It's pydantic, they're verifying types and syntax, those don't require the stdlib. Type hints, syntax checks, likely logical issues,etc.. static type checking is good with that, but LLMs can take to the next level where they analyze the intended data flow and find logical bugs, or good syntax and typing but not the intended syntax.

For example, incorrect levels of indentation. Let me use dots instead of space because of HN formatting:

for key,val in mydict.items():

..if key == "operation":

....logging.info("Executing operation %s",val)

..if val == "drop_table":

....self.drop_table()

This uses good syntax, and I the logging part is not in the stdlib, so I assume it would ignore it or replace it with dummy code? That shouldn't prevent it from analyzing that loop and determining that the second if-block was intended to be under the first, and the way it is written now, the key check isn't done.

In other words, if you don't want to do validate proper stdlib/module usage, but proper __Python__ usage, this makes sense. Although I'm speculating on exactly what they're trying to do.

EDIT: I think I my speculation was wrong, it looks like they might have developed this to write code for pydantic-ai: https://github.com/pydantic/pydantic-ai , i'll leave the comment above as-is though, since I think it would still be cool to have that capability in pydantic.