Scraping eBay in 2025 remains one of the most effective ways to collect price data, track product trends, and analyze competitors—especially with e-commerce growing rapidly. The demand for accurate, real-time insights has increased significantly, making scraped data incredibly valuable for sellers, analysts, and researchers.

At the same time, eBay has strengthened its anti-bot protection with tighter rate limits, CAPTCHA challenges, and behavior-based detection. That means scraping now requires smarter techniques—simply fetching HTML isn't enough. Your scraper must behave more like a real user.

Python continues to be the best option for solving these challenges. Libraries like Requests, BeautifulSoup, Selenium, and Playwright help you scrape static, dynamic, or JavaScript-heavy pages. Combined with rotating user agents, proxies, and random delays, your scraping becomes far more stable and undetected.

This guide covers the latest scraping methods for 2025, including code examples, anti-CAPTCHA strategies, and best practices.

What Is Web Scraping on eBay?

Web scraping on eBay is the process of automatically collecting information from product pages, search results, or seller listings using scripts.

You can extract data such as:

• Product titles
• Prices
• Item conditions
• Units sold
• Seller ratings
• Shipping info
• Seller locations
• Product images

This data is extremely useful for market research, price tracking, competitor analysis, product comparison tools, and more.

Scraping eBay does come with challenges due to its anti-bot systems, so you’ll need modern tools like Playwright, Selenium, user-agent rotation, and delays. Don’t worry—this guide walks you through every step.

What Data Can We Extract From eBay?

Here are the most useful data points:

1. Product Title

Example: Apple iPhone 14 Pro Max 256GB – Deep Purple

2. Price

Essential for price tracking and competitive analysis.

3. URL

Each product has a unique link you can store.

4. Item Condition

New, Used, Refurbished, etc.

5. Seller Rating

Example: 98.5% positive feedback

6. Units Sold

Example: 1,245 sold

Great for discovering top-selling items.

7. Seller Location

Useful for regional market research.

8. Main Image

Helps you build visual dashboards.

9. Shipping Info

Example:

• Free shipping
• $12.99 shipping
• Ships in 2–3 days

eBay Page Structure (2025 Update)

A standard search result item looks like this:

<li class="s-item">
  <a class="s-item__link" href="https://www.ebay.com/itm/example">
    <span class="s-item__title">Product Title</span>
    <span class="s-item__price">$499.99</span>
  </a>
</li>

Key selectors to scrape:

• .s-item__title
• .s-item__price
• .s-item__link

More eBay HTML Variants (2025)

Example 1 — With Image + Shipping

<li class="s-item">
  <div class="s-item__image-section">
    <img class="s-item__image-img" src="image.jpg" />
  </div>
  <a class="s-item__link" href="https://www.ebay.com/itm/abc123">
    <h3 class="s-item__title">Apple iPhone 13 Pro Max</h3>
    <span class="s-item__price">$799.00</span>
    <span class="s-item__shipping">+$12.99 shipping</span>
  </a>
</li>

Example 2 — Sponsored Listing

<li class="s-item s-item--sponsored">
  <a class="s-item__link" href="https://www.ebay.com/itm/xyz789">
    <span class="s-item__title">Samsung Galaxy S22 Ultra 5G</span>
    <span class="s-item__price">$999.00</span>
    <span class="s-item__subtitle">Sponsored</span>
  </a>
</li>

Example 3 — Dummy Block

<li class="s-item s-item--explore-more">
  <span class="s-item__title">Explore similar items</span>
</li>

Scraping eBay with Requests + BeautifulSoup (Simple & Fast)

Install dependencies:

pip install requests beautifulsoup4

Full Python Code

import requests
from bs4 import BeautifulSoup

def scrape_ebay(query):
    url = f"https://www.ebay.com/sch/i.html?_nkw={query}"
    headers = {
        "User-Agent": "Mozilla/5.0"
    }

    response = requests.get(url, headers=headers)
    soup = BeautifulSoup(response.text, "html.parser")

    results = []

    for item in soup.select(".s-item"):
        title = item.select_one(".s-item__title")
        price = item.select_one(".s-item__price")
        link = item.select_one(".s-item__link")

        if not title or not price or not link:
            continue

        results.append({
            "title": title.get_text(strip=True),
            "price": price.get_text(strip=True),
            "url": link.get("href")
        })

    return results


items = scrape_ebay("iphone 14 pro")
for i in items[:10]:
    print(i)

Scraping eBay with Playwright (Best for 2025)

For JavaScript-heavy or protected pages, Playwright is more reliable.

Install:

pip install playwright
playwright install

Full Code

from playwright.sync_api import sync_playwright

def scrape_ebay_playwright(query):
    with sync_playwright() as pw:
        browser = pw.chromium.launch(headless=True)
        page = browser.new_page()
        page.goto(f"https://www.ebay.com/sch/i.html?_nkw={query}")

        page.wait_for_selector(".s-item")
        cards = page.locator(".s-item")

        results = []

        for i in range(cards.count()):
            card = cards.nth(i)

            if not card.locator(".s-item__title").count():
                continue

            title = card.locator(".s-item__title").inner_text()
            price = card.locator(".s-item__price").inner_text() if card.locator(".s-item__price").count() else None
            link = card.locator(".s-item__link").get_attribute("href")

            results.append({
                "title": title,
                "price": price,
                "url": link
            })

        browser.close()
        return results


items = scrape_ebay_playwright("macbook pro")
for item in items[:10]:
    print(item)

Exporting eBay Data to CSV

pip install pandas

import pandas as pd

df = pd.DataFrame(items)
df.to_csv("ebay_results.csv", index=False)

eBay API vs Web Scraping

Conclusion

Scraping eBay in 2025 remains a powerful way to gather real-time market data and track pricing trends. With e-commerce competition rising, collecting accurate, fast insights gives sellers and analysts a strong edge.

However, eBay's stronger anti-bot systems mean traditional scraping isn't enough anymore. You’ll need browser automation, user-agent rotation, proxy usage, and realistic behavior patterns.

With tools like Requests, BeautifulSoup, and especially Playwright, you can build modern scrapers that stay undetected and collect clean data efficiently.

Python gives you everything needed to build scalable, resilient scraping systems for 2025 and beyond.