
Why do I need a proxy ip for real estate data capture?
The brothers who engaged in real estate data capture must have encountered this situation: just climbed a few minutes on the site to block your ip, or page loading suddenly become slow. Last year, a customer used an ordinary server to crawl an agent platform directly, and the result was blocked more than 20 ip in half an hour. this time, we need proxy ip toSwitching identities on a rotating basisIt's like playing a game and opening a small number, getting blocked and immediately changing to a new number and continuing to do it.
Take a real case: there is a small team to do house price monitoring, with dynamic residential ip every day can be stable crawl 100,000 + listings data. They use ipipgo's rotation strategy, set up every 5 minutes to automatically change the ip address, and ran for three months without being found by the target site.
Which proxy ip is the most reliable to choose?
There are three common types on the market:
| typology | Applicable Scenarios | Recommended Packages |
|---|---|---|
| Dynamic residential ip | High-frequency data crawling | ipipgo dynamic housing (standard) |
| Static residential ip | Long-term stable login required | ipipgo static homes |
| Data center ip | Short-term rapid capture | Not recommended (easily blocked) |
Here's the kicker.Dynamic residential ipThe advantages of dynamic ip are: ① IP from real home broadband ② automatic time change ③ support concurrent requests. For example, if you want to capture the historical transaction price of a certain neighborhood of Chain Store, you can simulate the access of users from different regions by using dynamic IP to reduce the risk of being blocked.
Hands-on configuration of proxy ip
Take the Python crawler for example, and use the ipipgo API to get the proxy ip:
import requests
def get_proxy().
Get dynamic residential ip from ipipgo
api_url = "https://api.ipipgo.com/dynamic?type=standard"
resp = requests.get(api_url).json()
return f"{resp['ip']}:{resp['port']}"
proxies = {
'http': 'socks5://' + get_proxy(),
'https': 'socks5://' + get_proxy()
}
Example of crawling Anjuke data
response = requests.get('https://www.anjuke.com/fangjia/', proxies=proxies)
Be careful to set thetimeout retry mechanism, which is recommended to be used with random User-Agent. If you are using the Scrapy framework, you can configure it like this in middlewares:
class ProxyMiddleware(object).
def process_request(self, request, spider).
proxy = get_proxy() Call the get method above
request.meta['proxy'] = f "socks5://{proxy}"
Randomly wait 1-3 seconds
time.sleep(random.uniform(1,3))
Frequently Asked Questions QA
Q: What should I do if my proxy ip is slow?
A: Priority is given to nodes that are geographically close, such as grabbing a domestic website and choosing the province's ip.ipipgo.TK LineSet latency can be controlled within 200ms.
Q: How can I tell if a proxy is in effect?
A: Print response.text in the code to see if the return content contains real data. Or use a third party website such as ipinfo.io to verify if the ip address has changed.
Q: What should I do if I encounter a 403 error?
A: ① immediately replace the proxy ip ② check whether the request header is complete ③ reduce the crawl frequency. It is recommended to use ipipgo'sDedicated static ippackage with up to 5000 requests per day for a single ip.
Why do you recommend ipipgo?
To be honest with you, after more than three years of experience, they have two killer features: 1)Real Residential IP PoolThe success rate of real estate websites can be as high as 98% ②.Automatic switching protocolFunctionality, encounter site upgrades backcrawl can also be adaptive.
The prices of specific packages are very transparent:
- Dynamic Residential (Standard) from $7.67/GB
- Static residential $35/month/ip
High-frequency crawling is recommended to choose a dynamic package, need to maintain the login status of the static ip.
Recently releasedSERP APIThe service is more trouble-free, directly call the interface to get the specified city's house price trend data, suitable for teams that do not want to maintain their own crawler.
As a final reminder, it is important to pay attention to frequency control when grabbing property data. Suggested settings:
①No more than 2 requests per second from a single IP.
② Change 50-100 IPs per day
③ Regular cleaning of cookies

