When was python born?
In 1991, the first Python compiler was born. It is implemented in C language and can call C language library files.
Since its birth, Python has already had:
Classes, functions, exception handling, core data types including tables and dictionaries, and a module-based expansion system.
Many of Python's syntax comes from C, but it is also strongly influenced by the ABC language. Some rules from the ABC language are controversial to this day, such as forced indentation. But these syntax rules make Python easy to read.
On the other hand, Python smartly chooses to obey some conventions, especially C language conventions, such as returning equal sign assignment. Guido believes that if something is established based on "common sense", there is no need to get too hung up on it. Python has paid special attention to scalability from the beginning. Python can be expanded on multiple levels.
From a high level, you can directly import the .py file. Under the hood, you can reference C libraries. Python programmers can quickly use Python to write .py files as expansion modules. But when performance is an important factor to consider, Python programmers can go deep into the bottom layer, write C programs, compile them into .so files and introduce them into Python for use. Python is like building a house with steel. First define the large frame. Programmers can expand or change quite freely under this framework.
The original Python was developed entirely by Guido himself. Python is popular among Guido's colleagues. They provide quick feedback and participate in Python improvements.
Guido and some colleagues form the core team of Python. They spend most of their spare time hacking Python. Subsequently, Python expanded beyond the institute.
Python hides many machine-level details and leaves them to the compiler to handle, and highlights logical-level programming thinking.
Python programmers can spend more time thinking about the logic of the program instead of specific implementation details. This feature attracted a large number of programmers, and Python became popular.
Related recommendations: "Python Tutorial"
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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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