Web Scraping Financial Data with Python: Best Practices

Accessing financial data programmatically is essential for any quant trader. Here's how to do it responsibly and efficiently. Data Sources Free APIs import requests # Yahoo Finance (unofficial) def get_stock_data ( symbol , period = ' 1mo ' ): url = f ' https://query1.finance.yahoo.com/v8/finance/chart/ { symbol } ' params = { ' range ' : period , ' interval ' : ' 1d ' } r = requests . get ( url , headers = { ' User-Agent ' : ' Mozilla/5.0 ' }) return r . json () # CoinGecko (crypto) def get_crypto_price ( coin_id ): url = f ' https://api.coingecko.com/api/v3/simple/price ' params = { ' ids ' : coin_id , ' vs_currencies ' : ' usd ' } return requests . get ( url ). json () Economic Calendar from datetime import datetime def get_forex_factory_events ( date = None ): """ Parse economic events - be respectful of rate limits """ if date is None : date = datetime . now (). strftime ( ' %Y-%m-%d ' ) # Use the ForexFactory RSS or API # Always add delays between requests pass Best Practices 1.