Apply changes as patches to pydanic models.
Project description
pydantic-apply
Installation
Just use pip install pydantic-apply
to install the library.
Note: pydantic-apply
is compatible with pydantic
versions 1.9
, 1.10
and even 2.x
(🥳) on
Python 3.8
, 3.9
, 3.10
and 3.11
. 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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