[Guido]

> What would be an example of a substitution that's too complex to do?

We also need to remember the dreaded arbitrary-length tuple. For example, I think it should be the case that:

```python
T = TypeVar('T')
Ts = TypeVarTuple('Ts')
class C(Generic[*Ts]): pass
Alias = C[T, *Ts]
Alias2 = Alias[*tuple[int, ...]]
# Alias2 should be C[int, *tuple[int, ...]]
```

Ok, this is a bit of a silly example, but if we're committing to evaluating substitutions correctly, we should probably make even this kind of example behave correctly so that users who accidentally do something silly can debug what's gone wrong.

[Serhiy]

> A repr can be less readable.

Definitely true.

> It will break equality comparison and hashing. Good bye caching.

Huh, I didn't know about this one. Fair enough, this is totally a downside.

> What about __origin__, __parameters__, __args__? How will they be calculated?

This could admittedly be thorny. We'd have to think it through carefully. Admittedly also a downside.

> It can break code which uses annotations for something. For example it can break dataclasses.

Oh, also interesting - I didn't know about this one either. Could you give an example?

> The first case will be practically fixed by GH 32030 after chenging the grammar to allow unpacking in index tuple: A[*B].

We actually deliberately chose not to unpack concrete tuple types - see the description of https://github.com/python/cpython/pull/30398, under the heading 'Starred tuple types'. (If you see another way around it, though, let me know.)

> Two other cases will be fixed by GH 32031. It does not require any C code.

I'm also not sure about this one; disallowing unpacked TypeVarTuples in argument lists to generic aliases completely (if I've understood right?) seems like too restrictive a solution. I can imagine there might be completely legitimate cases where the ability to do this would be important. For example:

```python
DType = TypeVar('DType')
Shape = TypeVarTuple('Shape')
class Tensor(Generic[DType, *Shape]): ...
Uint8Tensor = Tensor[uint8, *Shape]
Unit8BatchTensor = Uint8Tensor[Batch, *Shape]
```

> Note that the alternative proposition is even more lenient to errors.

True, but at least it's predictably lenient to errors - I think the repr makes it very clear that "Woah, you're doing something advanced here. You're on your own!" I think it better fits the principle of least astonishment to have something that consistently lets through all errors of a certain class than something that sometimes catches errors and sometimes doesn't.