Samuel Colvin
6914410f38
* starting validation_decorator * correct skip_pre_38 * fix coverage and type hints * mypy tests and move to class based decorator * 3.6 fix, prevent duplicate github actions * correct py 3.6 check * better errors * cleaner field names for args and kwargs * add change and comments * starting docs * back to 3.7 for docs * docs * bump * add async example and fix print indents * allow type annotations as strings * python 3.8 in docs
1.3 KiB
Pydantic models work with mypy provided you use the annotation-only version of required fields:
{!.tmp_examples/mypy_main.py!}
You can run your code through mypy with:
mypy \
--ignore-missing-imports \
--follow-imports=skip \
--strict-optional \
pydantic_mypy_test.py
If you call mypy on the example code above, you should see mypy detect the attribute access error:
13: error: "Model" has no attribute "middle_name"
Strict Optional
For your code to pass with --strict-optional, you need to to use Optional[] or an alias of Optional[]
for all fields with None as the default. (This is standard with mypy.)
Pydantic provides a few useful optional or union types:
NoneStraka.Optional[str]NoneBytesaka.Optional[bytes]StrBytesaka.Union[str, bytes]NoneStrBytesaka.Optional[StrBytes]
If these aren't sufficient you can of course define your own.
Mypy Plugin
Pydantic ships with a mypy plugin that adds a number of important pydantic-specific features to mypy that improve its ability to type-check your code.
See the pydantic mypy plugin docs for more details.
Other pydantic interfaces
Pydantic dataclasses and the validate_assignment decorator
should also work well with mypy.