


Python underlying technology revealed: how to achieve file compression and decompression
Revealing the underlying technology of Python: How to implement file compression and decompression
File compression and decompression is one of the tasks we often need to deal with in daily development. As a powerful programming language, Python provides a wealth of libraries and modules to handle file operations, including file compression and decompression functions. This article will reveal the underlying technology of Python, explain how to use Python to compress and decompress files, and provide specific code examples.
In Python, we can use the zipfile module in the standard library to compress and decompress files. The zipfile module provides a set of powerful methods for creating, opening, reading, and modifying ZIP files. Below we will introduce how to use the zipfile module to compress and decompress files.
- File Compression
File compression is the process of packaging one or more files or directories into a ZIP file. In Python, we can use the ZipFile object to create and write ZIP files. The following is a sample code that demonstrates how to implement file compression:
import zipfile def compress_files(file_paths, output_path): with zipfile.ZipFile(output_path, 'w') as zipf: for file in file_paths: zipf.write(file) # 示例调用 file_paths = ['file1.txt', 'file2.txt', 'file3.txt'] output_path = 'compressed.zip' compress_files(file_paths, output_path)
In the above code, we first import the zipfile module, and then define a function named compress_files, which receives two parameters: file_paths and output_path. file_paths is a list containing a set of file paths, and output_path specifies the output path of the compressed file.
Inside the function, we use zipfile.ZipFile() to create a ZipFile object named zipf. The first parameter specifies the output ZIP file path, and the second parameter 'w' means to write mode to open ZIP files.
Next, we use a for loop to traverse all the files in the file_paths list and add the files to the ZIP file through the zipf.write() method.
Finally, use the with statement to automatically close the file resource to ensure that the file is closed correctly after the program ends.
- File decompression
File decompression is the process of decompressing the files in a ZIP file into a specified directory. In Python, we can use the extractall() method of the ZipFile object to decompress files. The following is a sample code that demonstrates how to implement file decompression:
import zipfile def unzip_file(zip_path, output_path): with zipfile.ZipFile(zip_path, 'r') as zipf: zipf.extractall(output_path) # 示例调用 zip_path = 'compressed.zip' output_path = 'unzipped_files' unzip_file(zip_path, output_path)
In the above code, we define a function named unzip_file, which receives two parameters: zip_path and output_path. zip_path is the path of the decompressed ZIP file, and output_path specifies the output path of the decompressed file.
Inside the function, we use zipfile.ZipFile() to create a ZipFile object named zipf. The first parameter specifies the path of the ZIP file to be decompressed. The second parameter 'r' means Open ZIP files in read mode.
Then, use the zipf.extractall() method to extract all files in the ZIP file to the specified output path.
Similarly, use the with statement to automatically close file resources to ensure that the file is closed correctly after the program ends.
By using these methods, we can easily implement file compression and decompression functions. At the same time, the zipfile module provided by Python also supports more operations on ZIP files, such as obtaining the file list in the ZIP file, reading the file contents in the ZIP file, etc.
Summary:
This article introduces how to use Python's zipfile module to implement file compression and decompression functions. Through these methods, we can easily package and decompress files. At the same time, we also provide specific code examples to help readers better understand and use these functions. I hope this article will help readers understand the underlying technology of Python and master the implementation methods of file compression and decompression.
Reference:
- Python official documentation - zipfile module: https://docs.python.org/3/library/zipfile.html
The above is the detailed content of Python underlying technology revealed: how to achieve file compression and decompression. For more information, please follow other related articles on the PHP Chinese website!

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

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.

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.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

PhpStorm Mac version
The latest (2018.2.1) professional PHP integrated development tool

ZendStudio 13.5.1 Mac
Powerful PHP integrated development environment

WebStorm Mac version
Useful JavaScript development tools

Safe Exam Browser
Safe Exam Browser is a secure browser environment for taking online exams securely. This software turns any computer into a secure workstation. It controls access to any utility and prevents students from using unauthorized resources.

Notepad++7.3.1
Easy-to-use and free code editor