Zillow Dataset: Historical Real Estate Data Package Download

Why does the Zillow packet download always get stuck?

The old iron engaged in real estate data analysis must have encountered this situation: when climbing Zillow historical housing price data, either the page loads slowly into a tortoise, or suddenly popped up the CAPTCHA, the worst thing is that the IP is directly blocked. This shit is like eating noodles without seasoning packets - suffocating very much. The root cause is just two words:IP exposureZillow's anti-crawler system specifically focuses on high-frequency visits to IP addresses, and using a single IP to aggressively glean data will blacklist you in minutes.

How did proxy IPs become a lifesaver?

For example, downloading Zillow data on your home network is the equivalent of wearing a fluorescent green jacket and bouncing under the monitor. Switching to a proxy IP is like playing a drag show - a new vest (IP address) for every request. This is especially true withDynamic Residential AgentsZillow can't tell if it's a real person or a machine, with the thousands of real home network addresses in the IP pool.

import requests
proxies = {
  'http': 'http://user:password@gateway.ipipgo.io:3000',
  'https': 'http://user:password@gateway.ipipgo.io:3000'
}
response = requests.get('https://www.zillow.com/homes/data', proxies=proxies)

Three Tips for Choosing the Right Proxy Service Provider

There are many proxy IP service providers in the market, but there are more pits than motorcycle drivers at the subway entrance. Focus on these three indicators:

Like the ones we use at home.ipipgoThe biggest advantage ofThe residential IP pool is deepThe last time I helped a client climb Los Angeles home price data, 3 requests per second for 12 consecutive hours did not trigger wind control. The last time I helped a client crawl Los Angeles home price data, 3 requests per second for 12 hours straight didn't trigger wind control, and the background showed that 800+ residential IPs from different cities were used to switch automatically.

Hands-on configuration tutorial

Here's a demonstration using Python's Scrapy framework (don't panic, it's only 5 lines of code):

 Add these two lines to settings.py
ROTATING_PROXY_LIST = [
  'gateway.ipipgo.io:3000',
  
  'gateway.ipipgo.io:3002'
]
DOWNLOADER_MIDDLEWARES = {
  'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware': 543,
}

Here's the kicker: remember to turn it on in the ipipgo backend!Intelligent Routingmode, the system will automatically match the IP of the location of the Zillow server. for example, to climb the U.S. Texas data, it will prioritize the allocation of residential IP of Dallas and Houston, and the latency can be reduced by more than 60%.

Old Driver's Guide to Avoiding Pitfalls

1. Don't use free agents.: Nine out of ten IPs that claim to be free have been flagged by Zillow for crawlers.

2. Control request frequency: Even if you use a proxy, don't send 20 requests per second like you're having a seizure!

3. Fake Headers: Remember to randomize the User-Agent, don't use Scrapy's default!

Frequently Asked Questions QA

Q: Why is it still blocked even though I've already used a proxy?

A: Check if you are using a data center IP, replace it with ipipgo's residential proxy to solve the problem immediately.

Q: Do I need to maintain my own IP pool?

A: No need at all, ipipgo background automatically eliminates the invalid IP, at 2:00 in the morning can still run the data

Q: How long does it take to download historical data?

A: With a single-threaded crawl, 100,000 records about 6 hours, it is recommended to open 5 threads with ipipgo 5 ports at the same time to run!

And finally, the big truth: the whole data crawler thing.Proxy IPs are chosen correctly, and time off work is twice as early. Especially the ones with smart routing like ipipgo, which is equivalent to hiring an IP scheduler who doesn't sleep 24 hours a day, saving you enough time to brush up on ten episodes of Silicon Valley.