How to Scrape DuckDuckGo Results? A Guide to Stable Crawling with Proxies

As online privacy becomes increasingly valued, DuckDuckGo has grown rapidly with its “no tracking” promise, making it a rising source for web data among engineers and market analysts. However, its unique mechanism and anti-bot strategies pose challenges, especially when trying to obtain search results across multiple countries. Simple requests aren’t enough.

This guide walks you through real-world scraping scenarios, three viable scraping strategies, common pitfalls, and Python code examples. We’ll also show you how to build a stable, scalable, and geolocated DuckDuckGo data extraction setup using proxy services from kookeey.

1. Why Scrape DuckDuckGo?

While DuckDuckGo isn’t the global leader in search engine share, its privacy-first and ad-free approach gives it significant traction in Western markets. More importantly, its results aren’t heavily influenced by user history or location, making it a valuable source for:

• Global SEO rank tracking for cross-border brands
• Regional sentiment comparison for search terms
• Keyword and long-tail trend analysis

But to extract meaningful insights, you need to access original search pages from different regions—not just local browser versions with personalized content.

2. Common Technical Issues When Scraping DuckDuckGo

DuckDuckGo’s minimalist UI might seem easy to scrape, but underneath lie several challenges:

• IP-sensitive responses: Frequent requests from the same IP often trigger empty results or captchas
• Location-specific content: A keyword in the US returns different results than in Germany or Japan
• Dynamic pagination: Search result pages often rely on JavaScript
• Anti-crawling filters: Irregular headers or high-frequency requests can easily get blocked

That’s why you’ll need a robust proxy IP strategy and smart request scheduling to scrape DuckDuckGo reliably.

3. Three Scraping Approaches – Which Fits You Best?

Method 1: Static HTML Scraping (Lightweight)

DuckDuckGo offers a plain HTML interface (https://html.duckduckgo.com/html) that can be parsed with requests + BeautifulSoup.

We recommend using datacenter proxies here for their cost-efficiency and speed. For improved reliability and lower block rates, residential rotating proxies can automatically switch IPs and simulate organic traffic behavior.

Method 2: Dynamic Rendering (For Paginated or Rich Content)

Use tools like Playwright or Puppeteer to emulate full browser behavior and retrieve all paginated content or interactive elements.

Pairing this method with residential rotating proxies ensures smooth IP rotation and country-level targeting. If you are emulating mobile user behavior (e.g., scrolls, taps, or mobile UIs), then it’s best to switch to mobile proxies. Based on real SIM cards connected via 4G/5G networks, they provide the most natural mobile traffic profile and help you avoid automation detection. This is especially useful in mobile SEO or app-related scraping.

Method 3: Batch Crawling System (For Keywords x Countries)

Design a task queue system using Celery + MongoDB. Each task pairs a keyword with a location (e.g., “chatgpt”, “UK”). Rotate proxy IPs via API for each request.

kookeey offers API access to 47M+ rotating IPs across 41+ countries, with precise geolocation support. This forms a solid base for any scalable scraping operation.

4. Python Example: HTML Interface with BeautifulSoup

import requests
from bs4 import BeautifulSoup

query = "python proxy scraping"
url = f"https://html.duckduckgo.com/html/?q={query}"

proxies = {
    "http": "http://username:password@proxy.kookeey.com:8000",
    "https": "http://username:password@proxy.kookeey.com:8000"
}

headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64)"
}

resp = requests.get(url, headers=headers, proxies=proxies)
soup = BeautifulSoup(resp.text, 'html.parser')

for result in soup.select('.result__title'):
    print(result.get_text(strip=True))

This script demonstrates fetching results from DuckDuckGo and extracting search titles. For higher scale and geographic control, consider multi-threading and a proxy rotation framework.

5. Building a Scalable Scraper Architecture

Need to monitor 50 keywords in 10 countries every hour? Here’s a modular approach:

1. Task queue: holds (keyword + region) pairs
2. Proxy manager: assigns the right proxy (kookeey rotating proxy by region)
3. Scraper engine: hybrid of requests and browser automation
4. Storage: outputs JSON or CSV for downstream SEO or ad analytics

kookeey proxies include residential IPs, datacenter IPs, and mobile proxies, all with flexible rotation and failover features—perfect for stable, large-scale scrapers.

6. Conclusion: DuckDuckGo Scraping Requires Full Environment Control

Search scraping isn’t just about fetching HTML—it’s about simulating a realistic user environment. From headers to cookies, IPs to traffic pacing, everything needs to be just right.

kookeey offers four types of proxies tailored to different needs:

• Rotating residential proxies: Ideal for stable, country-specific web scraping with automatic IP change
• Datacenter proxies: High-speed, cost-efficient option for fast batch crawling
• Static residential proxies: Great for account farming or ad delivery simulation (not recommended for high-frequency scraping)
• Mobile proxies: Real SIM-based 4G/5G IPs that mimic smartphone users, perfect for stealth-critical scraping and mobile behavior emulation

Choose the right tools and you’ll unlock the full data value from DuckDuckGo.

Ready to build your keyword intelligence radar? Start with kookeey proxy services today!