cluster builder interface and updated output

[dhavalpatel624624]

Project Robyn

Generated cluster builder interface which will cluster models and updated the clustering_result dataclass for outputs

No testing needed at this point

[alxlyj]

few comments primarily on namings and refactoring for visualization. we can look into getting rid of the older clustering interfaces in our next iteration.

[sumane81]

I asked AI to review the code for me.

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I'll review cluster_builder.py and clustering_results.py focusing on code structure, encapsulation, type safety and proper initialization. Let me analyze each file and suggest improvements.

First, let's examine clustering_results.py:

Key improvements to clustering_results.py:

1. Added frozen=True to make dataclasses immutable
2. Added proper type annotations for all attributes
3. Used field(default_factory=...) for mutable defaults
4. Added comprehensive docstrings
5. Made all dataclasses properly initialized with defaults

Now let's examine cluster_builder.py. This class has multiple responsibilities and should be split up:

Key improvements to cluster_builder.py:

1. Split into specialized classes following Single Responsibility Principle:

   • DataPreprocessor: Handles data preparation
   • ClusterAnalyzer: Performs statistical analysis
   • ConfidenceIntervalCalculator: Calculates confidence intervals
   • ClusterBuilder: Coordinates the overall process

2. Improved encapsulation:

   • Made internal methods private with underscore prefix
   • Added proper type hints
   • Used dataclasses for data structures
   • Protected internal state

3. Better organization:

   • Each class has a single, clear responsibility
   • Methods are focused and cohesive
   • Clear separation of concerns

4. Additional improvements:

   • Added comprehensive docstrings
   • Made method signatures explicit
   • Used proper type annotations throughout
   • Made the code more maintainable and testable

The refactored code is now:

1. More maintainable due to clear separation of concerns
2. More robust with proper type checking
3. Better encapsulated with clear public/private interfaces
4. Easier to test due to smaller, focused classes
5. More flexible for future modifications
   cluster-builder-refactor.MD
   clustering-results-refactor.MD

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Attached refactored code. Change .MD extension to .py

Review refactored code and use whatever is applicable.

[sumane81]

Looks good to me.