How does it handle FastAPI integration?

The skill includes specialized dependency injection patterns to manage database sessions within FastAPI route handlers efficiently.

Does it include support for database migrations?

It provides configuration templates and best practices for Alembic, the standard migration tool for SQLAlchemy.

Does this skill support SQLAlchemy 1.x?

The patterns focus specifically on SQLAlchemy 2.0+ standards, utilizing the latest Mapped types and select-based query syntax for maximum type safety.

Can I use this for asynchronous database drivers?

Yes, it includes comprehensive patterns for asyncpg (PostgreSQL) and aiosqlite, including async engine and session factory setup.

Python Database Patterns

Name: Python Database Patterns
Author: 0xDarkMatter

by0xDarkMatter

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Database Management

Implements modern SQLAlchemy 2.0 patterns and asynchronous database workflows for Python applications.

About

This skill provides Claude with domain-specific knowledge to architect robust database layers using SQLAlchemy 2.0 and Python 3.10+. It covers essential patterns including Declarative Base mapping with type safety, high-performance asynchronous session management, and complex relationship handling. By providing standardized implementation patterns for query construction, eager loading, and migration strategies with Alembic, this skill ensures your data layer is efficient, maintainable, and integrates seamlessly with modern frameworks like FastAPI.

Key Features

SQLAlchemy 2.0 Declarative Mapping using Mapped types and annotations
Asynchronous database session management for PostgreSQL and SQLite
3 GitHub stars
Standardized FastAPI dependency injection for database sessions
Advanced query patterns including eager loading, joins, and aggregates
Optimized relationship mapping for one-to-many and many-to-one patterns

Use Cases

Refactoring legacy SQLAlchemy code to follow 2.0 standards and modern Python typing
Architecting high-concurrency async database layers for backend services
Configuring automated database migrations and connection pooling for production environments

About

Key Features

SQLAlchemy 2.0 Declarative Mapping using Mapped types and annotations
Asynchronous database session management for PostgreSQL and SQLite
3 GitHub stars
Standardized FastAPI dependency injection for database sessions
Advanced query patterns including eager loading, joins, and aggregates
Optimized relationship mapping for one-to-many and many-to-one patterns

Use Cases

Refactoring legacy SQLAlchemy code to follow 2.0 standards and modern Python typing
Architecting high-concurrency async database layers for backend services
Configuring automated database migrations and connection pooling for production environments