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How to scrape project data from Kickstarter.com using Python?
Scraping project data from Kickstarter.com using Python allows you to collect details like project titles, goals, and funding amounts. Using requests for HTTP calls and BeautifulSoup for HTML parsing, Python provides a straightforward solution for extracting structured data. Below is an example script to scrape Kickstarter project information.
import requests from bs4 import BeautifulSoup # Target URL url = "https://www.kickstarter.com/discover/categories/technology" headers = { "User-Agent": "Mozilla/5.0" } response = requests.get(url, headers=headers) if response.status_code == 200: soup = BeautifulSoup(response.content, "html.parser") projects = soup.find_all("div", class_="project-card") for project in projects: title = project.find("h3").text.strip() if project.find("h3") else "Title not available" goal = project.find("span", class_="goal").text.strip() if project.find("span", class_="goal") else "Goal not available" pledged = project.find("span", class_="pledged").text.strip() if project.find("span", class_="pledged") else "Pledged amount not available" print(f"Title: {title}, Goal: {goal}, Pledged: {pledged}") else: print("Failed to fetch Kickstarter page.")This script extracts project titles, funding goals, and pledged amounts from Kickstarter. Pagination support allows scraping additional projects by navigating through the “Next” button. Adding random delays between requests helps avoid detection.
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3 Replies
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Pagination is essential for scraping a complete dataset from Kickstarter. Projects are often distributed across multiple pages, so automating navigation through the “Next” button ensures that all data is collected. Adding random delays between requests mimics human browsing behavior. Proper pagination handling makes the scraper more effective for detailed analysis of Kickstarter trends.
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Error handling ensures the scraper remains functional despite changes in Kickstarter’s page layout. Missing elements, such as funding goals or pledged amounts, could cause the script to fail without proper checks. Adding conditions for null values prevents crashes and allows the scraper to skip problematic elements. Regular updates to the script ensure it adapts to Kickstarter’s changes.
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Using rotating proxies and random user-agent headers is essential for avoiding detection by Kickstarter’s anti-scraping systems. Multiple requests from the same IP or browser fingerprint can lead to blocks. Rotating these attributes and randomizing request intervals helps maintain anonymity. These practices are vital for long-term scraping projects.
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