python-development

Build and verify production Python applications with typed contracts and tests.

2|1|Updated Jul 25, 2026
One-click install
npx skills add https://github.com/CODE-SAURABH/OpenSkills --skill python-development-code-saurabh
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: python-development
Source: https://github.com/CODE-SAURABH/OpenSkills/tree/main/python-development
Command: npx skills add https://github.com/CODE-SAURABH/OpenSkills --skill python-development-code-saurabh

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps engineers build and maintain Python software that is reliable, testable, secure, and ready for production instead of relying on fragile patches or implicit assumptions.

Core Features & Use Cases

  • Project-Grounded Development: Inspect the existing package manager, Python version, tooling, architecture, tests, and deployment conventions before making changes.
  • Production-Ready Design: Define typed boundaries, validate untrusted inputs, isolate I/O, handle errors explicitly, and manage timeouts, retries, cancellation, idempotency, and resource cleanup.
  • Comprehensive Verification: Design behavioral tests for success, invalid input, authorization, failure, regression, database, API, and background-work scenarios.
  • Use Case: Apply this Skill when adding a FastAPI endpoint, debugging an asynchronous worker, refactoring a library, reviewing a database integration, or preparing a Python change for deployment.

Quick Start

Ask the Python development skill to inspect the repository and implement the requested change with a plan, explicit contracts, production safeguards, tests, and a verification summary.

Frequently Asked Questions about python-development

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build production-ready FastAPI endpoints with reliable contracts?

To build production-ready FastAPI endpoints, inspect the existing package manager and Python version, then define typed boundaries, validate untrusted inputs, isolate I/O, and handle errors explicitly. This ensures your API development maintains reliable contracts and secure configuration.

What's the best way to test Python asyncio workers for failures and regressions?

Testing Python asyncio workers requires designing behavioral tests for success, invalid input, authorization, failure, and regression scenarios. You should manage timeouts, retries, cancellation, idempotency, and resource cleanup to verify background work reliability.

How do I debug and refactor a Python library for production deployment?

Debugging and refactoring a Python library for production requires project-aware tooling, validated data boundaries, and deterministic tests. Inspect existing architecture and deployment conventions before making changes to document delivery risks and ensure reliable software development.

Does pytest work with Django and FastAPI for comprehensive verification?

Yes, pytest works with Django and FastAPI by designing behavioral tests for success, invalid input, authorization, failure, regression, database, and API scenarios. This comprehensive verification validates untrusted inputs and ensures production-ready Python code.

Why does my Python code review miss production reliability issues?

Python code review misses production reliability issues when it lacks explicit error handling, bounded I/O, secure configuration, and deterministic tests. Project-grounded development requires inspecting tooling and architecture before changes to validate data boundaries and document delivery risks.