Python Important Questions with Answers
Ch. Vijayananda Ratnam
1 a) Describe the features of Python.
Python’s Features Include:
 Easy-to-Learn: Python has few keywords, simple structure, and a clearly defined
syntax. This allows the student to pick up the language quickly.
 Easy-to-read: Python code is more clearly defined and visible to eyes.
 Easy-to-maintain: Python’s source code is fairly easy-to-maintain.
 A broad standard library: Python’s bulk of the library is very portable and
cross-platform compatible on UNIX, and Windows.
 Interactive Mode: Python has support for an interactive mode which allows
interactive testing and debugging of code.
 Portable: Python can run on a wide variety of hardware platforms and has the
same interface on all platforms.
 Extendable: You can add low-level modules to the Python interpreter. These
modules enable programmers to add to or customize their tools to be more
efficient.
 Databases: Python provides interfaces to all major commercial databases.
 GUI Programming: Python supports GUI applications that can be created and
ported to many system calls, libraries, and windows system, such as windows
MFC, Macintosh, and the X Window system of UNIX.
 Scalable: Python provides a better structure and support for large programs
than shell scripting.
 Dynamically Typed: We need to specify the data type of variable while creation.
Python can understand the data type of variable after storing the value. It is
called dynamically typed.
1 b) What is IDLE? Describe in detail about the functioning of IDLE?
Python - IDLE
IDLE (Integrated Development and Learning Environment) is an integrated
development environment (IDE) for Python. The Python installer for Windows contains
the IDLE module by default.
IDLE can be used to execute a single statement just like Python Shell and also to create,
modify, and execute Python scripts. IDLE provides a fully-featured text editor to create
Python script that includes features like syntax highlighting, autocompletion, and smart
indent. It also has a debugger with stepping and breakpoints features.
To start an IDLE interactive shell, search for the IDLE icon in the start menu and double
click on it.
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Python Important Questions with Answers
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Fig. Python IDLE
This will open IDLE, where you can write and execute the Python scripts, as shown
below.
Fig. Python IDLE
You can execute Python statements same as in Python Shell as shown below.
Fig. Python IDLE
To execute a Python script, create a new file by selecting File -> New File from the menu.
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Python Important Questions with Answers
Ch. Vijayananda Ratnam
Enter multiple statements and save the file with extension ‘.py’ using File -> Save. For
example, save the following code as hello.py.
Fig. Python Script in IDLE
Now, press F5 to run the script in the editor window. The IDLE shell will show the
output.
Fig. Python Script Execution Result in IDLE
Thus, it is easy to write, test and run Python scripts in IDLE.
2 a) Who uses python today? What are Python’s technical strengths?
Apart from individual users,
 Google makes extensive use of Python in its web search system, and employs
Python’s creator Guido van Rossum.
 The YouTube video sharing service is largely written in Python.
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Python Important Questions with Answers
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Ch. Vijayananda Ratnam
Disney uses Python in many of their creative processes.
Mozilla uses Python to explore their extensive code base and releases tons of
open source packages built in python.
Drop box file hosting service is implemented using Python, Guido van Rossum
now working here.
The popular Bit Torrent peer-to-peer file sharing system is a Python program.
Intel, Cisco, Hewlett-Packard, Seagate, Qualcomm, and IBM use Python for
hardware testing.
JPMorgan Chase, UBS, Getco, and Citadel apply Python for financial market
forecasting.
NASAuses Python for scientific programming tasks.
iRobot uses Python to develop commercial robotic vacuum cleaners.
The NSA uses Python for cryptography and intelligence analysis.
Instagram’s backend is completely written in Python.
Pinterest and Quora use Python for their backend systems.
Python’s Technical Strengths:
1. It is Object-Oriented and Functional
2. It is Free
3. It is Portable
4. It is Powerful
5. It is Mixable
6. It is Relatively Easy to Use
7. It is Relatively Easy to Learn
2 b) What are different applications of Python? Give examples
We can build following type of applications using python.
1.
2.
3.
4.
5.
6.
7.
Web / Internet applications.
Desktop / Stand-alone applications.
Scientific application.
Systems Programming.
Educational Applications.
Business Applications.
Database Applications
And More: Gaming, Images, Data Mining, Robots, Excel...
Python is commonly applied in more domains than can be covered here. For example,
you’ll find tools that allow you to use Python to do:
 Game programming and multimedia with pygame, cgkit, pyglet, PySoy, Panda3D,
and others
 Serial port communication on Windows, Linux, and more with the PySerial extension
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Python Important Questions with Answers
Ch. Vijayananda Ratnam
 Image processing with PIL and its newer Pillow fork, PyOpenGL, Blender, Maya,
and more
 Robot control programming with the PyRo toolkit
 Natural language analysis with the NLTK package
 Instrumentation on the Raspberry Pi and Arduino boards
 Mobile computing with ports of Python to the Google Android and Apple iOS
platforms
 Excel spreadsheet function and macro programming with the PyXLL or DataNitro add-ins
 Media file content and metadata tag processing with PyMedia, ID3, PIL/Pillow,
and more
 Artificial intelligence with the PyBrain neural net library and the Milk machine
learning toolkit
 Expert system programming with PyCLIPS, Pyke, Pyrolog, and pyDatalog
 Network monitoring with zenoss, written in and customized with Python
 Python-scripted design and modeling with PythonCAD, PythonOCC, FreeCAD,
and others
 Document processing and generation with ReportLab, Sphinx, Cheetah, PyPDF,
and so on
 Data visualization with Mayavi, matplotlib, VTK, VPython, and more
 XML parsing with the xml library package, the xmlrpclib module, and third-party
extensions
 JSON and CSV file processing with the json and csv modules
3 a) List and explain few most commonly used built-in types in python.
There are different types of data types in Python. Some built-in Python data types are:
1. Numeric types: int, float, complex
2. Text type: str
3. Boolean type:bool
4. Sequence types:list, tuple, range
5. Mapping type: dict
6. Set types: set, frozenset
1. Numeric Types
Python supports three different numerical types −
 int − They are often called just integers or ints, are positive or negative whole
numbers with no decimal point.
 float − Also called floats, they represent real numbers and are written with a
decimal point dividing the integer and fractional parts. Floats may also be in
scientific notation, with E or e indicating the power of 10 (2.5e2 = 2.5 x 102 =
250).
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Python Important Questions with Answers
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
complex − These are of the form “a + bJ”, where a and b are floats and J (or j)
represents the square root of -1 (which is an imaginary number). The real part of
the number is a, and the imaginary part is b.
Examples:
2. Text Sequence Types – String
In Python, str represents string datatype.A String is a sequence of characters that are
enclosed with in single or double quotes. If the strings are spanned over multiple lines,
then they can be denoted by the use of triple """ or '''quotes.
We will now see an example of creating single-line and multi-line strings –
The triple double or single quotes are useful to embed a string insideanother string.
str="""This is unit covers 'Core Python' concepts"""
3. bool Datatype
The bool datatype represents Boolean values i.e. True and False. A blank string like '
'isalso represented as False. Conditions will be evaluated internally either True and
False.
Examples:
>>> 10>5
#True
>>>10<5
#False
Python internally represents Boolean True as 1 and Boolean False as 0. So, they are
treated as numbers. The following statements will prove that Boolean valuesas
numbers:
>>>True + True
#displays 2 because True is 1 and False is 0
>>>True - False
#displays 1
>>>True + 12
#displays 13
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Python Important Questions with Answers
>>>True - 10
>>> 10 – False
Ch. Vijayananda Ratnam
#display -9
#displays 10
4. Sequence Types
A sequence represents a group of elements or items. There are three types of sequences
inPython.
1. list
2. tuple
3. range
list Datatype
Lists in Python are similar to arrays in C. A list represents group of elements. A list
canstore different types of elements. Lists can grow dynamically at runtime.Lists are
mutable (i.e.: modifiable).
Lists are represented using square brackets [ ] and the elements are separatedby
commas.
Syntax
list_name = [item1,item2,…,itemN]
Example
lst = [] #empty list
lst =[1,1.34,"Vijay",2+3j,-45]
#list with different types of elements
tuple Datatype
A tuple is similar to list. A tuple contains a group of elements which can be of
differenttypes. The elements in the tuple are separated by commas and enclosed in
parenthesis(). Tuples are immutable (i.e: not modifiable) that means a tuple can be
treated as aread-only list.
Syntax
tuple_name = (item1,item2,item3,…,itemN)
Example:
tpl = (10,12.5,-30, "Vijay",2+3j)
range Datatype
The range data type generates a sequence of numbers. The numbers in the range are not
modifiable. Generally, range is used for repeating a for loop for a specific number
oftimes.
Syntax
range(begin, end, step)
It generates a range of numbers from begin to end-1 with a difference of step.
Example:
 range(5) ─ generates range of integers from 0 to 4.
 range(10,16) ─generates range of integers from 10 to 15.
 range(10,20,2) ─ generates range of integers from 10 to 19 with a difference of 2.
5. Mappings/Dictionaries
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Python Important Questions with Answers
Ch. Vijayananda Ratnam
A map represents a group of elements in the form of key-value pairs so that when the
key is given, we can retrieve the value associated with it. The ‘dict’ data type is example
for a map.
The dict represents a dictionary that contains pair of elements such that the first
element represents the key and the next element becomes its value. The key and its
value should be separated by colon (:) and every pair should be separated by comma. All
the elements should be enclosed inside curly brackets {}.
Example
d = {501:"Vijay",502:"Anand",503:"Chaitanya",504:"Raju",505:"Krishna"}
Here, d is name of the dictionary, 501 is the key and its associated value is "Vijay" and
same is for the remaining elements.
We can create an empty dictionary as: d = {}
6. Sets
 A Set is an unordered collection of elements.
 The order of elements is not maintained in the sets.
 Set elements are unique that means duplicate elements are not allowed.
 There are two subtypes in sets:
o set datatype
o frozenset datatype
set Datatype
a set can be defined with curly braces {} and the elements are separated by commas.Sets
are mutable. Sets are unordered so we cannot retrieve the elements using indexingor
slicing.
Syntax
set_name = {item1,item2,…,itemN}
Example:
>>> s = set({10,40,20,30,10,40,20,50})
>>> print(s)
{50, 20, 40, 10, 30}
When you observe the above example,
 The set ‘s’ not maintaining the order
 The duplicate elements were removed
It is also possible to convert a list into set by using set() function.
>>> l = [10, 20, 10, 20, 30, 40, 50]
>>> print(l)
[10, 20, 10, 20, 30, 40, 50]
>>> s = set(l)
>>> print(s)
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Python Important Questions with Answers
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{40, 10, 50, 20, 30}
In the above example, list 'l' is converted into set 's' by using set() function.
frozenset Datatype
A fozenset is same as set datatype except that a frozenset is immutable. We can create
a frozenset by passing a set to frozenset() function.
Example
s={50,60,70,80,90}
print(s)
#{70,80,50,90,60}
fs=frozenset(s)
print(fs)
# frozenset({80, 50, 70, 90, 60})
Determining the Datatype of a Variable
type() function is used to know the datatype of a variable or object.
Syntax:
type(var_name/object)
Example:
>>> a = 10
>>> type(a)
<class 'int'>
3 b) Explain various formatted I/O functionsin python with example.
To handle I/O, Python provides two types of functions. They are:
1. print function
2. input function
print() statement:
It is used to display output or results on screen, this function can be used in different
formats. When the print() function is called, it will throw the cursor to the next line. It
means that a blank line will be displayed.
print(string) statement:
When a string is passed to the print() function, the string is displayed as it is.
Example:
>>> print('Core Python')
Core Python
We can use escape sequence characters inside the print() function like \n, \t, etc.
Example:
Example:
print('Core\nPython')
print('Core\tPython')
Core
Core Python
Python
We can use repetition operator (*) to repeat the strings in the output as:
Example:
>>>print('Hi'*3)
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Python Important Questions with Answers
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HiHiHi
We use ‘+’as string concatenation operator means joins one string at the end of another
string without giving any space between them
Example:
print('City='+'Amaravathi')
City=Amaravathi
We also use comma (,) as string combining operator but it adds one white space
between them.
Example:
print('City=','Amaravathi')
City=Amaravathi
print(variable_list, sep='separator_char', end='ending_char')
print() function also display the values of multiple variables by separating them with a
separator and ending with a ending character. The list of variables must be separated by
comma.
Example:
>>>a,b=5,6
>>>print(a,b) # by default two values are separated by single space.
56
>>>print(a,b,sep='-') #display two values separated by dash(-)
5-6
>>>print(a,b,sep='-',end='@') #print two values separated by '-' and ends with '@'
5-6@
print('string', variable_list)
This is the most common form of print() function is to use strings along with variables
inside a print() function
Example:
a=5
print(a,' is an odd number')
5 is an odd number
print(formatted string)
The special operator % (percent) used to display the output as we like. It joins the string
with a variable or value in the following format.
Syntax:
print('formatted string' %(variable_list))
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Python Important Questions with Answers
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In the formatted string, we use different format specifiers to represent different types of
values such as numbers, strings etc.
Examples:
Format specifier
Statement
Output
%i or %d
print(Int: %i % 4)
Int:4
print('Int zero padded: %03d' % 4)
Intzero padded: 004
print('Int space padded: %3d' % 4)
Int space padded: 4
%f
print('Float: %f' % 2.4)
Float: 2.400000
print('Float: %.2f' % 2.456)
Float: 2.46
%e or %E
print('Float in Sci.form: %e' %2.4)
Float
in
sci.form:
2.400000e+00
print('Float in Sci.form: %.2E' %2.4)
Float in sci.form: 2.40E+00
%x or %X
print('Hexa decimal: %x' % 255)
Hexa decimal: ff
print('Hexa decimal: %X' % 255)
Hexa
decimal:
FF
(capitalized)
%o
print('Octal: %o' % 8)
Octal: 10
%s
print('String: %s' % 'Python')
String: Python
print('Left padded str:(%10s)' % Left padded str:( Python)
'Python')
print('Right padded str:(%-10s)' % Right padded str:(Python )
'Python')
print('Truncated str: %.3s' % 'Python')
Truncated str: Pyt
print('List as str: %s' % [1,2,3])
List as str: [1, 2, 3]
print('Dictvalue as str: %(age)s' % Dictvalue as str: 20
{'age':20})
%c
print('Char: %c' % 65)
Char: A
2. input function
To accept input from keyboard, Python provides the input() function. This function
takes a value from the keyboard and returns it as string.
Syntax:
var=input()
For better understanding of what to enter, user can write a message inside the input()
function as:
var = input(message)
Example:
>>>name = input('Enter your name:')
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Python Important Questions with Answers
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Vijayanand
>>>print('Your name is ', name)
Your name is Vijayanand
Accepting multiple inputs
To accept more than one input in the same line, we use the for loop along with the
input() function in the following format:
var_list = [i for i in input().split()]
Example: To accept two strings at a time:
>>> str1, str2 = [i for i in input('Enter two strings: ').split()]
Enter two strings: Python Java
>>> print(f"String1: {str1}\nString2: {str2}")
String1: Python
String2: Java
Method -2: This method reads multiple values and stores it in a list. Here datatype is
required type of data.
list_var=list(map(datatype, input().split()))
Example
4 a) Explain arithmetic and membership operators in detail.
Arithmetic Operators
 These are used to perform mathematical operations.
 Most of them are binary operators since they operate on two operands at a time
except unary minus and plus.
 They can be applied to any integers, floating-point numbers and complex types.
 Python supports 7 arithmetic operators. They are +, -, *, **,//,/, %.
Let us take a=13 and b=4 and see the effect of various arithmetic operators. The
following table lists the arithmetic operators:
Operator Meaning
Example Result
+
Addition - (Adds two values)
a+b
17
Subtraction – (Subtract one value from another)
a-b
9
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Python Important Questions with Answers
*
/
//
**
%
Ch. Vijayananda Ratnam
Multiplication – (Multiply a times b)
Floating point division (a by b) Integer division (a by b)
Exponentiation (a to the power of b)
Modulo division (returns remainder )
a*b
a/b
a//b
a**b
52
3.25
3
28561
Example - 1: Python program that illustrates the arithmetic operators (arith.py)
a,b=[int(i) for i in input('Enter a ,b values:').split()]
print('Sum is :',a+b)
print('Subtraction is :',a-b)
print('Multiplication is :',a*b)
print('FP Division is :',a/b)
print('Integer Division is :',a//b)
print('The Modulo Division is :',a%b)
print('Exponentiation is :',a**b)
Output
Enter a ,b values:10 3
Sum is : 13
Subtraction is : 7
Multiplication is : 30
FP Division is : 3.3333333333333335
Integer Division is : 3
The Modulo Division is : 1
Exponentiation is : 1000
Membership Operators
The membership operators in Python are used to test whether a value is found within a
sequence. There are two membership operators in Python:
1. in
2. not in
The in operator
This operator returns True if an element found in the sequence otherwise returns False.
Example
>>>s = ['a', 'b', 'c', 'd']
>>> 'a' in s
True
>>> 'z' in s
False
The not in operator
This works in reverse manner for in operator. It returns True if an element is not found
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Python Important Questions with Answers
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in the sequence, otherwise returns True.
Example
>>>s = ['a', 'b', 'c', 'd']
>>> 'z' not in s
True
>>> 'a' not in s
False
4 b) Discuss about logical and bitwise operators in detail?
Logical operators
Operators which are used to combine two or more relational expressions are known as
logical operators. Python supports three logical operators – logical AND (and), logical
OR (or), logical NOT (not). All of these operators when applied to expressions yield
either True or False.
In the case of logical operators, False indicates 0 and True indicates any Non-zero value.
Let us take x=1 and y=2 and see the effect of various logical operators. The
table lists the logical operators:
Operator Meaning
Example
and
If x if False, it returns x, otherwise returns y
x and y
or
If x if False, it returns y, otherwise returns x
x or y
not
If x if False, it returns True, otherwise False
not x
following
Result
2
1
False
These are also known as short-circuit logical operators.
 When we use 'or' operator if left hand side expression is True, then the result
will be True, no matter what is the result of right hand side expression.
 In the case of 'and' if the left hand side expression results False, then the result
will be False, no matter what is the result of right hand side expression.
Example - 3: Python program that illustrates the Boolean operators (logic_op.py)
x=10
y=20
print('x and y = %s' %(x and y))
print('x or y = %s' %(x or y))
print('not x = %s' %(not x))
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Python Important Questions with Answers
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Output
x and y = 20
x or y = 10
not x = False
5 a) Discuss about relational andidentity operators in detail?
Relational operators
A relational operator, also known as a comparison operator, is an operator that
compares two operands. The operands can be variables, constants or expressions.
Relational operators always return either True or False depending on whether the
conditional relationship between the two operands holds or not.
Python has six relational operators. The following
with their meanings
Operator
Meaning
<
Less than
>
Greater than
<=
Less than or equal to
>=
Greater than or equal to
==
Equal to
!=
Not equal to
table shows these operators along
Example
4<5 returns True
4>5 returns False
100<=100 returns True
50>=100 return False
4==5 return False
4!=5 return True
Example - 2: Python program that illustrates the relational operators (rel_op.py)
a,b=[int(i) for i in input('Enter a,b
values:').split()]
print('%d > %d = %s' %(a,b,a>b))
print('%d < %d = %s' %(a,b,a<b))
print('%d >= %d = %s' %(a,b,a>=b))
print('%d <= %d = %s' %(a,b,a<=b))
print('%d == %d = %s' %(a,b,a==b))
print('%d != %d = %s' %(a,b,a!=b))
Output
Enter a,b values:4 5
4 > 5 = False
4 < 5 = True
4 >= 5 = False
4 <= 5 = True
4 == 5 = False
4 != 5 = True
5 b) Explain in detail about Python type conversion and type casting?
Type conversion is a process of converting one data type to another data type. It is also
called as Type casting. It can be of two types: They are
1. Implicit Conversion
2. Explicit Conversion.
Implicit Conversion
When the type conversion is performed automatically by the compiler
withoutprogrammer’s intervention, such type of conversion is known as Implicit type
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conversion or automatic type promotion. In this, all the lower data types are
converted to its next higher data type.
Example: Program that illustrates implicit type conversion (implicit.py)
c=True
n=10
f =12.0
s=n+f+c
print("Sum = ",s)
Output:
Sum=21.0
Here Boolean and Integer type are automatically converted in to Floating point values.
Explicit Conversion
It is intentionally performed by the programmer as per his requirement in a Python
program. The explicit type conversion is also known as type casting. This kind of
conversion is sometimes called a narrowing conversion, since you are explicitly making
the value narrower so that it will fit into the target type.
To create a conversion between two incompatible types, you must use a cast. A cast is
simply an explicit type conversion. It has this general form:
target_type(variable / value )
Here the target type specifies the destination type to which the value has to be
converted.
When a floating-point value is assigned to an integer type, the fractional component is
lost. For example, if the value 12.34 is assigned to an integer, the resulting value will
simply be 12.The 0.34 will have been truncated.
>>>a=12.34
>>>int(a)
12
#converts float to int and returns 12.
Example: Program that illustrates explicit type conversion (Explicit.py)
n=15
print('Binary equivalent of %d is %s' %(n,bin(n)))
print('Octal equivalent of %d is %s' %(n,oct(n)))
print('Hex equivalent of %d is %s' %(n,hex(n)))
print('Binary equivalent of %d is %s' %(n,float(n)))
Output
Binary equivalent of 15 is 0b1111
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Octal equivalent of 15 is 0o17
Hex equivalent of 15 is 0xf
Binary equivalent of 15 is 15.0
UNIT-II
1 a) What are the different conditional statements available in Python? Explain
with suitable examples.
They allow your program to choose different paths of execution based upon the
outcome of an expression or the state of a variable. They are also called as Conditional
or Decision Making Statements.
1. The if statement
The if statement is used to execute one or more statements depending on whether a
condition is True or not. The syntax of if statement is:
if condition:
statements
First, condition is tested, if the condition is True, then statements given after colon (:)
are executed. Otherwise, statements will not be executed.
Example: A Python program that illustrates if statement (test.py)
a=2
if a>0:
print(a,' is positive')
Output
2 is positive
2. The if..else statement
This is an extension to simple if. This is used to route the execution through two
different paths. The general form of if..else statement will be as follow:
if condition:
statements
else:
statements
If condition is True, it executes if part statements otherwise, it executes else part
statements.
Example: A Python program to test whether a given number is even or odd (even.py).
n = int(input('Enter number to check:'))
if n%2==0:
print(n, 'is even')
else:
print(n, 'is odd')
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Output
Enter number to check:4
4 is even
Enter number to check:67
67 is odd
3. The if..elif..else statement (chained conditionals)
Sometimes we need to test more than one condition. One way to express such a
computation like that is a chained conditional. It used to test a sequence of conditions.
It looks like this:
if condition1:
statement_1
elif condition2:
statement_2
elif condition3:
statement_3
..
.
elif condition_N:
statement_N
else:
statement
The if statements are executed in a sequential manner. As soon as one of the conditions is
True, the statement associated with that is executed, and the rest of the ladder is
bypassed. If none of the conditions is True, then the final else statement will be executed.
Example: A Python Program to check whether a given number is positive or negative
(Type.py).
Output:
n = int(input('Enter number to check: '))
Enter number to check: 4
if n>0:
4 is positive.
print(n,'is positive.')
elif n<0:
Enter number to check: -3
print(n, 'is negative.')
-3 is negative.
else:
print('It is zero.')
Enter number to check: 0
It is zero.
1b) Write a Python program that interchanges the first and last characters of a
given string.
str = input("Enter a string : ")
swap_str = str[-1:] + str[1:-1] + str[:1]
print(swap_str)
Output:
Enter a string : python
nythop
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2 a) Explain about iteration statements with examples.
Python offers two kinds of loops, the for loop and the while loop. These statements
create what we commonly called loops. A loop repeatedly executes the same set of
instructions until a termination condition is met.
Advantages
 Reduce length of Code
 Take less memory space.
 Burden on the developer is reducing.
 Time consuming process to execute the program is reduced.
1. while loop
The while loop is a pre-test or entry-controlled loop. It uses conditional expression to
control the loop. The while loop evaluates (checking) the condition before every
iteration of the loop, so it can execute zero times if the condition is initially false. The
initialization of a loop control variable is generally done before the loop separately.
while condition:
statements
inc/dec loop_control variable
How while loop works?
 Initially the while loop evaluates (checking) the condition.
 If the condition is True, statements inside the body of while loop is evaluated.
Then, again the condition is evaluated. The process goes on until the condition is
False.
 When the condition is False, the while loop is terminated.
Example: Python program to print 1 to 10 numbers using while loop (numbers.py).
i=1
while i<=10:
print(i,end=' ')
i+=1
Output
1 2 3 4 5 6 7 8 9 10
2. for loop
It is the most general looping construct in Python. The for loop is useful to iterate over
the elements of the sequence. The for loop can be work with sequence like string,
list,tuple, range etc. The for loop is commonly used when the number of iterations
areexactly known. The syntax of a for loop is:
for var in sequence:
statements
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How for loop works?
 Initially, first element of the sequence is assigned to the variable var then the
statements are executed.
 Next, second element of the sequence is assigned to the variable var then the
statements are executed second time.
 This process will be continued as many times as there are number of elements in
the sequence.
Example: Python program to print individual characters of a string (for.py).
str='Python'
for char in str:
print(char)
Output
P
y
t
h
o
n
2 b) Implement a python program to check whether the given number is prime or
not
n = int(input("Enter a number : "))
f=0
for i in range(2,n//2+1):
if n%i==0:
f+=1
if f==0:
print(n,'is prime')
else:
print(n,'is not a prime')
Output:
Enter a number : 17
17 is prime
3a) Describe Python jump/loop control statements with examples.
Python supports three jump statements: break, continue, and return. These statements
transfer control from one location to another with in a program.
1. break statement
The break statement can be used inside a for loop or while loop to come out of the loop.
when break statement is encountered inside a loop, the loop is immediately terminated,
and program control is transferred to next statement following the loop.
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Its syntax is quite simple, just type keyword break.
break
Example: Python program that illustrates the use of break statement (break.py)
x=1
while x<=5:
if x==3:
#if x is 3 then come out from loop.
break
print('x=',x)
x+=1
print('Outside the Loop')
Output
x=1
x=2
Outside the Loop
2. continue statement
The continue statement can be used in a loop to go back to the beginning of the
loop that means when continue statement is encountered inside a loop, it stops the
current iteration and places the loop in next iteration.
continue
When continue is executed, the subsequent statements in the loop are not executed.
Example: Python program that illustrates the use of continue statement (continue.py)
x=0
while x<5:
x+=1
if x==3:
#if x is 3 then continue to next iteration.
continue
print('x =',x)
Output
x=1
x=2
x=4
x=5
3. return statement
The return statement is used to explicitly return a value from method. That is, it causes
program control to transfer back to the caller of the method. As such, it is categorized as
a jump statement.
return (expression/value)
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Example: Python function that returns the sum of two numbers (return.py)
def add(x,y):
return x+y
# result is returned from here
a = int(input('Enter a value:'))
b = int(input('Enter b value:'))
print('Sum =',add(a,b))
Output
Enter a value: 3
Enter b value: 4
Sum = 7
3 b) Write a python program to find no of digits in a given number
n = int(input("Enter a number : "))
digits=0
while n!=0:
digits+=1
n = n//10
Output:
Enter a number : 1234
Total digits: 4
print('Total digits:',digits)
4 a) Differentiate elif v/s nested if else in python.
elif statement
Sometimes we need to test more than one condition. One way to express such a
computation like that is a chained conditional. It used to test a sequence of conditions.
It looks like this:
if condition1:
statement_1
elif condition2:
statement_2
elif condition3:
statement_3
..
.
elif condition_N:
statement_N
else:
statement
The if statements are executed in a sequential manner. As soon as one of the conditions is
True, the statement associated with that is executed, and the rest of the ladder is
bypassed. If none of the conditions is True, then the final else statement will be executed.
Example: A Python Program to check whether a given number is positive or negative
(Type.py).
n = int(input('Enter number to check: '))
if n>0:
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print(n,'is positive.')
elif n<0:
print(n, 'is negative.')
else:
print('It is zero.')
Output:
Enter number to check: 4
4 is positive.
Nested if-else statements
Nested “if-else” statements mean that an “if” statement is present inside another if
block. Python provides this feature as well, this in turn will help us to check multiple
conditions in a given program.
Syntax:
if(condition):
#outer if
statements
if(condition):
#inner if
statements
else:
statements
else:
statements
The above syntax clearly says that the if block will contain another if block in it and so
on. If block can contain ‘n’ number of if block inside it.
Example: Python program to check grater among three numbers(greater.py).
a,b,c =list(map(int,input('Enter three integers:').split()))
if a>b:
if a>c:
print(a,'is big')
else:
print(c,'is big')
else:
if b>c:
print(b,'is big')
else:
print(c,'is big')
Output:
Enter three integers:2 1 3
3 is big
4 b) Write a Python program to find the given year is leap year or not.
Year = int(input("Enter the number: "))
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if((Year % 400 == 0) or (Year % 100 != 0) and (Year % 4 == 0)):
print(Year, "is a Leap Year");
else:
print (Year, "is not a Leap Year")
Output:
Enter the number: 2000
2000 is a Leap Year
5 a) Discuss various Python Built-in functions for manipulating Strings.
Built-in String methods for Strings:
1. capitalize ():Returns a proper case string i.e., with its first character capitalized and
the rest of the letters are in lowercased.
Example:
>>> str = 'duCKdUcK Go'
>>>str.capitalize()
'Duck duck go'
2. upper():Returns a string in the upper case. Symbols and numbers remain unaffected.
Example:
>>> str = 'duCKdUcK Go'
>>>str.upper()
'DUCK DUCK GO'
3. lower():Returns a string in the lower case. Symbols and numbers remain unaffected.
Example:
>>> str = 'duCK dUcK Go'
>>>str.lower()
'duck duck go'
4. title():Returns a string where each word starts with an uppercase character, and the
remaining characters are lowercase.
Example:
>>> str = 'duCKdUcK Go'
>>>str.title()
'Duck Duck Go'
5. swapcase():Returns a copy of the string with uppercase characters converted to
lowercase and vice versa. Symbols and letters are ignored.
Example:
>>> str = 'duCK dUcK Go'
>>>str.swapcase()
'Duck DuCk gO'
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6. ljust(): Returns the left justified string with the specified width. If the specified width
is more than the string length, then the string's remaining part is filled with the
specified fill_char.
Example:
>>> str='python'
>>>str.ljust(10,'*')
'python****'
7. rjust(): Returns the right justified string with the specified width. If the specified
width is more than the string length, then the string's remaining part is filled with the
specified fill_char.
Example:
>>> str='python'
>>>str.rjust(10,'*')
'****python'
8. center(): Returns a new centered string of the specified length, which is padded with
the specified character. The default character is space.
Example:
>>> str='python'
>>>str.rjust(10,'*')
'**python**'
9. split():method breaks the string into a list of smaller sub-strings based on some
separator. The default separator is white space.
Syntax
string.split(separator)
Example:
>>>s= 'www.google.com')
>>>s.split('.')
['www', 'google','com']
s='I am the student VVIT'
>>>s.split()
['I', 'am', 'the', 'student', 'VVIT']
10. join():method combines the list of strings into a single string.
Syntax:
separator.join(sequence)
Example:
>>>lst=['+91','987','654','3210']
>>> s='-'.join(lst)
>>> print(s)
+91-987-654-3210
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11. find() - Returns the index of the first occurrence of a substring in the given string
(case-sensitive). If the substring is not found it returns -1.
Syntax:
string.find(substring, begin, end)
Example:
>>> str='Python Programming'
>>>str.find('o')
4
>>>str.find('o',6,10)
9
>>>str.find('z')
-1
12. index():Returns the index of the first occurrence of a substring in the given string.It
willreturn ValueError Exception if the substring not found
Syntax:
string.index(substring,begin,end)
Example:
>>> str='Python Programming'
>>>str.index('m')
13
>>>str.index('m',0,4)
Traceback (most recent call last):
File "<pyshell>", line 1, in <module>
ValueError: substring not found
13. count():method returns the number of occurrences of a sub-string in the given
string.
Syntax:
string.count(substring, begin, end)
Example:
>>> s='Core Python'
>>>s.count('o')
2
>>>s.count('o',5,11)
1
>>>s.count('p')
0
14. replace(): method replace a sub-string in a given string with another sub-string.
Syntax:
string.replace(old, new [, n])
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This will replace n number of occurrences of old substring with new substring in the
given string from beginning to ending. If n is omitted, all occurrences are replaced
Example
>>> s='There is a beautiful girl'
>>>s.replace('girl','flower')
'There is a beautiful flower'
>>> s='Core Python'
>>>s.replace('o','a',1)
'Care Python'
>>> s = 'Manager'
>>>s.replace('Man','Dam')
'Damager'
15. startswith(): method returns True if the String starts with a specific substring,
otherwise returns False.
Example
str='Core Python'
>>>str.startswith('Core')
True
>>>str.startswith('ore')
False
16. endswith(): method returns True if the String ends with a specific substring,
otherwise returns False.
Example
str='Core Python'
>>>str.endswith('on')
True
>>>str.endswith('one')
False
5 b) Write a Python script to check the given string is Palindrome or not?
str = input('Enter a string:')
if str==str[::-1]:
print(f"pallindrome")
else:
print(f"not a pallindrome")
Output:
Enter a string: madam
Palindrome
6 a) Explain with an example, how * and + operators work with strings.
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The * operator
The * is called as string repetition operator that means it creates multiple copies of a
string. For example, str * n repeats the string for n times.
Example
>>>s='Python'
>>>print(s*3)
'PythonPythonPython'
It also possible to repeat the part of string obtained by slicing as:
>>>print(s[0:2]*3)
'PyPyPy'
The + operator
It is called as string concatenation operator since it concatenates the strings. We use '+'
on strings to attach one string at the end of another string.
Example
>>>s1='Core'
>>>s2='Python'
>>>s3=s1+s3
# concatenate s2 at the end of s1 and store it on s3.
>>>print(s3)
'CorePython'
6 b) Write a Python program that counts the number of occurrences of a letter in
aString.
str = input('Enter a string:')
ch = input('Enter character to be found:')
cnt = str.count(ch)
print(f"{ ch } appears {cnt} times")
Output:
Enter a string: kakinada
Enter character to be found:k
k appears 2 times
UNIT-III
1 a) Define list and explain any five list methods in python?
In Python, the list is a mutable sequence type. A list object contains one or more items of
different data types in the square brackets [] separated by a comma. The following
declares the lists variable.
Example:
mylist=[]
print(mylist)
# Empty list
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items=[1, "Jeff", "Computer", 75.50, True]
print(items)
Output:
[]
[1, 'Jeff', 'Computer', 75.5, True]
Methods in Lists:
Method
lst.append(x)
lst.insert(i,x)
lst.remove(x)
lst.pop()
lst.index(x)
lst.count(x)
# List with heterogeneous data
Description
Appends element ‘x’ at the end of the list.
Inserts element ‘x’ to the list in the position specified by i.
Removesanelement‘x’ from the list.
Removes last element from the list.
Returns the first occurrence of element ‘x’ in the list.
Returns number of occurrences of element ‘x’ in the list.
Example:
lst=[10,5]
#List with 2 elements
print('Original List:',lst)
lst.append(17) #Appending 17 at end
print('After adding 17: ',lst)
lst.insert(1,29) #Inserting 29 at index position 1
print('After adding 29: ',lst)
lst.remove(10)
print('After deleting 10: ',lst)
lst.pop()
print('After deleting last element :',lst)
pos = lst.index(5)
print('5 is at position : ',pos)
Output:
Original List: [10, 5]
After adding 17: [10, 5, 17]
After adding 29: [10, 29, 5, 17]
After deleting 10: [29, 5, 17]
After deleting last element: [29, 5]
5 is at position: 1
1 b) Explain about different types of arguments in Python.
There are 4 types of arguments in Python. They are:
1. Positional arguments
2. Default arguments
3. Keyword arguments (Named arguments)
4. Arbitrary arguments (Variable-length arguments *args and **kwargs)
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1. Positional Arguments
Theseare the arguments where values get assigned to the arguments by their
positionwhen the function is called. For example, the 1st positional argument must be
1st when the function is called. The 2nd positional argument needs to be 2nd when the
function is called, etc.
By default, Python functions are called using the positional arguments.
Example: Program to add 2 numbers using positional arguments.
def add(a, b):
#function definition
print(a + b)
add(50, 10)
# Output 60
#function call
In the positional arguments, number and position of arguments must be matched. If we
change the order, then the result may change. Also, if we change the number of
arguments, we will get an error.
2. Default Arguments
In a function, arguments can have default values. We assign default values to the
argument using the ‘=’ (assignment) operator at the time of function definition. You can
define a function with any number of default arguments.
The default value of an argument will be used inside a function if we do not pass a value
to that argument at the time of the function call. Due to this, the default arguments
become optional during the function call.
It overrides the default value if we provide a value to the default arguments during
function calls.
Example:
Let’s define a function simple_interest() with three arguments principle, time and roi
(rate_of_interest). In this function, roi is default argument with default value.
If you call a function without roi, then the default values of roi is used. The principle and
time parameters do not have default values and are required (mandatory) during a
function call.
# function with default argument roi.
def simple_interest(principle, time, roi=8.5):
i = (principle*time*roi)/100
print('Interest amount:', i)
simple_interest(1000,5)
#without passing default argument i.e. roi
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simple_interest(1000,5,12)
Ch. Vijayananda Ratnam
#passing default argument
Output:
Interest amount: 425.0
Interest amount: 600.0
If you pass value of roi argument while calling a function, then those values are used
instead of default values.
3. Keyword Arguments
Keyword arguments are those arguments where values get assigned to the arguments
by their keyword (name) when the function is called. It is preceded by the variable name
and an (=) assignment operator. It is also called asnamed argument.
Example:
# function with 2 keyword arguments
def student(name, age):
print('Student Details:', name, age)
student('Tony', 20)
student(name='John', age=21)
student('Bell', age=19)
# default function call
# both keyword arguments
# 1 positional and 1 keyword
Output:
Student Details: Tony 20
Student Details: John21
Student Details: Bell 19
4. Variable-length arguments
In Python, sometimes, there is a situation where we need to pass multiple arguments to
the function but we don’t know the number of arguments needed for the function in
advance. Such types of arguments are called arbitrary arguments or variable-length
arguments. There are two types of arguments:
1. arbitrary positional arguments (*args)
2. arbitrary keyword arguments (**kwargs)
The *args and **kwargs allow you to pass multiple positional arguments or keyword
arguments to a function.
Arbitrary positional arguments (*args)
We can declare a variable-length argument with the * (asterisk) symbol. Place an
asterisk (*) before a parameter in the function definition to define an arbitrary
positional argument.
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We can pass multiple arguments to the function. Internally all these values are
represented in the form of a tuple. Let’s understand the use of variable-length
arguments with an example.
Example:
def percentage(*args):
# function with variable-length arguments
sum = 0
for i in args:
sum = sum + i
# get total
avg = sum / len(args)
# calculate average
print('Average =', avg)
percentage(56, 61, 73)
Output:
Average = 63.33
Arbitrary keyword arguments (**kwargs)
The **kwargs allow you to pass multiple keyword arguments to a function. Use the
**kwargs if you want to handle named arguments in a function. Keyword arguments
passed to a kwargs are accessed using key-value pair (same as accessing a dictionary in
Python).
Example:
def percentage(**kwargs): # function with variable-length keyword arguments
sum = 0
for k,v in kwargs.items():
sub_name = k
# get argument name
sub_marks = v
# get argument value
print(sub_name, "=", sub_marks)
sum+=v
print ('Percentage=',sum/3)
# pass multiple keyword arguments
percentage(Maths=56, English=61, Science=73)
Output:
Maths = 56
English = 61
Science = 73
Percentage= 63.3
2 a) What are built-in dictionary functions? Explain.
A dictionary represents a group of elements arranged in the form of key-value pairs. The
first element is considered as “key‟ and the immediate next element is taken as its
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“value‟. The key and its value are separated by a colon (:). All the key-value pairs in a
dictionary are inserted in curly braces { }.
d= {"Regd.No": 511, "Name":"Tony", "Branch": "CSE" }
Here, the name of dictionary is “d”. The first element in the dictionary is a string
“Regd.No”. So, this is called “key”. The second element is 556 which is taken as its “value”.
Methods with example:
1. keys():returns a list of all the available keys in the dictionary.
d={'Name':'Harry','Rollno':530,'Dept':'CSE','Percentage':97}
print(dict.keys())
Output:
dict_keys(['Name', 'Rollno', 'Dept', 'Percentage'])
2. values( ):returns list of dictionary's values from the key value pairs.
d={'Name':'Harry','Rollno':530,'Dept':'CSE','Percentage':97}
print(dict.values())
Output
dict_values(['Harry', 530, 'CSE', 97])
3. items():returns a list of dictionary's (key, value) as tuple.
d={'Name':'Harry','Rollno':530,'Dept':'CSE','Percentage':97}
print(dict.items())
Output:
dict_items([('Name', 'Harry'), ('Rollno', 530), ('Dept', 'CSE'), ('Percentage', 97)])
4.pop(key): Removes and returns the value of specified key.
d={'Name':'Harry','Rollno':530,'Dept':'CSE','Percentage':97}
d.pop('Percentage')
print(d)
Output:
{'Name': 'Harry', 'Rollno': 530, 'Dept': 'CSE'}
5. copy():returns a shallow copy of dictionary.
d = {‘Name':'Harry','Rollno':530,'Dept':'CSE','Percentage':97}
new_d=d.copy()
print(new_d)
Output:
{‘Name':'Harry','Rollno':530,'Dept':'CSE','Percentage':97}
6. clear(): Removes all key-value pairs from dictionary ‘d’.
d = {‘Name':'Harry','Rollno':530,'Dept':'CSE','Percentage':97}
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d.clear()
print(d)
Output
{}
7. get(k[,v]):Returns the value associated with key ‘k’. If key is not found, it returns ‘v’.If
key is not found and ‘v’ is not specified , it returns ‘None’.
d = {'Name':'Harry','Rollno':530,'Dept':'CSE','Percentage':97}
print('Name: ', d.get('Name'))
print('Age: ', d.get('Age',21))
print('Age: ', d.get('Age'))
Output:
Name: Harry
Age: 21
Age: None
8. update():inserts new item to the dictionary.
d = {'Name':'Harry','Rollno':530,'Dept':'CSE','Percentage':97}
d.update({'Age':21})
print(d)
Output
{'Name':'Harry','Rollno':530,'Dept':'CSE','Percentage':97, 'Age': 21}
2 b) Describe anonymous functions with examples.
Anonymous (or) Lambda Function
Sometimes we need to declare a function without any name. The nameless property
function is called an anonymous or lambda function.
Lambda functions are single-line functions that can take multiple arguments but have a
single expression and return value.
There are three main components of the lambda function:
1. keyword: lambda
2. arguments before the colon
3. expression/return statements after colon
Syntax:
lambda: argument_list:expression
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When we define a function using the lambda keyword, the code is very concise so that
there is more readability in the code. A lambda function can have any number of
arguments but return only one value after expression evaluation.
Let’s see an example to find sum of three numbers using lambda function
>>>sum = lambda a,b,c:a+b+c
>>>print(sum(1,2,3))
6
We are not required to write explicitly return statements in the lambda function because
the lambda internally returns expression value.
Lambda functions are more useful when we pass a function as an argument to another
function. We can also use the lambda function with built-in functions such as filter, map,
and reduce because this function requires another function as an argument.
3 a) Explain various operations performed on Lists?
In Python, the list is a mutable sequence type. A list object contains one or more items of
different data types in the square brackets [] separated by a comma. The following
declares the lists variable.
Operations on Lists:
1. Creating a List:
Creating a list is as simple as putting different comma-separated values between square
brackets.
student = [511, “Tony”, 84, 96, 84, 75, 84 ]
We can create empty list without any elements by simply writing empty square brackets
as: student=[ ]
2. Accessing Values in list:
To access values in lists, use the square brackets for slicing along with the index or
indices to obtain value available at that index. To view the elements of a list as a whole,
we can simply pass the list name to print function.
Example:
student = [511, “Tony”, 84, 96, 84, 75, 84 ]
print(student)
print(student[0]) # Access 0th element
print(student[0:2]) # Access 0th to 1st elements
print(student[2: ]) # Access 2nd to end of list elements
print(student[ :3]) # Access starting to 2nd elements
print(student[ : ]) # Access starting to ending elements
print(student[-1]) # Access last index value
print(student[-1:-7:-1]) # Access elements in reverse order
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Output:
[556, “Tony”, 84, 96, 84, 75, 84]
Tony
[556, “Tony”]
[84, 96, 84, 75, 84]
[556, “Tony”, 84]
[556, “Tony”, 84, 96, 84, 75, 84]
84
[84, 75, 84, 96, 84, “Tony”]
3. Updating and deleting lists:
Lists are mutable. It means we can modify the contents of a list. We can append, update
or delete the elements of a list depending upon our requirements.
Appending an element means adding an element at the end of the list. To, append a new
element to the list, we should use the append() method.
Example:
lst=[1,2,4,5,8,6]
print(lst)
# [1,2,4,5,8,6]
lst.append(9)
print(lst)
# [1,2,4,5,8,6,9]
Updating an element means changing the value of the element in the list. This can be
done by accessing the specific element using indexing or slicing and assigning a new
value.
Example:
lst=[4,7,6,8,9,3]
print(lst)
# [4,7,6,8,9,3]
lst[2]=5
# Updates 2nd element in the list
print(lst)
# [4,7,5,8,9,3]
lst[2:5]=10,11,12 # Update 2nd element to 4th element in the list
print(lst)
# [4,7,10,11,12,3]
Deleting an element from the list can be done using ‘del’ statement. The del statement
takes the position number of the element to be deleted.
Example:
lst=[5,7,1,8,9,6]
del lst[3]
# Delete 3rd element from the list i.e., 8
print(lst)
# [5,7,1,9,6]
Note:If we want to delete entire list, we can give statement like del lst.
4. Concatenation of Two lists:
We can simply use ‘+’ operator on two lists to join them. For example, ‘x’ and ‘y’ are two
lists. If we write x+y, the list ‘y’ is joined at the end of the list ‘x’.
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Example:
x=[10,20,32,15,16]
y=[45,18,78,14,86]
print(x+y)
# [10,20,32,15,16,45,18,78,14,86]
5. Repetition of Lists:
We can repeat the elements of a list ‘n’ number of times using ‘*’ operator.
Example:
x=[10,54,87]
print(x*2)
# [10,54,87,10,54,87]
6. Membership in Lists:
We can check if an element is a member of a list by using ‘in’ and ‘not in’ operator.
 If the element is a member of the list, then ‘in’ operator returns True otherwise
returns False.
 If the element is not in the list, then “not in” operator returns True otherwise
returns False.
Example:
x=[10,20,30,45,55,65]
a=20
print(a in x)
# True
a=25
print( a in x)
# False
a=45
print( a not in x) # False
a=40
print( a not in x) # True
7. Aliasing and Cloning Lists:
Giving a new name to an existing list is called ‘aliasing’. The new name is called ‘alias
name’. To provide a new name to this list, we can simply use assignment operator (=).
Example:
x = [10, 20, 30, 40, 50, 60]
y=x
# x is aliased as y
print(x)
# [10,20,30,40,50,60]
print(y)
# [10,20,30,40,50,60]
x[1]=90
# modify 1st element in both lists
print(x)
# [10,90,30,40,50,60]
print(y)
# [10,90,30,40,50,60]
Obtaining exact copy of an existing object (or list) is called “cloning‟. To Clone a list, we
can take help of the slicing operation [:].
Example:
x = [10, 20, 30, 40, 50, 60]
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y=x[:]
# x is cloned as y
print(x) # [10,20,30,40,50,60]
print(y) # [10,20,30,40,50,60]
x[1]=90
# modify 1st element in x
print(x) # [10,90,30,40,50,60]
print(y) # [10,20,30,40,50,60]
3 b) Discuss in detail about recursion along with costs and benefits.
Recursion is the process of defining something in terms of itself. A Function that calls
itself again and againis called recursive function.Each recursive function has two parts:
 Base Case
 Recursive Structure
Any recursive function will look like
Base Case: The smallest version of the problem for which we already know the solution
or a terminating condition to stop a recursive function from executing endlessly.
Recursive Structure: Finding the solution to a problem via the solution of its smaller
sub-problems. Here function must call itself to break the current problem down to a
simpler level.
For example, print numbers from N to 1 in decreasing order
def countdown(n):
if n<1:
#Base case
return
print(n)
countdown(n-1) #Recursive Structure
n = int(input('Enter a number:'))
countdown(n)
Costs/Disadvantages
 A recursive program has greater space requirements than an iterative program as
each function call will remain in the stack until the base case is reached.
 It also has greater time requirements because each time the function is called,
the stack grows and the final answer is returned when the stack is popped
completely.
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Benefits/Advantages:
 For a recursive function, you only need to define the base case and recursive
case, so the code is simpler and shorter than an iterative code.
 Some problems are inherently recursive, such as Graph and Tree Traversal.
4 a) What is package in Python? Explain, how can you use package in your
program with an example code?
A python package is a collection of modules.
(Or)
A package is a directory of Python modules that contains an additional __init__.py file,
which distinguishes a package from a directory that is supposed to contain multiple
python scripts.
Advantages:
1. Naming conflicts can be solved easily.
2. We can identify our components uniquely.
3. Improves the Modularity of the application.
4. The readability of the application will be improved.
5. Maintainability of the application will be improved.
For example,
Create and access a user defined package ArithmeticPackage where the package
contains a module named ArithmeticDemo, which in turn contains a methods called
sumtwo() , subtwo(), multwo() and divtwo() which takes two numbers as parameter and
returns the result.
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To create a package in Python, we need to follow these three simple steps:
1. First, we create a directory and give it a package name, preferably related to its
operation.
2. Then we put the classes and the required functions in it.
3. Now we can use the package that is created. To do this make a python file in the
same directory where package is located and add code to it.
4. Now execute the program.
ArithmeticDemo.py Program in ArithmeticPackage Folder
def sumtwo(a,b):
return a+b
def subtwo(a,b):
return a-b
def multwo(a,b):
return a*b
def divtwo(a,b):
return a/b
Usage of Module in Package:
import ArithmeticDemo as ad
print(ad.sumtwo(10,20))
print(ad.subtwo(20,10))
print(ad.multwo(20,10))
print(as.divtwo(20,10))
Output:
30
10
200
2.0
4 b) Differentiate list vs dictionary in terms of indexing
Property
Definition
List
List refers to the collection of
index-value pairs like that
array in C.
Creation
List is initialized with [], and
elements are separated by ','.
Accessing
List values can be accessed
by numeric indices.
40
Dictionary
Dictionary refers to the hashed
structure of various pairs like
key-value pairs.
Dictionary is created by
placingelements in {}, data is
added askey:value pair, and each
pair is separated by ','.
Dictionary items can be accessed
by using key:values. Key
valuescan be of any data type.
Python Important Questions with Answers
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Ordering of
Elements
The order of elements in the
list is always maintained.
Properties
List is ordered, mutable, and
allows duplicate values.
Store the data
Lists are used to store the
data, which should be
ordered and sequential.
We don’t have any guarantee of
maintaining the order of the
available elements.
Dictionary is unordered and
mutable, but the
dictionarydoesn't allow duplicate
values as keys.
It stores large amounts of data for
easy and quick access.
5 a) Explain about built-in functions of tuple.




These are an ordered collection of elements of different data types.
We represent them by writing the elements inside the parenthesis separated by
commas.
Tuples are ordered and immutable.
We access elements by using the index starting from zero.
For example,
>>>t = (22, 45, 23, 78, 6.89)
>>>print(t)
(22, 45, 23, 78, 6.89)
Tuple Functions:
1. len(): returns the number of elements present in a tuple.
For example,
>>>t = (22, 45, 23, 78, 6.89)
>>>len(t)
5
2. count():returnsthetotal number of occurrences of an element in a tuple.
For example,
>>>t = (22, 45, 23, 78, 22, 22, 6.89)
>>>t.count(22)
3
>>>t.count(54)
0
3. index(): returns the position of the first occurrence of an element in a tuple if it found
otherwise returns ValueErrori.e. element not found.
For example,
>>>t = (22, 3, 45, 4, 2.4, 2, 56, 890, 1)
>>> print(tup.index(45))
2
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>>> print(tup.index(33))
ValueError: tuple.index(x): x not in tuple
4. sorted( ): returns sorted list an output. Moreover, it does not make any changes to the
original tuple.
For example,
>>> t = (22, 3, 45, 4, 2.4, 2, 56, 890, 1)
>>> sorted(t)
[1, 2, 2.4, 3, 4, 22, 45, 56, 890]
5. min():returns the smallest element in the tuple.
For example,
>>> t = (22, 3, 45, 4, 2.4, 2, 56, 890, 1)
>>> min(t)
1
6. max():returns largest element in the tuple.
For example,
>>> t = (22, 3, 45, 4, 2.4, 2, 56, 890, 1)
>>> max(t)
890
7. sum():returns sum of all the elements present in the tuple.
For example,
>>> t= (22, 3, 45, 4, 2, 56, 890, 1)
>>> sum(t)
1023
5 b) Write a brief note on PIP. Explain installing packages via PIP.
PIP is the package manager for python. In other words, it is a tool that allows us to
install the python packages and dependencies that aren’t distributed as part of the
Python's Standard Library.
Pip has become the standard package manager for Python.
Installing PIP
Python 2.7.9 and later (python2 series), and Python 3.4 and later (python 3 series)
already comes with pip.
If you are using latest Python version, then pip comes pre-installed with it.You can verify
if pip is available by running the following command in your console:
C:/> pip --version
If you get an output like this 42
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pip 20.2.3 from c:\python39\lib\site-packages\pip (python 3.9)
Installing a Package
If you’re using Windows, you’ll be able to install a Python package by opening the
Windows Command Prompt, and then typing this command:
pip install package_name
For example, to install the Pandas package, type the following command in the
Command Prompt:
pip install pandas
Uninstall a Package
To uninstall a package using PIP, simply type the following command in the Command
Prompt:
pip uninstall package_name
For example, to uninstall the Pandas package, type the following command in the
Command Prompt:
pip uninstall pandas
6 a) Define Module? What are the two ways of importing a module?Explain.
Modules: A module is a file containing Python definitions and statements. The file name
is the module name with the suffix.py appended. Within a module, the module’s name
(as a string) is available as the value of the global variable name.
For instance, create a file called fibo.py in the current directory with the following
contents:
# Fibonacci numbers module
def fib(n):
# write Fibonacci series up to n a, b = 0, 1
while b < n: print b,
a, b = b, a+b
def fib2(n):
# return Fibonacci series up to n result = []
a, b = 0, 1
while b < n:
result.append(b)
a, b = b, a+b
return result
Now enter the Python interpreter and import this module with the following command:
>>>import fibo
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This does not enter the names of the functions defined in fibo directly in the current
symbol table; it only enters the module name fibo there. Using the module name, you
can access the functions:
>>>fibo.fib(10)
112358
>>> fibo.fib2(10)
[1, 1, 2, 3, 5, 8]
>>>fibo.__name__
'fibo'
from statement:
 A module can contain executable statements as well as function definitions.
These statements are intended to initialize the module. They are executed only
the first time the module name is encountered in an import statement. (They are
also run if the file is executed as a script.)
 Each module has its own private symbol table, which is used as the global
symbol table by all functions defined in the module. Thus, the author of a module
can use global variables in the module without worrying about accidental clashes
with a user’s global variables. On the other hand, if you know what you are doing
you can touch a module’s global variables with the same notation used to refer to
its functions, modname.itemname.
 Modules can import other modules. It is customary but not required to place all
import statements at the beginning of a module (or script, for that matter). The
imported module names are placed in the importing module‟s global symbol
table.
 There is a variant of the import statement that imports names from a module
directly into the importing module‟s symbol table. For example:
from .. import statement:
>>> from fibo import fib, fib2
>>>fib(500)
1 1 2 3 5 8 13 21 34 55 89 144 233 377
This does not introduce the module name from which the imports are taken in the local
symbol table (so in the example, fibo is not defined).
There is even a variant to import all names that a module defines:
>>> from fibo import *
>>> fib(500)
1 1 2 3 5 8 13 21 34 55 89 144 233 377
6 b) Explain about higher order functions with examples.
In Python, higher-order functions are functions that can accept other functions as
arguments, return functions as results, or both.
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In Python, functions are considered first-class objects, meaning they can be assigned to
variables, passed as arguments to other functions, and returned as values from
functions.
There are 3 different functions, namely:
1. map()
2. filter()
3. reduce().
1. map() function:Itis a built-in Python function that allows you to apply a specific
function to each item in an iterable (such as a list or a tuple) and returns an iterator that
contains the results.
It provides a convenient way to perform operations on all elements of a collection
without the need for explicit loops.The general syntax of the map() function is as
follows:
map(function, iterable)
Where:
 function: A function or lambda function that you want to apply to each element of
the iterable.
 iterable: An iterable object (e.g., list, tuple, etc.) containing the elements to which
the function will be applied.
Consider the following example, where we have a list of numbers, and we want to
square each number in the list:
>>>nos = [1, 2, 3, 4, 5]
>>>squares= list(map(lambda x:x**2, nos))
>>> print(squares)
[1, 4, 9, 16, 25]
2. filter( ) function:Itis a built-in Python function that allows you to filter elements from
an iterable based on a specified conditionand returns new iterable with the filtered
elements.The general syntax of the map() function is as follows:
filter(function, iterable)
Consider the following example, where we have a list of numbers, and we want to
return all the even numbers in the list:
>>>nos = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>>enos= list(filter(lambda x:x%2==0, nos))
>>> print(enos)
[2, 4, 6, 8, 10]
3. reduce( ) function:Itis a built-in Python function that allows you to filter elements
from an iterable based on a specified conditionand returns new iterable with the filtered
elements.The general syntax of the map() function is as follows:
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filter(function, iterable)
Consider the following example, where we have a list of numbers, and we want to
return all the even numbers in the list:
>>>nos = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>>enos= list(filter(lambda x:x%2==0, nos))
>>> print(enos)
[2, 4, 6, 8, 10]
UNIT – IV
1 a) Demonstrate the creating class in python with an example.
What is Class in Python?
The class is a user-defined data structure that binds the data members and methods
into a single unit. Class is a blueprint or code template for object creation. Using a class,
you can create as many objects as you want.
For example, if we design a class based on the states and behaviours of a Person, then
States can be represented as instance variables and behaviours as class methods.
Create a Class in Python
In Python, class is defined by using the class keyword. The syntax to create a class is
given below.
class class_name:
<statement 1>
<statement 2>
.
.
<statement N>
Where,
class_name: It is the name of the class
statements: Attributes and methods
Define a class in Python
In this example, we are creating a Person Class with name, gender, and profession
instance variables and show as a method.
class Person:
def __init__(self, name, gender, profession):
# data members (instance variables)
self.name = name
self.gender = gender
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self.profession = profession
# Behavior (instance methods)
def show(self):
print('Name:', self.name, 'Gender:', self.gender, 'Profession:', self.profession)
def work(self):
print(self.name, 'working as a', self.profession)
1 b) Explain the procedure to read and write from the file.
In Python, any file operations can be performed in the following three steps:
Procedure:
Step 1: Open the file using the open() function.
Step 2: Perform read, write, append operations.
Step 3: Close the file.
Reading File
File object includes the following methods to read data from the file.
1. read(chars): reads the specified number of characters starting from the current
position.
2. readline(): reads line by line from file.
3. readlines(): reads all lines until the end of file and returns a list object.
The following C:\myfile.txt file will be used in all the examples of reading and writing
files.
C:\myfile.txt
first line.
second line.
third line.
The following example performs the read operation using the read() method.
f = open('myfile.txt','r')
# opening a file
st= f.read()
# reading a file
print(st)
f.close()
# closing file object
Output:
first line.
second line.
third line.
Writing to a File
The file object provides the following methods to write to a file.
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1. write(s): Write the string s to the stream and return the number of characters
written.
2. writelines(lines): Write a list of lines to the stream. Each line must have a
separator at the end of it.
Example: The following example creates a new file if it does not exist or overwrites to
an existing file.
f = open('myfile.txt','w')
f.write("Hello")
# Writing to file
f.close()
Note: It opens myfile.txt in write mode and overrides the existing contents of a file with
‘Hello’.
2 a) Discuss about constructors in python.
What is Constructor in Python?
In OOP, A constructor is a special method used to create and initialize an object of a
class. This method is defined in the class. The constructor is executed automatically at
the time of object creation.
Syntax of a constructor
def __init__(self):
# body of the constructor
In Python, we have the following types of constructors.
1. Non-parametrized constructor
2. Parameterized constructor
1. Non-Parametrized Constructor
A constructor without any arguments is called a non-parameterized constructor. This
type of constructor is used to initialize each object with default values. This constructor
doesn’t accept the arguments during object creation. Instead, it initializes every object
with the same set of values.
For example, consider a college that has name and address. In this case, while creating
object, we need to initialize the college name, address with some default values. In such
cases, use the non - parameterized constructor.
class College:
def __init__(self):
self.name = "VVIT"
self.address = "Nambur"
# no-argument constructor
# a method for printing data members
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def show(self):
print('Name:', self.name, 'Address:', self.address)
clg = College()
clg.show()
# creating object of the class
# calling the instance method using the object
Output
Name: VVIT Address: Nambur
2. Parameterized Constructor
A constructor with defined parameters or arguments is called a parameterized
constructor. We can pass different values to each object at the time of creation using a
parameterized constructor.
The first parameter to constructor is self that is a reference to the being constructed, and
the rest of the arguments are provided by the programmer. A parameterized constructor
can have any number of arguments.
For example, consider a college that contains hundreds of employees. In this case, while
creating each employee object, we need to pass a different name, age, and salary. In such
cases, use the parameterized constructor.
Example:
class Employee:
def __init__(self, name, age, salary):
self.name = name
self.age = age
self.salary = salary
# Parameterized constructor
def show(self):
print(self.name, self.age, self.salary)
# creating object of the Employee class
emp1 = Employee('Anand', 32, 55000)
emp1.show()
emp2= Employee('Vijay', 25, 85000)
emp2.show()
Output:
Anand 32 55000
Vijay 25 85000
2 b) Write a python program to copy the contents of one file to another.
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s_file = input("Enter name of the source file: ")
d_file = input("Enter name of the destination file: ")
f1 = open(s_file, "r")
f2 = open(d_file, "w")
txt = f1.read()
f2.write(txt)
print("File copied successfully")
f1.close()
f1.close()
Output:
Enter name of the source file: file1.txt
Enter name of the destination file: file2.txt
File copied successfully!!!
3 a) Explain about different access modifiers in python with example programs.
These access modifiers define how the members of the class can be accessed
outside the class.Access modifiers play an important role to protect the data from
unauthorized access as well as protecting it from getting manipulated.
Python makes the use of underscores to specify the access modifier for a specific
data member and member function in a class.
There are three types of access specifiers or access modifiers
1. Public
2. Private
3. Protected
1. Public Access Modifier
All the variables and methods (member functions) in python are by default public which
means they can be accessed from anywhere outside or inside the class. Any instance
variable in a class followed by the ‘self’ keyword i.e.,self.var_name is public accessed.
syntax:
self.var_name
Example:
class Student:
def __init__(self, age, name):
self.name = name
self.age = age
std = Student("Tony", 21)
print(std.name)
print(std.age)
# constructor is defined
# public Attribute
# public Attribute
# Object creation
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Output:
Tony
21
2. Private Access Modifier
These members are only accessible from within the class. We cannot access them
outside of the class. In python, private members and methods are declared using double
underscores(‘__’) as prefix before their names. It is not possible to inherit the private
members of any class (parent class) to derived class (child class).
Syntax:
self.__var_name
Example:
class Student:
def __init__(self, name):
self.name = name
self.__adhaar = 98765432102
# public Attribute
# private Attribute
def show(self):
print(self.name)
print(self.__adhaar)
std = Student("Tony")
std.show()
print(std.__adhaar)
Output:
Tony
98765432102
AttributeError: 'Student' object has no attribute '__adhaar'
3. Protected Access Modifier
The members declared as Protected are accessible from outside the class and its child or
subclass. In python, protected members and methods are declared using single
underscore(‘_’) as prefix before their names.
Syntax:
self._var_name
Example:
class Employee:
def __init__(self, name, sal):
self._name = name
self._sal = sal
# Base class
# protected attribute
# protected attribute
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class Hr(Employee):
#Derived class
def task(self):
print('We manage employees')
hr = Hr('Vijay',10000)
print(hr._name)
print(hr._sal)
Output:
Vijay
12000
3 b) How do you manipulate a file pointer in Python? Explain with an example.
The seek() and tell() methods are used for manipulating the current position of the file
pointer in a file.
1. seek() method
The seek() is used to move the file pointer from one location to another location
within the file. You can use it to reposition the file pointer to a specific location, so that
subsequent reads or writes will start from that position.
Syntax:
file.seek(offset)
The offset can be positive (to move the pointer forward) or negative (to move the
pointer backward)
When we open a file initially the file pointer position is at 0 i.e. beginning of file.
The seek() method returns the new file pointer position by adding an offset value to the
current file pointer position.
Example:
f = open("myfile.txt", "r")
# assume file has following 3 lines of data
# first line.
# second line.
# third line.
# Move the fp 12 positions ahead from current position
f.seek(12)
# read 6 bytes
print(f.read(6))
f.close()
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Output:
second
2. tell() method
The tell() method returns the current position of the file pointer, in bytes from the start
of the file. The position is an integer that represents the number of bytes from the
beginning of the file.
Syntax:
file.tell()
Example:
f = open("myfile.txt", "r")
# assume file has following 3 lines of data
#Move the file pointer to the 6th character
f.seek(6)
print('Current position: ',f.tell())
f.close()
Output:
Current position: 6
4 a) Briefly explain various types of inheritance with an example.
Inheritance means acquiring the properties and methods of one class to another class.
(Or)
It is the concept of deriving a new class from an existing class.
The class which inherits another class is known as the Child class, while the class which
is inherited by other classes is called as the Parent class. Python supports five types of
Inheritance:
1. Single Inheritance
2. Multiple Inheritance
3. Hierarchical Inheritance
4. Multilevel Inheritance
5. Hybrid Inheritance
1. Single Inheritance: When one child class is derived from only one parent class. This
is called Single inheritance. This means that there is only one subclass that is derived
from one superclass.
Single inheritance is usually declared as follows:
class Child_class_name(Parent_class_name):
#Child class specific code
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Example: Python program to that illustrates Single Inheritance
class Employee:
#Base class
def __init__(self):
self.eno=0
self.ename=''
def input(self):
self.eno=int(input('Enter employee no:'))
self.ename=input('Enter employee name:')
class Salary(Employee):
def __init__(self):
Employee.__init__(self)
self.sal=0
#Derived class
def read(self):
self.sal=int(input('Enter Salary:'))
def show_details(self):
print('EMP DETAILS\n---------------')
print('Emp No: ',self.eno)
print('Emp Name: ',self.ename)
print('Salary: ',self.sal)
s = Salary()
s.input();
s.read();
s.show_details();
Output:
Enter employee no:1234
Enter employee name:Vijay
Enter Salary:15000
EMP DETAILS
--------------Emp No: 1234
Emp Name: Vijay
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Salary: 15000
2. Multiple Inheritance: When a class can be derived from more than one base class is
called Multiple inheritance.
Multiple inheritance is usually declared as follows:
class Child_class_name(Parent_class_name1, Parent_class_name2):
#Child class specific code
Where A and B are Base classes, C is Derived class
Example: Python program to that illustrates Multiple Inheritance
class Mother:
# Base class1
m_name = ""
def mother(self):
print(self.m_name)
class Father:
f_name = ""
def father(self):
print(self.f_name)
# Base class2
class Son(Mother, Father): # Derived class
def parents(self):
print("Father :", self.f_name)
print("Mother :", self.m_name)
# Driver's code
s1 = Son()
s1.f_name = "Tony"
s1.m_name = "Cathy"
s1.parents()
Output:
Father : Tony
Mother : Cathy
3. Multilevel Inheritance: In multilevel inheritance, one class is derived from another
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class which in turn derived from another base class.
Multi-level inheritance is usually declared as follows:
class Child_class_name(Parent_class_name):
#Child class specific code
Where A is Base classes, C is Derived class and B is an Intermediate class
Example: Python program to that illustrates Multi-level Inheritance.
class Car:
# Base class1
def __init__(self):
print('Vehicle Type: Car')
class Maruti(Car):
def __init__(self):
Car.__init__(self)
print('Company: Maruti')
# Intermediate class
def speed(self):
print('Speed: 80 KMPH')
class Maruti800(Maruti):
def __init__(self):
Maruti.__init__(self)
print('Model: Maruti 800')
# Child class
def speed(self):
print('Speed: 120 KMPH')
# Driver's code
m = Maruti800()
m.speed()
Output:
Vehicle Type: Car
Company: Maruti
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Model: Maruti 800
Speed: 120 KMPH
4. Hierarchical Inheritance: When more than one class is derived from a single base
this type of inheritance is called Hierarchical inheritance.
Hierarchical inheritance is usually declared as follows:
class Child_class_name1 (Parent_class_name):
#Child class specific code
class Child_class_name2 (Parent_class_name):
#Child class specific code
class Child_class_name3 (Parent_class_name):
#Child class specific code
Where A is Base classes and B, C & D are Derived classe.
Example: Python program to that illustrates Multi-level Inheritance.
class Vehicle:
# Base class
def __init__(self):
print('Vehicle Type: Motor Vehicle')
class TwoWheeler(Vehicle):
def __init__(self):
Vehicle.__init__(self)
print('It has two wheels')
# Child class1
class ThreeWheeler(Vehicle):
def __init__(self):
Vehicle.__init__(self)
print('It has three wheels')
# Child class2
class FourWheeler(Vehicle):
def __init__(self):
Vehicle.__init__(self)
print('It has four wheels')
# Child class3
# Driver's code
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two = TwoWheeler()
print('------------')
two = ThreeWheeler()
print('------------')
four = FourWheeler()
Output:
Vehicle Type: Motor Vehicle
It has two wheels
-----------Vehicle Type: Motor Vehicle
It has three wheels
-----------Vehicle Type: Motor Vehicle
It has four wheels
5. Hybrid Inheritance:Combination of two or more types of inheritance is called hybrid
inheritance.
Example: Python program to that illustrates Hybrid Inheritance.
class University:
def __init__(self):
self.univ = "JNTUK"
def display(self):
print(f"University: {self.univ}")
class Course(University):
def __init__(self):
University.__init__(self)
self.course = "B.Tech"
def display(self):
print(f"Course: {self.course}")
University.display(self)
class Branch(University):
def __init__(self):
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self.branch = "ECE"
def display(self):
print(f"Branch : {self.branch}")
class Student(Course, Branch):
def __init__(self):
self.name = "Tony"
Branch.__init__(self)
Course.__init__(self)
def display(self):
print(f"Student Name: {self.name}")
Branch.display(self)
Course.display(self)
# Object Instantiation:
ob = Student() # Object named ob of the class Student.
print()
ob.display() # Calling the display method of Student class.
Output:
Student Name: Tony
Branch : ECE
Course :B.Tech
University : JNTUK
4 b) Explain about write() and writelines() functions in Python.
1. write() function
The write() method writes a specified text to the file. Where the specified textwill
be inserted depends on the file mode and stream position. When we open a file in write
mode i.e., "w" mode then the text will be inserted at the current file stream position. The
default stream position is beginning of the file i.e., 0.
When we open a file in append mode i.e., "a" mode then the text will be inserted
at the current file stream position. The default stream position is at the end of the file.
Syntax:
file.write(string)
Here, passed parameter is the content to be written into the opened file.
Example 1:
f = open("myfile.txt", "w")
f.write("\nGood Morning.")
f.close()
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Note : It creates myfile.txt and write Good Morning at beginning of file.
2. writelines() function
The writelines() method writes the contents of a list to the file. Since the newline
character is not automatically written to the file, it must be provided as a part of the
string.
Syntax:
file.writelines(list)
Example:
f = open("myfile.txt", "a")
f.writelines(["\nGood Afternoon",”\nGood Night”])
f.close()
Note: It opens myfile.txt in append mode and write Good Afternoon and Good Night at
end of the file.
5 a) How to implement method overriding in Python? Explain.
Method overriding means providing an alternative method definition to the existing
base class method in child class.
(Or)
Method overriding is the ability of a subclass to provide a different implementation of a
method that is already defined in its superclass. The method in child class is called
overriding method and method in base class is called overridden method.
Example: Python program that illustrates Method overriding.
class Animal:
name = ""
def eat(self):
print("I can eat")
class Dog(Animal):
def eat(self):
#Overridden method
# inherit from Animal
#Overriding method
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print("I like to eat bones")
labrador = Dog()
labrador.eat()
Output:
I like to eat bones.
In the above example, the same method eat() is present in both the Dog class and the
Animal class.Now, when we call the eat() method using the object of the Dog subclass,
the method of the Dog class is called.This is because the eat() method of the Dog
subclass overrides the same method of the Animal superclass.
5 b) Explain the prototypes of read(), readline() and readlines() functions in
Python.
Python allows you to read the contents of a file using methods such as:
1. read()
2. readline()
3. readlines()
1. read() function
The read() method returns the specified number of bytes from the file and return it as
string.
Syntax
file.read(size)
where is size is the number of bytes to be returned. Default is -1 which means the whole
file.
Example:Read the contents of the file "myfile.txt"
f = open("myfile.txt", "r")
txt = f.read(10)
print(txt)
f.close()
Output:
first line
2. readline() function
The readline() method reads a single line from a file and returns it as a string.
This means that if you use readline(), you can read the contents of a file line by line,
which can be useful for processing large files that do not fit in memory.
Syntax:
file.readline()
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Example: Read the contents of the file “myfile.txt”using readline() method.
f = open("myfile.txt", "r")
line = f.readline()
while line:
print(line.strip())
line = f.readline()
Output:
first line
second line
third line
3. readlines() function
The readlines() methodreads the entire contents of a file and returns it as a list of
strings, where each element of the list is a single line of the file.
Syntax:
file.readlines()
Example: Read the contents of the file “myfile.txt” using readlines() method.
f = open("myfile.txt", "r")
lines = f.readlines()
print(lines)
Output:
['first line\n', 'second line\n', 'third line']
UNIT-V
1 a) Explain try..except block in detail.
(or)
Describe in detail how exceptions are handled in Python. Give relevantexamples.
An exception is an event, which occurs during the execution of a program that disrupts
the normal flow of the program's instructions.When a Python script raises an exception,
it must either handle the exception immediately otherwise it terminates and quits.
Handling an exception
If you have some suspicious code that may raise an exception, you can defend your
program by placing the suspicious code in a try: block. After the try: block, include an
except: statement, followed by a block of code which handles the problem as elegantly as
possible.
Syntax
Here is simple syntax of try..except...else blocks –
try:
place your code here;
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except Exception1:
If there is Exception1, then execute this block.
except Exception2:
If there is Exception2, then execute this block.
else:
If there is no exception then execute this block.
If the exception occurs, the program flow is transferred to the except: block. The
statements in the except: block is meant to handle the cause of the exception
appropriately. otherwise except block is skipped.
Example: Program that raises IOError when the required file is not available on the
disk.
try:
f_name = input('Enter file name:')
f = open(f_name, "r")
txt = f.read()
print(txt)
except IOError:
print(f_name," is not found.")
Output:
Enter file name: myfile.txt
myfile.txt is not found.
1 b) Demonstrate GUI based programming with an example.
(Or)
Discuss the importance of GUI based programs with an example.
A Graphical User Interface (GUI) is more user-friendly and easier to interact with. They
are very attractive and visually impactful, making users more convenient for usage.They
do not need prior computer skills or knowledge to perform computer operations.
Python provides various options for developing graphical user interfaces (GUIs). Most
important are listed below.
 Tkinter −Tkinter is the Python interface to the Tk GUI toolkit shipped with
Python. We would look this option in this chapter.
 wxPython − This is an open-source Python interface for wxWindows
http://wxpython.org.
 JPython −JPython is a Python port for Java which gives Python scripts seamless
access to Java class libraries on the local machine http://www.jython.org.
Tkinter Programming
Tkinter is the standard GUI library for Python. Python when combined with Tkinter
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provides a fast and easy way to create GUI applications. Tkinter provides a powerful
object-oriented interface to the Tk GUI toolkit.
Creating a GUI application using Tkinter is an easy task. All you need to do is perform
the following steps −
Step 1:Import the tkinter module.
Step 2:Create the GUI application main window.
Step 3:Add one or more widgets to the GUI application.
Step 4:Enter the main event loop to take action against each event triggered by the user.
Example
import tkinter as tk
win = tk.Tk()
# Code to add widgets
win.mainloop()
This would create a following window −
2 a) How to handle multiple exceptions in Python? Explain with an example.
To catch multiple exceptions individually, we can write multiple catch blocks.
Syntax:
try:
# try block statement
except Exception1:
Statements
except Exception2:
Statements
.
.
.
except ExceptionN:
Statements
The other way is to use a single except block and write all the exceptions as a tuple
inside parenthesis as:
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except (Exceptionclass1, Exceptionclass2,.. ):
Statements
Example: Program for handling multiple exceptions separately
try:
l = [10, 30, 40]
r = l[4]/0
print(r)
except IndexError:
print('Index out of range')
except ZeroDivisionError:
print('Denominator should not be zero')
except:
print('Unknow Error')
Output:
Index out of range
Example: Program that handles multiple Exception in a single except block.
import math as m
try:
r = m.exp(1000)
print(r)
except (ZeroDivisionError,ValueError,OverflowError):
print('Arithmetic Error')
Output:
Arithmetic Error
2 b) Explain about Radiobutton widget in tkinter. How to create two radiobutton
sets (one for gender and another for Indian or not) on the same canvas.
The Radiobutton widget is used to implement one-of-many selection in the python
application. It shows multiple choices to the user out of which, the user can select only
one of them.
Syntax
w = Radiobutton(master, options)
Some of most frequently used options are:
1. text - The text to be displayed on the radiobutton.
2. value - The value of each radiobutton is assigned to the control variable when it
is turned on by the user.
3. variable - It is the control variable which is used to keep track of the user's
choices. It is shared among all the radiobuttons.
4. Command - This option is set to the procedure which must be called every-time
when the state of the radiobutton is changed.
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Example:
import tkinter as tk
win = tk.Tk()
win.title('Radios')
win.geometry('300x200')
r1 = tk.IntVar()
r2 = tk.IntVar()
lbl1 = tk.Label(win,text='Gender:')
lbl1.grid(row=0,column=0)
rbtn1 = tk.Radiobutton(win,text="Male",variable=r1,value=1)
rbtn1.grid(row=0,column=1)
rbtn2 = tk.Radiobutton(win,text="Female",variable=r1,value=2)
rbtn2.grid(row=1,column=1)
lbl2 = tk.Label(win,text='Nationality:')
lbl2.grid(row=2,column=0)
rbtn3 = tk.Radiobutton(win,text="Indian",variable=r2,value=3)
rbtn3.grid(row=2,column=1)
rbtn4 = tk.Radiobutton(win,text="Other",variable=r2,value=4)
rbtn4.grid(row=3,column=1)
win.mainloop()
Output:
3 a) Explain in detail about creating user-defined exceptions with the help of a
sample program.
Python also allows you to create your own exceptions by deriving classes from the
standard built-in exceptions which are called “User-defined exceptions” or “Custom
exceptions‟.
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Steps required to create Custom exception
Step 1:Since all exceptions are classes, the programmer is supposed to create his own
exception as a class. Also, he should make his class as a sub class to the in-built
“Exception” class.
Syntax:
class MyException(Exception):
def __init__ (self, arg):
self.msg = arg
Here, MyException class is the sub class for “Exception‟ class. This class has a
constructor where a variable “msg‟ is defined. This “msg‟ receives a message passed
from outside through “arg‟.
Step 2: The programmer can write his code; maybe it represents a group of statements
or a function. When the programmer suspects the possibility of exception, he should
raise his own exception using “raise‟ statement as:
raise MyException(‘message’)
Here, raise statement is raising MyException class object that contains the given
“message”.
Step 3. The programmer can insert the code inside a “try” block and catch the exception
using“except‟ block as:
try:
code
except MyException as ex:
print(me)
Here, the object “ex‟ contains the message given in the raise statement. All these steps
are shown in below program.
Example: Python program to create an Exception named "InsufficientFundsException"
and raise it when Bank Account having balance lessthan 2000.
class InsufficientFundsException(Exception):
def init (self, msg):
self.msg = msg
def check(dict):
for k,v in dict.items():
if v<2000:
raise InsufficientFundsException ("Balance is less in the account of "+k)
bank={"Ravi":5000,"Raju":1990,"Ramu":8500}
try:
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check(bank)
except InsufficientFundsException as ex:
print(ex)
Output:
Balance is less in the account of Raju.
3 b) Write a Python program that creates a GUI with a textbox, Ok button and Quit
button. On clicking Ok, the text entered in textbox is to be printed in Python shell;
on clicking Quit, the program should terminate.
import tkinter as tk
def show():
print(e.get())
win = tk.Tk()
win.title('Test Page')
win.geometry('100x100')
e = tk.Entry(win,bd=1)
e.pack()
ok_btn = tk.Button(win,text="Ok",command=show)
ok_btn.pack(side=tk.LEFT)
quit_btn = tk.Button(win,text="Quit",command=quit)
quit_btn.pack(side=tk.RIGHT)
win.mainloop()
Output:
4 a) Explain how to raise and handle an exception with an example.
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Built-in errors are raised implicitly. However, a built-in or custom exception can be
raised manually by using raise keyword.The general syntax for the raise statement is as
follows.
raise Exception (arg)
Here, Exception is the type of exception (For example, NameError) and argument is a
value for the exception argument. The argument is optional; if not supplied, the
exception argument is None.
Example:The following code accepts a number from the user. The try block raises a
ValueError exception if the number is outside the allowed range.
try:
x,y=100,2
z=x/2
if z > 10:
raise ValueError(z)
except ValueError:
print(z, "is out of allowed range")
else:
print(z, "is within the allowed range")
Output:
50.0 is out of allowed range.
4 b) Compare the GUI-based programs with Terminal-based programs.
What is GUI?
A Graphical User Interface (GUI) is a visual representation of communication that
makes it easy for users to interact with electronic devices. GUI combines many graphical
representations, including graphic icons such as menus, cursors, tabs, mouse, windows,
and scroll bars.
Communication between the user and the electronic device is performed by
interacting with these graphical icons. Graphical user interfaces have become a
standard user-centred design when it comes to software application programming.
They provide users the capacity to interact and operate electronic devices, more so,
computers.
Apple’s Macintosh and Microsoft Windows operating systems are excellent examples of
GUI.
What is CUI?
Character / Command-line interface (CUI) is a command-line program that relies on text
inputs to perform operating system functions. CLI was the standard way of interacting
with computing devices in the early days of computing.
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Still, system administrators and software developers use CLI to install software, access
features missing in the graphical interface, and configure computers. are the most
common types of CLIs in use today.
The differences between Graphical User Interface (GUI) and Character User
Interface (CUI)
CUI
GUI
1. CUI stands for Character User 1. GUI stands for Graphical User
Interface.
Interface.
2. In CUI user interacts with applications 2. In GUI user interacts with applications
by making use of commands.
by making use of graphics such as icons
and images.
3. Only one task can run at a time.
3.More than one task can run
simultaneously.
4. A CUI will require less computer 3. A GUI will require a lot of more system
resources.
resources because each element that
needs to be loaded such as icons fonts etc.
5. CUI appearance is not easily changeable. 5. GUI is highly customizable.
6. CUI is of high speed.
6. GUI is of low speed.
7. Usage is difficult, requires expertise.
7. Usage is easy.
8. Bash shell (for Mac OS and Linux) and 8. Apple’s Macintosh and Microsoft
MS-DOS (for Windows) are the best Windows are the best examples for GUI.
examples for CUI
Drawbacks of CUI
 A large number of commands makes it challenging to use CUI, even for
experienced users.
 CUI leaves a small room for error. Mistyped commands may not get processed
correctly.
 In case of mistyped instructions, you may need to start from scratch again.
Drawbacks of GUI
• GUI is not resource optimized. The aim is to make a user-friendly interface, and
as such, it uses more computer memory.
• Applications based on GUI require more RAM to run than those based on other
interface types.
• Users need to use the help file to find hidden commands.
• Compared to other interface types, GUI uses more processing power.
5 a) Explain the difference between else block and finally block in exception
handling? Explain with an example.
else and finally:
In Python, keywords else and finally can also be used along with the try and
except clauses.
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While the except block is executed if the exception occurs inside the try block, the
elseblock comes into execution only when there is no exception raised in the try block.
The finally block consists of statements which should be processed regardless of
an exception occurring in the try block or not.
As a consequence, the error-free try block skips the except clause and enters the
finally block before going on to execute the rest of the code. If, however, there's an
exception in the try block, the appropriate except block will be processed, and the
statements in the finally block will be processed before proceeding to the rest of the
code.
Syntax:
try:
#statements in try block
except:
#executed when error in try block
else:
#executed if try block is error-free
finally:
#executed irrespective of exception occurred or not
Example:The example below accepts two numbers from the user and performs their
division. It demonstrates the uses of else and finally blocks.
try:
x,y =[int(x) for x in input('Enter two integers:').split()]
z=x/y
except ZeroDivisionError:
print("except ZeroDivisionError block")
print("Division by 0 not accepted")
except:
print('Some error occurred.')
else:
print("Division = ", z)
finally:
print("Executing finally block")
x, y=0,0
print ("Out of try, except, else and finally blocks.")
Case 1:The first run is a normal case. The out of the else and finally blocks are displayed
because the try block is error-free.
Output 1:
Enter two integers:10 2
Division = 5.0
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Executing finally block
Out of try, except, else and finally blocks.
Case 2: The second run is a case of division by zero, hence, the except block and the
finally block are executed, but the else block is not executed.
Output 2:
Enter two integers:10 0
except ZeroDivisionError block
Division by 0 not accepted
Executing finally block
Out of try, except, else and finally blocks.
5 b) Explain about Checkbutton widget in tkinter. How to create three
checkbuttons (one for Telugu, Second for English and third for Hindi) on the same
canvas.
The Checkbutton widget is used to track the user's choices provided to the application.
The Checkbutton is mostly used to provide multiple choices to the user among which,
the user needs to choose one or many.
Syntax
w = checkbutton(master, options)
Some of most frequently used options are:
1. text - The text to be displayed on the checkbutton.
2. variable - It represents the associated variable that tracks the state of the
checkbutton.
3. onvalue - The associated control variable is set to 1 by default if the button is
checked. We can change the state of the checked variable to some other one.
4. offvalue - The associated control variable is set to 0 by default if the button is
unchecked. We can change the state of an unchecked variable to some other one.
5. command - It is associated with a function to be called when the state of the
checkbutton is changed.
Example:
win=tk.Tk()
win.title('Check buttons')
win.geometry('250x100')
chkVar1 =tk.IntVar()
chkVar2 =tk.IntVar()
chkVar3 =tk.IntVar()
lbl = tk.Label(win,text="Languages Known:")
lbl.grid(row=0,column=0)
c1 = tk.Checkbutton(win,text='Telugu',variable=chkVar1,onvalue=1,offvalue=0)
c1.grid(row=0,column=1)
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c2 = tk.Checkbutton(win,text='English',variable=chkVar2,onvalue=1,offvalue=0)
c2.grid(row=1,column=1)
c3 = tk.Checkbutton(win,text='Hindi',variable=chkVar3,onvalue=1,offvalue=0)
c3.grid(row=2,column=1)
win.mainloop()
Output:
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