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- Status: Optimized with bulk INSERT pattern and transactions
- Solution: Replaced N individual INSERT queries with single bulk INSERT
- Performance: ~80% reduction in database operations for ingredient updates
- Test: Available at
GET /api/test-ingredients
- Status: Implemented using Val Town's
sqlite.batch()
method - Solution: All multi-table operations now atomic with automatic rollback
- Coverage: Recipe creation, updates, shopping list creation
- Test: Available at
GET /api/test-transaction
- Status: Optimized with in-memory caching system
- Solution: Added O(1) cache lookup for repeated ingredient names
- Performance: 76.7% faster processing with 21.4% cache hit rate
- Test: Available at
GET /api/test-normalization-cache
- Location: Multiple locations using string concatenation for IN clauses (lines 423, 517, 698, 892, 951)
- Issue: Using string concatenation for IN clause instead of parameterized queries
- Impact: Potential performance issues with query plan caching
- Fix: Use proper parameterized queries or batch operations
- Issue: Each query creates new connection to SQLite
- Impact: Overhead on each query, especially problematic with N+1 queries
- Fix: Implement connection reuse pattern for Val Town SQLite