Use partial functions in flows to increase user flexibility in setting job attributes (e.g. executor)

[Andrew-S-Rosen]

Continuation of #1322.

Challenges:

• Mainly Dask, which does not play nicely when functools.partial() is applied to a Delayed object. See Applying functools.partial() to a @delayed-decorated function changes the execution behavior dask/dask#10707. There is now a workaround.
• Also there is a minor issue with dynamic switching of Covalent executors, but there is a workaround. See Dynamically modifying the .electron_object.executor from an imported electron does not always work as expected AgnostiqHQ/covalent#1889

Remaining issue:

Need to be able to parallelize the following code on Dask.

from dask.distributed import Client
from ase.build import bulk
from quacc.recipes.emt.slabs import bulk_to_slabs_flow
from functools import partial

client = Client()

atoms = bulk("Cu")
delayed = bulk_to_slabs_flow(atoms)
result = client.gather(client.compute(delayed))

Hint: To monitor, set "logfile": "".

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Comparison is base (9f97088) 98.91% compared to head (98016ef) 98.90%.
Report is 2 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #1359      +/-   ##
==========================================
- Coverage   98.91%   98.90%   -0.01%     
==========================================
  Files          76       76              
  Lines        2951     2934      -17     
==========================================
- Hits         2919     2902      -17     
  Misses         32       32              

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