Clean up feature sets and labels flag

[cthoyt]

Summary

This PR removes the redundant re-definition of dictionary functions in the drug feature set and context feature set. It also removes the label flag, which is always true. This PR cleans up the LabeledTriples class to also be more contained. This PR finally also turns on MyPy checks.

• Code passes all tests
• Unit tests provided for these changes
• Documentation and docstrings added for these changes

Changes

• Replace superclass for DrugFeatureSet with UserDict and remove redundant functions
• Replace superclass for ContextFeatureSet with UserDict and remove redundant functions
• Replaced unnecessary abstractions for feature set classes that were never used
• Remove label flag from all classes since it's always true
• Update LabeledTriples class to be more contained (e.g., better pythonic style)
• Turn on MyPy checking in CI

[codecov-commenter]

Codecov Report

Merging #55 (6322506) into main (5dc39bb) will decrease coverage by 0.22%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##             main      #55      +/-   ##
==========================================
- Coverage   97.83%   97.60%   -0.23%     
==========================================
  Files          28       28              
  Lines         739      669      -70     
==========================================
- Hits          723      653      -70     
  Misses         16       16              

Impacted Files	Coverage Δ
chemicalx/pipeline.py	88.70% <ø> (ø)
chemicalx/data/batchgenerator.py	98.30% <100.00%> (-0.06%)	⬇️
chemicalx/data/contextfeatureset.py	100.00% <100.00%> (ø)
chemicalx/data/datasetloader.py	91.02% <100.00%> (-0.55%)	⬇️
chemicalx/data/drugfeatureset.py	100.00% <100.00%> (ø)
chemicalx/data/labeledtriples.py	97.36% <100.00%> (-0.51%)	⬇️
tests/unit/test_batching.py	100.00% <100.00%> (ø)
tests/unit/test_dataset.py	100.00% <100.00%> (ø)
tests/unit/test_datastructures.py	100.00% <100.00%> (ø)
tests/unit/test_models.py	100.00% <100.00%> (ø)

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[benedekrozemberczki]

Thank you @cthoyt looks great!