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FAQ

Is the Ruff linter compatible with Black?

Yes. The Ruff linter is compatible with Black out-of-the-box, as long as the line-length setting is consistent between the two.

Ruff is designed to be used alongside a formatter (like Ruff's own formatter, or Black) and, as such, will defer implementing stylistic rules that are obviated by automated formatting.

Note that Ruff's linter and Black treat line-length enforcement a little differently. Black, like Ruff's formatter, makes a best-effort attempt to adhere to the line-length, but avoids automatic line-wrapping in some cases (e.g., within comments). Ruff, on the other hand, will flag line-too-long (E501) for any line that exceeds the line-length setting. As such, if line-too-long (E501) is enabled, Ruff can still trigger line-length violations even when Black or ruff format is enabled.

How does Ruff's formatter compare to Black?

The Ruff formatter is designed to be a drop-in replacement for Black.

Specifically, the formatter is intended to emit near-identical output when run over Black-formatted code. When run over extensive Black-formatted projects like Django and Zulip, > 99.9% of lines are formatted identically. When migrating an existing project from Black to Ruff, you should expect to see a few differences on the margins, but the vast majority of your code should be unchanged.

When run over non-Black-formatted code, the formatter makes some different decisions than Black, and so more deviations should be expected, especially around the treatment of end-of-line comments.

See Black compatibility for more.

How does Ruff's linter compare to Flake8?

Ruff can be used as a drop-in replacement for Flake8 when used (1) without or with a small number of plugins, (2) alongside Black, and (3) on Python 3 code.

Under those conditions, Ruff implements every rule in Flake8. In practice, that means Ruff implements all of the F rules (which originate from Pyflakes), along with a subset of the E and W rules (which originate from pycodestyle).

Ruff also re-implements some of the most popular Flake8 plugins and related code quality tools natively, including:

Note that, in some cases, Ruff uses different rule codes and prefixes than would be found in the originating Flake8 plugins. For example, Ruff uses TID252 to represent the I252 rule from flake8-tidy-imports. This helps minimize conflicts across plugins and allows any individual plugin to be toggled on or off with a single (e.g.) --select TID, as opposed to --select I2 (to avoid conflicts with the isort rules, like I001).

Beyond the rule set, Ruff's primary limitation vis-à-vis Flake8 is that it does not support custom lint rules. (Instead, popular Flake8 plugins are re-implemented in Rust as part of Ruff itself.) One minor difference is that Ruff doesn't include all the 'opinionated' rules from flake8-bugbear.

How does Ruff's linter compare to Pylint?

At time of writing, Pylint implements ~409 total rules, while Ruff implements over 800, of which at least 209 overlap with the Pylint rule set (see: #970).

Pylint implements many rules that Ruff does not, and vice versa. For example, Pylint does more type inference than Ruff (e.g., Pylint can validate the number of arguments in a function call). As such, Ruff is not a "pure" drop-in replacement for Pylint (and vice versa), as they enforce different sets of rules.

Despite these differences, many users have successfully switched from Pylint to Ruff, especially those using Ruff alongside a type checker, which can cover some of the functionality that Pylint provides.

Like Flake8, Pylint supports plugins (called "checkers"), while Ruff implements all rules natively and does not support custom or third-party rules. Unlike Pylint, Ruff is capable of automatically fixing its own lint violations.

In some cases, Ruff's rules may yield slightly different results than their Pylint counterparts. For example, Ruff's too-many-branches does not count try blocks as their own branches, unlike Pylint's R0912. Ruff's PL rule group also includes a small number of rules from Pylint extensions (like magic-value-comparison), which need to be explicitly activated when using Pylint. By enabling Ruff's PL group, you may see violations for rules that weren't previously enabled through your Pylint configuration.

Pylint parity is being tracked in #970.

How does Ruff compare to Mypy, or Pyright, or Pyre?

Ruff is a linter, not a type checker. It can detect some of the same problems that a type checker can, but a type checker will catch certain errors that Ruff would miss. The opposite is also true: Ruff will catch certain errors that a type checker would typically ignore.

For example, unlike a type checker, Ruff will notify you if an import is unused, by looking for references to that import in the source code; on the other hand, a type checker could flag that you passed an integer argument to a function that expects a string, which Ruff would miss. The tools are complementary.

It's recommended that you use Ruff in conjunction with a type checker, like Mypy, Pyright, or Pyre, with Ruff providing faster feedback on lint violations and the type checker providing more detailed feedback on type errors.

Which tools does Ruff replace?

Today, Ruff can be used to replace Flake8 when used with any of the following plugins:

Ruff can also replace Black, isort, yesqa, eradicate, and most of the rules implemented in pyupgrade.

If you're looking to use Ruff, but rely on an unsupported Flake8 plugin, feel free to file an issue.

Do I have to use Ruff's linter and formatter together?

Nope! Ruff's linter and formatter can be used independently of one another -- you can use Ruff as a formatter, but not a linter, or vice versa.

What versions of Python does Ruff support?

Ruff can lint code for any Python version from 3.7 onwards, including Python 3.13.

Ruff does not support Python 2. Ruff may run on pre-Python 3.7 code, although such versions are not officially supported (e.g., Ruff does not respect type comments).

Ruff is installable under any Python version from 3.7 onwards.

Do I need to install Rust to use Ruff?

Nope! Ruff is available as ruff on PyPI:

$ pip install ruff

Ruff ships with wheels for all major platforms, which enables pip to install Ruff without relying on Rust at all.

Can I write my own linter plugins for Ruff?

Ruff does not yet support third-party plugins, though a plugin system is within-scope for the project. See #283 for more.

How does Ruff's import sorting compare to isort?

Ruff's import sorting is intended to be near-equivalent to isort's when using isort's profile = "black".

There are a few known differences in how Ruff and isort treat aliased imports, and in how Ruff and isort treat inline comments in some cases (see: #1381, #2104).

For example, Ruff tends to group non-aliased imports from the same module:

from numpy import cos, int8, int16, int32, int64, tan, uint8, uint16, uint32, uint64
from numpy import sin as np_sin

Whereas isort splits them into separate import statements at each aliased boundary:

from numpy import cos, int8, int16, int32, int64
from numpy import sin as np_sin
from numpy import tan, uint8, uint16, uint32, uint64

Ruff also correctly classifies some modules as standard-library that aren't recognized by isort, like _string and idlelib.

Like isort, Ruff's import sorting is compatible with Black.

How does Ruff determine which of my imports are first-party, third-party, etc.?

Ruff accepts a src option that in your pyproject.toml, ruff.toml, or .ruff.toml file, specifies the directories that Ruff should consider when determining whether an import is first-party.

For example, if you have a project with the following structure:

my_project
├── pyproject.toml
└── src
    └── foo
        ├── __init__.py
        └── bar
            ├── __init__.py
            └── baz.py

When Ruff sees an import like import foo, it will then iterate over the src directories, looking for a corresponding Python module (in reality, a directory named foo or a file named foo.py).

If the src field is omitted, Ruff will default to using the "project root", along with a "src" subdirectory, as the first-party sources, to support both flat and nested project layouts. The "project root" is typically the directory containing your pyproject.toml, ruff.toml, or .ruff.toml file, unless a configuration file is provided on the command-line via the --config option, in which case, the current working directory is used as the project root.

In this case, Ruff would check the "src" directory by default, but we can configure it as an explicit, exclusive first-party source like so:

=== "pyproject.toml"

```toml
[tool.ruff]
# Ruff supports a top-level `src` option in lieu of isort's `src_paths` setting.
# All paths are relative to the project root, which is the directory containing the pyproject.toml.
src = ["src"]
```

=== "ruff.toml"

```toml
# Ruff supports a top-level `src` option in lieu of isort's `src_paths` setting.
# All paths are relative to the project root, which is the directory containing the pyproject.toml.
src = ["src"]
```

If your pyproject.toml, ruff.toml, or .ruff.toml extends another configuration file, Ruff will still use the directory containing your pyproject.toml, ruff.toml, or .ruff.toml file as the project root (as opposed to the directory of the file pointed to via the extends option).

For example, if you add a configuration file to the tests directory in the above example, you'll want to explicitly set the src option in the extended configuration file:

=== "pyproject.toml"

```toml
[tool.ruff]
extend = "../pyproject.toml"
src = ["../src"]
```

=== "ruff.toml"

```toml
extend = "../pyproject.toml"
src = ["../src"]
```

Beyond this src-based detection, Ruff will also attempt to determine the current Python package for a given Python file, and mark imports from within the same package as first-party. For example, above, baz.py would be identified as part of the Python package beginning at ./my_project/src/foo, and so any imports in baz.py that begin with foo (like import foo.bar) would be considered first-party based on this same-package heuristic.

For a detailed explanation of src resolution, see the contributing guide.

Ruff can also be configured to treat certain modules as (e.g.) always first-party, regardless of their location on the filesystem. For example, you can set known-first-party like so:

=== "pyproject.toml"

```toml
[tool.ruff]
src = ["src", "tests"]

[tool.ruff.lint]
select = [
    # Pyflakes
    "F",
    # Pycodestyle
    "E",
    "W",
    # isort
    "I001"
]

[tool.ruff.lint.isort]
known-first-party = ["my_module1", "my_module2"]
```

=== "ruff.toml"

```toml
src = ["src", "tests"]

[lint]
select = [
    # Pyflakes
    "F",
    # Pycodestyle
    "E",
    "W",
    # isort
    "I001"
]

[lint.isort]
known-first-party = ["my_module1", "my_module2"]
```

Ruff does not yet support all of isort's configuration options, though it does support many of them. You can find the supported settings in the API reference.

Does Ruff support Jupyter Notebooks?

Ruff has built-in support for linting and formatting Jupyter Notebooks. Refer to the Jupyter Notebook section for more details.

Ruff also integrates with nbQA, a tool for running linters and code formatters over Jupyter Notebooks.

After installing ruff and nbqa, you can run Ruff over a notebook like so:

$ nbqa ruff Untitled.ipynb
Untitled.ipynb:cell_1:2:5: F841 Local variable `x` is assigned to but never used
Untitled.ipynb:cell_2:1:1: E402 Module level import not at top of file
Untitled.ipynb:cell_2:1:8: F401 `os` imported but unused
Found 3 errors.
1 potentially fixable with the --fix option.

Does Ruff support NumPy- or Google-style docstrings?

Yes! To enforce a docstring convention, add a convention setting following to your configuration file:

=== "pyproject.toml"

```toml
[tool.ruff.lint.pydocstyle]
convention = "google"  # Accepts: "google", "numpy", or "pep257".
```

=== "ruff.toml"

```toml
[lint.pydocstyle]
convention = "google"  # Accepts: "google", "numpy", or "pep257".
```

For example, if you're coming from flake8-docstrings, and your originating configuration uses --docstring-convention=numpy, you'd instead set convention = "numpy" in your pyproject.toml, as above.

Alongside convention, you'll want to explicitly enable the D rule code prefix, since the D rules are not enabled by default:

=== "pyproject.toml"

```toml
[tool.ruff.lint]
select = ["D"]

[tool.ruff.lint.pydocstyle]
convention = "google"
```

=== "ruff.toml"

```toml
[lint]
select = ["D"]

[lint.pydocstyle]
convention = "google"
```

Enabling a convention will disable any rules that are not included in the specified convention. As such, the intended workflow is to enable a convention and then selectively enable or disable any additional rules on top of it:

=== "pyproject.toml"

```toml
[tool.ruff.lint]
select = [
    "D",
    # Augment the convention by requiring an imperative mood for all docstrings.
    "D401",
]

ignore = [
    # Relax the convention by _not_ requiring documentation for every function parameter.
    "D417",
]

[tool.ruff.lint.pydocstyle]
convention = "google"
```

=== "ruff.toml"

```toml
[lint]
select = [
    "D",
    # Augment the convention by requiring an imperative mood for all docstrings.
    "D401",
]

ignore = [
    # Relax the convention by _not_ requiring documentation for every function parameter.
    "D417",
]

[lint.pydocstyle]
convention = "google"
```

The PEP 257 convention includes all D errors apart from: D203, D212, D213, D214, D215, D404, D405, D406, D407, D408, D409, D410, D411, D413, D415, D416, and D417.

The NumPy convention includes all D errors apart from: D107, D203, D212, D213, D402, D413, D415, D416, and D417.

The Google convention includes all D errors apart from: D203, D204, D213, D215, D400, D401, D404, D406, D407, D408, D409, and D413.

By default, no convention is set, and so the enabled rules are determined by the select setting alone.

What is "preview"?

Preview enables a collection of newer rules and fixes that are considered experimental or unstable. See the preview documentation for more details; or, to see which rules are currently in preview, visit the rules reference.

How can I tell what settings Ruff is using to check my code?

Run ruff check /path/to/code.py --show-settings to view the resolved settings for a given file.

I want to use Ruff, but I don't want to use pyproject.toml. What are my options?

In lieu of a pyproject.toml file, you can use a ruff.toml file for configuration. The two files are functionally equivalent and have an identical schema, with the exception that a ruff.toml file can omit the [tool.ruff] section header. For example:

=== "pyproject.toml"

[tool.ruff]
line-length = 88

[tool.ruff.lint.pydocstyle]
convention = "google"

=== "ruff.toml"

line-length = 88

[lint.pydocstyle]
convention = "google"

Ruff doesn't currently support INI files, like setup.cfg or tox.ini.

How can I change Ruff's default configuration?

When no configuration file is found, Ruff will look for a user-specific ruff.toml file as a last resort. This behavior is similar to Flake8's ~/.config/flake8.

On macOS and Linux, Ruff expects that file to be located at ~/.config/ruff/ruff.toml, and respects the XDG_CONFIG_HOME specification.

On Windows, Ruff expects that file to be located at ~\AppData\Roaming\ruff\ruff.toml.

!!! note Prior to v0.5.0, Ruff would read user-specific configuration from ~/Library/Application Support/ruff/ruff.toml on macOS. While Ruff will still respect such configuration files, the use of ~/Library/Application Support is considered deprecated.

For more, see the etcetera crate.

Ruff tried to fix something — but it broke my code. What's going on?

Ruff labels fixes as "safe" and "unsafe". By default, Ruff will fix all violations for which safe fixes are available, while unsafe fixes can be enabled via the unsafe-fixes setting, or passing the --unsafe-fixes flag to ruff check. For more, see the fix documentation.

Even still, given the dynamic nature of Python, it's difficult to have complete certainty when making changes to code, even for seemingly trivial fixes. If a "safe" fix breaks your code, please file an Issue.

How can I disable/force Ruff's color output?

Ruff's color output is powered by the colored crate, which attempts to automatically detect whether the output stream supports color. However, you can force colors off by setting the NO_COLOR environment variable to any value (e.g., NO_COLOR=1), or force colors on by setting FORCE_COLOR to any non-empty value (e.g. FORCE_COLOR=1).

colored also supports the CLICOLOR and CLICOLOR_FORCE environment variables (see the spec).