mirror of
https://github.com/kennethreitz/pydantic.git
synced 2026-06-05 23:00:18 +00:00
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
49 lines
1.3 KiB
Markdown
49 lines
1.3 KiB
Markdown
Pydantic models work with [mypy](http://mypy-lang.org/) provided you use the annotation-only version of
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required fields:
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```py
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{!.tmp_examples/mypy_main.py!}
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```
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You can run your code through mypy with:
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```bash
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mypy \
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--ignore-missing-imports \
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--follow-imports=skip \
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--strict-optional \
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pydantic_mypy_test.py
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```
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If you call mypy on the example code above, you should see mypy detect the attribute access error:
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```
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13: error: "Model" has no attribute "middle_name"
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```
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## Strict Optional
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For your code to pass with `--strict-optional`, you need to to use `Optional[]` or an alias of `Optional[]`
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for all fields with `None` as the default. (This is standard with mypy.)
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Pydantic provides a few useful optional or union types:
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* `NoneStr` aka. `Optional[str]`
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* `NoneBytes` aka. `Optional[bytes]`
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* `StrBytes` aka. `Union[str, bytes]`
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* `NoneStrBytes` aka. `Optional[StrBytes]`
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If these aren't sufficient you can of course define your own.
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## Mypy Plugin
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Pydantic ships with a mypy plugin that adds a number of important pydantic-specific
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features to mypy that improve its ability to type-check your code.
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See the [pydantic mypy plugin docs](../mypy_plugin.md) for more details.
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## Other pydantic interfaces
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Pydantic [dataclasses](dataclasses.md) and the [`validate_assignment` decorator](validation_decorator.md)
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should also work well with mypy.
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