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## Summary Part of #15383, this PR adds the core infrastructure to check for invalid overloads and adds a diagnostic to raise if there are < 2 overloads for a given definition. ### Design notes The requirements to check the overloads are: * Requires `FunctionType` which has the `to_overloaded` method * The `FunctionType` **should** be for the function that is either the implementation or the last overload if the implementation doesn't exists * Avoid checking any `FunctionType` that are part of an overload chain * Consider visibility constraints This required a couple of iteration to make sure all of the above requirements are fulfilled. #### 1. Use a set to deduplicate The logic would first collect all the `FunctionType` that are part of the overload chain except for the implementation or the last overload if the implementation doesn't exists. Then, when iterating over all the function declarations within the scope, we'd avoid checking these functions. But, this approach would fail to consider visibility constraints as certain overloads _can_ be behind a version check. Those aren't part of the overload chain but those aren't a separate overload chain either. <details><summary>Implementation:</summary> <p> ```rs fn check_overloaded_functions(&mut self) { let function_definitions = || { self.types .declarations .iter() .filter_map(|(definition, ty)| { // Filter out function literals that result from anything other than a function // definition e.g., imports. if let DefinitionKind::Function(function) = definition.kind(self.db()) { ty.inner_type() .into_function_literal() .map(|ty| (ty, definition.symbol(self.db()), function.node())) } else { None } }) }; // A set of all the functions that are part of an overloaded function definition except for // the implementation function and the last overload in case the implementation doesn't // exists. This allows us to collect all the function definitions that needs to be skipped // when checking for invalid overload usages. let mut overloads: HashSet<FunctionType<'db>> = HashSet::default(); for (function, _) in function_definitions() { let Some(overloaded) = function.to_overloaded(self.db()) else { continue; }; if overloaded.implementation.is_some() { overloads.extend(overloaded.overloads.iter().copied()); } else if let Some((_, previous_overloads)) = overloaded.overloads.split_last() { overloads.extend(previous_overloads.iter().copied()); } } for (function, function_node) in function_definitions() { let Some(overloaded) = function.to_overloaded(self.db()) else { continue; }; if overloads.contains(&function) { continue; } // At this point, the `function` variable is either the implementation function or the // last overloaded function if the implementation doesn't exists. if overloaded.overloads.len() < 2 { if let Some(builder) = self .context .report_lint(&INVALID_OVERLOAD, &function_node.name) { let mut diagnostic = builder.into_diagnostic(format_args!( "Function `{}` requires at least two overloads", &function_node.name )); if let Some(first_overload) = overloaded.overloads.first() { diagnostic.annotate( self.context .secondary(first_overload.focus_range(self.db())) .message(format_args!("Only one overload defined here")), ); } } } } } ``` </p> </details> #### 2. Define a `predecessor` query The `predecessor` query would return the previous `FunctionType` for the given `FunctionType` i.e., the current logic would be extracted to be a query instead. This could then be used to make sure that we're checking the entire overload chain once. The way this would've been implemented is to have a `to_overloaded` implementation which would take the root of the overload chain instead of the leaf. But, this would require updates to the use-def map to somehow be able to return the _following_ functions for a given definition. #### 3. Create a successor link This is what Pyrefly uses, we'd create a forward link between two functions that are involved in an overload chain. This means that for a given function, we can get the successor function. This could be used to find the _leaf_ of the overload chain which can then be used with the `to_overloaded` method to get the entire overload chain. But, this would also require updating the use-def map to be able to "see" the _following_ function. ### Implementation This leads us to the final implementation that this PR implements which is to consider the overloaded functions using: * Collect all the **function symbols** that are defined **and** called within the same file. This could potentially be an overloaded function * Use the public bindings to get the leaf of the overload chain and use that to get the entire overload chain via `to_overloaded` and perform the check This has a limitation that in case a function redefines an overload, then that overload will not be checked. For example: ```py from typing import overload @overload def f() -> None: ... @overload def f(x: int) -> int: ... # The above overload will not be checked as the below function with the same name # shadows it def f(*args: int) -> int: ... ``` ## Test Plan Update existing mdtest and add snapshot diagnostics. |
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| assets | ||
| crates | ||
| docs | ||
| fuzz | ||
| playground | ||
| python | ||
| scripts | ||
| .editorconfig | ||
| .gitattributes | ||
| .gitignore | ||
| .ignore | ||
| .markdownlint.yaml | ||
| .pre-commit-config.yaml | ||
| .prettierignore | ||
| _typos.toml | ||
| BREAKING_CHANGES.md | ||
| Cargo.lock | ||
| Cargo.toml | ||
| CHANGELOG.md | ||
| clippy.toml | ||
| CODE_OF_CONDUCT.md | ||
| CONTRIBUTING.md | ||
| Dockerfile | ||
| knot.schema.json | ||
| LICENSE | ||
| mkdocs.insiders.yml | ||
| mkdocs.public.yml | ||
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| pyproject.toml | ||
| README.md | ||
| ruff.schema.json | ||
| rust-toolchain.toml | ||
| SECURITY.md | ||
Ruff
An extremely fast Python linter and code formatter, written in Rust.
Linting the CPython codebase from scratch.
- ⚡️ 10-100x faster than existing linters (like Flake8) and formatters (like Black)
- 🐍 Installable via
pip - 🛠️
pyproject.tomlsupport - 🤝 Python 3.13 compatibility
- ⚖️ Drop-in parity with Flake8, isort, and Black
- 📦 Built-in caching, to avoid re-analyzing unchanged files
- 🔧 Fix support, for automatic error correction (e.g., automatically remove unused imports)
- 📏 Over 800 built-in rules, with native re-implementations of popular Flake8 plugins, like flake8-bugbear
- ⌨️ First-party editor integrations for VS Code and more
- 🌎 Monorepo-friendly, with hierarchical and cascading configuration
Ruff aims to be orders of magnitude faster than alternative tools while integrating more functionality behind a single, common interface.
Ruff can be used to replace Flake8 (plus dozens of plugins), Black, isort, pydocstyle, pyupgrade, autoflake, and more, all while executing tens or hundreds of times faster than any individual tool.
Ruff is extremely actively developed and used in major open-source projects like:
...and many more.
Ruff is backed by Astral. Read the launch post, or the original project announcement.
Testimonials
Sebastián Ramírez, creator of FastAPI:
Ruff is so fast that sometimes I add an intentional bug in the code just to confirm it's actually running and checking the code.
Nick Schrock, founder of Elementl, co-creator of GraphQL:
Why is Ruff a gamechanger? Primarily because it is nearly 1000x faster. Literally. Not a typo. On our largest module (dagster itself, 250k LOC) pylint takes about 2.5 minutes, parallelized across 4 cores on my M1. Running ruff against our entire codebase takes .4 seconds.
Bryan Van de Ven, co-creator of Bokeh, original author of Conda:
Ruff is ~150-200x faster than flake8 on my machine, scanning the whole repo takes ~0.2s instead of ~20s. This is an enormous quality of life improvement for local dev. It's fast enough that I added it as an actual commit hook, which is terrific.
Timothy Crosley, creator of isort:
Just switched my first project to Ruff. Only one downside so far: it's so fast I couldn't believe it was working till I intentionally introduced some errors.
Tim Abbott, lead developer of Zulip:
This is just ridiculously fast...
ruffis amazing.
Table of Contents
For more, see the documentation.
Getting Started
For more, see the documentation.
Installation
Ruff is available as ruff on PyPI.
Invoke Ruff directly with uvx:
uvx ruff check # Lint all files in the current directory.
uvx ruff format # Format all files in the current directory.
Or install Ruff with uv (recommended), pip, or pipx:
# With uv.
uv tool install ruff@latest # Install Ruff globally.
uv add --dev ruff # Or add Ruff to your project.
# With pip.
pip install ruff
# With pipx.
pipx install ruff
Starting with version 0.5.0, Ruff can be installed with our standalone installers:
# On macOS and Linux.
curl -LsSf https://astral.sh/ruff/install.sh | sh
# On Windows.
powershell -c "irm https://astral.sh/ruff/install.ps1 | iex"
# For a specific version.
curl -LsSf https://astral.sh/ruff/0.11.7/install.sh | sh
powershell -c "irm https://astral.sh/ruff/0.11.7/install.ps1 | iex"
You can also install Ruff via Homebrew, Conda, and with a variety of other package managers.
Usage
To run Ruff as a linter, try any of the following:
ruff check # Lint all files in the current directory (and any subdirectories).
ruff check path/to/code/ # Lint all files in `/path/to/code` (and any subdirectories).
ruff check path/to/code/*.py # Lint all `.py` files in `/path/to/code`.
ruff check path/to/code/to/file.py # Lint `file.py`.
ruff check @arguments.txt # Lint using an input file, treating its contents as newline-delimited command-line arguments.
Or, to run Ruff as a formatter:
ruff format # Format all files in the current directory (and any subdirectories).
ruff format path/to/code/ # Format all files in `/path/to/code` (and any subdirectories).
ruff format path/to/code/*.py # Format all `.py` files in `/path/to/code`.
ruff format path/to/code/to/file.py # Format `file.py`.
ruff format @arguments.txt # Format using an input file, treating its contents as newline-delimited command-line arguments.
Ruff can also be used as a pre-commit hook via ruff-pre-commit:
- repo: https://github.com/astral-sh/ruff-pre-commit
# Ruff version.
rev: v0.11.7
hooks:
# Run the linter.
- id: ruff
args: [ --fix ]
# Run the formatter.
- id: ruff-format
Ruff can also be used as a VS Code extension or with various other editors.
Ruff can also be used as a GitHub Action via
ruff-action:
name: Ruff
on: [ push, pull_request ]
jobs:
ruff:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: astral-sh/ruff-action@v3
Configuration
Ruff can be configured through a pyproject.toml, ruff.toml, or .ruff.toml file (see:
Configuration, or Settings
for a complete list of all configuration options).
If left unspecified, Ruff's default configuration is equivalent to the following ruff.toml file:
# Exclude a variety of commonly ignored directories.
exclude = [
".bzr",
".direnv",
".eggs",
".git",
".git-rewrite",
".hg",
".ipynb_checkpoints",
".mypy_cache",
".nox",
".pants.d",
".pyenv",
".pytest_cache",
".pytype",
".ruff_cache",
".svn",
".tox",
".venv",
".vscode",
"__pypackages__",
"_build",
"buck-out",
"build",
"dist",
"node_modules",
"site-packages",
"venv",
]
# Same as Black.
line-length = 88
indent-width = 4
# Assume Python 3.9
target-version = "py39"
[lint]
# Enable Pyflakes (`F`) and a subset of the pycodestyle (`E`) codes by default.
select = ["E4", "E7", "E9", "F"]
ignore = []
# Allow fix for all enabled rules (when `--fix`) is provided.
fixable = ["ALL"]
unfixable = []
# Allow unused variables when underscore-prefixed.
dummy-variable-rgx = "^(_+|(_+[a-zA-Z0-9_]*[a-zA-Z0-9]+?))$"
[format]
# Like Black, use double quotes for strings.
quote-style = "double"
# Like Black, indent with spaces, rather than tabs.
indent-style = "space"
# Like Black, respect magic trailing commas.
skip-magic-trailing-comma = false
# Like Black, automatically detect the appropriate line ending.
line-ending = "auto"
Note that, in a pyproject.toml, each section header should be prefixed with tool.ruff. For
example, [lint] should be replaced with [tool.ruff.lint].
Some configuration options can be provided via dedicated command-line arguments, such as those related to rule enablement and disablement, file discovery, and logging level:
ruff check --select F401 --select F403 --quiet
The remaining configuration options can be provided through a catch-all --config argument:
ruff check --config "lint.per-file-ignores = {'some_file.py' = ['F841']}"
To opt in to the latest lint rules, formatter style changes, interface updates, and more, enable
preview mode by setting preview = true in your configuration
file or passing --preview on the command line. Preview mode enables a collection of unstable
features that may change prior to stabilization.
See ruff help for more on Ruff's top-level commands, or ruff help check and ruff help format
for more on the linting and formatting commands, respectively.
Rules
Ruff supports over 800 lint rules, many of which are inspired by popular tools like Flake8, isort, pyupgrade, and others. Regardless of the rule's origin, Ruff re-implements every rule in Rust as a first-party feature.
By default, Ruff enables Flake8's F rules, along with a subset of the E rules, omitting any
stylistic rules that overlap with the use of a formatter, like ruff format or
Black.
If you're just getting started with Ruff, the default rule set is a great place to start: it catches a wide variety of common errors (like unused imports) with zero configuration.
Beyond the defaults, Ruff re-implements some of the most popular Flake8 plugins and related code quality tools, including:
- autoflake
- eradicate
- flake8-2020
- flake8-annotations
- flake8-async
- flake8-bandit (#1646)
- flake8-blind-except
- flake8-boolean-trap
- flake8-bugbear
- flake8-builtins
- flake8-commas
- flake8-comprehensions
- flake8-copyright
- flake8-datetimez
- flake8-debugger
- flake8-django
- flake8-docstrings
- flake8-eradicate
- flake8-errmsg
- flake8-executable
- flake8-future-annotations
- flake8-gettext
- flake8-implicit-str-concat
- flake8-import-conventions
- flake8-logging
- flake8-logging-format
- flake8-no-pep420
- flake8-pie
- flake8-print
- flake8-pyi
- flake8-pytest-style
- flake8-quotes
- flake8-raise
- flake8-return
- flake8-self
- flake8-simplify
- flake8-slots
- flake8-super
- flake8-tidy-imports
- flake8-todos
- flake8-type-checking
- flake8-use-pathlib
- flynt (#2102)
- isort
- mccabe
- pandas-vet
- pep8-naming
- pydocstyle
- pygrep-hooks
- pylint-airflow
- pyupgrade
- tryceratops
- yesqa
For a complete enumeration of the supported rules, see Rules.
Contributing
Contributions are welcome and highly appreciated. To get started, check out the contributing guidelines.
You can also join us on Discord.
Support
Having trouble? Check out the existing issues on GitHub, or feel free to open a new one.
You can also ask for help on Discord.
Acknowledgements
Ruff's linter draws on both the APIs and implementation details of many other tools in the Python ecosystem, especially Flake8, Pyflakes, pycodestyle, pydocstyle, pyupgrade, and isort.
In some cases, Ruff includes a "direct" Rust port of the corresponding tool. We're grateful to the maintainers of these tools for their work, and for all the value they've provided to the Python community.
Ruff's formatter is built on a fork of Rome's rome_formatter,
and again draws on both API and implementation details from Rome,
Prettier, and Black.
Ruff's import resolver is based on the import resolution algorithm from Pyright.
Ruff is also influenced by a number of tools outside the Python ecosystem, like Clippy and ESLint.
Ruff is the beneficiary of a large number of contributors.
Ruff is released under the MIT license.
Who's Using Ruff?
Ruff is used by a number of major open-source projects and companies, including:
- Albumentations
- Amazon (AWS SAM)
- Anthropic (Python SDK)
- Apache Airflow
- AstraZeneca (Magnus)
- Babel
- Benchling (Refac)
- Bokeh
- CrowdCent (NumerBlox)
- Cryptography (PyCA)
- CERN (Indico)
- DVC
- Dagger
- Dagster
- Databricks (MLflow)
- Dify
- FastAPI
- Godot
- Gradio
- Great Expectations
- HTTPX
- Hatch
- Home Assistant
- Hugging Face (Transformers, Datasets, Diffusers)
- IBM (Qiskit)
- ING Bank (popmon, probatus)
- Ibis
- ivy
- JAX
- Jupyter
- Kraken Tech
- LangChain
- Litestar
- LlamaIndex
- Matrix (Synapse)
- MegaLinter
- Meltano (Meltano CLI, Singer SDK)
- Microsoft (Semantic Kernel, ONNX Runtime, LightGBM)
- Modern Treasury (Python SDK)
- Mozilla (Firefox)
- Mypy
- Nautobot
- Netflix (Dispatch)
- Neon
- Nokia
- NoneBot
- NumPyro
- ONNX
- OpenBB
- Open Wine Components
- PDM
- PaddlePaddle
- Pandas
- Pillow
- Poetry
- Polars
- PostHog
- Prefect (Python SDK, Marvin)
- PyInstaller
- PyMC
- PyMC-Marketing
- pytest
- PyTorch
- Pydantic
- Pylint
- PyVista
- Reflex
- River
- Rippling
- Robyn
- Saleor
- Scale AI (Launch SDK)
- SciPy
- Snowflake (SnowCLI)
- Sphinx
- Stable Baselines3
- Starlette
- Streamlit
- The Algorithms
- Vega-Altair
- WordPress (Openverse)
- ZenML
- Zulip
- build (PyPA)
- cibuildwheel (PyPA)
- delta-rs
- featuretools
- meson-python
- nox
- pip
Show Your Support
If you're using Ruff, consider adding the Ruff badge to your project's README.md:
[](https://github.com/astral-sh/ruff)
...or README.rst:
.. image:: https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json
:target: https://github.com/astral-sh/ruff
:alt: Ruff
...or, as HTML:
<a href="https://github.com/astral-sh/ruff"><img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json" alt="Ruff" style="max-width:100%;"></a>
License
This repository is licensed under the MIT License
