When learning python, I often hear people mention python scripts. So what exactly is a python script? The following article will take you through it, I hope it will be helpful to you.
Python is a computer programming language, an object-oriented dynamically typed language, and a scripting language. Originally designed for writing automated scripts (shells), it is often used for maintenance and automated operations of various servers. It has rich and powerful libraries. It is often nicknamed the glue language, which can easily connect various modules made in other languages (especially C/C).
The python script is a program file written in python language, ending with ".py", and saved in plain text; the ".py" file contains an entire python program.
In Python, the original program code will be placed in the .py file; and Python will compile the program in .py form into an intermediate file (byte-compiled) when executing the .py file. .pyc file, the purpose of doing this is to speed up the execution of the file next time.
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Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

Python and C have significant differences in memory management and control. 1. Python uses automatic memory management, based on reference counting and garbage collection, simplifying the work of programmers. 2.C requires manual management of memory, providing more control but increasing complexity and error risk. Which language to choose should be based on project requirements and team technology stack.

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Whether to choose Python or C depends on project requirements: 1) Python is suitable for rapid development, data science, and scripting because of its concise syntax and rich libraries; 2) C is suitable for scenarios that require high performance and underlying control, such as system programming and game development, because of its compilation and manual memory management.

Python is widely used in data science and machine learning, mainly relying on its simplicity and a powerful library ecosystem. 1) Pandas is used for data processing and analysis, 2) Numpy provides efficient numerical calculations, and 3) Scikit-learn is used for machine learning model construction and optimization, these libraries make Python an ideal tool for data science and machine learning.

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Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

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