One‑Line Python Web Scraping with Scrapeasy: Installation, Usage, and Media Download Guide
This article introduces the Scrapeasy Python library, explains how to install it with a single pip command, and demonstrates step‑by‑step code examples for initializing websites, extracting links, images, videos, and other files, highlighting its ease of use for fast web data extraction.
Scrapeasy is a Python library that enables one‑line web scraping, allowing users to fetch data from websites, PDFs, and HTML tables with minimal code.
Key features include one‑click site crawling, handling of common media types (links, images, videos), and support for special file formats such as .php and .pdf.
Installation
<code>$ pip install scrapeasy</code>Basic usage
Import the required classes and create a Website object with the target URL:
<code>from scrapeasy import Website, Page
web = Website("https://tikocash.com/solange/index.php/2022/04/13/how-do-you-control-irrational-fear-and-overthinking/")</code>Retrieve all sub‑page links:
<code>links = web.getSubpagesLinks()</code>Fetch all images on the site:
<code>images = web.getImages()</code>Download all images to a local folder:
<code>web.download("img", "fahrschule/images")</code>Obtain domain links only:
<code>domains = web.getLinks(intern=False, extern=False, domain=True)</code>Obtain all external links (non‑domain):
<code>domains = web.getLinks(intern=False, extern=True, domain=False)</code>Working with a single page, e.g., a W3Schools video page:
<code>w3 = Page("https://www.w3schools.com/html/html5_video.asp")
w3.download("video", "w3/videos")
video_links = w3.getVideos()</code>Download specific file types such as PDFs or PHP files using the generic .get() or .download() methods:
<code>calendar_links = Page("https://tikocash.com").get("php")
Page("http://mathcourses.ch/mat182.html").download("pdf", "mathcourses/pdf-files")</code>In summary, Scrapeasy provides a concise, high‑level API for web crawling and data extraction, making Python a powerful tool for web scraping and data mining tasks.
Python Programming Learning Circle
A global community of Chinese Python developers offering technical articles, columns, original video tutorials, and problem sets. Topics include web full‑stack development, web scraping, data analysis, natural language processing, image processing, machine learning, automated testing, DevOps automation, and big data.
How this landed with the community
Was this worth your time?
0 Comments
Thoughtful readers leave field notes, pushback, and hard-won operational detail here.