September 29, 2025
How to Scrape Google Images With Python
TL;DR
Google Images is a valuable source for datasets, product research, and SEO—but it’s protected with dynamic rendering and anti-bot systems. To scrape it, you need headless browsers like Playwright or Selenium and a reliable proxy layer. Use Ping Network’s universal bandwidth layer to route through real residential IPs, apply sticky sessions, rotate when needed, and geo target results. This keeps scrapers stable while scaling across regions.
Introduction
Manually saving files from Google Images doesn’t scale. With Python and a headless browser, you can automate the collection of image URLs, metadata, and licensed assets.
The challenge: Google’s dynamic DOM, infinite scroll, and anti-bot protections. Without realistic behavior and stable IPs, you’ll hit CAPTCHAs or bans quickly.
This guide shows you how to:
The challenge: Google’s dynamic DOM, infinite scroll, and anti-bot protections. Without realistic behavior and stable IPs, you’ll hit CAPTCHAs or bans quickly.
This guide shows you how to:
- Build a Google Images scraper in Python
- Extract URLs or high-resolution assets
- Handle infinite scroll and side panels
- Keep sessions stable using Ping Network’s residential proxies with global coverage, API-first rotation, and on-demand scaling
Is It Legal to Scrape Google Images?
- Terms of Service: Google restricts automated scraping. Metadata like URLs is lower risk than downloading files.
- Copyright: Many images are protected. Always confirm licenses before reusing content commercially.
- Best practices: Respect robots.txt, throttle requests, and scrape responsibly.
How Google Images Renders Results
- Infinite scroll: New results load continuously.
- Dynamic DOM: Thumbnails and links are buried in generated markup.
- Full resolution: Only visible after clicking into the side viewer.
Tools You Need
- Python 3.x
- Headless browser: Playwright (recommended) or Selenium
- Parser: BeautifulSoup or Playwright’s locator methods
- HTTP client: requests or httpx for downloads
- Data utils: pandas for structured exports; Pillow/OpenCV for validation
- Proxy layer: Ping Network’s residential proxies for realism, rotation, and geo targeting
Scraping Strategy
- Open Google Images with a real User-Agent.
- Submit your search query.
- Scroll gradually to load more thumbnails.
- Collect thumbnail metadata.
- Click each result to extract the high-resolution URL.
- Save metadata and download only licensed images.
- Pace your actions and rotate IPs as needed.
Code Example: Playwright + Python (URLs Only)
import asyncio, json
from datetime import datetime
from playwright.async_api import async_playwright
QUERY = "sunset mountains"
RESULTS = 100
SCROLL_PAUSE = 1.2
PROXY = "http://username:password@HOST:PORT" # Ping proxy (add geo/session params if needed)
async def run():
async with async_playwright() as p:
browser = await p.chromium.launch(
headless=True,
proxy={"server": PROXY} if PROXY else None
)
context = await browser.new_context(
user_agent="Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
"AppleWebKit/537.36 (KHTML, like Gecko) Chrome/122.0.0.0 Safari/537.36",
viewport={"width": 1366, "height": 900}
)
page = await context.new_page()
await page.goto("https://www.google.com/imghp", wait_until="domcontentloaded")
# Handle consent dialog
try:
await page.click("button:has-text('I agree')", timeout=2000)
except:
pass
await page.fill("input[aria-label='Search for images']", QUERY)
await page.keyboard.press("Enter")
await page.wait_for_selector("div#islmp")
collected = set()
last_height = 0
while len(collected) < RESULTS:
thumbs = await page.locator("img[jsname='Q4LuWd']").element_handles()
for t in thumbs:
src = await t.get_attribute("src")
data_src = await t.get_attribute("data-src")
if src: collected.add(src)
if data_src: collected.add(data_src)
if len(collected) >= RESULTS:
break
await page.mouse.wheel(0, 3000)
await asyncio.sleep(SCROLL_PAUSE)
try:
await page.click("text=Show more results", timeout=1000)
except:
pass
new_height = await page.evaluate("document.body.scrollHeight")
if new_height == last_height and len(collected) >= RESULTS:
break
last_height = new_height
data = [{"query": QUERY, "img": url, "scraped_at": datetime.utcnow().isoformat()}
for url in list(collected)[:RESULTS]]
with open("google_images_urls.json", "w", encoding="utf-8") as f:
json.dump(data, f, ensure_ascii=False, indent=2)
await browser.close()
asyncio.run(run())Getting Full-Resolution Images
- Click each thumbnail → open the side viewer.
- Parse the high-resolution <img> element.
- Download files only if licenses permit.
Adding Ping Network Proxies
Scraping Google Images at scale requires IP hygiene. With Ping Network you can:
- Route through real residential IPs for natural traffic patterns.
- Use sticky sessions for multi-step flows.
- Rotate IPs for retries or bulk discovery.
- Geo target results to compare across regions.
http://username:password@HOST>:PORT
http://username=session-abc123-country-us:password@HOST>:PORTApply in Playwright’s launch(proxy=...) or Selenium’s proxy config.
Common Challenges & Fixes
- CAPTCHAs/blocks → Slow scroll speed, add jitter, rotate IPs.
- Only thumbnails → Click to reveal the side viewer.
- Infinite scroll stalls → Trigger “Show more results.”
- UI changes → Use resilient selectors (data-testid, XPath).
Responsible Image Use
- Use Google’s usage-rights filter.
- Favor public domain or Creative Commons sources.
- Follow attribution and licensing requirements.
Best Practices for Scale
- Respect robots.txt and ToS.
- Set per-host concurrency caps.
- Add exponential backoff for 429s/5xx.
- Store timestamps + original source URLs.
- Validate and deduplicate images by hash.
- Run smoke tests to detect selector drift.
FAQ
Is Playwright better than Selenium here?
Yes—Playwright is faster and more ergonomic for dynamic content. Selenium works but is heavier.
How do I get region-specific results?
Route queries via Ping Network’s residential IPs in your target country or city.
Can I always download the original image?
Only if exposed in the side panel—and only if the license allows.
What if I still get blocked?
Reduce request rate, randomize delays, rotate IPs, and adjust headers. Break tasks into smaller batches.
Conclusion
Scraping Google Images with Python is straightforward once you combine:
Book a call with our team and explore Ping Network’s proxy infrastructure.
📖 Docs
- A headless browser (Playwright/Selenium)
- Robust selectors & scroll logic
- Residential proxies for natural traffic
- Real residential IPs
- API-first rotation & geo targeting
- Sticky sessions for consistent flows
- On-demand scaling for large datasets
Book a call with our team and explore Ping Network’s proxy infrastructure.
📖 Docs