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Overview

Web scraping is the process of automatically extracting data from websites. RepoMaster can discover and utilize the best scraping tools from GitHub to help you collect data without writing scraping code yourself.

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The Challenge

Web scraping typically requires:
  • Understanding HTML/CSS selectors and DOM structure
  • Handling dynamic JavaScript-rendered content
  • Managing rate limiting and anti-bot measures
  • Dealing with pagination and navigation
  • Parsing and structuring extracted data
  • Writing robust error handling code
RepoMaster automates finding and using the right tools for your specific scraping task.

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How RepoMaster Helps

Simply describe what you want to extract: 
python launcher.py --mode backend --backend-mode unified
Example User Input: 
Help me scrape product prices from this webpage: https://example-store.com/products

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Real-World Example: PDF Parsing

From the example directory, here’s a complete workflow for parsing content from a PDF:
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Task Description

Help me parse the content of this website using GitHub repositories:
https://arxiv.org/pdf/2508.13167
2

Repository Search

RepoMaster automatically searches GitHub for PDF parsing tools:
  • Searches for “arXiv PDF parser”, “PDF parsing tools”, “arXiv content extraction”
  • Evaluates README files and repository quality
  • Identifies top candidates based on stars, maintenance, and suitability
3

Repository Selection

Top repositories identified:1. dsdanielpark/arxiv2text
  • Specifically designed for arXiv PDFs
  • Converts PDFs to structured text
  • High relevance for scientific papers
2. datalab-to/marker
  • Converts PDFs to Markdown and JSON
  • High accuracy with complex layouts
  • Supports tables and equations
3. opendatalab/PDF-Extract-Kit
  • Comprehensive extraction toolkit
  • Table recognition and reading order
  • High-quality content extraction
4. docling-project/docling
  • Advanced PDF understanding
  • Seamless AI integration
  • Multi-format support
4

Automatic Execution

RepoMaster selected arxiv2text as most suitable and:
  • Cloned the repository
  • Analyzed the code structure
  • Understood the API usage
  • Executed the PDF parsing
  • Extracted and saved the text content
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Result Delivery

Parsed content saved to output directory:
coding/2508.13167_parsed.txt

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Use Case Examples

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E-commerce Price Monitoring

Task: 
Scrape product prices from Amazon search results for "wireless headphones"
and save to CSV
What RepoMaster Does:
  • Finds web scraping libraries (BeautifulSoup, Scrapy, Selenium)
  • Handles dynamic content loading
  • Extracts product names, prices, ratings
  • Structures data into CSV format
  • Handles pagination automatically
Expected Output: 
Product Name,Price,Rating,URL
Sony WH-1000XM5,$349.99,4.8,https://...
Bose QuietComfort 45,$279.99,4.7,https://...

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News Article Collection

Task: 
Collect all article headlines and summaries from TechCrunch homepage
What RepoMaster Does:
  • Discovers newspaper3k or similar article extraction tools
  • Parses HTML structure
  • Extracts headlines, authors, publish dates, summaries
  • Saves to structured JSON format

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Academic Paper Metadata

Task: 
Extract title, authors, abstract from arXiv papers in category cs.AI
for the last week
What RepoMaster Does:
  • Finds arXiv API wrappers or PDF parsers
  • Queries arXiv database
  • Parses PDF content or uses API
  • Structures metadata into DataFrame

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Common Scraping Patterns

For simple HTML pages:
Extract all blog post titles and dates from https://blog.example.com
RepoMaster will use lightweight tools like BeautifulSoup or lxml.

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Output Formats

RepoMaster can deliver scraped data in multiple formats:

CSV

Structured tabular data for spreadsheets

JSON

Nested data structures for APIs

Excel

Multiple sheets with formatting

Markdown

Human-readable formatted text

HTML

Preserved web structure

Database

Direct insertion into SQLite/PostgreSQL

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Advanced Features

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Handling Authentication

Scrape my saved items from https://website.com after logging in with credentials
RepoMaster can work with tools that support:
  • Cookie-based sessions
  • OAuth authentication
  • API tokens
  • Form-based login

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Rate Limiting & Politeness

Scrape 1000 product pages from example.com with 2-second delays between requests
RepoMaster ensures:
  • Respectful crawling speeds
  • robots.txt compliance
  • User-agent rotation
  • Proxy support when needed

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Error Handling

Scrape all articles, skip broken pages, and continue on errors
Automatic handling of:
  • Network timeouts
  • Missing elements
  • Changed page structure
  • Rate limiting responses

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Real Execution Output

🌟 Unified Assistant started!
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📋 Task: Parse PDF from arXiv
🔧 Analyzing task...

🔍 Searching GitHub for PDF parsing repositories...
   Query: "arXiv PDF parser GitHub"
   Query: "PDF parsing GitHub repository"
   Query: "GitHub arXiv PDF content extraction"

✅ Found 15+ relevant repositories

📊 Evaluating repositories...
   1. dsdanielpark/arxiv2text - ⭐ Highly relevant for arXiv
   2. datalab-to/marker - ⭐ High accuracy PDF converter
   3. opendatalab/PDF-Extract-Kit - ⭐ Comprehensive toolkit
   4. docling-project/docling - ⭐ Advanced PDF understanding
   5. karpathy/arxiv-sanity-preserver - Web interface + parsing

✅ Selected: dsdanielpark/arxiv2text
   Reason: Specifically designed for arXiv PDFs

📦 Cloning repository...
   Cloning into 'coding/arxiv2text'...
✅ Repository cloned (311 objects)

🔍 Analyzing repository structure...
   Loaded 9 modules, 8 functions
   Main functions: arxiv_to_text, arxiv_to_md, arxiv_to_html

⚙️  Configuring PDF extraction...
   Using: arxiv_to_text()
   PDF URL: https://arxiv.org/pdf/2508.13167

📄 Extracting PDF content...
✅ Text extraction complete

💾 Saving results...
✅ Saved to: coding/2508.13167_parsed.txt

✨ Task completed successfully!

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Best Practices

Test your scraping task on a few pages first:
Scrape the first 5 product pages from this category
Clearly specify what you want:
Extract: product name, price, rating, availability status, and image URL

Scrape restaurant reviews and save as CSV with columns: name, rating, review_text, date
If the page loads content via JavaScript:
This page loads content dynamically. Wait for elements to load before scraping.

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Limitations & Considerations

Legal and Ethical Considerations:
  • Always check the website’s Terms of Service
  • Respect robots.txt directives
  • Don’t overload servers with requests
  • Consider using official APIs when available
  • Be aware of copyright and data protection laws
Technical Limitations:
  • Some sites use advanced anti-bot measures
  • CAPTCHAs cannot be bypassed automatically
  • Very complex SPAs may require manual configuration
  • Real-time data may require continuous monitoring setup

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Next Steps

Data Processing

Process and transform scraped data

AI/ML Tasks

Use scraped data for machine learning

Deep Search Agent

Learn about web research capabilities

Repository Agent

Understand how repositories are executed

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