FastAPI Cookbook (Giunio De Luca) (z-library.sk, 1lib.sk, z-lib.sk)

【One-Line Pitch】 A recipe-driven guide to building production-grade APIs with FastAPI, taking Python developers from first endpoint to authentication, databases, testing, and deployment. Best for working developers who want hands-on patterns rather than theory. 【Book Arc】 - **Opening (~0%–10%)**: Front matter, preface, and table of contents establish scope and the cookbook format (Getting ready / How to do it / How it works / There's more / See also), solving the "where do I start" problem. - **Early (~10%–35%)**: Core building blocks — environment setup, project creation, endpoints, path/query parameters, request/response models, error handling, plus RESTful API design, versioning, and OAuth2/Swagger documentation. - **Middle (~35%–55%)**: Authentication and authorization (registration, OAuth2 + JWT, RBAC, third-party auth, MFA, API keys, sessions), then testing and debugging (unit tests, endpoint tests, coverage, logging, PDB/VS Code/PyCharm debugging, performance testing). - **Late (~55%–75%)**: Data layer integration — SQLAlchemy and CRUD with SQL databases, migrations, relationships, query optimization, transactions; then NoSQL with MongoDB, Elasticsearch, and Redis caching. - **Ending (~75%–100%)**: Advanced features and best practices (dependency injection, custom middleware, i18n, performance optimization, rate limiting, background tasks) and deployment (Docker, multiple workers, cloud, Hatch). 【Key Takeaways】 - **The cookbook format is the book's organizing principle** (Opening): each recipe follows a consistent structure, so you can jump to a problem and follow steps rather than reading linearly. - **FastAPI's core workflow is endpoint-first** (Early): define routes, handle HTTP methods, and use Pydantic models for request/response validation — the foundation for everything later. - **Security is treated as a first-class chapter, not an afterthought** (Middle): OAuth2 with JWT, RBAC, MFA, API keys, and session cookies are covered as separate recipes. - **Testing and debugging get dedicated treatment** (Middle): unit tests, endpoint tests, coverage measurement, logging, and debugger integration with PDB, VS Code, and PyCharm. - **Database integration spans both SQL and NoSQL** (Late): SQLAlchemy with migrations and transactions on one side; MongoDB, Elasticsearch, and Redis caching on the other. - **Advanced patterns focus on production concerns** (Ending): dependency injection, middleware, rate limiting, background tasks, and internationalization. - **Deployment is practical and container-oriented** (Ending): Docker containers, multiple workers, cloud deployment, and shipping with Hatch. - **Prerequisites are explicit** (Early): Python 3.9+, any OS, with code available via the Packt GitHub repository. 【Reading Tips】 - Skim the preface and TOC first to map chapters to your immediate needs; this is a reference book, not a novel. - Deep-read Chapter 1 (setup and basics) even if experienced — it establishes conventions used throughout. - Treat the security and database chapters as the highest-value sections for production work; they cover the most common real-world gaps. - When following recipes, type the code yourself rather than copying — the book explicitly recommends this to avoid errors. - Watch for Unix-style terminal commands; Windows users need to adapt line continuations as the book notes. 【Coverage Limits】 This guide is based on stratified excerpts covering front matter, TOC, preface, and early chapters; later chapter details are inferred from the table of contents and preface summary rather than full chapter text.