AliasChoices Unhashable When Comparing Models

[iambroadband]

Initial Checks

• I confirm that I'm using Pydantic V2

Description

While upgrading from Pydantic v2.6.4 to v2.7.0 some of our tests comparing models started failing. My expectation here is that we'd be able to continue comparing models constructed in this way without any issue. The results here do not meet that expectation because we encounter a TypeError

Example Code

from pydantic import AliasChoices, BaseModel, Field

class MyModel(BaseModel):
    data: str
    our_id: str | None = Field(
        default=None,
        validation_alias=AliasChoices("their_id", "theirId", "our_id", "id"),
    )

def test_cardmodel_eq():
    model1 = MyModel.model_construct(data="test data")
    model2 = MyModel.model_construct(data="test data")
    model3 = MyModel.model_construct(data="other data")
    assert model1 == model2
    assert not model1 == model3

Python, Pydantic & OS Version

pydantic version: 2.7.0
pydantic-core version: 2.18.1
pydantic-core build: profile=release pgo=true
install path: /home/broadband/.cache/pypoetry/virtualenvs/scooze-iup8854z-py3.11/lib/python3.11/site-packages/pydantic
python version: 3.11.5 (main, Aug 26 2023, 21:51:13) [GCC 11.3.0]
platform: Linux-5.10.102.1-microsoft-standard-WSL2-x86_64-with-glibc2.35
related packages: fastapi-0.110.1 pydantic-settings-2.2.1 typing_extensions-4.11.0
commit: unknown

[sydney-runkle]

@iambroadband,

Thanks for reporting this! We'll roll a fix out with a patch release early next week!

[sydney-runkle]

Closing this as a dupe of #9216, but will make sure to resolve this in the patch release!

[sydney-runkle]

@iambroadband,

I don't think your test as it stands should pass - model1 and model2 aren't equivalent, unless I'm missing something?

[iambroadband]

@sydney-runkle

I see I have made a typo when writing my example code 🤦🏼I will fix it. It should be fixed now. Even when they should be equivalent this test is failing on a TypeError, but it seems like #9223 is addressing that?

Thank you 🙏 appreciate everything you all do.