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.

[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]

Thanks! Some things still need attention.

[carljm]

CI says conformance results need updating; can you do that and then re-request review?

[carljm]

Thank you! I pushed a few additional small changes (in separate commits so you can review each change if you like) -- this now looks good to me.

The most notable change is that I found three more places where the conformance suite used an implicitly-invariant ParamSpec in a location where it should be contravariant; thus a compliant checker should error on those uses, per the current spec / conformance suite. Fixing these involved a choice between unpalatable options:

1. The most obvious fix is to make those ParamSpecs explicitly contravariant=True, but this errors on four type checkers (mypy, pyright, zuban, pyrefly) which don't yet allow ParamSpecs to use that argument, making those type checkers fail on conformance tests that aren't really related to ParamSpec variance.
2. Another option is to define those ParamSpecs using PEP 695 syntax, which automatically opts into inferred variance, and allows those tests to stay focused on their core purpose. Unfortunately this seems to expose a crash in pycroscope.

I've gone with option (2) for now. @JelleZijlstra let me know if you are OK with landing this for now, would like to propose another alternative, or would like time to fix the pycroscope crash before we land this.

[JelleZijlstra]

Let's land it, I think I need to do a round of fixing bugs in pycroscope :)