Blockchain Scraping

Blockchain scraping is the process of collecting publicly available data from blockchain networks, explorers, or related websites for analysis and monitoring.

Core Methods of Extraction

On-Chain Scraping: Querying blockchain nodes directly via RPC/JSON-RPC calls (using languages like Rust, Python, or JavaScript) to parse individual blocks, slot numbers, and account balance changes.

Web Scraping Aggregators: Extracting off-chain market data, prices, trading volume, and liquidity stats from sites like CoinGecko or Crypto.com using tools like BeautifulSoup, Selenium, or Apify.

Indexed Data Scraping: Utilizing specialized indexing protocols (such as The Graph) to query pre-parsed blockchain events instead of scanning raw blocks sequentially.

Common Use Cases

Wallet & Fraud Tracking: Following fund movements and linking suspicious wallet addresses to web forums or social media mentions via OSINT.

Market Intelligence: Monitoring real-time floor prices, NFT traits, token trading volume, and historical OHLCV data.

Predictive Modeling: Feeding continuous price and transaction data streams into machine learning frameworks (like CNN-LSTM models) for market trend forecasting.

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