## Summary
closes#16615
This PR includes:
- Introduces a new type: `Type::BoundSuper`
- Implements member lookup for `Type::BoundSuper`, resolving attributes
by traversing the MRO starting from the specified class
- Adds support for inferring appropriate arguments (`pivot_class` and
`owner`) for `super()` when it is used without arguments
When `super(..)` appears in code, it can be inferred into one of the
following:
- `Type::Unknown`: when a runtime error would occur (e.g. calling
`super()` out of method scope, or when parameter validation inside
`super` fails)
- `KnownClass::Super::to_instance()`: when the result is an *unbound
super object* or when a dynamic type is used as parameters (MRO
traversing is meaningless)
- `Type::BoundSuper`: the common case, representing a properly
constructed `super` instance that is ready for MRO traversal and
attribute resolution
### Terminology
Python defines the terms *bound super object* and *unbound super
object*.
An **unbound super object** is created when `super` is called with only
one argument (e.g.
`super(A)`). This object may later be bound via the `super.__get__`
method. However, this form is rarely used in practice.
A **bound super object** is created either by calling
`super(pivot_class, owner)` or by using the implicit form `super()`,
where both arguments are inferred from the context. This is the most
common usage.
### Follow-ups
- Add diagnostics for `super()` calls that would result in runtime
errors (marked as TODO)
- Add property tests for `Type::BoundSuper`
## Test Plan
- Added `mdtest/class/super.md`
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
As discussed in https://github.com/astral-sh/ruff/issues/16983 and
"mitigate" said issue for the alpha.
This PR changes the default for `PythonPlatform` to be the current
platform rather than `all`.
I'm not sure if we should be as sophisticated as supporting `ios` and
`android` as defaults but it was easy...
## Test Plan
Updated Markdown tests.
---------
Co-authored-by: David Peter <mail@david-peter.de>
## Summary
We already have partial "support" for `assert_never`, because it is
annotated as
```pyi
def assert_never(arg: Never, /) -> Never: ...
```
in typeshed. So we already emit a `invalid-argument-type` diagnostic if
the argument type to `assert_never` is not assignable to `Never`.
That is not enough, however. Gradual types like `Any`, `Unknown`,
`@Todo(…)` or `Any & int` can be assignable to `Never`. Which means that
we didn't issue any diagnostic in those cases.
Also, it seems like `assert_never` deserves a dedicated diagnostic
message, not just a generic "invalid argument type" error.
## Test Plan
New Markdown tests.
## Summary
Following up from earlier discussion on Discord, this PR adds logic to
flag casts as redundant when the inferred type of the expression is the
same as the target type. It should follow the semantics from
[mypy](https://github.com/python/mypy/pull/1705).
Example:
```python
def f() -> int:
return 10
# error: [redundant-cast] "Value is already of type `int`"
cast(int, f())
```
This breaks up call binding into two phases:
- **_Matching parameters_** just looks at the names and kinds
(positional/keyword) of each formal and actual parameters, and matches
them up. Most of the current call binding errors happen during this
phase.
- Once we have matched up formal and actual parameters, we can **_infer
types_** of each actual parameter, and **_check_** that each one is
assignable to the corresponding formal parameter type.
As part of this, we add information to each formal parameter about
whether it is a type form or not. Once [PEP
747](https://peps.python.org/pep-0747/) is finalized, we can hook that
up to this internal type form representation. This replaces the
`ParameterExpectations` type, which did the same thing in a more ad hoc
way.
While we're here, we add a new fluent API for building `Parameter`s,
which makes our signature constructors a bit nicer to read. We also
eliminate a TODO where we were consuming types from the argument list
instead of the bound parameter list when evaluating our special-case
known functions.
Closes#15460
---------
Co-authored-by: Micha Reiser <micha@reiser.io>
## Summary
This PR closes#16248.
If the return type of the function isn't assignable to the one
specified, an `invalid-return-type` error occurs.
I thought it would be better to report this as a different kind of error
than the `invalid-assignment` error, so I defined this as a new error.
## Test Plan
All type inconsistencies in the test cases have been replaced with
appropriate ones.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
This updates the `Signature` and `CallBinding` machinery to support
multiple overloads for a callable. This is currently only used for
`KnownFunction`s that we special-case in our type inference code. It
does **_not_** yet update the semantic index builder to handle
`@overload` decorators and construct a multi-signature `Overloads`
instance for real Python functions.
While I was here, I updated many of the `try_call` special cases to use
signatures (possibly overloaded ones now) and `bind_call` to check
parameter lists. We still need some of the mutator methods on
`OverloadBinding` for the special cases where we need to update return
types based on some Rust code.
## Summary
This PR adds more features to #16468.
* Adds a new error rule `invalid-type-checking-constant`, which occurs
when we try to assign a value other than `False` to a user-defined
`TYPE_CHECKING` variable (it is possible to assign `...` in a stub
file).
* Allows annotated assignment to `TYPE_CHECKING`. Only types that
`False` can be assigned to are allowed. However, the type of
`TYPE_CHECKING` will be inferred to be `Literal[True]` regardless of
what the type is specified.
## Test plan
I ran the tests with `cargo test -p red_knot_python_semantic` and
confirmed that all tests passed.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
This PR generalize the idea that we may want to emit diagnostics for
invalid or incompatible configuration values similar to how we already
do it for `rules`.
This PR introduces a new `Settings` struct that is similar to `Options`
but, unlike
`Options`, are fields have their default values filled in and they use a
representation optimized for reads.
The diagnostics created during loading the `Settings` are stored on the
`Project` so that we can emit them when calling `check`.
The motivation for this work is that it simplifies adding new settings.
That's also why I went ahead and added the `terminal.error-on-warning`
setting to demonstrate how new settings are added.
## Test Plan
Existing tests, new CLI test.
## Summary
Adds a JSON schema generation step for Red Knot. This PR doesn't yet add
a publishing step because it's still a bit early for that
## Test plan
I tested the schema in Zed, VS Code and PyCharm:
* PyCharm: You have to manually add a schema mapping (settings JSON
Schema Mappings)
* Zed and VS code support the inline schema specification
```toml
#:schema /Users/micha/astral/ruff/knot.schema.json
[environment]
extra-paths = []
[rules]
call-possibly-unbound-method = "error"
unknown-rule = "error"
# duplicate-base = "error"
```
```json
{
"$schema": "file:///Users/micha/astral/ruff/knot.schema.json",
"environment": {
"python-version": "3.13",
"python-platform": "linux2"
},
"rules": {
"unknown-rule": "error"
}
}
```
https://github.com/user-attachments/assets/a18fcd96-7cbe-4110-985b-9f1935584411
The Schema overall works but all editors have their own quirks:
* PyCharm: Hovering a name always shows the section description instead
of the description of the specific setting. But it's the same for other
settings in `pyproject.toml` files 🤷
* VS Code (JSON): Using the generated schema in a JSON file gives
exactly the experience I want
* VS Code (TOML):
* Properties with multiple possible values are repeated during
auto-completion without giving any hint how they're different. 
* The property description mushes together the description of the
property and the value, which looks sort of ridiculous. 
* Autocompletion and documentation hovering works (except the
limitations mentioned above)
* Zed:
* Very similar to VS Code with the exception that it uses the
description attribute to distinguish settings with multiple possible
values 
I don't think there's much we can do here other than hope (or help)
editors improve their auto completion. The same short comings also apply
to ruff, so this isn't something new. For now, I think this is good
enough
