Contributing

Ptychography 4.0 is intended and designed as a collaboratively developed platform for data analysis. That means all our development is coordinated openly, mostly on our GitHub repository where our code is hosted. Any suggestions, Issues, bug reports, discussions and code contributions are highly appreciated! Please let us know if you think we can improve on something, be it code, communication or other aspects.

Development principles

We have a rather extensive and growing list of things to work on and therefore have to prioritize our limited resources to work on items with the largest benefit for our user base and project. Supporting users who contribute code is most important to us. Please contact us for help! Furthermore, we prioritize features that create direct benefits for many current users or open significant new applications. Generally, we follow user demand with our developments.

For design of new features we roughly follow the lead user method, which means that we develop new features closely along a non-trivial real-world application in order to make sure the developments are appropriate and easy to use in practice.

Furthermore we value a systematic approach to development with requirements analysis and evaluation of design options as well as iterative design with fast test and review cycles.

Code contributions

We are using pull requests to accept contributions. Each pull request should focus on a single issue, to keep the number of changes small and reviewable. To keep your changes organized and to prevent unrelated changes from disturbing your pull request, create a new branch for each pull request.

All pull requests should come from a user’s personal fork since we don’t push to the main repository for development. See the GitHub documentation on how to create and manage forks for details.

Before creating a pull request, please make sure all tests still pass. See Running the Tests for more information. You should also update the test suite and add test cases for your contribution. See the section Code coverage below on how to check if your new code is covered by tests.

To make sure our code base stays readable, we follow a Code Style.

Please update packaging/creators.json with your author information when you contribute to Ptychography 4.0 for the first time. This helps us to keep track of all contributors and give credit where credit is due! Please let us know if you wouldn’t like to be credited.

If you are changing parts of Ptychography 4.0 that are currently not covered by tests, please consider writing new tests! When changing example code, which is not run as part of the tests, make sure the example still runs.

When adding or changing a feature, you should also update the corresponding documentation, or add a new section for your feature. Follow the current documentation structure, or ask the maintainers where your new documentation should end up. When introducing a feature, it is okay to start with a draft documentation in the first PR, if it will be completed later. Changes of APIs should update the corresponding docstrings.

Please include version information if you add or change a feature in order to track and document changes. We use a rolling documentation that documents previous behavior as well, for example This feature was added in Version 0.3.0.dev0 or This describes the behavior from Version 0.3.0.dev0 and onwards. The previous behavior was this and that. If applicable, use versionadded and related directives.

The changelog for the development branch is maintained as a collection of files in the docs/source/changelog/*/ folder structure. Each change should get a separate file to avoid merge conflicts. The files are merged into the master changelog when creating a release.

The following items might require an update upon introducing or changing a feature:

  • Changelog snippet in docs/source/changelog/*/

  • Docstrings

  • Examples

  • Main Documentation

When you have submitted your pull request, someone from the Ptychography 4.0 organization will review your pull request, and may add comments or ask questions. If everything is good to go, your changes will be merged and you can delete the branch you created for the pull request.

See also the Guide on understanding the GitHub flow.

Running the tests

Our tests are written using pytest. For running them in a repeatable manner, we are using tox. Tox automatically manages virtualenvs and allows testing on different Python versions and interpreter implementations.

This makes sure that you can run the tests locally the same way as they are run in continuous integration.

After installing tox, you can run the tests on all Python versions by simply running tox:

$ tox

Or specify a specific environment you want to run:

$ tox -e py36

For faster iteration, you can also run only a part of the test suite, without using tox. To make this work, first install the test requirements into your virtualenv:

(ptychography) $ pip install -r test_requirements.txt

Now you can run pytest on a subset of tests, for example:

(ptychography) $ pytest tests/reconstruction/test_ssb.py

See the pytest documentation for details on how to select which tests to run. Before submitting a pull request, you should always run the whole test suite.

Some tests are marked with custom markers, for example we have some tests that take many seconds to complete. To select tests to run by these marks, you can use the -m switch. For example, to only run the slow tests:

$ tox -- -m slow

By default, these slow tests are not run. If you want to run both slow and all other tests, you can use a boolean expression like this:

$ tox -- -m "slow or not slow"

Another example, to exclude both slow and functional tests:

$ tox -- -m "not functional and not slow"

In these examples, -- separates the the arguments of tox (left of --) from the arguments for pytest on the right. List of marks used in our test suite:

  • slow: tests that take much more than 1 second to run

  • functional: tests that spin up a local dask cluster

Code coverage

After running the tests, you can inspect the test coverage by opening htmlcov/index.html in a web browser. When creating a pull request, the change in coverage is also reported by the codecov bot. Ideally, the test coverage should go up with each pull request, at least it should stay the same.

On Windows

On Windows with Anaconda, you have to create named aliases for the Python interpreter before you can run tox so that tox finds the python interpreter where it is expected. Assuming that you run Ptychography 4.0 with Python 3.6, place the following file as python3.6.bat in your ptychography conda environment base folder, typically %LOCALAPPDATA%\conda\conda\envs\ptychography\, where the python.exe of that environment is located.

@echo off
REM @echo off is vital so that the file doesn't clutter the output
REM execute python.exe with the same command line
@python.exe %*

To execute tests with Python 3.7, you create a new environment with Python 3.7:

> conda create -n ptychography-3.7 python=3.7

Now you can create python3.7.bat in your normal ptychography environment alongside python3.6.bat and make it execute the Python interpreter of your new ptychography-3.7 environment:

@echo off
REM @echo off is vital so that the file doesn't clutter the output
REM execute python.exe in a different environment
REM with the same command line
@%LOCALAPPDATA%\conda\conda\envs\ptychography-3.7\python.exe %*

See also: https://tox.readthedocs.io/en/latest/developers.html#multiple-python-versions-on-windows

Code style

We try to keep our code PEP8 -compliant, with line-length relaxed to 100 chars, and some rules ignored. See the flake8 section in setup.cfg for the current PEP8 settings. As a general rule, try to keep your changes in a similar style as the surrounding code.

You can check the code style by running:

$ tox -e flake8

We recommend using an editor that can check code style on the fly, such as Visual Studio Code.

Docstrings

The NumPy docstring guide is our guideline for formatting docstrings. We are testing docstring code examples in Continuous Integration using doctest. You can test files by hand by running pytest --doctest-modules <pathspec>.

Building the documentation

Documentation building is also done with tox, see above for the basics. It requires manual installation of pandoc on the build system since pandoc can’t be installed reliably using pip. To start the live building process:

$ tox -e docs

You can then view a live-built version at http://localhost:8009

You can include code samples with the doctest sphinx extension and test them with

$ tox -e docs-check

Advanced

See more: