Handle adding empty optimization data

[glatterf42]

In message_ix, we may iterate over all variables etc of one Scenario (backed by a Run) to add them to another Scenario (backed by another Run), which may include adding empty data ({} or pd.DataFrame()) to them. This should be working already as only the combination of existing and new data are validated.
However, this led to an error for indexsets because adding an empty list violates one of the UniqueConstraints for their underlying tables. So I was adjusting that already and figured the remaining items would also benefit from tests covering this case.
On top of which, I figure we don't need to bother the DB or validate data when adding empty data. This PR avoids that, which should make the code more performant.

NOTE: I'm also using this branch right now for some temporary debug commits.

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 88.7%. Comparing base (f907393) to head (71d71ec).

Additional details and impacted files

@@                         Coverage Diff                          @@
##           enh/make-equation-indexsets-optional    #169   +/-   ##
====================================================================
  Coverage                                  88.6%   88.7%           
====================================================================
  Files                                       223     223           
  Lines                                      8200    8219   +19     
====================================================================
+ Hits                                       7272    7291   +19     
  Misses                                      928     928           

Files with missing lines	Coverage Δ
ixmp4/data/db/optimization/equation/repository.py	98.8% <100.0%> (+<0.1%)	⬆️
ixmp4/data/db/optimization/indexset/repository.py	98.5% <100.0%> (+<0.1%)	⬆️
ixmp4/data/db/optimization/parameter/repository.py	97.0% <100.0%> (+0.2%)	⬆️
ixmp4/data/db/optimization/table/repository.py	98.7% <100.0%> (+<0.1%)	⬆️
ixmp4/data/db/optimization/utils.py	100.0% <100.0%> (ø)
ixmp4/data/db/optimization/variable/repository.py	98.9% <100.0%> (+<0.1%)	⬆️

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