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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Aherobo Ovie Victor
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"""
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Scrape SEDAR+ filings for Canadian companies
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Gets annual reports, AGM circulars, financial statements, tax disclosures
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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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import re
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from datetime import datetime
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from playwright.async_api import async_playwright
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from typing import Dict, List, Any
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import time
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from config import SEDAR_BASE_URL, SEDAR_SEARCH_URL, FILING_TYPES_SEDAR
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class SEDARPlusScraper:
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def __init__(self, output_dir="data/sedar_filings"):
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self.output_dir = output_dir
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os.makedirs(output_dir, exist_ok=True)
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async def search_company(self, company_name: str, ticker: str) -> List[Dict]:
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"""Search for a company on SEDAR+"""
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print(f"\n🔍 Searching SEDAR+ for {company_name} ({ticker})...")
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async with async_playwright() as p:
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browser = await p.chromium.launch(headless=False) # Non-headless for debugging
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page = await browser.new_page()
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try:
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# Navigate to SEDAR+ search
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await page.goto(SEDAR_BASE_URL, wait_until='networkidle', timeout=60000)
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await asyncio.sleep(3)
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# Try to find and use the search functionality
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# Note: SEDAR+ structure may vary, adjust selectors as needed
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search_input = await page.query_selector('input[type="search"], input[placeholder*="search"], input[name*="search"]')
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if search_input:
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await search_input.fill(ticker)
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await search_input.press('Enter')
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await asyncio.sleep(5)
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# Get page content to parse results
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content = await page.content()
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# Save HTML for debugging
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debug_file = f"{self.output_dir}/{ticker}_sedar_search.html"
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with open(debug_file, 'w', encoding='utf-8') as f:
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f.write(content)
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print(f" Saved search results to {debug_file}")
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# Try to extract filing links
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filings = []
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links = await page.query_selector_all('a[href*="document"], a[href*="filing"]')
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for link in links[:50]: # Get first 50 results
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try:
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href = await link.get_attribute('href')
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text = await link.inner_text()
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filings.append({
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'title': text.strip(),
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'url': href if href.startswith('http') else f"{SEDAR_BASE_URL}{href}",
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'found_at': datetime.now().isoformat()
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})
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except:
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continue
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print(f"✅ Found {len(filings)} potential filings")
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return filings
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except Exception as e:
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print(f"❌ Error searching SEDAR+: {e}")
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return []
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finally:
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await browser.close()
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async def get_filing_document(self, url: str) -> Dict[str, Any]:
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"""Download and parse a SEDAR+ document"""
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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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page = await browser.new_page()
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try:
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await page.goto(url, wait_until='networkidle', timeout=30000)
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await asyncio.sleep(2)
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content = await page.content()
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text = await page.inner_text('body')
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filing_data = {
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'url': url,
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'scraped_at': datetime.now().isoformat(),
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'text_content': text[:100000], # Limit size
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'html_content': content[:100000]
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}
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# Extract AGM information
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agm_patterns = [
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r'annual\s+general\s+meeting.*?(\d{1,2}\s+\w+\s+\d{4})',
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r'agm.*?(\d{1,2}\s+\w+\s+\d{4})',
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r'meeting\s+date.*?(\d{1,2}\s+\w+\s+\d{4})'
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]
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for pattern in agm_patterns:
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match = re.search(pattern, text.lower())
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if match:
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filing_data['agm_date'] = match.group(1)
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break
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# Extract location
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location_patterns = [
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r'meeting\s+location:?\s*([^\n]{10,100})',
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r'to\s+be\s+held\s+at\s+([^\n]{10,100})',
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r'location:?\s*([^\n]{10,100})'
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]
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for pattern in location_patterns:
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match = re.search(pattern, text.lower())
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if match:
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filing_data['agm_location'] = match.group(1).strip()
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break
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# Extract tax information
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tax_keywords = ['income tax', 'tax expense', 'effective tax rate', 'deferred tax',
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'tax loss carryforward', 'tax jurisdiction']
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tax_sections = []
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for keyword in tax_keywords:
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pattern = rf'{keyword}.*?(\d+(?:,\d{{3}})*(?:\.\d+)?)'
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matches = re.finditer(pattern, text.lower())
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for match in matches:
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tax_sections.append({
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'keyword': keyword,
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'context': match.group(0),
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'amount': match.group(1)
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})
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if tax_sections:
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filing_data['tax_information'] = tax_sections[:20] # Limit results
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# Extract share ownership information
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ownership_patterns = [
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r'(insider|director|officer|founder).*?(\d{1,3}(?:,\d{3})*)\s*shares',
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r'beneficially\s+own.*?(\d{1,3}(?:,\d{3})*)\s*shares',
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r'voting\s+shares.*?(\d{1,3}(?:,\d{3})*)'
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]
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ownership_data = []
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for pattern in ownership_patterns:
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matches = re.finditer(pattern, text.lower())
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for match in matches:
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ownership_data.append({
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'context': match.group(0)[:200],
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'shares': match.group(2) if len(match.groups()) > 1 else match.group(1)
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})
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if ownership_data:
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filing_data['ownership_mentions'] = ownership_data[:30]
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return filing_data
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except Exception as e:
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print(f"Error scraping document {url}: {e}")
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return {'url': url, 'error': str(e)}
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finally:
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await browser.close()
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async def get_complete_company_data(self, ticker: str, company_name: str) -> Dict[str, Any]:
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"""Get complete SEDAR+ data for a company"""
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print(f"\n{'='*70}")
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print(f"SCRAPING SEDAR+ FOR: {ticker} - {company_name}")
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print(f"{'='*70}")
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data = {
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'ticker': ticker,
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'company_name': company_name,
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'scraped_at': datetime.now().isoformat(),
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'filings': [],
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'agm_info': {},
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'tax_disclosures': {},
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'ownership_data': []
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}
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# Search for company
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filings = await self.search_company(company_name, ticker)
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data['filings'] = filings
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# Get details from key documents
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priority_keywords = ['annual', 'circular', 'information', 'financial statement', 'md&a']
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priority_filings = []
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for filing in filings:
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title_lower = filing['title'].lower()
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if any(keyword in title_lower for keyword in priority_keywords):
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priority_filings.append(filing)
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# Scrape top priority documents
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for filing in priority_filings[:5]: # Limit to top 5
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print(f" Scraping: {filing['title'][:60]}...")
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doc_data = await self.get_filing_document(filing['url'])
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filing['detailed_data'] = doc_data
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await asyncio.sleep(3) # Rate limiting
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# Aggregate AGM information
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agm_dates = []
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agm_locations = []
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for filing in data['filings']:
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if 'detailed_data' in filing:
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if 'agm_date' in filing['detailed_data']:
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agm_dates.append(filing['detailed_data']['agm_date'])
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if 'agm_location' in filing['detailed_data']:
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agm_locations.append(filing['detailed_data']['agm_location'])
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if agm_dates:
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data['agm_info']['date'] = agm_dates[0] # Most recent
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if agm_locations:
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data['agm_info']['location'] = agm_locations[0]
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# Save to file
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output_file = f"{self.output_dir}/{ticker}_sedar_data.json"
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with open(output_file, 'w', encoding='utf-8') as f:
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json.dump(data, f, indent=2)
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print(f"✅ Saved SEDAR+ data to {output_file}")
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return data
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async def scrape_multiple_companies(self, stock_list: List[Dict]):
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"""Scrape SEDAR+ data for multiple companies"""
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print("=" * 70)
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print("SEDAR+ SCRAPER")
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print("=" * 70)
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all_data = []
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for stock in stock_list:
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ticker = stock.get('symbol')
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company_name = stock.get('name')
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data = await self.get_complete_company_data(ticker, company_name)
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all_data.append(data)
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await asyncio.sleep(5) # Respectful rate limiting
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print(f"\n✅ Completed scraping {len(all_data)} companies")
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return all_data
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async def main():
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"""Test the SEDAR+ scraper"""
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scraper = SEDARPlusScraper()
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# Test with a sample Canadian company
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test_stocks = [
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{'symbol': 'SHOP', 'name': 'Shopify Inc.'},
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]
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await scraper.scrape_multiple_companies(test_stocks)
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if __name__ == "__main__":
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asyncio.run(main())
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