Home Backend Development Python Tutorial Detailed explanation of the web-side json communication protocol implemented by python3

Detailed explanation of the web-side json communication protocol implemented by python3

Feb 11, 2017 pm 01:21 PM

This article mainly introduces the web-side json communication protocol implemented by python3. It has certain reference value. Interested friends can refer to it.

I used python3 to implement the tcp protocol before, and later implemented the http protocol communication. Today the company wants to make a functional automatic test system.

After working on it for a while in the afternoon, I found that the json format The implementation can be simpler. The code is as follows: To explain briefly, communication with the server is generally divided into two parts, one is the get protocol and the other is the post protocol.

The get protocol is very simple and can be accessed directly. The post protocol , in fact, when data is used, the program will automatically identify the type.

I encountered three problems during the writing process:

1 I encountered an error when implementing the post protocol.

Generally speaking, the problem of data format is very easy to solve. Simple, convert to utf-8 format: bytes(data, 'utf8'),

2 The obtained json data encounters encoding problems when it encounters Chinese inside

It is found that it shows 0xaa0xbb0xcc0xdd like this For encoding, just call utf8 when loading json. Use this code: json.loads(rawtext.decode('utf8'))

3 When printing out json, a very long string will appear.

It’s very painful to read long strings, and I can’t clearly see the relationship between the objects in json. The Internet says what json.tool method should be used to solve it, but that is for the command line. I am here During the debugging process, you still want to print it out directly.

Use the following code: print (json.dumps(jsonStr, sort_keys=False, ensure_ascii= False, indent=2)). It should be noted here that ensure_ascii must be False, otherwise When there is Chinese in it, what you see is 0xx or something. indent=2 means formatted json display, and sort_keys means that this json does not need to be sorted.


#!/usr/bin/evn python3
#coding=utf-8

# 针对web端json协议的通信库,通信协议为json,传出的data为json格式,接收的数据也是json格式
# 外界调用时可先初始化web_json类,如下所示:
# get调用
# web = web_json("http://baidu.com/")
# params = "abcd/select/100000?userID=1234&groupID=79"
# web.url_get(params)
# 
# post调用
# web = web_json("http://baidu.com/")
# params = "abcd/select/100000"
# data = '{"name": "jack", "id": "1"}'
# web.url_post(params, data)

from urllib.request import urlopen
from urllib.parse import quote
import json

class web_json:
  def __init__(self, base_url):
    self.base_url = base_url
    
  def get_url_data(self, params, data):
    web = urlopen(self.base_url + params, data)
    print (web.url)
    print ("status: " , web.status)
    rawtext = web.read()
    jsonStr = json.loads(rawtext.decode('utf8'))  
    print (json.dumps(jsonStr, sort_keys=False, ensure_ascii= False, indent=2))
    return jsonStr    
  
  # get方法
  def url_get(self, params):
    return self.get_url_data(params, None)
  
  # post方法
  def url_post(self, params, data):
    data=bytes(data, 'utf8')
    return self.get_url_data(params, data)
Copy after login


The above is the entire content of this article. I hope it will be helpful to everyone’s learning. I also hope that everyone will support the PHP Chinese website.

For more detailed articles on the web-side json communication protocol implemented by python3, please pay attention to the PHP Chinese website!

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

Hot Topics

Java Tutorial
1664
14
PHP Tutorial
1267
29
C# Tutorial
1239
24
Python vs. C  : Applications and Use Cases Compared Python vs. C : Applications and Use Cases Compared Apr 12, 2025 am 12:01 AM

Python is suitable for data science, web development and automation tasks, while C is suitable for system programming, game development and embedded systems. Python is known for its simplicity and powerful ecosystem, while C is known for its high performance and underlying control capabilities.

Python: Games, GUIs, and More Python: Games, GUIs, and More Apr 13, 2025 am 12:14 AM

Python excels in gaming and GUI development. 1) Game development uses Pygame, providing drawing, audio and other functions, which are suitable for creating 2D games. 2) GUI development can choose Tkinter or PyQt. Tkinter is simple and easy to use, PyQt has rich functions and is suitable for professional development.

The 2-Hour Python Plan: A Realistic Approach The 2-Hour Python Plan: A Realistic Approach Apr 11, 2025 am 12:04 AM

You can learn basic programming concepts and skills of Python within 2 hours. 1. Learn variables and data types, 2. Master control flow (conditional statements and loops), 3. Understand the definition and use of functions, 4. Quickly get started with Python programming through simple examples and code snippets.

Python vs. C  : Learning Curves and Ease of Use Python vs. C : Learning Curves and Ease of Use Apr 19, 2025 am 12:20 AM

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

How Much Python Can You Learn in 2 Hours? How Much Python Can You Learn in 2 Hours? Apr 09, 2025 pm 04:33 PM

You can learn the basics of Python within two hours. 1. Learn variables and data types, 2. Master control structures such as if statements and loops, 3. Understand the definition and use of functions. These will help you start writing simple Python programs.

Python and Time: Making the Most of Your Study Time Python and Time: Making the Most of Your Study Time Apr 14, 2025 am 12:02 AM

To maximize the efficiency of learning Python in a limited time, you can use Python's datetime, time, and schedule modules. 1. The datetime module is used to record and plan learning time. 2. The time module helps to set study and rest time. 3. The schedule module automatically arranges weekly learning tasks.

Python: Automation, Scripting, and Task Management Python: Automation, Scripting, and Task Management Apr 16, 2025 am 12:14 AM

Python excels in automation, scripting, and task management. 1) Automation: File backup is realized through standard libraries such as os and shutil. 2) Script writing: Use the psutil library to monitor system resources. 3) Task management: Use the schedule library to schedule tasks. Python's ease of use and rich library support makes it the preferred tool in these areas.

Python: Exploring Its Primary Applications Python: Exploring Its Primary Applications Apr 10, 2025 am 09:41 AM

Python is widely used in the fields of web development, data science, machine learning, automation and scripting. 1) In web development, Django and Flask frameworks simplify the development process. 2) In the fields of data science and machine learning, NumPy, Pandas, Scikit-learn and TensorFlow libraries provide strong support. 3) In terms of automation and scripting, Python is suitable for tasks such as automated testing and system management.

See all articles