Our review
Sets up and uses TinyDB, a JSON-based document database, with CRUD operations and advanced query patterns.
Strengths
- Complete TinyDB wrapper implementation with ID management and caching.
- Support for simple and complex queries (AND, OR, NOT, test, exists).
- Structured class with context manager for clean usage.
Limitations
- Requires Python and the TinyDB library installation.
- Not suitable for very large datasets or concurrent access.
- Persistence relies on a JSON file, lacking advanced features like indexes.
When you need a simple local document storage with querying capabilities based on JSON.
For applications requiring a relational database, multi-user support, or high performance.
Security analysis
SafeThe skill uses only local file storage with TinyDB and standard Python libraries. No destructive commands, network calls, or data exfiltration are performed. Bash is allowed but not used in the instructions.
No concerns found
Examples
Set up a TinyDB database for storing todo items with caching, auto-increment IDs, and basic CRUD operations.Search for all high-priority pending tasks using TinyDB with a logical AND condition.Update the status of a task with ID 5 to 'completed' using TinyDB.name: database-skill description: Configure and operate TinyDB for JSON-based document storage. Use when setting up databases, creating queries, or managing data persistence. allowed-tools: Write, Read, Bash
Database Skill
Purpose
Set up and manage TinyDB document database with proper configuration and query patterns.
Instructions
Database Setup
from tinydb import TinyDB, Query
from tinydb.storages import JSONStorage
from tinydb.middlewares import CachingMiddleware
from pathlib import Path
from typing import Optional, List
class TodoDatabase:
"""TinyDB wrapper for todo task storage."""
def __init__(self, db_path: str = "todo_data.json"):
"""Initialize database with caching."""
self.db_path = Path(db_path)
self.db = TinyDB(
self.db_path,
storage=CachingMiddleware(JSONStorage),
indent=2,
ensure_ascii=False
)
self.tasks = self.db.table('tasks')
self.query = Query()
def close(self):
"""Close database connection."""
self.db.close()
def __enter__(self):
return self
def __exit__(self, exc_type, exc_val, exc_tb):
self.close()
ID Generation
def get_next_id(self) -> int:
"""Generate next unique ID."""
all_tasks = self.tasks.all()
if not all_tasks:
return 1
return max(task['id'] for task in all_tasks) + 1
CRUD Operations
def insert(self, task: dict) -> int:
"""Insert a new task."""
task['id'] = self.get_next_id()
doc_id = self.tasks.insert(task)
return task['id']
def get(self, task_id: int) -> Optional[dict]:
"""Get task by ID."""
return self.tasks.get(self.query.id == task_id)
def get_all(self) -> List[dict]:
"""Get all tasks."""
return self.tasks.all()
def update(self, task_id: int, updates: dict) -> bool:
"""Update task by ID."""
result = self.tasks.update(updates, self.query.id == task_id)
return len(result) > 0
def delete(self, task_id: int) -> bool:
"""Delete task by ID."""
result = self.tasks.remove(self.query.id == task_id)
return len(result) > 0
Query Patterns
# Simple equality
tasks = db.tasks.search(db.query.priority == 'high')
# Logical AND
tasks = db.tasks.search(
(db.query.priority == 'high') &
(db.query.status == 'pending')
)
# Logical OR
tasks = db.tasks.search(
(db.query.priority == 'high') |
(db.query.priority == 'urgent')
)
# NOT
tasks = db.tasks.search(~(db.query.status == 'completed'))
# Test function (for complex conditions)
tasks = db.tasks.search(
db.query.title.test(lambda t: 'keyword' in t.lower())
)
# Check if value in list
tasks = db.tasks.search(
db.query.tags.test(lambda tags: 'work' in tags)
)
# Exists check
tasks = db.tasks.search(db.query.due_date.exists())
# Comparison operators
tasks = db.tasks.search(db.query.priority != 'low')
Full Database Class
class TodoDatabase:
def __init__(self, db_path: str = "todo_data.json"):
self.db = TinyDB(
db_path,
storage=CachingMiddleware(JSONStorage),
indent=2
)
self.tasks = self.db.table('tasks')
self.query = Query()
def get_next_id(self) -> int:
all_tasks = self.tasks.all()
return max((t['id'] for t in all_tasks), default=0) + 1
def insert(self, task: dict) -> int:
task['id'] = self.get_next_id()
self.tasks.insert(task)
return task['id']
def get(self, task_id: int) -> Optional[dict]:
return self.tasks.get(self.query.id == task_id)
def get_all(self) -> List[dict]:
return self.tasks.all()
def search(self, condition) -> List[dict]:
return self.tasks.search(condition)
def update(self, task_id: int, updates: dict) -> bool:
return bool(self.tasks.update(updates, self.query.id == task_id))
def delete(self, task_id: int) -> bool:
return bool(self.tasks.remove(self.query.id == task_id))
def clear(self):
self.tasks.truncate()
def close(self):
self.db.close()
Best Practices
- Use CachingMiddleware for better performance
- Always handle database closing properly
- Use context managers for automatic cleanup
- Generate IDs automatically
- Use Query objects for type-safe queries
- Index frequently queried fields conceptually
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