Whole site crawling technology: whole site proxy crawling program

The pitfalls encountered by the whole site crawl

The old iron doing data collection knows that whole site crawling is like dancing in a minefield. The biggest headache isIP blockedThe crawler script was not easy to write, and it took two hours for the target site to be blacklisted. Last week there is an e-commerce price comparison brother spit, they use a fixed IP to catch the price of a platform, just after catching the first page of the goods to trigger the wind control, the result is that even the company's intranet are restricted access.

Another common problem isspeed bottleneckThe single-threaded crawling is so inefficient, especially when collecting dynamically loaded content, that you want to smash your keyboard. What's even more pitiful is that some websites will setGeographical limitationFor example, some government websites only allow local IP access, which is not possible without a proxy.

Proxy IP breakthroughs

Here's a wild card to teach you:distributed IP rotationIt's like a guerrilla war. Like guerrilla warfare, each request for a different exit IP. for example, with ipipgo's dynamic residential proxy, each request automatically switches to a different area of the residential IP, the site can not distinguish between a real person to visit or machine operation.

import requests
from itertools import cycle

proxies = cycle(ipipgo.get_proxy_list()) get dynamic proxy pool from ipipgo

for page in range(1,100): current_proxy = next(proxies)
    current_proxy = next(proxies)
    try.
        res = requests.get(url, proxies={'http': current_proxy}, timeout=10)
         Processing data...
    except: print(f "f")
        print(f"{current_proxy} failed, automatically switching to the next one.")

Take care to set up a reasonablerequest intervalIt is recommended to use it with randomized delays. Don't be like some Iron Bean, open 100 threads crazy request, even the best proxy can't carry so build.

Real-world configuration scenarios

It is important to choose the type of agent according to the collection needs, here is a comparison table:

There is a case of a customer doing public opinion monitoring: they used ipipgo's TK leased line proxy with customized request headers to successfully bypass the fingerprint detection of a social platform, collecting millions of data volume on average every day.

Guide to avoiding the pit

1. Don't use free agents.--Nine out of ten freebies are in the pit, and the rest are mining.
2. Encounter CAPTCHA don't tough - the use of coding platform on, don't with the CAPTCHA dead beat!
3. Update the User-Agent regularly - don't let all requests bear the same browser fingerprint!
4. Setting up a failure retry mechanism - it is recommended that the maximum number of retries be 3 to avoid a dead loop.

Frequently Asked Questions QA

Q: What should I do if my proxy IP is slow?
A: Prioritize the local operator resources, for example, ipipgo supports filtering nodes by country and city. At the same time, check whether the request carries extra cookies, sometimes clear the history of the session can speed up!

Q: How do I break into Cloudflare protection?
A: Use residential proxy + browser fingerprint simulation two-pronged. ipipgo's cross-border special line proxy for this type of protection has a miraculous effect, the success rate of the actual test to improve 60%

Q: Is data scraping legal?
A: Be sure to comply with the robots agreement and don't touch personal privacy data. It is recommended to set up a compliance policy in the ipipgo console to automatically filter sensitive websites

Lastly, a word of caution: technology is a double-edged sword, the use of proxy IP to do the collection to pay attention to thesense of proprietyIt's like eating a buffet. Like eating a buffet, do not catch a dish to the dead grip, the site can not carry, they are also prone to trouble. Reasonable control of the collection frequency, good request camouflage, this is the way to last.