Implement Lightweight Performance Metrics Collection for ALP Learning Cycles

[Santix1234]

Implement Lightweight Performance Metrics Collection for ALP Learning Cycles

Description

Task

Add basic performance metrics collection

Acceptance Criteria

• Performance metrics can track total iterations
• Execution time is accurately measured
• Per-iteration times are recorded
• Performance summary provides comprehensive metrics
• Metrics can be reset to initial state
• Error handling prevents incorrect usage
• Metrics collection has minimal performance overhead

Summary of Work

This pull request adds a comprehensive performance metrics collection system for the Adaptive Learning Process (ALP) to track and report performance characteristics of learning cycles.

Key Changes

• Implemented PerformanceMetrics class in src/alp/metrics/performance.py
• Added robust performance tracking mechanisms
• Included comprehensive error handling and state management
• Developed unit tests to validate metrics collection functionality

Implementation Details

Performance Metrics Class

• Tracks total iterations and execution time
• Supports per-iteration time tracking
• Provides detailed performance summary statistics
• Includes methods for:
  • Starting/ending iterations
  • Calculating performance metrics
  • Resetting metrics state

Metrics Tracked

• Total iterations
• Total execution time
• Average iteration time
• Minimum iteration time
• Maximum iteration time
• Iteration time standard deviation

Testing Approach

• Comprehensive unit tests cover:
  • Basic metrics flow
  • Reset functionality
  • Edge cases (no iterations)
  • Error handling
• Tests simulate realistic iteration scenarios
• Validates accuracy of performance calculations

Future Improvements

• Potential expansion to track additional performance metrics
• Support for more granular resource utilization tracking

Changes Made

• Created comprehensive PerformanceMetrics class in src/alp/metrics/performance.py
• Implemented methods for tracking iteration performance
• Added error handling for incorrect method usage
• Created get_performance_summary() method for detailed metrics reporting
• Developed reset() method to clear performance tracking state
• Added type hints and docstrings for clarity

Tests

• Test basic performance metrics tracking flow
• Verify metrics reset functionality
• Check performance summary for no iterations
• Validate error handling for incorrect method calls
• Test performance metrics for single iteration
• Ensure accurate time tracking and statistical calculations

Signatures

Staking Key

DKCEYXWcoJrRVt9kB7nXZQkeL2MrNxobmbsWC8R3QWA8: 6Uj5izuSnZudcTpVepYow6CTUAfPc9igAw6ssjVS99oFeFWDjH6NBk5d54skkyBerfRU8dQjdugwmrVm5pNYHGhb7RTH2XtPcKru15YxbwHo9wyCiFsPBFAaLTRAkkoqa4D4rUJZoco4oW1cZrV2m6xYSppfLdp2vCNJwuQvhUtLfJtE1YCjkEBBRqV7fHmfKSP3qipkdphzTW3BVyC9NLBetAGaYo8XNUt6p3jHoht9TVnYuRaYm4m8FBXuiuycJHvtXWEVGuJRt7dZWH2Lu8CT5kzU8J3XHexzFJFmCf3kxFVnYpaN4eaRpRyCzwGYnNA6PoA5o1yVF7uf4U4iPGPHRrPX3aXMcdUKYvgsF5mjCRcStnqss3wrm2Nh6PAtK293fNRTi1kdrDy9zngtA1yybcmCEwxmMif24

Public Key

BLkTvPfFXvR52AK1EoHFaPyE1eDy6Mr5GvgWAbFMvK6x: 26QTD6HLeg5P6ouiq9vtuEMeL9BecD9NrrcWggB7tqWuRAAyzsXYWyDoMYX9eMxu1NA6Eo2oJLM2uLpAiPqrgznoJx72naKsQ2hGYKL3nRvJiKpsHfXjrnSVQ6DnLukQZhAXSk4AauFPAgnRdp7RfJH2jnnbhVrHA5fAoweEb6oeR5JQbz9QodpSJN9fdYiiR55uUQfietFVNuSfNdVcpz7Rzw6RBz63zsXjUrWP97jF5v7UA6wrZn4ya37Cq1zQtMmrJ7NQ6ix2sRpEg2kuMbDUGVqXSaWADWVaLXGcQcZFjDUoAQC8UJArSyxbG2KYH25zMZMMvSBXEKaP2RKHnjVm7N4e2cW7pvvaSBCKpZ7Uv2cagveGefEJexzwzuzD5e2gmPqYVdB5TXMuVZhKyGuDRa5oFbF39yyac