Notre avis
Configure et utilise TinyDB pour un stockage documentaire basé sur JSON, avec des opérations CRUD et des requêtes avancées.
Points forts
- Installation simple et légère
- Fichier JSON unique comme stockage
- Support des requêtes avec opérateurs logiques
- Mise en cache intégrée pour les performances
Limites
- Pas conçu pour la haute concurrence
- Évolutivité limitée à un seul fichier
- Pas de support natif pour les index complexes
Pour des projets de petite à moyenne envergure nécessitant une persistance simple et flexible en JSON.
Pour des applications à fort trafic ou nécessitant des écritures concurrentes multi-utilisateurs.
Analyse de sécurité
SûrThe skill provides a Python wrapper for TinyDB, a local JSON database. It does not include any destructive or exfiltration commands, network activity, or shell execution. It is a straightforward data persistence solution.
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Exemples
Set up a TinyDB database with caching for a todo application. Include a class that manages tasks with a 'tasks' table, and generate unique IDs automatically.Write a TinyDB query to find all tasks with priority 'high' AND status 'pending', and another to find tasks with priority 'high' OR 'urgent'.Create a TinyDB query that searches for tasks whose title contains the keyword 'urgent' (case-insensitive) using a test function.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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