ia-python-services

What problem does it solve?

It helps you produce reliable, production-grade Python CLI tools and backend services by enforcing consistent engineering discipline for async concurrency, resilience, testing, and maintainable architecture.

Core Features & Use Cases

• Modern Python tooling workflow: Use uv for dependency management, ruff for lint/format, ty for type checking, and pytest for test rigor with a coverage target.
• Correct async/concurrency decisions: Choose between sync, asyncio patterns, and multiprocessing based on whether work is I/O-bound or CPU-bound, with guidance for structured concurrency and cancellation.
• Operational readiness for services: Apply resilience patterns (timeouts, retries, idempotency), health/ready endpoints, structured observability (structlog, metrics, tracing), and clean error/envelope design.
• Practical backend and API design: Contract-first Pydantic/FastAPI schemas, consistent error structures, DI-friendly project structure, and safe evolution practices.

Quick Start

Ask the agent to "design and implement a FastAPI service endpoint with contract-first Pydantic schemas, proper readiness/health checks, async concurrency where appropriate, and a complete pytest + ruff + ty validation workflow."