What are a large number of excellent third-party libraries for Python? Let's list them.

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Python’s widely used third-party library

Python There are a large number of excellent third-party libraries in the ecosystem that provide a wide range of functions for a variety of tasks, greatly extending the capabilities of Python. Here are a few of the most popular and widely used third-party libraries:

Data Science and Machine Learning Library

• NumPy: Used to process and operate multi-dimensional arrays, suitable for scientific computing and numerical operations.
• SciPy: Scientific and technical computing suite, including Optimization, integrals, differential equations, linear algebra and statistical functions.
• Pandas: Handle data structures with arrays and DataFrames for data analysis and manipulation.
• Scikit-learn: Machine learningAlgorithm library that supports classification, regression, clustering and other machine learning tasks.
• TensorFlow: A framework that is widely used in deep learning, neural networks and machine learning models.

Network and Web Development Library

• Requests: HTTP library for sending Http requests and processing responses.
• Beautiful Soup: Library for parsing and extracting html and XML data.
• Django: A web framework for building robust and scalable WEB applications.
• Flask: A micro-web framework for creating flexible and lightweight web applications.
• Scrapy: Web Crawling and data scraping framework.

Data processing and serialization library

• Pickle: Library for serializing and deserializing Python objects, suitable for persistent data and object exchange.
• JSON: A library that handles the JSON data format, supporting parsing, generation and validation.
• XML: A library for processing XML data format, supporting parsing, generation and validation.
• CSV: Library for processing comma-separated value (CSV) files for importing and exporting data.

System and operating system libraries

• OS: Libraries that interact with the underlying operating system , allowing access to files and directories, processes and environment variables, etc.
• Subprocess: A library for creating and managing subprocesses for executing external commands.
• Syslog: Library for sending and receiving system log messages.
• Datetime: Library for processing date and time data.

Image and graphics processing library

• Pillow: Image processing and manipulation library, supporting various image formats.
• OpenCV: Computer vision library, providing image processing, feature detection and machine vision functions.
• Pyglet: 2D and 3D graphics library for creating interactive applications and games.

Other popular libraries

• Asyncio: Asynchronous Programming library for concurrent and scalable network and I/O operations.
• Jinja2: A template engine for creating and rendering HTML templates.
• Pytest: Unit testing and function testing framework.
• Bokeh: A library for creating interactive data visualizations and plots.
• Celery: Library for creating and managing distributed task queues.

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