What is web scraping?

What is web scraping?

Web scraping is the process of extracting data from websites automatically, using a program that visits a page, reads its content and turns it into structured information that can be saved, analyzed and reused. Instead of copying and pasting data by hand for hours, a well-built scraper goes through dozens, hundreds or thousands of pages in minutes and delivers listings, prices, descriptions or any other public data in an organized format, such as a table, a text file or a database.

This technique has become a key piece of business and research: those who know how to collect data from the web make better-informed decisions about prices, products and markets. This article explains what web scraping is, what it is used for, how it works, the role played by crawlers or spiders, how it differs from using an API, and the legal rules and risks worth knowing before getting started.

What web scraping is used for

Web scraping applications are as varied as the data that exists on the internet. These are the most common uses in the business and academic world:

• Price comparison: an online store can check every day how much its competitors charge for the same products and adjust its prices or promotions with up-to-date information.
• Market research: collecting customer reviews, ratings, catalogs and search trends makes it possible to understand what the public demands and how supply behaves.
• Building listings and catalogs: real estate, job or product portals bring together, on a single site, information published across many different pages, and they do it with scraping.
• Competitor monitoring: tracking price changes, product launches, promotions or news from rivals helps react quickly to market movements.
• Academic and journalistic research: analyzing large volumes of public data, such as official records or scientific publications, is much easier when a program collects and organizes it.

In all these cases scraping does not create the information: it gathers and organizes it so that a person or a system can use it. The quality of the result depends both on the source data and on how it is processed.

How web scraping works

The basic mechanics are simpler than they seem. A website delivers to the browser a text document, usually in HTML, that describes the structure of the page: headings, paragraphs, images, links and tables. A scraping program does what the browser does, but instead of displaying the page it analyzes it and keeps the parts that matter.

1. Download the page: the program sends a request to the server and receives the HTML document, just as a browser would.
2. Interpret the structure: the content is organized into a tree of elements, where each tag indicates what each part of the page is.
3. Select the data: using rules called selectors, the program points out exactly which elements to extract, for example the price that appears inside a certain class.
4. Extract and clean: the data found is turned into clean text or numbers, without tags, extra spaces or leftover information.
5. Save the results: the information is stored in a spreadsheet, a file or a database, and the process can be repeated from time to time to keep it up to date.

The most common language for building scrapers is Python, which has specialized libraries for downloading pages, parsing documents and automating entire browsers; there are also visual tools that allow scraping without writing code. The core idea is always the same: automate a task that, done by hand, would be slow, expensive and prone to errors.

What a crawler or spider is

A crawler, also called a spider, is a program that moves across websites jumping from link to link, like a person who opens a page, clicks a link, then another one, and so on. Its job is to discover pages: it detects the links in each visited document, adds them to a to-do list and keeps moving until it has covered the ground that matters.

The difference from a scraper is one of focus: the crawler finds and visits pages, while the scraper extracts data from each specific page. In practice the two concepts are combined: a spider walks an entire product catalog and, on every product page it finds, a scraper extracts the name, price and availability. Search engines, for example, run on giant crawling systems that scan the web to index its content.

Web scraping vs. using an API

Many sites offer an official, orderly way to access their data: the API, that is, the application programming interface. When an API with the information you need exists, it almost always makes sense to use it before scraping. The difference between the two options is summarized in this table:

The practical rule is simple: if the site offers an API with the data you need, that is the fastest, most stable and most respectful option. Scraping remains the alternative for data the API does not deliver or for sites that offer none.

Is web scraping legal?

Web scraping is not illegal by itself: extracting public information from the internet is an everyday activity that search engines also do. Legality depends on how, what and where data is extracted. Accessing public information for legitimate purposes is usually acceptable, but scraping protected content, personal data or areas that the site explicitly blocks can violate laws and contracts.

To stay on the safe side, it is worth following these good practices:

• Respect the terms of use: many pages prohibit or limit automated extraction in their conditions; ignoring them can lead to complaints or loss of access.
• Check the robots.txt file: that file indicates which sections of the site allow programs in and which ones do not; following it is a basic sign of respect.
• Do not overload servers: sending thousands of requests per second affects the site and other users; the right approach is to space out requests and ask only for what is needed.
• Identify yourself: use a clear user agent that lets the site know that an automated program is accessing it and for what purpose.
• Protect personal data: collecting information about identifiable people is regulated in many countries; you must have a legal basis and handle the data responsibly.

Before building a scraper, it is worth asking whether the data is public, whether the site allows extraction and whether the intended use complies with the rules. When there are serious doubts, the opinion of a legal professional saves bigger problems later.

Risks and challenges of web scraping

Beyond the legal considerations, technical scraping has practical obstacles worth knowing before you start:

• IP blocks: servers detect automated access patterns and may block the address the requests come from.
• Captchas and verifications: many sites ask you to prove that a real person is behind the screen, forcing you to solve checks or look for alternatives.
• Design changes: if the page changes its structure or its classes, the selectors stop working and the program has to be rewritten.
• Incomplete or messy data: web content arrives in varying formats, with missing values and duplicates that need cleaning before analysis.
• Sites that change their logic: pages with dynamic loading, login requirements or anti-bot protection complicate extraction and demand more advanced techniques.

Most of these risks are managed with careful design: spaced-out requests, respect for the site's rules, constant monitoring of results and backup plans when a source changes or disappears. Well-made scraping is a permanent maintenance task, not a program you set up once.

In the end, web scraping is a tool: used responsibly, it turns the scattered information on the internet into an advantage for making better decisions. The data you collect only creates value when it is organized, combined with your own business information and turned into concrete actions. On the Kardex Tauro blog you will find guides for organizing your company's information and making the most of it every day.