# DEVELOPER INSTRUCTIONS
-Most users do not need to build yt-dlp and can [download the builds](https://github.com/yt-dlp/yt-dlp/releases) or get them via [the other installation methods](README.md#installation).
+Most users do not need to build yt-dlp and can [download the builds](https://github.com/yt-dlp/yt-dlp/releases), get them via [the other installation methods](README.md#installation) or directly run it using `python -m yt_dlp`.
-To run yt-dlp as a developer, you don't need to build anything either. Simply execute
+`yt-dlp` uses [`hatch`](<https://hatch.pypa.io>) as a project management tool.
+You can easily install it using [`pipx`](<https://pipx.pypa.io>) via `pipx install hatch`, or else via `pip` or your package manager of choice. Make sure you are using at least version `1.10.0`, otherwise some functionality might not work as expected.
- python3 -m yt_dlp
+If you plan on contributing to `yt-dlp`, best practice is to start by running the following command:
-To run all the available core tests, use:
+```shell
+$ hatch run setup
+```
+
+The above command will install a `pre-commit` hook so that required checks/fixes (linting, formatting) will run automatically before each commit. If any code needs to be linted or formatted, then the commit will be blocked and the necessary changes will be made; you should review all edits and re-commit the fixed version.
- python3 devscripts/run_tests.py
+After this you can use `hatch shell` to enable a virtual environment that has `yt-dlp` and its development dependencies installed.
+
+In addition, the following script commands can be used to run simple tasks such as linting or testing (without having to run `hatch shell` first):
+* `hatch fmt`: Automatically fix linter violations and apply required code formatting changes
+ * See `hatch fmt --help` for more info
+* `hatch test`: Run extractor or core tests
+ * See `hatch test --help` for more info
See item 6 of [new extractor tutorial](#adding-support-for-a-new-site) for how to run extractor specific test cases.
+While it is strongly recommended to use `hatch` for yt-dlp development, if you are unable to do so, alternatively you can manually create a virtual environment and use the following commands:
+
+```shell
+# To only install development dependencies:
+$ python -m devscripts.install_deps --include dev
+
+# Or, for an editable install plus dev dependencies:
+$ python -m pip install -e ".[default,dev]"
+
+# To setup the pre-commit hook:
+$ pre-commit install
+
+# To be used in place of `hatch test`:
+$ python -m devscripts.run_tests
+
+# To be used in place of `hatch fmt`:
+$ ruff check --fix .
+$ autopep8 --in-place .
+
+# To only check code instead of applying fixes:
+$ ruff check .
+$ autopep8 --diff .
+```
+
If you want to create a build of yt-dlp yourself, you can follow the instructions [here](README.md#compile).
1. [Fork this repository](https://github.com/yt-dlp/yt-dlp/fork)
1. Check out the source code with:
- git clone git@github.com:YOUR_GITHUB_USERNAME/yt-dlp.git
+ ```shell
+ $ git clone git@github.com:YOUR_GITHUB_USERNAME/yt-dlp.git
+ ```
1. Start a new git branch with
- cd yt-dlp
- git checkout -b yourextractor
+ ```shell
+ $ cd yt-dlp
+ $ git checkout -b yourextractor
+ ```
1. Start with this simple template and save it to `yt_dlp/extractor/yourextractor.py`:
# TODO more properties (see yt_dlp/extractor/common.py)
}
```
-1. Add an import in [`yt_dlp/extractor/_extractors.py`](yt_dlp/extractor/_extractors.py). Note that the class name must end with `IE`.
-1. Run `python3 devscripts/run_tests.py YourExtractor`. This *may fail* at first, but you can continually re-run it until you're done. Upon failure, it will output the missing fields and/or correct values which you can copy. If you decide to add more than one test, the tests will then be named `YourExtractor`, `YourExtractor_1`, `YourExtractor_2`, etc. Note that tests with an `only_matching` key in the test's dict are not included in the count. You can also run all the tests in one go with `YourExtractor_all`
+1. Add an import in [`yt_dlp/extractor/_extractors.py`](yt_dlp/extractor/_extractors.py). Note that the class name must end with `IE`. Also note that when adding a parenthesized import group, the last import in the group must have a trailing comma in order for this formatting to be respected by our code formatter.
+1. Run `hatch test YourExtractor`. This *may fail* at first, but you can continually re-run it until you're done. Upon failure, it will output the missing fields and/or correct values which you can copy. If you decide to add more than one test, the tests will then be named `YourExtractor`, `YourExtractor_1`, `YourExtractor_2`, etc. Note that tests with an `only_matching` key in the test's dict are not included in the count. You can also run all the tests in one go with `YourExtractor_all`
1. Make sure you have at least one test for your extractor. Even if all videos covered by the extractor are expected to be inaccessible for automated testing, tests should still be added with a `skip` parameter indicating why the particular test is disabled from running.
1. Have a look at [`yt_dlp/extractor/common.py`](yt_dlp/extractor/common.py) for possible helper methods and a [detailed description of what your extractor should and may return](yt_dlp/extractor/common.py#L119-L440). Add tests and code for as many as you want.
-1. Make sure your code follows [yt-dlp coding conventions](#yt-dlp-coding-conventions) and check the code with [flake8](https://flake8.pycqa.org/en/latest/index.html#quickstart):
+1. Make sure your code follows [yt-dlp coding conventions](#yt-dlp-coding-conventions), passes [ruff](https://docs.astral.sh/ruff/tutorial/#getting-started) code checks and is properly formatted:
+
+ ```shell
+ $ hatch fmt --check
+ ```
- $ flake8 yt_dlp/extractor/yourextractor.py
+ You can use `hatch fmt` to automatically fix problems. Rules that the linter/formatter enforces should not be disabled with `# noqa` unless a maintainer requests it. The only exception allowed is for old/printf-style string formatting in GraphQL query templates (use `# noqa: UP031`).
1. Make sure your code works under all [Python](https://www.python.org/) versions supported by yt-dlp, namely CPython and PyPy for Python 3.8 and above. Backward compatibility is not required for even older versions of Python.
1. When the tests pass, [add](https://git-scm.com/docs/git-add) the new files, [commit](https://git-scm.com/docs/git-commit) them and [push](https://git-scm.com/docs/git-push) the result, like this:
- $ git add yt_dlp/extractor/_extractors.py
- $ git add yt_dlp/extractor/yourextractor.py
- $ git commit -m '[yourextractor] Add extractor'
- $ git push origin yourextractor
+ ```shell
+ $ git add yt_dlp/extractor/_extractors.py
+ $ git add yt_dlp/extractor/yourextractor.py
+ $ git commit -m '[yourextractor] Add extractor'
+ $ git push origin yourextractor
+ ```
1. Finally, [create a pull request](https://help.github.com/articles/creating-a-pull-request). We'll then review and merge it.
projects / yt-dlp.git / blobdiff