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 to mypy that improve its ability to type-check your code.
For example, consider the following script:
from datetime import datetime from typing import List, 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 catches one of the errors:
16: error: "Model" has no attribute "middle_name" [attr-defined]
But with the plugin enabled, it catches both:
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.
There are other benefits too! See below for more details.
Using mypy without the plugin¶
You can run your code through mypy with:
mypy \ --ignore-missing-imports \ --follow-imports=skip \ --strict-optional \ pydantic_mypy_test.py
For your code to pass with
--strict-optional, you need to to use
Optional or an alias of
for all fields with
None as the default. (This is standard with mypy.)
Other Pydantic interfaces¶
Mypy Plugin Capabilities¶
Generate a signature for
- Any required fields that don't have dynamically-determined aliases will be included as required keyword arguments.
Config.populate_by_name=True, the generated signature will use the field names, rather than aliases.
Config.extra='forbid'and you don't make use of dynamically-determined aliases, the generated signature will not allow unexpected inputs.
- Optional: If the
init_forbid_extraplugin setting is set to
True, unexpected inputs to
__init__will raise errors even if
- Optional: If the
init_typedplugin setting is set to
True, the generated signature will use the types of the model fields (otherwise they will be annotated as
Anyto allow parsing).
Generate a typed signature for
model_constructmethod is an alternative to
__init__when input data is known to be valid and should not be parsed. Because this method performs no runtime validation, static checking is important to detect errors.
True, you'll get a mypy error if you try to change the value of a model field; cf. faux immutability.
Generate a signature for
- classes decorated with
@pydantic.dataclasses.dataclassare type checked the same as standard Python dataclasses
@pydantic.dataclasses.dataclassdecorator accepts a
configkeyword argument which has the same meaning as the
Respect the type of the
- Field with both a
default_factorywill result in an error during static checking.
- The type of the
default_factoryvalue must be compatible with the one of the field.
Warn about the use of untyped fields¶
- You'll get a mypy error any time you assign a public attribute on a model without annotating its type
- If your goal is to set a ClassVar, you should explicitly annotate the field using typing.ClassVar
Prevent the use of required dynamic aliases¶
- If the
warn_required_dynamic_aliasesplugin setting is set to
True, you'll get a mypy error any time you use a dynamically-determined alias or alias generator on a model with
- This is important because if such aliases are present, mypy cannot properly type check calls to
__init__. In this case, it will default to treating all arguments as optional.
Enabling the Plugin¶
To enable the plugin, just add
pydantic.mypy to the list of plugins in your
mypy config file
(this could be
To get started, all you need to do is create a
mypy.ini file with following contents:
[mypy] plugins = pydantic.mypy
The plugin is compatible with mypy versions
See the plugin configuration docs for more details.
Configuring the Plugin¶
To change the values of the plugin settings, create a section in your mypy config file called
and add any key-value pairs for settings you want to override.
mypy.ini 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 check_untyped_defs = True no_implicit_reexport = True # for strict mypy: (this is the tricky one :-)) disallow_untyped_defs = True [pydantic-mypy] init_forbid_extra = True init_typed = True warn_required_dynamic_aliases = True
mypy>=0.900, mypy config may also be included in the
pyproject.toml file rather than
The same configuration as above would be:
[tool.mypy] plugins = [ "pydantic.mypy" ] follow_imports = "silent" warn_redundant_casts = true warn_unused_ignores = true disallow_any_generics = true check_untyped_defs = true no_implicit_reexport = true # for strict mypy: (this is the tricky one :-)) disallow_untyped_defs = true [tool.pydantic-mypy] init_forbid_extra = true init_typed = true warn_required_dynamic_aliases = true