## Summary
We currently emit a diagnostic for code like the following:
```py
from typing import Any
# error: Invalid class base with type `GenericAlias` (all bases must be a class, `Any`, `Unknown` or `Todo`)
class C(tuple[Any, ...]): ...
```
The changeset here silences this diagnostic by recognizing instances of
`GenericAlias` in `ClassBase::try_from_type`, and inferring a `@Todo`
type for them. This is a change in preparation for #17557, because `C`
previously had `Unknown` in its MRO …
```py
reveal_type(C.__mro__) # tuple[Literal[C], Unknown, Literal[object]]
```
… which would cause us to think that `C` is assignable to everything.
The changeset also removes some false positive `invalid-base`
diagnostics across the ecosystem.
## Test Plan
Updated Markdown tests.
## 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
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
* 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
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
Related to #15848, this PR adds the imports explicitly as we'll now flag
these symbols as undefined.
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
Another small PR to focus #15674 solely on the relevant changes. This
makes our Markdown tests less dependent on precise types of public
symbols, without actually changing anything semantically in these tests.
Best reviewed using ignore-whitespace-mode.
## Test Plan
Tested these changes on `main` and on the branch from #15674.
## Summary
This changeset adds support for precise type-inference and
boundness-handling of definitions inside control-flow branches with
statically-known conditions, i.e. test-expressions whose truthiness we
can unambiguously infer as *always false* or *always true*.
This branch also includes:
- `sys.platform` support
- statically-known branches handling for Boolean expressions and while
loops
- new `target-version` requirements in some Markdown tests which were
now required due to the understanding of `sys.version_info` branches.
closes#12700closes#15034
## Performance
### `tomllib`, -7%, needs to resolve one additional module (sys)
| Command | Mean [ms] | Min [ms] | Max [ms] | Relative |
|:---|---:|---:|---:|---:|
| `./red_knot_main --project /home/shark/tomllib` | 22.2 ± 1.3 | 19.1 |
25.6 | 1.00 |
| `./red_knot_feature --project /home/shark/tomllib` | 23.8 ± 1.6 | 20.8
| 28.6 | 1.07 ± 0.09 |
### `black`, -6%
| Command | Mean [ms] | Min [ms] | Max [ms] | Relative |
|:---|---:|---:|---:|---:|
| `./red_knot_main --project /home/shark/black` | 129.3 ± 5.1 | 119.0 |
137.8 | 1.00 |
| `./red_knot_feature --project /home/shark/black` | 136.5 ± 6.8 | 123.8
| 147.5 | 1.06 ± 0.07 |
## Test Plan
- New Markdown tests for the main feature in
`statically-known-branches.md`
- New Markdown tests for `sys.platform`
- Adapted tests for `EllipsisType`, `Never`, etc
## Summary
This PR renames the `--custom-typeshed-dir`, `target-version`, and
`--current-directory` cli options to `--typeshed`,
`--python-version`, and `--project` as discussed in the CLI proposal
document.
I added aliases for `--target-version` (for Ruff compat) and
`--custom-typeshed-dir` (for Alex)
## Test Plan
Long help
```
An extremely fast Python type checker.
Usage: red_knot [OPTIONS] [COMMAND]
Commands:
server Start the language server
help Print this message or the help of the given subcommand(s)
Options:
--project <PROJECT>
Run the command within the given project directory.
All `pyproject.toml` files will be discovered by walking up the directory tree from the project root, as will the project's virtual environment (`.venv`).
Other command-line arguments (such as relative paths) will be resolved relative to the current working directory."#,
--venv-path <PATH>
Path to the virtual environment the project uses.
If provided, red-knot will use the `site-packages` directory of this virtual environment to resolve type information for the project's third-party dependencies.
--typeshed-path <PATH>
Custom directory to use for stdlib typeshed stubs
--extra-search-path <PATH>
Additional path to use as a module-resolution source (can be passed multiple times)
--python-version <VERSION>
Python version to assume when resolving types
[possible values: 3.7, 3.8, 3.9, 3.10, 3.11, 3.12, 3.13]
-v, --verbose...
Use verbose output (or `-vv` and `-vvv` for more verbose output)
-W, --watch
Run in watch mode by re-running whenever files change
-h, --help
Print help (see a summary with '-h')
-V, --version
Print version
```
Short help
```
An extremely fast Python type checker.
Usage: red_knot [OPTIONS] [COMMAND]
Commands:
server Start the language server
help Print this message or the help of the given subcommand(s)
Options:
--project <PROJECT> Run the command within the given project directory
--venv-path <PATH> Path to the virtual environment the project uses
--typeshed-path <PATH> Custom directory to use for stdlib typeshed stubs
--extra-search-path <PATH> Additional path to use as a module-resolution source (can be passed multiple times)
--python-version <VERSION> Python version to assume when resolving types [possible values: 3.7, 3.8, 3.9, 3.10, 3.11, 3.12, 3.13]
-v, --verbose... Use verbose output (or `-vv` and `-vvv` for more verbose output)
-W, --watch Run in watch mode by re-running whenever files change
-h, --help Print help (see more with '--help')
-V, --version Print version
```
---------
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
## Summary
Adds meta information to `Type::Todo`, allowing developers to easily
trace back the origin of a particular `@Todo` type they encounter.
Instead of `Type::Todo`, we now write either `type_todo!()` which
creates a `@Todo[path/to/source.rs:123]` type with file and line
information, or using `type_todo!("PEP 604 unions not supported")`,
which creates a variant with a custom message.
`Type::Todo` now contains a `TodoType` field. In release mode, this is
just a zero-sized struct, in order not to create any overhead. In debug
mode, this is an `enum` that contains the meta information.
`Type` implements `Copy`, which means that `TodoType` also needs to be
copyable. This limits the design space. We could intern `TodoType`, but
I discarded this option, as it would require us to have access to the
salsa DB everywhere we want to use `Type::Todo`. And it would have made
the macro invocations less ergonomic (requiring us to pass `db`).
So for now, the meta information is simply a `&'static str` / `u32` for
the file/line variant, or a `&'static str` for the custom message.
Anything involving a chain/backtrace of several `@Todo`s or similar is
therefore currently not implemented. Also because we currently don't see
any direct use cases for this, and because all of this will eventually
go away.
Note that the size of `Type` increases from 16 to 24 bytes, but only in
debug mode.
## Test Plan
- Observed the changes in Markdown tests.
- Added custom messages for all `Type::Todo`s that were revealed in the
tests
- Ran red knot in release and debug mode on the following Python file:
```py
def f(x: int) -> int:
reveal_type(x)
```
Prints `@Todo` in release mode and `@Todo(function parameter type)` in
debug mode.
## Summary
- Add a new `Type::SliceLiteral` variant
- Infer `SliceLiteral` types for slice expressions, such as
`<int-literal>:<int-literal>:<int-literal>`.
- Infer "sliced" literal types for subscript expressions using slices,
such as `<string-literal>[<slice-literal>]`.
- Infer types for expressions involving slices of tuples:
`<tuple>[<slice-literal>]`.
closes#13853
## Test Plan
- Unit tests for indexing/slicing utility functions
- Markdown-based tests for
- Subscript expressions `tuple[slice]`
- Subscript expressions `string_literal[slice]`
- Subscript expressions `bytes_literal[slice]`
Minor cleanup and consistent formatting of the Markdown-based tests.
- Removed lots of unnecessary `a`, `b`, `c`, … variables.
- Moved test assertions (`# revealed:` comments) closer to the tested
object.
- Always separate `# revealed` and `# error` comments from the code by
two spaces, according to the discussion
[here](https://github.com/astral-sh/ruff/pull/13746/files#r1799385758).
This trades readability for consistency in some cases.
- Fixed some headings
## Summary
Porting infer tests to new markdown tests framework.
Link to the corresponding issue: #13696
---------
Co-authored-by: Carl Meyer <carl@astral.sh>
