pydantic
Support `extra` specification on a field-by-field basis
Initial Checks
- [X] I have searched Google & GitHub for similar requests and couldn't find anything
- [X] I have read and followed the docs and still think this feature is missing
Description
I know that we can just ignore the additional fields for the schema. However, I want to specify certain fields that need to be ignored, for example at different resolution levels.
Example.
from pydantic import BaseModel, ConfigDict
class User(BaseModel):
model_config = ConfigDict(skip={'age': 'ignore', 'other': 'ignore'})
name: str
user = User(name='John Doe', age=20, job='writer')
print(user)
#> name='John Doe'
from pydantic import BaseModel, ConfigDict
class User(BaseModel):
model_config = ConfigDict(skip={'age': 'allow', 'other': 'ignore'})
name: str
user = User(name='John Doe', age=20, job='writer')
print(user)
#> name='John Doe' age=20
...
Affected Components
- [ ] Compatibility between releases
- [ ] Data validation/parsing
- [ ] Data serialization -
.model_dump()and.model_dump_json() - [ ] JSON Schema
- [ ] Dataclasses
- [ ] Model Config
- [ ] Field Types - adding or changing a particular data type
- [ ] Function validation decorator
- [ ] Generic Models
- [ ] Other Model behaviour -
model_construct(), pickling, private attributes, ORM mode - [ ] Plugins and integration with other tools - mypy, FastAPI, python-devtools, Hypothesis, VS Code, PyCharm, etc.
Hi @ArtemIsmagilov,
I could also see the API getting tricky, for example, what if someone wants to allow an extra field called other? Perhaps we could implement something like
ConfigDict(extra=Extra(forbid={...}, ignore={...}, allow={...}))
where you could set wildcard * values to specify the extra behavior for all remaining unspecified fields.
In the meantime, you can use a custom validator:
from typing import Any
from pydantic import BaseModel, ConfigDict, model_validator
class User(BaseModel):
model_config = ConfigDict(extra='allow')
name: str
@model_validator(mode='before')
@classmethod
def check_extras(cls, data: Any) -> Any:
if isinstance(data, dict):
allowed_keys = [*cls.model_fields.keys(), 'age']
return {k: v for k, v in data.items() if k in allowed_keys}
return data
user = User(name='John Doe', age=20, job='writer')
print(repr(user))
#> User(name='John Doe', age=20)
@ArtemIsmagilov,
I haven't yet added it to a milestone. It'll require pretty significant changes in pydantic-core.
I'd be happy to support development on this front with PR reviews, etc if anyone is interested in taking this on, but I don't think we'll pick this up until we've addressed some other more pressing things like performance improvements, etc.