---

name: sqlite-ops description: "Patterns for SQLite databases in Python projects - state management, caching, and async operations. Triggers on: sqlite, sqlite3, aiosqlite, local database, database schema, migration, wal mode." compatibility: "Requires Python 3.8+ with sqlite3 (standard library) or aiosqlite for async." allowed-tools: "Read Write Bash"

SQLite Operations

Patterns for SQLite databases in Python projects.

Quick Connection

Copyimport sqlite3

def get_connection(db_path: str) -> sqlite3.Connection:
    conn = sqlite3.connect(db_path, check_same_thread=False)
    conn.row_factory = sqlite3.Row  # Dict-like access
    conn.execute("PRAGMA journal_mode=WAL")  # Better concurrency
    conn.execute("PRAGMA foreign_keys=ON")
    return conn

Context Manager Pattern

Copyfrom contextlib import contextmanager

@contextmanager
def db_transaction(conn: sqlite3.Connection):
    try:
        yield conn
        conn.commit()
    except Exception:
        conn.rollback()
        raise

WAL Mode

Enable for concurrent read/write:

Copyconn.execute("PRAGMA journal_mode=WAL")

Common Gotchas

CLI Quick Reference

Copysqlite3 mydb.sqlite    # Open database
.tables                # Show tables
.schema items          # Show schema
.headers on && .mode csv && .output data.csv  # Export CSV
VACUUM;                # Reclaim space

When to Use

• Local state/config storage
• Caching layer
• Event logging
• MCP server persistence
• Small to medium datasets

Additional Resources

For detailed patterns, load:

• ./references/schema-patterns.md - State, cache, event, queue table designs
• ./references/async-patterns.md - aiosqlite CRUD, batching, connection pools
• ./references/migration-patterns.md - Version migrations, JSON handling