Understand Socket
Socket is also commonly called "socket", which is used to describe IP addresses and ports. It is the handle of a communication chain. Applications usually make requests to the network or respond to network requests through "sockets".
Socket originated from Unix, and one of the basic philosophies of Unix/Linux is "everything is a file". For files, use the [Open] [Read and Write] [Close] mode to operate. Socket is an implementation of this mode. Socket is a special file. Some socket functions are operations on it (read/write IO, open, close). The difference between socket and file:
file module is for [Open] [Read and Write] [Close] a specified file
The socket module is for server-side and client-side Sockets to [Open] [Read and Write] [Close]
ython (version 3.5 ) To achieve the simplest socket communication
#!/usr/bin/env python # coding=utf-8 # Author:Majh import socket ip_port = ('127.0.0.1', 9999) sk = socket.socket() sk.connect(ip_port) send_data = input('>>').strip() sk.send(bytes(send_data, encoding='utf-8')) recv_data = sk.recv(1024) print(str(recv_data, encoding='utf-8')) sk.close() 客户端代码
#!/usr/bin/env python # coding=utf-8 # Author:Majh import socket sk = socket.socket() ip_port = ('127.0.0.1', 9999) sk.bind(ip_port) print('sk.bind......') sk.listen(5) print('sk.listen......') conn, addr = sk.accept() print('conn:', conn) print('addr:', addr) read_data = conn.recv(1024) print('read_data', read_data) read_data = read_data.upper() conn.send(read_data) conn.close() 服务器端代码
socket keyword parameters:
sk = socket.socket(socket.AF_INET,socket.SOCK_STREAM,0)
Parameter 1: Address cluster
socket.AF_INET IPv4 (default)
socket.AF_INET6 IPv6
socket.AF_UNIX can only be used for inter-process communication in a single Unix system
Parameter 2: Type
socket.SOCK_STREAM Streaming socket, for TCP (default)
socket.SOCK_DGRAM Datagram socket , for UDP
socket.SOCK_RAW raw socket. Ordinary sockets cannot process network messages such as ICMP and IGMP, but SOCK_RAW can. Secondly, SOCK_RAW can also process special IPv4 messages. In addition, using raw sockets word, the IP header can be constructed by the user via the IP_HDRINCL socket option.
socket.SOCK_SEQPACKET Reliable continuous packet service
Parameter three: Protocol
0 (Default) The protocol related to a specific address family. If it is 0, the system will automatically select it based on the address format and socket category. A suitable protocol
sk.bind(address)
s.bind(address) binds the socket to the address. The format of address depends on the address family. Under AF_INET, the address is expressed in the form of a tuple (host, port).
sk.listen(backlog)
Start listening for incoming connections. The backlog specifies the maximum number of connections that can be pending before the connection is rejected.
Backlog equals 5, indicating that the kernel has received the connection request, but the server has not yet called accept for processing. The maximum number of connections is 5
This value cannot be infinite because the connection queue must be maintained in the kernel
sk.setblocking( bool)
Whether to block (default True), if set to False, an error will be reported if there is no data during accept and recv.
sk.accept()
Accept the connection and return (conn, address), where conn is a new socket object that can be used to receive and send data. address is the address to connect to the client.
Receive the connection from the TCP client (blocking) and wait for the connection to arrive
sk.connect(address)
Connect to the socket at address. Generally, the format of address is a tuple (hostname, port). If a connection error occurs, a socket.error error is returned.
sk.connect_ex(address)
Same as above, except there will be a return value, 0 is returned when the connection is successful, and the code is returned when the connection fails, for example: 10061
sk.close()
Close the socket
sk .recv(bufsize[,flag])
Accepts socket data. The data is returned as a string, and bufsize specifies the maximum number that can be received. flag provides additional information about the message and can usually be ignored.
sk.recvfrom(bufsize[.flag])
Similar to recv(), but the return value is (data, address). Where data is a string containing the received data, and address is the socket address to which the data is sent.
sk.send(string[,flag])
Send the data in string to the connected socket. The return value is the number of bytes to send, which may be less than the string's byte size. That is: all specified content may not be sent.
sk.sendall(string[,flag])
Sends the data in string to the connected socket, but attempts to send all data before returning. Returns None on success, throws an exception on failure.
Internally, all content is sent out by calling send recursively.
sk.sendto(string[,flag],address)
Send data to the socket, address is a tuple in the form of (ipaddr, port), specifying the remote address. The return value is the number of bytes sent. This function is mainly used for UDP protocol.
sk.settimeout(timeout)
Set the timeout period for socket operations. timeout is a floating point number in seconds. A value of None means there is no timeout period. Generally, the timeout period should be set when the socket is first created, because they may be used for connection operations (such as client connections waiting up to 5s)
sk.getpeername()
Returns the remote address of the connected socket. The return value is usually a tuple (ipaddr, port).
sk.getsockname()
Returns the socket’s own address. Usually a tuple (ipaddr,port)

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 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'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.

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 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.

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.


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