How Does a Web Scraper Work?
Web scrapers are tools that collect information from websites and turn it into structured data you can store, search, or analyze. They can be as simple as a short script that reads one page, or as complex as a system that crawls thousands of pages, handles logins, and tracks updates over time.
What a Web Scraper Actually Does
A web scraper automates what a person does manually: open a web page, look at the content, and copy the parts they need. The difference is that a scraper follows a repeatable process:
- Request a page (or load it like a browser would)
- Receive the page content
- Find the specific elements that contain the target data
- Extract and clean the data
- Save it in a useful format (CSV, JSON, database, etc.)
Some scrapers also follow links to other pages, creating a loop: fetch, parse, extract, follow.
Step 1: Fetching the Web Page
To read a website, the scraper first needs the page content. There are two common ways to get it.
HTTP Requests (Static HTML)
Many pages can be downloaded with a direct HTTP request. The server responds with HTML markup, plus headers and sometimes cookies. For these sites, the scraper can parse the HTML immediately.
This is quick and lightweight, and it’s often used for:
- News articles
- Product listings where content is present in the initial HTML
- Public directories
Browser Automation (JavaScript-Rendered Pages)
Some sites build the page using JavaScript after the initial HTML loads. In that case, the first response may contain only a basic template, while the real content arrives later through background requests.
A scraper can handle this by using a headless browser (a real browser running without a visible window). It loads the page, runs scripts, waits for elements to appear, then reads the final rendered content.
Step 2: How It Reads Website Content
Once the scraper has the page source, it needs a way to interpret it.
Reading HTML as a Tree
HTML is not read like plain text. Scrapers typically convert it into a DOM (Document Object Model), a tree-like structure of elements such as:
<div>containers<a>links<table>rows and cells<span>labels- Attributes like
class,id, andhref
This lets the scraper query the page in a precise way, such as:
- “Find all product cards”
- “Inside each card, get the title text and price”
- “Get the link to the details page”
Selectors: The Scraper’s Targeting System
To locate data, scrapers rely on selectors:
- CSS selectors (like
.priceordiv.card a.title) - XPath expressions (more verbose, but powerful for complex trees)
After selecting elements, the scraper reads:
- Text content (what you see on the page)
- Attributes (URLs, IDs, metadata)
- Nested values (items within a list or table)
Step 3: Extracting and Cleaning Data
Raw page content often needs cleanup. A scraper might:
- Strip extra whitespace and line breaks
- Convert “\$1,299.00” into a numeric value
- Normalize dates into a standard format
- Join multi-part fields (first name + last name)
- Handle missing fields without crashing
This step is where scraped content becomes consistent data.
Step 4: Following Links and Pagination
Many targets span multiple pages. Scrapers detect and follow:
- “Next page” links
- Page number URLs
- Category links
- Detail pages linked from listings
To avoid getting stuck in loops, scrapers track visited URLs and apply rules such as allowed domains and URL patterns.
Common Obstacles a Scraper Handles
Websites may try to limit automated access, or simply have patterns that are tricky to parse. Scrapers often deal with:
- Rate limits and request throttling
- Session cookies and logins
- Changing page layouts
- Captchas and bot checks
- Content loaded via background API calls
In many cases, the cleanest approach is to identify the background request that returns JSON data and collect from that source instead of scraping rendered HTML.
Why Scrapers Break and How People Maintain Them
A scraper can fail when the site layout changes, class names get renamed, or fields move to different containers. Maintenance usually means:
- Updating selectors
- Adding fallback rules
- Writing tests that alert you when extracted fields go missing
- Monitoring error rates and response status codes
Web scraping works best as an ongoing process, not a one-time script, especially for sites that change frequently.
