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## Summary
<!-- What's the purpose of the change? What does it do, and why? -->
Skip attribute check in try catch block (`AIR301`)
## Test Plan
<!-- How was it tested? -->
update
`crates/ruff_linter/resources/test/fixtures/airflow/AIR301_names_try.py`
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## Summary
<!-- What's the purpose of the change? What does it do, and why? -->
Remove `airflow.utils.dag_parsing_context.get_parsing_context` from
AIR301 as it has been moved to AIR311
## Test Plan
<!-- How was it tested? -->
the test fixture was updated in the previous PR
## Summary
When entering an `infer_expression_types` cycle from
`TypeInferenceBuilder::infer_standalone_expression`, we might get back a
`TypeInference::cycle_fallback(…)` that doesn't actually contain any new
types, but instead it contains a `cycle_fallback_type` which is set to
`Some(Type::Never)`. When calling `self.extend(…)`, we therefore don't
really pull in a type for the expression we're interested in. This
caused us to panic if we tried to call `self.expression_type(…)` after
`self.extend(…)`.
The proposed fix here is to retrieve that type from the nested
`TypeInferenceBuilder` directly, which will correctly fall back to
`cycle_fallback_type`.
## Details
I minimized the second example from #17792 a bit further and used this
example for debugging:
```py
from __future__ import annotations
class C: ...
def f(arg: C):
pass
x, _ = f(1)
assert x
```
This is self-referential because when we check the assignment statement
`x, _ = f(1)`, we need to look up the signature of `f`. Since evaluation
of annotations is deferred, we look up the public type of `C` for the
`arg` parameter. The public use of `C` is visibility-constraint by "`x`"
via the `assert` statement. While evaluating this constraint, we need to
look up the type of `x`, which in turn leads us back to the `x, _ =
f(1)` definition.
The reason why this only showed up in the relatively peculiar case with
unpack assignments is the code here:
78b4c3ccf1/crates/ty_python_semantic/src/types/infer.rs (L2709-L2718)
For a non-unpack assignment like `x = f(1)`, we would not try to infer
the right-hand side eagerly. Instead, we would enter a
`infer_definition_types` cycle that handles the situation correctly. For
unpack assignments, however, we try to infer the type of `value`
(`f(1)`) and therefore enter the cycle via `standalone_expression_type
=> infer_expression_type`.
closes#17792
## Test Plan
* New regression test
* Made sure that we can now run successfully on scipy => see #17850
This PR updates the semantic model for Python 3.14 by essentially
equating "run using Python 3.14" with "uses `from __future__ import
annotations`".
While this is not technically correct under the hood, it appears to be
correct for the purposes of our semantic model. That is: from the point
of view of deciding when to parse, bind, etc. annotations, these two
contexts behave the same. More generally these contexts behave the same
unless you are performing some kind of introspection like the following:
Without future import:
```pycon
>>> from annotationlib import get_annotations,Format
>>> def foo()->Bar:...
...
>>> get_annotations(foo,format=Format.FORWARDREF)
{'return': ForwardRef('Bar')}
>>> get_annotations(foo,format=Format.STRING)
{'return': 'Bar'}
>>> get_annotations(foo,format=Format.VALUE)
Traceback (most recent call last):
[...]
NameError: name 'Bar' is not defined
>>> get_annotations(foo)
Traceback (most recent call last):
[...]
NameError: name 'Bar' is not defined
```
With future import:
```
>>> from __future__ import annotations
>>> from annotationlib import get_annotations,Format
>>> def foo()->Bar:...
...
>>> get_annotations(foo,format=Format.FORWARDREF)
{'return': 'Bar'}
>>> get_annotations(foo,format=Format.STRING)
{'return': 'Bar'}
>>> get_annotations(foo,format=Format.VALUE)
{'return': 'Bar'}
>>> get_annotations(foo)
{'return': 'Bar'}
```
(Note: the result of the last call to `get_annotations` in these
examples relies on the fact that, as of this writing, the default value
for `format` is `Format.VALUE`).
If one day we support lint rules targeting code that introspects using
the new `annotationlib`, then it is possible we will need to revisit our
approximation.
Closes#15100
## Summary
Currently red-knot does not understand `Foo` and `Bar` here as being
equivalent:
```py
from typing import Protocol
class A: ...
class B: ...
class C: ...
class Foo(Protocol):
x: A | B | C
class Bar(Protocol):
x: B | A | C
```
Nor does it understand `A | B | Foo` as being equivalent to `Bar | B |
A`. This PR fixes that.
## Test Plan
new mdtest assertions added that fail on `main`
## Summary
Currently this assertion fails on `main`, because we do not synthesize a
`__call__` attribute for Callable types:
```py
from typing import Protocol, Callable
from knot_extensions import static_assert, is_assignable_to
class Foo(Protocol):
def __call__(self, x: int, /) -> str: ...
static_assert(is_assignable_to(Callable[[int], str], Foo))
```
This PR fixes that.
See previous discussion about this in
https://github.com/astral-sh/ruff/pull/16493#discussion_r1985098508 and
https://github.com/astral-sh/ruff/pull/17682#issuecomment-2839527750
## Test Plan
Existing mdtests updated; a couple of new ones added.
This adds support for legacy generic classes, which use a
`typing.Generic` base class, or which inherit from another generic class
that has been specialized with legacy typevars.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
Quick follow-on to #17788. If there is no bound `self` parameter, we can
reuse the existing `CallArgument{,Type}s`, and we can use a straight
`Vec` instead of a `VecDeque`.
## Summary
Remove mutability in parameter types for a few functions such as
`with_self` and `try_call`. I tried the `Rc`-approach with cheap cloning
[suggest
here](https://github.com/astral-sh/ruff/pull/17733#discussion_r2068722860)
first, but it turns out we need a whole stack of prepended arguments
(there can be [both `self` *and*
`cls`](3cf44e401a/crates/red_knot_python_semantic/resources/mdtest/call/constructor.md (L113))),
and we would need the same construct not just for `CallArguments` but
also for `CallArgumentTypes`. At that point we're cloning `VecDeque`s
anyway, so the overhead of cloning the whole `VecDeque` with all
arguments didn't seem to justify the additional code complexity.
## Benchmarks
Benchmarks on tomllib, black, jinja, isort seem neutral.
## Summary
Add the ability to detect instance attribute assignments in class
methods that are generic.
This does not address the code duplication mentioned in #16928. I can
open a ticket for this after this has been merged.
closes#16928
## Test Plan
Added regression test.
This PR does the wiring necessary to respond to completion requests from
LSP clients.
As far as the actual completion results go, they are nearly about the
dumbest and simplest thing we can do: we simply return a de-duplicated
list of all identifiers from the current module.
Summary
--
Fixes#16598 by adding the `--python` flag to `ruff analyze graph`,
which adds a `PythonPath` to the `SearchPathSettings` for module
resolution. For the [albatross-virtual-workspace] example from the uv
repo, this updates the output from the initial issue:
```shell
> ruff analyze graph packages/albatross
{
"packages/albatross/check_installed_albatross.py": [
"packages/albatross/src/albatross/__init__.py"
],
"packages/albatross/src/albatross/__init__.py": []
}
```
To include both the the workspace `bird_feeder` import _and_ the
third-party `tqdm` import in the output:
```shell
> myruff analyze graph packages/albatross --python .venv
{
"packages/albatross/check_installed_albatross.py": [
"packages/albatross/src/albatross/__init__.py"
],
"packages/albatross/src/albatross/__init__.py": [
".venv/lib/python3.12/site-packages/tqdm/__init__.py",
"packages/bird-feeder/src/bird_feeder/__init__.py"
]
}
```
Note the hash in the uv link! I was temporarily very confused why my
local tests were showing an `iniconfig` import instead of `tqdm` until I
realized that the example has been updated on the uv main branch, which
I had locally.
Test Plan
--
A new integration test with a stripped down venv based on the
`albatross` example.
[albatross-virtual-workspace]:
aa629c4a54/scripts/workspaces/albatross-virtual-workspace
## Summary
Contains the same changes to the semantic type inference as
https://github.com/astral-sh/ruff/pull/17705.
Fixes#17694
<!-- What's the purpose of the change? What does it do, and why? -->
## Test Plan
<!-- How was it tested? -->
Snapshot tests.
---------
Co-authored-by: Dhruv Manilawala <dhruvmanila@gmail.com>
Co-authored-by: Brent Westbrook <brentrwestbrook@gmail.com>
## Summary
Adds preliminary support for `NamedTuple`s, including:
* No false positives when constructing a `NamedTuple` object
* Correct signature for the synthesized `__new__` method, i.e. proper
checking of constructor calls
* A patched MRO (`NamedTuple` => `tuple`), mainly to make type inference
of named attributes possible, but also to better reflect the runtime
MRO.
All of this works:
```py
from typing import NamedTuple
class Person(NamedTuple):
id: int
name: str
age: int | None = None
alice = Person(1, "Alice", 42)
alice = Person(id=1, name="Alice", age=42)
reveal_type(alice.id) # revealed: int
reveal_type(alice.name) # revealed: str
reveal_type(alice.age) # revealed: int | None
# error: [missing-argument]
Person(3)
# error: [too-many-positional-arguments]
Person(3, "Eve", 99, "extra")
# error: [invalid-argument-type]
Person(id="3", name="Eve")
```
Not included:
* type inference for index-based access.
* support for the functional `MyTuple = NamedTuple("MyTuple", […])`
syntax
## Test Plan
New Markdown tests
## Ecosystem analysis
```
Diagnostic Analysis Report
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━┳━━━━━━━━━━━━┓
┃ Diagnostic ID ┃ Severity ┃ Removed ┃ Added ┃ Net Change ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━╇━━━━━━━━━━━━┩
│ lint:call-non-callable │ error │ 0 │ 3 │ +3 │
│ lint:call-possibly-unbound-method │ warning │ 0 │ 4 │ +4 │
│ lint:invalid-argument-type │ error │ 0 │ 72 │ +72 │
│ lint:invalid-context-manager │ error │ 0 │ 2 │ +2 │
│ lint:invalid-return-type │ error │ 0 │ 2 │ +2 │
│ lint:missing-argument │ error │ 0 │ 46 │ +46 │
│ lint:no-matching-overload │ error │ 19121 │ 0 │ -19121 │
│ lint:not-iterable │ error │ 0 │ 6 │ +6 │
│ lint:possibly-unbound-attribute │ warning │ 13 │ 32 │ +19 │
│ lint:redundant-cast │ warning │ 0 │ 1 │ +1 │
│ lint:unresolved-attribute │ error │ 0 │ 10 │ +10 │
│ lint:unsupported-operator │ error │ 3 │ 9 │ +6 │
│ lint:unused-ignore-comment │ warning │ 15 │ 4 │ -11 │
├───────────────────────────────────┼──────────┼─────────┼───────┼────────────┤
│ TOTAL │ │ 19152 │ 191 │ -18961 │
└───────────────────────────────────┴──────────┴─────────┴───────┴────────────┘
Analysis complete. Found 13 unique diagnostic IDs.
Total diagnostics removed: 19152
Total diagnostics added: 191
Net change: -18961
```
I uploaded the ecosystem full diff (ignoring the 19k
`no-matching-overload` diagnostics)
[here](https://shark.fish/diff-namedtuple.html).
* There are some new `missing-argument` false positives which come from
the fact that named tuples are often created using unpacking as in
`MyNamedTuple(*fields)`, which we do not understand yet.
* There are some new `unresolved-attribute` false positives, because
methods like `_replace` are not available.
* Lots of the `invalid-argument-type` diagnostics look like true
positives
---------
Co-authored-by: Douglas Creager <dcreager@dcreager.net>
## Summary
This PR updates the existing overload matching methods to return an
iterator of all the matched overloads instead.
This would be useful once the overload call evaluation algorithm is
implemented which should provide an accurate picture of all the matched
overloads. The return type would then be picked from either the only
matched overload or the first overload from the ones that are matched.
In an earlier version of this PR, it tried to check if using an
intersection of return types from the matched overload would help reduce
the false positives but that's not enough. [This
comment](https://github.com/astral-sh/ruff/pull/17618#issuecomment-2842891696)
keep the ecosystem analysis for that change for prosperity.
> [!NOTE]
>
> The best way to review this PR is by hiding the whitespace changes
because there are two instances where a large match expression is
indented to be inside a loop over matching overlods
>
> <img width="1207" alt="Screenshot 2025-04-28 at 15 12 16"
src="https://github.com/user-attachments/assets/e06cbfa4-04fa-435f-84ef-4e5c3c5626d1"
/>
## Test Plan
Make sure existing test cases are unaffected and no ecosystem changes.
## Summary
<!-- What's the purpose of the change? What does it do, and why? -->
This is not yet fixing anything as the names are not changed, but it
lays down the foundation for fixing.
## Test Plan
<!-- How was it tested? -->
the existing test fixture should already cover this change
## Summary
Part of #17412
Starred expressions cannot be used as values in assignment expressions.
Add a new semantic syntax error to catch such instances.
Note that we already have
`ParseErrorType::InvalidStarredExpressionUsage` to catch some starred
expression errors during parsing, but that does not cover top level
assignment expressions.
## Test Plan
- Added new inline tests for the new rule
- Found some examples marked as "valid" in existing tests (`_ = *data`),
which are not really valid (per this new rule) and updated them
- There was an existing inline test - `assign_stmt_invalid_value_expr`
which had instances of `*` expression which would be deemed invalid by
this new rule. Converted these to tuples, so that they do not trigger
this new rule.
## Summary
Model the lookup of `__new__` without going through
`Type::try_call_dunder`. The `__new__` method is only looked up on the
constructed type itself, not on the meta-type.
This now removes ~930 false positives across the ecosystem (vs 255 for
https://github.com/astral-sh/ruff/pull/17662). It introduces 30 new
false positives related to the construction of enums via something like
`Color = enum.Enum("Color", ["RED", "GREEN"])`. This is expected,
because we don't handle custom metaclass `__call__` methods. The fact
that we previously didn't emit diagnostics there was a coincidence (we
incorrectly called `EnumMeta.__new__`, and since we don't fully
understand its signature, that happened to work with `str`, `list`
arguments).
closes#17462
## Test Plan
Regression test
## Summary
Part of #15383.
As per the spec
(https://typing.python.org/en/latest/spec/overload.html#invalid-overload-definitions):
For `@staticmethod` and `@classmethod`:
> If one overload signature is decorated with `@staticmethod` or
`@classmethod`, all overload signatures must be similarly decorated. The
implementation, if present, must also have a consistent decorator. Type
checkers should report an error if these conditions are not met.
For `@final` and `@override`:
> If a `@final` or `@override` decorator is supplied for a function with
overloads, the decorator should be applied only to the overload
implementation if it is present. If an overload implementation isn’t
present (for example, in a stub file), the `@final` or `@override`
decorator should be applied only to the first overload. Type checkers
should enforce these rules and generate an error when they are violated.
If a `@final` or `@override` decorator follows these rules, a type
checker should treat the decorator as if it is present on all overloads.
## Test Plan
Update existing tests; add snapshots.
