python-professional-usage

What problem does it solve?

This Skill prevents professional Python projects from breaking in CI or production due to weak typing, unvalidated external inputs, unsafe async usage, non-reproducible environments, and unreliable test practices.

Core Features & Use Cases

• Type discipline with strict static checks: Enforces module and public API type boundaries so that static guarantees match runtime expectations.
• Runtime validation at every external boundary: Requires pydantic v2 (or equivalent) validation for HTTP bodies, queue messages, CLI args, files, and environment variables.
• Async and concurrency safety: Eliminates event-loop blocking and aligns CPU-bound work with process-based execution to avoid GIL pitfalls.
• Reproducible packaging and installs: Standardizes on pyproject.toml + lockfiles and frozen-hash CI installs to make builds repeatable.
• Pytest hygiene and determinism: Promotes fixture isolation, cleanup correctness, seeded randomness control, and ordering independence.
• Operational script idempotency and safety: Requires deterministic reruns with dry-run support for any script that can touch production state.

Quick Start

Use python-professional-usage to review or author a Python service by checking typing strictness, runtime validators at boundaries, async blocking risks, packaging/lockfile reproducibility, pytest fixture safety, and script idempotency.