## Summary
As discussed in Discord, and similar to oxc, we're going to refer to
this as `.semantic()` everywhere.
While I was auditing usages of `model: &SemanticModel`, I also changed
as many function signatures as I could find to consistently take the
model as the _last_ argument, rather than the first.
## Summary
This PR tackles a corner case that we'll need to support local symbol
renaming. It relates to a nuance in how we want handle annotations
(i.e., `AnnAssign` statements with no value, like `x: int` in a function
body).
When we see a statement like:
```python
x: int
```
We create a `BindingKind::Annotation` for `x`. This is a special
`BindingKind` that the resolver isn't allowed to return. For example,
given:
```python
x: int
print(x)
```
The second line will yield an `undefined-name` error.
So why does this `BindingKind` exist at all? In Pyflakes, to support the
`unused-annotation` lint:
```python
def f():
x: int # unused-annotation
```
If we don't track `BindingKind::Annotation`, we can't lint for unused
variables that are only "defined" via annotations.
There are a few other wrinkles to `BindingKind::Annotation`. One is
that, if a binding already exists in the scope, we actually just discard
the `BindingKind`. So in this case:
```python
x = 1
x: int
```
When we go to create the `BindingKind::Annotation` for the second
statement, we notice that (1) we're creating an annotation but (2) the
scope already has binding for the name -- so we just drop the binding on
the floor. This has the nice property that annotations aren't considered
to "shadow" another binding, which is important in a bunch of places
(e.g., if we have `import os; os: int`, we still consider `os` to be an
import, as we should). But it also means that these "delayed"
annotations are one of the few remaining references that we don't track
anywhere in the semantic model.
This PR adds explicit support for these via a new `delayed_annotations`
attribute on the semantic model. These should be extremely rare, but we
do need to track them if we want to support local symbol renaming.
### This isn't the right way to model this
This isn't the right way to model this.
Here's an alternative:
- Remove `BindingKind::Annotation`, and treat annotations as their own,
separate concept.
- Instead of storing a map from name to `BindingId` on each `Scope`,
store a map from name to... `SymbolId`.
- Introduce a `Symbol` abstraction, where a symbol can point to a
current binding, and a list of annotations, like:
```rust
pub struct Symbol {
binding: Option<BindingId>,
annotations: Vec<AnnotationId>
}
```
If we did this, we could appropriately model the semantics described
above. When we go to resolve a binding, we ignore annotations (always).
When we try to find unused variables, we look through the list of
symbols, and have sufficient information to discriminate between
annotations and bound variables. Etc.
The main downside of this `Symbol`-based approach is that it's going to
take a lot more work to implement, and it'll be less performant (we'll
be storing more data per symbol, and our binding lookups will have an
added layer of indirection).
## Summary
We now _always_ generate fixes, so `FixMode::None` and
`FixMode::Generate` are redundant. We can also remove the TODO around
`--fix-dry-run`, since that's our default behavior.
Closes#5081.
## Summary
Small follow-up to #4888 to add a dedicated `ResolvedRead` case for
unbound locals, mostly for clarity and documentation purposes (no
behavior changes).
## Test Plan
`cargo test`
## Summary
Our current mechanism for handling deletions (e.g., `del x`) is to
remove the symbol from the scope's `bindings` table. This "does the
right thing", in that if we then reference a deleted symbol, we're able
to determine that it's unbound -- but it causes a variety of problems,
mostly in that it makes certain bindings and references unreachable
after-the-fact.
Consider:
```python
x = 1
print(x)
del x
```
If we analyze this code _after_ running the semantic model over the AST,
we'll have no way of knowing that `x` was ever introduced in the scope,
much less that it was bound to a value, read, and then deleted --
because we effectively erased `x` from the model entirely when we hit
the deletion.
In practice, this will make it impossible for us to support local symbol
renames. It also means that certain rules that we want to move out of
the model-building phase and into the "check dead scopes" phase wouldn't
work today, since we'll have lost important information about the source
code.
This PR introduces two new `BindingKind` variants to model deletions:
- `BindingKind::Deletion`, which represents `x = 1; del x`.
- `BindingKind::UnboundException`, which represents:
```python
try:
1 / 0
except Exception as e:
pass
```
In the latter case, `e` gets unbound after the exception handler
(assuming it's triggered), so we want to handle it similarly to a
deletion.
The main challenge here is auditing all of our existing `Binding` and
`Scope` usages to understand whether they need to accommodate deletions
or otherwise behave differently. If you look one commit back on this
branch, you'll see that the code is littered with `NOTE(charlie)`
comments that describe the reasoning behind changing (or not) each of
those call sites. I've also augmented our test suite in preparation for
this change over a few prior PRs.
### Alternatives
As an alternative, I considered introducing a flag to `BindingFlags`,
like `BindingFlags::UNBOUND`, and setting that at the appropriate time.
This turned out to be a much more difficult change, because we tend to
match on `BindingKind` all over the place (e.g., we have a bunch of code
blocks that only run when a `BindingKind` is
`BindingKind::Importation`). As a result, introducing these new
`BindingKind` variants requires only a few changes at the client sites.
Adding a flag would've required a much wider-reaching change.
## Summary
This behavior dates back to a Pyflakes commit (5fc37cbd), which was used
to allow this test to pass:
```py
from __future__ import annotations
T: object
def f(t: T): pass
def g(t: 'T'): pass
```
But, I think this is an error. Mypy and Pyright don't accept it -- you
can only use variables as type annotations if they're type aliases
(i.e., annotated with `TypeAlias`), in which case, there has to be an
assignment on the right-hand side (see: [PEP
613](https://peps.python.org/pep-0613/)).
## Summary
This PR corrects a misunderstanding I had related to Python's handling
of bound exceptions.
Previously, I thought this code ran without error:
```py
def f():
x = 1
try:
1 / 0
except Exception as x:
pass
print(x)
```
My understanding was that `except Exception as x` bound `x` within the
`except` block, but then restored the `x = 1` binding after exiting the
block.
In practice, however, this throws a `UnboundLocalError` error, because
`x` becomes "unbound" after exiting the exception handler. It's similar
to a `del` statement in this way.
This PR removes our behavior to "restore" the previous binding. This
could lead to faulty analysis in conditional blocks due to our lack of
control flow analysis, but those same problems already exist for `del`
statements.
## Summary
In a dataclass:
```py
from dataclasses import dataclass
@dataclass
class X:
class_var = {}
x: int
```
`class_var` isn't actually a dataclass attribute, since it's
unannotated. This PR removes such attributes from RUF008
(`mutable-dataclass-default`), but it does enforce them in RUF012
(`mutable-class-default`), since those should be annotated with
`ClassVar` like any other mutable class attribute.
Closes#5043.
## Summary
This adds `json-lines` (https://jsonlines.org/ or http://ndjson.org/) as
an output format.
I'm sure you already know, but
* JSONL is more greppable (each record is a single line) than the pretty
JSON
* JSONL is faster to ingest piecewise (and/or in parallel) than JSON
## Test Plan
Snapshot test in the new module :)
I've written done my condensed learnings from working on the formatter
so that others can have an easier start working on it.
This is a pure docs change
## Summary
Per the [API
reference](https://docs.pytest.org/en/7.1.x/reference/reference.html#pytest.fail),
`reason` was added in version 7, and is equivalent to `msg` (but
preferred going forward).
I also grepped for `msg` usages in `flake8_pytest_style`, but found no
others (apart from those that reference `unittest` APIs.)
Closes#3387.
## Summary
This PR adds autofixer for rule ISC001 in cases where both string
literals are of the same kind and with same quotes (double / single).
Fixes#4829
## Test Plan
I added testcases with different combinations of string literals.
## Summary
This PR (1) avoids flagging `TypedDict` and `NamedTuple` conversions
when attributes are dunder methods, like `__dict__`, and (2) avoids
flagging the `A003` shadowed-attribute rule for `TypedDict` classes at
all, where it doesn't really apply (since those attributes are only
accessed via subscripting anyway).
Closes#5027.
## Summary
A few of our rules look at the parentheses that follow a class
definition (e.g., `class Foo(object):`) and attempt to modify those
parentheses. Neither of those rules were behaving properly in the
presence of decorators, which were recently added to the statement
range.
## Test Plan
`cargo test` with a variety of new fixture tests.
## Summary
Add rule to disallow implicit optional with autofix.
Currently, I've added it under `RUF` category.
### Limitation
Type aliases could result in false positive:
```python
from typing import Optional
StrOptional = Optional[str]
def foo(arg: StrOptional = None):
pass
```
## Test Plan
`cargo test`
resolves: #1983
---------
Co-authored-by: Micha Reiser <micha@reiser.io>
Co-authored-by: Charlie Marsh <charlie.r.marsh@gmail.com>
Improves the `ruff_parse_simple` fuzz harness by adding checks for
parsed locations to ensure they all lie on UTF-8 character boundaries.
This will allow for faster identification of issues like #5004.
This also adds additional details for Apple M1 users and clarifies the
importance of using `init-fuzzer.sh` (thanks for the feedback,
@jasikpark 🙂).
## Summary
Previously the rule for SIM117 explicitly ignored `async with`
statements as it would incorrectly suggestion to merge `async with` and
regular `with` statements as reported in issue #1902.
This partially reverts the fix for that (commit
396be5edea) by enabling the rules for
`async with` statements again, but with a check ensuring that the
statements are both of the same kind, i.e. both `async with` or both
(just) `with` statements.
Closes#3025
## Test Plan
Updated and existing test and added a new test case from #3025.
## Summary
Add support for applying auto-fixes in Jupyter Notebook.
### Solution
Cell offsets are the boundaries for each cell in the concatenated source
code. They are represented using `TextSize`. It includes the start and
end offset as well, thus creating a range for each cell. These offsets
are updated using the `SourceMap` markers.
### SourceMap
`SourceMap` contains markers constructed from each edits which tracks
the original source code position to the transformed positions. The
following drawing might make it clear:
The center column where the dotted lines are present are the markers
included in the `SourceMap`. The `Notebook` looks at these markers and
updates the cell offsets after each linter loop. If you notice closely,
the destination takes into account all of the markers before it.
The index is constructed only when required as it's only used to render
the diagnostics. So, a `OnceCell` is used for this purpose. The cell
offsets, cell content and the index will be updated after each iteration
of linting in the mentioned order. The order is important here as the
content is updated as per the new offsets and index is updated as per
the new content.
## Limitations
### 1
Styling rules such as the ones in `pycodestyle` will not be applicable
everywhere in Jupyter notebook, especially at the cell boundaries. Let's
take an example where a rule suggests to have 2 blank lines before a
function and the cells contains the following code:
```python
import something
# ---
def first():
pass
def second():
pass
```
(Again, the comment is only to visualize cell boundaries.)
In the concatenated source code, the 2 blank lines will be added but it
shouldn't actually be added when we look in terms of Jupyter notebook.
It's as if the function `first` is at the start of a file.
`nbqa` solves this by recording newlines before and after running
`autopep8`, then running the tool and restoring the newlines at the end
(refer https://github.com/nbQA-dev/nbQA/pull/807).
## Test Plan
Three commands were run in order with common flags (`--select=ALL
--no-cache --isolated`) to isolate which stage the problem is occurring:
1. Only diagnostics
2. Fix with diff (`--fix --diff`)
3. Fix (`--fix`)
### https://github.com/facebookresearch/segment-anything
```
-------------------------------------------------------------------------------
Jupyter Notebooks 3 0 0 0 0
|- Markdown 3 98 0 94 4
|- Python 3 513 468 4 41
(Total) 611 468 98 45
-------------------------------------------------------------------------------
```
```console
$ cargo run --all-features --bin ruff -- check --no-cache --isolated --select=ALL /path/to/segment-anything/**/*.ipynb --fix
...
Found 180 errors (89 fixed, 91 remaining).
```
### https://github.com/openai/openai-cookbook
```
-------------------------------------------------------------------------------
Jupyter Notebooks 65 0 0 0 0
|- Markdown 64 3475 12 2507 956
|- Python 65 9700 7362 1101 1237
(Total) 13175 7374 3608 2193
===============================================================================
```
```console
$ cargo run --all-features --bin ruff -- check --no-cache --isolated --select=ALL /path/to/openai-cookbook/**/*.ipynb --fix
error: Failed to parse /path/to/openai-cookbook/examples/vector_databases/Using_vector_databases_for_embeddings_search.ipynb:cell 4:29:18: unexpected token '-'
...
Found 4227 errors (2165 fixed, 2062 remaining).
```
### https://github.com/tensorflow/docs
```
-------------------------------------------------------------------------------
Jupyter Notebooks 150 0 0 0 0
|- Markdown 1 55 0 46 9
|- Python 1 402 289 60 53
(Total) 457 289 106 62
-------------------------------------------------------------------------------
```
```console
$ cargo run --all-features --bin ruff -- check --no-cache --isolated --select=ALL /path/to/tensorflow-docs/**/*.ipynb --fix
error: Failed to parse /path/to/tensorflow-docs/site/en/guide/extension_type.ipynb:cell 80:1:1: unexpected token Indent
error: Failed to parse /path/to/tensorflow-docs/site/en/r1/tutorials/eager/custom_layers.ipynb:cell 20:1:1: unexpected token Indent
error: Failed to parse /path/to/tensorflow-docs/site/en/guide/data.ipynb:cell 175:5:14: unindent does not match any outer indentation level
error: Failed to parse /path/to/tensorflow-docs/site/en/r1/tutorials/representation/unicode.ipynb:cell 30:1:1: unexpected token Indent
...
Found 12726 errors (5140 fixed, 7586 remaining).
```
### https://github.com/tensorflow/models
```
-------------------------------------------------------------------------------
Jupyter Notebooks 46 0 0 0 0
|- Markdown 1 11 0 6 5
|- Python 1 328 249 19 60
(Total) 339 249 25 65
-------------------------------------------------------------------------------
```
```console
$ cargo run --all-features --bin ruff -- check --no-cache --isolated --select=ALL /path/to/tensorflow-models/**/*.ipynb --fix
...
Found 4856 errors (2690 fixed, 2166 remaining).
```
resolves: #1218fixes: #4556
This implements formatting ExprTuple, including magic trailing comma. I
intentionally didn't change the settings mechanism but just added a
dummy global const flag.
Besides the snapshots, I added custom breaking/joining tests and a
deeply nested test case. The diffs look better than previously, proper
black compatibility depends on parentheses handling.
---------
Co-authored-by: Micha Reiser <micha@reiser.io>
## Summary
This implements PYI044. This rule checks if `from __future__ import
annotations` is used in stub files as it has no effect in stub files, since type
checkers automatically treat stubs as having those semantics.
Updates https://github.com/astral-sh/ruff/issues/848
## Test Plan
Added a test case and snapshots.
