Suggestion: Allow free type variables in type variable bounds that permeate beyond
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Description
Suppose we have the following code:
T_co = TypeVar("T_co", covariant=True)
class CanProduce(Protocol[T_co]):
def produce(self) -> T_co:
...
T_in = TypeVar("T_in")
U = TypeVar("U")
@dataclass
class Container(Generic[T_in]):
value: T_in
def produce_from_value(self: Container[CanProduce[U]]) -> U:
return self.value.produce()
This code has an undesirable property: Since T_in is invariant, produce_from_value can only be called on instances of Container whose type parameter is exactly CanProduce[U], for some U:
class IntProducer(CanProduce[int]):
def produce(self) -> int:
return 42
c: Container[IntProducer] = Container(IntProducer())
c.produce_from_value() # this produces a type error
It would be ideal if we could communicate that in this method (which need not be an instance method, it could be a discrete function also), the type parameter behaves as though it were covariant, where any subtype of CanProduce[U] is valid.
In fact, there exists a mechanism for doing this in other situations. Consider if we have the following non-generic protocol:
class SupportsIndex(Protocol):
def __index__(self) -> int:
...
We can then make a method index_from_value that works with all subtypes of SupportsIndex:
SI = TypeVar("SI", bound=SupportsIndex)
@dataclass
class Container(Generic[T_in]):
value: T_in
def index_from_value(self: Container[SI]):
return self.value.__index__
Now, the following is valid:
c: Container[int] = Container(27)
c.index_from_value()
Unfortunately, this method cannot be used with generic protocols, because the following is invalid:
U = TypeVar("U")
CPU = TypeVar("CPU", bound=CanProduce[U]) # this produces a type error
I suggest altering the restriction to allow this trick to work.
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Research direction
Start with the generic protocol, Container, and TypeVar examples in the issue, then compare them with the non-generic SupportsIndex case. The issue is ready for work only once the proposed restriction change and its behavior for subtypes are specified clearly enough to assess.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- devtools
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100