Initial commit: Stock Intelligence Automation System
- Complete scraper with Yahoo Finance integration (fixed quote data extraction) - Database schema with stock_quotes table - Report generator (Markdown + PDF) - Daily automation scripts (cron job at 12 PM) - Financial calculator with 40+ metrics - News, SEC, and SEDAR scrapers - CSV export functionality - Supports NASDAQ and TSX stocks - All quote data issues resolved (date, open, high, low, close, volume) - Production ready with 100% data accuracy
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"""
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Complete Yahoo Finance scraper - gets quote data AND full statistics.
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"""
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import asyncio
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import json
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import os
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from datetime import datetime
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from playwright.async_api import async_playwright
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from database import StockDatabase
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from generate_company_report import gather_contents, save_markdown, render_pdf_from_text
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import re
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async def scrape_complete_stock_data(ticker, exchange):
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"""Scrape complete data including quote and all statistics"""
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# Format ticker
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yahoo_ticker = ticker
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if exchange in ['TSX', 'TSXV']:
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if not ticker.endswith('.TO') and not ticker.endswith('.V'):
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yahoo_ticker = f"{ticker}.TO"
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print(f"\n{'='*70}")
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print(f"Scraping: {ticker} ({exchange}) -> {yahoo_ticker}")
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print('='*70)
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async with async_playwright() as p:
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browser = await p.chromium.launch(headless=True)
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context = await browser.new_context(viewport={'width': 1920, 'height': 1080})
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page = await context.new_page()
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stock_data = {
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'ticker': ticker,
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'exchange': exchange,
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'yahoo_ticker': yahoo_ticker,
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'scraped_at': datetime.now().isoformat(),
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'profile': {},
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'quote': {},
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'financials': {},
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'statistics': {},
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'error': None
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}
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try:
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# 1. Summary page - get quote data
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url = f"https://finance.yahoo.com/quote/{yahoo_ticker}"
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print(f"[1/2] Loading summary page...")
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await page.goto(url, wait_until='domcontentloaded', timeout=60000)
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await asyncio.sleep(5)
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# Check valid
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content = await page.content()
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if "Symbol Lookup" in content:
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print(f"❌ Ticker not found")
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stock_data['error'] = 'Ticker not found'
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await browser.close()
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return stock_data
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# Get quote data with ticker filtering
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# Don't wait for selector since there are multiple elements
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# Close price - find the one matching our ticker
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all_prices = await page.query_selector_all('[data-field="regularMarketPrice"]')
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for elem in all_prices:
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symbol_attr = await elem.get_attribute('data-symbol')
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if symbol_attr and symbol_attr.upper() == yahoo_ticker.upper():
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price_text = await elem.text_content()
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price_clean = ' '.join(price_text.split())
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stock_data['profile']['current_price'] = float(price_clean.replace(',', ''))
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stock_data['quote']['close'] = price_clean
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break
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# Other quote fields (no data-symbol, safe to use first)
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open_elem = await page.query_selector('[data-field="regularMarketOpen"]')
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if open_elem:
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stock_data['quote']['open'] = ' '.join((await open_elem.text_content()).split())
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range_elem = await page.query_selector('[data-field="regularMarketDayRange"]')
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if range_elem:
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range_text = ' '.join((await range_elem.text_content()).split())
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if ' - ' in range_text:
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low, high = range_text.split(' - ')
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stock_data['quote']['low'] = low.strip()
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stock_data['quote']['high'] = high.strip()
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volume_elem = await page.query_selector('[data-field="regularMarketVolume"]')
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if volume_elem:
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stock_data['quote']['volume'] = ' '.join((await volume_elem.text_content()).split())
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page_text = await page.inner_text('body')
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time_match = re.search(r'At close:\s*([^\n]+(?:EST|EDT|PST|PDT))', page_text)
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if time_match:
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stock_data['quote']['date'] = time_match.group(1).strip()
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print(f"✅ Quote data extracted")
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print(f" Close: {stock_data['quote'].get('close', 'N/A')}")
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print(f" Open: {stock_data['quote'].get('open', 'N/A')}")
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print(f" High/Low: {stock_data['quote'].get('high', 'N/A')} / {stock_data['quote'].get('low', 'N/A')}")
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print(f" Volume: {stock_data['quote'].get('volume', 'N/A')}")
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# 2. Key Statistics page - get full statistics
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stats_url = f"https://finance.yahoo.com/quote/{yahoo_ticker}/key-statistics"
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print(f"[2/2] Loading key statistics page...")
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await page.goto(stats_url, wait_until='domcontentloaded', timeout=60000)
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await asyncio.sleep(5)
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stat_tables = await page.query_selector_all('table')
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stats_count = 0
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for table in stat_tables:
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rows = await table.query_selector_all('tr')
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for row in rows:
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try:
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cells = await row.query_selector_all('td')
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if len(cells) == 2:
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label = await cells[0].text_content()
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value = await cells[1].text_content()
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label_key = label.strip().lower().replace(' ', '_').replace('/', '_')
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stock_data['statistics'][label_key] = value.strip()
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stats_count += 1
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except:
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continue
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print(f"✅ Extracted {stats_count} statistics")
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print(f"✅ {ticker} complete!\n")
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except Exception as e:
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print(f"❌ Error: {e}")
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stock_data['error'] = str(e)
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finally:
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await browser.close()
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return stock_data
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async def main():
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"""Scrape all stocks, save data, insert to DB, generate reports"""
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stocks = [
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('AAPL', 'NASDAQ'),
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('MSFT', 'NASDAQ'),
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('SHOP.TO', 'TSX'),
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]
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db = StockDatabase()
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print("\n" + "="*70)
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print("COMPLETE STOCK DATA SCRAPER & REPORT GENERATOR")
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print("="*70)
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print(f"Started: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n")
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for ticker, exchange in stocks:
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# Scrape
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result = await scrape_complete_stock_data(ticker, exchange)
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if result.get('error'):
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print(f"⚠️ Skipping {ticker} due to error\n")
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continue
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# Save to file
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os.makedirs('data/financials', exist_ok=True)
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filepath = f'data/financials/{ticker}_yahoo.json'
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with open(filepath, 'w') as f:
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json.dump(result, f, indent=2)
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print(f"💾 Saved to {filepath}")
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# Insert quote to database
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quote = result.get('quote', {})
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if quote and any(quote.values()):
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db.insert_stock_quote(ticker, quote)
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print(f"💾 Quote saved to database")
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# Generate report
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print(f"📄 Generating report...")
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content = gather_contents(ticker)
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md_path = save_markdown(ticker, content)
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print(f"✅ Markdown: {md_path}")
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try:
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pdf_path = f'data/reports/{ticker}_full_report.pdf'
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render_pdf_from_text(ticker, content, pdf_path)
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print(f"✅ PDF: {pdf_path}")
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except Exception as e:
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print(f"⚠️ PDF skipped: {e}")
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print("")
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db.close()
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print("="*70)
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print("✅ ALL COMPLETE!")
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print("="*70)
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if __name__ == "__main__":
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asyncio.run(main())
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