Is your feature request related to a problem? Please describe.
I'm using pydantic to parse raw data in a dataflow pipeline. This comes with a lot of nested data models where the inner field sometimes will be empty. These will cause error when calling a nested model that does not exist. The current solution is just to use: x = A.B.c if A.B else None similar to the x = A.get("B",{}).get("c") when using dictionaries.

Describe the solution you'd like
I want a flag --default-factory that sets the default value to an empty version of the datamodel:

Hence:
Currently a normal generation gives:

class B_model(BaseModel):
 c = Optional[List]=None
    
class A_model(BaseModel):
 B = Optional[B_model] = None

This works with input json {"A":{"B": {"c":[]} }} but I could also get {"A":None}.

class B_model(BaseModel):
 c = Optional[List]= None
    
class A_model(BaseModel):
 B = Optional[B_model] = Field(default_factory=B_model)

By then complementing this solution with a model_validator:

  @model_validator(mode="before")
  def default_children(cls, values):
      for key, value in values.items():
          if value is None and (default_factory := getattr(cls.model_fields[key], "default_factory")):
              values[key] = default_factory()
      return values

I'm able to safely call anything which will just return a None if the field does not exist.

Describe alternatives you've considered
The current solution is just to use: x = A.B.c if A.B else None similar to the x = A.get("B",{}).get("c") when using dictionaries. One could also overwrite the pydantic class methods to do something similar or use Field validators.