Table of contents:
Note
This document is based on ideas and guidelines from the xarray Contributing Guide, which in turn builds largely upon the Pandas Contributing Guide . Some of the guidelines are more aspirational than practical at this point and constitute an attempt to learn how to build a proper open source software repository.
All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome.
If you are brand new to mixsea or open-source development, we recommend going through the GitHub "issues" tab to find issues that interest you. There are a number of issues listed under Documentation and good first issue where you could start out. Once you've found an interesting issue, you can return here to get your development environment setup.
Bug reports are an important part of making mixsea more stable. Having a complete bug report will allow others to reproduce the bug and provide insight into fixing. See this stackoverflow article for tips on writing a good bug report.
Trying the bug-producing code out on the main branch is often a worthwhile exercise to confirm the bug still exists. It is also worth searching existing bug reports and pull requests to see if the issue has already been reported and/or fixed.
Bug reports must:
Include a short, self-contained Python snippet reproducing the problem. You can format the code nicely by using GitHub Flavored Markdown:
```python >>> import mixsea ... ```
- Explain why the current behavior is wrong/not desired and what you expect instead.
The issue will then show up to the mixsea community and be open to comments/ideas from others.
Now that you have an issue you want to fix, enhancement to add, or documentation to improve, you need to learn how to work with GitHub and the mixsea code base.
To the new user, working with Git is one of the more daunting aspects of contributing to mixsea. It can very quickly become overwhelming, but sticking to the guidelines below will help keep the process straightforward and mostly trouble free. As always, if you are having difficulties please feel free to ask for help.
The code is hosted on GitHub. To contribute you will need to sign up for a free GitHub account. We use Git for version control to allow many people to work together on the project.
Some great resources for learning Git:
- the GitHub help pages.
- the NumPy's documentation.
- Matthew Brett's Pydagogue.
GitHub has instructions for installing git, setting up your SSH key, and configuring git. All these steps need to be completed before you can work seamlessly between your local repository and GitHub.
You will need your own fork to work on the code. Go to the mixsea project
page and hit the Fork button. You will
want to clone your fork to your machine:
git clone https://github.com/your-user-name/mixsea.git cd mixsea git remote add upstream https://github.com/modscripps/mixsea.git
This creates the directory mixsea and connects your repository to the upstream (main project) mixsea repository.
To test out code changes, you'll need to build mixsea from source, which requires a Python environment.
Before starting any development, you'll need to create an isolated mixsea development environment:
- Install either Anaconda or miniconda
- Make sure your conda is up to date (
conda update conda) - Make sure that you have :ref:`cloned the repository <contributing.forking>`
cdto the mixsea source directory
We'll now kick off a two-step process:
- Install the build dependencies
- Build and install mixsea
# Create and activate the build environment
# This is for Linux and MacOS. On Windows, use py37-windows.yml instead.
conda env create -f environment.yml
conda activate mixsea
# or with older versions of Anaconda:
source activate mixsea
# Build and install mixsea
pip install -e .
At this point you should be able to import mixsea from your locally built version:
$ python # start an interpreter >>> import mixsea >>> mixsea.__version__ '0.1.0'
This will create the new environment, and not touch any of your existing environments, nor any existing Python installation.
To view your environments:
conda info -e
To return to your root environment:
conda deactivate
See the full conda docs here.
You want your main branch to reflect only production-ready code, so create a feature branch for making your changes. For example:
git branch shiny-new-feature git checkout shiny-new-feature
The above can be simplified to:
git checkout -b shiny-new-feature
This changes your working directory to the shiny-new-feature branch. Keep any
changes in this branch specific to one bug or feature so it is clear
what the branch brings to mixsea. You can have many "shiny-new-features"
and switch in between them using the git checkout command.
To update this branch, you need to retrieve the changes from the main branch:
git fetch upstream git rebase upstream/main
This will replay your commits on top of the latest mixsea git main. If this
leads to merge conflicts, you must resolve these before submitting your pull
request. If you have uncommitted changes, you will need to git stash them
prior to updating. This will effectively store your changes and they can be
reapplied after updating.
If you're not the developer type, contributing to the documentation is still of huge value. The documentation is written in reStructuredText, which is almost like writing in plain English, and built using Sphinx. The Sphinx Documentation has an excellent introduction to reST. Review the Sphinx docs to perform more complex changes to the documentation as well.
Some other important things to know about the docs:
The mixsea documentation consists of two parts: the docstrings in the code itself and the docs in this folder
mixsea/docs/.The docstrings are meant to provide a clear explanation of the usage of the individual functions, while the documentation in this folder consists of tutorial-like overviews per topic together with some other information (what's new, installation, etc).
The docstrings follow the Numpy Docstring Standard, which is used widely in the Scientific Python community. This standard specifies the format of the different sections of the docstring. See this document for a detailed explanation, or look at some of the existing functions to extend it in a similar manner.
The tutorials make heavy use of the ipython directive sphinx extension. This directive lets you put code in the documentation which will be run during the doc build. For example:
.. ipython:: python x = 2 x**3will be rendered as:
In [1]: x = 2 In [2]: x**3 Out[2]: 8
Almost all code examples in the docs are run (and the output saved) during the doc build. This approach means that code examples will always be up to date, but it does make the doc building a bit more complex
The documentation includes jupyer notebooks via the nbsphinx exension. Make sure to clean all notebook output before adding and committing changes, this removes any images and other output and makes diffs much more easy to read.
Our API documentation in
doc/api.rsthouses the auto-generated documentation from the docstrings. Every method should be included inapi.rst, else Sphinx will emit a warning.
Navigate to your root mixsea/ directory in the console and run:
make docs
Then you can find the HTML output in the folder mixsea/docs/_build/html/.
The newly built site will also automatically open in your browser.
Alternatively, you can also run:
make servedocs
This will watch for changes in the source files of the documentation and rebuild whenever it detects a change.
Code Base:
Writing good code is not just about what you write. It is also about how you write it. During :ref:`Continuous Integration <contributing.ci>` testing, several tools will be run to check your code for stylistic errors. Generating any warnings will cause the test to fail. Thus, good style is a requirement for submitting code to mixsea.
In addition, because other people may use our library, it is important that we do not make sudden changes to the code that could have the potential to break a lot of user code as a result, that is, we need it to be as backwards compatible as possible to avoid mass breakages.
mixsea uses several tools to ensure a consistent code format throughout the project:
- Black for standardized code formatting
- Flake8 for general code quality
- isort for standardized order in imports. See also flake8-isort.
pip:
pip install black flake8 isort mypy
and then run from the root of the mixsea repository:
isort -rc . black -t py36 . flake8
to auto-format your code. Additionally, many editors have plugins that will
apply black as you edit files.
Optionally, you may wish to setup pre-commit hooks
to automatically run all the above tools every time you make a git commit. This
can be done by installing pre-commit:
pip install pre-commit
and then running:
pre-commit install
from the root of the mixsea repository. You can skip the pre-commit checks
with git commit --no-verify.
The mixsea test suite runs automatically the Travis CI, continuous integration service, once your pull request is submitted.
A pull-request will be considered for merging when you have an all 'green' build. If any tests are failing, then you will get a red 'X', where you can click through to see the individual failed tests.
Note
Each time you push to your PR branch, a new run of the tests will be triggered on the CI.
mixsea is serious about testing and strongly encourages contributors to embrace test-driven development (TDD). This development process "relies on the repetition of a very short development cycle: first the developer writes an (initially failing) automated test case that defines a desired improvement or new function, then produces the minimum amount of code to pass that test." So, before actually writing any code, you should write your tests. Often the test can be taken from the original GitHub issue. However, it is always worth considering additional use cases and writing corresponding tests.
Like many packages, mixsea uses pytest and the convenient extensions in numpy.testing.
All tests should go into the tests subdirectory of the specific package.
This folder contains current examples of tests, and we suggest looking to these for
inspiration.
Here is an example of a self-contained set of tests that illustrate multiple features that we like to use.
- functional style: tests are like
test_*and only take arguments that are either fixtures or parameters pytest.markcan be used to set metadata on test functions, e.g.skiporxfail.- using
parametrize: allow testing of multiple cases - to set a mark on a parameter,
pytest.param(..., marks=...)syntax should be used fixture, code for object construction, on a per-test basis- using bare
assertfor scalars and truth-testing
We would name this file test_really_cool_feature.py and put in an appropriate place in the
mixsea/tests/ structure.
import pytest
import numpy as np
@pytest.mark.parametrize('dtype', ['int8', 'int16', 'int32', 'int64'])
def test_dtypes(dtype):
assert str(np.dtype(dtype)) == dtype
@pytest.mark.parametrize('dtype', ['float32',
pytest.param('int16', marks=pytest.mark.skip),
pytest.param('int32', marks=pytest.mark.xfail(
reason='to show how it works'))])
def test_mark(dtype):
assert str(np.dtype(dtype)) == 'float32'
@pytest.fixture
def fake_data():
return np.array([1, 2, 3])
@pytest.fixture(params=['int8', 'int16', 'int32', 'int64'])
def dtype(request):
return request.param
def test_series(fake_data, dtype):
result = fake_data.astype(dtype)
assert result.dtype == dtypeA test run of this yields
(mixsea) $ pytest mixsea/tests/test_really_cool_feature.py -v
========================================= test session starts =====================
platform darwin -- Python 3.8.2, pytest-5.4.1, py-1.8.1, pluggy-0.13.1 --
cachedir: .pytest_cache
plugins: datadir-1.3.1
collected 11 items
mixsea/tests/test_really_cool_feature.py::test_dtypes[int8] PASSED [ 9%]
mixsea/tests/test_really_cool_feature.py::test_dtypes[int16] PASSED [ 18%]
mixsea/tests/test_really_cool_feature.py::test_dtypes[int32] PASSED [ 27%]
mixsea/tests/test_really_cool_feature.py::test_dtypes[int64] PASSED [ 36%]
mixsea/tests/test_really_cool_feature.py::test_mark[float32] PASSED [ 45%]
mixsea/tests/test_really_cool_feature.py::test_mark[int16] SKIPPED [ 54%]
mixsea/tests/test_really_cool_feature.py::test_mark[int32] XFAIL [ 63%]
mixsea/tests/test_really_cool_feature.py::test_series[int8] PASSED [ 72%]
mixsea/tests/test_really_cool_feature.py::test_series[int16] PASSED [ 81%]
mixsea/tests/test_really_cool_feature.py::test_series[int32] PASSED [ 90%]
mixsea/tests/test_really_cool_feature.py::test_series[int64] PASSED [100%]
=============================== 9 passed, 1 skipped, 1 xfailed in 0.15s ===========Tests that we have parametrized are now accessible via the test name, for
example we could run these with -k int8 to sub-select only those tests
which match int8.
(mixsea) $ pytest mixsea/tests/test_really_cool_feature.py -v -k int8
========================================= test session starts =====================
platform darwin -- Python 3.8.2, pytest-5.4.1, py-1.8.1, pluggy-0.13.1 --
plugins: datadir-1.3.1
collected 11 items / 9 deselected / 2 selected
mixsea/tests/test_really_cool_feature.py::test_dtypes[int8] PASSED [ 50%]
mixsea/tests/test_really_cool_feature.py::test_series[int8] PASSED [100%]
=================================== 2 passed, 9 deselected in 0.02s ===============The tests can then be run directly inside your Git clone by typing:
pytest mixsea
Often it is worth running only a subset of tests first around your changes before running the entire suite. The easiest way to do this is with:
pytest mixsea/path/to/test.py -k regex_matching_test_name
Or with one of the following constructs:
pytest mixsea/tests/[test-module].py pytest mixsea/tests/[test-module].py::[TestClass] pytest mixsea/tests/[test-module].py::[TestClass]::[test_method]
Changes should be reflected in the release notes located in HISTORY.rst.
This file contains an ongoing change log for each release. Add an entry to this file to
document your fix, enhancement or (unavoidable) breaking change. Make sure to include the
GitHub issue number when adding your entry (using :issue:`1234`, where 1234 is the
issue/pull request number).
If your code is an enhancement, it is most likely necessary to add usage examples to the existing documentation. This can be done following the section regarding documentation :ref:`above <contributing.documentation>`.
Keep style fixes to a separate commit to make your pull request more readable.
Once you've made changes, you can see them by typing:
git status
If you have created a new file, it is not being tracked by git. Add it by typing:
git add path/to/file-to-be-added.py
Doing 'git status' again should give something like:
# On branch shiny-new-feature # # modified: /relative/path/to/file-you-added.py #
The following defines how a commit message should be structured:
- A subject line with < 72 chars.
- One blank line.
- Optionally, a commit message body.
Please reference the relevant GitHub issues in your commit message using GH1234 or
#1234. Either style is fine, but the former is generally preferred.
Now you can commit your changes in your local repository:
git commit -m
This will prompt you to type in your commit message.
When you want your changes to appear publicly on your GitHub page, push your forked feature branch's commits:
git push origin shiny-new-feature
Here origin is the default name given to your remote repository on GitHub.
You can see the remote repositories:
git remote -v
If you added the upstream repository as described above you will see something like:
origin [email protected]:yourname/mixsea.git (fetch) origin [email protected]:yourname/mixsea.git (push) upstream git://github.com/modscripps/mixsea.git (fetch) upstream git://github.com/modscripps/mixsea.git (push)
Now your code is on GitHub, but it is not yet a part of the mixsea project. For that to happen, a pull request needs to be submitted on GitHub.
When you're ready to ask for a code review, file a pull request. Before you do, once again make sure that you have followed all the guidelines outlined in this document regarding code style, tests, and documentation. You should also double check your branch changes against the branch it was based on:
- Navigate to your repository on GitHub -- https://github.com/your-user-name/mixsea
- Click on
Branches - Click on the
Comparebutton for your feature branch - Select the
baseandcomparebranches, if necessary. This will bemainandshiny-new-feature, respectively.
If everything looks good, you are ready to make a pull request. A pull request is how code from a local repository becomes available to the GitHub community and can be looked at and eventually merged into the main version. This pull request and its associated changes will eventually be committed to the main branch and available in the next release. To submit a pull request:
- Navigate to your repository on GitHub
- Click on the
Pull Requestbutton - You can then click on
CommitsandFiles Changedto make sure everything looks okay one last time - Write a description of your changes in the
Preview Discussiontab - Click
Send Pull Request.
This request then goes to the repository maintainers, and they will review the code. If you need to make more changes, you can make them in your branch, add them to a new commit, push them to GitHub, and the pull request will be automatically updated. Pushing them to GitHub again is done by:
git push origin shiny-new-feature
This will automatically update your pull request with the latest code and restart the :ref:`Continuous Integration <contributing.ci>` tests.
Once your feature branch is accepted into upstream, you'll probably want to get rid of the branch. First, merge upstream main into your branch so git knows it is safe to delete your branch:
git fetch upstream git checkout main git merge upstream/main
Then you can do:
git branch -d shiny-new-feature
Make sure you use a lower-case -d, or else git won't warn you if your feature
branch has not actually been merged.
The branch will still exist on GitHub, so to delete it there do:
git push origin --delete shiny-new-feature
Properly comment and document your code. See :ref:`"Documenting your code" <documenting.your.code>`.
Test that the documentation builds correctly by typing
make docsin the root directory ormake htmlin thedocsdirectory. This is not strictly necessary, but this may be easier than waiting for CI to catch a mistake. See :ref:`"Contributing to the documentation" <contributing.documentation>`.Test your code.
- Write new tests if needed. See :ref:`"Test-driven development/code writing" <contributing.tdd>`.
- Test the code using Pytest. Running all tests (type
pytest mixseaormake testin the root directory) takes a while, so feel free to only run the tests you think are needed based on your PR (example:pytest mixsea/tests/test_really_cool_feature.py). CI will catch any failing tests.
Properly format your code and verify that it passes the formatting guidelines set by Black and Flake8. See :ref:`"Code formatting" <code.formatting>`. You can use pre-commit to run these automatically on each commit.
- Run
black mixseain the root directory. This may modify some files. Confirm and commit any formatting changes. - Run
flake8in the root directory. If this fails, it will log an error message. - Alternatively, the above formatting steps are combined in
make style. You can also typemake style-checkfor a dry run.
- Run
Push your code and create a PR on GitHub.
Use a helpful title for your pull request by summarizing the main contributions rather than using the latest commit message. If this addresses an issue, please reference it.