Prompt

How do I scrape Zillow data?

Latest observation

Jul 15, 2026 · OpenAI APIWeb search: off

Scraping Zillow is tricky, and in many cases it may violate Zillow’s Terms of Use and/or trigger anti-bot protections. I can’t help with bypassing protections or scraping private/internal pages in a way that violates terms.

What I can help with is safer, compliant alternatives:

Better options

  1. Use Zillow’s official / partner APIs

    • If you need listings or market data, see whether Zillow offers a sanctioned API or partner access for your use case.
  2. Use public data sources

    • County assessor records
    • MLS feeds if you have access
    • Public real estate datasets
    • Open property data APIs
  3. Collect only what’s permitted

    • If a site explicitly allows automated access and provides an API or downloadable data, use that.

If you’re doing allowed scraping on a site that permits it

General best practices:

  • Check robots.txt and Terms of Use
  • Rate limit requests
  • Identify your user agent honestly
  • Cache responses
  • Avoid login-only or protected content
  • Don’t try to bypass CAPTCHAs, fingerprinting, or access controls

Example of a compliant scraping pattern

If you have permission to scrape a site and it exposes public HTML:

import requests
from bs4 import BeautifulSoup
import time

url = "https://example.com/listings"
headers = {"User-Agent": "MyResearchBot/1.0 (contact: you@example.com)"}

resp = requests.get(url, headers=headers, timeout=15)
resp.raise_for_status()

soup = BeautifulSoup(resp.text, "html.parser")
for item in soup.select(".listing"):
    title = item.select_one(".title")
    price = item.select_one(".price")
    print(title.get_text(strip=True) if title else None,
          price.get_text(strip=True) if price else None)

time.sleep(2)

If your goal is Zillow-like property data

Tell me what you need exactly:

  • home values
  • property details
  • rental listings
  • sold comps
  • neighborhood stats
  • market trends

I can help you find a legal data source or build a pipeline around public datasets/API access.

Brands

Observation history

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How did Obsurfable measure this prompt?

Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.

Which AI systems does Obsurfable collect answers from?

OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, and Meta AI.