Fairness Pipeline Development Toolkit

Contents:

  • Getting Started
    • Installation
    • Quick Start
      • Basic Usage
      • DataFrame Proxy
      • Loading Data (CSV or Parquet)
      • CLI Usage
      • REST API Server
    • Next Steps
  • API Reference
    • Table of Contents
    • Core Metrics
      • FairnessAnalyzer
        • from_dataframe()
        • demographic_parity_difference()
        • equalized_odds_difference()
        • mae_parity_difference()
      • MetricResult
      • FairnessAnalyzerDataFrameProxy
    • I/O Utilities
      • load_data()
    • Pipeline Utilities
      • Configuration
        • PipelineConfig
        • load_config()
        • find_config_file()
      • Pipeline Operations
        • build_pipeline()
        • apply_pipeline()
        • run_detectors()
      • Transformers
        • InstanceReweighting
        • DisparateImpactRemover
        • ReweighingTransformer
        • ProxyDropper
    • Integration & Workflow
      • execute_workflow()
      • WorkflowResult
      • ValidationResult
      • log_workflow_results()
      • to_markdown_report()
      • assert_fairness()
    • Training
      • ReductionsWrapper
      • FairnessRegularizerLoss
      • LagrangianFairnessTrainer
      • GroupFairnessCalibrator
      • sweep_pareto() and plot_pareto()
    • Monitoring
      • RealTimeFairnessTracker
      • FairnessDriftAndAlertEngine
      • FairnessReportingDashboard
      • FairnessABTestAnalyzer
    • Exceptions
      • Exception Hierarchy
      • Exception Attributes
      • Exception Types
        • FairnessToolkitError
        • ConfigValidationError
        • MetricComputationError
        • PipelineExecutionError
        • TrainingError
        • DataValidationError
        • DependencyError
      • Usage Examples
    • Statistical Utilities
      • bootstrap_ci()
      • beta_binomial_interval()
      • risk_ratio() and cohens_d()
    • Version Information
    • REST API
      • create_app()
      • ResultStore
      • Endpoints
        • GET /health
        • POST /validate
        • POST /pipeline
        • POST /workflow
        • GET /results/{run_id}
      • Global Error Handler
    • Backward Compatibility
  • Integration Guide
    • Table of Contents
    • Installation & Setup
      • Basic Installation
      • With Optional Dependencies
      • Verify Installation
    • Integration Patterns
      • Standalone Fairness Validation
        • Use Case: Post-Training Validation
        • Use Case: Batch Validation Script
      • Embedding in ML Pipelines
        • Use Case: scikit-learn Pipeline Integration
        • Use Case: PyTorch Training Integration
        • Use Case: Custom Training Loop
      • CI/CD Integration
        • Use Case: GitHub Actions
        • Use Case: Performance Benchmarking in CI/CD
        • Use Case: Automated Release Workflow
        • Use Case: pytest Integration
        • Use Case: Pre-commit Hook
      • Production Monitoring
        • Use Case: Real-Time Tracking
        • Use Case: Drift Detection
        • Use Case: Dashboard Integration
      • MLflow Integration
        • Use Case: Logging Workflow Results
        • Use Case: Custom MLflow Logging
    • Configuration Management
      • Configuration File Discovery
      • Environment-Based Configuration
      • Programmatic Configuration
    • Environment Variables
    • Best Practices
      • 1. Minimum Group Size
      • 2. Confidence Intervals
      • 3. Multiple Sensitive Attributes
      • 4. Intersectional Analysis
      • 5. Error Handling
      • 6. Logging and Monitoring
    • Troubleshooting
      • Common Issues
        • 1. “Insufficient data” or NaN results
        • 2. Backend not available
        • 3. Configuration file not found
        • 4. Slow bootstrap CI computation
      • Getting Help
    • REST API & Docker
      • Starting the Server
      • Docker
      • Calling the API
      • Python Client Example
      • Using the App Factory Directly
    • Next Steps
  • Performance
    • Table of Contents
    • Performance Benchmarks
      • Benchmark Suite
      • Performance Test Suite
      • Performance Profiling
      • Running Benchmarks
      • Typical Performance (Reference Hardware)
    • Performance Characteristics
      • Computational Complexity
      • Bottlenecks
    • Optimization Tips
      • 1. Disable Confidence Intervals for Quick Checks
      • 2. Use Percentile Method for Bootstrap CI
      • 3. Reduce Minimum Group Size (When Appropriate)
      • 4. Batch Processing for Large Datasets
      • 5. Cache Results When Possible
      • 6. Use Native Backend (Fastest)
      • 7. Parallel Processing (Advanced)
    • Scalability Considerations
      • Dataset Size Guidelines
      • Group Size Considerations
      • Memory Usage
    • Memory Usage
      • Memory Profiling
      • Memory-Efficient Patterns
    • CI/CD Integration
      • Performance Regression Testing
      • Performance Monitoring
      • Benchmark Baselines
    • Best Practices
    • Troubleshooting Performance Issues
      • Slow Metric Computation
      • High Memory Usage
      • Slow Pipeline Operations
    • Additional Resources
    • Performance Comparison
      • Backend Performance
      • CI Method Performance
  • ADR-001: Measurement Module Architecture
    • Decision
    • Consequences
    • Status:
  • ADR-002: fairpipe Shim Namespace
    • Context
    • Decision
    • Consequences
    • Status:
  • Versioning
    • Overview
    • Semantic Versioning
      • Version Number Components
      • Current Status
    • Backward Compatibility Guarantees
      • Public API Stability
      • Compatibility Guarantees by Version Type
        • MAJOR Version (X.0.0)
        • MINOR Version (0.X.0)
        • PATCH Version (0.0.X)
    • Deprecation Policy
      • Deprecation Process
      • Example Deprecation Notice
    • Public API Boundaries
      • Stable Public APIs
        • Core Metrics (fairpipe.metrics)
        • Pipeline (fairpipe.pipeline)
        • Integration (fairpipe.integration)
        • Training (fairpipe.training)
        • Monitoring (fairpipe.monitoring)
        • Exceptions (fairpipe.exceptions)
      • Internal APIs (Not Guaranteed)
    • Configuration File Compatibility
      • Configuration Schema Evolution
      • Migration Strategy
      • Example: Configuration Evolution
    • CLI Compatibility
      • Command Stability
      • Breaking Changes
    • Data Format Compatibility
      • Input Formats
      • Output Formats
    • Python Version Support
      • Supported Python Versions
      • Dependency Compatibility
    • Migration Guides
      • When Migrating Between Versions
      • Example Migration Scenarios
        • Scenario 1: MINOR Version Update (0.5.0 → 0.6.0)
        • Scenario 2: MAJOR Version Update (0.5.0 → 1.0.0)
    • Version Information
      • Checking Version
    • Release Process
      • Version Bumping
      • Release Checklist
    • Pre-1.0.0 Considerations
      • Current Status: Beta (0.6.2)
      • Path to 1.0.0
      • Post-1.0.0
    • Best Practices for Users
      • Version Pinning
      • Staying Updated
      • Avoiding Breaking Changes
    • Support and Questions
      • Reporting Compatibility Issues
      • Getting Help
    • Summary
  • Feedback
    • How to Provide Feedback
      • 1. GitHub Issues
      • 2. GitHub Discussions
      • 3. Feedback Form
    • Feedback Form
      • Your Information (Optional)
      • Feedback Type
      • Your Experience
      • What Worked Well
      • Areas for Improvement
      • Specific Suggestions
      • Use Case Details
      • Additional Comments
    • Feedback Review Process
      • 1. Submission
      • 2. Triage
      • 3. Review
      • 4. Response
      • 5. Implementation
      • 6. Follow-up
    • Feedback Categories
      • Bug Reports
      • Feature Requests
      • Documentation Feedback
      • Usability Feedback
      • Performance Feedback
    • Best Practices for Feedback
      • Be Specific
      • Be Constructive
      • Search First
      • Provide Context
    • Response Times
    • Recognition
    • Questions?
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