Instantiates all ParametrizedClass components and subcomponents of a given model.
Recursively calls model.instantiate() on all ParameterizedConfigClass instances under
the model, resulting in a new model which follows the same general structure as
the given model, but possibly containing totally different properties and methods.
Note that this method does a depth-first traversal of the model tree to to
instantiate leaf nodes first. Traversing breadth-first would result in new pydantic
models attempting to call the init method of child models, which is not valid
because the child models are ParameterizedConfigClass instances. Traversing
depth-first allows us to first transform child models into the appropriate type
using the classname of the ParameterizedConfigClass.
This method is primarily used to instantiate a Pipeline subclass and all of its
properties from a yaml pipeline config file, but it can be applied to any other
pydantic model.
Parameters:
| Name |
Type |
Description |
Default |
model |
Any
|
The object to recursively instantiate.
|
required
|
Returns:
| Name | Type |
Description |
Any |
Any
|
The recursively-instantiated object.
|
Source code in tsdat/config/utils/recursive_instantiate.py
| def recursive_instantiate(model: Any) -> Any:
"""---------------------------------------------------------------------------------
Instantiates all ParametrizedClass components and subcomponents of a given model.
Recursively calls model.instantiate() on all ParameterizedConfigClass instances under
the model, resulting in a new model which follows the same general structure as
the given model, but possibly containing totally different properties and methods.
Note that this method does a depth-first traversal of the model tree to to
instantiate leaf nodes first. Traversing breadth-first would result in new pydantic
models attempting to call the __init__ method of child models, which is not valid
because the child models are ParameterizedConfigClass instances. Traversing
depth-first allows us to first transform child models into the appropriate type
using the classname of the ParameterizedConfigClass.
This method is primarily used to instantiate a Pipeline subclass and all of its
properties from a yaml pipeline config file, but it can be applied to any other
pydantic model.
Args:
model (Any): The object to recursively instantiate.
Returns:
Any: The recursively-instantiated object.
---------------------------------------------------------------------------------"""
# Case: ParameterizedConfigClass. Want to instantiate any sub-models then return the
# class with all sub-models recursively instantiated, then statically instantiate
# the model. Note: the model is instantiated last so that sub-models are only
# processed once.
if isinstance(model, ParameterizedConfigClass):
fields = model.__fields_set__ - {"classname"} # No point checking classname
for field in fields:
setattr(model, field, recursive_instantiate(getattr(model, field)))
model = model.instantiate()
# Case: BaseModel. Want to instantiate any sub-models then return the model itself.
elif isinstance(model, BaseModel):
fields = model.__fields_set__
if "classname" in fields:
raise ValueError(
f"Model '{model.__repr_name__()}' provides a 'classname' but does not"
" extend ParametrizedConfigClass."
)
for field in fields:
setattr(model, field, recursive_instantiate(getattr(model, field)))
# Case: List. Want to iterate through and recursively instantiate all sub-models in
# the list, then return everything as a list.
elif isinstance(model, List):
model = [recursive_instantiate(m) for m in cast(List[Any], model)]
# Case Dict. Want to iterate through and recursively instantiate all sub-models in
# the Dict's values, then return everything as a Dict, unless the dict is meant to
# be turned into a parameterized class, in which case we instantiate it as the
# intended object
elif isinstance(model, Dict):
model = {
k: recursive_instantiate(v) for k, v in cast(Dict[str, Any], model).items()
}
if "classname" in model:
classname: str = model.pop("classname") # type: ignore
_cls = import_string(classname)
return _cls(**model)
return model
|