What is HTML?
HTML (Hypertext Markup Language) is the standard language for creating web pages. It's the code that defines the structure and content of every website you visit, using tags to mark up text, images, links, and other elements. When you view a web page, your browser reads HTML code and renders it as the formatted, interactive content you see on screen.
In web scraping, HTML is the raw material you're working with. Every page you scrape contains HTML that structures the data you want to extract. Understanding HTML helps you target the right elements, write better selectors, and troubleshoot when scraping doesn't work as expected. You don't need to be an HTML expert to scrape effectively, but knowing the basics makes everything easier.
How HTML structures web pages
HTML organizes content using elements wrapped in tags that tell browsers how to display information.
Tags are the building blocks, written with angle brackets. An opening tag like <p> starts a paragraph, and a closing tag like </p> ends it. Everything between these tags is the paragraph content. Most HTML elements follow this pattern with opening and closing tags surrounding content.
Elements nest inside each other to create hierarchy. A div might contain multiple paragraphs, each paragraph might contain links or bold text, and those elements might contain more nested elements. This nesting creates the tree-like structure that browsers parse and scrapers navigate.
Attributes add information to tags. They appear inside opening tags and provide details like IDs, classes, URLs, or custom data. A link tag looks like <a href="https://example.com">Click here</a>, where href is an attribute specifying the link destination. Attributes are crucial for web scraping because they often contain or identify the data you want.
Common HTML elements for web scraping
Certain HTML elements appear constantly in scraping projects because they typically contain the data you need.
Headings (h1, h2, h3, h4, h5, h6) organize content hierarchically. Product names often live in h1 or h2 tags. Section titles use h3 or h4. When scraping, headings usually contain important identifiers or names you want to extract.
Paragraphs (p) hold blocks of text like product descriptions, article content, or general information. Scraping paragraphs captures descriptive content that doesn't fit into structured fields.
Links (a) connect pages together. The href attribute contains URLs you might need to follow for detail page extraction or to collect related content. The link text (between opening and closing tags) often describes what you'll find at that URL.
Images (img) display pictures using the src attribute to specify the image file location. Scraping images means extracting these src URLs so you can download or reference the actual image files.
Divs (div) are generic containers that group related content. Sites use divs extensively to structure layouts, often with class names like "product-card" or "listing-item" that identify repeating elements you want to scrape.
Spans (span) are inline containers for styling or grouping text within larger elements. Prices, ratings, or labels often live in span tags with identifying classes.
Lists (ul, ol, li) organize related items. Unordered lists (ul) create bullet points, ordered lists (ol) create numbered lists, and list items (li) are the individual entries. Product features, navigation menus, and categorical information often use list structures.
Tables (table, tr, td, th) organize data in rows and columns. Table rows (tr) contain table data cells (td) or table header cells (th). Specifications, pricing tiers, and structured comparisons often appear in tables, making them important extraction targets.
HTML attributes important for scraping
Attributes provide the metadata and identifiers that make targeted scraping possible.
class assigns one or more CSS classes to elements. Sites use classes to style similar elements consistently, which means items sharing a class (like "product-price") contain the same type of data. This makes class attributes perfect for writing selectors that target specific data across multiple items.
id provides a unique identifier for a single element on a page. Because IDs should be unique, they're reliable targets when you need to extract data from one specific element like the main heading or a particular section.
href appears in link tags (a) and specifies the destination URL. Scraping href attributes lets you collect links to follow for deeper extraction or to gather related page URLs.
src appears in image tags (img) and script tags, specifying the source file location. For images, this is the actual image URL you need if you want to download or reference product photos.
data-* attributes store custom data that JavaScript or applications use. Sites often put product IDs, prices, or other structured information in data attributes like data-product-id or data-price. These attributes frequently contain clean, structured values perfect for scraping.
title and alt provide descriptive text. Title attributes add tooltip text, while alt attributes describe images for accessibility. This text sometimes contains information that doesn't appear visibly on the page but is still valuable to extract.
Reading HTML source code
Viewing and understanding HTML source helps you identify what to scrape and how to target it.
Right-click any element on a web page and select "Inspect" or "Inspect Element" to open browser developer tools. This shows you the HTML for that specific element, highlighting its tags, attributes, and position in the page structure. You can navigate through nested elements, see exactly what classes and IDs apply, and understand how data is organized.
The Elements panel in developer tools displays the complete DOM tree. You can expand and collapse sections, hover over elements to see them highlight on the page, and search for specific tags or text. This live view updates as you interact with the page, showing how JavaScript modifies the HTML.
View the raw HTML source by right-clicking the page and selecting "View Page Source" or pressing Ctrl+U. This shows the initial HTML the server sent, before JavaScript made any modifications. Comparing this with the inspected elements reveals what content loads dynamically, which matters for scraping strategy.
HTML vs DOM
Understanding this distinction prevents confusion about what you're actually scraping.
HTML is the text-based markup code the server sends to your browser. It's static source code that describes how the page should be structured. When you make a basic HTTP request and receive a response, you get HTML as text.
The DOM (Document Object Model) is the live, interactive representation your browser creates by parsing that HTML. The browser converts text markup into a tree of objects you can navigate and manipulate. JavaScript can modify the DOM, adding elements, changing text, or altering attributes without changing the original HTML.
For web scraping, this matters because modern sites heavily use JavaScript to build content dynamically. The initial HTML might be minimal, with JavaScript filling in actual content after the page loads. Simple HTTP requests only get the initial HTML. Scraping these sites requires rendering the DOM so JavaScript executes and content appears, just like in a real browser.
HTML parsing in web scraping
Converting raw HTML into navigable structure is the first step of every scraping operation.
When your scraper receives HTML from a web server, it's just a long string of text with tags and content mixed together. Parsing transforms this text into a structured tree you can navigate using selectors. The parser reads through the HTML, identifies tags and their relationships, and builds a hierarchical representation where you can easily find specific elements.
Most scraping tools parse HTML automatically. You send a request, receive HTML, and the tool parses it behind the scenes before you write selectors to target elements. You never see the parsing step, but it's essential infrastructure that converts raw code into queryable structure.
Broken or malformed HTML can cause parsing problems. Real websites often contain unclosed tags, improperly nested elements, or other violations of HTML standards. Modern parsers handle most of these gracefully, correcting obvious mistakes to build usable document structures. But severely malformed HTML might parse incorrectly, causing your selectors to miss elements or find them in unexpected places.
Common HTML patterns in web scraping
Recognizing typical HTML structures helps you scrape more effectively.
Repeating containers mark items in lists or grids. An e-commerce page might have a div with class "product-grid" containing multiple divs with class "product-card". Each card follows the same HTML structure with product names in h3 tags, prices in span tags, and images in img tags. Recognizing this pattern lets you target one card, identify its data structure, then apply that extraction pattern to all cards.
Nested data structures contain information at multiple levels. A product card might contain top-level information like name and price, but also nested review sections with ratings and comments. Understanding the nesting helps you navigate to exactly the data you need.
Semantic HTML uses meaningful tag names that describe content. Header tags contain headers, nav tags contain navigation, article tags contain article content. When sites use semantic HTML properly, identifying target content becomes easier because tag names indicate purpose.
Class-based organization uses descriptive class names to identify content types. Classes like "price", "product-title", "rating", or "description" explicitly label what data each element contains. This makes selector writing straightforward because you target classes that match your data needs.
How Browse AI handles HTML
Traditional web scraping requires reading HTML source, understanding tag structures, writing selectors that navigate nested elements, and debugging when HTML changes break your extraction. This technical barrier prevents many people from collecting web data they need.
Browse AI eliminates the need to read or understand HTML directly. Instead of inspecting source code and writing selectors, you simply click on the data you want in your browser. The platform analyzes the underlying HTML automatically, determines how to target those elements, and extracts data without requiring you to see or write HTML selectors.
When websites change their HTML structure, traditional scrapers break because selectors no longer match the new markup. Browse AI's visual approach makes updates simple. You click the data in its new location, and the platform adapts to the new HTML structure automatically. This turns HTML maintenance from a technical challenge requiring code changes into a visual workflow that anyone can handle.
The platform also handles HTML parsing, DOM rendering, and JavaScript execution automatically. You don't need to understand the difference between initial HTML and dynamically loaded content, or configure rendering engines. Browse AI manages all HTML processing behind the scenes, letting you focus on what data you need rather than how HTML structures that data.
