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Mypy

Pydantic works well with mypy right out of the box.

However, Pydantic also ships with a mypy plugin that adds a number of important Pydantic-specific features that improve its ability to type-check your code.

For example, consider the following script:

from datetime import datetime
from typing import Optional

from pydantic import BaseModel


class Model(BaseModel):
    age: int
    first_name = 'John'
    last_name: Optional[str] = None
    signup_ts: Optional[datetime] = None
    list_of_ints: list[int]


m = Model(age=42, list_of_ints=[1, '2', b'3'])
print(m.middle_name)  # not a model field!
Model()  # will raise a validation error for age and list_of_ints

Without any special configuration, mypy does not catch the missing model field annotation and errors about the list_of_ints argument which Pydantic parses correctly:

15: error: List item 1 has incompatible type "str"; expected "int"  [list-item]
15: error: List item 2 has incompatible type "bytes"; expected "int"  [list-item]
16: error: "Model" has no attribute "middle_name"  [attr-defined]
17: error: Missing named argument "age" for "Model"  [call-arg]
17: error: Missing named argument "list_of_ints" for "Model"  [call-arg]

But with the plugin enabled, it gives the correct errors:

9: error: Untyped fields disallowed  [pydantic-field]
16: error: "Model" has no attribute "middle_name"  [attr-defined]
17: error: Missing named argument "age" for "Model"  [call-arg]
17: error: Missing named argument "list_of_ints" for "Model"  [call-arg]

With the pydantic mypy plugin, you can fearlessly refactor your models knowing mypy will catch any mistakes if your field names or types change.

Note that mypy already supports some features without using the Pydantic plugin, such as synthesizing a __init__ method for Pydantic models and dataclasses. See the mypy plugin capabilities for a list of additional features.

The Pydantic mypy plugin is tested against the latest mypy version. Older versions might work but won’t be tested.

Enabling the Plugin

To enable the plugin, just add pydantic.mypy to the list of plugins in your mypy config file:

[mypy]
plugins = pydantic.mypy

See the plugin configuration for more details.

Mypy plugin capabilities

Generate a __init__ signature for Pydantic models

  • Any required fields that don’t have dynamically-determined aliases will be included as required keyword arguments.
  • If the validate_by_name model configuration value is set to True, the generated signature will use the field names rather than aliases.
  • The init_forbid_extra and init_typed plugin configuration values can further fine-tune the synthesized __init__ method.

Generate a typed signature for model_construct

  • The model_construct method is an alternative to model validation when input data is known to be valid and should not be parsed (see the documentation). Because this method performs no runtime validation, static checking is important to detect errors.

Support for frozen models

  • If the frozen configuration is set to True, you will get an error if you try mutating a model field (see faux immutability)

Respect the type of the Field’s default and default_factory

  • Field with both a default and a default_factory will result in an error during static checking.
  • The type of the default and default_factory value must be compatible with the one of the field.

Warn about the use of untyped fields

  • While defining a field without an annotation will result in a runtime error, the plugin will also emit a type checking error.

Prevent the use of required dynamic aliases

See the documentation of the warn_required_dynamic_aliases plugin configuration value.

Configuring the Plugin

To change the values of the plugin settings, create a section in your mypy config file called [pydantic-mypy], and add any key-value pairs for settings you want to override.

A configuration file with all plugin strictness flags enabled (and some other mypy strictness flags, too) might look like:

[mypy]
plugins = pydantic.mypy

follow_imports = silent
warn_redundant_casts = True
warn_unused_ignores = True
disallow_any_generics = True
no_implicit_reexport = True
disallow_untyped_defs = True

[pydantic-mypy]
init_forbid_extra = True
init_typed = True
warn_required_dynamic_aliases = True

init_typed

Because Pydantic performs data conversion by default, the following is still valid at runtime:

class Model(BaseModel):
    a: int


Model(a='1')

For this reason, the plugin will use Any for field annotations when synthesizing the __init__ method, unless init_typed is set or strict mode is enabled on the model.

init_forbid_extra

By default, Pydantic allows (and ignores) any extra provided argument:

class Model(BaseModel):
    a: int = 1


Model(unrelated=2)

For this reason, the plugin will add an extra **kwargs: Any parameter when synthesizing the __init__ method, unless init_forbid_extra is set or the extra is set to 'forbid'.

warn_required_dynamic_aliases

Whether to error when using a dynamically-determined alias or alias generator on a model with validate_by_name set to False. If such aliases are present, mypy cannot properly type check calls to __init__. In this case, it will default to treating all arguments as not required.