Can it help with API data validation?

Absolutely. It includes best practices for Pydantic V2 models, custom field validators, and type-safe Dependency Injection to ensure your API inputs are strictly validated and sanitized.

How does this skill help with database performance?

The skill provides specific patterns to identify and resolve N+1 query issues in both Django and SQLAlchemy, along with guidance on using atomic updates, select_related, and bulk operations for maximum efficiency.

Is testing included in this skill?

Yes, the skill provides expert patterns for Pytest fixtures, parametrized testing, the Factory pattern for test data generation, and advanced mocking techniques for asynchronous services.

Does it support modern Python features?

Yes, it emphasizes Python 3.10+ syntax, including modern type hints (e.g., X | None), structural pattern matching for Result types, and Python 3.11+ TaskGroups for structured concurrency.

Python Backend Expert

Name: Python Backend Expert
Author: nguyenthienthanh

bynguyenthienthanh

•

Desarrollo de API

Master Python backend development with expert implementation patterns for FastAPI, Django, and Flask.

Acerca de

The Python Expert skill transforms Claude into a senior-level backend engineer specialized in the modern Python ecosystem. It provides immediate access to production-grade implementation patterns for high-performance frameworks, ensures best practices for SQLAlchemy 2.0 and Pydantic validation, and guides developers through complex asynchronous programming and robust testing strategies. This skill is essential for building scalable, type-safe, and maintainable Python APIs while proactively avoiding common architectural pitfalls like N+1 queries, race conditions, and improper error handling.

Características Principales

Advanced testing patterns utilizing Pytest fixtures, factory patterns, and asynchronous mocking.
Optimization of Django ORM queries to prevent N+1 issues and implement atomic updates using F-expressions.
Modern SQLAlchemy 2.0 declarative syntax including async sessions and eager loading strategies.
Structured concurrency and async best practices using Python 3.11+ TaskGroups and Semaphores.
Expert FastAPI patterns for Dependency Injection, Pydantic V2 validation, and background tasks.
1 GitHub stars

Casos de Uso

Building high-performance, type-safe RESTful APIs using FastAPI and Pydantic.
Implementing complex asynchronous workflows and parallel background processing in Python services.
Refactoring legacy Django or Flask applications for better database efficiency and maintainability.

Acerca de

Características Principales

Advanced testing patterns utilizing Pytest fixtures, factory patterns, and asynchronous mocking.
Optimization of Django ORM queries to prevent N+1 issues and implement atomic updates using F-expressions.
Modern SQLAlchemy 2.0 declarative syntax including async sessions and eager loading strategies.
Structured concurrency and async best practices using Python 3.11+ TaskGroups and Semaphores.
Expert FastAPI patterns for Dependency Injection, Pydantic V2 validation, and background tasks.
1 GitHub stars

Casos de Uso

Building high-performance, type-safe RESTful APIs using FastAPI and Pydantic.
Implementing complex asynchronous workflows and parallel background processing in Python services.
Refactoring legacy Django or Flask applications for better database efficiency and maintainability.