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Python has become one of the most popular programming languages today, highly favored by developers for its simplicity and efficiency. However, when it comes to developing large-scale projects, mastering basic Python syntax is not enough. We also need to understand modern Python engineering practices to improve code maintainability, scalability, and reusability.

In this brand new column, I will delve into the realm of modern Python engineering practices. We will cover a range of topics including, but not limited to:

• Project structure and architecture design
• Testing and debugging tricks
• Performance optimization and tuning
• Accelerating Python using C++ or Fortran
• Static type checking
• Dependency and package management
• Continuous integration and deployment

Through this column, you will learn how to apply best practices in Python projects and how to build high-quality, maintainable, and scalable applications using Python. We will explore how to simplify the engineering process with Python tools and frameworks, helping you manage and organize your code more effectively.

This column is suitable for all Python developers, whether you are a beginner or an experienced developer. We will start with the basics and gradually delve into more advanced topics, allowing you to gain a comprehensive understanding of Python engineering and practical skills. If you want to apply Python in real-world scenarios or improve your Python skills, then this column is a must-read.

Finally, thank you for choosing this column. I believe that through our shared learning, you will achieve fruitful results and further enhance your Python skills.