Browser7

What Is Web Scraping?

Web scraping is the process of automatically extracting data from websites. Instead of manually visiting pages and copying information, a program reads the page for you and pulls out the specific data you need - product prices, job listings, contact information, reviews, or anything else that appears on a public web page.

How web scraping works

At a high level, web scraping involves three steps:

1. Fetch the page

Your program requests a web page, just like a browser does when you type a URL. The server responds with the page's HTML - the code that describes the page's structure and content. For simple websites, a basic HTTP request is enough. For modern JavaScript-heavy sites, you need a real browser to execute the JavaScript and render the full page.

2. Parse the HTML

Once you have the HTML, you use a parser to navigate its structure and find the data you want. HTML is organized in a tree of elements - headings, paragraphs, links, tables, lists. You write selectors (like CSS selectors or XPath expressions) that identify the specific elements containing your target data.

3. Extract and store the data

With the right elements identified, you extract the text, attributes, or links you need and save them in a structured format - a database, a spreadsheet, a JSON file, or wherever your application needs the data. This is the part where raw HTML becomes useful, structured information.

What it looks like in code

Here is a simple example that scrapes the top 5 story titles from Hacker News. Browser7 fetches and renders the page, then a parser extracts the titles from the HTML.

from browser7 import Browser7
from bs4 import BeautifulSoup

client = Browser7(api_key="b7_your_api_key")

# Render the page in a real browser and get the HTML
result = client.render("https://news.ycombinator.com")

# Parse the HTML and extract data
soup = BeautifulSoup(result.html, "html.parser")

for item in soup.select(".titleline > a")[:5]:
    print(item.get_text(strip=True))

That is a complete web scraper. Three lines to fetch the page, a few more to parse out the data you want. The complexity of web scraping comes not from the code itself, but from the challenges that real-world websites present - JavaScript rendering, anti-bot detection, CAPTCHAs, and rate limiting.

What people use web scraping for

Price monitoring

E-commerce businesses track competitor prices to stay competitive. Scraping product pages daily reveals pricing trends, promotions, and stock changes.

Market research

Analysts collect product catalogs, customer reviews, and industry data to understand markets. Web scraping turns scattered public information into structured datasets.

Lead generation

Sales teams build prospect lists from job boards, business directories, and company websites. Scraping collects thousands of leads in minutes.

SEO monitoring

SEO professionals track search engine rankings across countries and keywords. Scraping Google results shows exactly where a site ranks for each query.

Real estate data

Investors and analysts aggregate property listings from Zillow, Realtor.com, and local platforms to track market trends and find opportunities.

Academic research

Researchers collect data from social media, news sites, and public databases for studies in fields from economics to linguistics to public health.

Why web scraping is harder than it sounds

The concept is simple, but real-world websites present several challenges:

JavaScript rendering

Most modern websites use JavaScript to load their content. A simple HTTP request returns an empty page shell - you need a real browser to execute the JavaScript and get the actual content. This is the single biggest hurdle for beginners.

Anti-bot detection

Websites use systems like Cloudflare, DataDome, and Akamai to detect and block automated access. These systems check browser fingerprints, IP reputation, TLS signatures, and behavioral patterns.

CAPTCHAs

Sites serve CAPTCHAs to verify that visitors are human. Handling them programmatically requires either a solving service or an API that includes CAPTCHA solving.

Changing page structures

Websites update their HTML structure regularly. A scraper that works today might break tomorrow if the site changes its CSS classes or element hierarchy. Maintaining scrapers requires ongoing attention.

How Browser7 simplifies web scraping

Browser7 is a web scraping API that handles the hard parts - JavaScript rendering, proxy rotation, anti-bot bypass, and CAPTCHA solving - so you can focus on the data extraction. You send a URL, and you get back the fully rendered HTML as if you opened the page in your own browser.

Every request uses a real Chrome browser on a residential IP address. There is no infrastructure to manage, no browser to install, and no proxy pool to maintain. It costs $0.01 per page with everything included.

Where to go from here

If you are new to web scraping, these resources will help you get started:

Try web scraping yourself

100 free renders - enough to scrape any website and see how it works. No payment required.