# Generic functions: PEP 695 syntax ```toml [environment] python-version = "3.12" ``` ## Typevar must be used at least twice If you're only using a typevar for a single parameter, you don't need the typevar — just use `object` (or the typevar's upper bound): ```py # TODO: error, should be (x: object) def typevar_not_needed[T](x: T) -> None: pass # TODO: error, should be (x: int) def bounded_typevar_not_needed[T: int](x: T) -> None: pass ``` Typevars are only needed if you use them more than once. For instance, to specify that two parameters must both have the same type: ```py def two_params[T](x: T, y: T) -> T: return x ``` or to specify that a return value is the same as a parameter: ```py def return_value[T](x: T) -> T: return x ``` Each typevar must also appear _somewhere_ in the parameter list: ```py def absurd[T]() -> T: # There's no way to construct a T! raise ValueError("absurd") ``` ## Inferring generic function parameter types If the type of a generic function parameter is a typevar, then we can infer what type that typevar is bound to at each call site. ```py def f[T](x: T) -> T: return x reveal_type(f(1)) # revealed: Literal[1] reveal_type(f(1.0)) # revealed: float reveal_type(f(True)) # revealed: Literal[True] reveal_type(f("string")) # revealed: Literal["string"] ``` ## Inferring “deep” generic parameter types The matching up of call arguments and discovery of constraints on typevars can be a recursive process for arbitrarily-nested generic classes and protocols in parameters. TODO: Note that we can currently only infer a specialization for a generic protocol when the argument _explicitly_ implements the protocol by listing it as a base class. ```py from typing import Protocol, TypeVar S = TypeVar("S") class CanIndex(Protocol[S]): def __getitem__(self, index: int, /) -> S: ... class ExplicitlyImplements[T](CanIndex[T]): ... def takes_in_list[T](x: list[T]) -> list[T]: return x def takes_in_protocol[T](x: CanIndex[T]) -> T: return x[0] def deep_list(x: list[str]) -> None: reveal_type(takes_in_list(x)) # revealed: list[str] # TODO: revealed: str reveal_type(takes_in_protocol(x)) # revealed: Unknown def deeper_list(x: list[set[str]]) -> None: reveal_type(takes_in_list(x)) # revealed: list[set[str]] # TODO: revealed: set[str] reveal_type(takes_in_protocol(x)) # revealed: Unknown def deep_explicit(x: ExplicitlyImplements[str]) -> None: reveal_type(takes_in_protocol(x)) # revealed: str def deeper_explicit(x: ExplicitlyImplements[set[str]]) -> None: reveal_type(takes_in_protocol(x)) # revealed: set[str] def takes_in_type[T](x: type[T]) -> type[T]: return x reveal_type(takes_in_type(int)) # revealed: type[int] ``` This also works when passing in arguments that are subclasses of the parameter type. ```py class Sub(list[int]): ... class GenericSub[T](list[T]): ... reveal_type(takes_in_list(Sub())) # revealed: list[int] # TODO: revealed: int reveal_type(takes_in_protocol(Sub())) # revealed: Unknown reveal_type(takes_in_list(GenericSub[str]())) # revealed: list[str] # TODO: revealed: str reveal_type(takes_in_protocol(GenericSub[str]())) # revealed: Unknown class ExplicitSub(ExplicitlyImplements[int]): ... class ExplicitGenericSub[T](ExplicitlyImplements[T]): ... reveal_type(takes_in_protocol(ExplicitSub())) # revealed: int reveal_type(takes_in_protocol(ExplicitGenericSub[str]())) # revealed: str ``` ## Inferring tuple parameter types ```py def takes_mixed_tuple_suffix[T](x: tuple[int, bytes, *tuple[str, ...], T, int]) -> T: return x[-2] def takes_mixed_tuple_prefix[T](x: tuple[int, T, *tuple[str, ...], bool, int]) -> T: return x[1] def _(x: tuple[int, bytes, *tuple[str, ...], bool, int]): reveal_type(takes_mixed_tuple_suffix(x)) # revealed: bool reveal_type(takes_mixed_tuple_prefix(x)) # revealed: bytes reveal_type(takes_mixed_tuple_suffix((1, b"foo", "bar", "baz", True, 42))) # revealed: Literal[True] reveal_type(takes_mixed_tuple_prefix((1, b"foo", "bar", "baz", True, 42))) # revealed: Literal[b"foo"] def takes_fixed_tuple[T](x: tuple[T, int]) -> T: return x[0] def _(x: tuple[str, int]): reveal_type(takes_fixed_tuple(x)) # revealed: str reveal_type(takes_fixed_tuple((True, 42))) # revealed: Literal[True] def takes_homogeneous_tuple[T](x: tuple[T, ...]) -> T: return x[0] def _(x: tuple[str, int], y: tuple[bool, ...], z: tuple[int, str, *tuple[range, ...], bytes]): reveal_type(takes_homogeneous_tuple(x)) # revealed: str | int reveal_type(takes_homogeneous_tuple(y)) # revealed: bool reveal_type(takes_homogeneous_tuple(z)) # revealed: int | str | range | bytes reveal_type(takes_homogeneous_tuple((42,))) # revealed: Literal[42] reveal_type(takes_homogeneous_tuple((42, 43))) # revealed: Literal[42, 43] ``` ## Inferring a bound typevar ```py from typing_extensions import reveal_type def f[T: int](x: T) -> T: return x reveal_type(f(1)) # revealed: Literal[1] reveal_type(f(True)) # revealed: Literal[True] # error: [invalid-argument-type] reveal_type(f("string")) # revealed: Unknown ``` ## Inferring a constrained typevar ```py from typing_extensions import reveal_type def f[T: (int, None)](x: T) -> T: return x reveal_type(f(1)) # revealed: int reveal_type(f(True)) # revealed: int reveal_type(f(None)) # revealed: None # error: [invalid-argument-type] reveal_type(f("string")) # revealed: Unknown ``` ## Typevar constraints If a type parameter has an upper bound, that upper bound constrains which types can be used for that typevar. This effectively adds the upper bound as an intersection to every appearance of the typevar in the function. ```py def good_param[T: int](x: T) -> None: reveal_type(x) # revealed: T@good_param ``` If the function is annotated as returning the typevar, this means that the upper bound is _not_ assignable to that typevar, since return types are contravariant. In `bad`, we can infer that `x + 1` has type `int`. But `T` might be instantiated with a narrower type than `int`, and so the return value is not guaranteed to be compatible for all `T: int`. ```py def good_return[T: int](x: T) -> T: return x def bad_return[T: int](x: T) -> T: # error: [invalid-return-type] "Return type does not match returned value: expected `T@bad_return`, found `int`" return x + 1 ``` ## All occurrences of the same typevar have the same type If a typevar appears multiple times in a function signature, all occurrences have the same type. ```py def different_types[T, S](cond: bool, t: T, s: S) -> T: if cond: return t else: # error: [invalid-return-type] "Return type does not match returned value: expected `T@different_types`, found `S@different_types`" return s def same_types[T](cond: bool, t1: T, t2: T) -> T: if cond: return t1 else: return t2 ``` ## All occurrences of the same constrained typevar have the same type The above is true even when the typevars are constrained. Here, both `int` and `str` have `__add__` methods that are compatible with the return type, so the `return` expression is always well-typed: ```py def same_constrained_types[T: (int, str)](t1: T, t2: T) -> T: # TODO: no error # error: [unsupported-operator] "Operator `+` is not supported between two objects of type `T@same_constrained_types`" return t1 + t2 ``` This is _not_ the same as a union type, because of this additional constraint that the two occurrences have the same type. In `unions_are_different`, `t1` and `t2` might have different types, and an `int` and a `str` cannot be added together: ```py def unions_are_different(t1: int | str, t2: int | str) -> int | str: # error: [unsupported-operator] "Operator `+` is not supported between two objects of type `int | str`" return t1 + t2 ``` ## Typevar inference is a unification problem When inferring typevar assignments in a generic function call, we cannot simply solve constraints eagerly for each parameter in turn. We must solve a unification problem involving all of the parameters simultaneously. ```py def two_params[T](x: T, y: T) -> T: return x reveal_type(two_params("a", "b")) # revealed: Literal["a", "b"] reveal_type(two_params("a", 1)) # revealed: Literal["a", 1] ``` When one of the parameters is a union, we attempt to find the smallest specialization that satisfies all of the constraints. ```py def union_param[T](x: T | None) -> T: if x is None: raise ValueError return x reveal_type(union_param("a")) # revealed: Literal["a"] reveal_type(union_param(1)) # revealed: Literal[1] reveal_type(union_param(None)) # revealed: Unknown def _(x: int | None): reveal_type(union_param(x)) # revealed: int ``` ```py def union_and_nonunion_params[T](x: T | int, y: T) -> T: return y reveal_type(union_and_nonunion_params(1, "a")) # revealed: Literal["a"] reveal_type(union_and_nonunion_params("a", "a")) # revealed: Literal["a"] reveal_type(union_and_nonunion_params(1, 1)) # revealed: Literal[1] reveal_type(union_and_nonunion_params(3, 1)) # revealed: Literal[1] reveal_type(union_and_nonunion_params("a", 1)) # revealed: Literal["a", 1] ``` This also works if the typevar has a bound: ```py def accepts_t_or_int[T_str: str](x: T_str | int) -> T_str: raise NotImplementedError reveal_type(accepts_t_or_int("a")) # revealed: Literal["a"] reveal_type(accepts_t_or_int(1)) # revealed: Unknown class Unrelated: ... # error: [invalid-argument-type] "Argument type `Unrelated` does not satisfy upper bound `str` of type variable `T_str`" reveal_type(accepts_t_or_int(Unrelated())) # revealed: Unknown def accepts_t_or_list_of_t[T: str](x: T | list[T]) -> T: raise NotImplementedError reveal_type(accepts_t_or_list_of_t("a")) # revealed: Literal["a"] # error: [invalid-argument-type] "Argument type `Literal[1]` does not satisfy upper bound `str` of type variable `T`" reveal_type(accepts_t_or_list_of_t(1)) # revealed: Unknown def _(list_ofstr: list[str], list_of_int: list[int]): reveal_type(accepts_t_or_list_of_t(list_ofstr)) # revealed: str # TODO: the error message here could be improved by referring to the second union element # error: [invalid-argument-type] "Argument type `list[int]` does not satisfy upper bound `str` of type variable `T`" reveal_type(accepts_t_or_list_of_t(list_of_int)) # revealed: Unknown ``` Here, we make sure that `S` is solved as `Literal[1]` instead of a union of the two literals, which would also be a valid solution: ```py def tuple_param[T, S](x: T | S, y: tuple[T, S]) -> tuple[T, S]: return y reveal_type(tuple_param("a", ("a", 1))) # revealed: tuple[Literal["a"], Literal[1]] reveal_type(tuple_param(1, ("a", 1))) # revealed: tuple[Literal["a"], Literal[1]] ``` When a union parameter contains generic classes like `P[T] | Q[T]`, we can infer the typevar from the actual argument even for non-final classes. ```py class P[T]: x: T # invariant class Q[T]: x: T # invariant def extract_t[T](x: P[T] | Q[T]) -> T: raise NotImplementedError reveal_type(extract_t(P[int]())) # revealed: int reveal_type(extract_t(Q[str]())) # revealed: str ``` Passing anything else results in an error: ```py # error: [invalid-argument-type] reveal_type(extract_t([1, 2])) # revealed: Unknown ``` This also works when different union elements have different typevars: ```py def extract_both[T, S](x: P[T] | Q[S]) -> tuple[T, S]: raise NotImplementedError reveal_type(extract_both(P[int]())) # revealed: tuple[int, Unknown] reveal_type(extract_both(Q[str]())) # revealed: tuple[Unknown, str] ``` Inference also works when passing subclasses of the generic classes in the union. ```py class SubP[T](P[T]): pass class SubQ[T](Q[T]): pass reveal_type(extract_t(SubP[int]())) # revealed: int reveal_type(extract_t(SubQ[str]())) # revealed: str reveal_type(extract_both(SubP[int]())) # revealed: tuple[int, Unknown] reveal_type(extract_both(SubQ[str]())) # revealed: tuple[Unknown, str] ``` When a type is a subclass of both `P` and `Q` with different specializations, we cannot infer a single type for `T` in `extract_t`, because `P` and `Q` are invariant. However, we can still infer both types in a call to `extract_both`: ```py class PandQ(P[int], Q[str]): pass # TODO: Ideally, we would return `Unknown` here. # error: [invalid-argument-type] reveal_type(extract_t(PandQ())) # revealed: int | str reveal_type(extract_both(PandQ())) # revealed: tuple[int, str] ``` When non-generic types are part of the union, we can still infer typevars for the remaining generic types: ```py def extract_optional_t[T](x: None | P[T]) -> T: raise NotImplementedError reveal_type(extract_optional_t(None)) # revealed: Unknown reveal_type(extract_optional_t(P[int]())) # revealed: int ``` Passing anything else results in an error: ```py # error: [invalid-argument-type] reveal_type(extract_optional_t(Q[str]())) # revealed: Unknown ``` If the union contains contains parent and child of a generic class, we ideally pick the union element that is more precise: ```py class Base[T]: x: T class Sub[T](Base[T]): ... def f[T](t: Base[T] | Sub[T | None]) -> T: raise NotImplementedError reveal_type(f(Base[int]())) # revealed: int # TODO: Should ideally be `str` reveal_type(f(Sub[str | None]())) # revealed: str | None ``` If we have a case like the following, where only one of the union elements matches due to the typevar bound, we do not emit a specialization error: ```py class P[T]: value: T def f[I: int, S: str](t: P[I] | P[S]) -> tuple[I, S]: raise NotImplementedError reveal_type(f(P[int]())) # revealed: tuple[int, Unknown] reveal_type(f(P[str]())) # revealed: tuple[Unknown, str] ``` However, if we pass something that does not match _any_ union element, we do emit an error: ```py # error: [invalid-argument-type] reveal_type(f(P[bytes]())) # revealed: tuple[Unknown, Unknown] ``` ## Inferring nested generic function calls We can infer type assignments in nested calls to multiple generic functions. If they use the same type variable, we do not confuse the two; `T@f` and `T@g` have separate types in each example below. ```py def f[T](x: T) -> tuple[T, int]: return (x, 1) def g[T](x: T) -> T | None: return x reveal_type(f(g("a"))) # revealed: tuple[Literal["a"] | None, int] reveal_type(g(f("a"))) # revealed: tuple[Literal["a"], int] | None ``` ## Passing generic functions to generic functions ```py from typing import Callable def invoke[A, B](fn: Callable[[A], B], value: A) -> B: return fn(value) def identity[T](x: T) -> T: return x def head[T](xs: list[T]) -> T: return xs[0] reveal_type(invoke(identity, 1)) # revealed: Literal[1] # TODO: this should be `Unknown | int` reveal_type(invoke(head, [1, 2, 3])) # revealed: Unknown ``` ## Protocols as TypeVar bounds Protocol types can be used as TypeVar bounds, just like nominal types. ```py from typing import Any, Protocol from ty_extensions import static_assert, is_assignable_to class SupportsClose(Protocol): def close(self) -> None: ... class ClosableFullyStaticProtocol(Protocol): x: int def close(self) -> None: ... class ClosableNonFullyStaticProtocol(Protocol): x: Any def close(self) -> None: ... class ClosableFullyStaticNominal: x: int def close(self) -> None: ... class ClosableNonFullyStaticNominal: x: int def close(self) -> None: ... class NotClosableProtocol(Protocol): ... class NotClosableNominal: ... def close_and_return[T: SupportsClose](x: T) -> T: x.close() return x def f( a: SupportsClose, b: ClosableFullyStaticProtocol, c: ClosableNonFullyStaticProtocol, d: ClosableFullyStaticNominal, e: ClosableNonFullyStaticNominal, f: NotClosableProtocol, g: NotClosableNominal, ): reveal_type(close_and_return(a)) # revealed: SupportsClose reveal_type(close_and_return(b)) # revealed: ClosableFullyStaticProtocol reveal_type(close_and_return(c)) # revealed: ClosableNonFullyStaticProtocol reveal_type(close_and_return(d)) # revealed: ClosableFullyStaticNominal reveal_type(close_and_return(e)) # revealed: ClosableNonFullyStaticNominal # error: [invalid-argument-type] "does not satisfy upper bound" reveal_type(close_and_return(f)) # revealed: Unknown # error: [invalid-argument-type] "does not satisfy upper bound" reveal_type(close_and_return(g)) # revealed: Unknown ``` ## Opaque decorators don't affect typevar binding Inside the body of a generic function, we should be able to see that the typevars bound by that function are in fact bound by that function. This requires being able to see the enclosing function's _undecorated_ type and signature, especially in the case where a gradually typed decorator "hides" the function type from outside callers. ```py from typing import cast, Any, Callable def opaque_decorator(f: Any) -> Any: return f def transparent_decorator[F: Callable[..., Any]](f: F) -> F: return f @opaque_decorator def decorated[T](t: T) -> None: # error: [redundant-cast] reveal_type(cast(T, t)) # revealed: T@decorated @transparent_decorator def decorated[T](t: T) -> None: # error: [redundant-cast] reveal_type(cast(T, t)) # revealed: T@decorated ``` ## Solving TypeVars with upper bounds in unions ```py class A: ... class B[T: A]: x: T def f[T: A](c: T | None): return None def g[T: A](b: B[T]): return f(b.x) # Fine ``` ## Typevars in a union ```py def takes_in_union[T](t: T | None) -> T: raise NotImplementedError def takes_in_bigger_union[T](t: T | int | None) -> T: raise NotImplementedError def _(x: str | None) -> None: reveal_type(takes_in_union(x)) # revealed: str reveal_type(takes_in_bigger_union(x)) # revealed: str def _(x: str | int | None) -> None: reveal_type(takes_in_union(x)) # revealed: str | int reveal_type(takes_in_bigger_union(x)) # revealed: str ``` This is a regression test for an issue that surfaced in the primer report of an early version of , where we failed to solve the `TypeVar` here due to the fact that it only appears in the function's type annotations as part of a union: ```py def f[T: (str, bytes)](suffix: T | None, prefix: T | None): return None def g(x: str): f(prefix=x, suffix=".tar.gz") ``` If the type variable is present multiple times in the union, we choose the correct union element to infer against based on the argument type: ```py def h[T](x: list[T] | dict[T, T]) -> T | None: ... def _(x: list[int], y: dict[int, int]): reveal_type(h(x)) # revealed: int | None reveal_type(h(y)) # revealed: int | None ``` ## Nested functions see typevars bound in outer function ```py from typing import overload def outer[T](t: T) -> None: def inner[T](t: T) -> None: ... inner(t) @overload def overloaded_outer() -> None: ... @overload def overloaded_outer[T](t: T) -> None: ... def overloaded_outer[T](t: T | None = None) -> None: def inner(t: T) -> None: ... if t is not None: inner(t) def outer[T](t: T) -> None: def inner[S](inner_t: T, s: S) -> tuple[T, S]: return inner_t, s reveal_type(inner(t, 1)) # revealed: tuple[T@outer, Literal[1]] inner("wrong", 1) # error: [invalid-argument-type] ``` ## Unpacking a TypeVar We can infer precise heterogeneous types from the result of an unpacking operation applied to a TypeVar if the TypeVar's upper bound is a type with a precise tuple spec: ```py from dataclasses import dataclass from typing import NamedTuple, Final def f[T: tuple[int, str]](x: T) -> T: a, b = x reveal_type(a) # revealed: int reveal_type(b) # revealed: str return x @dataclass class Team[T: tuple[int, str]]: employees: list[T] def x[T: tuple[int, str]](team: Team[T]) -> Team[T]: age, name = team.employees[0] reveal_type(age) # revealed: int reveal_type(name) # revealed: str return team class Age(int): ... class Name(str): ... class Employee(NamedTuple): age: Age name: Name EMPLOYEES: Final = (Employee(name=Name("alice"), age=Age(42)),) team = Team(employees=list(EMPLOYEES)) reveal_type(team.employees) # revealed: list[Employee] age, name = team.employees[0] reveal_type(age) # revealed: Age reveal_type(name) # revealed: Name ``` ## `self` in PEP 695 generic methods When a generic method uses a PEP 695 generic context, an implict or explicit annotation of `self: Self` is still part of the full generic context: ```py from typing import Self class C: def explicit_self[T](self: Self, x: T) -> tuple[Self, T]: return self, x def implicit_self[T](self, x: T) -> tuple[Self, T]: return self, x def _(x: int): reveal_type(C().explicit_self(x)) # revealed: tuple[C, int] reveal_type(C().implicit_self(x)) # revealed: tuple[C, int] ``` ## `~T` is never assignable to `T` ```py from ty_extensions import Not def f[T](x: T, y: Not[T]) -> T: x = y # error: [invalid-assignment] y = x # error: [invalid-assignment] return x ``` ## `Callable` parameters We can recurse into the parameters and return values of `Callable` parameters to infer specializations of a generic function. ```py from typing import Any, Callable, NoReturn, overload, Self from ty_extensions import generic_context, into_callable def accepts_callable[**P, R](callable: Callable[P, R]) -> Callable[P, R]: return callable def returns_int() -> int: raise NotImplementedError # revealed: () -> int reveal_type(into_callable(returns_int)) # revealed: () -> int reveal_type(accepts_callable(returns_int)) # revealed: int reveal_type(accepts_callable(returns_int)()) class ClassWithoutConstructor: ... # revealed: () -> ClassWithoutConstructor reveal_type(into_callable(ClassWithoutConstructor)) # revealed: () -> ClassWithoutConstructor reveal_type(accepts_callable(ClassWithoutConstructor)) # revealed: ClassWithoutConstructor reveal_type(accepts_callable(ClassWithoutConstructor)()) class ClassWithNew: def __new__(cls, *args, **kwargs) -> Self: raise NotImplementedError # revealed: (...) -> ClassWithNew reveal_type(into_callable(ClassWithNew)) # revealed: (...) -> ClassWithNew reveal_type(accepts_callable(ClassWithNew)) # revealed: ClassWithNew reveal_type(accepts_callable(ClassWithNew)()) class ClassWithInit: def __init__(self) -> None: ... # revealed: () -> ClassWithInit reveal_type(into_callable(ClassWithInit)) # revealed: () -> ClassWithInit reveal_type(accepts_callable(ClassWithInit)) # revealed: ClassWithInit reveal_type(accepts_callable(ClassWithInit)()) class ClassWithNewAndInit: def __new__(cls, *args, **kwargs) -> Self: raise NotImplementedError def __init__(self, x: int) -> None: ... # TODO: We do not currently solve a common behavioral supertype for the two solutions of P. # revealed: ((...) -> ClassWithNewAndInit) | ((x: int) -> ClassWithNewAndInit) reveal_type(into_callable(ClassWithNewAndInit)) # TODO: revealed: ((...) -> ClassWithNewAndInit) | ((x: int) -> ClassWithNewAndInit) # revealed: (...) -> ClassWithNewAndInit reveal_type(accepts_callable(ClassWithNewAndInit)) # revealed: ClassWithNewAndInit reveal_type(accepts_callable(ClassWithNewAndInit)()) class Meta(type): def __call__(cls, *args: Any, **kwargs: Any) -> NoReturn: raise NotImplementedError class ClassWithNoReturnMetatype(metaclass=Meta): def __new__(cls, *args: Any, **kwargs: Any) -> Self: raise NotImplementedError # TODO: The return types here are wrong, because we end up creating a constraint (Never ≤ R), which # we confuse with "R has no lower bound". # revealed: (...) -> Never reveal_type(into_callable(ClassWithNoReturnMetatype)) # TODO: revealed: (...) -> Never # revealed: (...) -> Unknown reveal_type(accepts_callable(ClassWithNoReturnMetatype)) # TODO: revealed: Never # revealed: Unknown reveal_type(accepts_callable(ClassWithNoReturnMetatype)()) class Proxy: ... class ClassWithIgnoredInit: def __new__(cls) -> Proxy: return Proxy() def __init__(self, x: int) -> None: ... # revealed: () -> Proxy reveal_type(into_callable(ClassWithIgnoredInit)) # revealed: () -> Proxy reveal_type(accepts_callable(ClassWithIgnoredInit)) # revealed: Proxy reveal_type(accepts_callable(ClassWithIgnoredInit)()) class ClassWithOverloadedInit[T]: t: T # invariant @overload def __init__(self: "ClassWithOverloadedInit[int]", x: int) -> None: ... @overload def __init__(self: "ClassWithOverloadedInit[str]", x: str) -> None: ... def __init__(self, x: int | str) -> None: ... # TODO: The old solver cannot handle this overloaded constructor. The ideal solution is that we # would solve **P once, and map it to the entire overloaded signature of the constructor. This # mapping would have to include the return types, since there are different return types for each # overload. We would then also have to determine that R must be equal to the return type of **P's # solution. # revealed: Overload[(x: int) -> ClassWithOverloadedInit[int], (x: str) -> ClassWithOverloadedInit[str]] reveal_type(into_callable(ClassWithOverloadedInit)) # TODO: revealed: Overload[(x: int) -> ClassWithOverloadedInit[int], (x: str) -> ClassWithOverloadedInit[str]] # revealed: Overload[(x: int) -> ClassWithOverloadedInit[int] | ClassWithOverloadedInit[str], (x: str) -> ClassWithOverloadedInit[int] | ClassWithOverloadedInit[str]] reveal_type(accepts_callable(ClassWithOverloadedInit)) # TODO: revealed: ClassWithOverloadedInit[int] # revealed: ClassWithOverloadedInit[int] | ClassWithOverloadedInit[str] reveal_type(accepts_callable(ClassWithOverloadedInit)(0)) # TODO: revealed: ClassWithOverloadedInit[str] # revealed: ClassWithOverloadedInit[int] | ClassWithOverloadedInit[str] reveal_type(accepts_callable(ClassWithOverloadedInit)("")) class GenericClass[T]: t: T # invariant def __new__(cls, x: list[T], y: list[T]) -> Self: raise NotImplementedError def _(x: list[str]): # TODO: This fails because we are not propagating GenericClass's generic context into the # Callable that we create for it. # revealed: (x: list[T@GenericClass], y: list[T@GenericClass]) -> GenericClass[T@GenericClass] reveal_type(into_callable(GenericClass)) # revealed: ty_extensions.GenericContext[T@GenericClass] reveal_type(generic_context(into_callable(GenericClass))) # revealed: (x: list[T@GenericClass], y: list[T@GenericClass]) -> GenericClass[T@GenericClass] reveal_type(accepts_callable(GenericClass)) # TODO: revealed: ty_extensions.GenericContext[T@GenericClass] # revealed: None reveal_type(generic_context(accepts_callable(GenericClass))) # TODO: revealed: GenericClass[str] # TODO: no errors # revealed: GenericClass[T@GenericClass] # error: [invalid-argument-type] # error: [invalid-argument-type] reveal_type(accepts_callable(GenericClass)(x, x)) ```