[2.0 regression] TypeVar with constrains Sub and Super does not accept Sub as a default value

λ cat test.py   
from typing import TypeVar
T = TypeVar("T", int, float)
def f(x: T = 0): ...

λ mypy test.py --no-incremental                       
test.py:3: error: Incompatible default for parameter "x" (default has type "int", parameter has type "T")  [assignment]
Found 1 error in 1 file (checked 1 source file)

Bisects to #21119

This is not specific to int vs float, i.e. not related to promotions. The same reproduces with:

class B: ...
class C(B): ...

S = TypeVar("S", B, C)
c = C()
def g(x: S = c): ...

Anyway, it looks like this exposes pre-existing missing edge case in is_subtype() and there is an easy fix. I will make a PR soon.

Fix type variable with values as a supertype (#21431)

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[2.0 regression] TypeVar with constrains Sub and Super does not accept Sub as a default value #21424

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[2.0 regression] TypeVar with constrains Sub and Super does not accept Sub as a default value #21424

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ilevkivskyi commented on May 7, 2026

ilevkivskyi commented on May 7, 2026

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