Proxies for Web Scraping

Why use proxies for web scraping

Scrapers send many requests from one place, and that is exactly what websites rate-limit or block. A proxy pool spreads requests across many addresses, and a local IP lets you see the page that real visitors in a given country see, including local prices, languages and stock.

Typical jobs are price and availability monitoring, SERP and rank tracking, lead and listing research, ad verification and collecting public data for analytics.

• Price and stock monitoring across marketplaces and countries.
• Rank tracking and local SERP collection.
• Public data collection for analytics and AI datasets.
• Brand and listing monitoring.

Which proxy type fits

See the product pages for residential, mobile and ISP proxies, or compare all prices on the cheap proxies page.

A minimal rotating example

This sends ten requests through one rotating proxy line. Each request can leave from a different IP.

import requests

proxy = 'http://USERNAME:PASSWORD@HOST:PORT'
proxies = {'http': proxy, 'https': proxy}

for _ in range(10):
    r = requests.get('https://api.ipify.org', proxies=proxies, timeout=30)
    print(r.text)

Swap the line for a sticky one when your scraper needs cookies or a login to survive across requests.

How to set it up

1. Create an account and buy a small residential package to test your target.
2. In the generator choose the country, a rotating session and HTTP or SOCKS5.
3. Copy the proxy line into your scraper or framework (requests, Scrapy, Playwright, Puppeteer).
4. Check the success rate and traffic per page, then scale up the package.

Good practice

• Respect robots.txt, the site’s terms and sensible request rates.
• Add retries with back-off instead of hammering a failing URL.
• Keep cookies and headers consistent within a sticky session.
• Block images and fonts in headless browsers to save traffic and cost.
• See cheap proxies for ways to cut cost per page.