Crypto Data Scraper in 1 Day

Today, I engineered an advanced Python application for extracting cryptocurrency data from CoinMarketCap and associated project websites, with seamless integration into Google Sheets. Here's a breakdown of the implementation:

🔍 CoinMarketCap API Integration

• Utilizes the CMC API for real-time data on newly listed coins, employing batch requests to manage rate limits
• Implements automatic pagination to handle large datasets without manual intervention
• Data filtering to eliminate duplicates, ensuring each coin's metadata is unique and accurate

🌐 Web Scraping for Emails

• Employs Breadth-First Search (BFS) for comprehensive site traversal, with configurable depth limits
• Overcomes Cloudflare email protection using JavaScript execution within a headless browser
• URL filtering based on domain relevance to narrow down scraping targets
• Incorporates PDF parsing for email detection within documents using PyPDF2
• Utilizes BeautifulSoup for HTML parsing, complemented by requests for HTTP interactions

📊 Google Sheets Data Storage

• Data is dynamically appended using the googleapiclient, formatted for ease of analysis
• Implements a resume mechanism to continue from where it left off during interruptions

🔧 Error Management and Robustness

• Comprehensive error logging with logging module for both development and production
• Retry logic for network requests and API calls to handle transient failures gracefully

🔐 Configuration Management

• Sensitive data and operational parameters managed through environment variables
• Configuration files used for complex settings, allowing easy adjustments without code changes

Tech Stack

Libraries and Tools

• requests for HTTP requests
• bs4 for parsing
• googleapiclient for Sheets integration
• re for regex operations
• Custom modules for specific tasks

Development Environment

• o1 pro for enhanced performance
• Cursor for IDE capabilities
• Gemini 2.0 Flash for AI-driven code suggestions

Results and Future Plans

The project was completed in one day, with successful implementation and smooth operation. Currently, we've captured emails from 24.4% of analyzed projects.

Future Enhancements

• Refinement of URL filters to reduce noise in data collection
• Addition of proxy support for geo-specific scraping
• Further enhancement of error strategies for greater reliability