Contents
First off, thank you for considering contributing to beets! It’s people like you that make beets continue to succeed.
These guidelines describe how you can help most effectively. By following these guidelines, you can make life easier for the development team as it indicates you respect the maintainers’ time; in return, the maintainers will reciprocate by helping to address your issue, review changes, and finalize pull requests.
We love to get contributions from our community—you! There are many ways to contribute, whether you’re a programmer or not.
The first thing to do, regardless of how you'd like to contribute to the project, is to check out our :doc:`Code of Conduct <code_of_conduct>` and to keep that in mind while interacting with other contributors and users.
- Promote beets! Help get the word out by telling your friends, writing a blog post, or discussing it on a forum you frequent.
- Improve the documentation. It’s incredibly easy to contribute here: just find a page you want to modify and hit the “Edit on GitHub” button in the upper-right. You can automatically send us a pull request for your changes.
- GUI design. For the time being, beets is a command-line-only affair. But that’s mostly because we don’t have any great ideas for what a good GUI should look like. If you have those great ideas, please get in touch.
- Benchmarks. We’d like to have a consistent way of measuring speed improvements in beets’ tagger and other functionality as well as a way of comparing beets’ performance to other tools. You can help by compiling a library of freely-licensed music files (preferably with incorrect metadata) for testing and measurement.
- Think you have a nice config or cool use-case for beets? We’d love to hear about it! Submit a post to our discussion board under the “Show and Tell” category for a chance to get featured in the docs.
- Consider helping out fellow users by by responding to support requests .
- As a programmer (even if you’re just a beginner!), you have a ton of opportunities to get your feet wet with beets.
- For developing plugins, or hacking away at beets, there’s some good information in the “For Developers” section of the docs.
In order to develop beets, you will need a few tools installed:
- poetry for packaging, virtual environment and dependency management
- poethepoet to run tasks, such as linting, formatting, testing
Python community recommends using pipx to install stand-alone command-line applications such as above. pipx installs each application in an isolated virtual environment, where its dependencies will not interfere with your system and other CLI tools.
If you do not have pipx installed in your system, follow pipx-installation-instructions or
$ python3 -m pip install --user pipxInstall poetry and poethepoet using pipx:
$ pipx install poetry poethepoet
The easiest way to get started with the latest beets source is to clone the
repository and install beets in a local virtual environment using poetry.
This can be done with:
$ git clone https://github.com/beetbox/beets.git
$ cd beets
$ poetry installThis will install beets and all development dependencies into its own
virtual environment in your $POETRY_CACHE_DIR. See poetry install
--help for installation options, including installing extra dependencies
for plugins.
In order to run something within this virtual environment, start the command
with poetry run to them, for example poetry run pytest.
On the other hand, it may get tedious to type poetry run before every
command. Instead, you can activate the virtual environment in your shell with:
$ poetry shell
You should see (beets-py38) prefix in your shell prompt. Now you can run
commands directly, for example:
$ (beets-py38) pytest
Additionally, poethepoet task runner assists us with the most common
operations. Formatting, linting, testing are defined as poe tasks in
pyproject.toml. Run:
$ poe
to see all available tasks. They can be used like this, for example
$ poe lint # check code style
$ poe format # fix formatting issues
$ poe test # run tests
# ... fix failing tests
$ poe test --lf # re-run failing tests (note the additional pytest option)
$ poe check-types --pretty # check types with an extra option for mypy- We maintain a set of issues marked as “bite-sized”. These are issues that would serve as a good introduction to the codebase. Claim one and start exploring!
- Like testing? Our test coverage is somewhat low. You can help out by finding low-coverage modules or checking out other testing-related issues.
- There are several ways to improve the tests in general (see :ref:`testing` and some places to think about performance optimization (see Optimization).
- Not all of our code is up to our coding conventions. In particular, the library API documentation are currently quite sparse. You can help by adding to the docstrings in the code and to the documentation pages themselves. beets follows PEP-257 for docstrings and in some places, we also sometimes use ReST autodoc syntax for Sphinx to, for example, refer to a class name.
If this is your first time contributing to an open source project, welcome! If you are confused at all about how to contribute or what to contribute, take a look at this great tutorial, or stop by our discussion board if you have any questions.
We maintain a list of issues we reserved for those new to open source labeled “first timers only”. Since the goal of these issues is to get users comfortable with contributing to an open source project, please do not hesitate to ask any questions.
Do you have a great bug fix, new feature, or documentation expansion you’d like to contribute? Follow these steps to create a GitHub pull request and your code will ship in no time.
- Fork the beets repository and clone it (see above) to create a workspace.
- Install pre-commit, following the instructions here.
- Make your changes.
- Add tests. If you’ve fixed a bug, write a test to ensure that you’ve actually fixed it. If there’s a new feature or plugin, please contribute tests that show that your code does what it says.
- Add documentation. If you’ve added a new command flag, for example,
find the appropriate page under
docs/where it needs to be listed. - Add a changelog entry to
docs/changelog.rstnear the top of the document. - Run the tests and style checker, see :ref:`testing`.
- Push to your fork and open a pull request! We’ll be in touch shortly.
- If you add commits to a pull request, please add a comment or re-request a review after you push them since GitHub doesn’t automatically notify us when commits are added.
Remember, code contributions have four parts: the code, the tests, the documentation, and the changelog entry. Thank you for contributing!
The documentation has a section on the library API that serves as an introduction to beets’ design.
There are a few coding conventions we use in beets:
Whenever you access the library database, do so through the provided Library methods or via a Transaction object. Never call
lib.conn.*directly. For example, do this:with g.lib.transaction() as tx: rows = tx.query("SELECT DISTINCT '{0}' FROM '{1}' ORDER BY '{2}'" .format(field, model._table, sort_field))
To fetch Item objects from the database, use lib.items(…) and supply a query as an argument. Resist the urge to write raw SQL for your query. If you must use lower-level queries into the database, do this:
with lib.transaction() as tx: rows = tx.query("SELECT …")
Transaction objects help control concurrent access to the database and assist in debugging conflicting accesses.
Always use the future imports
print_function,division, andabsolute_import, but notunicode_literals. These help keep your code modern and will help in the eventual move to Python 3.str.format()should be used instead of the%operatorNever
printinformational messages; use the logging module instead. In particular, we have our own logging shim, so you’ll seefrom beets import loggingin most files.- The loggers use
str.format-style
logging instead of
%-style, so you can typelog.debug("{0}", obj)to do your formatting.
- The loggers use
str.format-style
logging instead of
Exception handlers must use
except A as B:instead ofexcept A, B:.
We use ruff to format and lint the codebase.
Run poe check-format and poe lint to check your code for style and
linting errors. Running poe format will automatically format your code
according to the specifications required by the project.
A great deal of convention deals with the handling of paths. Paths
are stored internally—in the database, for instance—as byte strings
(i.e., bytes instead of str in Python 3). This is because POSIX
operating systems’ path names are only reliably usable as byte
strings—operating systems typically recommend but do not require that
filenames use a given encoding, so violations of any reported encoding
are inevitable. On Windows, the strings are always encoded with UTF-8;
on Unix, the encoding is controlled by the filesystem. Here are some
guidelines to follow:
- If you have a Unicode path or you’re not sure whether something is
Unicode or not, pass it through
bytestring_pathfunction in thebeets.utilmodule to convert it to bytes. - Pass every path name through the
syspathfunction (also inbeets.util) before sending it to any operating system file operation (open, for example). This is necessary to use long filenames (which, maddeningly, must be Unicode) on Windows. This allows us to consistently store bytes in the database but use the native encoding rule on both POSIX and Windows. - Similarly, the
displayable_pathutility function converts bytestring paths to a Unicode string for displaying to the user. Every time you want to print out a string to the terminal or log it with theloggingmodule, feed it through this function.
Personally, I work on beets with vim. Here are
some .vimrc lines that might help with PEP 8-compliant Python
coding:
filetype indent on autocmd FileType python setlocal shiftwidth=4 tabstop=4 softtabstop=4 expandtab shiftround autoindent
Consider installing this alternative Python indentation plugin. I also like neomake with its flake8 checker.
Use poe to run tests:
$ poe test [pytest options]
You can disable a hand-selected set of "slow" tests by setting the
environment variable SKIP_SLOW_TESTS, for example:
$ SKIP_SLOW_TESTS=1 poe test
The test command does not include coverage as it slows down testing. In
order to measure it, use the test-with-coverage task
$ poe test-with-coverage [pytest options]
You are welcome to explore coverage by opening the HTML report in
.reports/html/index.html.
Note that for each covered line the report shows which tests cover it (expand the list on the right-hand side of the affected line).
You can find project coverage status on Codecov.
The pytest-random plugin makes it easy to randomize the order of
tests. poe test --random will occasionally turn up failing tests
that reveal ordering dependencies—which are bad news!
The tests have a few more dependencies than beets itself. (The additional
dependencies consist of testing utilities and dependencies of non-default
plugins exercised by the test suite.) The dependencies are listed under the
tool.poetry.group.test.dependencies section in pyproject.toml.
Writing tests is done by adding or modifying files in folder test. Take a look at https://github.com/beetbox/beets/blob/master/test/test_template.py#L224 to get a basic view on how tests are written. Since we are currently migrating the tests from unittest to pytest, new tests should be written using pytest. Contributions migrating existing tests are welcome!
External API requests under test should be mocked with `requests_mock`_, However, we still want to know whether external APIs are up and that they return expected responses, therefore we test them weekly with our integration test suite.
In order to add such a test, mark your test with the integration_test marker
@pytest.mark.integration_test
def test_external_api_call():
...This way, the test will be run only in the integration test suite.