Real Estate Property Monitoring

import requests
import os

api_key = os.environ['SUPACRAWLER_API_KEY']

properties = [
    {
        "site": "Zillow",
        "url": "https://www.zillow.com/san-francisco-ca/",
        "selector": ".property-card-price"
    },
    {
        "site": "Realtor.com",
        "url": "https://www.realtor.com/realestateandhomes-search/San-Francisco_CA",
        "selector": ".listing-price"
    }
]

for prop in properties:
    requests.post("https://api.supacrawler.com/api/v1/watch",
        headers={"Authorization": f"Bearer {api_key}"},
        json={
            "url": prop["url"],
            "frequency": "daily",
            "selector": prop["selector"],
            "notify_email": "[email protected]",
            "webhook_url": "https://your-api.com/property-updates"
        }
    )

from supacrawler import SupacrawlerClient

client = SupacrawlerClient(api_key=os.environ['SUPACRAWLER_API_KEY'])

def track_price_changes(url):
    result = client.scrape(url, format="markdown")
    
    # Extract prices and property details
    import re
    prices = re.findall(r'\$[\d,]+', result.content)
    
    return {
        'url': url,
        'prices': prices,
        'timestamp': datetime.now().isoformat()
    }

job = client.create_crawl_job(
    url="https://www.zillow.com/san-francisco-ca/",
    depth=2,
    link_limit=50,
    patterns=["/homedetails/*"]
)

result = client.wait_for_crawl(job.job_id)

prices = []
for url, data in result.data.crawl_data.items():
    price_match = re.search(r'\$[\d,]+', data.markdown)
    if price_match:
        prices.append(int(price_match.group().replace('$', '').replace(',', '')))

avg_price = sum(prices) / len(prices)
print(f"Average price: ${avg_price:,.0f}")