
## 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.
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Binary operations on instances
Binary operations in Python are implemented by means of magic double-underscore methods.
For references, see:
- https://snarky.ca/unravelling-binary-arithmetic-operations-in-python/
- https://docs.python.org/3/reference/datamodel.html#emulating-numeric-types
Operations
We support inference for all Python's binary operators: +
, -
, *
, @
, /
, //
, %
, **
,
<<
, >>
, &
, ^
, and |
.
class A:
def __add__(self, other) -> "A":
return self
def __sub__(self, other) -> "A":
return self
def __mul__(self, other) -> "A":
return self
def __matmul__(self, other) -> "A":
return self
def __truediv__(self, other) -> "A":
return self
def __floordiv__(self, other) -> "A":
return self
def __mod__(self, other) -> "A":
return self
def __pow__(self, other) -> "A":
return self
def __lshift__(self, other) -> "A":
return self
def __rshift__(self, other) -> "A":
return self
def __and__(self, other) -> "A":
return self
def __xor__(self, other) -> "A":
return self
def __or__(self, other) -> "A":
return self
class B: ...
reveal_type(A() + B()) # revealed: A
reveal_type(A() - B()) # revealed: A
reveal_type(A() * B()) # revealed: A
reveal_type(A() @ B()) # revealed: A
reveal_type(A() / B()) # revealed: A
reveal_type(A() // B()) # revealed: A
reveal_type(A() % B()) # revealed: A
reveal_type(A() ** B()) # revealed: A
reveal_type(A() << B()) # revealed: A
reveal_type(A() >> B()) # revealed: A
reveal_type(A() & B()) # revealed: A
reveal_type(A() ^ B()) # revealed: A
reveal_type(A() | B()) # revealed: A
Reflected
We also support inference for reflected operations:
class A:
def __radd__(self, other) -> "A":
return self
def __rsub__(self, other) -> "A":
return self
def __rmul__(self, other) -> "A":
return self
def __rmatmul__(self, other) -> "A":
return self
def __rtruediv__(self, other) -> "A":
return self
def __rfloordiv__(self, other) -> "A":
return self
def __rmod__(self, other) -> "A":
return self
def __rpow__(self, other) -> "A":
return self
def __rlshift__(self, other) -> "A":
return self
def __rrshift__(self, other) -> "A":
return self
def __rand__(self, other) -> "A":
return self
def __rxor__(self, other) -> "A":
return self
def __ror__(self, other) -> "A":
return self
class B: ...
reveal_type(B() + A()) # revealed: A
reveal_type(B() - A()) # revealed: A
reveal_type(B() * A()) # revealed: A
reveal_type(B() @ A()) # revealed: A
reveal_type(B() / A()) # revealed: A
reveal_type(B() // A()) # revealed: A
reveal_type(B() % A()) # revealed: A
reveal_type(B() ** A()) # revealed: A
reveal_type(B() << A()) # revealed: A
reveal_type(B() >> A()) # revealed: A
reveal_type(B() & A()) # revealed: A
reveal_type(B() ^ A()) # revealed: A
reveal_type(B() | A()) # revealed: A
Returning a different type
The magic methods aren't required to return the type of self
:
class A:
def __add__(self, other) -> int:
return 1
def __rsub__(self, other) -> int:
return 1
class B: ...
reveal_type(A() + B()) # revealed: int
reveal_type(B() - A()) # revealed: int
Non-reflected precedence in general
In general, if the left-hand side defines __add__
and the right-hand side defines __radd__
and
the right-hand side is not a subtype of the left-hand side, lhs.__add__
will take precedence:
class A:
def __add__(self, other: "B") -> int:
return 42
class B:
def __radd__(self, other: "A") -> str:
return "foo"
reveal_type(A() + B()) # revealed: int
# Edge case: C is a subtype of C, *but* if the two sides are of *equal* types,
# the lhs *still* takes precedence
class C:
def __add__(self, other: "C") -> int:
return 42
def __radd__(self, other: "C") -> str:
return "foo"
reveal_type(C() + C()) # revealed: int
Reflected precedence for subtypes (in some cases)
If the right-hand operand is a subtype of the left-hand operand and has a different implementation of the reflected method, the reflected method on the right-hand operand takes precedence.
class A:
def __add__(self, other) -> str:
return "foo"
def __radd__(self, other) -> str:
return "foo"
class MyString(str): ...
class B(A):
def __radd__(self, other) -> MyString:
return MyString()
reveal_type(A() + B()) # revealed: MyString
# N.B. Still a subtype of `A`, even though `A` does not appear directly in the class's `__bases__`
class C(B): ...
reveal_type(A() + C()) # revealed: MyString
Reflected precedence 2
If the right-hand operand is a subtype of the left-hand operand, but does not override the reflected method, the left-hand operand's non-reflected method still takes precedence:
class A:
def __add__(self, other) -> str:
return "foo"
def __radd__(self, other) -> int:
return 42
class B(A): ...
reveal_type(A() + B()) # revealed: str
Only reflected supported
For example, at runtime, (1).__add__(1.2)
is NotImplemented
, but (1.2).__radd__(1) == 2.2
,
meaning that 1 + 1.2
succeeds at runtime (producing 2.2
). The runtime tries the second one only
if the first one returns NotImplemented
to signal failure.
Typeshed and other stubs annotate dunder-method calls that would return NotImplemented
as being
"illegal" calls. int.__add__
is annotated as only "accepting" int
s, even though it
strictly-speaking "accepts" any other object without raising an exception -- it will simply return
NotImplemented
, allowing the runtime to try the __radd__
method of the right-hand operand as
well.
class A:
def __sub__(self, other: "A") -> "A":
return A()
class B:
def __rsub__(self, other: A) -> "B":
return B()
reveal_type(A() - B()) # revealed: B
Callable instances as dunders
Believe it or not, this is supported at runtime:
class A:
def __call__(self, other) -> int:
return 42
class B:
__add__ = A()
reveal_type(B() + B()) # revealed: Unknown | int
Note that we union with Unknown
here because __add__
is not declared. We do infer just int
if
the callable is declared:
class B2:
__add__: A = A()
reveal_type(B2() + B2()) # revealed: int
Integration test: numbers from typeshed
We get less precise results from binary operations on float/complex literals due to the special case
for annotations of float
or complex
, which applies also to return annotations for typeshed
dunder methods. Perhaps we could have a special-case on the special-case, to exclude these typeshed
return annotations from the widening, and preserve a bit more precision here?
reveal_type(3j + 3.14) # revealed: int | float | complex
reveal_type(4.2 + 42) # revealed: int | float
reveal_type(3j + 3) # revealed: int | float | complex
reveal_type(3.14 + 3j) # revealed: int | float | complex
reveal_type(42 + 4.2) # revealed: int | float
reveal_type(3 + 3j) # revealed: int | float | complex
def _(x: bool, y: int):
reveal_type(x + y) # revealed: int
reveal_type(4.2 + x) # revealed: int | float
reveal_type(y + 4.12) # revealed: int | float
With literal types
When we have a literal type for one operand, we're able to fall back to the instance handling for its instance super-type.
class A:
def __add__(self, other) -> "A":
return self
def __radd__(self, other) -> "A":
return self
reveal_type(A() + 1) # revealed: A
reveal_type(1 + A()) # revealed: A
reveal_type(A() + "foo") # revealed: A
reveal_type("foo" + A()) # revealed: A
reveal_type(A() + b"foo") # revealed: A
# TODO should be `A` since `bytes.__add__` doesn't support `A` instances
reveal_type(b"foo" + A()) # revealed: bytes
reveal_type(A() + ()) # revealed: A
# TODO this should be `A`, since `tuple.__add__` doesn't support `A` instances
reveal_type(() + A()) # revealed: @Todo(full tuple[...] support)
literal_string_instance = "foo" * 1_000_000_000
# the test is not testing what it's meant to be testing if this isn't a `LiteralString`:
reveal_type(literal_string_instance) # revealed: LiteralString
reveal_type(A() + literal_string_instance) # revealed: A
reveal_type(literal_string_instance + A()) # revealed: A
Operations involving instances of classes inheriting from Any
Any
and Unknown
represent a set of possible runtime objects, wherein the bounds of the set are
unknown. Whether the left-hand operand's dunder or the right-hand operand's reflected dunder depends
on whether the right-hand operand is an instance of a class that is a subclass of the left-hand
operand's class and overrides the reflected dunder. In the following example, because of the
unknowable nature of Any
/Unknown
, we must consider both possibilities: Any
/Unknown
might
resolve to an unknown third class that inherits from X
and overrides __radd__
; but it also might
not. Thus, the correct answer here for the reveal_type
is int | Unknown
.
from does_not_exist import Foo # error: [unresolved-import]
reveal_type(Foo) # revealed: Unknown
class X:
def __add__(self, other: object) -> int:
return 42
class Y(Foo): ...
# TODO: Should be `int | Unknown`; see above discussion.
reveal_type(X() + Y()) # revealed: int
Operations involving types with invalid __bool__
methods
class NotBoolable:
__bool__: int = 3
a = NotBoolable()
# error: [unsupported-bool-conversion]
10 and a and True
Operations on class objects
When operating on class objects, the corresponding dunder methods are looked up on the metaclass.
from __future__ import annotations
class Meta(type):
def __add__(self, other: Meta) -> int:
return 1
def __lt__(self, other: Meta) -> bool:
return True
def __getitem__(self, key: int) -> str:
return "a"
class A(metaclass=Meta): ...
class B(metaclass=Meta): ...
reveal_type(A + B) # revealed: int
# error: [unsupported-operator] "Operator `-` is unsupported between objects of type `Literal[A]` and `Literal[B]`"
reveal_type(A - B) # revealed: Unknown
reveal_type(A < B) # revealed: bool
reveal_type(A > B) # revealed: bool
# error: [unsupported-operator] "Operator `<=` is not supported for types `Literal[A]` and `Literal[B]`"
reveal_type(A <= B) # revealed: Unknown
reveal_type(A[0]) # revealed: str
Unsupported
Dunder as instance attribute
The magic method must exist on the class, not just on the instance:
def add_impl(self, other) -> int:
return 1
class A:
def __init__(self):
self.__add__ = add_impl
# error: [unsupported-operator] "Operator `+` is unsupported between objects of type `A` and `A`"
# revealed: Unknown
reveal_type(A() + A())
Missing dunder
class A: ...
# error: [unsupported-operator]
# revealed: Unknown
reveal_type(A() + A())
Wrong position
A left-hand dunder method doesn't apply for the right-hand operand, or vice versa:
class A:
def __add__(self, other) -> int:
return 1
class B:
def __radd__(self, other) -> int:
return 1
class C: ...
# error: [unsupported-operator]
# revealed: Unknown
reveal_type(C() + A())
# error: [unsupported-operator]
# revealed: Unknown
reveal_type(B() + C())
Reflected dunder is not tried between two objects of the same type
For the specific case where the left-hand operand is the exact same type as the right-hand operand, the reflected dunder of the right-hand operand is not tried; the runtime short-circuits after trying the unreflected dunder of the left-hand operand. For context, see this mailing list discussion.
class Foo:
def __radd__(self, other: "Foo") -> "Foo":
return self
# error: [unsupported-operator]
# revealed: Unknown
reveal_type(Foo() + Foo())
Wrong type
TODO: check signature and error if other
is the wrong type