Python Parsing JSON Files: Data Structure Processing

Python play around with JSON files, proxy IP veteran driver to lead the way

Recently, a lot of old iron crawlers and I touted that now the site anti-climbing mechanism is more and more ruthless, especially when dealing with JSON data often eat the door. This is not, we will nag today how to use Python to JSON files packaged in a convincing manner, and then with a proxy IP killer, guaranteed to make your data collection as stable as the old dog.

I. JSON data structure three axes

First of all, the whole understanding of the JSON this stuff routine, it is akey-value pairThe nesting game. As a chestnut, the JSON returned using ipipgo's proxy IP interface looks like this:

{
  "status": "success",
  "proxies": [
    {"ip": "203.12.34.56", "port": 8888}, {"ip": "112.89.75.43", "port": 3128}, [
    {"ip": "112.89.75.43", "port": 3128}
  ]
}

To deal with this nested structure, keep three top tips in mind:

1. json.loads() - Turning strings into dictionaries
2. Dictionary.get() - Securely obtaining field values
3. list-deductive formula - Batch Processing Proxy IP List

Second, the proxy IP real combat scenarios revealed

When you're dealing with multiple data sources, remember to put a proxy vest on the requests:

import requests
import json

proxy = {"http": "http://203.12.34.56:8888"}

response = requests.get("http://api.example.com/data",
                       proxies=proxy, timeout=5)
                       timeout=5)
data = json.loads(response.text)

Here's a pitfall to watch out for:Survival detection of proxy IPsIt must be done! Recommended to use ipipgo's API to directly obtain a valid proxy, their IP pool survival rate can reach 99%, more reliable than the free proxy ten streets.

Third, JSON processing common rollover site

IV. QA time for veteran drivers

Q: What should I do if my proxy IP is not working?
A: It is recommended to replace a batch of IPs every 20-30 minutes. ipipgo's automatic replacement interface can be tuned directly, and the code is finished by adding a timed task.

Q: What should I do if the memory explodes when parsing JSON?
A: Try streaming parsing with the ijson library, especially when dealing with large files of up to G. This can be a lifesaver.

Q: How can I improve efficiency if I need to handle multiple APIs at the same time?
A: on the asynchronous request library aiohttp, together with ipipgo's concurrent proxy pool, the speed directly take off.

V. Guide to avoiding pitfalls

A few final words of advice for newbies:

• Free agents are like roadside stalls, it's okay to eat occasionally, but for long term use you have to be a regular army like ipipgo.
• Remember to check the encoding when dealing with Chinese data, don't wait for the messy code and then scratch your head.
• JSONPath syntax can save lives, complex structures directly on the $...xxx positioning

Engaging in data collection is like fighting guerrilla warfare, both the basic skills of parsing data, but also have to have a proxy IP this secret weapon. The next time you encounter a difficult website, remember to wear a proxy vest for the program, ipipgo family IP resource base is big enough and fresh enough, basically can handle the market 90% anti-climbing mechanism. Code tired of writing might as well go to their official website to take a look, recently seems to be doing activities, new users to send 10G traffic package it.