What Is Scraping? A Comprehensive Guide to Web Scraping for Beginners

The sheer volume of information online draws many people to the internet. They seek quick and easy methods to access this content. If you’ve ever tried to track changing prices, compile product lists, or gather insights about competitors or potential clients, you know the task of manual copy-pasting is overwhelming. It’s a familiar struggle: the needed information exists, yet acquiring it is time-consuming and laborious. 

This guide introduces web scraping as a technique that enables the collection of online data. Historically, it required a dedicated team. Now, you can explore a user-friendly approach using a free template with Headless Browser and ChatGPT. Think of this scenario as a starting point after which you can automate most of such tasks. This allows anyone to convert the vast web into a structured and readily available resource.

What is Web Scraping? 

Scraping is a method for the automated retrieval of info from various online sources, with a particular focus here on websites. It works as an enhanced form of copy-pasting, but is much faster and more precise. Instead of simply taking the displayed text from a page, scrapers utilize the site’s source code. This allows you to access the true materials, enabling the obtaining of specific details with ease.

Furthermore, web scraping software is built to handle the complexities of modern sites, such as navigating through various pages, handling interactive elements, pop-ups, and dynamic content. This is a notable leap from manual collection, where each page would have to be visited individually in order to receive and organize the desired information. 

Scrapers ease the burden of complex processes, saving time and effort by collecting content from multiple pages as if it were centralized. This is what made web scraping essential in fields like market research, financial analysis, e-commerce, and basically all areas requiring real-time updates to remain competitive.

After all, the internet is like a sprawling library with books strewn across the floor, rather than neatly arranged on shelves. Web scraping provides a way to bring order to this chaos by acquiring this raw info and formatting it into a structured and usable format, giving access to what previously was inaccessible.

Why Is Scraping Useful (5 Examples)

There are numerous applications of this technique for personal and professional use. Essentially, you transform a disorganized pile of online data into a straightforward pipeline.

Practical Use Cases of Web Scraping

Beyond saving time, scraping unlocks access to material that's otherwise unavailable.  This technique transforms this overwhelming sea of knowledge into structured knowledge, and its potential is only limited by your imagination.

How Webscraping Works (Basic Steps)

Though the mechanisms may seem complex, the process itself is straightforward. Web scraping has a few basic phases to fetch the content.

1. Getting the Webpage’s Content

This initial stage involves our tool "asking" a website for its structural "blueprint," which is created using HTML (HyperText Markup Language). Look at HTML as the framework that shapes a website's appearance; it’s what dictates where text, images, and other elements reside. When you access a website, your browser translates this HTML structure into the visual page you see. 

In contrast, bots for scraping take a different approach and download it for direct analysis, bypassing the visual layer. This retrieval process utilizes HTTP requests, which is how browsers and servers engage in communication. Think of it as procuring the necessary building blocks for the construction ahead.

2. Finding the desired data

Once the HTML "blueprint" is retrieved, the next step involves directing the tool to locate specific pieces of information you want to extract. Instead of processing all the data from the page, the tool uses “instructions,” typically defined using CSS selectors, to target elements like product prices, descriptions, or other info. These selectors act like addresses within the website's map, pinpointing where exactly the needed content is.

This process is akin to using a map to locate a specific building in a city, and requires identifying specific patterns and tags, where the needed info is stored. The tool follows these instructions to pull only the relevant context, filtering out irrelevant components of the page.

3. Saving the collected data

After scraping web resources, the tool converts raw material into structured information, offering output in various formats: text (.txt), spreadsheet-friendly CSV (.csv), or JSON (JavaScript Object Notation) for more complex operations. The choice depends on the user's needs, making this stuff eligible for analysis and reporting.

4. That’s It!

These actions allow a vast array of use-cases to come to life; here is a way to utilize these steps by implementing a web-scraping scenario, for obtaining website context by using out-of-the-box solutions. 

Building Your Scraping Bot: Headless Browser + ChatGPT

Let’s build a basic scraper. Once configured, you can try it in the current form or add it as an integral part to other scenarios if needed. This template shows how to achieve quite complex tasks without coding. It shows that anyone can obtain different data from websites using readily available options. 

To start, we'll focus on the specific website you choose. You’ll see firsthand how simple it is: you only need to provide the address, and the nodes will do all the rest for you. You do not have to worry about what's happening in the background, as the scenario on Latenode does for you. This will enable you to dive into the world of data with no effort.

Note: The "Run Once" trigger is here for testing purposes but can be easily swapped out with a trigger for a new database table row or anything else you need.

Step 1: Setting the Target URL

The journey begins by specifying the website you wish to extract from. You will need a Set Variables option, that allows you to define the URL for your scraping bot. Copy the address and paste it into a text field, like you would when visiting it normally. This single action tells the nodes where to navigate.

Step 2: Content Scraping via Headless Browser

Next comes the fascinating part, where we need a Headless Browser node to explore the website. This node is based on one of Javascript libraries called Puppeteer, specifically designed for scraping. It's like a ghost agent, silently locating and collecting details, all while you focus on what to do with the results. Learn about this tool here, as it's your key to unlocking automated webscrapping.

Within the node, you'll insert the following code generated by our AI assistant based on ChatGPT, which acts like a set of precise instructions. Don’t worry about understanding all of it, simply copy and paste this into the needed field:

// Insert the link
const url = data["{{4.site_url}}"];
console.log('Navigating to:', url); // Logging the URL

// Navigating to the specified URL
await page.goto(url, { waitUntil: 'networkidle2' });

// Extracting all visible text from the page
const markdown = await page.evaluate(() => {
    // Function to filter only visible elements
    function getVisibleTextFromElement(el) {
        const style = window.getComputedStyle(el);
        // Checking for element visibility and presence of text
        if (style && style.display !== 'none' && style.visibility !== 'hidden' && el.innerText) {
            return el.innerText.trim();
        }
        return '';
    }

    // Extracting text from all visible elements
    const allTextElements = document.body.querySelectorAll('*');
    let textContent = '';

    allTextElements.forEach(el => {
        const text = getVisibleTextFromElement(el);
        if (text) {
            textContent += `${text}\n\n`;
        }
    });

    return textContent.trim();
});

// Returning the result
return {
    markdown
};

This JavaScript code is like an engine for the Headless Browser, instructing it to visit the URL and retrieve all visible text from the site, and format it in Markdown.

Step 3: Cleaning and Formatting with ChatGPT

After the research has been finished, you’ll quickly see that a lot of it is raw text, which is hard to interpret. This is where the ChatGPT integration comes in. By copying the extracted data into ChatGPT, you can instruct the tool to organize it, and structure it to your needs. 

This is like hiring a personal organizer, which allows you to take the raw material and structure it into something useful and practical. Ask ChatGPT to fetch specific sections, remove irrelevant details, and create a clean, accessible dataset, ready for you to work with.

Step 4: Outputting a JSON File

Finally, the output from ChatGPT is now ready to be transformed into a usable format through a custom JavaScript node. The output is a JSON (JavaScript Object Notation) file, which is ideal for complex processing and analysis tasks. To write a script for this, just instruct our JavaScript AI Assistant to "Extract JSON from ChatGPT's response" – it manages this task with ease!

The output is a ready-made JSON with all the requested information:

Impressive, isn’t it?

Potential Use Cases

There are multiple potential ways to employ this scenario:

• Keep up to date with changes to the site
• Publish posts from site updates
• Track desired keywords
• Analyze client resources for detailed information
• And much more - easy and simple with Latenode!

This blueprint, while simple, demonstrates the power of web scrapping. It shows that you do not need to learn coding to acquire information. This approach makes it more accessible for those that wish to take control of the insights they need.

Ethical and Legal Considerations for Web Scraping 

Remember that with the ability to automate comes a responsibility to utilize this capability with care. Treat websites as valuable resources that need to be protected, and avoid any actions that would negatively impact their accessibility or functionality. Ethical web scraping upholds the integrity, long-term viability, and responsible collection practices. 

It's about finding a balance between harnessing the power of scraping and honoring the established rules and regulations of each online space.

Be Mindful:

• Avoid Overburdening Servers: Do not send a barrage of rapid requests. Websites, like any resource, have limits to how much processing they handle. Excessive traffic degrades performance for everyone. A good practice is to create a slight pause between each of your automated requests.
• Review Site Agreements: Before pulling anything from the web, review the terms of service or usage agreements. These agreements usually lay out what actions are and are not allowed on the platform and whether extraction is permitted or not.
• Gather Only What's Needed: Scraping web without a specific goal strains resources unnecessarily. Be selective and target only what you truly require, which not only reduces strain but also shows respect to website owners. Think of it as carefully curating a collection, taking only the items that are essential.

Many platforms have systems in place that actively monitor and block IP addresses when unusual amounts of activity is detected, which makes it harder to collect the information you need. Responsible scraping is not just about following guidelines, but rather ensuring that you can keep using these valuable techniques.

Your Scraping Journey Begins

So, what is a Web Scraper? You've now grasped the basic concepts of this topic, and got a simple template for extracting the information without coding. We hope this guide has prepared you to creatively leverage internet insights. Keep exploring and enjoy the journey; this is just the start!