pydantic-partial

Installation

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

About

Create partial models from your normal pydantic models. Partial models will allow some or all fields to be optional and thus not be required when creating the model instance.

Partial models can be used to support PATCH HTTP requests where the user only wants to update some fields of the model and normal validation for required fields is not required. It may also be used to have partial response DTOs where you want to skip certain fields, this can be useful in combination with exclude_none. It is - like shown in these examples - intended to be used with API use cases, so when using pydantic with for example FastAPI.

Disclaimer: This is still an early release of pydantic-partial. Things might change in the future. PR welcome. ;-)

Usage example

pydantic-partial provides a mixin to generate partial model classes. The mixin can be used like this:

import pydantic
from pydantic_partial import PartialModelMixin

# Something model, then can be used as a partial, too:
class Something(PartialModelMixin, pydantic.BaseModel):
    name: str
    age: int


# Create a full partial model
FullSomethingPartial = Something.as_partial()
FullSomethingPartial(name=None, age=None)

Without using the mixin

You also may create partial models without using the mixin:

import pydantic
from pydantic_partial import create_partial_model

# Something model, without the mixin:
class Something(pydantic.BaseModel):
    name: str
    age: int


# Create a full partial model
FullSomethingPartial = create_partial_model(Something)
FullSomethingPartial(name=None, age=None)

Only changing some fields to being optional

pydantic-partial can be used to create partial models that only change some of the fields to being optional. Just pass the list of fields to be optional to the as_partial() or create_partial_model() function.

import pydantic
from pydantic_partial import create_partial_model

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

# Create a partial model only for the name attribute
FullSomethingPartial = create_partial_model(Something, 'name')
FullSomethingPartial(name=None)
# This would still raise an error: FullSomethingPartial(age=None)

Recursive partials

Partial models can be created changing the field of all nested models to being optional, too.

from typing import List

import pydantic
from pydantic_partial import PartialModelMixin, create_partial_model

class InnerSomething(PartialModelMixin, pydantic.BaseModel):
    name: str

class OuterSomething(pydantic.BaseModel):
    name: str
    things: List[InnerSomething]

# Create a full partial model
RecursiveOuterSomethingPartial = create_partial_model(OuterSomething, recursive=True)
RecursiveOuterSomethingPartial(things=[
    {},
])

Note: The inner model MUST extend the PartialModelMixin mixin. Otherwise pydantic-partial will not be able to detect which fields may allow to being converted to partial models.

Also note: My recommendation would be to always create such recursive partials by creating partials for all the required models and then override the fields on you outer partial model class. This is way more explicit.

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.