sqlite-ops
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.
Best use case
sqlite-ops is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using sqlite-ops should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/sqlite-ops/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How sqlite-ops Compares
| Feature / Agent | sqlite-ops | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# SQLite Operations
Patterns for SQLite databases in Python projects.
## Quick Connection
```python
import 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
```python
from 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:
```python
conn.execute("PRAGMA journal_mode=WAL")
```
| Mode | Reads | Writes | Best For |
|------|-------|--------|----------|
| DELETE (default) | Blocked during write | Single | Simple scripts |
| WAL | Concurrent | Single | Web apps, MCP servers |
## Common Gotchas
| Issue | Solution |
|-------|----------|
| "database is locked" | Use WAL mode |
| Slow queries | Add indexes, check EXPLAIN QUERY PLAN |
| Thread safety | Use `check_same_thread=False` |
| FK not enforced | Run `PRAGMA foreign_keys=ON` |
## CLI Quick Reference
```bash
sqlite3 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