search
HomeBackend DevelopmentPython TutorialAnalysis and implementation of sending emails with Python and 163 mailbox authorization code (code)

The content of this article is about the analysis and implementation (code) of sending emails with Python and 163 mailbox authorization code. It has certain reference value. Friends in need can refer to it. I hope it will be helpful to you. .

Background

I wrote an automatic clock-in script some time ago, but the script was not perfect enough. I needed to know whether the clock-in was successful or not, so I I thought of using Python to execute the code and then execute a piece of code to send the email. Once the requirements are clear, start analyzing and writing code to implement them.

Analysis

SMTP (Simple Mail Transfer Protocol), which is a simple mail transfer protocol, is a set of rules for transmitting mail from the source address to the destination address. It controls how letters are relayed.
Python's smtplib provides a very convenient way to send emails. It simply encapsulates the SMTP protocol.

Code implementation

import smtplib
from email.mime.text import MIMEText  
# 引入smtplib和MIMEText
from time import sleep

def sentemail():
    host = 'smtp.163.com'  
    # 设置发件服务器地址
    port = 465  
    # 设置发件服务器端口号。注意,这里有SSL和非SSL两种形式,现在一般是SSL方式
    sender = 'a419914150@163.com'  
    # 设置发件邮箱,一定要自己注册的邮箱
    pwd = 'SGJEKFBFK322'  
    # 设置发件邮箱的授权码密码,根据163邮箱提示,登录第三方邮件客户端需要授权码
    receiver = '419914150@qq.com' 
    # 设置邮件接收人,可以是QQ邮箱
    body = &#39;<h1 id="你已成功打卡">你已成功打卡</h1><p>zhongfs</p>&#39; 
    # 设置邮件正文,这里是支持HTML的
    msg = MIMEText(body, &#39;html&#39;) 
    # 设置正文为符合邮件格式的HTML内容
    msg[&#39;subject&#39;] = &#39;打卡通知&#39; 
    # 设置邮件标题
    msg[&#39;from&#39;] = sender  
    # 设置发送人
    msg[&#39;to&#39;] = receiver  
    # 设置接收人
    try:
        s = smtplib.SMTP_SSL(host, port)  
        # 注意!如果是使用SSL端口,这里就要改为SMTP_SSL
        s.login(sender, pwd)  
        # 登陆邮箱
        s.sendmail(sender, receiver, msg.as_string())
        # 发送邮件!
        print (&#39;Done.sent email success&#39;)
    except smtplib.SMTPException:
        print (&#39;Error.sent email fail&#39;)
        
if __name__ == &#39;__main__&#39;:
    sentemail()

Execution

Program running screenshot:

Analysis and implementation of sending emails with Python and 163 mailbox authorization code (code)

Screenshot of received email:

Analysis and implementation of sending emails with Python and 163 mailbox authorization code (code)

##Summary

This article briefly introduces how to use python to send emails through the 163 mailbox. And attached the code. Since it is relatively simple, I won’t elaborate further. The github code has been uploaded, the link is as follows:

https://github.com/rootzhongfengshan/python_practical/blob/master/SentMail/SentMail.py

The above is the detailed content of Analysis and implementation of sending emails with Python and 163 mailbox authorization code (code). For more information, please follow other related articles on the PHP Chinese website!

Statement
This article is reproduced at:博客园. If there is any infringement, please contact admin@php.cn delete
Python vs. C  : Learning Curves and Ease of UsePython vs. C : Learning Curves and Ease of UseApr 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.

Python vs. C  : Memory Management and ControlPython vs. C : Memory Management and ControlApr 19, 2025 am 12:17 AM

Python and C have significant differences in memory management and control. 1. Python uses automatic memory management, based on reference counting and garbage collection, simplifying the work of programmers. 2.C requires manual management of memory, providing more control but increasing complexity and error risk. Which language to choose should be based on project requirements and team technology stack.

Python for Scientific Computing: A Detailed LookPython for Scientific Computing: A Detailed LookApr 19, 2025 am 12:15 AM

Python's applications in scientific computing include data analysis, machine learning, numerical simulation and visualization. 1.Numpy provides efficient multi-dimensional arrays and mathematical functions. 2. SciPy extends Numpy functionality and provides optimization and linear algebra tools. 3. Pandas is used for data processing and analysis. 4.Matplotlib is used to generate various graphs and visual results.

Python and C  : Finding the Right ToolPython and C : Finding the Right ToolApr 19, 2025 am 12:04 AM

Whether to choose Python or C depends on project requirements: 1) Python is suitable for rapid development, data science, and scripting because of its concise syntax and rich libraries; 2) C is suitable for scenarios that require high performance and underlying control, such as system programming and game development, because of its compilation and manual memory management.

Python for Data Science and Machine LearningPython for Data Science and Machine LearningApr 19, 2025 am 12:02 AM

Python is widely used in data science and machine learning, mainly relying on its simplicity and a powerful library ecosystem. 1) Pandas is used for data processing and analysis, 2) Numpy provides efficient numerical calculations, and 3) Scikit-learn is used for machine learning model construction and optimization, these libraries make Python an ideal tool for data science and machine learning.

Learning Python: Is 2 Hours of Daily Study Sufficient?Learning Python: Is 2 Hours of Daily Study Sufficient?Apr 18, 2025 am 12:22 AM

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Python for Web Development: Key ApplicationsPython for Web Development: Key ApplicationsApr 18, 2025 am 12:20 AM

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python vs. C  : Exploring Performance and EfficiencyPython vs. C : Exploring Performance and EfficiencyApr 18, 2025 am 12:20 AM

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

See all articles

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

DVWA

DVWA

Damn Vulnerable Web App (DVWA) is a PHP/MySQL web application that is very vulnerable. Its main goals are to be an aid for security professionals to test their skills and tools in a legal environment, to help web developers better understand the process of securing web applications, and to help teachers/students teach/learn in a classroom environment Web application security. The goal of DVWA is to practice some of the most common web vulnerabilities through a simple and straightforward interface, with varying degrees of difficulty. Please note that this software

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

mPDF

mPDF

mPDF is a PHP library that can generate PDF files from UTF-8 encoded HTML. The original author, Ian Back, wrote mPDF to output PDF files "on the fly" from his website and handle different languages. It is slower than original scripts like HTML2FPDF and produces larger files when using Unicode fonts, but supports CSS styles etc. and has a lot of enhancements. Supports almost all languages, including RTL (Arabic and Hebrew) and CJK (Chinese, Japanese and Korean). Supports nested block-level elements (such as P, DIV),

PhpStorm Mac version

PhpStorm Mac version

The latest (2018.2.1) professional PHP integrated development tool