On Python 3.11 pydantic's use of dataclass_transform is incorrect

[erictraut]

Initial Checks

• I have searched GitHub for a duplicate issue and I'm sure this is something new
• I have searched Google & StackOverflow for a solution and couldn't find anything
• I have read and followed the docs and still think this is a bug
• I am confident that the issue is with pydantic (not my code, or another library in the ecosystem like FastAPI or mypy)

Description

Pydantic uses PEP 681's dataclass_transform for compatibility with static type checkers. One of the features described in PEP 681 is the ability to describe a set of custom "field specifier" classes. In an early version of PEP 681, these were specified using a parameter named field_descriptors, but based on feedback the parameter name was changed to field_specifiers for the final version of the PEP. Pydantic is still using the (now obsolete) parameter name.

See microsoft/pyright#3912 for details.

Example Code

No response

Python, Pydantic & OS Version

Python 3.11
Pydantic 1.10.2

Affected Components

• Compatibility between releases
• Data validation/parsing
• Data serialization - .dict() and .json()
• JSON Schema
• Dataclasses
• Model Config
• Field Types - adding or changing a particular data type
• Function validation decorator
• Generic Models
• Other Model behaviour - construct(), pickling, private attributes, ORM mode
• Settings Management
• Plugins and integration with other tools - mypy, FastAPI, python-devtools, Hypothesis, VS Code, PyCharm, etc.

[samuelcolvin]

Thanks so much, will fix.

[samuelcolvin]

will be fixed in #4501.

[samuelcolvin]

ops, cherry-picking to main closed this.

[erictraut]

@samuelcolvin, thanks for the quick fix!

Currently there are relatively few pydantic + pyright users who are on Python 3.11, but that number will increase as 3.11 approaches release. I could put some temporary special-case hackery in place within pyright to work around this issue, but I'd prefer not to do this if it can be helped. It looks like you release new versions of pydantic pretty frequently (ever week or so). I think it's therefore safe to just wait for your next release and tell developers to upgrade to it. Let me know if you have concerns with that plan.

[samuelcolvin]

A patch release for v1.10 (the first pydantic version which supports 3.11) will be out in the next few days I would guess, so no need.

I've also fixed it on main, so it'll be correct in v2.

[samuelcolvin]

thanks for letting me know about this, on this occasion the fix was very simple.