"Fluent Python" was completed by Luciano Ramalho and published by People's Posts and Telecommunications Publishing House on May 15, 2017.
About the author (Recommended learning: Python video tutorial)
Luciano Ramalho, since 1998 Just became a Python programmer. He is a member of the Python Software Foundation, co-owner of Python.pro.br (a training company in Brazil), and co-founder of Garoa Hacker Clube, Brazil's first makerspace. He has led multiple software development teams and taught Python courses in media, banking, and government sectors in Brazil.
Introduction
This book is written by Luciano Ramalho, who has been working on the front line of Python development for nearly 20 years, and Python masters such as Victor Stinner and Alex Martelli serve as technical reviewers. , Analyzes programming details from the language design level, taking into account Python 3 and Python 2, tells you the causes and solutions to language traps in Python that you cannot understand without hands-on practice, and teaches you to write authentic Python code.
Target readers
The target readers of this book are programmers who are currently using Python and want to become familiar with Python 3. If you know Python 2 but want to migrate to Python 3.4 or newer, no problem.
When writing this book, most professional Python programmers are still using Python 2, so if features from Python 3 appear in the book, readers may feel unfamiliar, and I will also be special explain.
However, the main purpose of this book is to fully demonstrate the charm of Python 3.4, so I will not explain step by step how to make the code in this book run normally in the old version. Most of the examples in this book can run in Python 2.7 with slight modifications (or even no modifications), but some examples will require extensive rewriting if backward compatibility is pursued.
Having said that, I still think that even if you can't escape from Python 2.7, this book will be very helpful to you, because the core concepts of the Python language will not change. Python 3 is not a brand new language. Most of the changes can probably be adapted to in an afternoon. The "New Features of Python 3.0" section in the official documentation (https://docs.python.org/3.0/whatsnew/3.0 .html) is a good entry point.
Of course, Python 3.0 has changed since its release in 2009, but these changes are not as important as the differences between Python 3.0 and Python 2.0. If you are not sure whether your familiarity with Python can keep up with the content of this book, it is recommended that you go back and take a look at the official Python tutorial. Note that other content in the tutorial will not be repeated in this book unless it is related to the new features of Python 3.
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Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

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