A scraper send a HTTP request to a web page, reads the HTML code It retrieves the data, extracts the targeted information, and then stores it. The principle is the same as that of a traditional browser, but it is fully automated and has no graphical user interface.
Here's how this process works in practice, step by step.
Step 1: Sending the HTTP request
During the web scraping, the scraper starts by send an HTTP request (often of the type GET) at the’URL of the page to be extracted. It's exactly the same mechanism as a standard browser, except that everything is automated, without any visible window or a click on your part.
To avoid being blocked, the scraper can add HTTP headers. For example, a User-Agent which imitates that of Chrome Where Firefox, or cookies. In short, it pretends to be a browser normal from the target server's perspective.
Many websites still detect these automated requests, via rate-limiting or some captchas, to curb web scraping.
Step 2: Receiving and analyzing HTML content
In response to the request, the site returns the HTML code the entire page: titles, text, images, links, price, customer reviews. The scraper doesn't “see” this content the way you do. It works directly on the gross code, without any graphical user interface.
Specifically, the scraper will analyze the HTML structure to identify the information that interests him. This analysis is based on tags and classes CSS or sometimes some JavaScript.
Step 3: Data extraction
Once the HTML code has been parsed, the scraper targets the elements to extract : article titles, product prices, customer reviews. The goal is simple: sort through them and keep only the useful data.
The most common method uses sélecteurs CSS, which allow you to target specific elements based on their classes, IDs, or position in the site's hierarchy. Let's look at a concrete example using this HTML code:
<h1>Sports shoes</h1>
<span>79,99 €</span>To retrieve this information, the scraper uses the following selectors:
- .product-title for the product title
- .price for the price
For more complex structures (based on an element's position or its text), the scraper can use the method XPath, which provides more precise targeting when CSS selectors aren't enough.
On the dynamic websites For websites that load their content via JavaScript, additional software is required: a headless browser. You then control a real browser in the background using Puppeteer (a library Node.js who controls Chrome) or Playwright (an automation framework developed by Microsoft). The browser runs the JavaScript, displays the entire page, and then the scraper reads all the data.
There are, therefore, various types of scrapers Depending on the process in question: a simple scraper for static sites, a headless scraper for dynamic sites, and a scraper that uses an API when the site provides one.
Step 4: Data storage
Once the data has been extracted, the scraper saving in various formats. This is the final step in the process. Depending on your needs, you can choose from these options:
- CSV file : Looks like an Excel spreadsheet—perfect for basic use.
- JSON : a more flexible format, often preferred by developers.
- Database : ideal when there is a large amount of information.
You can then analyze, sort, or view this data however you like. In practice, this storage transforms raw data into a actionable dataset, ready for market research or competitive intelligence.
What is the role of a scraper?
The role of a scraper is to’automatically extract and store data from web pages, without you having to copy each piece of information one by one. It's a program or bot that does all the work for you.
In practical terms, the scraper crawls a website, reads its content, and then collects the targeted information. With powerful scrapers, such as those offered by Bright Data, you can find prices, articles, and business data and much more.
You can also scrape a website directly from your browser using dedicated extensions.
Here are a few examples of practical applications:
- Competitive intelligence : Collect product prices from your competitors to adjust your strategy, for example through scraping on Amazon.
- Market analysis : Collect data on trends and new shopping habits.
- Content aggregation : Create a news feed from multiple websites.
- Sales Prospecting : build a contact list, particularly through scraping on Google Maps.
- Scientific Research : Collect public data for research purposes.
In practice, the scraper saves you a considerable amount of time whenever you need to process a large amount of data quickly.
How to scrape for free?
Do you have a web scraping project but a tight budget? Several free software allow you to collect data for free, whether they are ready-to-use tools, browser extensions, or code libraries.
Here are three reliable options based on your profile:
- Beautiful Soup : a library Python Free and open source. It reads a website's HTML code and helps you extract information from it. Ideal for getting started with simple pages.
- Scrapy : a free, open-source Python framework maintained by Zyte. It handles more complex web scraping projects and large volumes of data across numerous pages.
- Octoparse : a no-code platform with a free plan. Its free version includes up to 10 tasks and 50,000 lines exported per month—perfect if you don't want to write code.
You can also use the extension Instant Data Scraper right in your browser, with no installation or code required.
For more information, we go into detail about each option in our article on the free web scraping.
What is the difference between an API and a scraper?
Both are used to extract data online, but they don't work the same way.
The API
A API is an interface that a website intentionally makes available. It returns structured data (often in JSON), which can be used directly. You retrieve only the information that the site authorizes, within the framework it defines itself. It’s clean, stable, and perfectly legal, but you’re limited to the content that the API exposes.
The scraper
A scraper, on the other hand, reads the HTML code from a website, just as a browser would. It can therefore retrieve data even when There is no API. However, you are still subject to the Terms of Use from the website, to the RGPD and anti-bot mechanisms. The file robots.txt is not a legal obligation, but a technical agreement that responsible scrapers follow.
In practice, you use an API when one is available and meets your needs. You switch to the web scraping when the data is accessible only on the site's visible pages.
If you're just starting out, you can begin by Scraping with Excel : It's simple and convenient, despite a few limitations. What about you? Do you know of any scrapers that work differently? Share your experience in the comments.
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