This article mainly introduces the detailed introduction of Python Socket programming. Socket can establish connections and transmit data. It has certain reference value. Interested friends can refer to it.
When using Python for socket programming, since you need to use blocking (default) to read the data stream, you need to handle the end of the data yourself every time, which is too troublesome. And I couldn't find a good package on the Internet, so I wrote a simple package myself.
Encapsulation ideas
1. The client sends a SocketRequest object for each request, which encapsulates specific data. json is used here. For the data to be sent, an end character identifier (EOF = ‘0x00’) is automatically added.
2. When the server receives data, it generates complete data based on the end character identifier and unpacks it into a SocketRequest object.
3. The server generates a SocketResponse object based on the content of the SocketRequest. Here a SimpleRequestHandler class is used to process it. In the example, no processing is done and the object is returned as is.
4. The server sends SocketResponse to the client. The package also needs to be encapsulated, and an end character identifier (EOF = ‘0x00’) will be automatically added.
5. When the client receives data, it generates complete data based on the end character identifier, unpacks it into a SocketResponse object, and then returns it.
Packaging class
sockets.py
#!/usr/bin/env python # -*- coding: utf-8 -*- import socket import pickle import thread PORT = 12345 EOF = '0x00' class SocketServer(object): def __init__(self, port=None): self.port = port def startup(self): sock_server = socket.socket(socket.AF_INET, socket.SOCK_STREAM) sock_server.bind(('0.0.0.0', self.port)) sock_server.listen(0) while True: sock, address = sock_server.accept() thread.start_new_thread(self.__invoke, (sock, address)) def shutdown(self): pass def __invoke(self, sock, address): try: full_data = '' while True: data = sock.recv(1024) if data is None: return full_data += data if full_data.endswith(EOF): full_data = full_data[0:len(full_data) - len(EOF)] request = pickle.loads(full_data) response = SimpleRequestHandler().handle(request) sock.sendall(pickle.dumps(response) + EOF) return except Exception as e: print e finally: sock.close() class SocketClient(object): def __init__(self, host, port): self.host = host self.port = port def execute(self, request): sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) sock.connect((self.host, self.port)) try: sock.sendall(pickle.dumps(request) + EOF) full_data = '' while True: data = sock.recv(1024) if data: full_data += data if full_data.endswith(EOF): full_data = full_data[0:len(full_data) - len(EOF)] response = pickle.loads(full_data) return response else: return None except Exception as e: print e return None finally: sock.close() class SocketRequest(object): def __init__(self, data): self.data = data def __repr__(self): return repr(self.__dict__) class SocketResponse(object): def __init__(self, data): self.data = data def __repr__(self): return repr(self.__dict__) class SimpleRequestHandler(object): def __init__(self): pass def __repr__(self): return repr(self.__dict__) def handle(self, request): return SocketResponse(request.data)
Test
socket_server.py
##
#!/usr/bin/env python # -*- coding: utf-8 -*- from agent.sockets import * ss = SocketServer(PORT) ss.startup()socket_client.py
##
#!/usr/bin/env python # -*- coding: utf-8 -*- import pickle from agent.sockets import * sc = SocketClient('localhost', PORT) request = SocketRequest('abc') response = sc.execute(request) print request print response
Run test
First, run socket_server.py
Then, run socket_client.py
The above is the detailed content of Detailed explanation of using Python Socket programming. For more information, please follow other related articles on the PHP Chinese website!

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.

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 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.

Python's real-world applications include data analytics, web development, artificial intelligence and automation. 1) In data analysis, Python uses Pandas and Matplotlib to process and visualize data. 2) In web development, Django and Flask frameworks simplify the creation of web applications. 3) In the field of artificial intelligence, TensorFlow and PyTorch are used to build and train models. 4) In terms of automation, Python scripts can be used for tasks such as copying files.

Python is widely used in data science, web development and automation scripting fields. 1) In data science, Python simplifies data processing and analysis through libraries such as NumPy and Pandas. 2) In web development, the Django and Flask frameworks enable developers to quickly build applications. 3) In automated scripts, Python's simplicity and standard library make it ideal.

Python's flexibility is reflected in multi-paradigm support and dynamic type systems, while ease of use comes from a simple syntax and rich standard library. 1. Flexibility: Supports object-oriented, functional and procedural programming, and dynamic type systems improve development efficiency. 2. Ease of use: The grammar is close to natural language, the standard library covers a wide range of functions, and simplifies the development process.

Python is highly favored for its simplicity and power, suitable for all needs from beginners to advanced developers. Its versatility is reflected in: 1) Easy to learn and use, simple syntax; 2) Rich libraries and frameworks, such as NumPy, Pandas, etc.; 3) Cross-platform support, which can be run on a variety of operating systems; 4) Suitable for scripting and automation tasks to improve work efficiency.

Yes, learn Python in two hours a day. 1. Develop a reasonable study plan, 2. Select the right learning resources, 3. Consolidate the knowledge learned through practice. These steps can help you master Python in a short time.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

PhpStorm Mac version
The latest (2018.2.1) professional PHP integrated development tool

SublimeText3 Linux new version
SublimeText3 Linux latest version

VSCode Windows 64-bit Download
A free and powerful IDE editor launched by Microsoft

ZendStudio 13.5.1 Mac
Powerful PHP integrated development environment

Notepad++7.3.1
Easy-to-use and free code editor