How to Scrape Any Website for Free Using DeepSeek & Crawl4AI

Web scraping has become one of the most in-demand skills in the tech industry, enabling businesses to extract valuable data from websites for lead generation, market research, and more. In this guide, we’ll explore how to build a free, AI-powered web scraper using DeepSeek, Crawl4AI, and Grok. These tools make it easy to scrape websites, process data, and even integrate AI for advanced insights.

Whether you’re a developer looking to expand your skillset or a business owner seeking to automate data collection, this step-by-step tutorial will help you get started.

What You’ll Learn

How to set up and use DeepSeek, Crawl4AI, and Grok.
How to scrape websites for leads and save the data in a structured format.
How to integrate AI to process and enhance scraped data.
How to export your results to Google Sheets for easy sharing.

Why Web Scraping is Essential

Web scraping allows businesses to:

Generate Leads: Extract contact information from websites to reach potential clients.
Market Research: Gather data on competitors, pricing, and trends.
Automation: Save time by automating repetitive data collection tasks.

With tools like DeepSeek and Crawl4AI, you can build powerful scrapers without spending a fortune on software or services.

Tools You’ll Need

Crawl4AI: An open-source library for scraping websites. It can tag and structure scraped content, making it easy to process with AI.
DeepSeek: A reasoning model that processes scraped data. It’s fast, affordable, and comparable to OpenAI’s GPT models.
Grok: A platform with specialized AI chips for running models like DeepSeek. It offers a free tier for developers.

Step 1: Setting Up Your Environment

Before diving into the code, you’ll need to set up your development environment.

Install Dependencies

Install Conda to manage your Python environment.
Create a new environment: conda create -n webscraper python=3.9 conda activate webscraper
Install the required libraries: pip install crawl4ai

Configure API Keys

Sign up for Grok and get your API key.
Add the API key to your environment file: export GROK_API_KEY=your_api_key

Step 2: Building the Web Scraper

Let’s build a scraper for a wedding photographer who wants to collect leads from wedding venue websites.

Core Components

Browser Configuration: Set up the browser for scraping.
Crawler Configuration: Define what data to extract and how to process it.
AI Integration: Use DeepSeek to process raw data into structured information.

Code Overview

Here’s a high-level breakdown of the code:

1. Browser Configuration

Set up the browser to scrape websites: from crawl4ai import BrowserConfig

browser_config = BrowserConfig( browser=”chrome”, headless=False, # Set to True to run in the background window_size=(1024, 768) )

2. Define the Data Model

Create a schema for the data you want to extract: class Venue: def init(self, name, location, price, description): self.name = name self.location = location self.price = price self.description = description

3. AI Extraction Strategy

Use DeepSeek to process raw HTML into structured data: from crawl4ai import LLMExtractionStrategy

extraction_strategy = LLMExtractionStrategy( model=”deepseek-r1″, instructions=””” Extract the following details for each wedding venue: – Name – Location – Price – A one-sentence description “”” )

4. Scraping Logic

Iterate through pages and extract data: from crawl4ai import Crawler

def scrape_venues(base_url, max_pages): crawler = Crawler(browser_config) venues = []

for page in range(1, max_pages + 1):
    url = f"{base_url}?page={page}"
    results = crawler.scrape(url, extraction_strategy)

    if "no results" in results.text.lower():
        break

    venues.extend(results.data)

return venues

Step 3: Running the Scraper

Run the scraper and save the results to a CSV file: import csv

venues = scrape_venues(“https://example.com/wedding-venues“, max_pages=10)

with open(“venues.csv”, “w”, newline=””) as file: writer = csv.writer(file) writer.writerow([“Name”, “Location”, “Price”, “Description”]) for venue in venues: writer.writerow([venue.name, venue.location, venue.price, venue.description])

Step 4: Exporting to Google Sheets

Once you have the data in a CSV file, you can easily import it into Google Sheets:

Open Google Sheets and click File > Import.
Upload the CSV file.
Format the data as a table for easy filtering and sorting.

Advanced Features

1. CSS Selectors

Use CSS selectors to target specific elements on the page: css_selector = “.info-container”

2. AI-Generated Descriptions

DeepSeek can generate one-sentence descriptions for each venue, making the data more useful for clients.

3. Custom Models

You can switch to other models like GPT-4 or LLaMA for more advanced processing.

Use Cases

Lead Generation: Collect contact information for potential clients.
Market Research: Analyze competitor pricing and offerings.
Content Aggregation: Gather data for blogs, reports, or dashboards.

Conclusion

With tools like DeepSeek, Crawl4AI, and Grok, web scraping has never been easier or more powerful. By combining traditional scraping techniques with AI, you can extract, process, and enhance data in ways that were previously impossible.

Whether you’re a developer or a business owner, this guide provides everything you need to start scraping websites for free. So, what are you waiting for? Start building your AI-powered web scraper today!

Resources

Start scraping smarter, not harder!