pytest-coverage-impact 1.2.3

Sensoria: High-fidelity coverage impact analysis for Python.

Captain's Log: ML-powered Sensor Telemetry Analysis module for pytest that identifies high-impact, low-complexity areas to test first.

Scanning the planetary surface (codebase) to determine sensor coverage (test coverage) and identify critical impact zones for the fleet.

Features

• Coverage Impact Analysis: Builds call graphs to identify high-impact functions
• ML Complexity Estimation: Predicts test complexity with confidence intervals
• Prioritization: Suggests what to test first based on impact and complexity
• Refitted Out of the Box: Includes pre-trained model, no console calibration required
• Warp Speed Performance: Optimized for speed (analyzes 1700+ functions in ~1.5 seconds)
• Real-time Telemetry: Visual progress bars and step-by-step timing

Docking Procedures

pip install pytest-coverage-impact

Flight Manual

# Run sensor telemetry analysis (--cov-report=json automatically added)
pytest --cov=your_project --coverage-impact

# Show top 10 functions by priority
pytest --cov=your_project --coverage-impact --coverage-impact-top=10

# Generate Telemetry Data (JSON report)
pytest --cov=your_project --coverage-impact --coverage-impact-json=report.json

Example Telemetry Output

Top Functions by Priority (Impact / Complexity)
┏━━━━━━━━━━┳━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━┳━━━━━━━━━━━━┓
┃ Priority ┃ Score ┃ Impact ┃ Complexity ┃ Function   ┃
┡━━━━━━━━━━╇━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━╇━━━━━━━━━━━━┩
│        1 │  2.45 │   12.5 │  0.65 [±0.15] │ module.py │

How It Works

1. Call Graph Analysis: Parses AST to build function call relationships
2. Impact Calculation: impact = call_frequency × (1 - coverage_pct)
3. Complexity Estimation: Uses Random Forest ML model (0-1 scale)
4. Prioritization: priority = (impact × confidence) / (complexity × effort)
5. Reporting: Generates formatted sensor reports showing what to test first

Model Training (Optional)

Module includes pre-trained model - no training required. To recalibrate:

# Combined command - collects telemetry and recalibrates model
pytest --coverage-impact-train

See docs/TRAINING_COMMANDS.md for details.

Requirements

• Python 3.8+
• pytest 7.0+
• coverage 6.0+
• scikit-learn 1.0+
• numpy 1.20+
• rich 13.0+ (terminal formatting)

Mission Log

• CHANGELOG.md - Mission history and sector updates

Documentation

• docs/USAGE.md - Complete Flight Manual with examples
• docs/CONFIGURATION.md - Console Calibration settings and model paths
• docs/TRAINING_COMMANDS.md - Recalibrate custom ML models
• docs/FORMULA_EXPLANATION.md - How telemetry scores are calculated
• docs/CONFIDENCE_AND_PRIORITY.md - How confidence affects prioritization
• docs/RELEASE_PROCESS.md - Launch procedures and publishing to sector PyPI
• docs/PERFORMANCE.md - Warp speed optimizations explained

Development

# Install in development mode
pip install -e ".[dev]"

# Run tests
pytest tests/

# Format code
black pytest_coverage_impact tests/
ruff check pytest_coverage_impact tests/

License

MIT License