A clear and concise guide on modern web scraping.
**Web scraping** is the automated process of extracting data from websites using software or scripts that retrieve and parse HTML content.
1. **Fetching** — The scraper requests the page HTML.
2. **Parsing** — Extract relevant elements from the HTML/DOM.
3. **Storing** — Save extracted data in CSV, JSON, or a database.
There are several programming languages that can be used for web scraping. Below, I’ve listed them along with a brief description of their commonly used libraries and tools for each language.
| Language | Strengths | Common Libraries / Tools |
|---|---|---|
| Python | Easy syntax, rich ecosystem | Requests, BeautifulSoup, Scrapy, |
Selenium, Playwright, pandas |
|JavaScript| Browser-like scraping | Puppeteer, Cheerio, Axios, Playwright | | Java | High performance at scale | Jsoup, Selenium | | PHP | Server-side scripting; small projects | cURL, DOMDocument | | Go | Fast, lightweight concurrency | colly, goquery | | R | Data science oriented | rvest, httr | |C# (.NET) | Enterprise and Windows apps | HtmlAgilityPack, Selenium |
Although there are several languages available for web scraping, Python is the most popular and powerful one. That’s why I prefer using Python for scraping. The reasons for my choice are listed below.
- Simple syntax — easy to learn and fast to prototype.
- Extensive libraries for HTTP, parsing, browser automation, and data handling.
- Excellent tools for automation and integration (pandas, NumPy, DB drivers).
- Large community and well-documented ecosystem.
Pre-Scrape Analysis — Essential Checklist
- Determine rendering type: Identify whether the site is Static, Dynamic (CSR), SSR, or SPA.
- Inspect HTML structure: Right-click → Inspect → Elements to locate the data you want to extract.
- Check the Network tab: In the XHR or Fetch section, look for API calls that return JSON — these often contain raw data.
- Check authentication requirements: Note if login, tokens, or cookies are required for access.
- Review robots.txt: See which paths are allowed or disallowed for crawlers.
- Identify pagination patterns: Detect if the site uses lazy loading or infinite scroll.
- Plan your storage schema: Choose between CSV, JSON, Relational DB, or NoSQL (e.g.MongoDB) based on your needs.
Knowing whether a website is Static, CSR, SSR, or SPA helps you choose the most effective scraping method.
Step-by-Step Process:
1. Open Developer Tools: Press F12 or Right-click → Inspect.
2. Check the Elements tab:
- If the desired content (text, images, etc.) is visible directly in the HTML, the page is likely Static or SSR.
3. Disable JavaScript:
- Click the three dots in the top-right corner of DevTools.
- Open Run Command (or Command Menu) and type “Disable JavaScript”.
- Press Enter to disable it.
4. Reload the page:
- If the page still loads fully and shows content → it’s Static or SSR.
- If the page loads partially or stays blank → it’s CSR (Client-Side Rendered) or a SPA (Single Page Application).
| Protection | Description |
|---|---|
| robots.txt | Suggests crawler-friendly paths — follow it as etiquette. |
| Rate limiting | Throttle requests; use delays or paginated APIs. |
| IP blocking | Avoid excessive requests; use legitimate data sources. |
| CAPTCHA | Prevents automation — do not bypass. |
| JavaScript challenges | Requires real browser context (e.g. Playwright). |
| Fingerprinting | Detects non-human patterns or bot signals. |
Important: Never bypass security, authentication, or CAPTCHA.
Always use legal APIs or authorized partnerships where available.
| Use Case | Recommended Tool |
|---|---|
| Static pages, simple scraping | requests + BeautifulSoup |
| Large-scale crawling | Scrapy |
| JS-heavy sites | Playwright |
| Browser automation (legacy) | Selenium |
| Async scraping | httpx, aiohttp |
Here we discuss about a comparative overview of popular web scraping tools — Selenium, BeautifulSoup, Scrapy, and Playwright.
It explains their strengths, weaknesses, use cases, and real-life analogies to help you decide which one to use for your specific project.
Use Case:
Simple HTML parsing, small projects, or static pages.
Key Features:
- Parses HTML or XML documents easily.
- Works well when you already have page source (no JavaScript rendering).
- Lightweight and beginner-friendly.
Advantages:
- Very easy to learn and implement.
- Integrates well with
requestsfor static site scraping. - Fast for simple HTML parsing.
Limitations:
- Cannot handle JavaScript-rendered pages directly.
- Not ideal for automation or large-scale scraping.
Real-life Analogy:
If BeautifulSoup is a skilled librarian who can find and organize information in already opened books, it still depends on someone else to bring the book.
Use Case:
Automated browsing, dynamic websites, and web apps that heavily depend on JavaScript.
Key Features:
- Can control browsers like Chrome, Edge, or Firefox.
- Supports dynamic content loading and user actions (clicks, scrolls, logins).
- Often used for testing as well as scraping.
Advantages:
- Handles all JavaScript-based websites.
- Simulates human-like interactions.
- Provides screenshots and even video recordings of the browser.
Limitations:
- Slower compared to other scrapers.
- High resource consumption (runs real browser).
- Can be easily detected by anti-bot systems.
Real-life Analogy:
If Selenium is an old manual robot that can do everything like a human — open pages, click buttons, type text — it’s powerful but slow and noisy.
Use Case:
Large-scale scraping, crawling multiple pages, and managing structured data pipelines.
Key Features:
- Built-in crawling, item pipelines, and request scheduling.
- Handles concurrency efficiently.
- Best suited for structured and large scraping projects.
Advantages:
- Highly scalable and production-ready.
- Offers middleware, pipelines, and settings for customization.
- Can export data to JSON, CSV, or databases.
Limitations:
- Has a learning curve.
- Not suitable for simple, one-off scraping tasks.
Real-life Analogy:
If Scrapy is a factory with many robotic arms, it’s designed for large-scale data extraction — efficient, systematic, but requires setup and structure.
Use Case:
Modern web automation, handling complex and dynamic pages efficiently.
Key Features:
- Supports multiple browsers (Chromium, Firefox, WebKit).
- Handles iframes, pop-ups, and Shadow DOM smoothly.
- Provides built-in parallelization and automation APIs.
Advantages:
- Faster and lighter than Selenium.
- Detects fewer anti-bot measures.
- Ideal for modern sites using React, Vue, or Angular.
Limitations:
- Slightly newer; ecosystem smaller than Selenium.
- Needs some setup for advanced tasks.
Real-life Analogy:
If Selenium is an old manual robot, Playwright is a fleet of modern smart robots — faster, quieter, can multitask, and understand complex web pages better.