feat: enable template histogram creation and collection to accept list of tasks

[alexander-held]

This updates the templates.build, templates.collect, and templates.postprocess implementations to accept a list of templates to produce via a new template_list keyword argument. The full list can be obtained via route.required_templates. By default, all templates will still be processed.

This allows users to parallelize the template histogram production / collection, partially addressing #401. An example of this would be the following:

from dask.distributed import Client, LocalCluster, wait

def produce_single_template(template):
    cabinetry.templates.build(config, template_list=[template])

template_list = cabinetry.route.required_templates(config)

with LocalCluster(n_workers=2) as cluster:
    client = Client(cluster)
    wait(client.map(produce_single_template, template_list))

compared to the non-parallelized version, which is unchanged:

cabinetry.templates.build(config)

breaking change:

• renamed route.apply_to_all_templates to route.apply_to_templates and changed signature: now takes a list of tasks, which can be generated by route.required_templates

* templates.build, templates.collect, and templates.postprocess now accept a list of tasks
* breaking change: route. apply_to_all_templates renamed to route.apply_to_templates
* breaking change: route.apply_to_templates now requires a list of tasks as argument

[alexander-held]

This will require a different approach to handle remote workers without access to a shared filesystem. To handle this, histograms would have to be passed back and saved at the head node. The current API does not surface the call to utils._name_and_save, which is quite deep inside internal APIs.

Currently route.apply_to_templates does generic function execution. This might have to be changed to support handling return values and passing those back to the higher level, e.g. templates.build for saving. The downside of this is that saving would only happen (in the non-parallel version) after all templates are constructed (and passed back as histograms).

to-do / think about:

• is writing at the very end maybe be a problem if some late templates crash
• memory (or other) issues from keeping all histograms in memory?
• writing only once at the very end means all histograms can easily be written into a single file (this is a bigger refactor)