Название: Python Web Scraping for Developers: Extracting Data from Websites Using Practical Python Автор: Stephen G Schmitt Издательство: Independently published Год: October 7, 2024 Страниц: 149 Язык: английский Формат: pdf, azw3, epub, mobi Размер: 10.1 MB
Python is of the most popular and versatile programming languages in the tech industry. However, despite their popularity and versatility, mastering them can be challenging, especially for beginners. Technical challenges such as debugging and tight deadlines can cause stress and anxiety, and career advancement and staying up to date with the latest developments in the field can be daunting.
The process of extracting data from websites is called web scraping. Sometimes you can find it referred to as web harvesting as well. The term typically refers to an automated process that is created with intention to extract data using a bot or a web crawler. Sometimes the concept of web scraping is confused with web crawling. For this reason, we have covered this issue in our other blog post about the main differences between web crawling and web scraping.
Programmers skilled in programming languages like Python can develop web data extraction scripts, so-called scraper bots. Python advantages such as diverse libraries, simplicity, and active community make it the most popular programming language for writing web scraping scripts. These scripts can scrape data in an automated way. They send a request to a server, visit the chosen URL, go through every previously defined page, HTML tag, and components. Then they pull data from them.
Scripts that are used to extract data can be custom-tailored to extract data from only specific HTML elements. The data you need to get extracted depends on your business goals and objectives. There is no need to extract everything when you can specifically target just the data you need. This will also put less strain on your servers, reduce storage space requirements, and make data processing easier.
An increasing number of websites are using frontend frameworks like Vue.js or React.js. Such frameworks employ backend APIs to fetch data and rendering to draw the DOM (Document Object Model). Regular HTML client wouldn’t render the javascript code; thus, without a headless browser, you’d get an empty page. Also, websites often detect if HTTP clients are bots. In this case, headless browsers can aid in accessing the target HTML page. The most popular APIs for headless browsers are Selenium, Puppeteer, and Playwright.
Here what you'll learn after downloading this book:
- Extract Data from A Website - Make Web Scraping Faster - Best No-Code Scrapers - Web Scraping with Scrapy - Asynchronous Web Scraping With Python & AIOHTTP - Pagination In Web Scraping: How Challenging It May Be - Puppeteer Tutorial: Scraping With a Headless Browser - Bypass CAPTCHA With Puppeteer - Puppeteer on AWS Lambda - Scrape Images from a Website With Python - Guide to Scraping Data from Websites to Excel with Web Query - Guide to Extracting Website Data by Using Excel VBA - Guide to Using Google Sheets for Basic Web Scraping - Web Scraping for Machine Learning - Use ChatGPT for Web Scraping in 2023 And more…
This Book Is Perfect For:
- Total beginners with zero programming experience - Returning professionals who haven’t written code in years - Seasoned professionals looking for a fast, simple, crash course in Python
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