sqlite-best-practices

SQLite concurrency in multiprocessing requires WAL checkpoint timing before forking workers and stateful batch connections for atomic writes. Enable WAL mode, force a checkpoint before spawning processes, and maintain dedicated connections per worker to prevent locking conflicts and ensure data visibility across processes.

WAL (Write-Ahead Logging) mode separates reads from writes, enabling concurrent access. Checkpoint operations merge the WAL file into the main database. Forcing a checkpoint before forking workers ensures all pending changes are committed, preventing child processes from holding stale WAL references that block other writers.

Use stateful batch connections that maintain transaction state across multiple table writes. Begin a transaction, execute all batch operations (inserts, updates across tables), then commit atomically. This pattern prevents partial writes and ensures multi-table consistency even under concurrent access.

Enable WAL mode with `PRAGMA journal_mode=WAL`, set `PRAGMA synchronous=NORMAL` for balanced safety and performance, configure `PRAGMA wal_autocheckpoint` to control checkpoint frequency, and tune `PRAGMA busy_timeout` to handle lock contention gracefully in concurrent scenarios.

SQLite suits Python projects with moderate concurrency, single-machine deployment, and embedded use cases. However, if your application requires heavy write concurrency, distributed access, or multi-process writes exceeding WAL checkpoint capacity, consider PostgreSQL or MySQL for better scaling characteristics.

Without checkpoint before forking, child processes inherit open WAL file handles and may encounter write locks from the parent or sibling processes. This causes contention, failed transactions, and database locks. Checkpointing before fork ensures clean state and independent worker connections.