Python Online Training

Introduction

• History
• Features
• Setting up path
• Working with Python
• Basic Syntax
• Variable and Data Types
• Operator

Conditional Statements

• If
• If- else
• Nested if-else

Looping

• For
• While
• Nested loops

Control Statements

• Break
• Continue
• Pass

String Manipulation

• Accessing Strings
• Basic Operations
• String slices
• Function and Methods

Lists

• Introduction
• Accessing list
• Operations
• Working with lists
• Function and Methods

Tuple

• Introduction
• Accessing tuples
• Operation
• Working
• Functions and Methods

Dictionaries

• Introduction
• Accessing values in dictionaries
• Working with dictionaries
• Properties
• Functions

Functions

Defining a function
Calling a function
Types of functions
Function Arguments
Anonymous functions
Global and local variables

Modules

• Importing module
• Math module
• Random module
• Packages
• Composition

Input-Output

• Printing on screen
• Reading data from keyboard
• Opening and closing file
• Reading and writing files
• Functions

Exception Handling

• Exception
• Exception Handling
• Except clause
• Try ? finally clause
• User Defined Exceptions

Advanced Python

OOPS

Attributes Inheritance Overloading Overriding Data hiding

Regular expressions

• Match function
• Search function
• Matching VS Searching
• Modifiers
• Patterns

CGI

• Introduction
• Architecture
• CGI environment variable
• GET and POST methods
• Cookies
• File upload

Database

• Introduction
• Connections
• Executing queries
• Transactions
• Handling error

Networking

• Socket
• Socket Module
• Methods
• Client and server
• Internet module

CGI

• Introduction
• Architecture
• CGI environment variable
• GET and POST methods
• Cookies
• File upload

GUI Programming

• Introduction
• Tkinter programming
• Tkinter widgets

Some useful info on Python

Difference between Python2 and Python3:

Difference between Python2 and Python3:

Python3 was released in year 2008. Python3 stopped supporting some of the syntax of its predecssor Python2.7. Python2.7 is supposed to be retired and it’s no longer be used.
There are several differences between Python2.7 and Python3.0. Here are a few major differences:
1. Python3.0 has different division from Python2.7: In Python2, 5/2 will result 2, where as 5.0/2.0 results 2.5
That means, if you are not using decimals in any of the two numbers, the result will not truncate the value after decimal point.
In Python3.0, 5/2 will result 2.5, which is as expected.
This way, Python3 is more intuitive. That’s one reason why it has become more popular over Python2

2. Difference in ‘print’ statement: Python2, it was a print statement whereas it’s replaced by print() function in Python3.
Python2: print “hello”
Python3: print(“hello”)

3. Strings ASCII vs UNICODE: In Python2, Strings are stored as ASCII, you have to add a “u” if you want to store strings as Unicode in Python 2.x.
In Python3, String are stored as Unicode by default

This is important because Unicode is more versatile than ASCII. Unicode strings can store foreign language letters, Roman letters and numerals, symbols, emojis, etc., offering you more choices.

How to convert Python2.x code to Python3.x

2to3 is a Python program, that can read the 2.x source and convert to 3.x code. The is program is located under Tools/scripts folder.

Some Useful Concepts and Programs in Python

Print even numbers within a given number (include the given number)

Program:
limit = 20;
print (“Even Numbers within: “, limit);
for n in list(range(1, limit+1)):
if (n%2==0):
print(n, end =” “)
print() print (“End of the program”)
Output:
Even Numbers within: 20
2 4 6 8 10 12 14 16 18 20
End of the program

List in Python: some common usage

Program:
l = [0,1,2,3,4,5,6,7,8,9]
print (“Length of the list: “, len(l))
l1 = l[:3]
print (“Sub list below index 3: “, l1)
l2 = l[3:]
print (“Sub list from index 3 (includes): “, l2)
l3 = l[:-2]
print (“List excluding last 2 elements from the list: “, l3)

l3a = l[-2:]
print (“Last 2 elements from the list: “, l3a)

l4=[10, 11]
l.extend(l4);
print (“Concatenate two lists: “, l)

l.append(12);
print (“Append one element to the list: “, l)

l6 = [89,45,9,23,89,5,890,3,60,45,9]
print(“Original list, before sort: “,l6);
l6.sort();
print(“Sorted list ascending: “,l6);
l6.sort(reverse=True)
print(“Sorted list descending: “,l6)

# list of lists
list1 = [‘first’, ‘second’]
list2 = [‘third’, ‘fourth’]
list1Andlist2 = [list1, list2]
print (‘list1: ‘, list1)
print (‘list2: ‘, list2)
print (‘lis of lists: ‘, list1Andlist2)

# Access a specific element in the list
print (‘index 1 is second element: ‘, list1[1])
print (‘index 0 is first element: ‘, list1[0])

Output:
Length of the list: 10
Sub list below index 3: [0, 1, 2]
Sub list from index 3 (includes): [3, 4, 5, 6, 7, 8, 9]
List excluding last 2 elements from the list: [0, 1, 2, 3, 4, 5, 6, 7]
Last 2 elements from the list: [8, 9]
Concatenate two lists: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
Append one element to the list: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
Original list, before sort: [89, 45, 9, 23, 89, 5, 890, 3, 60, 45, 9]
Sorted list ascending: [3, 5, 9, 9, 23, 45, 45, 60, 89, 89, 890]
Sorted list descending: [890, 89, 89, 60, 45, 45, 23, 9, 9, 5, 3]
list1: [‘first’, ‘second’]
list2: [‘third’, ‘fourth’]
lis of lists: [[‘first’, ‘second’], [‘third’, ‘fourth’]]
index 1 is second element: second
index 0 is first element: first

Tuple in Python: some examples

Program:
# Tuple. They are similar to Lists and immutable. Just use () instead of []. Use tuple when you have fixed lists
weekdays = (‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’, ‘Saturday’, ‘Sunday’)
print (‘Week days: ‘, weekdays);
print (“Week’s first day: “, weekdays[0])
print (“Week’s last day: “, weekdays[len(weekdays)-1])

Output:
Week days: (‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’, ‘Saturday’, ‘Sunday’)
Week’s first day: Monday
Week’s last day: Sunday

Dictionary in Python: some examples

Program:
#Dictionary is similar to Map in Java
examSchedule = {}
examSchedule[‘Mon’] = ‘English’
examSchedule[‘Tue’] = ‘Maths’
examSchedule[‘Wed’] = ‘Science’
examSchedule[‘Thu’] = ‘Social’
examSchedule[‘Fri’] = ‘French’

print (“Monday:”, examSchedule[‘Mon’])
print (“Monday:”, examSchedule.get(‘Mon’))
print()

#Loop through a dictionary
for key in examSchedule:
print(key, ‘:’, examSchedule[key])

print();
#Check if a key exists
if “Tue” in examSchedule:
print(“‘Tue’ exists in examSchedule and the value is: “, examSchedule[‘Tue’])
else:
print(“‘Tue’ not exists in the examSchedule”)

print()
#Remove an item in Dictionary
examSchedule.pop(“Tue”);
print(“‘Tue’ is popped”);
if “Tue” in examSchedule:
print(“‘Tue’ exists in examSchedule and the value is: “, examSchedule[‘Tue’])
else:
print(“‘Tue’ not exists in the examSchedule”)

print()
# Clear emptys the dictionary
examSchedule.clear()
print(“Dictionary after clear: “, examSchedule)

Output:
Monday: English
Monday: English

Fri : French
Mon : English
Wed : Science
Tue : Maths
Thu : Social

‘Tue’ exists in examSchedule and the value is: Maths

‘Tue’ is popped
‘Tue’ not exists in the examSchedule

Dictionary after clear: {}

Functions in Python: Example1

Program:
def add(a, b):
return a + b

x=10
y=20
print (“Sum of”, x, “and”, y, “is:”, add(x, y))

# Using function as Param
def callAdd(addFunc, x, y):
return addFunc(x,y)

s = callAdd(add, 20, 30)
print (“Sum of 20 and 30 is:”, s)

Output:
Sum of 10 and 20 is: 30
Sum of 20 and 30 is: 50

Function as Param in Python: Example2

Program:
# return Junior or Senior based on the experience only two conditions
def empType(experience):
if (experience < 8):
return ‘Junior’
else:
return ‘Senior’

# return Junior or Senior or Executive based on the experience three conditions
def empType1(experience):
if (experience < 8):
return ‘Junior’
elif (experience < 15):
return ‘Senior’
else:
return ‘Executive’

#Using function as parameter for another function
# Bonus based on the emp type
def empBonus(empTypeFunc, exp):
eType = empTypeFunc(exp)
if (eType == ‘Junior’):
return 20
elif (eType == ‘Senior’) :
return 10
else:
return 5

#Calling empType, will treat 16 years as Senior and hence Bonus as 10
print (“Case1, Bonus for 16 years of Emp: “, empBonus(empType, 16))
#Calling empType, will treat 16 years as Executive and hence Bonus as 5
print (“Case2, Bonus for 16 years of Emp: “, empBonus(empType1, 16))

Output:
Case1, Bonus for 16 years of Emp: 10
Case2, Bonus for 16 years of Emp: 5

Numpy and Pandas Library in Python

Numpy means Numerical Python. This library consists of multi-dimensional array objects and collections of routines to handle them.This is specifically useful for developing algorithms. It is also widely used in the areas of shape manipultation and linear algebra.

Pandas library provides tools for data structures and data analysis. This library widely used in the field of data science and mahine learning.

Program1: One dimensional and two dimensional data using Numpy
import numpy as np

marks = np.array([80, 90, 95, 75])
sub = np.array([‘English’, ‘Maths’, ‘Science’, ‘French’])
sub_and_marks = np.array([sub, marks])

print(“Marks array:”, marks)
print(“Subjects array:”,sub)
print(“Subjects and Marks:”,sub_and_marks)

Output:
Marks array: [80 90 95 75]
Subjects array: [‘English’ ‘Maths’ ‘Science’ ‘French’]
Subjects and Marks: [[‘English’ ‘Maths’ ‘Science’ ‘French’]
[’80’ ’90’ ’95’ ’75’]]