Parsing Data: A Guide to Information Extraction and Cleansing

When data capture meets proxy IPs, it's halfway there!

Anyone who has ever engaged in data crawling knows that the most afraid of encountering the face of the target site - either to limit the frequency of visits, or directly block the IP, at this time, if you have a reliable proxy IP on hand, it is like having a master key with you. For example, if you use ipipgo's IP rotation function to automatically switch to a different outlet for each request, the website's anti-crawling mechanism will not be able to figure out the rules.

import requests
from itertools import cycle

ip_pool = ipipgo.get_proxy_pool() get dynamic IP pool from ipipgo
proxies = cycle(ip_pool)

for page in range(1,101): current_proxy = next(proxies)
    current_proxy = next(proxies)
    current_proxy = next(proxies)
        res = requests.get(url, proxies={'http': current_proxy}, timeout=10)
         This is where the data parsing logic comes in...
    except: print(f "http": current_proxy}, timeout=10)
        print(f"{current_proxy} failed, automatically switching to the next one.")

Data Cleaning Triple Axe, Proxy IP to Assist

Often encountered with captured dataIt's like rice with sand in it., have to be handled with these tricks:

• Outlier filtering: multi-node validation with proxy IPs to exclude region-specific data interference
• Format standardization: different regions return time format differences, with ipipgo's location function intelligent conversion
• De-duplication optimization: combining IP geolocation tagging to identify duplicate content disguised as different regions

CAPTCHA hacking is not the only way out

Many tutorials teach people to stiffen CAPTCHA recognition, but actually use a proxy IP for thePace control of visitsSave more. Set ipipgo's IP pool to switch 1 new IP in 10 seconds, and the access frequency of single IP will naturally drop. This method is measured to reduce the CAPTCHA trigger rate by more than 60%.

A practical guide to avoiding the pit

Recently, I stepped into a pit when I helped a client grab e-commerce pricing data: a platform's anti-crawl will detect theASN information for IP addresses. The ASNs for regular proxy IPs are data center segments, and it took the residential IP service from ipipgo to fix it. Here's a tip - set the crawler request interval to a random value of 7-13 seconds, which is more natural than a fixed interval.

Frequently Asked Questions QA

Q: Why do I still get blocked with a proxy IP?
A: Check if you are using a transparent proxy, ipipgo's high stash of proxies will completely hide the real IP, and the request header will be randomized.

Q: What if I need to capture offshore data?
A: directly choose ipipgo's overseas nodes, pay attention to matching the time zone settings of the target region, do not catch the data in the other side of the early hours of the morning wild!

Q: What should I do if I encounter dynamically loaded data?
A: When using with headless browsers, remember to assign independent proxy IPs to each browser instance to avoid cookie crosstalk.

Q: How to verify if the proxy IP is effective?
A: Add a debugging check in the code, and periodically visit the IP verification interface provided by ipipgo to ensure that the proxy channel is normal

One last piece of cold knowledge: when using a proxy IP for data cleansing, you can take theIP Geographic Information as a Cleaning Dimension. For example, detecting the same content returning the same results from multiple country IPs will be much more credible than single region data. This kind of play is especially handy with ipipgo with geotagged IP pools, which is sort of a hidden trick for data people.