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This article compiles twenty‑three Python web‑scraping projects, each described with its purpose, key features, and a direct GitHub repository link, offering developers a ready‑made toolbox for data collection across platforms such as WeChat, DouBan, Zhihu, Bilibili, and more.
This article presents a practical Python web crawler that retrieves Douban movie data, offers ranking and keyword search, displays details via a Tkinter GUI, lists free streaming sources, and discusses configuration steps, features, known issues, and core code snippets.
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This article demonstrates how to use Python's requests and BeautifulSoup libraries to scrape current and 14‑day weather data from China Weather Network, store it in CSV files, and then apply pandas, numpy, and matplotlib for comprehensive visual analysis of temperature, humidity, air quality, wind direction, and climate distribution.
This tutorial demonstrates how to use Python libraries such as requests and Pillow to scrape individual Chinese characters, resize them, compose them onto a background image, and output a customized "Fu" couplet image, complete with full source code and usage instructions.
This tutorial explains how to use Python 3 with Requests, lxml, and Baidu's AipFace SDK to crawl images from Zhihu's "beauty" topic, filter them by face detection and gender criteria, and store the qualified pictures locally.
This tutorial shows how to use Python to crawl Douban's Top250 movie list, handle anti‑scraping measures, extract detailed fields, store the data in Excel, and perform data cleaning, statistical analysis, and visualizations such as year distribution, rating trends, and genre word clouds.
This tutorial demonstrates how to use Python's urllib module to simulate browser requests, parse HTML with Beautiful Soup, extract text and image URLs, and store the scraped data locally using file I/O and the with statement, providing complete code examples.
This article explains why web servers block crawlers, how to identify a browser's User-Agent (using Chrome as an example), and demonstrates step‑by‑step how to disguise a scraper as a browser to retrieve the CSDN homepage and its article list.
This tutorial walks through analyzing a website’s image categories, constructing parameterized URLs, creating a Tkinter GUI to select download paths and categories, handling filename issues, and finally packaging the Python scraper as a standalone executable.