Bug risk: Using customize_funcs() with Dask to update the parameters of a @flow or @subflow

[Andrew-S-Rosen]

Details about the quacc environment

• quacc version: 0.6.10+
• Python version: 3.11

What is the issue?

quacc/src/quacc/wflow_tools/customizers.py

Lines 100 to 135 in fae6393

	def update_parameters(
	func: Callable,
	params: dict[str, Any],
	decorator: Literal["job", "flow", "subflow"] | None = "job",
	) -> Callable:
	"""
	Update the parameters of a (potentially decorated) function.
	Parameters
	----------
	func
	The function to update.
	params
	The parameters and associated values to update.
	decorator
	The decorator associated with `func`.
	Returns
	-------
	Callable
	The updated function.
	"""
	from quacc import SETTINGS, flow, job, subflow
	if decorator and SETTINGS.WORKFLOW_ENGINE == "dask":
	if decorator == "job":
	decorator = job
	elif decorator == "flow":
	decorator = flow
	elif decorator == "subflow":
	decorator = subflow
	func = strip_decorator(func)
	return decorator(partial(func, **params))
	return partial(func, **params)

When calling customize_funcs() with the update_parameters keyword argument, the user can update the parameters of any @job, @flow, or @subflow. In most cases, this is a @job. However, if the object we are updating the parameters of is a @flow or @subflow, it won't be properly updated when using Dask unless we pass the decorator keyword argument to update_parameters which seems very easy to forget.