Job Posting Dataset: How to Crawl Global Recruitment Data Efficiently with Proxy IPs

When crawlers meet job boards: the potholes we stepped on in those years

Recently, a friend who does AI training complained to me that he spent three days to climb the job data, and just two hours after the capture, the website blocked the IP. this scene is like a barbecue stall just set up, the city police came to collect the table as embarrassing. Friends who do data analysis should understand that the biggest roadblock to global recruitment data collection is the website'santi-climbing mechanismThe

To cite a real case: a job search platform only allows the same IP access 50 times per hour, more than 24 hours of direct ban. If you use a single IP hard to catch the global job data of a multinational enterprise, it is estimated that you have to wait until the next century. This is the time toproxy IPOn the field, the equivalent of the crawler put on a myriad of "vests", so that the site thinks that each visit is a different real person.

Choosing a proxy IP is like buying seafood: live is fresh!

The agent service providers on the market are a mixed bag, here to teach you three tricks to pick goods skills:

Here's an honorable mention for our own productsipipgoThe Dynamic Residential Proxy, the measured success rate of switching IP 500 times when catching LinkedIn stays above 98%. Just like the oxygen pump in the seafood market, it ensures that every IP is fresh and available.

A handful of reptilian "vests".

In the case of the Python crawler, for example, there are only three steps to use ipipgo's proxy service:

import requests

 Proxy information from ipipgo
proxy = {
    'http': 'http://用户名:密码@gateway.ipipgo.com:端口',
    'https': 'https://用户名:密码@gateway.ipipgo.com:端口'
}

response = requests.get('Target site URL', proxies=proxy, timeout=10)

focus ontimeout settingrespond in singingException handling, it is recommended to use with random User-Agent. It's like playing a game of chicken, not only do you have to change your outfit frequently, but you also have to learn to snake your way around.

A practical guide to avoiding the pit

Lessons learned while helping a client grab Indeed data recently:

1. Don't focus on one country, alternate between European, American and Southeast Asian IPs.
2. Success rate increase of 40% from 2-5 a.m. (site defense is relatively lax)
3. Don't fight with CAPTCHA, automatic IP switching is more efficient than cracking.
4. Replacement of agent authorization keys on a daily basis (self-service operation available in the ipipgo back office)

Frequently Asked Questions First Aid Kit

Q: What should I do if I always encounter a 403 error?
A: First check if the IP is exposed, use ipipgo's high stash proxy mode. It's like passing notes in the exam room, you can't let the invigilator find out the source.

Q: How to deal with incomplete data capture?
A: It may be that the IP is marked by the website, switch the country node immediately. It is recommended to enable ipipgo's intelligent routing function to automatically avoid blacklisted IPs.

Q: Will it conflict to have more than one crawler on at the same time?
A: With ipipgo's concurrent proxy pool, each crawler independent IP channel. Like a highway with multiple lanes, each running their own without crashing.

Q: How can I tell if a proxy is in effect?
A: Visit https://ip.ipipgo.com/ to see the country and carrier information of the current export IP.

Tell the truth.

Used more than a dozen kinds of agent services, the final choice of self-built ip ipgo is not without reason. A lot of agents say "millions of IP pool", the actual can be used less than 30%. Our family's proxy IP survival rate is strictly controlled at 95% or more, just like the delivery boy's electric car, always keep full power on standby.

Finally, I would like to remind you: reasonable control of the collection frequency, it is recommended to cooperate with the time random interval (0.5-3 seconds). After all, the site has to live, don't crash their servers. Use a good proxy IP this tool, in order to get the gold mine of data in the long run.