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Apply changes as patches to pydantic models.

Project description

pydantic-apply

Installation

Just use pip install pydantic-apply to install the library.

Note: pydantic-apply is compatible with pydantic version 2.x on Python 3.10, 3.11, 3.12 and 3.13. This is also ensured running all tests on all those versions using tox.

About

With pydantic-apply you can apply changes to your pydantic models by using the ApplyModelMixin it provides:

import pydantic

from pydantic_apply import ApplyModelMixin


class Something(ApplyModelMixin, pydantic.BaseModel):
    name: str
    age: int


obj = Something(name='John Doe', age=42)
obj.model_apply({
    "age": 43,
})
assert obj.age == 43

As the apply data you may pass any dictionary or other pydanic object as you wish. pydantic objects will be converted to dict's when being applied - but will only use fields that where explicitly set on the model instance. Also note that .apply() will ignore all fields not present in the model, like the model constructor would.

Nested models

pydantic-apply will also know how to apply changes to nested models. If those models are by themself subclasses of ApplyModelMixin it will call apply() on those fields as well. Otherwise the whole attribute will be replaced.

Apply changes when using validate_assignment

When your models have validate_assignment enabled it may become tricky to apply changes to the model. This is due to the fact that you only can assign fields once at a time. But with validate_assignment enabled this means each field assignment will trigger its own validation and this validation might fail as the model state is not completely changes and thus in a "broken" intermediate state.

pydantic-apply will take care of this issue and disable the validation for each assignment while applying the changes. It will also ensure the resulting object will still pass the validation, so you don't have to care about this case at all.

Contributing

If you want to contribute to this project, feel free to just fork the project, create a dev branch in your fork and then create a pull request (PR). If you are unsure about whether your changes really suit the project please create an issue first, to talk about this.

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