Python provides two levels of access to network services. At a low level, you can access the basic socket support in the underlying operating system, which allows you to implement clients and servers for both connection-oriented and connectionless protocols.
Python also has libraries that provide higher-level access to specific application-level network protocols, such as FTP, HTTP, and so on.
This chapter gives you understanding on most famous concept in Networking – Socket Programming.

Table of Contents

What are Sockets?

Sockets are the endpoints of a bidirectional communications channel. Sockets may communicate within a process, between processes on the same machine, or between processes on different continents.
Sockets may be implemented over a number of different channel types: Unix domain sockets, TCP, UDP, and so on. The socket library provides specific classes for handling the common transports as well as a generic interface for handling the rest.
Sockets have their own vocabulary

Sr.No.	Term & Description
1	Domain The family of protocols that is used as the transport mechanism. These values are constants such as AF_INET, PF_INET, PF_UNIX, PF_X25, and so on.
2	type The type of communications between the two endpoints, typically SOCK_STREAM for connection-oriented protocols and SOCK_DGRAM for connectionless protocols.
3	protocol Typically zero, this may be used to identify a variant of a protocol within a domain and type.
4	hostname The identifier of a network interface − A string, which can be a host name, a dotted-quad address, or an IPV6 address in colon (and possibly dot) notation A string “<broadcast>”, which specifies an INADDR_BROADCAST address. A zero-length string, which specifies INADDR_ANY, or An Integer, interpreted as a binary address in host byte order.
5	port Each server listens for clients calling on one or more ports. A port may be a Fixnum port number, a string containing a port number, or the name of a service.

The socket Module

To create a socket, you must use the socket.socket() function available in socket module, which has the general syntax −
s = socket.socket (socket_family, socket_type, protocol=0)
Here is the description of the parameters −
• socket_family − This is either AF_UNIX or AF_INET, as explained earlier.
• socket_type − This is either SOCK_STREAM or SOCK_DGRAM.
• protocol − This is usually left out, defaulting to 0.
Once you have socket object, then you can use required functions to create your client or server program. Following is the list of functions required −

Server Socket Methods

Sr.No.	Method & Description
1	s.bind() This method binds address (hostname, port number pair) to socket.
2	s.listen() This method sets up and start TCP listener.
3	s.accept() This passively accept TCP client connection, waiting until connection arrives (blocking).

Client Socket Methods

Sr.No.

Method & Description

s.connect()

This method actively initiates TCP server connection.

General Socket Methods

Sr.No.	Method & Description
1	s.recv() This method receives TCP message
2	s.send() This method transmits TCP message
3	s.recvfrom() This method receives UDP message
4	s.sendto() This method transmits UDP message
5	s.close() This method closes socket
6	socket.gethostname() Returns the hostname.

A Simple Server

To write Internet servers, we use the socket function available in socket module to create a socket object. A socket object is then used to call other functions to setup a socket server.
Now call bind(hostname, port) function to specify a port for your service on the given host.
Next, call the accept method of the returned object. This method waits until a client connects to the port you specified, and then returns a connection object that represents the connection to that client.

#!/usr/bin/python # This is server.py file

import socket # Import socket module

s = socket.socket() # Create a socket object
host = socket.gethostname() # Get local machine name
port = 12345 # Reserve a port for your service.
s.bind((host, port)) # Bind to the port

s.listen(5) # Now wait for client connection.
while True:
c, addr = s.accept() # Establish connection with client.
print 'Got connection from', addr
c.send('Thank you for connecting')
c.close() # Close the connection

A Simple Client

Let us write a very simple client program which opens a connection to a given port 12345 and given host. This is very simple to create a socket client using Python’s socket module function.
The socket.connect(hosname, port ) opens a TCP connection to hostname on the port. Once you have a socket open, you can read from it like any IO object. When done, remember to close it, as you would close a file.
The following code is a very simple client that connects to a given host and port, reads any available data from the socket, and then exits −

#!/usr/bin/python # This is client.py file

import socket # Import socket module

s = socket.socket() # Create a socket object
host = socket.gethostname() # Get local machine name
port = 12345 # Reserve a port for your service.

s.connect((host, port))
print s.recv(1024)
s.close() # Close the socket when done
Now run this server.py in background and then run above client.py to see the result.
# Following would start a server in background.
$ python server.py &

# Once server is started run client as follows:
$ python client.py

This would produce following result −
Got connection from (‘127.0.0.1’, 48437)
Thank you for connecting

Python Internet modules

A list of some important modules in Python Network/Internet programming.

Protocol	Common function	Port No	Python module
HTTP	Web pages	80	httplib, urllib, xmlrpclib
NNTP	Usenet news	119	nntplib
FTP	File transfers	20	ftplib, urllib
SMTP	Sending email	25	smtplib
POP3	Fetching email	110	poplib
IMAP4	Fetching email	143	imaplib
Telnet	Command lines	23	telnetlib
Gopher	Document transfers	70	gopherlib, urllib

Please check all the libraries mentioned above to work with FTP, SMTP, POP, and IMAP protocols.
So, this brings us to the end of blog. This Tecklearn ‘Network Programming in Python’ blog helps you with commonly asked questions if you are looking out for a job in Python Programming. If you wish to learn Python and build a career in Python Programming domain, then check out our interactive, Python with Data Science Training, that comes with 24*7 support to guide you throughout your learning period.

Python with Data Science Training

About the Course

Python with Data Science training lets you master the concepts of the widely used and powerful programming language, Python. This Python Course will also help you master important Python programming concepts such as data operations, file operations, object-oriented programming and various Python libraries such as Pandas, NumPy, Matplotlib which are essential for Data Science. You will work on real-world projects in the domain of Python and apply it for various domains of Big Data, Data Science and Machine Learning.

Why Should you take Python with Data Science Training?

• Python is the preferred language for new technologies such as Data Science and Machine Learning.
• Average salary of Python Certified Developer is $123,656 per annum – Indeed.com
• Python is by far the most popular language for data science. Python held 65.6% of the data science market.

What you will Learn in this Course?

Introduction to Python

• Define Python
• Understand the need for Programming
• Know why to choose Python over other languages
• Setup Python environment
• Understand Various Python concepts – Variables, Data Types Operators, Conditional Statements and Loops
• Illustrate String formatting
• Understand Command Line Parameters and Flow control

Python Environment Setup and Essentials

• Python installation
• Windows, Mac & Linux distribution for Anaconda Python
• Deploying Python IDE
• Basic Python commands, data types, variables, keywords and more

Python language Basic Constructs

• Looping in Python
• Data Structures: List, Tuple, Dictionary, Set
• First Python program
• Write a Python Function (with and without parameters)
• Create a member function and a variable
• Tuple
• Dictionary
• Set and Frozen Set
• Lambda function

OOP (Object Oriented Programming) in Python

• Object-Oriented Concepts

Working with Modules, Handling Exceptions and File Handling

• Standard Libraries
• Modules Used in Python (OS, Sys, Date and Time etc.)
• The Import statements
• Module search path
• Package installation ways
• Errors and Exception Handling
• Handling multiple exceptions

Introduction to NumPy

• Introduction to arrays and matrices
• Indexing of array, datatypes, broadcasting of array math
• Standard deviation, Conditional probability
• Correlation and covariance
• NumPy Exercise Solution

Introduction to Pandas

• Pandas for data analysis and machine learning
• Pandas for data analysis and machine learning Continued
• Time series analysis
• Linear regression
• Logistic Regression
• ROC Curve
• Neural Network Implementation
• K Means Clustering Method

Data Visualisation

• Matplotlib library
• Grids, axes, plots
• Markers, colours, fonts and styling
• Types of plots – bar graphs, pie charts, histograms
• Contour plots

Data Manipulation

• Perform function manipulations on Data objects
• Perform Concatenation, Merging and Joining on DataFrames
• Iterate through DataFrames
• Explore Datasets and extract insights from it

Scikit-Learn for Natural Language Processing

• What is natural language processing, working with NLP on text data
• Scikit-Learn for Natural Language Processing
• The Scikit-Learn machine learning algorithms
• Sentimental Analysis – Twitter

Introduction to Python for Hadoop

• Deploying Python coding for MapReduce jobs on Hadoop framework.
• Python for Apache Spark coding
• Deploying Spark code with Python
• Machine learning library of Spark MLlib
• Deploying Spark MLlib for Classification, Clustering and Regression

Got a question for us? Please mention it in the comments section and we will get back to you.

451