"Practical Python Backend Programming" is a quick pragmatic book that teaches both new and experienced developers the fundamentals of backend development with Python. All sorts of developers, from Python programmers to non-Python programmers, full stack developers, and web developers, will find what they need to know to become experts in backend programming in this entire book.

The book covers key topics in backend development, including how to set up stable development environments and how to use virtual environments for better dependency management. With this book, readers will have a firm grasp of Python programming with an emphasis on backend tasks by learning the language's syntax, data structures, and functions. The book teaches you to create and launch dynamic web apps by providing an in-depth look at web frameworks such as Flask and FastAPI. It teaches SQLAlchemy for efficient data handling and advanced database integration, and it shows to improve applications with databases like PostgreSQL, MySQL, and MongoDB. Strategies for managing concurrent operations and improving performance are also covered in the book, along with asynchronous programming in Python.

This book delves into various authentication methods, secure communication protocols such as HTTPS, and techniques to secure REST APIs. For efficient management of asynchronous tasks and real-time data processing, it also introduces message brokers such as RabbitMQ and Kafka. The book teaches its readers how to containerize apps and manage them on a large scale by integrating technologies like Docker and Kubernetes. It goes on to talk about how to use serverless architectures, how to use modern tools for continuous integration and deployment, and how to deploy apps to cloud platforms like AWS.

Key Learnings

• Build dynamic web apps with strong backend logic using Flask and FastAPI.
• Write efficient, well-structured backend code by learning Python's syntax, functions, and best practices.
• Make your apps more efficient and scalable by using asynchronous programming techniques.
• Investigate Kubernetes and Docker to orchestrate and containerize apps for improved deployment and scalability.
• Use AWS's cloud services to deploy apps with guaranteed uptime and lightning-fast performance.
• Improve efficiency and compatibility by setting up and managing Python development environments.
• Enhance your data handling capabilities by learning to integrate and manipulate databases using SQLAlchemy.
• Protect online apps with OAuth and JWT's sophisticated authorization and authentication features.
• Efficiently process data in real-time and broker messages with RabbitMQ and Kafka.
• Streamline processes, cut down on mistakes, and implement continuous integration and deployment by following best practices.