Building a Live Earnings Surprise Tracker with Financial Scraping

Earnings surprises drive massive stock movements. In this tutorial, I'll show you how to build a real-time earnings surprise tracker by scraping financial data sources. Why Track Earnings Surprises? When a company reports earnings that differ significantly from Wall Street estimates, the stock can move 5-20% in minutes. A live tracker helps you: Monitor earnings season in real time Identify sector outperformance patterns Build datasets for quantitative trading strategies Create alerts for significant beats or misses Project Setup import requests from bs4 import BeautifulSoup import pandas as pd from datetime import datetime import json import time SCRAPER_KEY = " YOUR_SCRAPERAPI_KEY " def scrape_page ( url ): resp = requests . get ( " http://api.scraperapi.com " , params = { " api_key " : SCRAPER_KEY , " url " : url }, timeout = 30 ) return BeautifulSoup ( resp . text , " html.parser " ) Scraping the Earnings Calendar def get_earnings_calendar ( date_str ): url = f " https://finance.ya