def _make_output_class(f, json_encoders=None):
return_annot = typing.get_type_hints(f).get('return', inspect._empty)
if return_annot is inspect._empty:
raise TypeError(
f"Unable to construct a Task from function '{f.__qualname__}': "
"the annotation for the return value is missing. "
"This may be a type, or a subclass of TaskOutput.")
json_encoders_arg = json_encoders if json_encoders else {}
class Config: # NB: MIGHT NOT be used if `f` includes a 'return' annotation
json_encoders = {
**json_encoders_arg,
**smttask_json_encoders,
**base.TaskOutput.Config.json_encoders
}
if lenient_issubclass(return_annot, base.TaskOutput):
# Nothing to do
Outputs = return_annot
# Add the json_encoders to the Output type, but only if they were not
# given explicitely in the Output type.
if json_encoders:
if hasattr(Outputs, 'Config') and not hasattr(
Outputs.Config, 'json_encoders'):
Outputs.Config.json_encoders = Config.json_encoders
elif not hasattr(Outputs, 'Config'):
Outputs.Config = Config
else:
assert isinstance(return_annot, (type, typing._GenericAlias))
# A bare annotation does not define a variable name; we set it to the
# empty string (i.e., the variable is only identified by the task name)
Outputs = ModelMetaclass(f"{f.__qualname__}.Outputs",
(base.TaskOutput, ), {
'__annotations__': {
"": return_annot
},
'Config': Config
})
# Set correct module; workaround for https://bugs.python.org/issue28869
Outputs.__module__ = f.__module__
# update_forward_refs required for 3.9+ style annotations
Outputs.update_forward_refs()
return Outputs
def _make_input_class(f, json_encoders=None):
defaults = {}
annotations = {}
json_encoders_arg = json_encoders if json_encoders else {}
class Config:
# Override the lenience of the base TaskInput class and only allow expected arguments
extra = 'forbid'
json_encoders = {
**json_encoders_arg,
**smttask_json_encoders,
**base.TaskInput.Config.json_encoders
}
for nm, param in inspect.signature(f).parameters.items():
if param.annotation is inspect._empty:
raise TypeError(
"Constructing a Task requires that all function arguments "
f"be annotated. Offender: argument '{nm}' of '{f.__qualname__}'."
)
annotation = param.annotation
if isinstance(annotation, str):
# HACK to resolve forward refs
globalns = sys.modules[f.__module__].__dict__.copy()
annotation = evaluate_forwardref(ForwardRef(annotation),
globalns=globalns,
localns=None)
annotations[nm] = Union[base.Task, annotation]
if param.default is not inspect._empty:
defaults[nm] = param.default
Inputs = ModelMetaclass(f"{f.__qualname__}.Inputs", (base.TaskInput, ), {
**defaults, 'Config': Config,
'__annotations__': annotations
})
# Set correct module; workaround for https://bugs.python.org/issue28869
Inputs.__module__ = f.__module__
# update_forward_refs required for 3.9+ style annotations
# DEVNOTE: When one inspects Inputs.__fields__, some types may still contain 'ForwardRef'
# I don't know why that is, but checking Inputs.__fields__[field name].__args__[ForwardRef index].__forward_evaluated__ should still be True
# and [...].__forward_value__ should be the expected type
Inputs.update_forward_refs()
return Inputs