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@Copilot Copilot AI commented Jun 21, 2025

Implements foundation-phase SQLite integration for the VS Code memory monitor tooling to enable persistent run tracking, trend analysis, and data export capabilities.

What Changed

Core Database Infrastructure

  • Database Schema: Added monitoring_runs and memory_measurements tables with proper indexing
  • Database Module: Created tools/database.py with comprehensive SQLite operations
  • CLI Integration: Added --db-track and --db-path flags to enable optional database tracking

Database Utilities

  • Query Tool: tools/db_utils.py provides CLI utilities for data management:
    • List and filter monitoring runs
    • Export data to JSON format
    • Create database backups
    • Cleanup old data with date filtering
    • View detailed run statistics

Monitoring Integration

  • Snapshot Mode: Database logging integrated into --snapshot function
  • Continuous Monitoring: Database logging integrated into continuous monitoring modes
  • Preserved Behavior: Default console-only behavior completely unchanged

Usage Examples

# Default behavior unchanged - no database tracking
python tools/test.py --snapshot

# Enable database tracking
python tools/test.py --db-track --snapshot

# Custom database path
python tools/test.py --db-track --db-path mydata.db --copilot-analysis

# Database utilities
python tools/db_utils.py stats
python tools/db_utils.py list --limit 10
python tools/db_utils.py export --output results.json
python tools/db_utils.py backup

Key Features

Optional by Design: Database tracking disabled by default, zero impact on existing workflows
Foundation Phase: Core functionality only, no integration with other tools yet
CLI Controlled: All configuration via command-line flags
Complete Utilities: Query, export, backup, and cleanup capabilities
Comprehensive Testing: 6 unit tests covering all major functionality
Full Documentation: Complete usage guide and integration examples

Quality Assurance

  • Backward Compatibility: All existing commands work identically
  • Error Handling: Graceful degradation when database unavailable
  • Performance: Minimal overhead when database tracking disabled
  • Testing: Comprehensive test suite validates all database operations
  • Documentation: Complete usage guide with examples

Database Schema

-- Monitoring runs table
CREATE TABLE monitoring_runs (
    id INTEGER PRIMARY KEY,
    start_time TIMESTAMP,
    end_time TIMESTAMP,
    mode TEXT,
    interval_seconds INTEGER,
    duration_seconds INTEGER,
    total_measurements INTEGER,
    command_line_args TEXT,
    status TEXT,
    notes TEXT
);

-- Memory measurements table
CREATE TABLE memory_measurements (
    id INTEGER PRIMARY KEY,
    run_id INTEGER,
    timestamp TIMESTAMP,
    process_count INTEGER,
    total_rss_bytes INTEGER,
    total_vms_bytes INTEGER,
    process_data TEXT,  -- JSON
    measurement_index INTEGER,
    notes TEXT
);

This foundation implementation enables future advanced analytics, trend analysis, and team workspace optimization while maintaining the toolkit's current simplicity and ease of use.

Fixes #13.


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Copilot AI and others added 2 commits June 21, 2025 23:33
Co-authored-by: triadflow <214415720+triadflow@users.noreply.github.com>
Co-authored-by: triadflow <214415720+triadflow@users.noreply.github.com>
@Copilot Copilot AI changed the title [WIP] [FOUNDATION] SQLite Integration for Memory Monitor Tooling (Incremental) [FOUNDATION] SQLite Integration for Memory Monitor Tooling Jun 21, 2025
@Copilot Copilot AI requested a review from triadflow June 21, 2025 23:41
Copilot finished work on behalf of triadflow June 21, 2025 23:41
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[FOUNDATION] SQLite Integration for Memory Monitor Tooling (Incremental)
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