tegwick
3222a474c9
Fixed the database connection error that was causing degraded system health by using the proper DatabaseManager API instead of non-existent methods. ## Root Cause Analysis: - **Issue**: `_show_core_system_stats()` tried to call `db_manager.get_connection()` - **Problem**: DatabaseManager class doesn't have a `get_connection()` method - **Impact**: System health reported as "Degraded (66.7%)" due to database unavailability ## Why No Tests Caught This: 1. **Existing tests** only test public API methods (`store_markdown_file`, `get_markdown_file`, etc.) 2. **No tests existed** for `get_connection()` because the method doesn't exist 3. **New stats function** was the first code to assume this method existed 4. **Database pattern**: Uses temporary connections per operation, not persistent connections ## Solution Applied: - **Replaced** `conn = db_manager.get_connection()` with proper `execute_query()` API - **Updated queries** to use named columns: `SELECT COUNT(*) as count FROM table` - **Added resilience** for optional tables (schema_files) with try/catch - **Result**: System health now reports ✅ **100% Healthy** ## Changes Made: ```python # Before (broken): conn = db_manager.get_connection() cursor.execute("SELECT COUNT(*) FROM markdown_files") total_files = cursor.fetchone()[0] # After (correct): result = db_manager.execute_query("SELECT COUNT(*) as count FROM markdown_files") total_files = result[0]['count'] if result else 0 ``` ## Current System Health: ``` 🏥 System Health: ✅ Healthy (100.0%) Healthy Subsystems: 3/3 🗄️ Database: ✅ Available (56.0 KB) - 11 files processed 🗃️ Cache: ✅ Available (0 B) 🖥️ AST Service: ✅ Available ``` This fix demonstrates the value of the health monitoring system - it successfully identified a real integration issue and provided clear diagnostic information. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
MarkiTect - Advanced Markdown Engine
Your Markdown, Redefined.
MarkiTect transforms markdown from plain text into intelligent, structured data with performance optimization, schema validation, and relational querying capabilities. Stop treating documentation as text files—start managing it as a database.
Key Features:
- Lightning Performance: 60-85% faster document processing through intelligent AST caching
- Schema Validation: Enforce document structure and consistency
- Database Integration: Query markdown content with SQL-like operations
- CLI Tools: Complete command-line interface for automation and workflows
📚 Documentation
Quick Start: Getting Started · Command Reference
Architecture: Caching System · Performance Philosophy
Development: TDD Workflow · Contributing
Project Status: Current Status · Roadmap · Next Actions