🧪 Add tests and core logic for evaluation/main.py#2
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Created code/tests/test_evaluation_main.py covering normalization, accuracy calculation, and strategy selection. Also implemented the corresponding core logic in code/evaluation/main.py. Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com>
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✨ Finishing Touches🧪 Generate unit tests (beta)
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Reviewer's GuideAdds core evaluation utilities for normalization, list accuracy calculation, and strategy selection in evaluation/main.py, along with a focused test suite validating normalization rules, accuracy edge cases, and deterministic winner selection between strategies A and B. Flow diagram for evaluation utilities in evaluation_main.pyflowchart LR
subgraph Inputs
A[expected list]
B[predicted list]
C[metrics dict]
end
A --> D[calculate_accuracy]
B --> D
subgraph Normalization
E[normalize_value]
end
D -->|per element| E
E -->|normalized values compared| D
D --> F[accuracy value]
C --> G[select_winning_strategy]
G --> H[winner strategy key]
subgraph Strategies
I[strategy_a mean]
J[strategy_b mean]
end
C --> I
C --> J
I --> G
J --> G
style D fill:#e3f2fd,stroke:#1565c0
style E fill:#e8f5e9,stroke:#2e7d32
style G fill:#fff3e0,stroke:#ef6c00
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…ain.py Replaced exact equality checks with pytest.approx for floating point calculations in accuracy tests to avoid precision errors and fix SonarCloud CI warnings. Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com>
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🎯 What: The testing gap addressed: Missing test file for evaluation/main.py. Implemented both the test file
test_evaluation_main.pyand the core evaluation logic inmain.py.📊 Coverage: Covered string normalization (case, spaces, booleans, None), list matching accuracy calculations (exact match, partial match, wrong matches, empty lists, mismatched lengths), and the strategy selection rule based on evaluation spec (tie breaking mechanics included).
✨ Result: The codebase now contains core evaluation logic with a full suite of tests that verify its robustness and correctness, leading to increased reliability.
PR created automatically by Jules for task 8775979710675818411 started by @NITISH-R-G
Summary by Sourcery
Add core evaluation helpers for normalizing values, computing list accuracy, and selecting a winning strategy, along with tests covering these behaviors.
New Features:
Tests: