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What is Web Scraping? Complete Guide 2025 + Tools and Examples

What is Web Scraping?

Web scraping is a technique that involves automatically collecting data from websites. This process consists of sending HTTP requests to web pages, analyzing their HTML or JavaScript code, and extracting structured information for later analysis or storage.

It’s a powerful tool used by developers, data analysts, and companies looking to extract value from publicly available data on the Internet. However, like any technology, it must be used responsibly while respecting legal and ethical frameworks.

Legitimate and Ethical Uses of Web Scraping

Although web scraping can be misused, it also has completely valid and useful applications when done with permission and transparency:

Academic research: Studies based on large volumes of data from public sources.
Market analysis: Companies monitoring trends, prices, and user opinions to make informed decisions.
Authorized price aggregators: Platforms comparing prices between e-commerce sites after obtaining explicit access.
Media monitoring: Tracking news, comments, or brand mentions across different portals.
Catalog updates: Automating the addition of new products from partner websites.

These are clear examples of how to use ethical web scraping, respecting copyright, privacy, and terms of use.

Common Tools for Web Scraping

There are several tools and libraries that make it easier to develop scraping projects. Here are some of the most popular ones:

1. BeautifulSoup

BeautifulSoup is ideal for beginners and static web pages. It is used together with requests to download HTML content and parse it easily.

Basic usage example (in Python):

import requests
from bs4 import BeautifulSoup

url = 'https://example.com'
response = requests.get(url)
soup = BeautifulSoup(response.text, 'html.parser')

for title in soup.find_all('h2'):
    print(title.get_text())

2. Scrapy

Scrapy is a complete and powerful framework for building scalable spiders. It is especially useful for large-scale projects or those involving multiple pages.

Basic usage example (in Python):

import scrapy
from scrapy.crawler import CrawlerProcess

class MySpider(scrapy.Spider):
    name = 'my_spider'
    start_urls = ['https://example.com']

    def parse(self, response):
        for h2 in response.css('h2::text').getall():
            yield {'title': h2}

process = CrawlerProcess()
process.crawl(MySpider)
process.start()

3. Selenium

Selenium allows you to interact with dynamic pages generated by JavaScript. Ideal for sites that load content via AJAX or frameworks like React or Angular.

Basic usage example (in Python):

from selenium import webdriver

driver = webdriver.Chrome()
driver.get('https://example.com')
titles = driver.find_elements_by_tag_name('h2')

for title in titles:
    print(title.text)

driver.quit()

4. Korpdeck

Korpdeck is a web-based tool designed to facilitate the extraction of public information from social networks, focusing especially on platforms such as Instagram and WhatsApp.

This platform allows filtered searches of Instagram users, helping to identify profiles according to defined criteria, all while respecting the limits of publicly available content and under explicit consent when necessary. In addition, Korpdeck offers the possibility to obtain phone numbers associated with participants in public WhatsApp groups, relying only on openly available information.

Thanks to its intuitive interface and user-focused approach, Korpdeck becomes an accessible option for digital marketing professionals and research teams who need to access data in an agile, transparent, and responsible manner.

As part of the movement toward ethical web scraping, Korpdeck promotes access to public information without bypassing protections or violating privacy policies, reinforcing the importance of respecting user rights and complying with current regulations.

All these tools can be used in personal projects, always respecting the rules of the target website.

5. Playwright

Playwright is a powerful library developed by Microsoft that allows automation of browsers such as Chromium, Firefox, and WebKit. Unlike Selenium, Playwright is designed from scratch to support scraping and testing scenarios in dynamic and complex web environments.

One of its main advantages is its ability to handle SPA web applications (Single Page Applications), JavaScript-loaded content, and authentication in real-world environments, all with optimized performance and a clean, easy-to-use API.

Playwright is ideal for projects where other tools like BeautifulSoup or Scrapy are not sufficient due to the dynamic nature of the target pages.

Basic usage example (in Node.js):

const { chromium } = require('playwright');

(async () => {
  const browser = await chromium.launch();
  const page = await browser.newPage();
  await page.goto('https://example.com');

  const title = await page.title();
  console.log('Page title:', title);

  await browser.close();
})();

6. PyDoll

PyDoll is a web automation library developed in Python that allows interaction with dynamic pages using Chromium or Chrome. Designed to offer fine control over the browser, PyDoll is especially useful when DOM events need to be manipulated, requests intercepted, or JavaScript-generated content handled.

Its minimalist approach and native integration with Chrome’s DevTools protocol make it an efficient alternative for modern scraping projects where other tools may fall short.

Basic usage example (in Python):

from pydoll import launch

async def main():
    browser = await launch(headless=True)
    page = await browser.new_page()
    await page.goto('https://example.com')

    title = await page.get_title()
    print(f"Page title: {title}")

    await browser.close()

if __name__ == '__main__':
    import asyncio
    asyncio.run(main())

7. SerpAPI

SerpAPI is a commercial API-based service that allows automated and structured retrieval of real search engine results, such as Google, Bing, or Yahoo. It’s especially useful for tasks like SEO ranking monitoring, competitive analysis, product data collection, or trend studies.

Unlike traditional scraping tools, SerpAPI handles all the infrastructure behind the scenes: CAPTCHA solving, IP rotation, compliance with terms of service, and maintaining up-to-date results.

Basic usage example (in Python):

import os
from serpapi import GoogleSearch

params = {
    "q": "ethical web scraping",
    "hl": "en",
    "api_key": os.getenv("SERPAPI_KEY")
}

search = GoogleSearch(params)
results = search.get_dict()

for result in results["organic_results"]:
    print(f"Title: {result['title']}")
    print(f"Link: {result['link']}")
    print(f"Snippet: {result['snippet']}\n")

8. Requests

Requests is one of the most popular Python libraries for making HTTP requests. Although not a direct scraping tool like Scrapy or Playwright, it is essential when applying reverse engineering to find and consume internal endpoints that expose structured data (e.g., in JSON format).

Many modern websites load content dynamically through hidden API calls. Using Requests along with browser developer tools (like the Network tab in Chrome DevTools) allows identifying these endpoints and consuming them directly, avoiding unnecessary HTML or JavaScript processing.

Basic usage example (in Python):

import requests

url = "https://example.com/api/products"
response = requests.get(url)

if response.status_code == 200:
    products = response.json()
    for product in products:
        print(f"Name: {product['name']}")
        print(f"Price: {product['price']}\n")
else:
    print("Error retrieving data:", response.status_code)

Legal Limits of Web Scraping

It is essential to know the legal boundaries before implementing any scraping project:

Terms of Service

Most websites prohibit automated access in their Terms of Use. Reviewing these documents is crucial to avoid legal penalties or blocks.

robots.txt

This file indicates which parts of a site can or cannot be accessed by bots. You can find it at https://domain.com/robots.txt. Respecting it is a sign of good practice within ethical web scraping.

If you’re collecting data from European citizens, you must comply with the General Data Protection Regulation (GDPR). This includes obtaining explicit consent if handling personal data.

Alternatives to Aggressive Scraping

Instead of performing intensive scraping that could overload servers or violate policies, there are more efficient and respectful alternatives:

Public APIs

Many services offer official APIs that allow controlled and secure access to their data. Some examples include:

Open Datasets

Platforms like Kaggle, data.gov, or datos.gob.es offer pre-structured datasets, eliminating the need for manual scraping.

Access Agreements

Whenever possible, contact the website owner directly to establish access or data exchange agreements. This ensures legality and improves business relationships.

Conclusion

Web scraping is a valuable technique that, when used correctly, can provide significant benefits to researchers, entrepreneurs, and businesses. However, it’s important to always prioritize respect for terms of service, privacy, and technical best practices.

If you’re interested in starting your own projects, consider beginning with tools like BeautifulSoup or Scrapy, and don’t forget to explore options like public APIs or open datasets to avoid aggressive scraping.

KORPDECK

What is Web Scraping? Complete Guide 2025 + Tools and Examples