Accumulate run signals with scoped labels not objects

[liamhuber]

The scoped label will always be unique, so just store that.

The point is that as we move towards storage and serialization, this gives one less complex object that needs to live on the node.

Right now I lean towards restoring graphs by re-executing from the top, but just not actually re-running nodes who have the same input as they had at their last execution (optional (for slow nodes), evaluated by hash comparison). In that case, we don't need to reload this data as the set will get re-populated at run-time. However, IMO it doesn't hurt to have it serialized, and it will be necessary for finding graph state if we wind up taking a different path to reloading.

[github-actions]

👈 Launch a binder notebook on branch pyiron/pyiron_workflow/store_scoped_labels

[codacy-production]

Coverage summary from Codacy

See diff coverage on Codacy

Coverage variation	Diff coverage
✅ +0.00% (target: -1.00%)	✅ 100.00%

Coverage variation details

	Coverable lines	Covered lines	Coverage
Common ancestor commit (46a5534)	2596	2218	85.44%
Head commit (651c2bd)	2596 (+0)	2218 (+0)	85.44% (+0.00%)

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Diff coverage details

	Coverable lines	Covered lines	Diff coverage
Pull request (#173)	3	3	100.00%

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[coveralls]

Pull Request Test Coverage Report for Build 7618377654

• 0 of 0 changed or added relevant lines in 0 files are covered.
• No unchanged relevant lines lost coverage.
• Overall coverage increased (+0.006%) to 90.31%

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Totals
Change from base Build 7617353667:	0.006%
Covered Lines:	4697
Relevant Lines:	5201

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💛 - Coveralls