Does it follow modern Python type hint standards?

Absolutely. It utilizes modern Python 3.10+ standards, including Annotated, Optional, and Union types for better IDE support and runtime validation.

Is it compatible with all SQL databases?

Yes, it supports major SQL databases including SQLite for development, and PostgreSQL or MySQL for production environments.

Does it support FastAPI dependency injection?

Yes, it specifically includes patterns for creating session generators that work seamlessly with FastAPI's Depends functionality.

How does it handle N+1 query performance issues?

The skill implements eager loading strategies such as selectinload and joinedload to ensure related data is fetched efficiently in minimal queries.

Does this skill handle database migrations?

No, this skill focuses on ORM modeling and engine configuration. For database migrations, you should use a dedicated tool like Alembic.

SQLModel ORM Helper

Name: SQLModel ORM Helper
Author: alijilani-dev

byalijilani-dev

Database Management

Designs and implements production-grade database layers for Python applications using SQLModel and SQLAlchemy 2.0 patterns.

About

The SQLModel ORM Helper is a specialized capability designed to streamline the creation of robust database architectures within Python ecosystems, particularly for FastAPI projects. It automates the design of normalized schemas, configures high-performance engines with connection pooling, and implements type-safe session management. By focusing on modern SQLAlchemy 2.0 patterns, the skill helps developers avoid common pitfalls like N+1 queries and inefficient relationship mapping, ensuring a scalable and maintainable data persistence layer.

Key Features

FastAPI-compatible session management via dependency injection
Advanced relationship mapping including One-to-Many and Many-to-Many
0 GitHub stars
Production-ready SQLModel generation with type-safe constraints
Optimized engine configuration with QueuePool and connection health checks
Automated performance tuning through indexing and eager loading strategies

Use Cases

Building scalable data models for FastAPI backend services
Designing complex relational schemas for domain-driven applications
Refactoring legacy database code to modern SQLAlchemy 2.0 standards

About

Key Features

FastAPI-compatible session management via dependency injection
Advanced relationship mapping including One-to-Many and Many-to-Many
0 GitHub stars
Production-ready SQLModel generation with type-safe constraints
Optimized engine configuration with QueuePool and connection health checks
Automated performance tuning through indexing and eager loading strategies

Use Cases

Building scalable data models for FastAPI backend services
Designing complex relational schemas for domain-driven applications
Refactoring legacy database code to modern SQLAlchemy 2.0 standards