How to ignore invalid values when creating model instance

Given a sample model:

from pydantic import BaseModel
from typing import Optional

class Foo(BaseModel):
     age: Optional[int]
     name: Optional[str]

I want my model to digest but ignore invalid values to receive an instance in any case. For example, Foo(age="I", name="Jim") should (instead of raising a ValidationError) automatically discard the value for the age field and result Foo(age=None, name='Jim').

I could manually loop over the ValidationErrors and drop the corresponding data or loop over the values and use validate_assignment, but I was thinking I am missing something built-in.

Pydantic 2.12+

In recent versions of Pydantic (I tested on 2.12.3) the __init_subclass__ hack described in the top answer is not necessary when validating all fields of the model.

Here's a variation of that approach that uses @field_validator('*', mode='wrap') to validate all fields:

from typing import Any
from pydantic import BaseModel, ValidationError, ValidatorFunctionWrapHandler, field_validator

class ForgivingModel(BaseModel):
    age: int | None
    name: str | None

    @field_validator('*', mode='wrap')
    @classmethod
    def ignore_invalid(cls, value: Any, handler: ValidatorFunctionWrapHandler) -> Any:
        try:
            return handler(value)
        except ValidationError as e:
            return handler(None)

res = ForgivingModel.model_validate({ "age": "Invalid age", "name": "Bob" })
print(res) # age=None name='Bob'

Pydantic docs

Note that in this version, instead of just returning None from validator, we invoke handler(None). This way, only optional fields are ignored. Invalid required values will still raise ValidationError.