Contributing
Bug reports, feature suggestions, and other contributions are greatly appreciated! pysat is a community-driven project and welcomes both feedback and contributions.
Come join us on Slack! An invitation to the pysat workspace is available in the ‘About’ section of the pysat GitHub Repository. Development meetings are generally held fortnightly.
Short version
Submit bug reports, feature requests, and questions at GitHub
Make pull requests to the
develop
branch
Issues
Bug reports, questions, and feature requests should all be made as GitHub Issues. Templates are provided for each type of issue, to help you include all the necessary information.
Questions
Not sure how something works? Ask away! The more information you provide, the easier the question will be to answer. You can also interact with the pysat developers on our slack channel.
Bug reports
When 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
Feature requests and feedback
The best way to send feedback is to file an issue.
If you are proposing a new feature or a change in something that already exists:
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 code contributions are welcome :)
Development
To set up pysat
for local development:
Clone your fork locally:
git clone git@github.com:your_name_here/pysat.git
Create a branch for local development:
git checkout -b name-of-your-bugfix-or-feature
Now you can make your changes locally.
Tests for new instruments are performed automatically. See discussion here for more information on triggering these standard tests.
Tests for custom functions should be added to the appropriately named file in
pysat/tests
. For example, custom functions for the time utilities are tested inpysat/tests/test_utils_time.py
. If no test file exists, then you should create one. This testing uses pytest, which will run tests on any Python file in the test directory that starts withtest
. Classes must begin withTest
, and methods must begin withtest
as well.When you’re done making changes, run all the checks to ensure that nothing is broken on your local system, as well as check for flake8 compliance:
pytest
You should also check for flake8 style compliance:
flake8 . --count --select=D,E,F,H,W --show-source --statistics
Note that pysat uses the
flake-docstrings
andhacking
packages to ensure standards in docstring formatting.Update/add documentation (in
docs
). Even if you don’t think it’s relevant, check to see if any existing examples have changed.Add your name to the .zenodo.json file as an author
Commit your changes:
git add . git commit -m "AAA: Brief description of your changes"
Where AAA is a standard shorthand for the type of change (e.g., BUG or DOC).
pysat
follows the numpy development workflow, see the discussion there for a full list of this shorthand notation.Once you are happy with the local changes, push to GitHub:
git push origin name-of-your-bugfix-or-feature
Note that each push will trigger the Continuous Integration workflow.
Submit a pull request through the GitHub website. Pull requests should be made to the
develop
branch. Note that automated tests will be run on GitHub Actions, but these must be initialized by a member of the pysat team for first time contributors.
Pull Request Guidelines
If you need some code review or feedback while you’re developing the code, just
make a pull request. Pull requests should be made to the develop
branch.
For merging, you should:
Include an example for use
Add a note to
CHANGELOG.md
about the changesUpdate the author list in
zenodo.json
, if applicableEnsure that all checks passed (current checks include GitHub Actions, Coveralls and ReadTheDocs)
If you don’t have all the necessary Python versions available locally or have trouble building all the testing environments, you can rely on GitHub Actions to run the tests for each change you add in the pull request. Because testing here will delay tests by other developers, please ensure that the code passes all tests on your local system first.
Project Style Guidelines
In general, pysat follows PEP8 and numpydoc guidelines. Pytest runs the unit and integration tests, flake8 checks for style, and sphinx-build performs documentation tests. However, there are certain additional style elements that have been adopted to ensure the project maintains a consistent coding style. These include:
Line breaks should occur before a binary operator (ignoring flake8 W503)
Combine long strings using
join
Preferably break long lines on open parentheses rather than using
\
Use no more than 80 characters per line
Avoid using Instrument class key attribute names as unrelated variable names:
platform
,name
,tag
, andinst_id
The pysat logger is imported into each sub-module and provides status updates at the info and warning levels (as appropriate)
Several dependent packages have common nicknames, including:
import datetime as dt
import numpy as np
import pandas as pds
import xarray as xr
When incrementing a timestamp, use
dt.timedelta
instead ofpds.DateOffset
when possible to reduce program runtimeAll classes should have
__repr__
and__str__
functionsDocstrings use
Note
instead ofNotes
Try to avoid creating a try/except statement where except passes
Use setup_method (or setup_class) and teardown_method (or teardown_class) in test classes
Use pytest parametrize in test classes when appropriate
Use pysat testing utilities when appropriate
Provide testing class methods with informative failure statements and descriptive, one-line docstrings
Block and inline comments should use proper English grammar and punctuation with the exception of single sentences in a block, which may then omit the final period
When casting is necessary, use
np.int64
andnp.float64
to ensure operating system agnosticism
Ecosystem Style Guidelines
If you are creating a new project that you wish to incorporate into the pysat ecosystem: welcome! We have a template repository that contains many of the common documents needed for a new project that you can use to get started. You may find this helpful when getting started, though this repository is under active development.