PythonJSON Parser: Data Processing Module

First, let's talk about Python's handling of JSON.

engage in data processing brothers should have encountered such a scene: from the Internet to pull down the data like a pile of messy hemp in front of the same, especially the JSON format, looking at the sky book like. At this time we have to come out of our Python JSON parser, this thing is simply the Swiss army knife of the data world. But ah, recently a lot of partners in the practice of encountering new problems -Requests too frequent to be pulled from the site, it's time for proxy IPs to step up to the plate and perform.

Hands-on teaching you to use proxy IP anti-blocking

For example, suppose we want to use requests library to capture the price data of an e-commerce platform. If we use the code directly, we will be blocked in less than half an hour.ipipgoThe proxy service will immediately come back to life. Watch this, the key code looks like this:

import requests
from json import JSONDecoder

 Here we replace the proxy tunnel address provided by ipipgo
proxy = {
    'http': 'http://username:password@gateway.ipipgo.com:9020', 'https': 'http://username:password@gateway.ipipgo.com:9020'
    'https': 'http://username:password@gateway.ipipgo.com:9020'
}

try.
    response = requests.get('https://api.example.com/data', proxies=proxy, timeout=10)
    data = JSONDecoder().decode(response.text)
     Processing data...
except Exception as e.
    print(f "There was an error capturing: {str(e)}")

Notice the proxy dictionary.username and passwordTo change to their own in ipipgo background to get the authentication information. After using this trick, each request will automatically switch to a different export IP, the site simply can not feel your real way.

Summary of common pitfalls in the real world

Private optimization tips for veteran drivers

1. Add to requestsretry decoratorAutomatically retry in case of failure
2. Use of ipipgoquantity-based billing packageIt's a great way to save money when doing small batch testing.
3. Save the parsed data asCompressed jsonlines formatThe following is an example of a space-saving and easy-to-follow-up process.

A must-see QA session for newbies

Q：JSON parsing always report errors?
A: First print the original response content, eighty percent of the site returned an error page. It is recommended to use ipipgo's high-quality proxy to reduce the probability of being anti-climbing

Q: What should I do if the proxy IP is invalid after I use it?
A: That's why it's important to go with ipipgo, whose IP pools200,000+ fresh IPs updated dailyAutomatic elimination of failed nodes

Q: How can I improve the efficiency of data collection?
A: Get on the multithread! In conjunction with ipipgo'sConcurrency-specific packagesRemember to control the frequency of requests, don't hang the other servers!

As a final note, data processing is like stir-frying, you have to get the seasoning right. Choose the right tool (such as ipipgo) can make your work efficiency doubled, less to go a lot of detours. Don't be deadlocked when you encounter problems, look at the official documentation, or directly to their technical support, the response speed is quite fast.