parameter specification/type variable tuple variance

[KotlinIsland]

discussion: https://discuss.python.org/t/parameter-specifications-should-have-variance/106452

• support in basedpyright variance for parameter specification and type variable tuples DetachHead/basedpyright#1771
• support in pycharm: JetBrains/intellij-community@7196a70
• cpython tvt variance: gh-148207: add additional keywords to typing.TypeVarTuple cpython#148212
• typeshed: typing.TypeVarTuple: add bound/variance properties from 3.15 typeshed#15670 / Add Python 3.15 typing updates typeshed#15725
• typing_extensions: Type variable tuple variance typing_extensions#741
• typing-council: spec change: support variance on parameter specification and type variable tuple typing-council#59

[JelleZijlstra]

I like adding this if we can get it specified nicely, but this PR is not ready; the proposed test is incorrect.

Also, https://typing.python.org/en/latest/spec/generics.html#paramspec-variables still says variance on ParamSpec is unsupported; this should be updated.

I'd also like to see an implementation in at least one type checker, even if only as a draft PR, so we can be confident this is something that can be feasibly implemented.

[davidhalter]

I personally would also like to see tests added for param spec variance inference, since that would probably need to be supported as well.

[JelleZijlstra]

The test cases do have variance inference, though as I noted some of the cases are wrong. But it would probably be useful to have a few more cases, and I'd recommend putting the tests for paramspec variance in their own file so we can track type checker support more precisely.

[KotlinIsland]

I'd also like to see an implementation in at least one type checker

I have wip support in PyCharm, but I could also add it to basedpyright

it was very straightforward to implement

[davidhalter]

The test cases do have variance inference, though as I noted some of the cases are wrong. But it would probably be useful to have a few more cases, and I'd recommend putting the tests for paramspec variance in their own file so we can track type checker support more precisely.

Oh right, sorry I didn't see them, because I thought they would be in a different file. I'm also very much +1 on putting those tests into a different file (for example generics_paramspec_variance.py).

[KotlinIsland]

support has landed in pycharm and cpython

[JelleZijlstra]

https://typing.python.org/en/latest/spec/generics.html#paramspec-variables stills says that we don't support variance in ParamSpec, that should be fixed in this PR.

[JelleZijlstra]

Also can you open an issue on python/typing-council asking for a formal pronouncement?

[KotlinIsland]

python/typing-council#59

[JelleZijlstra]

Noticed some more issues:

• generics_typevartuple_basic.py still has a line Ts1 = TypeVarTuple("Ts1", covariant=True) # E. But of course that's legal now. I'd delete the line and leave all variance testing to the new file generics_typevartuple_variance.py.
• The description of the variance inference algorithm says "In the upper specialized class, specialize the target type parameter with an object instance". But that doesn't make sense for ParamSpec and TypeVarTuple. I think TypeVarTuple should instead be specialized with *tuple[object, ...]. For ParamSpec perhaps Callable[..., object] is right but not 100% sure.
• The way the tests are written produces some incidental errors, like from ty generics_paramspec_variance.py:28:23: error[empty-body] Function always implicitly returns `None`, which is not assignable to return type `(...) -> Unknown` and mypy generics_typevartuple_variance.py:18: error: Missing return statement [empty-body]. Should add something like raise NotImplementedError.

[KotlinIsland]

Callable[..., object] is right but not 100% sure.

not Callable, and not ..., as this is the gradual form. but (*object, **object), which is a non-denotable psuedo representation of the widest value for a parameter specification

[JelleZijlstra]

I don't think that's right. The form we want here should be a supertype of every other possible value, and something like a one-parameter callable is not a subtype of (*: object, **: object).

[AlexWaygood]

In ty we have a type that we spell as Top[Callable[..., object]] in ty's type display (a fully static type describing the infinite union of all possible Callable types). It's not representable using standard Python notation currently.

[davidhalter]

I like the general approach. I think it would also be useful to have at least one type checker with a proper implementation of this new feature.

[KotlinIsland]

proper implementation of this new feature.

see the mr description, it's implemented in pycharm and basedpyright

[jorenham]

The lack of co/contra variance for TypeVarTuples has caused problems for me on several occasions in the past. So thanks for patching this hole in the spec!

The changes to the variance algorithm also look like the way to go. It's too bad we don't have a general notion of the "top signature" like we do for the general top type (object) and the top product type (tuple[object, ...]). But I expect that the way you informally describe it here will be understood just fine by anyone that needs to know.

[KotlinIsland]

@carljm good to review now

[carljm]

The direction here remains correct IMO, but I think there are some updates needed.

[carljm]

All of the ParamSpec specializations here have one required positional parameter. Could we add cases involving keyword-only or positional-only parameters, parameter names, defaults, and differing callable arities, perhaps also Concatenate? Otherwise an implementation that compares only a tuple of parameter types could pass without implementing actual signature assignability.

[KotlinIsland]

without the ability to denote any of these forms (apart from arity), i'm having trouble find a way to test them

[KotlinIsland]

okay, i think i managed to get some of these cases using an invariant box

[carljm]

What should the "dummy type instance" be when one of the other parameters is a TypeVarTuple or ParamSpec? An ordinary dummy class isn't a valid specialization for either kind. Could we spell out kind-compatible substitutions and cover a mixed example such as:

class Mixed[T, *Ts, **P]:
    def f(self, x: T, /, *args: P.args, **kwargs: P.kwargs) -> tuple[*Ts]: ...

I would expect T and P to be contravariant and Ts to be covariant, independently.