
  girder client that is connected to a Digital Slide Archive server. For example,
  you may want to test a feature that fetches regions from a slide on the DSA server and
  does some analysis with it. In that case, be sure to use the helper methods provided
  in ``./tests/htk_test_utilities.py``.
  The unit tests in ``./histomicstk/annotations_and_masks/tests/annotations_to_masks_handler_test.py``
  provide an example of how to handle these situations. Note that when access is need to
  a very large whole-slide image, ``GirderClient`` is used to provide access to the
  slide and annotations, which are referenced using ``.sha512`` hash that
  is present in ``./tests/data/``.

  The ``pytest`` fixture ``girderClient``, defined in ``tests/htk_test_utilities.py``
  yields an authenticated girder client that points to the server. If a local
  girder server docker is running, this will connect to it, otherwise, it will
  spin up a local girder server, load it with some initial data, and connect to it.

    **NOTE:**

    The default behavior initializes the docker image once per module and
    re-uses it for all tests. This means whatever one unit test changes in
    the DSA database is persistent for the next unit test. So if, for example,
    you remove one annotation as part of the first unit test, the next unit
    test will not have access to that annotation. Once all the unit tests are
    done, the database is torn down.

    If, instead, if you would like to run tests *repeatedly* (i.e. prototyping),
    or you would like the changes written by tests in one module to be
    carried over to the next test module, you may prefer to start the server
    manually. That way you won't worry about unknown wait time till the local
    server is fully initialized. To manually start a DSA docker image::

      $ cd HistomicsTK/tests/
      $ docker-compose up --build

  You can run your tests using something like::

  $ pytest test_python_file.py

  Of course, you need to have docker installed and to either
  run this as sudo or be added to the docker group by the system admins.

  Please contact the owners if you have questions about this or need support on how to
  host your test data on ``data.kitware.com`` to make this work.


Travis Integration Notes
----------------------------

When you submit a pull request to merge your branch with master, it will be
automatically submitted to Travis CI for continuous integration. In plain
English, your new branch will be tested to make sure it complies with the
standardized coding and documentation style of this repo. If you'd like
to help the organizers integrate your changes seamlessly, check to see
if the travis CI was passed. Otherwise, examine for errors and see if you
can get them fixed. Oftentimes, the errors originate from code and docstring
formatting and/or integration of jupyter notebooks into the documentaion
examples. Here are some pointers to help you handle some of these issues:

* Consider using ``flake8`` package to check if you comply with the
  formatting standard. HistomicsTK uses PEP8 standard with some options
  turned off. The ``flake8`` parameters we use can be found in:
  https://github.com/girder/girder/blob/2.x-maintenance/setup.cfg

  For example::

  $ flake8 your_python_file.py

  You can find ``flake8`` at: http://flake8.pycqa.org/en/latest/

  If you like using Vim editor, there is a tool to integrate ``flake8``
  with Vim for easy correction of errors at: https://github.com/nvie/vim-flake8

* If your text editor does not already have this feature, consider using the
  package ``autopep8`` to comply with PEP8 standard: https://github.com/hhatto/autopep8 .
  for example::

  $ autopep8 --in-place --aggressive your_python_file.py

* Consider using ``pydocstyle`` to check if you comply with the PEP257
  standard for docstrings: https://github.com/PyCQA/pydocstyle . For example::

  $ pydocstyle your_python_file.py

* If your text editor does not already do this, consider using ``docformatter``
  to fix docstrings to standard: https://pypi.org/project/docformatter/ . For
  example::

  $ docformatter --in-place --pre-summary-newline --blank your_python_file.py

* If you added new functionality, consider adding the documentation under
  ``doc`` in the form of rst files. Also consider creating Jupyter
  Notebooks to showcase functionality under ``doc/examples/``. The documentation
  is automatically generated using ``sphinx`` when you push your pull request and
  it gets submitted for travis integration. If you added documentation, consider
  checking if ``sphinx`` throws errors offline. you may install it from:
  https://www.sphinx-doc.org/en/master/index.html
  create a folder for the generated documentation to be saved, let's say
  ``~/HistomicsTK_test_build/`` . Then you may run something like::

  $ cd HistomicsTK
  $ sphinx-build ./docs/ ~/HistomicsTK_test_build/ 2>&1 | tee out.log

  Then you may check the file ``out.log`` for build errors.
