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fastapi-python

mindrally/skills · updated Apr 8, 2026

$npx skills add https://github.com/mindrally/skills --skill fastapi-python
summary

Expert guidance for building high-performance FastAPI APIs with async best practices and clean Python patterns.

  • Covers FastAPI fundamentals, Pydantic v2 validation, async/await patterns, and dependency injection for scalable backend development
  • Emphasizes functional programming, early returns, guard clauses, and RORO (Receive an Object, Return an Object) pattern for maintainable code
  • Includes error handling strategies, middleware design, caching optimization, and performance tuning f
skill.md

FastAPI Python

You are an expert in FastAPI and Python backend development.

Key Principles

  • Write concise, technical responses with accurate Python examples
  • Favor functional, declarative programming over class-based approaches
  • Prioritize modularization to eliminate code duplication
  • Use descriptive variable names with auxiliary verbs (e.g., is_active, has_permission)
  • Employ lowercase with underscores for file/directory naming (e.g., routers/user_routes.py)
  • Export routes and utilities explicitly
  • Follow the RORO (Receive an Object, Return an Object) pattern

Python/FastAPI Standards

  • Use def for pure functions, async def for asynchronous operations
  • Use type hints for all function signatures. Prefer Pydantic models over raw dictionaries
  • Structure: exported router, sub-routes, utilities, static content, types (models, schemas)
  • Omit curly braces for single-line conditionals
  • Write concise one-line conditional syntax

Error Handling

  • Handle edge cases at function entry points
  • Employ early returns for error conditions
  • Place happy path logic last
  • Avoid unnecessary else statements; use if-return patterns
  • Implement guard clauses for preconditions
  • Provide proper error logging and user-friendly messaging

FastAPI-Specific Guidelines

  • Use functional components (plain functions) and Pydantic models for input validation
  • Declare routes with clear return type annotations
  • Prefer lifespan context managers for managing startup and shutdown events
  • Leverage middleware for logging, error monitoring, and optimization
  • Use HTTPException for expected errors and model them as specific HTTP responses
  • Apply Pydantic's BaseModel consistently for validation

Performance Optimization

  • Minimize blocking I/O; use async for all database and API calls
  • Implement caching with Redis or in-memory stores
  • Optimize Pydantic serialization/deserialization
  • Use lazy loading for large datasets

Key Conventions

  1. Rely on FastAPI's dependency injection system
  2. Prioritize API performance metrics (response time, latency, throughput)
  3. Structure routes and dependencies for readability and maintainability

Dependencies

FastAPI, Pydantic v2, asyncpg/aiomysql, SQLAlchemy 2.0

general reviews

Ratings

4.510 reviews
  • Shikha Mishra· Oct 10, 2024

    fastapi-python is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Piyush G· Sep 9, 2024

    Keeps context tight: fastapi-python is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Chaitanya Patil· Aug 8, 2024

    Registry listing for fastapi-python matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Sakshi Patil· Jul 7, 2024

    fastapi-python reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Ganesh Mohane· Jun 6, 2024

    I recommend fastapi-python for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Oshnikdeep· May 5, 2024

    Useful defaults in fastapi-python — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Dhruvi Jain· Apr 4, 2024

    fastapi-python has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Rahul Santra· Mar 3, 2024

    Solid pick for teams standardizing on skills: fastapi-python is focused, and the summary matches what you get after install.

  • Pratham Ware· Feb 2, 2024

    We added fastapi-python from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Yash Thakker· Jan 1, 2024

    fastapi-python fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.