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>
## 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.
## Summary
This PR is a follow-up to #16852.
Instance variables bound in comprehensions are recorded, allowing type
inference to work correctly.
This required adding support for unpacking in comprehension which
resolves https://github.com/astral-sh/ruff/issues/15369.
## Test Plan
One TODO in `mdtest/attributes.md` is now resolved, and some new test
cases are added.
---------
Co-authored-by: Dhruv Manilawala <dhruvmanila@gmail.com>
## Summary
If two types are gradually-equivalent, that means they share the same
set of possible materializations. There's no need to keep two such types
in the same union or intersection; we should simplify them.
Fixes https://github.com/astral-sh/ruff/issues/17465
The one downside here is that now we will simplify e.g. `Unknown |
Todo(...)` to just `Unknown`, if `Unknown` was added to the union first.
This is correct from a type perspective (they are equivalent types), but
it can mean we lose visibility into part of the cause for the type
inferring as unknown. I think this is OK, but if we think it's important
to avoid this, I can add a special case to try to preserve `Todo` over
`Unknown`, if we see them both in the same union or intersection.
## Test Plan
Added and updated mdtests.
## Summary
Member lookup can be cyclic, with type inference of implicit members. A
sample case is shown in the added mdtest.
There's no clear way to handle such cases other than to fixpoint-iterate
the cycle.
Fixes#17457.
## Test Plan
Added test.
You can now use subscript expressions in a type expression to explicitly
specialize generic classes, just like you could already do in value
expressions.
This still does not implement bidirectional checking, so a type
annotation on an assignment does not influence how we infer a
specialization for a (not explicitly specialized) constructor call. You
might get an `invalid-assignment` error if (a) we cannot infer a class
specialization from the constructor call (in which case you end up e.g.
trying to assign `C[Unknown]` to `C[int]`) or if (b) we can infer a
specialization, but it doesn't match the annotation.
Closes https://github.com/astral-sh/ruff/issues/17432
## Summary
Part of #15383, this PR adds support for overloaded callables.
Typing spec: https://typing.python.org/en/latest/spec/overload.html
Specifically, it does the following:
1. Update the `FunctionType::signature` method to return signatures from
a possibly overloaded callable using a new `FunctionSignature` enum
2. Update `CallableType` to accommodate overloaded callable by updating
the inner type to `Box<[Signature]>`
3. Update the relation methods on `CallableType` with logic specific to
overloads
4. Update the display of callable type to display a list of signatures
enclosed by parenthesis
5. Update `CallableTypeOf` special form to recognize overloaded callable
6. Update subtyping, assignability and fully static check to account for
callables (equivalence is planned to be done as a follow-up)
For (2), it is required to be done in this PR because otherwise I'd need
to add some workaround for `into_callable_type` and I though it would be
best to include it in here.
For (2), another possible design would be convert `CallableType` in an
enum with two variants `CallableType::Single` and
`CallableType::Overload` but I decided to go with `Box<[Signature]>` for
now to (a) mirror it to be equivalent to `overload` field on
`CallableSignature` and (b) to avoid any refactor in this PR. This could
be done in a follow-up to better split the two kind of callables.
### Design
There were two main candidates on how to represent the overloaded
definition:
1. To include it in the existing infrastructure which is what this PR is
doing by recognizing all the signatures within the
`FunctionType::signature` method
2. To create a new `Overload` type variant
<details><summary>For context, this is what I had in mind with the new
type variant:</summary>
<p>
```rs
pub enum Type {
FunctionLiteral(FunctionType),
Overload(OverloadType),
BoundMethod(BoundMethodType),
...
}
pub struct OverloadType {
// FunctionLiteral or BoundMethod
overloads: Box<[Type]>,
// FunctionLiteral or BoundMethod
implementation: Option<Type>
}
pub struct BoundMethodType {
kind: BoundMethodKind,
self_instance: Type,
}
pub enum BoundMethodKind {
Function(FunctionType),
Overload(OverloadType),
}
```
</p>
</details>
The main reasons to choose (1) are the simplicity in the implementation,
reusing the existing infrastructure, avoiding any complications that the
new type variant has specifically around the different variants between
function and methods which would require the overload type to use `Type`
instead.
### Implementation
The core logic is how to collect all the overloaded functions. The way
this is done in this PR is by recording a **use** on the `Identifier`
node that represents the function name in the use-def map. This is then
used to fetch the previous symbol using the same name. This way the
signatures are going to be propagated from top to bottom (from first
overload to the final overload or the implementation) with each function
/ method. For example:
```py
from typing import overload
@overload
def foo(x: int) -> int: ...
@overload
def foo(x: str) -> str: ...
def foo(x: int | str) -> int | str:
return x
```
Here, each definition of `foo` knows about all the signatures that comes
before itself. So, the first overload would only see itself, the second
would see the first and itself and so on until the implementation or the
final overload.
This approach required some updates specifically recognizing
`Identifier` node to record the function use because it doesn't use
`ExprName`.
## Test Plan
Update existing test cases which were limited by the overload support
and add test cases for the following cases:
* Valid overloads as functions, methods, generics, version specific
* Invalid overloads as stated in
https://typing.python.org/en/latest/spec/overload.html#invalid-overload-definitions
(implementation will be done in a follow-up)
* Various relation: fully static, subtyping, and assignability (others
in a follow-up)
## Ecosystem changes
_WIP_
After going through the ecosystem changes (there are a lot!), here's
what I've found:
We need assignability check between a callable type and a class literal
because a lot of builtins are defined as classes in typeshed whose
constructor method is overloaded e.g., `map`, `sorted`, `list.sort`,
`max`, `min` with the `key` parameter, `collections.abc.defaultdict`,
etc. (https://github.com/astral-sh/ruff/issues/17343). This makes up
most of the ecosystem diff **roughly 70 diagnostics**. For example:
```py
from collections import defaultdict
# red-knot: No overload of bound method `__init__` matches arguments [lint:no-matching-overload]
defaultdict(int)
# red-knot: No overload of bound method `__init__` matches arguments [lint:no-matching-overload]
defaultdict(list)
class Foo:
def __init__(self, x: int):
self.x = x
# red-knot: No overload of function `__new__` matches arguments [lint:no-matching-overload]
map(Foo, ["a", "b", "c"])
```
Duplicate diagnostics in unpacking
(https://github.com/astral-sh/ruff/issues/16514) has **~16
diagnostics**.
Support for the `callable` builtin which requires `TypeIs` support. This
is **5 diagnostics**. For example:
```py
from typing import Any
def _(x: Any | None) -> None:
if callable(x):
# red-knot: `Any | None`
# Pyright: `(...) -> object`
# mypy: `Any`
# pyrefly: `(...) -> object`
reveal_type(x)
```
Narrowing on `assert` which has **11 diagnostics**. This is being worked
on in https://github.com/astral-sh/ruff/pull/17345. For example:
```py
import re
match = re.search("", "")
assert match
match.group() # error: [possibly-unbound-attribute]
```
Others:
* `Self`: 2
* Type aliases: 6
* Generics: 3
* Protocols: 13
* Unpacking in comprehension: 1
(https://github.com/astral-sh/ruff/pull/17396)
## Performance
Refer to
https://github.com/astral-sh/ruff/pull/17366#issuecomment-2814053046.
## 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
* Partial #17238
* Flyby from discord discussion - `todo_type!` now statically checks for
no parens in the message to avoid issues between debug & release build
tests
## Test Plan
many mdtests are changing
## Summary
There is a new official URL for the typing documentation:
https://typing.python.org/
Change all https://typing.readthedocs.io/ links to use the new sub
domain, which is slightly shorter and looks more official.
## Test Plan
Tested to see if each and every new URL is accessible. I noticed that
some links go to https://typing.python.org/en/latest/source/stubs.html
which seems to be outdated, but that is a separate issue. The same page
shows up for the old URL.
## Summary
Add support for decorators on function as well as support
for properties by adding special handling for `@property` and `@<name of
property>.setter`/`.getter` decorators.
closes https://github.com/astral-sh/ruff/issues/16987
## Ecosystem results
- ✔️ A lot of false positives are fixed by our new
understanding of properties
- 🔴 A bunch of new false positives (typically
`possibly-unbound-attribute` or `invalid-argument-type`) occur because
we currently do not perform type narrowing on attributes. And with the
new understanding of properties, this becomes even more relevant. In
many cases, the narrowing occurs through an assertion, so this is also
something that we need to implement to get rid of these false positives.
- 🔴 A few new false positives occur because we do not
understand generics, and therefore some calls to custom setters fail.
- 🔴 Similarly, some false positives occur because we do not
understand protocols yet.
- ✔️ Seems like a true positive to me. [The
setter](e624d8edfa/src/packaging/specifiers.py (L752-L754))
only accepts `bools`, but `None` is assigned in [this
line](e624d8edfa/tests/test_specifiers.py (L688)).
```
+ error[lint:invalid-assignment]
/tmp/mypy_primer/projects/packaging/tests/test_specifiers.py:688:9:
Invalid assignment to data descriptor attribute `prereleases` on type
`SpecifierSet` with custom `__set__` method
```
- ✔️ This is arguable also a true positive. The setter
[here](0c6c75644f/rich/table.py (L359-L363))
returns `Table`, but typeshed wants [setters to return
`None`](bf8d2a9912/stdlib/builtins.pyi (L1298)).
```
+ error[lint:invalid-argument-type]
/tmp/mypy_primer/projects/rich/rich/table.py:359:5: Object of type
`Literal[padding]` cannot be assigned to parameter 2 (`fset`) of bound
method `setter`; expected type `(Any, Any, /) -> None`
```
## Follow ups
- Fix the `@no_type_check` regression
- Implement class decorators
## Test Plan
New Markdown test suites for decorators and properties.
## Summary
This PR adds some branches so that we infer `Todo` types for attribute
access on instances of `super()` and subtypes of `type[Enum]`. It reduces
false positives in the short term until we implement full support for
these features.
## Test Plan
New mdtests added + mypy_primer report
## Summary
This PR adds initial support for `*` imports to red-knot. The approach
is to implement a standalone query, called from semantic indexing, that
visits the module referenced by the `*` import and collects all
global-scope public names that will be imported by the `*` import. The
`SemanticIndexBuilder` then adds separate definitions for each of these
names, all keyed to the same `ast::Alias` node that represents the `*`
import.
There are many pieces of `*`-import semantics that are still yet to be
done, even with this PR:
- This PR does not attempt to implement any of the semantics to do with
`__all__`. (If a module defines `__all__`, then only the symbols
included in `__all__` are imported, _not_ all public global-scope
symbols.
- With the logic implemented in this PR as it currently stands, we
sometimes incorrectly consider a symbol bound even though it is defined
in a branch that is statically known to be dead code, e.g. (assuming the
target Python version is set to 3.11):
```py
# a.py
import sys
if sys.version_info < (3, 10):
class Foo: ...
```
```py
# b.py
from a import *
print(Foo) # this is unbound at runtime on 3.11,
# but we currently consider it bound with the logic in this PR
```
Implementing these features is important, but is for now deferred to
followup PRs.
Many thanks to @ntBre, who contributed to this PR in a pairing session
on Friday!
## Test Plan
Assertions in existing mdtests are adjusted, and several new ones are
added.
## Summary
Here I fix the last English spelling errors I could find in the repo.
Again, I am trying not to touch variable/function names, or anything
that might be misspelled in the API. The goal is to make this PR safe
and easy to merge.
## Test Plan
I have run all the unit tests. Though, again, all of the changes I make
here are to docs and docstrings. I make no code changes, which I believe
should greatly mitigate the testing concerns.
## Summary
This changeset adds proper support for assignments to attributes:
```py
obj.attr = value
```
In particular, the following new features are now available:
* We previously didn't raise any errors if you tried to assign to a
non-existing attribute `attr`. This is now fixed.
* If `type(obj).attr` is a data descriptor, we now call its `__set__`
method instead of trying to assign to the load-context type of
`obj.attr`, which can be different for data descriptors.
* An initial attempt was made to support unions and intersections, as
well as possibly-unbound situations. There are some remaining TODOs in
tests, but they only affect edge cases. Having nested diagnostics would
be one way that could help solve the remaining cases, I believe.
## Follow ups
The following things are planned as follow-ups:
- Write a test suite with snapshot diagnostics for various attribute
assignment errors
- Improve the diagnostics. An easy improvement would be to highlight the
right hand side of the assignment as a secondary span (with the rhs type
as additional information). Some other ideas are mentioned in TODO
comments in this PR.
- Improve the union/intersection/possible-unboundness handling
- Add support for calling custom `__setattr__` methods (see new false
positive in the ecosystem results)
## Ecosystem changes
Some changes are related to assignments on attributes with a custom
`__setattr__` method (see above). Since we didn't notice missing
attributes at all in store context previously, these are new.
The other changes are related to properties. We previously used their
read-context type to test the assignment. That results in weird error
messages, as we often see assignments to `self.property` and then we
think that those are instance attributes *and* descriptors, leading to
union types. Now we properly look them up on the meta type, see the
decorated function, and try to overwrite it with the new value (as we
don't understand decorators yet). Long story short: the errors are still
weird, we need to understand decorators to make them go away.
## Test Plan
New Markdown tests
## Summary
Add support for calling custom `__getattr__` methods in case an
attribute is not otherwise found. This allows us to get rid of many
ecosystem false positives where we previously emitted errors when
accessing attributes on `argparse.Namespace`.
closes#16614
## Test Plan
* New Markdown tests
* Observed expected ecosystem changes (the changes for `arrow` also look
fine, since the `Arrow` class has a custom [`__getattr__`
here](1d70d00919/arrow/arrow.py (L802-L815)))
## Summary
Implements attribute access on intersection types, which didn't
previously work. For example:
```py
from typing import Any
class P: ...
class Q: ...
class A:
x: P = P()
class B:
x: Any = Q()
def _(obj: A):
if isinstance(obj, B):
reveal_type(obj.x) # revealed: P & Any
```
Refers to [this comment].
[this comment]:
https://github.com/astral-sh/ruff/pull/16416#discussion_r1985040363
## Test Plan
New Markdown tests
## Summary
This is a pure restructuring of the `attributes.md` and
`descriptor_protocol.md` test suites. They have grown organically and I
didn't want to make major structural changes in my recent PR to keep the
diff clean.
## 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>
## Summary
Fixes a small nit of mine -- we are currently inconsistent in our
spelling between "metaclass" and "meta class", and between "meta type"
and "meta-type". This PR means that we consistently use "metaclass" and
"meta-type".
## Test Plan
`uvx pre-commit run -a`
## Summary
Resolves#16365
Add support for unpacking `with` statement targets.
## Test Plan
Added some test cases, alike the ones added by #15058.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
* Attributes/method are now properly looked up on metaclasses, when
called on class objects
* We properly distinguish between data descriptors and non-data
descriptors (but we do not yet support them in store-context, i.e.
`obj.data_descr = …`)
* The descriptor protocol is now implemented in a single unified place
for instances, classes and dunder-calls. Unions and possibly-unbound
symbols are supported in all possible stages of the process by creating
union types as results.
* In general, the handling of "possibly-unbound" symbols has been
improved in a lot of places: meta-class attributes, attributes,
descriptors with possibly-unbound `__get__` methods, instance
attributes, …
* We keep track of type qualifiers in a lot more places. I anticipate
that this will be useful if we import e.g. `Final` symbols from other
modules (see relevant change to typing spec:
https://github.com/python/typing/pull/1937).
* Detection and special-casing of the `typing.Protocol` special form in
order to avoid lots of changes in the test suite due to new `@Todo`
types when looking up attributes on builtin types which have `Protocol`
in their MRO. We previously
looked up attributes in a wrong way, which is why this didn't come up
before.
closes#16367closes#15966
## Context
The way attribute lookup in `Type::member` worked before was simply
wrong (mostly my own fault). The whole instance-attribute lookup should
probably never have been integrated into `Type::member`. And the
`Type::static_member` function that I introduced in my last descriptor
PR was the wrong abstraction. It's kind of fascinating how far this
approach took us, but I am pretty confident that the new approach
proposed here is what we need to model this correctly.
There are three key pieces that are required to implement attribute
lookups:
- **`Type::class_member`**/**`Type::find_in_mro`**: The
`Type::find_in_mro` method that can look up attributes on class bodies
(and corresponding bases). This is a partial function on types, as it
can not be called on instance types like`Type::Instance(…)` or
`Type::IntLiteral(…)`. For this reason, we usually call it through
`Type::class_member`, which is essentially just
`type.to_meta_type().find_in_mro(…)` plus union/intersection handling.
- **`Type::instance_member`**: This new function is basically the
type-level equivalent to `obj.__dict__[name]` when called on
`Type::Instance(…)`. We use this to discover instance attributes such as
those that we see as declarations on class bodies or as (annotated)
assignments to `self.attr` in methods of a class.
- The implementation of the descriptor protocol. It works slightly
different for instances and for class objects, but it can be described
by the general framework:
- Call `type.class_member("attribute")` to look up "attribute" in the
MRO of the meta type of `type`. Call the resulting `Symbol` `meta_attr`
(even if it's unbound).
- Use `meta_attr.class_member("__get__")` to look up `__get__` on the
*meta type* of `meta_attr`. Call it with `__get__(meta_attr, self,
self.to_meta_type())`. If this fails (either the lookup or the call),
just proceed with `meta_attr`. Otherwise, replace `meta_attr` in the
following with the return type of `__get__`. In this step, we also probe
if a `__set__` or `__delete__` method exists and store it in
`meta_attr_kind` (can be either "data descriptor" or "normal attribute
or non-data descriptor").
- Compute a `fallback` type.
- For instances, we use `self.instance_member("attribute")`
- For class objects, we use `class_attr =
self.find_in_mro("attribute")`, and then try to invoke the descriptor
protocol on `class_attr`, i.e. we look up `__get__` on the meta type of
`class_attr` and call it with `__get__(class_attr, None, self)`. This
additional invocation of the descriptor protocol on the fallback type is
one major asymmetry in the otherwise universal descriptor protocol
implementation.
- Finally, we look at `meta_attr`, `meta_attr_kind` and `fallback`, and
handle various cases of (possible) unboundness of these symbols.
- If `meta_attr` is bound and a data descriptor, just return `meta_attr`
- If `meta_attr` is not a data descriptor, and `fallback` is bound, just
return `fallback`
- If `meta_attr` is not a data descriptor, and `fallback` is unbound,
return `meta_attr`
- Return unions of these three possibilities for partially-bound
symbols.
This allows us to handle class objects and instances within the same
framework. There is a minor additional detail where for instances, we do
not allow the fallback type (the instance attribute) to completely
shadow the non-data descriptor. We do this because we (currently) don't
want to pretend that we can statically infer that an instance attribute
is always set.
Dunder method calls can also be embedded into this framework. The only
thing that changes is that *there is no fallback type*. If a dunder
method is called on an instance, we do not fall back to instance
variables. If a dunder method is called on a class object, we only look
it up on the meta class, never on the class itself.
## Test Plan
New Markdown tests.
## Summary
- `Never` is callable
- `Never` is iterable
- Arbitrary attributes can be accessed on `Never`
Split out from #16416 that is going to be required.
## Test Plan
Tests for all properties above.
## Summary
Add a diagnostic if a pure instance variable is accessed on a class object. For example
```py
class C:
instance_only: str
def __init__(self):
self.instance_only = "a"
# error: Attribute `instance_only` can only be accessed on instances, not on the class object `Literal[C]` itself.
C.instance_only
```
---------
Co-authored-by: David Peter <mail@david-peter.de>
## Summary
Add support for `@classmethod`s.
```py
class C:
@classmethod
def f(cls, x: int) -> str:
return "a"
reveal_type(C.f(1)) # revealed: str
```
## Test Plan
New Markdown tests
## Summary
This PR achieves the following:
* Add support for checking method calls, and inferring return types from
method calls. For example:
```py
reveal_type("abcde".find("abc")) # revealed: int
reveal_type("foo".encode(encoding="utf-8")) # revealed: bytes
"abcde".find(123) # error: [invalid-argument-type]
class C:
def f(self) -> int:
pass
reveal_type(C.f) # revealed: <function `f`>
reveal_type(C().f) # revealed: <bound method: `f` of `C`>
C.f() # error: [missing-argument]
reveal_type(C().f()) # revealed: int
```
* Implement the descriptor protocol, i.e. properly call the `__get__`
method when a descriptor object is accessed through a class object or an
instance of a class. For example:
```py
from typing import Literal
class Ten:
def __get__(self, instance: object, owner: type | None = None) ->
Literal[10]:
return 10
class C:
ten: Ten = Ten()
reveal_type(C.ten) # revealed: Literal[10]
reveal_type(C().ten) # revealed: Literal[10]
```
* Add support for member lookup on intersection types.
* Support type inference for `inspect.getattr_static(obj, attr)` calls.
This was mostly used as a debugging tool during development, but seems
more generally useful. It can be used to bypass the descriptor protocol.
For the example above:
```py
from inspect import getattr_static
reveal_type(getattr_static(C, "ten")) # revealed: Ten
```
* Add a new `Type::Callable(…)` variant with the following sub-variants:
* `Type::Callable(CallableType::BoundMethod(…))` — represents bound
method objects, e.g. `C().f` above
* `Type::Callable(CallableType::MethodWrapperDunderGet(…))` — represents
`f.__get__` where `f` is a function
* `Type::Callable(WrapperDescriptorDunderGet)` — represents
`FunctionType.__get__`
* Add new known classes:
* `types.MethodType`
* `types.MethodWrapperType`
* `types.WrapperDescriptorType`
* `builtins.range`
## Performance analysis
On this branch, we do more work. We need to do more call checking, since
we now check all method calls. We also need to do ~twice as many member
lookups, because we need to check if a `__get__` attribute exists on
accessed members.
A brief analysis on `tomllib` shows that we now call `Type::call` 1780
times, compared to 612 calls before.
## Limitations
* Data descriptors are not yet supported, i.e. we do not infer correct
types for descriptor attribute accesses in `Store` context and do not
check writes to descriptor attributes. I felt like this was something
that could be split out as a follow-up without risking a major
architectural change.
* We currently distinguish between `Type::member` (with descriptor
protocol) and `Type::static_member` (without descriptor protocol). The
former corresponds to `obj.attr`, the latter corresponds to
`getattr_static(obj, "attr")`. However, to model some details correctly,
we would also need to distinguish between a static member lookup *with*
and *without* instance variables. The lookup without instance variables
corresponds to `find_name_in_mro`
[here](https://docs.python.org/3/howto/descriptor.html#invocation-from-an-instance).
We currently approximate both using `member_static`, which leads to two
open TODOs. Changing this would be a larger refactoring of
`Type::own_instance_member`, so I chose to leave it out of this PR.
## Test Plan
* New `call/methods.md` test suite for method calls
* New tests in `descriptor_protocol.md`
* New `call/getattr_static.md` test suite for `inspect.getattr_static`
* Various updated tests
## Summary
* Support assignments to attributes in more cases:
- assignments in `for` loops
- in unpacking assignments
* Add test for multi-target assignments
* Add tests for all other possible assignments to attributes that could
possibly occur (in decreasing order of likeliness):
- augmented attribute assignments
- attribute assignments in `with` statements
- attribute assignments in comprehensions
- Note: assignments to attributes in named expressions are not
syntactically allowed
closes#15962
## Test Plan
New Markdown tests
## Summary
- Minor wording update
- Code improvement (thanks Alex)
- Removed all unnecessary filenames throughout our Markdown tests (two
new ones were added in the meantime)
- Minor rewording of the statically-known-branches introduction
## Summary
Allow for literate style in Markdown tests and merge multiple (unnamed)
code blocks into a single embedded file.
closes#15941
## Test Plan
- Interactively made sure that error-lines were reported correctly in
multi-snippet sections.
## Summary
Resolves#15695, rework of #15704.
This change modifies the Mdtests framework so that:
* Paths must now be specified in a separate preceding line:
`````markdown
`a.py`:
```py
x = 1
```
`````
If the path of a file conflicts with its `lang`, an error will be
thrown.
* Configs are no longer accepted. The pattern still take them into
account, however, to avoid "Unterminated code block" errors.
* Unnamed files are now assigned unique, `lang`-respecting paths
automatically.
Additionally, all legacy usages have been updated.
## Test Plan
Unit tests and Markdown tests.
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
## Summary
Add support for implicitly-defined instance attributes, i.e. support
type inference for cases like this:
```py
class C:
def __init__(self) -> None:
self.x: int = 1
self.y = None
reveal_type(C().x) # int
reveal_type(C().y) # Unknown | None
```
## Benchmarks
Codspeed reports no change in a cold-cache benchmark, and a -1%
regression in the incremental benchmark. On `black`'s `src` folder, I
don't see a statistically significant difference between the branches:
| Command | Mean [ms] | Min [ms] | Max [ms] | Relative |
|:---|---:|---:|---:|---:|
| `./red_knot_main check --project /home/shark/black/src` | 133.7 ± 9.5 | 126.7 | 164.7 | 1.01 ± 0.08 |
| `./red_knot_feature check --project /home/shark/black/src` | 132.2 ± 5.1 | 118.1 | 140.9 | 1.00 |
## Test Plan
Updated and new Markdown tests
## Summary
When we discussed the plan on how to proceed with instance attributes,
we said that we should first extend our research into the behavior of
existing type checkers. The result of this research is summarized in the
newly added / modified tests in this PR. The TODO comments align with
existing behavior of other type checkers. If we deviate from the
behavior, it is described in a comment.
## Summary
Use `Unknown | T_inferred` as the type for *undeclared* public symbols.
## Test Plan
- Updated existing tests
- New test for external `__slots__` modifications.
- New tests for external modifications of public symbols.
## Summary
Raise "invalid-assignment" diagnostics for incorrect assignments to
attributes, for example:
```py
class C:
var: str = "a"
C.var = 1 # error: "Object of type `Literal[1]` is not assignable to `str`"
```
closes#15456
## Test Plan
- Updated test assertions
- New test for assignments to module-attributes
## Summary
Add support for `typing.ClassVar`, i.e. emit a diagnostic in this
scenario:
```py
from typing import ClassVar
class C:
x: ClassVar[int] = 1
c = C()
c.x = 3 # error: "Cannot assign to pure class variable `x` from an instance of type `C`"
```
## Test Plan
- New tests for the `typing.ClassVar` qualifier
- Fixed one TODO in `attributes.md`
## Summary
This is a small, tentative step towards the bigger goal of understanding
instance attributes.
- Adds partial support for pure instance variables declared in the class
body, i.e. this case:
```py
class C:
variable1: str = "a"
variable2 = "b"
reveal_type(C().variable1) # str
reveal_type(C().variable2) # Unknown | Literal["b"]
```
- Adds `property` as a known class to query for `@property` decorators
- Splits up various `@Todo(instance attributes)` cases into
sub-categories.
## Test Plan
Modified existing MD tests.
## Summary
Adds some initial tests for class and instance attributes, mostly to
document (and discuss) what we want to support eventually. These
tests are not exhaustive yet. The idea is to specify the coarse-grained
behavior first.
Things that we'll eventually want to test:
- Interplay with inheritance
- Support `Final` in addition to `ClassVar`
- Specific tests for `ClassVar`, like making sure that we support things
like `x: Annotated[ClassVar[int], "metadata"]`
- … or making sure that we raise an error here:
```py
class Foo:
def __init__(self):
self.x: ClassVar[str] = "x"
```
- Add tests for `__new__` in addition to the tests for `__init__`
- Add tests that show that we use the union of types if multiple methods
define the symbol with different types
- Make sure that diagnostics are raised if, e.g., the inferred type of
an assignment within a method does not match the declared type in the
class body.
- https://github.com/astral-sh/ruff/pull/15474#discussion_r1916556284
- Method calls are completely left out for now.
- Same for `@property`
- … and the descriptor protocol
## Test Plan
New Markdown tests
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
