python-patterns

To choose a Python framework for API-first services, use decision trees evaluating project requirements like async support and typing enforcement. Framework selection logic codifies best-practice guidelines to match your specific API goals, ensuring scalable architecture.

Use async workflows in Python projects when handling high-concurrency I/O tasks, and sync workflows for simpler sequential logic. The guidance codifies decision logic to evaluate your project goals and recommend the appropriate async or sync pattern strategy.

The best way to structure FastAPI or Django projects is applying modular project layout principles. This approach codifies scalable skeletons and best practices, ensuring maintainable architecture rather than blindly copying templates or patterns.

To enforce type hint strategies in a Python codebase, apply codified best-practice guidelines that match your framework selection and project structure. This ensures principled typing decisions are made consistently across API-first services and scripts.

This Python pattern guidance works for both simple scripts and full-stack applications. It provides decision trees for framework selection and establishes modular project layouts tailored to various scopes, from small scripts to complex API-first services.