Python Notes.pdf

Durgasoft PYTHON
1
Python
By
DURGA

1 DURGASOFT, # 202, 2
nd
Floor, HUDA Maitrivanam, Ameerpet, Hyderabad - 500038,
 040 – 64 51 27 86, 80 96 96 96 96, 92 46 21 21 43 | www.durgasoft.com
Language Fundamentals
Introduction
 Python is a general purpose high level programming language.
 Python was developed by Guido Van Rossam in 1989 while working at National
Research Institute at Netherlands.
 But officially Python was made available to public in 1991. The official Date of Birth for
Python is : Feb 20th 1991.
 Python is recommended as first programming language for beginners.
Eg1: To print Helloworld:
Java:
1) public class HelloWorld
2) {
3) p s v main(String[] args)
4) {
5) SOP("Hello world");
6) }
7) }
C:
1) #include<stdio.h>
2) void main()
3) {
4) print("Hello world");
5) }
Python:
print("Hello World")

nd
Eg2: To print the sum of 2 numbers
Java:
1) public class Add
2) {
3) public static void main(String[] args)
4) {
5) int a,b;
6) a =10;
7) b=20;
8) System.out.println("The Sum:"+(a+b));
9) }
10) }
C:
1) #include <stdio.h>
2)
3) void main()
4) {
5) int a,b;
6) a =10;
7) b=20;
8) printf("The Sum:%d",(a+b));
9) }
Python:
1) a=10
2) b=20
3) print("The Sum:",(a+b))
The name Python was selected from the TV Show
"The Complete
Monty
Python's
Circus", which was broadcasted in BBC from 1969 to 1974.
Guido developed Python language by taking almost all programming features from
different languages
1. Functional Programming Features from C
2. Object Oriented Programming Features from C++
3. Scripting Language Features from Perl and Shell Script

nd
4. Modular Programming Features from Modula-3
Most of syntax in Python Derived from C and ABC languages.
Where we can use Python:
We can use everywhere. The most common important application areas are
1. For developing Desktop Applications
2. For developing web Applications
3. For developing database Applications
4. For Network Programming
5. For developing games
6. For Data Analysis Applications
7. For Machine Learning
8. For developing Artificial Intelligence Applications
9. For IOT
...
Note:
Internally Google and Youtube use Python coding
NASA and Nework Stock Exchange Applications developed by Python.
Top Software companies like Google, Microsoft, IBM, Yahoo using Python.
Features of Python:
1. Simple and easy to learn:
Python is a simple programming language. When we read Python program,we can feel like
reading english statements.
The syntaxes are very simple and only 30+ kerywords are available.
When compared with other languages, we can write programs with very less number of
lines. Hence more readability and simplicity.
We can reduce development and cost of the project.
2. Freeware and Open Source:
We can use Python software without any licence and it is freeware.
Its source code is open,so that we can we can customize based on our requirement.
Eg: Jython is customized version of Python to work with Java Applications.

nd
3. High Level Programming language:
Python is high level programming language and hence it is programmer friendly language.
Being a programmer we are not required to concentrate low level activities like memory
management and security etc..
4. Platform Independent:
Once we write a Python program,it can run on any platform without rewriting once again.
Internally PVM is responsible to convert into machine understandable form.
5. Portability:
Python programs are portable. ie we can migrate from one platform to another platform
very easily. Python programs will provide same results on any paltform.
6. Dynamically Typed:
In Python we are not required to declare type for variables. Whenever we are assigning
the value, based on value, type will be allocated automatically.Hence Python is considered
as dynamically typed language.
But Java, C etc are Statically Typed Languages b'z we have to provide type at the beginning
only.
This dynamic typing nature will provide more flexibility to the programmer.
7. Both Procedure Oriented and Object Oriented:
Python language supports both Procedure oriented (like C, pascal etc) and object oriented
(like C++,Java) features. Hence we can get benefits of both like security and reusability etc
8. Interpreted:
We are not required to compile Python programs explcitly. Internally Python interpreter
will take care that compilation.
If compilation fails interpreter raised syntax errors. Once compilation success then PVM
(Python Virtual Machine) is responsible to execute.
9. Extensible:
We can use other language programs in Python.
The main advantages of this approach are:

nd
1. We can use already existing legacy non-Python code
2. We can improve performance of the application
10. Embedded:
We can use Python programs in any other language programs.
i.e we can embedd Python programs anywhere.
11. Extensive Library:
Python has a rich inbuilt library.
Being a programmer we can use this library directly and we are not responsible to
implement the functionality.
etc...
Limitations of Python:
1. Performance wise not up to the mark b'z it is interpreted language.
2. Not using for mobile Applications
Flavors of Python:
1.CPython:
It is the standard flavor of Python. It can be used to work with C lanugage Applications
2. Jython or JPython:
It is for Java Applications. It can run on JVM
3. IronPython:
It is for C#.Net platform
4.PyPy:
The main advantage of PyPy is performance will be improved because JIT compiler is
available inside PVM.
5.RubyPython
For Ruby Platforms
6. AnacondaPython
It is specially designed for handling large volume of data processing.
...

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Python Versions:
Python 1.0V introduced in Jan 1994
Python 2.0V introduced in October 2000
Python 3.0V introduced in December 2008
Note: Python 3 won't provide backward compatibility to Python2
i.e there is no guarantee that Python2 programs will run in Python3.
Current versions
Python 3.6.1 Python 2.7.13

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Identifiers
A name in Python program is called identifier.
It can be class name or function name or module name or variable name.
a = 10
Rules to define identifiers in Python:
1. The only allowed characters in Python are
 alphabet symbols(either lower case or upper case)
 digits(0 to 9)
 underscore symbol(_)
By mistake if we are using any other symbol like $ then we will get syntax error.
 cash = 10 √
 ca$h =20 
2. Identifier should not starts with digit
 123total 
 total123 √
3. Identifiers are case sensitive. Of course Python language is case sensitive language.
 total=10
 TOTAL=999
 print(total) #10
 print(TOTAL) #999

nd
Identifier:
1. Alphabet Symbols (Either Upper case OR Lower case)
2. If Identifier is start with Underscore (_) then it indicates it is private.
3. Identifier should not start with Digits.
4. Identifiers are case sensitive.
5. We cannot use reserved words as identifiers
Eg: def=10 
6. There is no length limit for Python identifiers. But not recommended to use too lengthy
identifiers.
7. Dollor ($) Symbol is not allowed in Python.
Q. Which of the following are valid Python identifiers?
1) 123total 
2) total123 √
3) java2share √
4) ca$h 
5) _abc_abc_ √
6) def 
7) if 
Note:
1. If identifier starts with _ symbol then it indicates that it is private
2. If identifier starts with __(two under score symbols) indicating that strongly private
identifier.
3.If the identifier starts and ends with two underscore symbols then the identifier is
language defined special name,which is also known as magic methods.
Eg: __add__

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Reserved Words
In Python some words are reserved to represent some meaning or functionality. Such type
of words are called Reserved words.
There are 33 reserved words available in Python.
 True,False,None
 and, or ,not,is
 if,elif,else
 while,for,break,continue,return,in,yield
 try,except,finally,raise,assert
 import,from,as,class,def,pass,global,nonlocal,lambda,del,with
Note:
1. All Reserved words in Python contain only alphabet symbols.
2. Except the following 3 reserved words, all contain only lower case alphabet symbols.
 True
 False
 None
Eg: a= true 
a=True √
>>> import keyword
>>> keyword.kwlist
['False', 'None', 'True', 'and', 'as', 'assert', 'break', 'class', 'continue', 'def', 'del', 'elif', 'else',
'except', 'finally', 'for', 'from', 'global', 'if', 'import', 'in', 'is', 'lambda', 'nonlocal', 'not', 'or',
'pass', 'raise', 'return', 'try', 'while', 'with', 'yield']

nd
Data Types
Data Type represent the type of data present inside a variable.
In Python we are not required to specify the type explicitly. Based on value provided,the
type will be assigned automatically.Hence Python is Dynamically Typed Language.
Python contains the following inbuilt data types
1. int
2. float
3.complex
4.bool
5.str
6.bytes
7.bytearray
8.range
9.list
10.tuple
11.set
12.frozenset
13.dict
14.None
Note: Python contains several inbuilt functions
1.type()
to check the type of variable
2. id()
to get address of object
10
10
20
a
a
b
a = 10
a = 20
a = 10
b = 10

nd
3. print()
to print the value
In Python everything is object
int data type:
We can use int data type to represent whole numbers (integral values)
Eg:
a=10
type(a) #int
Note:
In Python2 we have long data type to represent very large integral values.
But in Python3 there is no long type explicitly and we can represent long values also by
using int type only.
We can represent int values in the following ways
1. Decimal form
2. Binary form
3. Octal form
4. Hexa decimal form
1. Decimal form(base-10):
It is the default number system in Python
The allowed digits are: 0 to 9
Eg: a =10
2. Binary form(Base-2):
The allowed digits are : 0 & 1
Literal value should be prefixed with 0b or 0B
Eg: a = 0B1111
a =0B123
a=b111
3. Octal Form(Base-8):
The allowed digits are : 0 to 7
Literal value should be prefixed with 0o or 0O.

nd
Eg: a=0o123
a=0o786
4. Hexa Decimal Form(Base-16):
The allowed digits are : 0 to 9, a-f (both lower and upper cases are allowed)
Literal value should be prefixed with 0x or 0X
Eg:
a =0XFACE
a=0XBeef
a =0XBeer
Note: Being a programmer we can specify literal values in decimal, binary, octal and hexa
decimal forms. But PVM will always provide values only in decimal form.
a=10
b=0o10
c=0X10
d=0B10
print(a)10
print(b)8
print(c)16
print(d)2
Base Conversions
Python provide the following in-built functions for base conversions
1.bin():
We can use bin() to convert from any base to binary
Eg:
1) >>> bin(15)
2) '0b1111'
3) >>> bin(0o11)
4) '0b1001'
5) >>> bin(0X10)
6) '0b10000'
2. oct():
We can use oct() to convert from any base to octal

nd
Eg:
1) >>> oct(10)
2) '0o12'
3) >>> oct(0B1111)
4) '0o17'
5) >>> oct(0X123)
6) '0o443'
3. hex():
We can use hex() to convert from any base to hexa decimal
Eg:
1) >>> hex(100)
2) '0x64'
3) >>> hex(0B111111)
4) '0x3f'
5) >>> hex(0o12345)
6) '0x14e5'
float data type:
We can use float data type to represent floating point values (decimal values)
Eg: f=1.234
type(f) float
We can also represent floating point values by using exponential form (scientific notation)
Eg: f=1.2e3
print(f) 1200.0
instead of 'e' we can use 'E'
The main advantage of exponential form is we can represent big values in less memory.
***Note:
We can represent int values in decimal, binary, octal and hexa decimal forms. But we can
represent float values only by using decimal form.
Eg:
1) >>> f=0B11.01
2) File "<stdin>", line 1
3) f=0B11.01

nd
4) ^
5) SyntaxError: invalid syntax
6)
7) >>> f=0o123.456
9)
10) >>> f=0X123.456
Complex Data Type:
A complex number is of the form
a and b contain intergers or floating point values
Eg:
3+5j
10+5.5j
0.5+0.1j
In the real part if we use int value then we can specify that either by decimal,octal,binary
or hexa decimal form.
But imaginary part should be specified only by using decimal form.
1) >>> a=0B11+5j
2) >>> a
3) (3+5j)
4) >>> a=3+0B11j
Even we can perform operations on complex type values.
1) >>> a=10+1.5j
2) >>> b=20+2.5j
3) >>> c=a+b
4) >>> print(c)
5) (30+4j)
6) >>> type(c)
7) <class 'complex'>
a + bj
Real Part Imaginary Part
j2 = -1
j =

nd
Note: Complex data type has some inbuilt attributes to retrieve the real part and
imaginary part
c=10.5+3.6j
c.real==>10.5
c.imag==>3.6
We can use complex type generally in scientific Applications and electrical engineering
Applications.
4.bool data type:
We can use this data type to represent boolean values.
The only allowed values for this data type are:
True and False
Internally Python represents True as 1 and False as 0
b=True
type(b) =>bool
Eg:
a=10
b=20
c=aTrue
True+True==>2
True-False==>1
str type:
str represents String data type.
A String is a sequence of characters enclosed within single quotes or double quotes.
s1='durga'
s1="durga"
By using single quotes or double quotes we cannot represent multi line string literals.
s1="durga

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soft"
For this requirement we should go for triple single quotes(''') or triple double quotes(""")
s1='''durga
soft'''
s1="""durga
soft"""
We can also use triple quotes to use single quote or double quote in our String.
''' This is " character'''
' This i " Character '
We can embed one string in another string
'''This "Python class very helpful" for java students'''
Slicing of Strings:
slice means a piece
[ ] operator is called slice operator,which can be used to retrieve parts of String.
In Python Strings follows zero based index.
The index can be either +ve or -ve.
+ve index means forward direction from Left to Right
-ve index means backward direction from Right to Left
1) >>> s="durga"
2) >>> s[0]
3) 'd'
4) >>> s[1]
5) 'u'
6) >>> s[-1]
7) 'a'
8) >>> s[40]
IndexError: string index out of range
d u r g a
0 1 2 3 4
-5 -4 -3 -2 -1

nd
1) >>> s[1:40]
2) 'urga'
3) >>> s[1:]
4) 'urga'
5) >>> s[:4]
6) 'durg'
7) >>> s[:]
8) 'durga'
9) >>>
10)
11)
12) >>> s*3
13) 'durgadurgadurga'
14)
15) >>> len(s)
16) 5
Note:
1. In Python the following data types are considered as Fundamental Data types
 int
 float
 complex
 bool
 str
2. In Python,we can represent char values also by using str type and explicitly char type is
not available.
Eg:
1) >>> c='a'
2) >>> type(c)
3) <class 'str'>
3. long Data Type is available in Python2 but not in Python3. In Python3 long values also
we can represent by using int type only.
4. In Python we can present char Value also by using str Type and explicitly char Type is
not available.

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Type Casting
We can convert one type value to another type. This conversion is called Typecasting or
Type coersion.
The following are various inbuilt functions for type casting.
1. int()
2. float()
3. complex()
4. bool()
5. str()
1.int():
We can use this function to convert values from other types to int
Eg:
1) >>> int(123.987)
2) 123
3) >>> int(10+5j)
4) TypeError: can't convert complex to int
5) >>> int(True)
6) 1
7) >>> int(False)
8) 0
9) >>> int("10")
10) 10
11) >>> int("10.5")
12) ValueError: invalid literal for int() with base 10: '10.5'
13) >>> int("ten")
14) ValueError: invalid literal for int() with base 10: 'ten'
15) >>> int("0B1111")
16) ValueError: invalid literal for int() with base 10: '0B1111'
Note:
1. We can convert from any type to int except complex type.
2. If we want to convert str type to int type, compulsary str should contain only integral
value and should be specified in base-10

nd
2. float():
We can use float() function to convert other type values to float type.
1) >>> float(10)
2) 10.0
3) >>> float(10+5j)
4) TypeError: can't convert complex to float
5) >>> float(True)
6) 1.0
7) >>> float(False)
8) 0.0
9) >>> float("10")
10) 10.0
11) >>> float("10.5")
12) 10.5
13) >>> float("ten")
14) ValueError: could not convert string to float: 'ten'
15) >>> float("0B1111")
16) ValueError: could not convert string to float: '0B1111'
Note:
1. We can convert any type value to float type except complex type.
2. Whenever we are trying to convert str type to float type compulsary str should be
either integral or floating point literal and should be specified only in base-10.
3.complex():
We can use complex() function to convert other types to complex type.
Form-1: complex(x)
We can use this function to convert x into complex number with real part x and imaginary
part 0.
Eg:
1) complex(10)==>10+0j
2) complex(10.5)===>10.5+0j
3) complex(True)==>1+0j
4) complex(False)==>0j
5) complex("10")==>10+0j
6) complex("10.5")==>10.5+0j
7) complex("ten")
8) ValueError: complex() arg is a malformed string

nd
Form-2: complex(x,y)
We can use this method to convert x and y into complex number such that x will be real
part and y will be imaginary part.
Eg: complex(10,-2)==>10-2j
complex(True,False)==>1+0j
4. bool():
We can use this function to convert other type values to bool type.
Eg:
1) bool(0)==>False
2) bool(1)==>True
3) bool(10)===>True
4) bool(10.5)===>True
5) bool(0.178)==>True
6) bool(0.0)==>False
7) bool(10-2j)==>True
8) bool(0+1.5j)==>True
9) bool(0+0j)==>False
10) bool("True")==>True
11) bool("False")==>True
12) bool("")==>False

nd
5. str():
We can use this method to convert other type values to str type
Eg:
1) >>> str(10)
2) '10'
3) >>> str(10.5)
4) '10.5'
5) >>> str(10+5j)
6) '(10+5j)'
7) >>> str(True)
8) 'True'
Fundamental Data Types vs Immutability:
All Fundamental Data types are immutable. i.e once we creates an object,we cannot
perform any changes in that object. If we are trying to change then with those changes a
new object will be created. This non-chageable behaviour is called immutability.

nd
In Python if a new object is required, then PVM wont create object immediately. First it
will check is any object available with the required content or not. If available then
existing object will be reused. If it is not available then only a new object will be created.
The advantage of this approach is memory utilization and performance will be improved.
But the problem in this approach is,several references pointing to the same object,by
using one reference if we are allowed to change the content in the existing object then the
remaining references will be effected. To prevent this immutability concept is required.
According to this once creates an object we are not allowed to change content. If we are
trying to change with those changes a new object will be created.
Eg:
1) >>> a=10
2) >>> b=10
3) >>> a is b
4) True
5) >>> id(a)
6) 1572353952
7) >>> id(b)
8) 1572353952
9) >>>
>>> a=10
>>> b=10
>>> id(a)
1572353952
>>> id(b)
1572353952
>>> a is b
True
>>> a=10+5j
>>> b=10+5j
>>> a is b
False
>>> id(a)
15980256
>>> id(b)
15979944
>>> a=True
>>> b=True
>>> a is b
True
>>> id(a)
1572172624
>>> id(b)
1572172624
>>> a='durga'
>>> b='durga'
>>> a is b
True
>>> id(a)
16378848
>>> id(b)
16378848

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bytes Data Type:
bytes data type represens a group of byte numbers just like an array.
Eg:
1) x = [10,20,30,40]
2) b = bytes(x)
3) type(b)==>bytes
4) print(b[0])==> 10
5) print(b[-1])==> 40
6) >>> for i in b : print(i)
7)
8) 10
9) 20
10) 30
11) 40
Conclusion 1:
The only allowed values for byte data type are 0 to 256. By mistake if we are trying to
provide any other values then we will get value error.
Conclusion 2:
Once we creates bytes data type value, we cannot change its values,otherwise we will get
TypeError.
Eg:
1) >>> x=[10,20,30,40]
2) >>> b=bytes(x)
3) >>> b[0]=100
4) TypeError: 'bytes' object does not support item assignment
bytearray Data type:
bytearray is exactly same as bytes data type except that its elements can be modified.
Eg 1:
1) x=[10,20,30,40]
2) b = bytearray(x)
3) for i in b : print(i)
4) 10

nd
5) 20
6) 30
7) 40
8) b[0]=100
9) for i in b: print(i)
10) 100
11) 20
12) 30
13) 40
Eg 2:
1) >>> x =[10,256]
2) >>> b = bytearray(x)
3) ValueError: byte must be in range(0, 256)
list data type:
If we want to represent a group of values as a single entity where insertion order required
to preserve and duplicates are allowed then we should go for list data type.
1. insertion order is preserved
2. heterogeneous objects are allowed
3. duplicates are allowed
4. Growable in nature
5. values should be enclosed within square brackets.
Eg:
1) list=[10,10.5,'durga',True,10]
2) print(list) # [10,10.5,'durga',True,10]
Eg:
1) list=[10,20,30,40]
2) >>> list[0]
3) 10
4) >>> list[-1]
5) 40
6) >>> list[1:3]
7) [20, 30]
8) >>> list[0]=100
9) >>> for i in list:print(i)
10) ...
11) 100
12) 20
13) 30

nd
14) 40
list is growable in nature. i.e based on our requirement we can increase or decrease the
size.
1) >>> list=[10,20,30]
2) >>> list.append("durga")
3) >>> list
4) [10, 20, 30, 'durga']
5) >>> list.remove(20)
6) >>> list
7) [10, 30, 'durga']
8) >>> list2=list*2
9) >>> list2
10) [10, 30, 'durga', 10, 30, 'durga']
Note: An ordered, mutable, heterogenous collection of eleemnts is nothing but list, where
duplicates also allowed.
tuple data type:
tuple data type is exactly same as list data type except that it is immutable.i.e we cannot
chage values.
Tuple elements can be represented within parenthesis.
Eg:
1) t=(10,20,30,40)
2) type(t)
3) <class 'tuple'>
4) t[0]=100
5) TypeError: 'tuple' object does not support item assignment
6) >>> t.append("durga")
7) AttributeError: 'tuple' object has no attribute 'append'
8) >>> t.remove(10)
9) AttributeError: 'tuple' object has no attribute 'remove'
Note: tuple is the read only version of list
range Data Type:
range Data Type represents a sequence of numbers.
The elements present in range Data type are not modifiable. i.e range Data type is
immutable.

nd
Form-1: range(10)
generate numbers from 0 to 9
Eg:
r=range(10)
for i in r : print(i) 0 to 9
Form-2: range(10,20)
generate numbers from 10 to 19
r = range(10,20)
for i in r : print(i) 10 to 19
Form-3: range(10,20,2)
2 means increment value
r = range(10,20,2)
for i in r : print(i) 10,12,14,16,18
We can access elements present in the range Data Type by using index.
r=range(10,20)
r[0]==>10
r[15]==>IndexError: range object index out of range
We cannot modify the values of range data type
Eg:
r[0]=100
TypeError: 'range' object does not support item assignment
We can create a list of values with range data type
Eg:
1) >>> l = list(range(10))
2) >>> l
3) [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
set Data Type:
If we want to represent a group of values without duplicates where order is not important
then we should go for set Data Type.

nd
1. insertion order is not preserved
2. duplicates are not allowed
3. heterogeneous objects are allowed
4. index concept is not applicable
5. It is mutable collection
6. Growable in nature
Eg:
1) s={100,0,10,200,10,'durga'}
2) s # {0, 100, 'durga', 200, 10}
3) s[0] ==>TypeError: 'set' object does not support indexing
4)
5) set is growable in nature, based on our requirement we can increase or decrease the size.
6)
7) >>> s.add(60)
8) >>> s
9) {0, 100, 'durga', 200, 10, 60}
10) >>> s.remove(100)
11) >>> s
12) {0, 'durga', 200, 10, 60}
frozenset Data Type:
It is exactly same as set except that it is immutable.
Hence we cannot use add or remove functions.
1) >>> s={10,20,30,40}
2) >>> fs=frozenset(s)
3) >>> type(fs)
4) <class 'frozenset'>
5) >>> fs
6) frozenset({40, 10, 20, 30})
7) >>> for i in fs:print(i)
8) ...
9) 40
10) 10
11) 20
12) 30
13)
14) >>> fs.add(70)
15) AttributeError: 'frozenset' object has no attribute 'add'
16) >>> fs.remove(10)
17) AttributeError: 'frozenset' object has no attribute 'remove'

nd
dict Data Type:
If we want to represent a group of values as key-value pairs then we should go for dict
data type.
Eg:
d={101:'durga',102:'ravi',103:'shiva'}
Duplicate keys are not allowed but values can be duplicated. If we are trying to insert an
entry with duplicate key then old value will be replaced with new value.
Eg:
1. >>> d={101:'durga',102:'ravi',103:'shiva'}
2. >>> d[101]='sunny'
3. >>> d
4. {101: 'sunny', 102: 'ravi', 103: 'shiva'}
5.
6. We can create empty dictionary as follows
7. d={ }
8. We can add key-value pairs as follows
9. d['a']='apple'
10. d['b']='banana'
11. print(d)
Note: dict is mutable and the order wont be preserved.
Note:
1. In general we can use bytes and bytearray data types to represent binary information
like images,video files etc
2. In Python2 long data type is available. But in Python3 it is not available and we can
represent long values also by using int type only.
3. In Python there is no char data type. Hence we can represent char values also by using
str type.

nd
Summary of Datatypes in Python3
Datatype Description Is Immutable Example
Int We can use to represent the
whole/integral numbers
Immutable >>> a=10
>>> type(a)
<class 'int'>
Float We can use to represent the
decimal/floating point
numbers
Immutable >>> b=10.5
>>> type(b)
<class 'float'>
Complex We can use to represent the
complex numbers
Immutable >>> c=10+5j
>>> type(c)
<class 'complex'>
>>> c.real
10.0
>>> c.imag
5.0
Bool We can use to represent the
logical values(Only allowed
values are True and False)
Immutable >>> flag=True
>>> flag=False
>>> type(flag)
<class 'bool'>
Str To represent sequence of
Characters
Immutable >>> s='durga'
>>> type(s)
<class 'str'>
>>> s="durga"
>>> s='''Durga Software Solutions
... Ameerpet'''
>>> type(s)
<class 'str'>
bytes To represent a sequence of
byte values from 0-255
Immutable >>> list=[1,2,3,4]
>>> b=bytes(list)
>>> type(b)
<class 'bytes'>
bytearray To represent a sequence of
byte values from 0-255
Mutable >>> list=[10,20,30]
>>> ba=bytearray(list)
>>> type(ba)
<class 'bytearray'>
range To represent a range of
values
Immutable >>> r=range(10)
>>> r1=range(0,10)
>>> r2=range(0,10,2)
list To represent an ordered
collection of objects
Mutable >>> l=[10,11,12,13,14,15]
>>> type(l)
<class 'list'>
tuple To represent an ordered
collections of objects
Immutable >>> t=(1,2,3,4,5)
>>> type(t)
<class 'tuple'>
set To represent an unordered
collection of unique objects
Mutable >>> s={1,2,3,4,5,6}
>>> type(s)

nd
<class 'set'>
frozenset To represent an unordered
collection of unique objects
Immutable >>> s={11,2,3,'Durga',100,'Ramu'}
>>> fs=frozenset(s)
>>> type(fs)
<class 'frozenset'>
dict To represent a group of key
value pairs
Mutable >>>
d={101:'durga',102:'ramu',103:'hari'}
>>> type(d)
<class 'dict'>
None Data Type:
None means Nothing or No value associated.
If the value is not available,then to handle such type of cases None introduced.
It is something like null value in Java.
Eg:
def m1():
a=10
print(m1())
None
Escape Characters:
In String literals we can use esacpe characters to associate a special meaning.
1) >>> s="durgansoftware"
2) >>> print(s)
3) durga
4) software
5) >>> s="durgatsoftware"
6) >>> print(s)
7) durga software
8) >>> s="This is " symbol"
9) File "<stdin>", line 1
10) s="This is " symbol"
11) ^
13) >>> s="This is " symbol"
14) >>> print(s)
15) This is " symbol

nd
The following are various important escape characters in Python
1) n==>New Line
2) t===>Horizontal tab
3) r ==>Carriage Return
4) b===>Back space
5) f===>Form Feed
6) v==>Vertical tab
7) '===>Single quote
8) "===>Double quote
9) ===>back slash symbol
....
Constants:
Constants concept is not applicable in Python.
But it is convention to use only uppercase characters if we don’t want to change value.
MAX_VALUE=10
It is just convention but we can change the value.

nd
Operators
Operator is a symbol that performs certain operations.
Python provides the following set of operators
1. Arithmetic Operators
2. Relational Operators or Comparison Operators
3. Logical operators
4. Bitwise oeprators
5. Assignment operators
6. Special operators
1. Arithmetic Operators:
+ ==>Addition
- ==>Subtraction
* ==>Multiplication
/ ==>Division operator
% ===>Modulo operator
// ==>Floor Division operator
** ==>Exponent operator or power operator
Eg: test.py:
1) a=10
2) b=2
3) print('a+b=',a+b)
4) print('a-b=',a-b)
5) print('a*b=',a*b)
6) print('a/b=',a/b)
7) print('a//b=',a//b)
8) print('a%b=',a%b)
9) print('a**b=',a**b)

nd
Output:
1) Python test.py or py test.py
2) a+b= 12
3) a-b= 8
4) a*b= 20
5) a/b= 5.0
6) a//b= 5
7) a%b= 0
8) a**b= 100
Eg:
1) a = 10.5
2) b=2
3)
4) a+b= 12.5
5) a-b= 8.5
6) a*b= 21.0
7) a/b= 5.25
8) a//b= 5.0
9) a%b= 0.5
10) a**b= 110.25
Eg:
10/2==>5.0
10//2==>5
10.0/2===>5.0
10.0//2===>5.0
Note: / operator always performs floating point arithmetic. Hence it will always returns
float value.
But Floor division (//) can perform both floating point and integral arithmetic. If
arguments are int type then result is int type. If atleast one argument is float type then
result is float type.
Note:
We can use +,* operators for str type also.
If we want to use + operator for str type then compulsory both arguments should be str
type only otherwise we will get error.
1) >>> "durga"+10
2) TypeError: must be str, not int
3) >>> "durga"+"10"
4) 'durga10'

nd
If we use * operator for str type then compulsory one argument should be int and other
argument should be str type.
2*"durga"
"durga"*2
2.5*"durga" ==>TypeError: can't multiply sequence by non-int of type 'float'
"durga"*"durga"==>TypeError: can't multiply sequence by non-int of type 'str'
+====>String concatenation operator
* ===>String multiplication operator
Note: For any number x,
x/0 and x%0 always raises "ZeroDivisionError"
10/0
10.0/0
.....
Relational Operators:
>,>=,<,<=
Eg 1:
1) a=10
2) b=20
3) print("a > b is ",a>b)
4) print("a >= b is ",a>=b)
5) print("a b is False
9) a >= b is False
10) a b is ",a>b)
4) print("a >= b is ",a>=b)
5) print("a < b is ",a<b)

nd
6) print("a <= b is ",a<=b)
7)
8) a > b is False
9) a >= b is True
10) a True) False
2) print(True>=True) True
3) print(10 >True) True
4) print(False > True) False
5)
6) print(10>'durga')
7) TypeError: '>' not supported between instances of 'int' and 'str'
Eg:
1) a=10
2) b=20
3) if(a>b):
4) print("a is greater than b")
5) else:
6) print("a is not greater than b")
Outputa is not greater than b
Note: Chaining of relational operators is possible. In the chaining, if all comparisons
returns True then only result is True. If atleast one comparison returns False then the
result is False
Eg:
1) 10<20 ==>True
2) 10<20<30 ==>True
3) 10<20<30<40 ==>True
4) 10<20<30<40>50 ==>False
equality operators:
== , !=
We can apply these operators for any type even for incompatible types also
1) >>> 10==20
2) False
3) >>> 10!= 20

nd
4) True
5) >>> 10==True
6) False
7) >>> False==False
8) True
9) >>> "durga"=="durga"
10) True
11) >>> 10=="durga"
12) False
Note: Chaining concept is applicable for equality operators. If atleast one comparison
returns False then the result is False. otherwise the result is True.
Eg:
1) >>> 10==20==30==40
2) False
3) >>> 10==10==10==10
4) True
Logical Operators:
and, or ,not
We can apply for all types.
For boolean types behaviour:
and ==>If both arguments are True then only result is True
or ====>If atleast one arugemnt is True then result is True
not ==>complement
True and False ==>False
True or False ===>True
not False ==>True
For non-boolean types behaviour:
0 means False
non-zero means True
empty string is always treated as False
x and y:
==>if x is evaluates to false return x otherwise return y

nd
Eg:
10 and 20
0 and 20
If first argument is zero then result is zero otherwise result is y
x or y:
If x evaluates to True then result is x otherwise result is y
10 or 20 ==> 10
0 or 20 ==> 20
not x:
If x is evalutates to False then result is True otherwise False
not 10 ==>False
not 0 ==>True
Eg:
1) "durga" and "durgasoft" ==>durgasoft
2) "" and "durga" ==>""
3) "durga" and "" ==>""
4) "" or "durga" ==>"durga"
5) "durga" or ""==>"durga"
6) not ""==>True
7) not "durga" ==>False
Bitwise Operators:
We can apply these operators bitwise.
These operators are applicable only for int and boolean types.
By mistake if we are trying to apply for any other type then we will get Error.
&,|,^,~,<<,>>
print(4&5) ==>valid
print(10.5 & 5.6) ==>
TypeError: unsupported operand type(s) for &: 'float' and 'float'
print(True & True) ==>valid

nd
& ==> If both bits are 1 then only result is 1 otherwise result is 0
| ==> If atleast one bit is 1 then result is 1 otherwise result is 0
^ ==>If bits are different then only result is 1 otherwise result is 0
~ ==>bitwise complement operator
1==>0 & 0==>1
<< ==>Bitwise Left shift
>> ==>Bitwise Right Shift
print(4&5) ==>4
print(4|5) ==>5
print(4^5) ==>1
Operator Description
& If both bits are 1 then only result is 1 otherwise result is 0
| If atleast one bit is 1 then result is 1 otherwise result is 0
^ If bits are different then only result is 1 otherwise result is 0
~ bitwise complement operator i.e 1 means 0 and 0 means 1
>> Bitwise Left shift Operator
<< Bitwise Right shift Operator
bitwise complement operator(~):
We have to apply complement for total bits.
Eg: print(~5) ==>-6
Note:
The most significant bit acts as sign bit. 0 value represents +ve number where as 1
represents -ve value.
positive numbers will be repesented directly in the memory where as -ve numbers will be
represented indirectly in 2's complement form.
Shift Operators:
<< Left shift operator
After shifting the empty cells we have to fill with zero
print(10<<2)==>40
0 0 0 0 1 0 1 0
0 0 1 0 1 0 0 0

nd
>> Right Shift operator
After shifting the empty cells we have to fill with sign bit.( 0 for +ve and 1 for -ve)
print(10>>2) ==>2
We can apply bitwise operators for boolean types also
print(True & False) ==>False
print(True | False) ===>True
print(True ^ False) ==>True
print(~True) ==>-2
print(True<<2) ==>4
print(True>>2) ==>0
Assignment Operators:
We can use assignment operator to assign value to the variable.
Eg:
x=10
We can combine asignment operator with some other operator to form compound
assignment operator.
Eg: x+=10 ====> x = x+10
The following is the list of all possible compound assignment operators in Python
+=
-=
*=
/=
%=
//=
**=
&=
|=
^=
0 0 0 0 1 0 1 0
0 0 0 0 0 0 1 0

nd
>>=
<<=
Eg:
1) x=10
2) x+=20
3) print(x) ==>30
Eg:
1) x=10
2) x&=5
3) print(x) ==>0
Ternary Operator:
Syntax:
x = firstValue if condition else secondValue
If condition is True then firstValue will be considered else secondValue will be considered.
Eg 1:
1) a,b=10,20
2) x=30 if a<b else 40
3) print(x) #30
Eg 2: Read two numbers from the keyboard and print minimum value
1) a=int(input("Enter First Number:"))
2) b=int(input("Enter Second Number:"))
3) min=a if a<b else b
4) print("Minimum Value:",min)
Output:
Enter First Number:10
Enter Second Number:30
Minimum Value: 10
Note: Nesting of ternary operator is possible.

nd
Q. Program for minimum of 3 numbers
3) c=int(input("Enter Third Number:"))
4) min=a if ab and a>c else b if b>c else c
5) print("Maximum Value:",max)
Eg:
3) print("Both numbers are equal" if a==b else "First Number is Less than Second Number" if
apy test.py
Both numbers are equal
First Number is Less than Second Number
First Number Greater than Second Number

nd
Special operators:
Python defines the following 2 special operators
1. Identity Operators
2. Membership operators
1. Identity Operators
We can use identity operators for address comparison.
2 identity operators are available
1. is
2. is not
r1 is r2 returns True if both r1 and r2 are pointing to the same object
r1 is not r2 returns True if both r1 and r2 are not pointing to the same object
Eg:
1) a=10
2) b=10
3) print(a is b) True
4) x=True
5) y=True
6) print( x is y) True
Eg:
1) a="durga"
2) b="durga"
3) print(id(a))
4) print(id(b))
5) print(a is b)
Eg:
1) list1=["one","two","three"]
2) list2=["one","two","three"]
3) print(id(list1))
4) print(id(list2))
5) print(list1 is list2) False
6) print(list1 is not list2) True
7) print(list1 == list2) True

nd
Note:
We can use is operator for address comparison where as == operator for content
comparison.
2. Membership operators:
We can use Membership operators to check whether the given object present in the
given collection.(It may be String,List,Set,Tuple or Dict)
in  Returns True if the given object present in the specified Collection
not in  Retruns True if the given object not present in the specified Collection
Eg:
1) x="hello learning Python is very easy!!!"
2) print('h' in x) True
3) print('d' in x) False
4) print('d' not in x) True
5) print('Python' in x) True
Eg:
1) list1=["sunny","bunny","chinny","pinny"]
2) print("sunny" in list1) True
3) print("tunny" in list1) False
4) print("tunny" not in list1) True
Operator Precedence:
If multiple operators present then which operator will be evaluated first is decided by
operator precedence.
Eg:
print(3+10*2)  23
print((3+10)*2)  26
The following list describes operator precedence in Python
()  Parenthesis
**  exponential operator
~,-  Bitwise complement operator,unary minus operator
*,/,%,//  multiplication,division,modulo,floor division
+,-  addition,subtraction
<<,>>  Left and Right Shift
&  bitwise And

nd
^  Bitwise X-OR
|  Bitwise OR
>,>=,<,<=, ==, != ==>Relational or Comparison operators
=,+=,-=,*=... ==>Assignment operators
is , is not  Identity Operators
in , not in  Membership operators
not  Logical not
and  Logical and
or  Logical or
Eg:
1) a=30
2) b=20
3) c=10
4) d=5
5) print((a+b)*c/d) 100.0
6) print((a+b)*(c/d)) 100.0
7) print(a+(b*c)/d) 70.0
8)
9)
10) 3/2*4+3+(10/5)**3-2
11) 3/2*4+3+2.0**3-2
12) 3/2*4+3+8.0-2
13) 1.5*4+3+8.0-2
14) 6.0+3+8.0-2
15) 15.0

nd
Mathematical Functions (math Module)
A Module is collection of functions, variables and classes etc.
math is a module that contains several functions to perform mathematical operations
If we want to use any module in Python, first we have to import that module.
import math
Once we import a module then we can call any function of that module.
import math
print(math.sqrt(16))
print(math.pi)
4.0
3.141592653589793
We can create alias name by using as keyword.
import math as m
Once we create alias name, by using that we can access functions and variables of that
module
import math as m
print(m.sqrt(16))
print(m.pi)
We can import a particular member of a module explicitly as follows
from math import sqrt
from math import sqrt,pi
If we import a member explicitly then it is not required to use module name while
accessing.
from math import sqrt,pi
print(sqrt(16))
print(pi)
print(math.pi)  NameError: name 'math' is not defined

nd
important functions of math module:
ceil(x)
floor(x)
pow(x,y)
factorial(x)
trunc(x)
gcd(x,y)
sin(x)
cos(x)
tan(x)
....
important variables of math module:
pi3.14
e===>2.71
inf ==>infinity
nan ==>not a number
Q. Write a Python program to find area of circle
pi*r**2
from math import pi
r=16
print("Area of Circle is :",pi*r**2)
OutputArea of Circle is : 804.247719318987

nd
Input And Output Statements
Reading dynamic input from the keyboard:
In Python 2 the following 2 functions are available to read dynamic input from the
keyboard.
1. raw_input()
2. input()
1. raw_input():
This function always reads the data from the keyboard in the form of String Format. We
have to convert that string type to our required type by using the corresponding type
casting methods.
Eg:
x=raw_input("Enter First Number:")
print(type(x)) It will always print str type only for any input type
2. input():
input() function can be used to read data directly in our required format.We are not
required to perform type casting.
x=input("Enter Value)
type(x)
10 ===> int
"durga"===>str
10.5===>float
True==>bool
***Note: But in Python 3 we have only input() method and raw_input() method is not
available.
Python3 input() function behaviour exactly same as raw_input() method of Python2. i.e
every input value is treated as str type only.
raw_input() function of Python 2 is renamed as input() function in Python3

nd
Eg:
1) >>> type(input("Enter value:"))
2) Enter value:10
3) <class 'str'>
4)
5) Enter value:10.5
6) <class 'str'>
7)
8) Enter value:True
9) <class 'str'>
Q. Write a program to read 2 numbers from the keyboard and print sum.
1) x=input("Enter First Number:")
2) y=input("Enter Second Number:")
3) i = int(x)
4) j = int(y)
5) print("The Sum:",i+j)
6)
7) Enter First Number:100
8) Enter Second Number:200
9) The Sum: 300
-----------------------------------------------------
1) x=int(input("Enter First Number:"))
2) y=int(input("Enter Second Number:"))
3) print("The Sum:",x+y)
-----------------------------------------------------------
1) print("The Sum:",int(input("Enter First Number:"))+int(input("Enter Second Number:")))
Q. Write a program to read Employee data from the keyboard and print that data.
1) eno=int(input("Enter Employee No:"))
2) ename=input("Enter Employee Name:")
3) esal=float(input("Enter Employee Salary:"))
4) eaddr=input("Enter Employee Address:")
5) married=bool(input("Employee Married ?[True|False]:"))
6) print("Please Confirm Information")
7) print("Employee No :",eno)
8) print("Employee Name :",ename)
9) print("Employee Salary :",esal)
10) print("Employee Address :",eaddr)
11) print("Employee Married ? :",married)
12)

nd
13) D:Python_classes>py test.py
14) Enter Employee No:100
15) Enter Employee Name:Sunny
16) Enter Employee Salary:1000
17) Enter Employee Address:Mumbai
18) Employee Married ?[True|False]:True
19) Please Confirm Information
20) Employee No : 100
21) Employee Name : Sunny
22) Employee Salary : 1000.0
23) Employee Address : Mumbai
24) Employee Married ? : True
How to read multiple values from the keyboard in a single line:
1) a,b= [int(x) for x in input("Enter 2 numbers :").split()]
2) print("Product is :", a*b)
3)
5) Enter 2 numbers :10 20
6) Product is : 200
Note: split() function can take space as seperator by default .But we can pass
anything as seperator.
Q. Write a program to read 3 float numbers from the keyboard with , seperator and print
their sum.
1) a,b,c= [float(x) for x in input("Enter 3 float numbers :").split(',')]
2) print("The Sum is :", a+b+c)
3)
5) Enter 3 float numbers :10.5,20.6,20.1
6) The Sum is : 51.2
eval():
eval Function take a String and evaluate the Result.
Eg: x = eval(“10+20+30”)
print(x)
Output: 60
Eg: x = eval(input(“Enter Expression”))
Enter Expression: 10+2*3/4
Output11.5

nd
eval() can evaluate the Input to list, tuple, set, etc based the provided Input.
Eg: Write a Program to accept list from the keynboard on the display
1) l = eval(input(“Enter List”))
2) print (type(l))
3) print(l)
Command Line Arguments
 argv is not Array it is a List. It is available sys Module.
 The Argument which are passing at the time of execution are called Command Line
Arguments.
Eg: D:Python_classes py test.py 10 20 30
Command Line Arguments
Within the Python Program this Command Line Arguments are available in argv. Which is
present in SYS Module.
Note: argv[0] represents Name of Program. But not first Command Line Argument.
argv[1] represent First Command Line Argument.
Program: To check type of argv from sys
import argv
print(type(argv))
D:Python_classespy test.py
Write a Program to display Command Line Arguments
1) from sys import argv
2) print(“The Number of Command Line Arguments:”, len(argv))
3) print(“The List of Command Line Arguments:”, argv)
4) print(“Command Line Arguments one by one:”)
5) for x in argv:
6) print(x)
7)
8) D:Python_classes>py test.py 10 20 30
9) The Number of Command Line Arguments: 4
test.py 10 20 30

nd
10) The List of Command Line Arguments: [‘test.py’, ‘10’,’20’,’30’]
11) Command Line Arguments one by one:
12) test.py
13) 10
14) 20
15) 30
2) sum=0
3) args=argv[1:]
4) for x in args :
5) n=int(x)
6) sum=sum+n
7) print("The Sum:",sum)
8)
9) D:Python_classes>py test.py 10 20 30 40
10) The Sum: 100
Note1: usually space is seperator between command line arguments. If our command line
argument itself contains space then we should enclose within double quotes(but not
single quotes)
Eg:
2) print(argv[1])
3)
4) D:Python_classes>py test.py Sunny Leone
5) Sunny
6)
7) D:Python_classes>py test.py 'Sunny Leone'
8) 'Sunny
9)
10) D:Python_classes>py test.py "Sunny Leone"
11) Sunny Leone
Note2: Within the Python program command line arguments are available in the String
form. Based on our requirement,we can convert into corresponding type by using type
casting methods.
Eg:
2) print(argv[1]+argv[2])
3) print(int(argv[1])+int(argv[2]))

nd
4)
5) D:Python_classes>py test.py 10 20
6) 1020
7) 30
Note3: If we are trying to access command line arguments with out of range index then
we will get Error.
Eg:
2) print(argv[100])
3)
4) D:Python_classes>py test.py 10 20
5) IndexError: list index out of range
Note:
In Python there is argparse module to parse command line arguments and display some
help messages whenever end user enters wrong input.
input()
raw_input()
command line arguments
output statements:
We can use print() function to display output.
Form-1: print() without any argument
Just it prints new line character
Form-2:
1) print(String):
2) print("Hello World")
3) We can use escape characters also
4) print("Hello n World")
5) print("HellotWorld")
6) We can use repetetion operator (*) in the string
7) print(10*"Hello")
8) print("Hello"*10)
9) We can use + operator also
10) print("Hello"+"World")

nd
Note:
If both arguments are String type then + operator acts as concatenation operator.
If one argument is string type and second is any other type like int then we will get Error
If both arguments are number type then + operator acts as arithmetic addition operator.
Note:
1) print("Hello"+"World")
2) print("Hello","World")
3)
4) HelloWorld
5) Hello World
Form-3: print() with variable number of arguments:
1. a,b,c=10,20,30
2. print("The Values are :",a,b,c)
3.
4. OutputThe Values are : 10 20 30
By default output values are seperated by space.If we want we can specify seperator by
using "sep" attribute
1. a,b,c=10,20,30
2. print(a,b,c,sep=',')
3. print(a,b,c,sep=':')
4.
5. D:Python_classes>py test.py
6. 10,20,30
7. 10:20:30
Form-4:print() with end attribute:
1. print("Hello")
2. print("Durga")
3. print("Soft")
Output:
1. Hello
2. Durga
3. Soft
If we want output in the same line with space

nd
1. print("Hello",end=' ')
2. print("Durga",end=' ')
3. print("Soft")
Output: Hello Durga Soft
Note: The default value for end attribute is n,which is nothing but new line character.
Form-5: print(object) statement:
We can pass any object (like list,tuple,set etc)as argument to the print() statement.
Eg:
1. l=[10,20,30,40]
2. t=(10,20,30,40)
3. print(l)
4. print(t)
Form-6: print(String,variable list):
We can use print() statement with String and any number of arguments.
Eg:
1. s="Durga"
2. a=48
3. s1="java"
4. s2="Python"
5. print("Hello",s,"Your Age is",a)
6. print("You are teaching",s1,"and",s2)
Output:
1) Hello Durga Your Age is 48
2) You are teaching java and Python
Form-7: print(formatted string):
%i====>int
%d====>int
%f=====>float
%s======>String type

nd
Syntax:
print("formatted string" %(variable list))
Eg 1:
1) a=10
2) b=20
3) c=30
4) print("a value is %i" %a)
5) print("b value is %d and c value is %d" %(b,c))
6)
7) Output
8) a value is 10
9) b value is 20 and c value is 30
Eg 2:
1) s="Durga"
2) list=[10,20,30,40]
3) print("Hello %s ...The List of Items are %s" %(s,list))
4)
5) Output Hello Durga ...The List of Items are [10, 20, 30, 40]
Form-8: print() with replacement operator {}
Eg:
1) name="Durga"
2) salary=10000
3) gf="Sunny"
4) print("Hello {0} your salary is {1} and Your Friend {2} is waiting".format(name,salary,gf))
5) print("Hello {x} your salary is {y} and Your Friend {z} is waiting".format(x=name,y=salary,z=
gf))
6)
7) Output
8) Hello Durga your salary is 10000 and Your Friend Sunny is waiting
9) Hello Durga your salary is 10000 and Your Friend Sunny is waiting

nd
Flow Control
Flow control describes the order in which statements will be executed at runtime.
I. Conditional Statements
1) if
if condition : statement
or
if condition :
statement-1
statement-2
statement-3
If condition is true then statements will be executed.
Control Flow
Conditional
Statements
Transfer
Statements
Iterative
Statements
1) if
2) if-elif
3) if-elif-else
1) break
2) continue
3) pass
1) for
2) while

nd
Eg:
1) name=input("Enter Name:")
2) if name=="durga" :
3) print("Hello Durga Good Morning")
4) print("How are you!!!")
5)
7) Enter Name:durga
8) Hello Durga Good Morning
9) How are you!!!
10)
12) Enter Name:Ravi
13) How are you!!!
2) if-else:
if condition :
Action-1
else :
Action-2
if condition is true then Action-1 will be executed otherwise Action-2 will be executed.
Eg:
2) if name=="durga" :
3) print("Hello Durga Good Morning")
4) else:
5) print("Hello Guest Good Moring")
6) print("How are you!!!")
7)
9) Enter Name:durga
11) How are you!!!
12)
14) Enter Name:Ravi
15) Hello Guest Good Moring
16) How are you!!!

nd
3) if-elif-else:
Syntax:
if condition1:
Action-1
elif condition2:
Action-2
elif condition3:
Action-3
elif condition4:
Action-4
...
else:
Default Action
Based condition the corresponding action will be executed.
Eg:
1) brand=input("Enter Your Favourite Brand:")
2) if brand=="RC" :
3) print("It is childrens brand")
4) elif brand=="KF":
5) print("It is not that much kick")
6) elif brand=="FO":
7) print("Buy one get Free One")
8) else :
9) print("Other Brands are not recommended")
10)
11)
13) Enter Your Favourite Brand:RC
14) It is childrens brand
15)
17) Enter Your Favourite Brand:KF
18) It is not that much kick
19)
21) Enter Your Favourite Brand:KALYANI
22) Other Brands are not recommended

nd
Note:
1. else part is always optional
Hence the following are various possible syntaxes.
1. if
2. if - else
3. if-elif-else
4.if-elif
2. There is no switch statement in Python
Q. Write a program to find biggest of given 2 numbers from the commad prompt?
1) n1=int(input("Enter First Number:"))
2) n2=int(input("Enter Second Number:"))
3) if n1>n2:
4) print("Biggest Number is:",n1)
5) else :
7)
11) Biggest Number is: 20
Q. Write a program to find biggest of given 3 numbers from the commad prompt?
1) n1=int(input("Enter First Number:"))
2) n2=int(input("Enter Second Number:"))
3) n3=int(input("Enter Third Number:"))
4) if n1>n2 and n1>n3:
6) elif n2>n3:
8) else :
10)
14) Enter Third Number:30
16)

nd
20) Enter Third Number:20
Q. Write a program to find smallest of given 2 numbers?
Q. Write a program to find smallest of given 3 numbers?
Q. Write a program to check whether the given number is even or odd?
Q. Write a program to check whether the given number is in between 1 and 100?
1) n=int(input("Enter Number:"))
2) if n>=1 and n<=10 :
3) print("The number",n,"is in between 1 to 10")
4) else:
5) print("The number",n,"is not in between 1 to 10")
Q. Write a program to take a single digit number from the key board and print is value in
English word?
1) 0==>ZERO
2) 1 ==>ONE
3)
4) n=int(input("Enter a digit from o to 9:"))
5) if n==0 :
6) print("ZERO")
7) elif n==1:
8) print("ONE")
9) elif n==2:
10) print("TWO")
11) elif n==3:
12) print("THREE")
13) elif n==4:
14) print("FOUR")
15) elif n==5:
16) print("FIVE")
17) elif n==6:
18) print("SIX")
19) elif n==7:
20) print("SEVEN")
21) elif n==8:
22) print("EIGHT")
23) elif n==9:
24) print("NINE")
25) else:
26) print("PLEASE ENTER A DIGIT FROM 0 TO 9")

nd
II. Iterative Statements
If we want to execute a group of statements multiple times then we should go for
Iterative statements.
Python supports 2 types of iterative statements.
1. for loop
2. while loop
1) for loop:
If we want to execute some action for every element present in some sequence(it may be
string or collection)then we should go for for loop.
Syntax:
for x in sequence :
body
where sequence can be string or any collection.
Body will be executed for every element present in the sequence.
Eg 1: To print characters present in the given string
1) s="Sunny Leone"
2) for x in s :
3) print(x)
4)
5) Output
6) S
7) u
8) n
9) n
10) y
11)
12) L
13) e
14) o
15) n
16) e

nd
Eg 2: To print characters present in string index wise:
1) s=input("Enter some String: ")
2) i=0
3) for x in s :
4) print("The character present at ",i,"index is :",x)
5) i=i+1
6)
7)
9) Enter some String: Sunny Leone
10) The character present at 0 index is : S
11) The character present at 1 index is : u
12) The character present at 2 index is : n
14) The character present at 4 index is : y
15) The character present at 5 index is :
16) The character present at 6 index is : L
17) The character present at 7 index is : e
18) The character present at 8 index is : o
20) The character present at 10 index is : e
Eg 3: To print Hello 10 times
1) for x in range(10) :
2) print("Hello")
Eg 4: To display numbers from 0 to 10
2) print(x)
Eg 5: To display odd numbers from 0 to 20
2) if (x%2!=0):
3) print(x)
Eg 6: To display numbers from 10 to 1 in descending order
1) for x in range(10,0,-1) :
2) print(x)

nd
Eg 7: To print sum of numbers presenst inside list
1) list=eval(input("Enter List:"))
2) sum=0;
3) for x in list:
4) sum=sum+x;
5) print("The Sum=",sum)
6)
8) Enter List:[10,20,30,40]
9) The Sum= 100
10)
12) Enter List:[45,67]
13) The Sum= 112
2) while loop:
If we want to execute a group of statements iteratively until some condition false,then we
should go for while loop.
Syntax:
while condition :
body
Eg: To print numbers from 1 to 10 by using while loop
1) x=1
2) while x <=10:
3) print(x)
4) x=x+1
Eg: To display the sum of first n numbers
1) n=int(input("Enter number:"))
2) sum=0
3) i=1
4) while i<=n:
5) sum=sum+i
6) i=i+1
7) print("The sum of first",n,"numbers is :",sum)

nd
Eg: write a program to prompt user to enter some name until entering Durga
1) name=""
2) while name!="durga":
4) print("Thanks for confirmation")
Infinite Loops:
1) i=0;
2) while True :
3) i=i+1;
4) print("Hello",i)
Nested Loops:
Sometimes we can take a loop inside another loop,which are also known as nested loops.
Eg:
1) for i in range(4):
2) for j in range(4):
3) print("i=",i," j=",j)
4)
5) Output
7) i= 0 j= 0
8) i= 0 j= 1
9) i= 0 j= 2
10) i= 0 j= 3
11) i= 1 j= 0
12) i= 1 j= 1
13) i= 1 j= 2
14) i= 1 j= 3
15) i= 2 j= 0
16) i= 2 j= 1
17) i= 2 j= 2
18) i= 2 j= 3
19) i= 3 j= 0
20) i= 3 j= 1
21) i= 3 j= 2
22) i= 3 j= 3

nd
Q. Write a program to dispaly *'s in Right angled triangled form
1) *
2) * *
3) * * *
4) * * * *
5) * * * * *
6) * * * * * *
7) * * * * * * *
8)
9) n = int(input("Enter number of rows:"))
10) for i in range(1,n+1):
11) for j in range(1,i+1):
12) print("*",end=" ")
13) print()
Alternative way:
3) print("* " * i)
Q. Write a program to display *'s in pyramid style(also known as equivalent triangle)
1) *
2) * *
3) * * *
4) * * * *
5) * * * * *
6) * * * * * *
7) * * * * * * *
8)
11) print(" " * (n-i),end="")
12) print("* "*i)

nd
III. Transfer Statements
1) break:
We can use break statement inside loops to break loop execution based on some
condition.
Eg:
2) if i==7:
3) print("processing is enough..plz break")
4) break
5) print(i)
6)
8) 0
9) 1
10) 2
11) 3
12) 4
13) 5
14) 6
15) processing is enough..plz break
Eg:
1) cart=[10,20,600,60,70]
2) for item in cart:
3) if item>500:
4) print("To place this order insurence must be required")
5) break
6) print(item)
7)
9) 10
10) 20
11) To place this order insurence must be required

nd
2) continue:
We can use continue statement to skip current iteration and continue next iteration.
Eg 1: To print odd numbers in the range 0 to 9
2) if i%2==0:
3) continue
4) print(i)
5)
7) 1
8) 3
9) 5
10) 7
11) 9
Eg 2:
1) cart=[10,20,500,700,50,60]
3) if item>=500:
4) print("We cannot process this item :",item)
5) continue
6) print(item)
7)
8) Output
10) 10
11) 20
12) We cannot process this item : 500
13) We cannot process this item : 700
14) 50
15) 60
Eg 3:
1) numbers=[10,20,0,5,0,30]
2) for n in numbers:
3) if n==0:
4) print("Hey how we can divide with zero..just skipping")
5) continue
6) print("100/{} = {}".format(n,100/n))
7)

nd
8) Output
9)
10) 100/10 = 10.0
11) 100/20 = 5.0
12) Hey how we can divide with zero..just skipping
13) 100/5 = 20.0
14) Hey how we can divide with zero..just skipping
15) 100/30 = 3.3333333333333335
loops with else block:
Inside loop execution,if break statement not executed ,then only else part will be
executed.
else means loop without break
Eg:
1) cart=[10,20,30,40,50]
3) if item>=500:
4) print("We cannot process this order")
5) break
6) print(item)
7) else:
8) print("Congrats ...all items processed successfully")
9)
10) Output
11) 10
12) 20
13) 30
14) 40
15) 50
16) Congrats ...all items processed successfully
Eg:
1) cart=[10,20,600,30,40,50]
3) if item>=500:
4) print("We cannot process this order")
5) break
6) print(item)
7) else:
8) print("Congrats ...all items processed successfully")

nd
9)
10) Output
12) 10
13) 20
14) We cannot process this order
Q. What is the difference between for loop and while loop in Python?
We can use loops to repeat code execution
Repeat code for every item in sequence ==>for loop
Repeat code as long as condition is true ==>while loop
Q. How to exit from the loop?
by using break statement
Q. How to skip some iterations inside loop?
by using continue statement.
Q. When else part will be executed wrt loops?
If loop executed without break
3) pass statement:
pass is a keyword in Python.
In our programming syntactically if block is required which won't do anything then we can
define that empty block with pass keyword.
pass
|- It is an empty statement
|- It is null statement
|- It won't do anything
Eg:
if True:
SyntaxError: unexpected EOF while parsing
if True: pass
==>valid
def m1():
SyntaxError: unexpected EOF while parsing

nd
def m1(): pass
use case of pass:
Sometimes in the parent class we have to declare a function with empty body and child
class responsible to provide proper implementation. Such type of empty body we can
define by using pass keyword. (It is something like abstract method in java)
Eg:
def m1(): pass
Eg:
2) if i%9==0:
3) print(i)
4) else:pass
5)
7) 0
8) 9
9) 18
10) 27
11) 36
12) 45
13) 54
14) 63
15) 72
16) 81
17) 90
18) 99
del statement:
del is a keyword in Python.
After using a variable, it is highly recommended to delete that variable if it is no longer
required,so that the corresponding object is eligible for Garbage Collection.
We can delete variable by using del keyword.
Eg:
1) x=10
2) print(x)
3) del x

nd
After deleting a variable we cannot access that variable otherwise we will get NameError.
Eg:
1) x=10
2) del x
3) print(x)
NameError: name 'x' is not defined.
Note:
We can delete variables which are pointing to immutable objects.But we cannot delete
the elements present inside immutable object.
Eg:
1) s="durga"
2) print(s)
3) del s==>valid
4) del s[0] ==>TypeError: 'str' object doesn't support item deletion
Difference between del and None:
In the case del, the variable will be removed and we cannot access that variable(unbind
operation)
1) s="durga"
2) del s
3) print(s) ==>NameError: name 's' is not defined.
But in the case of None assignment the variable won't be removed but the corresponding
object is eligible for Garbage Collection(re bind operation). Hence after assigning with
None value,we can access that variable.
1) s="durga"
2) s=None
3) print(s) # None

nd
String Data Type
The most commonly used object in any project and in any programming language is String only.
Hence we should aware complete information about String data type.
What is String?
Any sequence of characters within either single quotes or double quotes is considered as a String.
Syntax:
s='durga'
s="durga"
Note: In most of other languges like C, C++,Java, a single character with in single quotes is treated
as char data type value. But in Python we are not having char data type.Hence it is treated as
String only.
Eg:
>>> ch='a'
>>> type(ch)
<class 'str'>
How to define multi-line String literals:
We can define multi-line String literals by using triple single or double quotes.
Eg:
>>> s='''durga
software
solutions'''
We can also use triple quotes to use single quotes or double quotes as symbol inside String literal.
Eg:
s='This is ' single quote symbol' ==>invalid
s='This is ' single quote symbol' ==>valid
s="This is ' single quote symbol"====>valid
s='This is " double quotes symbol' ==>valid
s='The "Python Notes" by 'durga' is very helpful' ==>invalid
s="The "Python Notes" by 'durga' is very helpful"==>invalid
s='The "Python Notes" by 'durga' is very helpful' ==>valid
s='''The "Python Notes" by 'durga' is very helpful''' ==>valid

nd
How to access characters of a String:
We can access characters of a string by using the following ways.
1. By using index
2. By using slice operator
1. By using index:
Python supports both +ve and -ve index.
+ve index means left to right(Forward direction)
-ve index means right to left(Backward direction)
Eg:
s='durga'
diagram
Eg:
>>> s='durga'
>>> s[0]
'd'
>>> s[4]
'a'
>>> s[-1]
'a'
>>> s[10]
IndexError: string index out of range
Note: If we are trying to access characters of a string with out of range index then we will get
error saying : IndexError
Q. Write a program to accept some string from the keyboard and display its characters by
index wise(both positive and nEgative index)
test.py:
1) s=input("Enter Some String:")
2) i=0
3) for x in s:
4) print("The character present at positive index {} and at nEgative index {} is {}".format(i,i
-len(s),x))
5) i=i+1
Output:
Enter Some String:durga

nd
The character present at positive index 0 and at nEgative index -5 is d
The character present at positive index 1 and at nEgative index -4 is u
The character present at positive index 2 and at nEgative index -3 is r
The character present at positive index 3 and at nEgative index -2 is g
The character present at positive index 4 and at nEgative index -1 is a
2. Accessing characters by using slice operator:
Syntax: s[bEginindex:endindex:step]
bEginindex:From where we have to consider slice(substring)
endindex: We have to terminate the slice(substring) at endindex-1
step: incremented value
Note: If we are not specifying bEgin index then it will consider from bEginning of the string.
If we are not specifying end index then it will consider up to end of the string
The default value for step is 1
Eg:
1) >>> s="Learning Python is very very easy!!!"
2) >>> s[1:7:1]
3) 'earnin'
4) >>> s[1:7]
5) 'earnin'
6) >>> s[1:7:2]
7) 'eri'
8) >>> s[:7]
9) 'Learnin'
10) >>> s[7:]
11) 'g Python is very very easy!!!'
12) >>> s[::]
13) 'Learning Python is very very easy!!!'
14) >>> s[:]
15) 'Learning Python is very very easy!!!'
16) >>> s[::-1]
17) '!!!ysae yrev yrev si nohtyP gninraeL'
Behaviour of slice operator:
s[bEgin:end:step]
step value can be either +ve or –ve
if +ve then it should be forward direction(left to right) and we have to consider bEgin to end-1
if -ve then it should be backward direction(right to left) and we have to consider bEgin to end+1

nd
***Note:
In the backward direction if end value is -1 then result is always empty.
In the forward direction if end value is 0 then result is always empty.
In forward direction:
default value for bEgin: 0
default value for end: length of string
default value for step: +1
In backward direction:
default value for bEgin: -1
default value for end: -(length of string+1)
Note: Either forward or backward direction, we can take both +ve and -ve values for bEgin and
end index.
Mathematical Operators for String:
We can apply the following mathematical operators for Strings.
1. + operator for concatenation
2. * operator for repetition
print("durga"+"soft") #durgasoft
print("durga"*2) #durgadurga
Note:
1. To use + operator for Strings, compulsory both arguments should be str type
2. To use * operator for Strings, compulsory one argument should be str and other argument
should be int
len() in-built function:
We can use len() function to find the number of characters present in the string.
Eg:
s='durga'
print(len(s)) #5

nd
Q. Write a program to access each character of string in forward and backward direction
by using while loop?
1) s="Learning Python is very easy !!!"
2) n=len(s)
3) i=0
4) print("Forward direction")
5) while i<n:
6) print(s[i],end=' ')
7) i +=1
8) print("Backward direction")
9) i=-1
10) while i>=-n:
11) print(s[i],end=' ')
12) i=i-1
Alternative ways:
1) s="Learning Python is very easy !!!"
3) for i in s:
4) print(i,end=' ')
5)
7) for i in s[::]:
8) print(i,end=' ')
9)
10) print("Backward direction")
11) for i in s[::-1]:
12) print(i,end=' ')
Checking Membership:
We can check whether the character or string is the member of another string or not by using in
and not in operators
s='durga'
print('d' in s) #True
print('z' in s) #False
Program:
1) s=input("Enter main string:")
2) subs=input("Enter sub string:")
3) if subs in s:
4) print(subs,"is found in main string")
5) else:

nd
6) print(subs,"is not found in main string")
Output:
Enter main string:durgasoftwaresolutions
Enter sub string:durga
durga is found in main string
Enter main string:durgasoftwaresolutions
Enter sub string:python
python is not found in main string
Comparison of Strings:
We can use comparison operators (<,<=,>,>=) and equality operators(==,!=) for strings.
Comparison will be performed based on alphabetical order.
Eg:
1) s1=input("Enter first string:")
2) s2=input("Enter Second string:")
3) if s1==s2:
4) print("Both strings are equal")
5) elif s1<s2:
6) print("First String is less than Second String")
7) else:
8) print("First String is greater than Second String")
Output:
Enter first string:durga
Enter Second string:durga
Both strings are equal
Enter Second string:ravi
First String is less than Second String
Enter Second string:anil
First String is greater than Second String

nd
Removing spaces from the string:
We can use the following 3 methods
1. rstrip()===>To remove spaces at right hand side
2. lstrip()===>To remove spaces at left hand side
3. strip() ==>To remove spaces both sides
Eg:
1) city=input("Enter your city Name:")
2) scity=city.strip()
3) if scity=='Hyderabad':
4) print("Hello Hyderbadi..Adab")
5) elif scity=='Chennai':
6) print("Hello Madrasi...Vanakkam")
7) elif scity=="Bangalore":
8) print("Hello Kannadiga...Shubhodaya")
9) else:
10) print("your entered city is invalid")
Finding Substrings:
We can use the following 4 methods
For forward direction:
find()
index()
For backward direction:
rfind()
rindex()
1. find():
s.find(substring)
Returns index of first occurrence of the given substring. If it is not available then we will get -1
Eg:
1) s="Learning Python is very easy"

nd
2) print(s.find("Python")) #9
3) print(s.find("Java")) # -1
4) print(s.find("r"))#3
5) print(s.rfind("r"))#21
Note: By default find() method can search total string. We can also specify the boundaries to
search.
s.find(substring,bEgin,end)
It will always search from bEgin index to end-1 index
Eg:
1) s="durgaravipavanshiva"
2) print(s.find('a'))#4
3) print(s.find('a',7,15))#10
4) print(s.find('z',7,15))#-1
index() method:
index() method is exactly same as find() method except that if the specified substring is not
available then we will get ValueError.
Eg:
3) try:
4) n=s.index(subs)
5) except ValueError:
6) print("substring not found")
7) else:
8) print("substring found")
Output:
Enter main string:learning python is very easy
Enter sub string:python
substring found
Enter main string:learning python is very easy
Enter sub string:java
substring not found

nd
Q. Program to display all positions of substring in a given main string
3) flag=False
4) pos=-1
5) n=len(s)
6) while True:
7) pos=s.find(subs,pos+1,n)
8) if pos==-1:
9) break
10) print("Found at position",pos)
11) flag=True
12) if flag==False:
13) print("Not Found")
Output:
Enter main string:abbababababacdefg
Enter sub string:a
Found at position 0
Found at position 3
Found at position 5
Found at position 7
Found at position 9
Found at position 11
Enter main string:abbababababacdefg
Enter sub string:bb
Found at position 1
Counting substring in the given String:
We can find the number of occurrences of substring present in the given string by using count()
method.
1. s.count(substring) ==> It will search through out the string
2. s.count(substring, bEgin, end) ===> It will search from bEgin index to end-1 index
Eg:
1) s="abcabcabcabcadda"
2) print(s.count('a'))
3) print(s.count('ab'))
4) print(s.count('a',3,7))

nd
Output:
6
4
2
Replacing a string with another string:
s.replace(oldstring,newstring)
inside s, every occurrence of oldstring will be replaced with newstring.
Eg1:
s="Learning Python is very difficult"
s1=s.replace("difficult","easy")
print(s1)
Output:
Learning Python is very easy
Eg2: All occurrences will be replaced
s="ababababababab"
s1=s.replace("a","b")
print(s1)
Output: bbbbbbbbbbbbbb
Q. String objects are immutable then how we can change the content by
using replace() method.
Once we creates string object, we cannot change the content.This non changeable behaviour is
nothing but immutability. If we are trying to change the content by using any method, then with
those changes a new object will be created and changes won't be happend in existing object.
Hence with replace() method also a new object got created but existing object won't be changed.
Eg:
s="abab"
s1=s.replace("a","b")
print(s,"is available at :",id(s))
print(s1,"is available at :",id(s1))
Output:
abab is available at : 4568672
bbbb is available at : 4568704

nd
In the above example, original object is available and we can see new object which was created
because of replace() method.
Splitting of Strings:
We can split the given string according to specified seperator by using split() method.
l=s.split(seperator)
The default seperator is space. The return type of split() method is List
Eg1:
1) s="durga software solutions"
2) l=s.split()
3) for x in l:
4) print(x)
Output:
durga
software
solutions
Eg2:
1) s="22-02-2018"
2) l=s.split('-')
3) for x in l:
4) print(x)
Output:
22
02
2018
Joining of Strings:
We can join a group of strings(list or tuple) wrt the given seperator.
s=seperator.join(group of strings)
Eg:
t=('sunny','bunny','chinny')
s='-'.join(t)
print(s)
Output: sunny-bunny-chinny

nd
Eg2:
l=['hyderabad','singapore','london','dubai']
s=':'.join(l)
print(s)
hyderabad:singapore:london:dubai
Changing case of a String:
We can change case of a string by using the following 4 methods.
1. upper()===>To convert all characters to upper case
2. lower() ===>To convert all characters to lower case
3. swapcase()===>converts all lower case characters to upper case and all upper case characters to
lower case
4. title() ===>To convert all character to title case. i.e first character in every word should be upper
case and all remaining characters should be in lower case.
5. capitalize() ==>Only first character will be converted to upper case and all remaining characters
can be converted to lower case
Eg:
s='learning Python is very Easy'
print(s.upper())
print(s.lower())
print(s.swapcase())
print(s.title())
print(s.capitalize())
Output:
LEARNING PYTHON IS VERY EASY
learning python is very easy
LEARNING pYTHON IS VERY eASY
Learning Python Is Very Easy
Learning python is very easy
Checking starting and ending part of the string:
Python contains the following methods for this purpose
1. s.startswith(substring)
2. s.endswith(substring)
Eg:
s='learning Python is very easy'
print(s.startswith('learning'))
print(s.endswith('learning'))
print(s.endswith('easy'))

nd
Output:
True
False
True
To check type of characters present in a string:
Python contains the following methods for this purpose.
1) isalnum(): Returns True if all characters are alphanumeric( a to z , A to Z ,0 to9 )
2) isalpha(): Returns True if all characters are only alphabet symbols(a to z,A to Z)
3) isdigit(): Returns True if all characters are digits only( 0 to 9)
4) islower(): Returns True if all characters are lower case alphabet symbols
5) isupper(): Returns True if all characters are upper case aplhabet symbols
6) istitle(): Returns True if string is in title case
7) isspace(): Returns True if string contains only spaces
Eg:
print('Durga786'.isalnum()) #True
print('durga786'.isalpha()) #False
print('durga'.isalpha()) #True
print('durga'.isdigit()) #False
print('786786'.isdigit()) #True
print('abc'.islower()) #True
print('Abc'.islower()) #False
print('abc123'.islower()) #True
print('ABC'.isupper()) #True
print('Learning python is Easy'.istitle()) #False
print('Learning Python Is Easy'.istitle()) #True
print(' '.isspace()) #True
Demo Program:
1) s=input("Enter any character:")
2) if s.isalnum():
3) print("Alpha Numeric Character")
4) if s.isalpha():
5) print("Alphabet character")
6) if s.islower():
7) print("Lower case alphabet character")
8) else:
9) print("Upper case alphabet character")
10) else:
11) print("it is a digit")
12) elif s.isspace():
13) print("It is space character")
14) else:

nd
15) print("Non Space Special Character")
Enter any character:7
Alpha Numeric Character
it is a digit
Enter any character:a
Alphabet character
Lower case alphabet character
Enter any character:$
Non Space Special Character
Enter any character:A
Alphabet character
Upper case alphabet character
Formatting the Strings:
We can format the strings with variable values by using replacement operator {} and format()
method.
Eg:
name='durga'
salary=10000
age=48
print("{} 's salary is {} and his age is {}".format(name,salary,age))
print("{0} 's salary is {1} and his age is {2}".format(name,salary,age))
print("{x} 's salary is {y} and his age is {z}".format(z=age,y=salary,x=name))
Output:
durga 's salary is 10000 and his age is 48

nd
Important Programs rEgarding String Concept
Q1. Write a program to reverse the given String
input: durga
output:agrud
1st
Way:
s=input("Enter Some String:")
print(s[::-1])
2nd
Way:
print(''.join(reversed(s)))
3rd
Way:
i=len(s)-1
target=''
while i>=0:
target=target+s[i]
i=i-1
print(target)
Q2. Program to reverse order of words.
1) input: Learning Python is very Easy
2) output: Easy Very is Python Learning
3)
5) l=s.split()
6) l1=[]
7) i=len(l)-1
8) while i>=0:
9) l1.append(l[i])
10) i=i-1
11) output=' '.join(l1)
12) print(output)
Output:
Enter Some String:Learning Python is very easy!!
easy!!! very is Python Learning

nd
Q3. Program to reverse internal content of each word.
input: Durga Software Solutions
output:agruD erawtfoS snoituloS
2) l=s.split()
3) l1=[]
4) i=0
5) while i<len(l):
6) l1.append(l[i][::-1])
7) i=i+1
8) output=' '.join(l1)
9) print(output)
Q4. Write a program to print characters at odd position and even position for the given
String?
1st
Way:
print("Characters at Even Position:",s[0::2])
print("Characters at Odd Position:",s[1::2])
2nd
Way:
2) i=0
3) print("Characters at Even Position:")
4) while i< len(s):
5) print(s[i],end=',')
6) i=i+2
7) print()
8) print("Characters at Odd Position:")
9) i=1
10) while i< len(s):
11) print(s[i],end=',')
12) i=i+2
Q5. Program to merge characters of 2 strings into a single string by taking characters
alternatively.
s1="ravi"
s2="reja"
output: rtaevjia

nd
1) s1=input("Enter First String:")
2) s2=input("Enter Second String:")
3) output=''
4) i,j=0,0
5) while i<len(s1) or j<len(s2):
6) if i<len(s1):
7) output=output+s1[i]
8) i+=1
9) if j<len(s2):
10) output=output+s2[j]
11) j+=1
12) print(output)
Output:
Enter First String:durga
Enter Second String:ravisoft
druarvgiasoft
Q6. Write a program to sort the characters of the string and first alphabet symbols
followed by numeric values
input: B4A1D3
Output: ABD134
2) s1=s2=output=''
3) for x in s:
4) if x.isalpha():
5) s1=s1+x
6) else:
7) s2=s2+x
8) for x in sorted(s1):
9) output=output+x
10) for x in sorted(s2):
11) output=output+x
12) print(output)
Q7. Write a program for the following requirement
input: a4b3c2
output: aaaabbbcc
2) output=''
3) for x in s:
4) if x.isalpha():
5) output=output+x
6) previous=x

nd
7) else:
8) output=output+previous*(int(x)-1)
9) print(output)
Note: chr(unicode)===>The corresponding character
ord(character)===>The corresponding unicode value
Q8. Write a program to perform the following activity
input: a4k3b2
output:aeknbd
2) output=''
3) for x in s:
4) if x.isalpha():
5) output=output+x
6) previous=x
7) else:
8) output=output+chr(ord(previous)+int(x))
9) print(output)
Q9. Write a program to remove duplicate characters from the given input string?
input: ABCDABBCDABBBCCCDDEEEF
output: ABCDEF
2) l=[]
3) for x in s:
4) if x not in l:
5) l.append(x)
6) output=''.join(l)
7) print(output)
Q10. Write a program to find the number of occurrences of each character present in the
given String?
input: ABCABCABBCDE
output: A-3,B-4,C-3,D-1,E-1
1) s=input("Enter the Some String:")
2) d={}
3) for x in s:
4) if x in d.keys():
5) d[x]=d[x]+1
6) else:
7) d[x]=1

nd
8) for k,v in d.items():
9) print("{} = {} Times".format(k,v))
Formatting the Strings:
We can format the strings with variable values by using replacement operator {} and format()
method.
The main objective of format() method to format string into meaningful output form.
Case- 1: Basic Formatting for default, positional and keyword arguments
name='durga'
salary=10000
age=48
print("{} 's salary is {} and his age is {}".format(name,salary,age))
print("{0} 's salary is {1} and his age is {2}".format(name,salary,age))
print("{x} 's salary is {y} and his age is {z}".format(z=age,y=salary,x=name))
Output:
Case-2: Formatting Numbers
d--->Decimal IntEger
f----->Fixed point number(float).The default precision is 6
b-->Binary format
o--->Octal Format
x-->Hexa Decimal Format(Lower case)
X-->Hexa Decimal Format(Upper case)
Eg-1:
print("The intEger number is: {}".format(123))
print("The intEger number is: {:d}".format(123))
print("The intEger number is: {:5d}".format(123))
print("The intEger number is: {:05d}".format(123))
Output:
The intEger number is: 123
Eg-2:
print("The float number is: {}".format(123.4567))
print("The float number is: {:f}".format(123.4567))

nd
print("The float number is: {:8.3f}".format(123.4567))
Output:
The float number is: 123.4567
Note:
{:08.3f}
Total positions should be minimum 8.
After decimal point exactly 3 digits are allowed.If it is less then 0s will be placed in the last
positions
If total number is < 8 positions then 0 will be placed in MSBs
If total number is >8 positions then all intEgral digits will be considered.
The extra digits we can take only 0
Note: For numbers default alignment is Right Alignment(>)
Eg-3: Print Decimal value in binary, octal and hexadecimal form
print("Binary Form:{0:b}".format(153))
print("Octal Form:{0:o}".format(153))
print("Hexa decimal Form:{0:x}".format(154))
print("Hexa decimal Form:{0:X}".format(154))
Output:
Binary Form:10011001
Octal Form:231
Hexa decimal Form:9a
Hexa decimal Form:9A
Note: We can represent only int values in binary, octal and hexadecimal and it is not possible for
float values.
Note:
{:5d} It takes an intEger argument and assigns a minimum width of 5.
{:8.3f} It takes a float argument and assigns a minimum width of 8 including "." and after decimal
point excatly 3 digits are allowed with round operation if required
{:05d} The blank places can be filled with 0. In this place only 0 allowed.

nd
Case-3: Number formatting for signed numbers
While displaying positive numbers,if we want to include + then we have to write
{:+d} and {:+f}
Using plus for -ve numbers there is no use and for -ve numbers - sign will come automatically.
print("int value with sign:{:+d}".format(123))
print("int value with sign:{:+d}".format(-123))
print("float value with sign:{:+f}".format(123.456))
print("float value with sign:{:+f}".format(-123.456))
Output:
int value with sign:+123
int value with sign:-123
float value with sign:+123.456000
float value with sign:-123.456000
Case-4: Number formatting with alignment
<,>,^ and = are used for alignment
<==>Left Alignment to the remaining space
^===>Center alignment to the remaining space
>===> Right alignment to the remaining space
= ===>Forces the signed(+) (-) to the left most position
Note: Default Alignment for numbers is Right Alignment.
Ex:
1) print("{:5d}".format(12))
2) print("{:<5d}".format(12))
3) print("{:<05d}".format(12))
4) print("{:>5d}".format(12))
5) print("{:>05d}".format(12))
6) print("{:^5d}".format(12))
7) print("{:=5d}".format(-12))
8) print("{:^10.3f}".format(12.23456))
9) print("{:=8.3f}".format(-12.23456))
Output:
12
12
12000
12
00012
12
-12

nd
12.235
- 12.235
Case-5: String formatting with format()
Similar to numbers, we can format String values also with format() method.
s.format(string)
Eg:
1) print("{:5d}".format(12))
2) print("{:5}".format("rat"))
3) print("{:>5}".format("rat"))
4) print("{:<5}".format("rat"))
5) print("{:^5}".format("rat"))
6) print("{:*^5}".format("rat")) #Instead of * we can use any character(like +,$,a etc)
Output:
12
rat
rat
rat
rat
*rat*
Note: For numbers default alignment is right where as for strings default alignment is left
Case-6: Truncating Strings with format() method
1) print("{:.3}".format("durgasoftware"))
2) print("{:5.3}".format("durgasoftware"))
3) print("{:>5.3}".format("durgasoftware"))
4) print("{:^5.3}".format("durgasoftware"))
5) print("{:*^5.3}".format("durgasoftware"))
Output:
dur
dur
dur
dur
*dur*
Case-7: Formatting dictionary members using format()
1) person={'age':48,'name':'durga'}
2) print("{p[name]}'s age is: {p[age]}".format(p=person))

nd
Output:
durga's age is: 48
Note: p is alias name of dictionary
person dictionary we are passing as keyword argument
More convinient way is to use **person
Eg:
1) person={'age':48,'name':'durga'}
2) print("{name}'s age is: {age}".format(**person))
Output:
durga's age is: 48
Case-8: Formatting class members using format()
Eg:
1) class Person:
2) age=48
3) name="durga"
4) print("{p.name}'s age is :{p.age}".format(p=Person()))
Output:
durga's age is :48
Eg:
1) class Person:
2) def __init__(self,name,age):
3) self.name=name
4) self.age=age
5) print("{p.name}'s age is :{p.age}".format(p=Person('durga',48)))
6) print("{p.name}'s age is :{p.age}".format(p=Person('Ravi',50)))
Note: Here Person object is passed as keyword argument. We can access by using its reference
variable in the template string
Case-9: Dynamic Formatting using format()
1) string="{:{fill}{align}{width}}"
2) print(string.format('cat',fill='*',align='^',width=5))
3) print(string.format('cat',fill='*',align='^',width=6))
4) print(string.format('cat',fill='*',align='<',width=6))
5) print(string.format('cat',fill='*',align='>',width=6))

nd
Output:
*cat*
*cat**
cat***
***cat
Case-10: Dynamic Float format template
1) num="{:{align}{width}.{precision}f}"
2) print(num.format(123.236,align='<',width=8,precision=2))
3) print(num.format(123.236,align='>',width=8,precision=2))
Output:
123.24
123.24
Case-11: Formatting Date values
1) import datetime
2) #datetime formatting
3) date=datetime.datetime.now()
4) print("It's now:{:%d/%m/%Y %H:%M:%S}".format(date))
Output: It's now:09/03/2018 12:36:26
Case-12: Formatting complex numbers
1) complexNumber=1+2j
2) print("Real Part:{0.real} and Imaginary Part:{0.imag}".format(complexNumber))
Output: Real Part:1.0 and Imaginary Part:2.0

nd
List Data Structure
If we want to represent a group of individual objects as a single entity where insertion
order preserved and duplicates are allowed, then we should go for List.
insertion order preserved.
duplicate objects are allowed
heterogeneous objects are allowed.
List is dynamic because based on our requirement we can increase the size and decrease
the size.
In List the elements will be placed within square brackets and with comma seperator.
We can differentiate duplicate elements by using index and we can preserve insertion
order by using index. Hence index will play very important role.
Python supports both positive and negative indexes. +ve index means from left to right
where as negative index means right to left
[10,"A","B",20, 30, 10]
List objects are mutable.i.e we can change the content.
Creation of List Objects:
1. We can create empty list object as follows...
1) list=[]
2) print(list)
3) print(type(list))
4)
5) []
6) <class 'list'>
2. If we know elements already then we can create list as follows
list=[10,20,30,40]
10 A B 20 30 10
-6 -5 -4 -3 -2 -1
0 1 2 3 4 5

nd
3. With dynamic input:
1) list=eval(input("Enter List:"))
2) print(list)
3) print(type(list))
4)
6) Enter List:[10,20,30,40]
7) [10, 20, 30, 40]
8) <class 'list'>
4. With list() function:
1) l=list(range(0,10,2))
2) print(l)
3) print(type(l))
4)
6) [0, 2, 4, 6, 8]
7) <class 'list'>
Eg:
1) s="durga"
2) l=list(s)
3) print(l)
4)
6) ['d', 'u', 'r', 'g', 'a']
5. with split() function:
1) s="Learning Python is very very easy !!!"
2) l=s.split()
3) print(l)
4) print(type(l))
5)
7) ['Learning', 'Python', 'is', 'very', 'very', 'easy', '!!!']
8) <class 'list'>
Note:
Sometimes we can take list inside another list,such type of lists are called nested lists.
[10,20,[30,40]]

nd
Accessing elements of List:
We can access elements of the list either by using index or by using slice operator(:)
1. By using index:
List follows zero based index. ie index of first element is zero.
List supports both +ve and -ve indexes.
+ve index meant for Left to Right
-ve index meant for Right to Left
list=[10,20,30,40]
print(list[0]) ==>10
print(list[-1]) ==>40
print(list[10]) ==>IndexError: list index out of range
2. By using slice operator:
Syntax:
list2= list1[start:stop:step]
start ==>it indicates the index where slice has to start
default value is 0
stop ===>It indicates the index where slice has to end
default value is max allowed index of list ie length of the list
step ==>increment value
default value is 1
Eg:
1) n=[1,2,3,4,5,6,7,8,9,10]
2) print(n[2:7:2])
3) print(n[4::2])
4) print(n[3:7])
5) print(n[8:2:-2])
6) print(n[4:100])
10 20 30 40
-4 -3 -2 -1
0 1 2 3
list

nd
7)
8) Output
10) [3, 5, 7]
11) [5, 7, 9]
12) [4, 5, 6, 7]
13) [9, 7, 5]
14) [5, 6, 7, 8, 9, 10]
List vs mutability:
Once we creates a List object,we can modify its content. Hence List objects are mutable.
Eg:
1) n=[10,20,30,40]
2) print(n)
3) n[1]=777
4) print(n)
5)
7) [10, 20, 30, 40]
8) [10, 777, 30, 40]
Traversing the elements of List:
The sequential access of each element in the list is called traversal.
1. By using while loop:
1) n=[0,1,2,3,4,5,6,7,8,9,10]
2) i=0
3) while i<len(n):
4) print(n[i])
5) i=i+1
6)
8) 0
9) 1
10) 2
11) 3
12) 4
13) 5
14) 6
15) 7
16) 8
17) 9

nd
18) 10
2. By using for loop:
1) n=[0,1,2,3,4,5,6,7,8,9,10]
2) for n1 in n:
3) print(n1)
4)
6) 0
7) 1
8) 2
9) 3
10) 4
11) 5
12) 6
13) 7
14) 8
15) 9
16) 10
3. To display only even numbers:
1) n=[0,1,2,3,4,5,6,7,8,9,10]
2) for n1 in n:
3) if n1%2==0:
4) print(n1)
5)
7) 0
8) 2
9) 4
10) 6
11) 8
12) 10
4. To display elements by index wise:
1) l=["A","B","C"]
2) x=len(l)
3) for i in range(x):
4) print(l[i],"is available at positive index: ",i,"and at negative index: ",i-x)
5)
6) Output
8) A is available at positive index: 0 and at negative index: -3
9) B is available at positive index: 1 and at negative index: -2
10) C is available at positive index: 2 and at negative index: -1

nd
Important functions of List:
I. To get information about list:
1. len():
returns the number of elements present in the list
Eg: n=[10,20,30,40]
print(len(n))==>4
2. count():
It returns the number of occurrences of specified item in the list
1) n=[1,2,2,2,2,3,3]
2) print(n.count(1))
6)
7) Output
9) 1
10) 4
11) 2
12) 0
3. index() function:
returns the index of first occurrence of the specified item.
Eg:
1) n=[1,2,2,2,2,3,3]
2) print(n.index(1)) ==>0
5) print(n.index(4)) ==>ValueError: 4 is not in list
Note: If the specified element not present in the list then we will get ValueError.Hence
before index() method we have to check whether item present in the list or not by using in
operator.
print( 4 in n)==>False

nd
II. Manipulating elements of List:
1. append() function:
We can use append() function to add item at the end of the list.
Eg:
1) list=[]
2) list.append("A")
3) list.append("B")
4) list.append("C")
5) print(list)
6)
8) ['A', 'B', 'C']
Eg: To add all elements to list upto 100 which are divisible by 10
1) list=[]
3) if i%10==0:
4) list.append(i)
5) print(list)
6)
7)
9) [0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
2. insert() function:
To insert item at specified index position
1) n=[1,2,3,4,5]
2) n.insert(1,888)
3) print(n)
4)
6) [1, 888, 2, 3, 4, 5]
Eg:
1) n=[1,2,3,4,5]
2) n.insert(10,777)
3) n.insert(-10,999)
4) print(n)
5)

nd
7) [999, 1, 2, 3, 4, 5, 777]
Note: If the specified index is greater than max index then element will be inserted at last
position. If the specified index is smaller than min index then element will be inserted at
first position.
Differences between append() and insert()
3. extend() function:
To add all items of one list to another list
l1.extend(l2)
all items present in l2 will be added to l1
Eg:
1) order1=["Chicken","Mutton","Fish"]
2) order2=["RC","KF","FO"]
3) order1.extend(order2)
4) print(order1)
5)
7) ['Chicken', 'Mutton', 'Fish', 'RC', 'KF', 'FO']
Eg:
1) order=["Chicken","Mutton","Fish"]
2) order.extend("Mushroom")
3) print(order)
4)
6) ['Chicken', 'Mutton', 'Fish', 'M', 'u', 's', 'h', 'r', 'o', 'o', 'm']
4. remove() function:
We can use this function to remove specified item from the list.If the item present
multiple times then only first occurrence will be removed.
append() insert()
In List when we add any element it will
come in last i.e. it will be last element.
In List we can insert any element in
particular index number

nd
1) n=[10,20,10,30]
2) n.remove(10)
3) print(n)
4)
6) [20, 10, 30]
If the specified item not present in list then we will get ValueError
1) n=[10,20,10,30]
2) n.remove(40)
3) print(n)
4)
5) ValueError: list.remove(x): x not in list
Note: Hence before using remove() method first we have to check specified element
present in the list or not by using in operator.
5. pop() function:
It removes and returns the last element of the list.
This is only function which manipulates list and returns some element.
Eg:
1) n=[10,20,30,40]
2) print(n.pop())
3) print(n.pop())
4) print(n)
5)
7) 40
8) 30
9) [10, 20]
If the list is empty then pop() function raises IndexError
Eg:
1) n=[]
2) print(n.pop()) ==> IndexError: pop from empty list

nd
Note:
1. pop() is the only function which manipulates the list and returns some value
2. In general we can use append() and pop() functions to implement stack datastructure
by using list,which follows LIFO(Last In First Out) order.
In general we can use pop() function to remove last element of the list. But we can use to
remove elements based on index.
n.pop(index)===>To remove and return element present at specified index.
n.pop()==>To remove and return last element of the list
1) n=[10,20,30,40,50,60]
2) print(n.pop()) #60
3) print(n.pop(1)) #20
4) print(n.pop(10)) ==>IndexError: pop index out of range
Differences between remove() and pop()
Note:
List objects are dynamic. i.e based on our requirement we can increase and decrease the
size.
append(),insert() ,extend() ===>for increasing the size/growable nature
remove(), pop() ======>for decreasing the size /shrinking nature
remove() pop()
1) We can use to remove special element
from the List.
1) We can use to remove last element
from the List.
2) It can’t return any value. 2) It returned removed element.
3) If special element not available then we
get VALUE ERROR.
3) If List is empty then we get Error.

nd
III. Ordering elements of List:
1. reverse():
We can use to reverse() order of elements of list.
1) n=[10,20,30,40]
2) n.reverse()
3) print(n)
4)
6) [40, 30, 20, 10]
2. sort() function:
In list by default insertion order is preserved. If want to sort the elements of list according
to default natural sorting order then we should go for sort() method.
For numbers ==>default natural sorting order is Ascending Order
For Strings ==> default natural sorting order is Alphabetical Order
1) n=[20,5,15,10,0]
2) n.sort()
3) print(n) #[0,5,10,15,20]
4)
5) s=["Dog","Banana","Cat","Apple"]
6) s.sort()
7) print(s) #['Apple','Banana','Cat','Dog']
Note: To use sort() function, compulsory list should contain only homogeneous elements.
otherwise we will get TypeError
Eg:
1) n=[20,10,"A","B"]
2) n.sort()
3) print(n)
4)
5) TypeError: '<' not supported between instances of 'str' and 'int'
Note: In Python 2 if List contains both numbers and Strings then sort() function first sort
numbers followed by strings
1) n=[20,"B",10,"A"]
2) n.sort()

nd
3) print(n)# [10,20,'A','B']
But in Python 3 it is invalid.
To sort in reverse of default natural sorting order:
We can sort according to reverse of default natural sorting order by using reverse=True
argument.
Eg:
1. n=[40,10,30,20]
2. n.sort()
3. print(n) ==>[10,20,30,40]
4. n.sort(reverse=True)
5. print(n) ===>[40,30,20,10]
6. n.sort(reverse=False)
7. print(n) ==>[10,20,30,40]
Aliasing and Cloning of List objects:
The process of giving another reference variable to the existing list is called aliasing.
Eg:
1) x=[10,20,30,40]
2) y=x
3) print(id(x))
4) print(id(y))
The problem in this approach is by using one reference variable if we are changing
content,then those changes will be reflected to the other reference variable.
1) x=[10,20,30,40]
2) y=x
3) y[1]=777
4) print(x) ==>[10,777,30,40]
To overcome this problem we should go for cloning.
The process of creating exactly duplicate independent object is called cloning.
We can implement cloning by using slice operator or by using copy() function
10 20 30 40
x
y
10 20
777
30 40
x
y

nd
1) x=[10,20,30,40]
2) y=x[:]
3) y[1]=777
4) print(x) ==>[10,20,30,40]
5) print(y) ==>[10,777,30,40]
2. By using copy() function:
1) x=[10,20,30,40]
2) y=x.copy()
3) y[1]=777
4) print(x) ==>[10,20,30,40]
5) print(y) ==>[10,777,30,40]
Q. Difference between = operator and copy() function
= operator meant for aliasing
copy() function meant for cloning
10 20 30 40
x
10 20
777
30 40
y
10 20 30 40
x
10 20
777
30 40
y

nd
Using Mathematical operators for List Objects:
We can use + and * operators for List objects.
1. Concatenation operator(+):
We can use + to concatenate 2 lists into a single list
1) a=[10,20,30]
2) b=[40,50,60]
3) c=a+b
4) print(c) ==>[10,20,30,40,50,60]
Note: To use + operator compulsory both arguments should be list objects,otherwise we
will get TypeError.
Eg:
c=a+40 ==>TypeError: can only concatenate list (not "int") to list
c=a+[40] ==>valid
2. Repetition Operator(*):
We can use repetition operator * to repeat elements of list specified number of times
Eg:
1) x=[10,20,30]
2) y=x*3
3) print(y)==>[10,20,30,10,20,30,10,20,30]
Comparing List objects
We can use comparison operators for List objects.
Eg:
1. x=["Dog","Cat","Rat"]
2. y=["Dog","Cat","Rat"]
3. z=["DOG","CAT","RAT"]
4. print(x==y) True
5. print(x==z) False
6. print(x != z) True

nd
Note:
Whenever we are using comparison operators(==,!=) for List objects then the following
should be considered
1. The number of elements
2. The order of elements
3. The content of elements (case sensitive)
Note: When ever we are using relatational operators(<,<=,>,>=) between List objects,only
first element comparison will be performed.
Eg:
1. x=[50,20,30]
2. y=[40,50,60,100,200]
3. print(x>y) True
4. print(x>=y) True
5. print(x<y) False
6. print(x<=y) False
Eg:
1. x=["Dog","Cat","Rat"]
2. y=["Rat","Cat","Dog"]
3. print(x>y) False
4. print(x>=y) False
5. print(x<y) True
6. print(x<=y) True
Membership operators:
We can check whether element is a member of the list or not by using memebership
operators.
in operator
not in operator
Eg:
1. n=[10,20,30,40]
2. print (10 in n)
3. print (10 not in n)
4. print (50 in n)
5. print (50 not in n)
6.
7. Output

nd
8. True
9. False
10. False
11. True
clear() function:
We can use clear() function to remove all elements of List.
Eg:
1. n=[10,20,30,40]
2. print(n)
3. n.clear()
4. print(n)
5.
6. Output
8. [10, 20, 30, 40]
9. []
Nested Lists:
Sometimes we can take one list inside another list. Such type of lists are called nested
lists.
Eg:
1. n=[10,20,[30,40]]
2. print(n)
3. print(n[0])
4. print(n[2])
5. print(n[2][0])
6. print(n[2][1])
7.
8. Output
10. [10, 20, [30, 40]]
11. 10
12. [30, 40]
13. 30
14. 40
Note: We can access nested list elements by using index just like accessing multi
dimensional array elements.

nd
Nested List as Matrix:
In Python we can represent matrix by using nested lists.
1) n=[[10,20,30],[40,50,60],[70,80,90]]
2) print(n)
3) print("Elements by Row wise:")
4) for r in n:
5) print(r)
6) print("Elements by Matrix style:")
7) for i in range(len(n)):
8) for j in range(len(n[i])):
9) print(n[i][j],end=' ')
10) print()
11)
12) Output
14) [[10, 20, 30], [40, 50, 60], [70, 80, 90]]
15) Elements by Row wise:
16) [10, 20, 30]
17) [40, 50, 60]
18) [70, 80, 90]
19) Elements by Matrix style:
20) 10 20 30
21) 40 50 60
22) 70 80 90
List Comprehensions:
It is very easy and compact way of creating list objects from any iterable objects(like
list,tuple,dictionary,range etc) based on some condition.
Syntax:
list=[expression for item in list if condition]
Eg:
1) s=[ x*x for x in range(1,11)]
2) print(s)
3) v=[2**x for x in range(1,6)]
4) print(v)
5) m=[x for x in s if x%2==0]
6) print(m)
7)
8) Output
10) [1, 4, 9, 16, 25, 36, 49, 64, 81, 100]

nd
11) [2, 4, 8, 16, 32]
12) [4, 16, 36, 64, 100]
Eg:
1) words=["Balaiah","Nag","Venkatesh","Chiranjeevi"]
2) l=[w[0] for w in words]
3) print(l)
4)
5) Output['B', 'N', 'V', 'C']
Eg:
1) num1=[10,20,30,40]
2) num2=[30,40,50,60]
3) num3=[ i for i in num1 if i not in num2]
4) print(num3) [10,20]
5)
6) common elements present in num1 and num2
7) num4=[i for i in num1 if i in num2]
8) print(num4) [30, 40]
Eg:
1) words="the quick brown fox jumps over the lazy dog".split()
2) print(words)
3) l=[[w.upper(),len(w)] for w in words]
4) print(l)
5)
6) Output
7) ['the', 'quick', 'brown', 'fox', 'jumps', 'over', 'the', 'lazy', 'dog']
8) [['THE', 3], ['QUICK', 5], ['BROWN', 5], ['FOX', 3], ['JUMPS', 5], ['OVER', 4],
9) ['THE', 3], ['LAZY', 4], ['DOG', 3]]
Q. Write a program to display unique vowels present in the given word?
1) vowels=['a','e','i','o','u']
2) word=input("Enter the word to search for vowels: ")
3) found=[]
4) for letter in word:
5) if letter in vowels:
6) if letter not in found:
7) found.append(letter)
8) print(found)
9) print("The number of different vowels present in",word,"is",len(found))
10)
11)

nd
13) Enter the word to search for vowels: durgasoftwaresolutions
14) ['u', 'a', 'o', 'e', 'i']
15) The number of different vowels present in durgasoftwaresolutions is 5
list out all functions of list and write a program to use these functions

nd
Tuple Data Structure
1. Tuple is exactly same as List except that it is immutable. i.e once we creates Tuple
object,we cannot perform any changes in that object.
Hence Tuple is Read Only version of List.
2. If our data is fixed and never changes then we should go for Tuple.
3. Insertion Order is preserved
4. Duplicates are allowed
5. Heterogeneous objects are allowed.
6. We can preserve insertion order and we can differentiate duplicate objects by using
index. Hence index will play very important role in Tuple also.
Tuple support both +ve and -ve index. +ve index means forward direction(from left to
right) and -ve index means backward direction(from right to left)
7. We can represent Tuple elements within Parenthesis and with comma seperator.
Parenethesis are optional but recommended to use.
Eg:
1. t=10,20,30,40
2. print(t)
3. print(type(t))
4.
5. Output
6. (10, 20, 30, 40)
7. <class 'tuple'>
8.
9. t=()
10. print(type(t)) # tuple
Note: We have to take special care about single valued tuple.compulsary the value
should ends with comma,otherwise it is not treated as tuple.
Eg:
1. t=(10)
2. print(t)
3. print(type(t))
4.
5. Output
6. 10
7. <class 'int'>

nd
Eg:
1. t=(10,)
2. print(t)
3. print(type(t))
4.
5. Output
6. (10,)
7. <class 'tuple'>
Q. Which of the following are valid tuples?
1. t=()
2. t=10,20,30,40
3. t=10
4. t=10,
5. t=(10)
6. t=(10,)
7.t=(10,20,30,40)
Tuple creation:
1. t=()
creation of empty tuple
2. t=(10,)
t=10,
creation of single valued tuple ,parenthesis are optional,should ends with comma
3. t=10,20,30
t=(10,20,30)
creation of multi values tuples & parenthesis are optional
4. By using tuple() function:
1. list=[10,20,30]
2. t=tuple(list)
3. print(t)
4.
5. t=tuple(range(10,20,2))
6. print(t)

nd
Accessing elements of tuple:
We can access either by index or by slice operator
1. By using index:
1. t=(10,20,30,40,50,60)
2. print(t[0]) #10
3. print(t[-1]) #60
4. print(t[100]) IndexError: tuple index out of range
1. t=(10,20,30,40,50,60)
2. print(t[2:5])
3. print(t[2:100])
4. print(t[::2])
5.
6. Output
7. (30, 40, 50)
8. (30, 40, 50, 60)
9. (10, 30, 50)
Tuple vs immutability:
Once we creates tuple,we cannot change its content.
Hence tuple objects are immutable.
Eg:
t=(10,20,30,40)
t[1]=70 TypeError: 'tuple' object does not support item assignment
Mathematical operators for tuple:
We can apply + and * operators for tuple
1. Concatenation Operator(+):
1. t1=(10,20,30)
2. t2=(40,50,60)
3. t3=t1+t2
4. print(t3) # (10,20,30,40,50,60)

nd
2. Multiplication operator or repetition operator(*)
1. t1=(10,20,30)
2. t2=t1*3
3. print(t2) #(10,20,30,10,20,30,10,20,30)
Important functions of Tuple:
1. len()
To return number of elements present in the tuple
Eg:
t=(10,20,30,40)
print(len(t)) #4
2. count()
To return number of occurrences of given element in the tuple
Eg:
t=(10,20,10,10,20)
print(t.count(10)) #3
3. index()
returns index of first occurrence of the given element.
If the specified element is not available then we will get ValueError.
Eg:
t=(10,20,10,10,20)
print(t.index(10)) #0
print(t.index(30)) ValueError: tuple.index(x): x not in tuple
4. sorted()
To sort elements based on default natural sorting order
1. t=(40,10,30,20)
2. t1=sorted(t)
3. print(t1)
4. print(t)
5.
6. Output
7. [10, 20, 30, 40]
8. (40, 10, 30, 20)
We can sort according to reverse of default natural sorting order as follows

nd
t1=sorted(t,reverse=True)
print(t1) [40, 30, 20, 10]
5. min() and max() functions:
These functions return min and max values according to default natural sorting order.
Eg:
1. t=(40,10,30,20)
2. print(min(t)) #10
3. print(max(t)) #40
6. cmp():
It compares the elements of both tuples.
If both tuples are equal then returns 0
If the first tuple is less than second tuple then it returns -1
If the first tuple is greater than second tuple then it returns +1
Eg:
1. t1=(10,20,30)
2. t2=(40,50,60)
3. t3=(10,20,30)
4. print(cmp(t1,t2)) # -1
5. print(cmp(t1,t3)) # 0
6. print(cmp(t2,t3)) # +1
Note: cmp() function is available only in Python2 but not in Python 3
Tuple Packing and Unpacking:
We can create a tuple by packing a group of variables.
Eg:
a=10
b=20
c=30
d=40
t=a,b,c,d
print(t) #(10, 20, 30, 40)
Here a,b,c,d are packed into a tuple t. This is nothing but tuple packing.

nd
Tuple unpacking is the reverse process of tuple packing
We can unpack a tuple and assign its values to different variables
Eg:
1. t=(10,20,30,40)
2. a,b,c,d=t
3. print("a=",a,"b=",b,"c=",c,"d=",d)
4.
5. Output
6. a= 10 b= 20 c= 30 d= 40
Note: At the time of tuple unpacking the number of variables and number of values
should be same. ,otherwise we will get ValueError.
Eg:
t=(10,20,30,40)
a,b,c=t #ValueError: too many values to unpack (expected 3)
Tuple Comprehension:
Tuple Comprehension is not supported by Python.
t= ( x**2 for x in range(1,6))
Here we are not getting tuple object and we are getting generator object.
1. t= ( x**2 for x in range(1,6))
2. print(type(t))
3. for x in t:
4. print(x)
5.
6. Output
8. <class 'generator'>
9. 1
10. 4
11. 9
12. 16
13. 25

nd
Q. Write a program to take a tuple of numbers from the keyboard and print its sum and
average?
1. t=eval(input("Enter Tuple of Numbers:"))
2. l=len(t)
3. sum=0
4. for x in t:
5. sum=sum+x
6. print("The Sum=",sum)
7. print("The Average=",sum/l)
8.
10. Enter Tuple of Numbers:(10,20,30,40)
11. The Sum= 100
12. The Average= 25.0
13.
15. Enter Tuple of Numbers:(100,200,300)
16. The Sum= 600
17. The Average= 200.0
Differences between List and Tuple:
List and Tuple are exactly same except small difference: List objects are mutable where as
Tuple objects are immutable.
In both cases insertion order is preserved, duplicate objects are allowed, heterogenous
objects are allowed, index and slicing are supported.
List Tuple
1) List is a Group of Comma separeated
Values within Square Brackets and Square
Brackets are mandatory.
Eg: i = [10, 20, 30, 40]
1) Tuple is a Group of Comma separeated
Values within Parenthesis and Parenthesis
are optional.
Eg: t = (10, 20, 30, 40)
t = 10, 20, 30, 40
2) List Objects are Mutable i.e. once we
creates List Object we can perform any
changes in that Object.
Eg: i[1] = 70
2) Tuple Objeccts are Immutable i.e. once
we creates Tuple Object we cannot change
its content.
t[1] = 70  ValueError: tuple object does
not support item assignment.
3) If the Content is not fixed and keep on
changing then we should go for List.
3) If the content is fixed and never changes
then we should go for Tuple.
4) List Objects can not used as Keys for
Dictionries because Keys should be
Hashable and Immutable.
4) Tuple Objects can be used as Keys for
Dictionries because Keys should be
Hashable and Immutable.

nd

nd
Set Data Structure
 If we want to represent a group of unique values as a single entity then we should go
for set.
 Duplicates are not allowed.
 Insertion order is not preserved.But we can sort the elements.
 Indexing and slicing not allowed for the set.
 Heterogeneous elements are allowed.
 Set objects are mutable i.e once we creates set object we can perform any changes in
that object based on our requirement.
 We can represent set elements within curly braces and with comma seperation
 We can apply mathematical operations like union,intersection,difference etc on set
objects.
Creation of Set objects:
Eg:
1. s={10,20,30,40}
2. print(s)
3. print(type(s))
4.
5. Output
6. {40, 10, 20, 30}
7. <class 'set'>
We can create set objects by using set() function
s=set(any sequence)
Eg 1:
1. l = [10,20,30,40,10,20,10]
2. s=set(l)
3. print(s) # {40, 10, 20, 30}
Eg 2:
1. s=set(range(5))
2. print(s) #{0, 1, 2, 3, 4}
Note: While creating empty set we have to take special care.
Compulsory we should use set() function.

nd
s={} ==>It is treated as dictionary but not empty set.
Eg:
1. s={}
2. print(s)
3. print(type(s))
4.
5. Output
6. {}
7. <class 'dict'>
Eg:
1. s=set()
2. print(s)
3. print(type(s))
4.
5. Output
6. set()
7. <class 'set'>
Important functions of set:
1. add(x):
Adds item x to the set
Eg:
1. s={10,20,30}
2. s.add(40);
3. print(s) #{40, 10, 20, 30}
2. update(x,y,z):
To add multiple items to the set.
Arguments are not individual elements and these are Iterable objects like List,range etc.
All elements present in the given Iterable objects will be added to the set.
Eg:
1. s={10,20,30}
2. l=[40,50,60,10]
3. s.update(l,range(5))
4. print(s)

nd
5.
6. Output
7. {0, 1, 2, 3, 4, 40, 10, 50, 20, 60, 30}
Q. What is the difference between add() and update() functions in set?
We can use add() to add individual item to the Set,where as we can use update() function
to add multiple items to Set.
add() function can take only one argument where as update() function can take any
number of arguments but all arguments should be iterable objects.
Q. Which of the following are valid for set s?
1. s.add(10)
2. s.add(10,20,30) TypeError: add() takes exactly one argument (3 given)
3. s.update(10) TypeError: 'int' object is not iterable
4. s.update(range(1,10,2),range(0,10,2))
3. copy():
Returns copy of the set.
It is cloned object.
s={10,20,30}
s1=s.copy()
print(s1)
4. pop():
It removes and returns some random element from the set.
Eg:
1. s={40,10,30,20}
2. print(s)
3. print(s.pop())
4. print(s)
5.
6. Output
7. {40, 10, 20, 30}
8. 40
9. {10, 20, 30}

nd
5. remove(x):
It removes specified element from the set.
If the specified element not present in the Set then we will get KeyError
s={40,10,30,20}
s.remove(30)
print(s) # {40, 10, 20}
s.remove(50) ==>KeyError: 50
6. discard(x):
It removes the specified element from the set.
If the specified element not present in the set then we won't get any error.
s={10,20,30}
s.discard(10)
print(s) ===>{20, 30}
s.discard(50)
print(s) ==>{20, 30}
Q. What is the difference between remove() and discard() functions in Set?
Q. Explain differences between pop(),remove() and discard() functionsin Set?
7.clear():
To remove all elements from the Set.
1. s={10,20,30}
2. print(s)
3. s.clear()
4. print(s)
5.
6. Output
7. {10, 20, 30}
8. set()

nd
Mathematical operations on the Set:
1.union():
x.union(y) ==>We can use this function to return all elements present in both sets
x.union(y) or x|y
Eg:
x={10,20,30,40}
y={30,40,50,60}
print(x.union(y)) #{10, 20, 30, 40, 50, 60}
print(x|y) #{10, 20, 30, 40, 50, 60}
2. intersection():
x.intersection(y) or x&y
Returns common elements present in both x and y
Eg:
x={10,20,30,40}
y={30,40,50,60}
print(x.intersection(y)) #{40, 30}
print(x&y) #{40, 30}
3. difference():
x.difference(y) or x-y
returns the elements present in x but not in y
Eg:
x={10,20,30,40}
y={30,40,50,60}
print(x.difference(y)) #{10, 20}
print(x-y) #{10, 20}
print(y-x) #{50, 60}

nd
4.symmetric_difference():
x.symmetric_difference(y) or x^y
Returns elements present in either x or y but not in both
Eg:
x={10,20,30,40}
y={30,40,50,60}
print(x.symmetric_difference(y)) #{10, 50, 20, 60}
print(x^y) #{10, 50, 20, 60}
Membership operators: (in , not in)
Eg:
1. s=set("durga")
2. print(s)
3. print('d' in s)
4. print('z' in s)
5.
6. Output
7. {'u', 'g', 'r', 'd', 'a'}
8. True
9. False
Set Comprehension:
Set comprehension is possible.
s={x*x for x in range(5)}
print(s) #{0, 1, 4, 9, 16}
s={2**x for x in range(2,10,2)}
print(s) #{16, 256, 64, 4}
set objects won't support indexing and slicing:
Eg:
s={10,20,30,40}
print(s[0]) ==>TypeError: 'set' object does not support indexing
print(s[1:3]) ==>TypeError: 'set' object is not subscriptable

nd
Q.Write a program to eliminate duplicates present in the list?
Approach-1:
1. l=eval(input("Enter List of values: "))
2. s=set(l)
3. print(s)
4.
5. Output
7. Enter List of values: [10,20,30,10,20,40]
8. {40, 10, 20, 30}
Approach-2:
1. l=eval(input("Enter List of values: "))
2. l1=[]
3. for x in l:
4. if x not in l1:
5. l1.append(x)
6. print(l1)
7.
8. Output
10. Enter List of values: [10,20,30,10,20,40]
11. [10, 20, 30, 40]
Q. Write a program to print different vowels present in the given word?
1. w=input("Enter word to search for vowels: ")
2. s=set(w)
3. v={'a','e','i','o','u'}
4. d=s.intersection(v)
5. print("The different vowel present in",w,"are",d)
6.
7. Output
9. Enter word to search for vowels: durga
10. The different vowel present in durga are {'u', 'a'}

nd
Dictionary Data Structure
We can use List,Tuple and Set to represent a group of individual objects as a single entity.
If we want to represent a group of objects as key-value pairs then we should go for
Dictionary.
Eg:
rollno----name
phone number--address
ipaddress---domain name
Duplicate keys are not allowed but values can be duplicated.
Hetrogeneous objects are allowed for both key and values.
insertion order is not preserved
Dictionaries are mutable
Dictionaries are dynamic
indexing and slicing concepts are not applicable
Note: In C++ and Java Dictionaries are known as "Map" where as in Perl and Ruby it is
known as "Hash"
How to create Dictionary?
d={} or d=dict()
we are creating empty dictionary. We can add entries as follows
d[100]="durga"
d[200]="ravi"
d[300]="shiva"
print(d) #{100: 'durga', 200: 'ravi', 300: 'shiva'}
If we know data in advance then we can create dictionary as follows
d={100:'durga' ,200:'ravi', 300:'shiva'}
d={key:value, key:value}

nd
How to access data from the dictionary?
We can access data by using keys.
d={100:'durga' ,200:'ravi', 300:'shiva'}
print(d[100]) #durga
print(d[300]) #shiva
If the specified key is not available then we will get KeyError
print(d[400]) # KeyError: 400
We can prevent this by checking whether key is already available or not by using
has_key() function or by using in operator.
d.has_key(400) ==> returns 1 if key is available otherwise returns 0
But has_key() function is available only in Python 2 but not in Python 3. Hence
compulsory we have to use in operator.
if 400 in d:
print(d[400])
Q. Write a program to enter name and percentage marks in a dictionary and
display information on the screen
1) rec={}
2) n=int(input("Enter number of students: "))
3) i=1
4) while i <=n:
5) name=input("Enter Student Name: ")
6) marks=input("Enter % of Marks of Student: ")
7) rec[name]=marks
8) i=i+1
9) print("Name of Student","t","% of marks")
10) for x in rec:
11) print("t",x,"tt",rec[x])
12)
13) Output
15) Enter number of students: 3
16) Enter Student Name: durga
17) Enter % of Marks of Student: 60%
18) Enter Student Name: ravi
20) Enter Student Name: shiva

nd
22) Name of Student % of marks
23) durga 60%
24) ravi 70 %
25) shiva 80%
How to update dictionaries?
d[key]=value
If the key is not available then a new entry will be added to the dictionary with the
specified key-value pair
If the key is already available then old value will be replaced with new value.
Eg:
1. d={100:"durga",200:"ravi",300:"shiva"}
2. print(d)
3. d[400]="pavan"
4. print(d)
5. d[100]="sunny"
6. print(d)
7.
8. Output
9. {100: 'durga', 200: 'ravi', 300: 'shiva'}
10. {100: 'durga', 200: 'ravi', 300: 'shiva', 400: 'pavan'}
11. {100: 'sunny', 200: 'ravi', 300: 'shiva', 400: 'pavan'}
How to delete elements from dictionary?
del d[key]
It deletes entry associated with the specified key.
If the key is not available then we will get KeyError
Eg:
2. print(d)
3. del d[100]
4. print(d)
5. del d[400]
6.
7. Output
8. {100: 'durga', 200: 'ravi', 300: 'shiva'}

nd
9. {200: 'ravi', 300: 'shiva'}
10. KeyError: 400
d.clear()
To remove all entries from the dictionary
Eg:
2. print(d)
3. d.clear()
4. print(d)
5.
6. Output
7. {100: 'durga', 200: 'ravi', 300: 'shiva'}
8. {}
del d
To delete total dictionary.Now we cannot access d
Eg:
2. print(d)
3. del d
4. print(d)
5.
6. Output
7. {100: 'durga', 200: 'ravi', 300: 'shiva'}
8. NameError: name 'd' is not defined
Important functions of dictionary:
1. dict():
To create a dictionary
d=dict() ===>It creates empty dictionary
d=dict({100:"durga",200:"ravi"}) ==>It creates dictionary with specified elements
d=dict([(100,"durga"),(200,"shiva"),(300,"ravi")])==>It creates dictionary with the given
list of tuple elements

nd
2. len()
Returns the number of items in the dictionary
3. clear():
To remove all elements from the dictionary
4. get():
To get the value associated with the key
d.get(key)
If the key is available then returns the corresponding value otherwise returns None.It
wont raise any error.
d.get(key,defaultvalue)
If the key is available then returns the corresponding value otherwise returns default
value.
Eg:
d={100:"durga",200:"ravi",300:"shiva"}
print(d[100]) ==>durga
print(d[400]) ==>KeyError:400
print(d.get(100)) ==durga
print(d.get(400)) ==>None
print(d.get(100,"Guest")) ==durga
print(d.get(400,"Guest")) ==>Guest
3. pop():
d.pop(key)
It removes the entry associated with the specified key and returns the corresponding
value
If the specified key is not available then we will get KeyError
Eg:
1) d={100:"durga",200:"ravi",300:"shiva"}
2) print(d.pop(100))
3) print(d)
4) print(d.pop(400))
5)
6) Output

nd
7) durga
8) {200: 'ravi', 300: 'shiva'}
9) KeyError: 400
4. popitem():
It removes an arbitrary item(key-value) from the dictionaty and returns it.
Eg:
2) print(d)
3) print(d.popitem())
4) print(d)
5)
6) Output
7) {100: 'durga', 200: 'ravi', 300: 'shiva'}
8) (300, 'shiva')
9) {100: 'durga', 200: 'ravi'}
If the dictionary is empty then we will get KeyError
d={}
print(d.popitem()) ==>KeyError: 'popitem(): dictionary is empty'
5. keys():
It returns all keys associated eith dictionary
Eg:
2) print(d.keys())
3) for k in d.keys():
4) print(k)
5)
6) Output
7) dict_keys([100, 200, 300])
8) 100
9) 200
10) 300
6. values():
It returns all values associated with the dictionary

nd
Eg:
2. print(d.values())
3. for v in d.values():
4. print(v)
5.
6. Output
7. dict_values(['durga', 'ravi', 'shiva'])
8. durga
9. ravi
10. shiva
7. items():
It returns list of tuples representing key-value pairs.
[(k,v),(k,v),(k,v)]
Eg:
2. for k,v in d.items():
3. print(k,"--",v)
4.
5. Output
6. 100 -- durga
7. 200 -- ravi
8. 300 -- shiva
8. copy():
To create exactly duplicate dictionary(cloned copy)
d1=d.copy();
9. setdefault():
d.setdefault(k,v)
If the key is already available then this function returns the corresponding value.
If the key is not available then the specified key-value will be added as new item to the
dictionary.

nd
Eg:
2. print(d.setdefault(400,"pavan"))
3. print(d)
4. print(d.setdefault(100,"sachin"))
5. print(d)
6.
7. Output
8. pavan
10. durga
10. update():
d.update(x)
All items present in the dictionary x will be added to dictionary d
Q. Write a program to take dictionary from the keyboard and print the sum
of values?
1. d=eval(input("Enter dictionary:"))
2. s=sum(d.values())
3. print("Sum= ",s)
4.
5. Output
7. Enter dictionary:{'A':100,'B':200,'C':300}
8. Sum= 600
Q. Write a program to find number of occurrences of each letter present in
the given string?
1. word=input("Enter any word: ")
2. d={}
3. for x in word:
4. d[x]=d.get(x,0)+1
5. for k,v in d.items():
6. print(k,"occurred ",v," times")
7.
8. Output
10. Enter any word: mississippi
11. m occurred 1 times
12. i occurred 4 times
13. s occurred 4 times

nd
14. p occurred 2 times
Q. Write a program to find number of occurrences of each vowel present in
the given string?
1. word=input("Enter any word: ")
2. vowels={'a','e','i','o','u'}
3. d={}
4. for x in word:
5. if x in vowels:
6. d[x]=d.get(x,0)+1
7. for k,v in sorted(d.items()):
8. print(k,"occurred ",v," times")
9.
10. Output
12. Enter any word: doganimaldoganimal
13. a occurred 4 times
14. i occurred 2 times
15. o occurred 2 times
Q. Write a program to accept student name and marks from the keyboard
and creates a dictionary. Also display student marks by taking student name
as input?
1) n=int(input("Enter the number of students: "))
2) d={}
3) for i in range(n):
4) name=input("Enter Student Name: ")
5) marks=input("Enter Student Marks: ")
6) d[name]=marks
7) while True:
8) name=input("Enter Student Name to get Marks: ")
9) marks=d.get(name,-1)
10) if marks== -1:
11) print("Student Not Found")
12) else:
13) print("The Marks of",name,"are",marks)
14) option=input("Do you want to find another student marks[Yes|No]")
15) if option=="No":
16) break
17) print("Thanks for using our application")
18)
19) Output
21) Enter the number of students: 5
22) Enter Student Name: sunny
23) Enter Student Marks: 90

nd
24) Enter Student Name: banny
26) Enter Student Name: chinny
28) Enter Student Name: pinny
30) Enter Student Name: vinny
32) Enter Student Name to get Marks: sunny
33) The Marks of sunny are 90
34) Do you want to find another student marks[Yes|No]Yes
35) Enter Student Name to get Marks: durga
36) Student Not Found
37) Do you want to find another student marks[Yes|No]No
38) Thanks for using our application
Dictionary Comprehension:
Comprehension concept applicable for dictionaries also.
1. squares={x:x*x for x in range(1,6)}
2. print(squares)
3. doubles={x:2*x for x in range(1,6)}
4. print(doubles)
5.
6. Output
7. {1: 1, 2: 4, 3: 9, 4: 16, 5: 25}
8. {1: 2, 2: 4, 3: 6, 4: 8, 5: 10}

nd
FUNCTIONS
If a group of statements is repeatedly required then it is not recommended to write these
statements everytime seperately.We have to define these statements as a single unit and
we can call that unit any number of times based on our requirement without rewriting.
This unit is nothing but function.
The main advantage of functions is code Reusability.
Note: In other languages functions are known as methods,procedures,subroutines etc
Python supports 2 types of functions
1. Built in Functions
2. User Defined Functions
1. Built in Functions:
The functions which are coming along with Python software automatically,are called built
in functions or pre defined functions
Eg:
id()
type()
input()
eval()
etc..
2. User Defined Functions:
The functions which are developed by programmer explicitly according to business
requirements ,are called user defined functions.
Syntax to create user defined functions:
def function_name(parameters) :
""" doc string"""
----
-----
return value

nd
Note: While creating functions we can use 2 keywords
1. def (mandatory)
2. return (optional)
Eg 1: Write a function to print Hello
test.py:
1) def wish():
2) print("Hello Good Morning")
3) wish()
4) wish()
5) wish()
Parameters
Parameters are inputs to the function. If a function contains parameters,then at the time
of calling,compulsory we should provide values otherwise,otherwise we will get error.
Eg: Write a function to take name of the student as input and print wish message by
name.
1. def wish(name):
2. print("Hello",name," Good Morning")
3. wish("Durga")
4. wish("Ravi")
5.
6.
8. Hello Durga Good Morning
9. Hello Ravi Good Morning
Eg: Write a function to take number as input and print its square value
1. def squareIt(number):
2. print("The Square of",number,"is", number*number)
3. squareIt(4)
4. squareIt(5)
5.
7. The Square of 4 is 16
8. The Square of 5 is 25

nd
Return Statement:
Function can take input values as parameters and executes business logic, and returns
output to the caller with return statement.
Q. Write a function to accept 2 numbers as input and return sum.
1. def add(x,y):
2. return x+y
3. result=add(10,20)
4. print("The sum is",result)
5. print("The sum is",add(100,200))
6.
7.
9. The sum is 30
10. The sum is 300
If we are not writing return statement then default return value is None
Eg:
1. def f1():
2. print("Hello")
3. f1()
4. print(f1())
5.
6. Output
7. Hello
8. Hello
9. None
Q. Write a function to check whether the given number is even or odd?
1. def even_odd(num):
2. if num%2==0:
3. print(num,"is Even Number")
4. else:
5. print(num,"is Odd Number")
6. even_odd(10)
7. even_odd(15)
8.
9. Output
11. 10 is Even Number
12. 15 is Odd Number

nd
Q. Write a function to find factorial of given number?
1) def fact(num):
2) result=1
3) while num>=1:
4) result=result*num
5) num=num-1
6) return result
7) for i in range(1,5):
8) print("The Factorial of",i,"is :",fact(i))
9)
10) Output
12) The Factorial of 1 is : 1
Returning multiple values from a function:
In other languages like C,C++ and Java, function can return atmost one value. But in
Python, a function can return any number of values.
Eg 1:
1) def sum_sub(a,b):
2) sum=a+b
3) sub=a-b
4) return sum,sub
5) x,y=sum_sub(100,50)
6) print("The Sum is :",x)
7) print("The Subtraction is :",y)
8)
9) Output
10) The Sum is : 150
11) The Subtraction is : 50
Eg 2:
1) def calc(a,b):
2) sum=a+b
3) sub=a-b
4) mul=a*b
5) div=a/b
6) return sum,sub,mul,div
7) t=calc(100,50)
8) print("The Results are")

nd
9) for i in t:
10) print(i)
11)
12) Output
13) The Results are
14) 150
15) 50
16) 5000
17) 2.0
Types of arguments
def f1(a,b):
------
------
------
f1(10,20)
a,b are formal arguments where as 10,20 are actual arguments
There are 4 types are actual arguments are allowed in Python.
1. positional arguments
2. keyword arguments
3. default arguments
4. Variable length arguments
1. positional arguments:
These are the arguments passed to function in correct positional order.
def sub(a,b):
print(a-b)
sub(100,200)
sub(200,100)
The number of arguments and position of arguments must be matched. If we change the
order then result may be changed.
If we change the number of arguments then we will get error.

nd
2. keyword arguments:
We can pass argument values by keyword i.e by parameter name.
Eg:
1. def wish(name,msg):
2. print("Hello",name,msg)
3. wish(name="Durga",msg="Good Morning")
4. wish(msg="Good Morning",name="Durga")
5.
6. Output
Here the order of arguments is not important but number of arguments must be matched.
Note:
We can use both positional and keyword arguments simultaneously. But first we have to
take positional arguments and then keyword arguments,otherwise we will get
syntaxerror.
def wish(name,msg):
print("Hello",name,msg)
wish("Durga","GoodMorning") ==>valid
wish("Durga",msg="GoodMorning") ==>valid
wish(name="Durga","GoodMorning") ==>invalid
SyntaxError: positional argument follows keyword argument
3. Default Arguments:
Sometimes we can provide default values for our positional arguments.
Eg:
1) def wish(name="Guest"):
2) print("Hello",name,"Good Morning")
3)
4) wish("Durga")
5) wish()
6)
7) Output
9) Hello Guest Good Morning

nd
If we are not passing any name then only default value will be considered.
***Note:
After default arguments we should not take non default arguments
def wish(name="Guest",msg="Good Morning"): ===>Valid
def wish(name,msg="Good Morning"): ===>Valid
def wish(name="Guest",msg): ==>Invalid
SyntaxError: non-default argument follows default argument
4. Variable length arguments:
Sometimes we can pass variable number of arguments to our function,such type of
arguments are called variable length arguments.
We can declare a variable length argument with * symbol as follows
def f1(*n):
We can call this function by passing any number of arguments including zero number.
Internally all these values represented in the form of tuple.
Eg:
1) def sum(*n):
2) total=0
3) for n1 in n:
4) total=total+n1
5) print("The Sum=",total)
6)
7) sum()
8) sum(10)
9) sum(10,20)
10) sum(10,20,30,40)
11)
12) Output
13) The Sum= 0
14) The Sum= 10
15) The Sum= 30
16) The Sum= 100
Note:
We can mix variable length arguments with positional arguments.

nd
Eg:
1) def f1(n1,*s):
2) print(n1)
3) for s1 in s:
4) print(s1)
5)
6) f1(10)
7) f1(10,20,30,40)
8) f1(10,"A",30,"B")
9)
10) Output
11) 10
12) 10
13) 20
14) 30
15) 40
16) 10
17) A
18) 30
19) B
Note: After variable length argument,if we are taking any other arguments then we
should provide values as keyword arguments.
Eg:
1) def f1(*s,n1):
2) for s1 in s:
3) print(s1)
4) print(n1)
5)
6) f1("A","B",n1=10)
7) Output
8) A
9) B
10) 10
f1("A","B",10) ==>Invalid
TypeError: f1() missing 1 required keyword-only argument: 'n1'
Note: We can declare key word variable length arguments also.
For this we have to use **.
def f1(**n):

nd
We can call this function by passing any number of keyword arguments. Internally these
keyword arguments will be stored inside a dictionary.
Eg:
1) def display(**kwargs):
2) for k,v in kwargs.items():
3) print(k,"=",v)
4) display(n1=10,n2=20,n3=30)
5) display(rno=100,name="Durga",marks=70,subject="Java")
6)
7) Output
8) n1 = 10
9) n2 = 20
10) n3 = 30
11) rno = 100
12) name = Durga
13) marks = 70
14) subject = Java
Case Study:
def f(arg1,arg2,arg3=4,arg4=8):
print(arg1,arg2,arg3,arg4)
1. f(3,2) ==> 3 2 4 8
2. f(10,20,30,40) ===>10 20 30 40
3. f(25,50,arg4=100) ==>25 50 4 100
4. f(arg4=2,arg1=3,arg2=4)===>3 4 4 2
5. f()===>Invalid
TypeError: f() missing 2 required positional arguments: 'arg1' and 'arg2'
6. f(arg3=10,arg4=20,30,40) ==>Invalid
SyntaxError: positional argument follows keyword argument
[After keyword arguments we should not take positional arguments]
7. f(4,5,arg2=6)==>Invalid
TypeError: f() got multiple values for argument 'arg2'
8. f(4,5,arg3=5,arg5=6)==>Invalid
TypeError: f() got an unexpected keyword argument 'arg5'

nd
Note: Function vs Module vs Library:
1. A group of lines with some name is called a function
2. A group of functions saved to a file , is called Module
3. A group of Modules is nothing but Library
Types of Variables
Python supports 2 types of variables.
1. Global Variables
2. Local Variables
1. Global Variables
The variables which are declared outside of function are called global variables.
These variables can be accessed in all functions of that module.
Eg:
1) a=10 # global variable
2) def f1():
3) print(a)
4)
5) def f2():
6) print(a)
7)
8) f1()
9) f2()
10)
11) Output
12) 10
13) 10
Function 1
Function 2
Function 3
Module 1
Function 1
Function 2
Function 3
Module 2
Library
-----------------
-----------------
-----------------
-----------------
-----------------
-----------------
-----------------
-----------------
-----------------
-
Function

nd
2. Local Variables:
The variables which are declared inside a function are called local variables.
Local variables are available only for the function in which we declared it.i.e from outside
of function we cannot access.
Eg:
1) def f1():
2) a=10
3) print(a) # valid
4)
5) def f2():
6) print(a) #invalid
7)
8) f1()
9) f2()
10)
11) NameError: name 'a' is not defined
global keyword:
We can use global keyword for the following 2 purposes:
1. To declare global variable inside function
2. To make global variable available to the function so that we can perform required
modifications
Eg 1:
1) a=10
2) def f1():
3) a=777
4) print(a)
5)
6) def f2():
7) print(a)
8)
9) f1()
10) f2()
11)
12) Output
13) 777
14) 10

nd
Eg 2:
1) a=10
2) def f1():
3) global a
4) a=777
5) print(a)
6)
7) def f2():
8) print(a)
9)
10) f1()
11) f2()
12)
13) Output
14) 777
15) 777
Eg 3:
1) def f1():
2) a=10
3) print(a)
4)
5) def f2():
6) print(a)
7)
8) f1()
9) f2()
10)
11) NameError: name 'a' is not defined
Eg 4:
1) def f1():
2) global a
3) a=10
4) print(a)
5)
6) def f2():
7) print(a)
8)
9) f1()
10) f2()
11)
12) Output
13) 10
14) 10

nd
Note: If global variable and local variable having the same name then we can access
global variable inside a function as follows
1) a=10 #global variable
2) def f1():
3) a=777 #local variable
4) print(a)
5) print(globals()['a'])
6) f1()
7)
8)
9) Output
10) 777
11) 10
Recursive Functions
A function that calls itself is known as Recursive Function.
Eg:
factorial(3)=3*factorial(2)
=3*2*factorial(1)
=3*2*1*factorial(0)
=3*2*1*1
=6
factorial(n)= n*factorial(n-1)
The main advantages of recursive functions are:
1. We can reduce length of the code and improves readability
2. We can solve complex problems very easily.
Q. Write a Python Function to find factorial of given number with recursion.
Eg:
1) def factorial(n):
2) if n==0:
3) result=1
4) else:
5) result=n*factorial(n-1)
6) return result
7) print("Factorial of 4 is :",factorial(4))
8) print("Factorial of 5 is :",factorial(5))
9)
10) Output

nd
11) Factorial of 4 is : 24
12) Factorial of 5 is : 120
Anonymous Functions:
Sometimes we can declare a function without any name,such type of nameless functions
are called anonymous functions or lambda functions.
The main purpose of anonymous function is just for instant use(i.e for one time usage)
Normal Function:
We can define by using def keyword.
def squareIt(n):
return n*n
lambda Function:
We can define by using lambda keyword
lambda n:n*n
Syntax of lambda Function:
lambda argument_list : expression
Note: By using Lambda Functions we can write very concise code so that readability of
the program will be improved.
Q. Write a program to create a lambda function to find square of given
number?
1) s=lambda n:n*n
2) print("The Square of 4 is :",s(4))
3) print("The Square of 5 is :",s(5))
4)
5) Output
6) The Square of 4 is : 16
7) The Square of 5 is : 25
Q. Lambda function to find sum of 2 given numbers
1) s=lambda a,b:a+b
2) print("The Sum of 10,20 is:",s(10,20))

nd
3) print("The Sum of 100,200 is:",s(100,200))
4)
5) Output
6) The Sum of 10,20 is: 30
7) The Sum of 100,200 is: 300
Q. Lambda Function to find biggest of given values.
1) s=lambda a,b:a if a>b else b
2) print("The Biggest of 10,20 is:",s(10,20))
3) print("The Biggest of 100,200 is:",s(100,200))
4)
5) Output
6) The Biggest of 10,20 is: 20
7) The Biggest of 100,200 is: 200
Note:
Lambda Function internally returns expression value and we are not required to write
return statement explicitly.
Note: Sometimes we can pass function as argument to another function. In such cases
lambda functions are best choice.
We can use lambda functions very commonly with filter(),map() and reduce() functions,b'z
these functions expect function as argument.
filter() function:
We can use filter() function to filter values from the given sequence based on some
condition.
filter(function,sequence)
where function argument is responsible to perform conditional check
sequence can be list or tuple or string.
Q. Program to filter only even numbers from the list by using filter()
function?
without lambda Function:
1) def isEven(x):
2) if x%2==0:
3) return True
4) else:

nd
5) return False
6) l=[0,5,10,15,20,25,30]
7) l1=list(filter(isEven,l))
8) print(l1) #[0,10,20,30]
with lambda Function:
1) l=[0,5,10,15,20,25,30]
2) l1=list(filter(lambda x:x%2==0,l))
3) print(l1) #[0,10,20,30]
4) l2=list(filter(lambda x:x%2!=0,l))
5) print(l2) #[5,15,25]
map() function:
For every element present in the given sequence,apply some functionality and generate
new element with the required modification. For this requirement we should go for
map() function.
Eg: For every element present in the list perform double and generate new list of doubles.
Syntax:
map(function,sequence)
The function can be applied on each element of sequence and generates new sequence.
Eg: Without lambda
1) l=[1,2,3,4,5]
2) def doubleIt(x):
3) return 2*x
4) l1=list(map(doubleIt,l))
5) print(l1) #[2, 4, 6, 8, 10]
with lambda
1) l=[1,2,3,4,5]
2) l1=list(map(lambda x:2*x,l))
3) print(l1) #[2, 4, 6, 8, 10]
-------------------------------------------------------------

nd
Eg 2: To find square of given numbers
1. l=[1,2,3,4,5]
2. l1=list(map(lambda x:x*x,l))
3. print(l1) #[1, 4, 9, 16, 25]
We can apply map() function on multiple lists also.But make sure all list should have same
length.
Syntax: map(lambda x,y:x*y,l1,l2))
x is from l1 and y is from l2
Eg:
1. l1=[1,2,3,4]
2. l2=[2,3,4,5]
3. l3=list(map(lambda x,y:x*y,l1,l2))
4. print(l3) #[2, 6, 12, 20]
reduce() function:
reduce() function reduces sequence of elements into a single element by applying the
specified function.
reduce(function,sequence)
reduce() function present in functools module and hence we should write import
statement.
Eg:
1) from functools import *
2) l=[10,20,30,40,50]
3) result=reduce(lambda x,y:x+y,l)
4) print(result) # 150
Eg:
1) result=reduce(lambda x,y:x*y,l)
2) print(result) #12000000
Eg:
1) from functools import *
2) result=reduce(lambda x,y:x+y,range(1,101))
3) print(result) #5050

nd
Note:
 In Python every thing is treated as object.
 Even functions also internally treated as objects only.
Eg:
1) def f1():
2) print("Hello")
3) print(f1)
4) print(id(f1))
Output
<function f1 at 0x00419618>
4298264
Function Aliasing:
For the existing function we can give another name, which is nothing but function aliasing.
Eg:
1) def wish(name):
2) print("Good Morning:",name)
3)
4) greeting=wish
5) print(id(wish))
6) print(id(greeting))
7)
8) greeting('Durga')
9) wish('Durga')
Output
4429336
4429336
Good Morning: Durga
Good Morning: Durga
Note: In the above example only one function is available but we can call that function by using
either wish name or greeting name.
If we delete one name still we can access that function by using alias name
Eg:
1) def wish(name):
2) print("Good Morning:",name)

nd
3)
4) greeting=wish
5)
6) greeting('Durga')
7) wish('Durga')
8)
9) del wish
10) #wish('Durga') ==>NameError: name 'wish' is not defined
11) greeting('Pavan')
Output
Good Morning: Durga
Good Morning: Durga
Good Morning: Pavan
Nested Functions:
We can declare a function inside another function, such type of functions are called Nested
functions.
Eg:
1) def outer():
2) print("outer function started")
3) def inner():
4) print("inner function execution")
5) print("outer function calling inner function")
6) inner()
7) outer()
8) #inner() ==>NameError: name 'inner' is not defined
Output
outer function started
outer function calling inner function
inner function execution
In the above example inner() function is local to outer() function and hence it is not possible to call
directly from outside of outer() function.
Note: A function can return another function.
Eg:
1) def outer():
2) print("outer function started")
3) def inner():
4) print("inner function execution")

nd
5) print("outer function returning inner function")
6) return inner
7) f1=outer()
8) f1()
9) f1()
10) f1()
Output
outer function started
outer function returning inner function
Q. What is the differenece between the following lines?
f1 = outer
f1 = outer()
 In the first case for the outer() function we are providing another name f1(function aliasing).
 But in the second case we calling outer() function,which returns inner function.For that inner
function() we are providing another name f1
Note: We can pass function as argument to another function
Eg: filter(function,sequence)
map(function,sequence)
reduce(function,sequence)

nd
Function Decorators:
Decorator is a function which can take a function as argument and extend its functionality
and returns modified function with extended functionality.
The main objective of decorator functions is we can extend the functionality of existing
functions without modifies that function.
1) def wish(name):
This function can always print same output for any name
Hello Durga Good Morning
Hello Ravi Good Morning
Hello Sunny Good Morning
But we want to modify this function to provide different message if name is Sunny.
We can do this without touching wish() function by using decorator.
Eg:
1) def decor(func):
2) def inner(name):
3) if name=="Sunny":
4) print("Hello Sunny Bad Morning")
5) else:
6) func(name)
7) return inner
8)
9) @decor
10) def wish(name):
12)
13) wish("Durga")
14) wish("Ravi")
15) wish("Sunny")
16)
Decorator
Input Function
wish()
new(add some functionality)
inner()
Decorator
Function
Input Function Output Function with
extended Functionality

nd
17) Output
19) Hello Ravi Good Morning
20) Hello Sunny Bad Morning
In the above program whenever we call wish() function automatically decor function will
be executed.
How to call same function with decorator and without decorator:
We should not use @decor
1) def decor(func):
2) def inner(name):
3) if name=="Sunny":
4) print("Hello Sunny Bad Morning")
5) else:
6) func(name)
7) return inner
8)
9)
10) def wish(name):
12)
13) decorfunction=decor(wish)
14)
15) wish("Durga") #decorator wont be executed
16) wish("Sunny") #decorator wont be executed
17)
18) decorfunction("Durga")#decorator will be executed
19) decorfunction("Sunny")#decorator will be executed
20)
21) Output
23) Hello Sunny Good Morning
25) Hello Sunny Bad Morning
Eg 2:
1) def smart_division(func):
2) def inner(a,b):
3) print("We are dividing",a,"with",b)
4) if b==0:
5) print("OOPS...cannot divide")
6) return
7) else:
8) return func(a,b)

nd
9) return inner
10)
11) @smart_division
12) def division(a,b):
13) return a/b
14)
15) print(division(20,2))
17)
18) without decorator we will get Error.In this case output is:
19)
20) 10.0
21) Traceback (most recent call last):
22) File "test.py", line 16, in <module>
24) File "test.py", line 13, in division
25) return a/b
26) ZeroDivisionError: division by zero
with decorator we won't get any error. In this case output is:
We are dividing 20 with 2
10.0
We are dividing 20 with 0
OOPS...cannot divide
None
Decorator Chaining
We can define multiple decorators for the same function and all these decorators will
form Decorator Chaining.
Eg:
@decor1
@decor
def num():
For num() function we are applying 2 decorator functions. First inner decorator will work
and then outer decorator.
Eg:
1) def decor1(func):
2) def inner():
3) x=func()
4) return x*x

nd
5) return inner
6)
7) def decor(func):
8) def inner():
9) x=func()
10) return 2*x
11) return inner
12)
13) @decor1
14) @decor
15) def num():
16) return 10
17)
18) print(num())
Demo Program for decorator Chaining:
1) def decor(func):
2) def inner(name):
3) print("First Decor(decor) Function Execution")
4) func(name)
5) return inner
6)
7) def decor1(func):
8) def inner(name):
9) print("Second Decor(decor1) Execution")
10) func(name)
11) return inner
12)
13) @decor1
14) @decor
15) def wish(name):
17)
18) wish("Durga")
D:durgaclasses>py decaratordemo1.py
Second Decor(decor1) Execution
First Decor(decor) Function Execution
Hello Durga Good Morning

nd
Generators
Generator is a function which is responsible to generate a sequence of values.
We can write generator functions just like ordinary functions, but it uses yield keyword to
return values.
Eg 1:
1) def mygen():
2) yield 'A'
3) yield 'B'
4) yield 'C'
5)
6) g=mygen()
7) print(type(g))
8)
9) print(next(g))
10) print(next(g))
11) print(next(g))
12) print(next(g))
13)
14) Output
15) <class 'generator'>
16) A
17) B
18) C
21) print(next(g))
22) StopIteration
Eg 2:
1) def countdown(num):
2) print("Start Countdown")
3) while(num>0):
4) yield num
5) num=num-1
6)
7) values=countdown(5)
8) for x in values:
Generator
Function
A Sequence of Values
yield

nd
9) print(x)
10)
11) Output
12) Start Countdown
13) 5
14) 4
15) 3
16) 2
17) 1
Eg 3: To generate first n numbers:
1) def firstn(num):
2) n=1
3) while n<=num:
4) yield n
5) n=n+1
6)
7) values=firstn(5)
8) for x in values:
9) print(x)
10)
11) Output
12) 1
13) 2
14) 3
15) 4
16) 5
We can convert generator into list as follows:
values=firstn(10)
l1=list(values)
print(l1) #[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
Eg 4: To generate Fibonacci Numbers...
The next is the sum of previous 2 numbers
Eg: 0,1,1,2,3,5,8,13,21,...
1) def fib():
2) a,b=0,1
3) while True:
4) yield a
5) a,b=b,a+b
6) for f in fib():
7) if f>100:
8) break
9) print(f)

nd
10)
11) Output
12) 0
13) 1
14) 1
15) 2
16) 3
17) 5
18) 8
19) 13
20) 21
21) 34
22) 55
23) 89
Advantages of Generator Functions:
1. when compared with class level iterators, generators are very easy to use
2. Improves memory utilization and performance.
3. Generators are best suitable for reading data from large number of large files
4. Generators work great for web scraping and crawling.
Generators vs Normal Collections wrt performance:
1) import random
2) import time
3)
4) names = ['Sunny','Bunny','Chinny','Vinny']
5) subjects = ['Python','Java','Blockchain']
6)
7) def people_list(num_people):
8) results = []
9) for i in range(num_people):
10) person = {
11) 'id':i,
12) 'name': random.choice(names),
13) 'subject':random.choice(subjects)
14) }
15) results.append(person)
16) return results
17)
18) def people_generator(num_people):
19) for i in range(num_people):
20) person = {
21) 'id':i,
22) 'name': random.choice(names),
23) 'major':random.choice(subjects)

nd
24) }
25) yield person
26)
27) '''''t1 = time.clock()
28) people = people_list(10000000)
29) t2 = time.clock()'''
30)
31) t1 = time.clock()
32) people = people_generator(10000000)
33) t2 = time.clock()
34)
35) print('Took {}'.format(t2-t1))
Note: In the above program observe the differnce wrt execution time by using list and generators
Generators vs Normal Collections wrt Memory Utilization:
Normal Collection:
l=[x*x for x in range(10000000000000000)]
print(l[0])
We will get MemoryError in this case because all these values are required to store in the memory.
Generators:
g=(x*x for x in range(10000000000000000))
print(next(g))
Output: 0
We won't get any MemoryError because the values won't be stored at the beginning

nd
Modules
A group of functions, variables and classes saved to a file, which is nothing but module.
Every Python file (.py) acts as a module.
Eg: durgamath.py
1) x=888
2)
3) def add(a,b):
4) print("The Sum:",a+b)
5)
6) def product(a,b):
7) print("The Product:",a*b)
durgamath module contains one variable and 2 functions.
If we want to use members of module in our program then we should import that module.
import modulename
We can access members by using module name.
modulename.variable
modulename.function()
test.py:
1) import durgamath
2) print(durgamath.x)
3) durgamath.add(10,20)
4) durgamath.product(10,20)
5)
6) Output
7) 888
8) The Sum: 30
9) The Product: 200

nd
Note:
whenever we are using a module in our program, for that module compiled file will be
generated and stored in the hard disk permanently.
Renaming a module at the time of import (module aliasing):
Eg:
import durgamath as m
here durgamath is original module name and m is alias name.
We can access members by using alias name m
test.py:
1) import durgamath as m
2) print(m.x)
3) m.add(10,20)
4) m.product(10,20)
from ... import:
We can import particular members of module by using from ... import .
The main advantage of this is we can access members directly without using module
name.
Eg:
from durgamath import x,add
print(x)
add(10,20)
product(10,20)==> NameError: name 'product' is not defined
We can import all members of a module as follows
from durgamath import *
test.py:
1) from durgamath import *
2) print(x)
3) add(10,20)
4) product(10,20)

nd
Various possibilties of import:
import modulename
import module1,module2,module3
import module1 as m
import module1 as m1,module2 as m2,module3
from module import member
from module import member1,member2,memebr3
from module import memeber1 as x
from module import *
member aliasing:
from durgamath import x as y,add as sum
print(y)
sum(10,20)
Once we defined as alias name,we should use alias name only and we should not use
original name
Eg:
from durgamath import x as y
print(x)==>NameError: name 'x' is not defined
Reloading a Module:
By default module will be loaded only once eventhough we are importing multiple
multiple times.
Demo Program for module reloading:
1) import time
2) from imp import reload
3) import module1
4) time.sleep(30)
5) reload(module1)
6) time.sleep(30)
7) reload(module1)
8) print("This is test file")
Note: In the above program, everytime updated version of module1 will be available to
our program

nd
module1.py:
print("This is from module1")
test.py
1) import module1
2) import module1
3) import module1
4) import module1
5) print("This is test module")
6)
7) Output
8) This is from module1
9) This is test module
In the above program test module will be loaded only once eventhough we are importing
multiple times.
The problem in this approach is after loading a module if it is updated outside then
updated version of module1 is not available to our program.
We can solve this problem by reloading module explicitly based on our requirement.
We can reload by using reload() function of imp module.
import imp
imp.reload(module1)
test.py:
1) import module1
2) import module1
3) from imp import reload
4) reload(module1)
5) reload(module1)
6) reload(module1)
7) print("This is test module")
In the above program module1 will be loaded 4 times in that 1 time by default and 3 times
explicitly. In this case output is
5) This is test module

nd
The main advantage of explicit module reloading is we can ensure that updated version is
always available to our program.
Finding members of module by using dir() function:
Python provides inbuilt function dir() to list out all members of current module or a
specified module.
dir() ===>To list out all members of current module
dir(moduleName)==>To list out all members of specified module
Eg 1: test.py
1) x=10
2) y=20
3) def f1():
4) print("Hello")
5) print(dir()) # To print all members of current module
6)
7) Output
8) ['__annotations__', '__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__nam
e__', '__package__', '__spec__', 'f1', 'x', 'y']
Eg 2: To display members of particular module:
durgamath.py:
1) x=888
2)
3) def add(a,b):
4) print("The Sum:",a+b)
5)
6) def product(a,b):
7) print("The Product:",a*b)
test.py:
1) import durgamath
2) print(dir(durgamath))
3)
4) Output
5) ['__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__',
6) '__package__', '__spec__', 'add', 'product', 'x']
Note: For every module at the time of execution Python interpreter will add some special
properties automatically for internal use.

nd
Eg: __builtins__,__cached__,'__doc__,__file__, __loader__, __name__,__package__,
__spec__
Based on our requirement we can access these properties also in our program.
Eg: test.py:
1) print(__builtins__ )
2) print(__cached__ )
3) print(__doc__)
4) print(__file__)
5) print(__loader__)
6) print(__name__)
7) print(__package__)
8) print(__spec__)
9)
10) Output
11) <module 'builtins' (built-in)>
12) None
13) None
test.py
1) <_frozen_importlib_external.SourceFileLoader object at 0x00572170>
2) __main__
3) None
4) None
The Special variable __name__:
For every Python program , a special variable __name__ will be added internally.
This variable stores information regarding whether the program is executed as an
individual program or as a module.
If the program executed as an individual program then the value of this variable is
__main__
If the program executed as a module from some other program then the value of this
variable is the name of module where it is defined.
Hence by using this __name__ variable we can identify whether the program executed
directly or as a module.

nd
Demo program:
module1.py:
1) def f1():
2) if __name__=='__main__':
3) print("The code executed as a program")
4) else:
5) print("The code executed as a module from some other program")
6) f1()
test.py:
1) import module1
2) module1.f1()
3)
4) D:Python_classes>py module1.py
5) The code executed as a program
6)
8) The code executed as a module from some other program
9) The code executed as a module from some other program
Working with math module:
Python provides inbuilt module math.
This module defines several functions which can be used for mathematical operations.
The main important functions are
1. sqrt(x)
2. ceil(x)
3. floor(x)
4. fabs(x)
5.log(x)
6. sin(x)
7. tan(x)
....
Eg:
1) from math import *
2) print(sqrt(4))
3) print(ceil(10.1))
4) print(floor(10.1))
5) print(fabs(-10.6))
6) print(fabs(10.6))

nd
7)
8) Output
9) 2.0
10) 11
11) 10
12) 10.6
13) 10.6
Note:
We can find help for any module by using help() function
Eg:
import math
help(math)
Working with random module:
This module defines several functions to generate random numbers.
We can use these functions while developing games,in cryptography and to generate
random numbers on fly for authentication.
1. random() function:
This function always generate some float value between 0 and 1 ( not inclusive)
0<x<1
Eg:
1) from random import *
3) print(random())
4)
5) Output
6) 0.4572685609302056
7) 0.6584325233197768
8) 0.15444034016553587
9) 0.18351427005232201
10) 0.1330257265904884
11) 0.9291139798071045
12) 0.6586741197891783
13) 0.8901649834019002
14) 0.25540891083913053
15) 0.7290504335962871

nd
2. randint() function:
To generate random integer beween two given numbers(inclusive)
Eg:
3) print(randint(1,100)) # generate random int value between 1 and 100(inclusive)
4)
5) Output
6) 51
7) 44
8) 39
9) 70
10) 49
11) 74
12) 52
13) 10
14) 40
15) 8
3. uniform():
It returns random float values between 2 given numbers(not inclusive)
Eg:
3) print(uniform(1,10))
4)
5) Output
6) 9.787695398230332
7) 6.81102218793548
8) 8.068672144377329
9) 8.567976357239834
10) 6.363511674803802
11) 2.176137584071641
12) 4.822867939432386
13) 6.0801725149678445
14) 7.508457735544763
15) 1.9982221862917555
random() ===>in between 0 and 1 (not inclusive)
randint(x,y) ==>in between x and y ( inclusive)
uniform(x,y) ==> in between x and y ( not inclusive)

nd
4. randrange([start],stop,[step])
returns a random number from range
start<= x < stop
start argument is optional and default value is 0
step argument is optional and default value is 1
randrange(10)-->generates a number from 0 to 9
randrange(1,11)-->generates a number from 1 to 10
randrange(1,11,2)-->generates a number from 1,3,5,7,9
Eg 1:
3) print(randrange(10))
4)
5) Output
6) 9
7) 4
8) 0
9) 2
10) 9
11) 4
12) 8
13) 9
14) 5
15) 9
Eg 2:
3) print(randrange(1,11))
4)
5) Output
6) 2
7) 2
8) 8
9) 10
10) 3
11) 5
12) 9
13) 1
14) 6
15) 3

nd
Eg 3:
3) print(randrange(1,11,2))
4)
5) Output
6) 1
7) 3
8) 9
9) 5
10) 7
11) 1
12) 1
13) 1
14) 7
15) 3
5. choice() function:
It wont return random number.
It will return a random object from the given list or tuple.
Eg:
2) list=["Sunny","Bunny","Chinny","Vinny","pinny"]
4) print(choice(list))
Output
Bunny
pinny
Bunny
Sunny
Bunny
pinny
pinny
Vinny
Bunny
Sunny

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Packages
It is an encapsulation mechanism to group related modules into a single unit.
package is nothing but folder or directory which represents collection of Python modules.
Any folder or directory contains __init__.py file,is considered as a Python package.This file
can be empty.
A package can contains sub packages also.
File 1
x.py y.py
Home Loan
__init__.py
File 1
m.py n.py
Vehicle Loan
__init__.py
Loan
File 1
__init__.py

nd
The main advantages of package statement are
1. We can resolve naming conflicts
2. We can identify our components uniquely
3. It improves modularity of the application
Eg 1:
D:Python_classes>
|-test.py
|-pack1
|-module1.py
|-__init__.py
__init__.py:
empty file
module1.py:
def f1():
print("Hello this is from module1 present in pack1")
test.py (version-1):
import pack1.module1
pack1.module1.f1()
Loan
File 1
__init__.py
File 1
Module 1
Home Loan
Module 1
__init__.py
Vehicle Loan
File 1
Module 1 Module 1
__init__.py

nd
test.py (version-2):
from pack1.module1 import f1
f1()
Eg 2:
D:Python_classes>
|-test.py
|-com
|-module1.py
|-__init__.py
|-durgasoft
|-module2.py
|-__init__.py
__init__.py:
empty file
module1.py:
def f1():
print("Hello this is from module1 present in com")
module2.py:
def f2():
print("Hello this is from module2 present in com.durgasoft")
test.py:
1. from com.module1 import f1
2. from com.durgasoft.module2 import f2
3. f1()
4. f2()
5.
6. Output
8. Hello this is from module1 present in com
9. Hello this is from module2 present in com.durgasoft
Note: Summary diagram of library,packages,modules which contains functions,classes
and variables.

nd
module 1 module 2 module n
Library
pack 1 pack 2 --------------- pack n
module 1 module 2 module n
function 1 function 2 function n variables classes

nd
File Handling
As the part of programming requirement, we have to store our data permanently for
future purpose. For this requirement we should go for files.
Files are very common permanent storage areas to store our data.
Types of Files:
There are 2 types of files
1. Text Files:
Usually we can use text files to store character data
eg: abc.txt
2. Binary Files:
Usually we can use binary files to store binary data like images,video files, audio files etc...
Opening a File:
Before performing any operation (like read or write) on the file,first we have to open that
file.For this we should use Python's inbuilt function open()
But at the time of open, we have to specify mode,which represents the purpose of
opening file.
f = open(filename, mode)
The allowed modes in Python are
1. r  open an existing file for read operation. The file pointer is positioned at the
beginning of the file.If the specified file does not exist then we will get
FileNotFoundError.This is default mode.

nd
2. w  open an existing file for write operation. If the file already contains some data
then it will be overridden. If the specified file is not already avaialble then this mode will
create that file.
3. a  open an existing file for append operation. It won't override existing data.If the
specified file is not already avaialble then this mode will create a new file.
4. r+  To read and write data into the file. The previous data in the file will not be
deleted.The file pointer is placed at the beginning of the file.
5. w+  To write and read data. It will override existing data.
6. a+  To append and read data from the file.It wont override existing data.
7. x  To open a file in exclusive creation mode for write operation. If the file already
exists then we will get FileExistsError.
Note: All the above modes are applicable for text files. If the above modes suffixed with
'b' then these represents for binary files.
Eg: rb,wb,ab,r+b,w+b,a+b,xb
f = open("abc.txt","w")
We are opening abc.txt file for writing data.
Closing a File:
After completing our operations on the file,it is highly recommended to close the file.
For this we have to use close() function.
f.close()
Various properties of File Object:
Once we opend a file and we got file object,we can get various details related to that file
by using its properties.
name  Name of opened file
mode  Mode in which the file is opened
closed  Returns boolean value indicates that file is closed or not
readable() Retruns boolean value indicates that whether file is readable or not
writable() Returns boolean value indicates that whether file is writable or not.

nd
Eg:
1) f=open("abc.txt",'w')
2) print("File Name: ",f.name)
3) print("File Mode: ",f.mode)
4) print("Is File Readable: ",f.readable())
5) print("Is File Writable: ",f.writable())
6) print("Is File Closed : ",f.closed)
7) f.close()
8) print("Is File Closed : ",f.closed)
9)
10)
11) Output
13) File Name: abc.txt
14) File Mode: w
15) Is File Readable: False
16) Is File Writable: True
17) Is File Closed : False
18) Is File Closed : True
Writing data to text files:
We can write character data to the text files by using the following 2 methods.
write(str)
writelines(list of lines)
Eg:
1) f=open("abcd.txt",'w')
2) f.write("Durgan")
3) f.write("Softwaren")
4) f.write("Solutionsn")
5) print("Data written to the file successfully")
6) f.close()
abcd.txt:
Durga
Software
Solutions
Note: In the above program, data present in the file will be overridden everytime if we
run the program. Instead of overriding if we want append operation then we should open
the file as follows.
f = open("abcd.txt","a")

nd
Eg 2:
1) f=open("abcd.txt",'w')
2) list=["sunnyn","bunnyn","vinnyn","chinny"]
3) f.writelines(list)
4) print("List of lines written to the file successfully")
5) f.close()
abcd.txt:
sunny
bunny
vinny
chinny
Note: while writing data by using write() methods, compulsory we have to provide line
seperator(n),otherwise total data should be written to a single line.
Reading Character Data from text files:
We can read character data from text file by using the following read methods.
read() To read total data from the file
read(n)  To read 'n' characters from the file
readline() To read only one line
readlines() To read all lines into a list
Eg 1: To read total data from the file
1) f=open("abc.txt",'r')
2) data=f.read()
3) print(data)
4) f.close()
5)
6) Output
7) sunny
8) bunny
9) chinny
10) vinny
Eg 2: To read only first 10 characters:
2) data=f.read(10)
3) print(data)
4) f.close()
5)

nd
6) Output
7) sunny
8) bunn
Eg 3: To read data line by line:
2) line1=f.readline()
3) print(line1,end='')
8) f.close()
9)
10) Output
11) sunny
12) bunny
13) chinny
Eg 4: To read all lines into list:
2) lines=f.readlines()
3) for line in lines:
4) print(line,end='')
5) f.close()
6)
7) Output
8) sunny
9) bunny
10) chinny
11) vinny
Eg 5:
1) f=open("abc.txt","r")
2) print(f.read(3))
3) print(f.readline())
4) print(f.read(4))
5) print("Remaining data")
6) print(f.read())
7)
8) Output
9) sun
10) ny
11)
12) bunn
13) Remaining data

nd
14) y
15) chinny
16) vinny
The with statement:
The with statement can be used while opening a file.We can use this to group file
operation statements within a block.
The advantage of with statement is it will take care closing of file,after completing all
operations automatically even in the case of exceptions also, and we are not required to
close explicitly.
Eg:
1) with open("abc.txt","w") as f:
2) f.write("Durgan")
3) f.write("Softwaren")
4) f.write("Solutionsn")
5) print("Is File Closed: ",f.closed)
6) print("Is File Closed: ",f.closed)
7)
8) Output
9) Is File Closed: False
10) Is File Closed: True
The seek() and tell() methods:
tell():
==>We can use tell() method to return current position of the cursor(file pointer) from
beginning of the file. [ can you plese telll current cursor position]
The position(index) of first character in files is zero just like string index.
Eg:
1) f=open("abc.txt","r")
2) print(f.tell())
3) print(f.read(2))
4) print(f.tell())
5) print(f.read(3))
6) print(f.tell())
abc.txt:
sunny
bunny
chinny
vinny

nd
Output:
0
su
2
nny
5
seek():
We can use seek() method to move cursor(file pointer) to specified location.
[Can you please seek the cursor to a particular location]
f.seek(offset, fromwhere)
offset represents the number of positions
The allowed values for second attribute(from where) are
0---->From beginning of file(default value)
1---->From current position
2--->From end of the file
Note: Python 2 supports all 3 values but Python 3 supports only zero.
Eg:
1) data="All Students are STUPIDS"
2) f=open("abc.txt","w")
3) f.write(data)
4) with open("abc.txt","r+") as f:
5) text=f.read()
6) print(text)
7) print("The Current Cursor Position: ",f.tell())
8) f.seek(17)
9) print("The Current Cursor Position: ",f.tell())
10) f.write("GEMS!!!")
11) f.seek(0)
12) text=f.read()
13) print("Data After Modification:")
14) print(text)
15)
16) Output
17)
18) All Students are STUPIDS
19) The Current Cursor Position: 24
20) The Current Cursor Position: 17
21) Data After Modification:

nd
22) All Students are GEMS!!!
How to check a particular file exists or not?
We can use os library to get information about files in our computer.
os module has path sub module,which contains isFile() function to check whether a
particular file exists or not?
os.path.isfile(fname)
Q. Write a program to check whether the given file exists or not. If it is
available then print its content?
1) import os,sys
2) fname=input("Enter File Name: ")
3) if os.path.isfile(fname):
4) print("File exists:",fname)
5) f=open(fname,"r")
6) else:
7) print("File does not exist:",fname)
8) sys.exit(0)
9) print("The content of file is:")
10) data=f.read()
11) print(data)
12)
13) Output
15) Enter File Name: durga.txt
16) File does not exist: durga.txt
17)
19) Enter File Name: abc.txt
20) File exists: abc.txt
21) The content of file is:
Note:
sys.exit(0) ===>To exit system without executing rest of the program.
argument represents status code . 0 means normal termination and it is the default value.

nd
Q. Program to print the number of lines,words and characters present in the
given file?
1) import os,sys
2) fname=input("Enter File Name: ")
3) if os.path.isfile(fname):
4) print("File exists:",fname)
5) f=open(fname,"r")
6) else:
7) print("File does not exist:",fname)
8) sys.exit(0)
9) lcount=wcount=ccount=0
10) for line in f:
11) lcount=lcount+1
12) ccount=ccount+len(line)
13) words=line.split()
14) wcount=wcount+len(words)
15) print("The number of Lines:",lcount)
16) print("The number of Words:",wcount)
17) print("The number of Characters:",ccount)
18)
19) Output
21) Enter File Name: durga.txt
22) File does not exist: durga.txt
23)
25) Enter File Name: abc.txt
26) File exists: abc.txt
27) The number of Lines: 6
28) The number of Words: 24
29) The number of Characters: 149
abc.txt:
All Students are GEMS!!!

nd
Handling Binary Data:
It is very common requirement to read or write binary data like images,video files,audio
files etc.
Q. Program to read image file and write to a new image file?
1) f1=open("rossum.jpg","rb")
2) f2=open("newpic.jpg","wb")
3) bytes=f1.read()
4) f2.write(bytes)
5) print("New Image is available with the name: newpic.jpg")
Handling csv files:
CSV==>Comma seperated values
As the part of programming,it is very common requirement to write and read data wrt csv
files. Python provides csv module to handle csv files.
Writing data to csv file:
1) import csv
2) with open("emp.csv","w",newline='') as f:
3) w=csv.writer(f) # returns csv writer object
4) w.writerow(["ENO","ENAME","ESAL","EADDR"])
5) n=int(input("Enter Number of Employees:"))
7) eno=input("Enter Employee No:")
9) esal=input("Enter Employee Salary:")
11) w.writerow([eno,ename,esal,eaddr])
12) print("Total Employees data written to csv file successfully")
Note: Observe the difference with newline attribute and without
with open("emp.csv","w",newline='') as f:
with open("emp.csv","w") as f:
Note: If we are not using newline attribute then in the csv file blank lines will be included
between data. To prevent these blank lines, newline attribute is required in Python-3,but
in Python-2 just we can specify mode as 'wb' and we are not required to use newline
attribute.

nd
Reading Data from csv file:
1) import csv
2) f=open("emp.csv",'r')
3) r=csv.reader(f) #returns csv reader object
4) data=list(r)
5) #print(data)
6) for line in data:
7) for word in line:
8) print(word,"t",end='')
9) print()
10)
11) Output
13) ENO ENAME ESAL EADDR
14) 100 Durga 1000 Hyd
15) 200 Sachin 2000 Mumbai
16) 300 Dhoni 3000 Ranchi
Zipping and Unzipping Files:
It is very common requirement to zip and unzip files.
The main advantages are:
1. To improve memory utilization
2. We can reduce transport time
3. We can improve performance.
To perform zip and unzip operations, Python contains one in-bulit module zip file.
This module contains a class : ZipFile
To create Zip file:
We have to create ZipFile class object with name of the zip file,mode and constant
ZIP_DEFLATED. This constant represents we are creating zip file.
f = ZipFile("files.zip","w","ZIP_DEFLATED")
Once we create ZipFile object,we can add files by using write() method.
f.write(filename)

nd
Eg:
1) from zipfile import *
2) f=ZipFile("files.zip",'w',ZIP_DEFLATED)
3) f.write("file1.txt")
6) f.close()
7) print("files.zip file created successfully")
To perform unzip operation:
We have to create ZipFile object as follows
f = ZipFile("files.zip","r",ZIP_STORED)
ZIP_STORED represents unzip operation. This is default value and hence we are not
required to specify.
Once we created ZipFile object for unzip operation,we can get all file names present in
that zip file by using namelist() method.
names = f.namelist()
Eg:
1) from zipfile import *
2) f=ZipFile("files.zip",'r',ZIP_STORED)
3) names=f.namelist()
4) for name in names:
5) print( "File Name: ",name)
6) print("The Content of this file is:")
7) f1=open(name,'r')
8) print(f1.read())
9) print()
Working with Directories:
It is very common requirement to perform operations for directories like
1. To know current working directory
2. To create a new directory
3. To remove an existing directory
4. To rename a directory
5. To list contents of the directory
etc...

nd
To perform these operations,Python provides inbuilt module os,which contains several
functions to perform directory related operations.
Q1. To Know Current Working Directory:
import os
cwd=os.getcwd()
print("Current Working Directory:",cwd)
Q2. To create a sub directory in the current working directory:
import os
os.mkdir("mysub")
print("mysub directory created in cwd")
Q3. To create a sub directory in mysub directory:
cwd
|-mysub
|-mysub2
import os
os.mkdir("mysub/mysub2")
print("mysub2 created inside mysub")
Note: Assume mysub already present in cwd.
Q4. To create multiple directories like sub1 in that sub2 in that sub3:
import os
os.makedirs("sub1/sub2/sub3")
print("sub1 and in that sub2 and in that sub3 directories created")
Q5. To remove a directory:
import os
os.rmdir("mysub/mysub2")
print("mysub2 directory deleted")
Q6. To remove multiple directories in the path:
import os
os.removedirs("sub1/sub2/sub3")
print("All 3 directories sub1,sub2 and sub3 removed")

nd
Q7. To rename a directory:
import os
os.rename("mysub","newdir")
print("mysub directory renamed to newdir")
Q8. To know contents of directory:
os module provides listdir() to list out the contents of the specified directory. It won't
display the contents of sub directory.
Eg:
1) import os
2) print(os.listdir("."))
3)
4) Output
6) ['abc.py', 'abc.txt', 'abcd.txt', 'com', 'demo.py', 'durgamath.py', 'emp.csv', '
7) file1.txt', 'file2.txt', 'file3.txt', 'files.zip', 'log.txt', 'module1.py', 'myl
8) og.txt', 'newdir', 'newpic.jpg', 'pack1', 'rossum.jpg', 'test.py', '__pycache__'
9) ]
The above program display contents of current working directory but not contents of sub
directories.
If we want the contents of a directory including sub directories then we should go for
walk() function.
Q9. To know contents of directory including sub directories:
We have to use walk() function
[Can you please walk in the directory so that we can aware all contents of that directory]
os.walk(path,topdown=True,onerror=None,followlinks=False)
It returns an Iterator object whose contents can be displayed by using for loop
path-->Directory path. cwd means .
topdown=True --->Travel from top to bottom
onerror=None --->on error detected which function has to execute.
followlinks=True -->To visit directories pointed by symbolic links

nd
Eg: To display all contents of Current working directory including sub directories:
1) import os
2) for dirpath,dirnames,filenames in os.walk('.'):
3) print("Current Directory Path:",dirpath)
4) print("Directories:",dirnames)
5) print("Files:",filenames)
6) print()
7)
8)
9) Output
10) Current Directory Path: .
11) Directories: ['com', 'newdir', 'pack1', '__pycache__']
12) Files: ['abc.txt', 'abcd.txt', 'demo.py', 'durgamath.py', 'emp.csv', 'file1.txt'
13) , 'file2.txt', 'file3.txt', 'files.zip', 'log.txt', 'module1.py', 'mylog.txt', '
14) newpic.jpg', 'rossum.jpg', 'test.py']
15)
16) Current Directory Path: .com
17) Directories: ['durgasoft', '__pycache__']
18) Files: ['module1.py', '__init__.py']
19)
20) ...
Note: To display contents of particular directory,we have to provide that directory name
as argument to walk() function.
os.walk("directoryname")
Q. What is the difference between listdir() and walk() functions?
In the case of listdir(), we will get contents of specified directory but not sub directory
contents. But in the case of walk() function we will get contents of specified directory and
its sub directories also.
Running Other programs from Python program:
os module contains system() function to run programs and commands.
It is exactly same as system() function in C language.
os.system("commad string")
The argument is any command which is executing from DOS.
Eg:
import os
os.system("dir *.py")
os.system("py abc.py")

nd
How to get information about a File:
We can get statistics of a file like size, last accessed time,last modified time etc by using
stat() function of os module.
stats = os.stat("abc.txt")
The statistics of a file includes the following parameters:
st_mode==>Protection Bits
st_ino==>Inode number
st_dev===>device
st_nlink===>no of hard links
st_uid===>userid of owner
st_gid==>group id of owner
st_size===>size of file in bytes
st_atime==>Time of most recent access
st_mtime==>Time of Most recent modification
st_ctime==> Time of Most recent meta data change
Note:
st_atime, st_mtime and st_ctime returns the time as number of milli seconds since Jan 1st
1970 ,12:00AM. By using datetime module fromtimestamp() function,we can get exact
date and time.
Q. To print all statistics of file abc.txt:
1) import os
2) stats=os.stat("abc.txt")
3) print(stats)
4)
5) Output
6) os.stat_result(st_mode=33206, st_ino=844424930132788, st_dev=2657980798, st_nlin
7) k=1, st_uid=0, st_gid=0, st_size=22410, st_atime=1505451446, st_mtime=1505538999
8) , st_ctime=1505451446)
Q. To print specified properties:
1) import os
2) from datetime import *
3) stats=os.stat("abc.txt")
4) print("File Size in Bytes:",stats.st_size)
5) print("File Last Accessed Time:",datetime.fromtimestamp(stats.st_atime))
6) print("File Last Modified Time:",datetime.fromtimestamp(stats.st_mtime))
7)

nd
8) Output
9) File Size in Bytes: 22410
10) File Last Accessed Time: 2017-09-15 10:27:26.599490
11) File Last Modified Time: 2017-09-16 10:46:39.245394
Pickling and Unpickling of Objects:
Sometimes we have to write total state of object to the file and we have to read total
object from the file.
The process of writing state of object to the file is called pickling and the process of
reading state of an object from the file is called unpickling.
We can implement pickling and unpickling by using pickle module of Python.
pickle module contains dump() function to perform pickling.
pickle.dump(object,file)
pickle module contains load() function to perform unpickling
obj=pickle.load(file)
e2
eno: 100
ename: Durga
esal: 10000
eaddr: HYD
abc.txt
pickle.dump
(e1, f)
pickling
pickle load (f)
unpickling
eno: 100
ename: Durga
esal: 10000
eaddr: HYD
eno: 100
ename: Durga
esal: 10000
eaddr: HYD
e1

nd
Writing and Reading State of object by using pickle Module:
1) import pickle
2) class Employee:
3) def __init__(self,eno,ename,esal,eaddr):
4) self.eno=eno;
5) self.ename=ename;
6) self.esal=esal;
7) self.eaddr=eaddr;
8) def display(self):
9) print(self.eno,"t",self.ename,"t",self.esal,"t",self.eaddr)
10) with open("emp.dat","wb") as f:
11) e=Employee(100,"Durga",1000,"Hyd")
12) pickle.dump(e,f)
13) print("Pickling of Employee Object completed...")
14)
15) with open("emp.dat","rb") as f:
16) obj=pickle.load(f)
17) print("Printing Employee Information after unpickling")
18) obj.display()
Writing Multiple Employee Objects to the file:
emp.py:
1) class Employee:
2) def __init__(self,eno,ename,esal,eaddr):
3) self.eno=eno;
4) self.ename=ename;
5) self.esal=esal;
6) self.eaddr=eaddr;
8)
9) print(self.eno,"t",self.ename,"t",self.esal,"t",self.eaddr)
pick.py:
1) import emp,pickle
2) f=open("emp.dat","wb")
3) n=int(input("Enter The number of Employees:"))
5) eno=int(input("Enter Employee Number:"))
9) e=emp.Employee(eno,ename,esal,eaddr)
10) pickle.dump(e,f)
11) print("Employee Objects pickled successfully")

nd
unpick.py:
1) import emp,pickle
2) f=open("emp.dat","rb")
3) print("Employee Details:")
4) while True:
5) try:
6) obj=pickle.load(f)
7) obj.display()
8) except EOFError:
9) print("All employees Completed")
10) break
11) f.close()

nd
Exception Handling
In any programming language there are 2 types of errors are possible.
1. Syntax Errors
2. Runtime Errors
1. Syntax Errors:
The errors which occurs because of invalid syntax are called syntax errors.
Eg 1:
x=10
if x==10
print("Hello")
SyntaxError: invalid syntax
Eg 2:
print "Hello"
SyntaxError: Missing parentheses in call to 'print'
Note:
Programmer is responsible to correct these syntax errors. Once all syntax errors are
corrected then only program execution will be started.
2. Runtime Errors:
Also known as exceptions.
While executing the program if something goes wrong because of end user input or
programming logic or memory problems etc then we will get Runtime Errors.
Eg: print(10/0) ==>ZeroDivisionError: division by zero
print(10/"ten") ==>TypeError: unsupported operand type(s) for /: 'int' and 'str'
x=int(input("Enter Number:"))
print(x)
D:Python_classes>py test.py

nd
Enter Number:ten
ValueError: invalid literal for int() with base 10: 'ten'
Note: Exception Handling concept applicable for Runtime Errors but not for syntax errors
What is Exception:
An unwanted and unexpected event that disturbs normal flow of program is called
exception.
Eg:
ZeroDivisionError
TypeError
ValueError
FileNotFoundError
EOFError
SleepingError
TyrePuncturedError
It is highly recommended to handle exceptions. The main objective of exception handling
is Graceful Termination of the program(i.e we should not block our resources and we
should not miss anything)
Exception handling does not mean repairing exception. We have to define alternative way
to continue rest of the program normally.
Eg:
For example our programming requirement is reading data from remote file locating at
London. At runtime if london file is not available then the program should not be
terminated abnormally. We have to provide local file to continue rest of the program
normally. This way of defining alternative is nothing but exception handling.
try:
read data from remote file locating at london
except FileNotFoundError:
use local file and continue rest of the program normally
Q. What is an Exception?
Q. What is the purpose of Exception Handling?
Q. What is the meaning of Exception Handling?

nd
Default Exception Handing in Python:
Every exception in Python is an object. For every exception type the corresponding classes
are available.
Whevever an exception occurs PVM will create the corresponding exception object and
will check for handling code. If handling code is not available then Python interpreter
terminates the program abnormally and prints corresponding exception information to
the console.
The rest of the program won't be executed.
Eg:
1) print("Hello")
2) print(10/0)
3) print("Hi")
4)
6) Hello
9) print(10/0)

nd
Python's Exception Hierarchy
Every Exception in Python is a class.
All exception classes are child classes of BaseException.i.e every exception class extends
BaseException either directly or indirectly. Hence BaseException acts as root for Python
Exception Hierarchy.
Most of the times being a programmer we have to concentrate Exception and its child
classes.
Customized Exception Handling by using try-except:
It is highly recommended to handle exceptions.
The code which may raise exception is called risky code and we have to take risky code
inside try block. The corresponding handling code we have to take inside except block.
Attribute
Error
Arithmetic
Error
EOF
Error
Name
Error
Lookup
Error
OS
Error
Type
Error
Value
Error
BaseException
Exception KeyboardInterrupt
SystemExit GeneratorExit
ZeroDivision
Error
FloatingPoint
Error
Overflow
Error
Index
Error
Key
Error
FileNotFound
Error
Interrupted
Error
Permission
Error
TimeOut
Error

nd
try:
Risky Code
except XXX:
Handling code/Alternative Code
without try-except:
1. print("stmt-1")
2. print(10/0)
3. print("stmt-3")
4.
5. Output
6. stmt-1
7. ZeroDivisionError: division by zero
Abnormal termination/Non-Graceful Termination
with try-except:
1. print("stmt-1")
2. try:
3. print(10/0)
4. except ZeroDivisionError:
5. print(10/2)
6. print("stmt-3")
7.
8. Output
9. stmt-1
10. 5.0
11. stmt-3
Normal termination/Graceful Termination
Control Flow in try-except:
try:
stmt-1
stmt-2
stmt-3
except XXX:
stmt-4
stmt-5
case-1: If there is no exception
1,2,3,5 and Normal Termination

nd
case-2: If an exception raised at stmt-2 and corresponding except block matched
1,4,5 Normal Termination
case-3: If an exception raised at stmt-2 and corresponding except block not matched
1, Abnormal Termination
case-4: If an exception raised at stmt-4 or at stmt-5 then it is always abnormal
termination.
Conclusions:
1. within the try block if anywhere exception raised then rest of the try block wont be
executed eventhough we handled that exception. Hence we have to take only risky code
inside try block and length of the try block should be as less as possible.
2. In addition to try block,there may be a chance of raising exceptions inside except and
finally blocks also.
3. If any statement which is not part of try block raises an exception then it is always
abnormal termination.
How to print exception information:
try:
1. print(10/0)
2. except ZeroDivisionError as msg:
3. print("exception raised and its description is:",msg)
4.
5. Output exception raised and its description is: division by zero
try with multiple except blocks:
The way of handling exception is varied from exception to exception.Hence for every
exception type a seperate except block we have to provide. i.e try with multiple except
blocks is possible and recommended to use.
Eg:
try:
-------
-------
-------
except ZeroDivisionError:
perform alternative
arithmetic operations

nd
except FileNotFoundError:
use local file instead of remote file
If try with multiple except blocks available then based on raised exception the
corresponding except block will be executed.
Eg:
1) try:
2) x=int(input("Enter First Number: "))
3) y=int(input("Enter Second Number: "))
4) print(x/y)
5) except ZeroDivisionError :
6) print("Can't Divide with Zero")
7) except ValueError:
8) print("please provide int value only")
9)
11) Enter First Number: 10
12) Enter Second Number: 2
13) 5.0
14)
18) Can't Divide with Zero
19)
22) Enter Second Number: ten
23) please provide int value only
If try with multiple except blocks available then the order of these except blocks is
important .Python interpreter will always consider from top to bottom until matched
except block identified.
Eg:
1) try:
4) print(x/y)
5) except ArithmeticError :
6) print("ArithmeticError")
7) except ZeroDivisionError:
8) print("ZeroDivisionError")
9)

nd
13) ArithmeticError
Single except block that can handle multiple exceptions:
We can write a single except block that can handle multiple different types of exceptions.
except (Exception1,Exception2,exception3,..): or
except (Exception1,Exception2,exception3,..) as msg :
Parenthesis are mandatory and this group of exceptions internally considered as tuple.
Eg:
1) try:
4) print(x/y)
5) except (ZeroDivisionError,ValueError) as msg:
6) print("Plz Provide valid numbers only and problem is: ",msg)
7)
11) Plz Provide valid numbers only and problem is: division by zero
12)
16) Plz Provide valid numbers only and problem is: invalid literal for int() with b
17) ase 10: 'ten'
Default except block:
We can use default except block to handle any type of exceptions.
In default except block generally we can print normal error messages.
Syntax:
except:
statements
Eg:
1) try:
4) print(x/y)

nd
6) print("ZeroDivisionError:Can't divide with zero")
7) except:
8) print("Default Except:Plz provide valid input only")
9)
13) ZeroDivisionError:Can't divide with zero
14)
18) Default Except:Plz provide valid input only
***Note: If try with multiple except blocks available then default except block should be
last,otherwise we will get SyntaxError.
Eg:
1) try:
2) print(10/0)
3) except:
4) print("Default Except")
6) print("ZeroDivisionError")
7)
8) SyntaxError: default 'except:' must be last
Note:
The following are various possible combinations of except blocks
1. except ZeroDivisionError:
1. except ZeroDivisionError as msg:
3. except (ZeroDivisionError,ValueError) :
4. except (ZeroDivisionError,ValueError) as msg:
5. except :
finally block:
1. It is not recommended to maintain clean up code(Resource Deallocating Code or
Resource Releasing code) inside try block because there is no guarentee for the execution
of every statement inside try block always.
2. It is not recommended to maintain clean up code inside except block, because if there
is no exception then except block won't be executed.

nd
Hence we required some place to maintain clean up code which should be executed
always irrespective of whether exception raised or not raised and whether exception
handled or not handled. Such type of best place is nothing but finally block.
Hence the main purpose of finally block is to maintain clean up code.
try:
Risky Code
except:
Handling Code
finally:
Cleanup code
The speciality of finally block is it will be executed always whether exception raised or not
raised and whether exception handled or not handled.
Case-1: If there is no exception
1) try:
2) print("try")
3) except:
4) print("except")
5) finally:
6) print("finally")
7)
8) Output
9) try
10) finally
Case-2: If there is an exception raised but handled:
1) try:
2) print("try")
3) print(10/0)
5) print("except")
6) finally:
7) print("finally")
8)
9) Output
10) try
11) except
12) finally

nd
Case-3: If there is an exception raised but not handled:
1) try:
2) print("try")
3) print(10/0)
4) except NameError:
5) print("except")
6) finally:
7) print("finally")
8)
9) Output
10) try
11) finally
12) ZeroDivisionError: division by zero(Abnormal Termination)
*** Note: There is only one situation where finally block won't be executed ie whenever
we are using os._exit(0) function.
Whenever we are using os._exit(0) function then Python Virtual Machine itself will be
shutdown.In this particular case finally won't be executed.
1) imports
2) try:
3) print("try")
4) os._exit(0)
5) except NameError:
6) print("except")
7) finally:
8) print("finally")
9)
10) Output
11) try
Note:
os._exit(0)
where 0 represents status code and it indicates normal termination
There are multiple status codes are possible.
Control flow in try-except-finally:
try:
stmt-1
stmt-2
stmt-3
except:
stmt-4

nd
finally:
stmt-5
stmt6
Case-1: If there is no exception
1,2,3,5,6 Normal Termination
Case-2: If an exception raised at stmt2 and the corresponding except block matched
1,4,5,6 Normal Termination
Case-3: If an exception raised at stmt2 but the corresponding except block not matched
1,5 Abnormal Termination
Case-4:If an exception raised at stmt4 then it is always abnormal termination but before
that finally block will be executed.
Case-5: If an exception raised at stmt-5 or at stmt-6 then it is always abnormal
termination
Nested try-except-finally blocks:
We can take try-except-finally blocks inside try or except or finally blocks.i.e nesting of try-
except-finally is possible.
try:
----------
----------
----------
try:
-------------
--------------
--------------
except:
--------------
--------------
--------------
------------
except:
-----------
-----------
-----------
General Risky code we have to take inside outer try block and too much risky code we
have to take inside inner try block. Inside Inner try block if an exception raised then inner

nd
except block is responsible to handle. If it is unable to handle then outer except block is
responsible to handle.
Eg:
1) try:
2) print("outer try block")
3) try:
4) print("Inner try block")
5) print(10/0)
7) print("Inner except block")
8) finally:
9) print("Inner finally block")
10) except:
11) print("outer except block")
12) finally:
13) print("outer finally block")
14)
15) Output
16) outer try block
17) Inner try block
18) Inner except block
19) Inner finally block
20) outer finally block
Control flow in nested try-except-finally:
try:
stmt-1
stmt-2
stmt-3
try:
stmt-4
stmt-5
stmt-6
except X:
stmt-7
finally:
stmt-8
stmt-9
except Y:
stmt-10
finally:
stmt-11
stmt-12

nd
case-1: If there is no exception
1,2,3,4,5,6,8,9,11,12 Normal Termination
case-2: If an exception raised at stmt-2 and the corresponding except block matched
1,10,11,12 Normal Termination
case-3: If an exceptiion raised at stmt-2 and the corresponding except block not matched
1,11,Abnormal Termination
case-4: If an exception raised at stmt-5 and inner except block matched
1,2,3,4,7,8,9,11,12 Normal Termination
case-5: If an exception raised at stmt-5 and inner except block not matched but outer
except block matched
1,2,3,4,8,10,11,12,Normal Termination
case-6:If an exception raised at stmt-5 and both inner and outer except blocks are not
matched
1,2,3,4,8,11,Abnormal Termination
1,2,3,.,.,.,8,10,11,12,Normal Termination
1,2,3,.,.,.,8,11,Abnormal Termination
1,2,3,.,.,.,.,10,11,12 Normal Termination
1,2,3,.,.,.,.,11,Abnormal Termination
1,2,3,.,.,.,.,8,10,11,12,Normal Termination
1,2,3,.,.,.,.,8,11,Abnormal Termination
case-13: If an exception raised at stmt-10 then it is always abonormal termination but
before abnormal termination finally block(stmt-11) will be executed.

nd
case-14: If an exception raised at stmt-11 or stmt-12 then it is always abnormal
termination.
Note: If the control entered into try block then compulsary finally block will be executed.
If the control not entered into try block then finally block won't be executed.
else block with try-except-finally:
We can use else block with try-except-finally blocks.
else block will be executed if and only if there are no exceptions inside try block.
try:
Risky Code
except:
will be executed if exception inside try
else:
will be executed if there is no exception inside try
finally:
will be executed whether exception raised or not raised and handled or not
handled
Eg:
try:
print("try")
print(10/0)--->1
except:
print("except")
else:
print("else")
finally:
print("finally")
If we comment line-1 then else block will be executed b'z there is no exception inside try.
In this case the output is:
try
else
finally
If we are not commenting line-1 then else block won't be executed b'z there is exception
inside try block. In this case output is:

nd
try
except
finally
Various possible combinations of try-except-else-finally:
1. Whenever we are writing try block, compulsory we should write except or finally
block.i.e without except or finally block we cannot write try block.
2. Wheneever we are writing except block, compulsory we should write try block. i.e
except without try is always invalid.
3. Whenever we are writing finally block, compulsory we should write try block. i.e finally
without try is always invalid.
4. We can write multiple except blocks for the same try,but we cannot write multiple
finally blocks for the same try
5. Whenever we are writing else block compulsory except block should be there. i.e
without except we cannot write else block.
6. In try-except-else-finally order is important.
7. We can define try-except-else-finally inside try,except,else and finally blocks. i.e nesting
of try-except-else-finally is always possible.
1
try:
print("try") 
2
except:
print("Hello") 
3
else:
print("Hello") 
4
finally:
print("Hello") 
5
try:
print("try")
except:
print("except")
√
6
try:
print("try")
finally:
print("finally")
√
7
try:
print("try") √

nd
except:
print("except")
else:
print("else")
8
try:
print("try")
else:
print("else")

9
try:
print("try")
else:
print("else")
finally:
print("finally")

10
try:
print("try")
except XXX:
print("except-1")
except YYY:
print("except-2")
√
11
try:
print("try")
except :
print("except-1")
else:
print("else")
else:
print("else")

12
try:
print("try")
except :
print("except-1")
finally:
print("finally")
finally:
print("finally")

13
try:
print("try")
print("Hello")
except:
print("except")

14
try:
print("try")
except:


nd
print("except")
print("Hello")
except:
print("except")
15
try:
print("try")
except:
print("except")
print("Hello")
finally:
print("finally")

16
try:
print("try")
except:
print("except")
print("Hello")
else:
print("else")

17
try:
print("try")
except:
print("except")
try:
print("try")
except:
print("except")
√
18
try:
print("try")
except:
print("except")
try:
print("try")
finally:
print("finally")
√
19
try:
print("try")
except:
print("except")
if 10>20:
print("if")
else:
print("else")

20
try:
print("try") √

nd
try:
print("inner try")
except:
print("inner except block")
finally:
print("inner finally block")
except:
print("except")
21
try:
print("try")
except:
print("except")
try:
print("inner try")
except:
finally:
√
22
try:
print("try")
except:
print("except")
finally:
try:
print("inner try")
except:
finally:
√
23
try:
print("try")
except:
print("except")
try:
print("try")
else:
print("else")

24
try:
print("try")
try:
print("inner try")
except:
print("except")


nd
Types of Exceptions:
In Python there are 2 types of exceptions are possible.
1. Predefined Exceptions
2. User Definded Exceptions
1. Predefined Exceptions:
Also known as in-built exceptions
The exceptions which are raised automatically by Python virtual machine whenver a
particular event occurs, are called pre defined exceptions.
Eg 1: Whenever we are trying to perform Division by zero, automatically Python will raise
ZeroDivisionError.
print(10/0)
Eg 2: Whenever we are trying to convert input value to int type and if input value is not
int value then Python will raise ValueError automatically
x=int("ten")===>ValueError
2. User Defined Exceptions:
Also known as Customized Exceptions or Programatic Exceptions
Some time we have to define and raise exceptions explicitly to indicate that something
goes wrong ,such type of exceptions are called User Defined Exceptions or Customized
Exceptions
Programmer is responsible to define these exceptions and Python not having any idea
about these. Hence we have to raise explicitly based on our requirement by using "raise"
keyword.
25
try:
print("try")
else:
print("else")
except:
print("except")
finally:
print("finally")


nd
Eg:
InSufficientFundsException
InvalidInputException
TooYoungException
TooOldException
How to Define and Raise Customized Exceptions:
Every exception in Python is a class that extends Exception class either directly or
indirectly.
Syntax:
class classname(predefined exception class name):
def __init__(self,arg):
self.msg=arg
Eg:
1) class TooYoungException(Exception):
2) def __init__(self,arg):
3) self.msg=arg
TooYoungException is our class name which is the child class of Exception
We can raise exception by using raise keyword as follows
raise TooYoungException("message")
Eg:
1) class TooYoungException(Exception):
3) self.msg=arg
4)
5) class TooOldException(Exception):
7) self.msg=arg
8)
9) age=int(input("Enter Age:"))
10) if age>60:
11) raise TooYoungException("Plz wait some more time you will get best match soon!!!")
12) elif age<18:
13) raise TooOldException("Your age already crossed marriage age...no chance of getting ma
rriage")
14) else:
15) print("You will get match details soon by email!!!")
16)

nd
18) Enter Age:90
19) __main__.TooYoungException: Plz wait some more time you will get best match soon!!!
20)
22) Enter Age:12
23) __main__.TooOldException: Your age already crossed marriage age...no chance of g
24) etting marriage
25)
27) Enter Age:27
28) You will get match details soon by email!!!
Note:
raise keyword is best suitable for customized exceptions but not for pre defined
exceptions

nd
PYTHON LOGGING
Logging the Exceptions:
It is highly recommended to store complete application flow and exceptions information
to a file. This process is called logging.
The main advantages of logging are:
1. We can use log files while performing debugging
2. We can provide statistics like number of requests per day etc
To implement logging, Python provides one inbuilt module logging.
logging levels:
Depending on type of information, logging data is divided according to the following 6
levels in Python.
table
1. CRITICAL==>50==>Represents a very serious problem that needs high attention
2. ERROR===>40===>Represents a serious error
3. WARNING==>30==>Represents a warning message, some caution needed. It is alert to
the programmer
4. INFO===>20===>Represents a message with some important information
5. DEBUG===>10==>Represents a message with debugging information
6. NOTSET==>0==>Rrepresents that the level is not set.
By default while executing Python program only WARNING and higher level messages will
be displayed.
How to implement logging:
To perform logging, first we required to create a file to store messages and we have to
specify which level messages we have to store.
We can do this by using basicConfig() function of logging module.
logging.basicConfig(filename='log.txt',level=logging.WARNING)

nd
The above line will create a file log.txt and we can store either WARNING level or higher
level messages to that file.
After creating log file, we can write messages to that file by using the following methods.
logging.debug(message)
logging.info(message)
logging.warning(message)
logging.error(message)
logging.critical(message)
Q.Write a Python program to create a log file and write WARNING and higher
level messages?
1) import logging
2) logging.basicConfig(filename='log.txt',level=logging.WARNING)
3) print("Logging Module Demo")
4) logging.debug("This is debug message")
5) logging.info("This is info message")
6) logging.warning("This is warning message")
7) logging.error("This is error message")
8) logging.critical("This is critical message")
log.txt:
1) WARNING:root:This is warning message
2) ERROR:root:This is error message
3) CRITICAL:root:This is critical message
Note:
In the above program only WARNING and higher level messages will be written to log file.
If we set level as DEBUG then all messages will be written to log file.
1) import logging
2) logging.basicConfig(filename='log.txt',level=logging.DEBUG)
3) print("Logging Module Demo")
4) logging.debug("This is debug message")
5) logging.info("This is info message")
6) logging.warning("This is warning message")
7) logging.error("This is error message")
8) logging.critical("This is critical message")
log.txt:
1) DEBUG:root:This is debug message
2) INFO:root:This is info message

nd
3) WARNING:root:This is warning message
4) ERROR:root:This is error message
5) CRITICAL:root:This is critical message
Note: We can format log messages to include date and time, ip address of the client etc
at advanced level.
How to write Python program exceptions to the log file:
By using the following function we can write exceptions information to the log file.
logging.exception(msg)
Q. Python Program to write exception information to the log file
1) import logging
2) logging.basicConfig(filename='mylog.txt',level=logging.INFO)
3) logging.info("A New request Came:")
4) try:
7) print(x/y)
8) except ZeroDivisionError as msg:
9) print("cannot divide with zero")
10) logging.exception(msg)
11) except ValueError as msg:
12) print("Enter only int values")
13) logging.exception(msg)
14) logging.info("Request Processing Completed")
15)
16)
20) 5.0
21)
25) cannot divide with zero
26)
30) Enter only int values

nd
mylog.txt:
1) INFO:root:A New request Came:
2) INFO:root:Request Processing Completed
4) ERROR:root:division by zero
7) print(x/y)
11) ERROR:root:invalid literal for int() with base 10: 'ten'
15) ValueError: invalid literal for int() with base 10: 'ten'

nd
PYTHON DEBUGGING BY USING ASSERTIONS
Debugging Python Program by using assert keyword:
The process of identifying and fixing the bug is called debugging.
Very common way of debugging is to use print() statement. But the problem with the
print() statement is after fixing the bug,compulsory we have to delete the extra added
print() statments,otherwise these will be executed at runtime which creates performance
problems and disturbs console output.
To overcome this problem we should go for assert statement. The main advantage of
assert statement over print() statement is after fixing bug we are not required to delete
assert statements. Based on our requirement we can enable or disable assert statements.
Hence the main purpose of assertions is to perform debugging. Usully we can perform
debugging either in development or in test environments but not in production
environment. Hence assertions concept is applicable only for dev and test environments
but not for production environment.
Types of assert statements:
There are 2 types of assert statements
1. Simple Version
2. Augmented Version
1. Simple Version:
assert conditional_expression
2. Augmented Version:
assert conditional_expression,message
conditional_expression will be evaluated and if it is true then the program will be
continued.
If it is false then the program will be terminated by raising AssertionError.
By seeing AssertionError, programmer can analyze the code and can fix the problem.
Eg:
1) def squareIt(x):
2) return x**x

nd
3) assert squareIt(2)==4,"The square of 2 should be 4"
6) print(squareIt(2))
9)
14) AssertionError: The square of 3 should be 9
15)
16) def squareIt(x):
17) return x*x
24)
25) Output
26) 4
27) 9
28) 16
Exception Handling vs Assertions:
Assertions concept can be used to alert programmer to resolve development time errors.
Exception Handling can be used to handle runtime errors.

nd
Python's Object Oriented Programming (OOPs)
What is Class:
⚽ In Python every thing is an object. To create objects we required some Model or Plan or Blue
print, which is nothing but class.
⚽ We can write a class to represent properties (attributes) and actions (behaviour) of object.
⚽ Properties can be represented by variables
⚽ Actions can be represented by Methods.
⚽ Hence class contains both variables and methods.
How to Define a class?
We can define a class by using class keyword.
Syntax:
class className:
''' documenttation string '''
variables:instance variables,static and local variables
methods: instance methods,static methods,class methods
Documentation string represents description of the class. Within the class doc string is always
optional. We can get doc string by using the following 2 ways.
1. print(classname.__doc__)
2. help(classname)
Example:
1) class Student:
2) ''''' This is student class with required data'''
3) print(Student.__doc__)
4) help(Student)
Within the Python class we can represent data by using variables.
There are 3 types of variables are allowed.
1. Instance Variables (Object Level Variables)
2. Static Variables (Class Level Variables)
3. Local variables (Method Level Variables)
Within the Python class, we can represent operations by using methods. The following are various
types of allowed methods

nd
1. Instance Methods
2. Class Methods
3. Static Methods
Example for class:
1) class Student:
2) '''''Developed by durga for python demo'''
3) def __init__(self):
4) self.name='durga'
5) self.age=40
6) self.marks=80
7)
8) def talk(self):
9) print("Hello I am :",self.name)
10) print("My Age is:",self.age)
11) print("My Marks are:",self.marks)
What is Object:
Pysical existence of a class is nothing but object. We can create any number of objects for a class.
Syntax to create object: referencevariable = classname()
Example: s = Student()
What is Reference Variable:
The variable which can be used to refer object is called reference variable.
By using reference variable, we can access properties and methods of object.
Program: Write a Python program to create a Student class and Creates an object to it. Call the
method talk() to display student details
1) class Student:
2)
3) def __init__(self,name,rollno,marks):
4) self.name=name
5) self.rollno=rollno
6) self.marks=marks
7)
8) def talk(self):
9) print("Hello My Name is:",self.name)
10) print("My Rollno is:",self.rollno)
11) print("My Marks are:",self.marks)
12)

nd
13) s1=Student("Durga",101,80)
14) s1.talk()
Output:
D:durgaclasses>py test.py
Hello My Name is: Durga
My Rollno is: 101
My Marks are: 80
Self variable:
self is the default variable which is always pointing to current object (like this keyword in Java)
By using self we can access instance variables and instance methods of object.
Note:
1. self should be first parameter inside constructor
def __init__(self):
2. self should be first parameter inside instance methods
def talk(self):
Constructor Concept:
☕ Constructor is a special method in python.
☕ The name of the constructor should be __init__(self)
☕ Constructor will be executed automatically at the time of object creation.
☕ The main purpose of constructor is to declare and initialize instance variables.
☕ Per object constructor will be exeucted only once.
☕ Constructor can take atleast one argument(atleast self)
☕ Constructor is optional and if we are not providing any constructor then python will provide
default constructor.
Example:
1) def __init__(self,name,rollno,marks):
2) self.name=name
3) self.rollno=rollno
4) self.marks=marks
Program to demonistrate constructor will execute only once per object:
1) class Test:
2)
4) print("Constructor exeuction...")
5)

nd
6) def m1(self):
7) print("Method execution...")
8)
9) t1=Test()
10) t2=Test()
11) t3=Test()
12) t1.m1()
Output
Constructor exeuction...
Method execution...
Program:
1) class Student:
2)
3) ''''' This is student class with required data'''
4) def __init__(self,x,y,z):
5) self.name=x
6) self.rollno=y
7) self.marks=z
8)
10) print("Student Name:{}nRollno:{} nMarks:{}".format(self.name,self.rollno,self.marks)
)
11)
12) s1=Student("Durga",101,80)
13) s1.display()
14) s2=Student("Sunny",102,100)
15) s2.display()
Output
Student Name:Durga
Rollno:101
Marks:80
Student Name:Sunny
Rollno:102
Marks:100

nd
Differences between Methods and Constructors:
Method Constructor
1. Name of method can be any name 1. Constructor name should be always __init__
2. Method will be executed if we call that
method
2. Constructor will be executed automatically at
the time of object creation.
3. Per object, method can be called any number
of times.
3. Per object, Constructor will be executed only
once
4. Inside method we can write business logic 4. Inside Constructor we have to declare and
initialize instance variables
Types of Variables:
Inside Python class 3 types of variables are allowed.
1. Instance Variables (Object Level Variables)
2. Static Variables (Class Level Variables)
3. Local variables (Method Level Variables)
1. Instance Variables:
If the value of a variable is varied from object to object, then such type of variables are called
instance variables.
For every object a separate copy of instance variables will be created.
Where we can declare Instance variables:
1. Inside Constructor by using self variable
2. Inside Instance Method by using self variable
3. Outside of the class by using object reference variable
1. Inside Constructor by using self variable:
We can declare instance variables inside a constructor by using self keyword. Once we creates
object, automatically these variables will be added to the object.
Example:
1) class Employee:
2)
4) self.eno=100
5) self.ename='Durga'
6) self.esal=10000
7)
8) e=Employee()

nd
9) print(e.__dict__)
Output: {'eno': 100, 'ename': 'Durga', 'esal': 10000}
2. Inside Instance Method by using self variable:
We can also declare instance variables inside instance method by using self variable. If any
instance variable declared inside instance method, that instance variable will be added once we
call taht method.
Example:
1) class Test:
2)
4) self.a=10
5) self.b=20
6)
7) def m1(self):
8) self.c=30
9)
10) t=Test()
11) t.m1()
12) print(t.__dict__)
Output
{'a': 10, 'b': 20, 'c': 30}
3. Outside of the class by using object reference variable:
We can also add instance variables outside of a class to a particular object.
1) class Test:
2)
4) self.a=10
5) self.b=20
6)
7) def m1(self):
8) self.c=30
9)
10) t=Test()
11) t.m1()
12) t.d=40
Output {'a': 10, 'b': 20, 'c': 30, 'd': 40}

nd
How to access Instance variables:
We can access instance variables with in the class by using self variable and outside of the class by
using object reference.
1) class Test:
2)
4) self.a=10
5) self.b=20
6)
8) print(self.a)
9) print(self.b)
10)
11) t=Test()
12) t.display()
13) print(t.a,t.b)
Output
10
20
10 20
How to delete instance variable from the object:
1. Within a class we can delete instance variable as follows
del self.variableName
2. From outside of class we can delete instance variables as follows
del objectreference.variableName
Example:
1) class Test:
3) self.a=10
4) self.b=20
5) self.c=30
6) self.d=40
7) def m1(self):
8) del self.d
9)
10) t=Test()

nd
12) t.m1()
14) del t.c
Output
{'a': 10, 'b': 20, 'c': 30, 'd': 40}
{'a': 10, 'b': 20, 'c': 30}
{'a': 10, 'b': 20}
Note: The instance variables which are deleted from one object,will not be deleted from other
objects.
Example:
1) class Test:
3) self.a=10
4) self.b=20
5) self.c=30
6) self.d=40
7)
8)
9) t1=Test()
10) t2=Test()
11) del t1.a
12) print(t1.__dict__)
13) print(t2.__dict__)
Output
{'b': 20, 'c': 30, 'd': 40}
{'a': 10, 'b': 20, 'c': 30, 'd': 40}
If we change the values of instance variables of one object then those changes won't be reflected
to the remaining objects, because for every object we are separate copy of instance variables are
available.
Example:
1) class Test:
3) self.a=10
4) self.b=20
5)
6) t1=Test()
7) t1.a=888
8) t1.b=999
9) t2=Test()
10) print('t1:',t1.a,t1.b)

nd
11) print('t2:',t2.a,t2.b)
Output
t1: 888 999
t2: 10 20
1. Static variables:
If the value of a variable is not varied from object to object, such type of variables we have to
declare with in the class directly but outside of methods. Such type of variables are called Static
variables.
For total class only one copy of static variable will be created and shared by all objects of that
class.
We can access static variables either by class name or by object reference. But recommended to
use class name.
Instance Variable vs Static Variable:
Note: In the case of instance variables for every object a seperate copy will be created,but in the
case of static variables for total class only one copy will be created and shared by every object of
that class.
1) class Test:
2) x=10
4) self.y=20
5)
6) t1=Test()
7) t2=Test()
8) print('t1:',t1.x,t1.y)
10) Test.x=888
11) t1.y=999
12) print('t1:',t1.x,t1.y)
13) print('t2:',t2.x,t2.y)
Output
t1: 10 20
t2: 10 20
t1: 888 999
t2: 888 20

nd
Various places to declare static variables:
1. In general we can declare within the class directly but from out side of any method
2. Inside constructor by using class name
3. Inside instance method by using class name
4. Inside classmethod by using either class name or cls variable
5. Inside static method by using class name
1) class Test:
2) a=10
4) Test.b=20
5) def m1(self):
6) Test.c=30
7) @classmethod
8) def m2(cls):
9) cls.d1=40
10) Test.d2=400
11) @staticmethod
12) def m3():
13) Test.e=50
14) print(Test.__dict__)
15) t=Test()
17) t.m1()
19) Test.m2()
21) Test.m3()
23) Test.f=60
How to access static variables:
1. inside constructor: by using either self or classname
2. inside instance method: by using either self or classname
3. inside class method: by using either cls variable or classname
4. inside static method: by using classname
5. From outside of class: by using either object reference or classnmae
1) class Test:
2) a=10
4) print(self.a)
5) print(Test.a)
6) def m1(self):
7) print(self.a)

nd
8) print(Test.a)
9) @classmethod
10) def m2(cls):
11) print(cls.a)
12) print(Test.a)
13) @staticmethod
14) def m3():
15) print(Test.a)
16) t=Test()
17) print(Test.a)
18) print(t.a)
19) t.m1()
20) t.m2()
21) t.m3()
Where we can modify the value of static variable:
Anywhere either with in the class or outside of class we can modify by using classname.
But inside class method, by using cls variable.
Example:
1) class Test:
2) a=777
3) @classmethod
4) def m1(cls):
5) cls.a=888
6) @staticmethod
7) def m2():
8) Test.a=999
9) print(Test.a)
10) Test.m1()
11) print(Test.a)
12) Test.m2()
13) print(Test.a)
Output
777
888
999

nd
*****
If we change the value of static variable by using either self
or object reference variable:
If we change the value of static variable by using either self or object reference variable, then the
value of static variable won't be changed,just a new instance variable with that name will be
added to that particular object.
Example 1:
1) class Test:
2) a=10
3) def m1(self):
4) self.a=888
5) t1=Test()
6) t1.m1()
7) print(Test.a)
8) print(t1.a)
Output
10
888
Example:
1) class Test:
2) x=10
4) self.y=20
5)
6) t1=Test()
7) t2=Test()
10) t1.x=888
11) t1.y=999
12) print('t1:',t1.x,t1.y)
13) print('t2:',t2.x,t2.y)
Output
t1: 10 20
t2: 10 20
t1: 888 999
t2: 10 20

nd
Example:
1) class Test:
2) a=10
4) self.b=20
5) t1=Test()
6) t2=Test()
7) Test.a=888
8) t1.b=999
9) print(t1.a,t1.b)
10) print(t2.a,t2.b)
Output
888 999
888 20
------------------------------------
1) class Test:
2) a=10
4) self.b=20
5) def m1(self):
6) self.a=888
7) self.b=999
8)
9) t1=Test()
10) t2=Test()
11) t1.m1()
Output
888 999
10 20
Example:
1) class Test:
2) a=10
4) self.b=20
5) @classmethod
6) def m1(cls):
7) cls.a=888
8) cls.b=999
9)
10) t1=Test()
11) t2=Test()

nd
12) t1.m1()
15) print(Test.a,Test.b)
Output
888 20
888 20
888 999
How to delete static variables of a class:
We can delete static variables from anywhere by using the following syntax
del classname.variablename
But inside classmethod we can also use cls variable
del cls.variablename
1) class Test:
2) a=10
3) @classmethod
4) def m1(cls):
5) del cls.a
6) Test.m1()
Example:
1) class Test:
2) a=10
4) Test.b=20
5) del Test.a
6) def m1(self):
7) Test.c=30
8) del Test.b
9) @classmethod
10) def m2(cls):
11) cls.d=40
12) del Test.c
13) @staticmethod
14) def m3():
15) Test.e=50
16) del Test.d
18) t=Test()

nd
20) t.m1()
22) Test.m2()
24) Test.m3()
26) Test.f=60
28) del Test.e
****
Note: By using object reference variable/self we can read static variables, but we cannot modify
or delete.
If we are trying to modify, then a new instance variable will be added to that particular object.
t1.a = 70
If we are trying to delete then we will get error.
Example:
1) class Test:
2) a=10
3)
4) t1=Test()
5) del t1.a ===>AttributeError: a
We can modify or delete static variables only by using classname or cls variable.
1) import sys
2) class Customer:
3) ''''' Customer class with bank operations.. '''
4) bankname='DURGABANK'
5) def __init__(self,name,balance=0.0):
6) self.name=name
7) self.balance=balance
8) def deposit(self,amt):
9) self.balance=self.balance+amt
10) print('Balance after deposit:',self.balance)
11) def withdraw(self,amt):
12) if amt>self.balance:
13) print('Insufficient Funds..cannot perform this operation')
14) sys.exit()
15) self.balance=self.balance-amt
16) print('Balance after withdraw:',self.balance)
17)
18) print('Welcome to',Customer.bankname)

nd
19) name=input('Enter Your Name:')
20) c=Customer(name)
21) while True:
22) print('d-Deposit nw-Withdraw ne-exit')
23) option=input('Choose your option:')
24) if option=='d' or option=='D':
25) amt=float(input('Enter amount:'))
26) c.deposit(amt)
27) elif option=='w' or option=='W':
28) amt=float(input('Enter amount:'))
29) c.withdraw(amt)
30) elif option=='e' or option=='E':
31) print('Thanks for Banking')
32) sys.exit()
33) else:
34) print('Invalid option..Plz choose valid option')
output:
D:durga_classes>py test.py
Welcome to DURGABANK
Enter Your Name:Durga
d-Deposit
w-Withdraw
e-exit
Choose your option:d
Enter amount:10000
Balance after deposit: 10000.0
d-Deposit
w-Withdraw
e-exit
Choose your option:d
Enter amount:20000
Balance after deposit: 30000.0
d-Deposit
w-Withdraw
e-exit
Choose your option:w
Enter amount:2000
Balance after withdraw: 28000.0
d-Deposit
w-Withdraw
e-exit
Choose your option:r
Invalid option..Plz choose valid option
d-Deposit
w-Withdraw
e-exit
Choose your option:e
Thanks for Banking

nd
Local variables:
Sometimes to meet temporary requirements of programmer,we can declare variables inside a
method directly,such type of variables are called local variable or temporary variables.
Local variables will be created at the time of method execution and destroyed once method
completes.
Local variables of a method cannot be accessed from outside of method.
Example:
1) class Test:
2) def m1(self):
3) a=1000
4) print(a)
5) def m2(self):
6) b=2000
7) print(b)
8) t=Test()
9) t.m1()
10) t.m2()
Output
1000
2000
Example 2:
1) class Test:
2) def m1(self):
3) a=1000
4) print(a)
5) def m2(self):
6) b=2000
7) print(a) #NameError: name 'a' is not defined
8) print(b)
9) t=Test()
10) t.m1()
11) t.m2()

nd
Types of Methods:
Inside Python class 3 types of methods are allowed
1. Instance Methods
2. Class Methods
3. Static Methods
1. Instance Methods:
Inside method implementation if we are using instance variables then such type of methods are
called instance methods.
Inside instance method declaration,we have to pass self variable.
def m1(self):
By using self variable inside method we can able to access instance variables.
Within the class we can call instance method by using self variable and from outside of the class
we can call by using object reference.
1) class Student:
2) def __init__(self,name,marks):
3) self.name=name
4) self.marks=marks
6) print('Hi',self.name)
7) print('Your Marks are:',self.marks)
8) def grade(self):
9) if self.marks>=60:
10) print('You got First Grade')
11) elif self.marks>=50:
12) print('Yout got Second Grade')
13) elif self.marks>=35:
14) print('You got Third Grade')
15) else:
16) print('You are Failed')
17) n=int(input('Enter number of students:'))
19) name=input('Enter Name:')
20) marks=int(input('Enter Marks:'))
21) s= Student(name,marks)
22) s.display()
23) s.grade()
24) print()

nd
ouput:
Enter number of students:2
Enter Name:Durga
Enter Marks:90
Hi Durga
Your Marks are: 90
You got First Grade
Enter Name:Ravi
Enter Marks:12
Hi Ravi
Your Marks are: 12
You are Failed
Setter and Getter Methods:
We can set and get the values of instance variables by using getter and setter methods.
Setter Method:
setter methods can be used to set values to the instance variables. setter methods also known as
mutator methods.
syntax:
def setVariable(self,variable):
self.variable=variable
Example:
def setName(self,name):
self.name=name
Getter Method:
Getter methods can be used to get values of the instance variables. Getter methods also known as
accessor methods.
syntax:
def getVariable(self):
return self.variable
Example:
def getName(self):
return self.name

nd
Demo Program:
1) class Student:
2) def setName(self,name):
3) self.name=name
4)
5) def getName(self):
6) return self.name
7)
8) def setMarks(self,marks):
9) self.marks=marks
10)
11) def getMarks(self):
12) return self.marks
13)
14) n=int(input('Enter number of students:'))
16) s=Student()
17) name=input('Enter Name:')
18) s.setName(name)
19) marks=int(input('Enter Marks:'))
20) s.setMarks(marks)
21)
22) print('Hi',s.getName())
23) print('Your Marks are:',s.getMarks())
24) print()
output:
Enter number of students:2
Enter Name:Durga
Enter Marks:100
Hi Durga
Your Marks are: 100
Enter Name:Ravi
Enter Marks:80
Hi Ravi
Your Marks are: 80
2. Class Methods:
Inside method implementation if we are using only class variables (static variables), then such type
of methods we should declare as class method.
We can declare class method explicitly by using @classmethod decorator.
For class method we should provide cls variable at the time of declaration

nd
We can call classmethod by using classname or object reference variable.
Demo Program:
1) class Animal:
2) legs=4
3) @classmethod
4) def walk(cls,name):
5) print('{} walks with {} legs...'.format(name,cls.legs))
6) Animal.walk('Dog')
7) Animal.walk('Cat')
Output
Dog walks with 4 legs...
Cat walks with 4 legs...
Program to track the number of objects created for a class:
1) class Test:
2) count=0
4) Test.count =Test.count+1
5) @classmethod
6) def noOfObjects(cls):
7) print('The number of objects created for test class:',cls.count)
8)
9) t1=Test()
10) t2=Test()
11) Test.noOfObjects()
12) t3=Test()
13) t4=Test()
14) t5=Test()
15) Test.noOfObjects()
3. Static Methods:
In general these methods are general utility methods.
Inside these methods we won't use any instance or class variables.
Here we won't provide self or cls arguments at the time of declaration.
We can declare static method explicitly by using @staticmethod decorator
We can access static methods by using classname or object reference
1) class DurgaMath:
2)
3) @staticmethod
4) def add(x,y):

nd
5) print('The Sum:',x+y)
6)
7) @staticmethod
8) def product(x,y):
9) print('The Product:',x*y)
10)
11) @staticmethod
12) def average(x,y):
13) print('The average:',(x+y)/2)
14)
15) DurgaMath.add(10,20)
16) DurgaMath.product(10,20)
17) DurgaMath.average(10,20)
Output
The Sum: 30
The Product: 200
The average: 15.0
Note: In general we can use only instance and static methods.Inside static method we can access
class level variables by using class name.
class methods are most rarely used methods in python.
Passing members of one class to another class:
We can access members of one class inside another class.
1) class Employee:
2) def __init__(self,eno,ename,esal):
3) self.eno=eno
4) self.ename=ename
5) self.esal=esal
7) print('Employee Number:',self.eno)
8) print('Employee Name:',self.ename)
9) print('Employee Salary:',self.esal)
10) class Test:
11) def modify(emp):
12) emp.esal=emp.esal+10000
13) emp.display()
14) e=Employee(100,'Durga',10000)
15) Test.modify(e)
Output
Employee Number: 100
Employee Name: Durga

nd
Employee Salary: 20000
In the above application, Employee class members are available to Test class.
Inner classes:
Sometimes we can declare a class inside another class,such type of classes are called inner classes.
Without existing one type of object if there is no chance of existing another type of object,then we
should go for inner classes.
Example: Without existing Car object there is no chance of existing Engine object. Hence Engine
class should be part of Car class.
class Car:
.....
class Engine:
......
Example: Without existing university object there is no chance of existing Department object
class University:
.....
class Department:
......
eg3:
Without existing Human there is no chance of existin Head. Hence Head should be part of Human.
class Human:
class Head:
Note: Without existing outer class object there is no chance of existing inner class object. Hence
inner class object is always associated with outer class object.
Demo Program-1:
1) class Outer:
3) print("outer class object creation")
4) class Inner:
6) print("inner class object creation")
7) def m1(self):
8) print("inner class method")
9) o=Outer()
10) i=o.Inner()
11) i.m1()

nd
Output
outer class object creation
inner class object creation
inner class method
Note: The following are various possible syntaxes for calling inner class method
1.
o=Outer()
i=o.Inner()
i.m1()
2.
i=Outer().Inner()
i.m1()
3. Outer().Inner().m1()
Demo Program-2:
1) class Person:
3) self.name='durga'
4) self.db=self.Dob()
6) print('Name:',self.name)
7) class Dob:
9) self.dd=10
10) self.mm=5
11) self.yy=1947
13) print('Dob={}/{}/{}'.format(self.dd,self.mm,self.yy))
14) p=Person()
15) p.display()
16) x=p.db
17) x.display()
Output
Name: durga
Dob=10/5/1947
Demo Program-3:
Inside a class we can declare any number of inner classes.
1) class Human:
2)

nd
4) self.name = 'Sunny'
5) self.head = self.Head()
6) self.brain = self.Brain()
8) print("Hello..",self.name)
9)
10) class Head:
11) def talk(self):
12) print('Talking...')
13)
14) class Brain:
15) def think(self):
16) print('Thinking...')
17)
18) h=Human()
19) h.display()
20) h.head.talk()
21) h.brain.think()
Output
Hello.. Sunny
Talking...
Thinking...
Garbage Collection:
In old languages like C++, programmer is responsible for both creation and destruction of
objects.Usually programmer taking very much care while creating object, but neglecting
destruction of useless objects. Because of his neglectance, total memory can be filled with useless
objects which creates memory problems and total application will be down with Out of memory
error.
But in Python, We have some assistant which is always running in the background to destroy
useless objects.Because this assistant the chance of failing Python program with memory
problems is very less. This assistant is nothing but Garbage Collector.
Hence the main objective of Garbage Collector is to destroy useless objects.
If an object does not have any reference variable then that object eligible for Garbage Collection.
How to enable and disable Garbage Collector in our program:
By default Gargbage collector is enabled, but we can disable based on our requirement. In this
context we can use the following functions of gc module.
1. gc.isenabled()
Returns True if GC enabled

nd
2. gc.disable()
To disable GC explicitly
3. gc.enable()
To enable GC explicitly
Example:
1) import gc
2) print(gc.isenabled())
3) gc.disable()
5) gc.enable()
Output
True
False
True
Destructors:
Destructor is a special method and the name should be __del__
Just before destroying an object Garbage Collector always calls destructor to perform clean up
activities (Resource deallocation activities like close database connection etc).
Once destructor execution completed then Garbage Collector automatically destroys that object.
Note: The job of destructor is not to destroy object and it is just to perform clean up activities.
Example:
1) import time
2) class Test:
4) print("Object Initialization...")
5) def __del__(self):
6) print("Fulfilling Last Wish and performing clean up activities...")
7)
8) t1=Test()
9) t1=None
10) time.sleep(5)
11) print("End of application")
Output
Object Initialization...
Fulfilling Last Wish and performing clean up activities...
End of application

nd
Note:
If the object does not contain any reference variable then only it is eligible fo GC. ie if the
reference count is zero then only object eligible for GC
Example:
1) import time
2) class Test:
4) print("Constructor Execution...")
6) print("Destructor Execution...")
7)
8) t1=Test()
9) t2=t1
10) t3=t2
11) del t1
12) time.sleep(5)
13) print("object not yet destroyed after deleting t1")
14) del t2
15) time.sleep(5)
16) print("object not yet destroyed even after deleting t2")
17) print("I am trying to delete last reference variable...")
18) del t3
Example:
1) import time
2) class Test:
4) print("Constructor Execution...")
6) print("Destructor Execution...")
7)
8) list=[Test(),Test(),Test()]
9) del list
10) time.sleep(5)
11) print("End of application")
Output
Constructor Execution...
Destructor Execution...
End of application

nd
How to find the number of references of an object:
sys module contains getrefcount() function for this purpose.
sys.getrefcount(objectreference)
Example:
1) import sys
2) class Test:
3) pass
4) t1=Test()
5) t2=t1
6) t3=t1
7) t4=t1
8) print(sys.getrefcount(t1))
Output 5
Note: For every object, Python internally maintains one default reference variable self.

nd
Polymorphism
Poly means many. Morphs means forms.
Polymorphism means 'Many Forms'.
Eg1: Yourself is best example of polymorphism.In front of Your parents You will have one type of
behaviour and with friends another type of behaviour.Same person but different behaviours at
different places,which is nothing but polymorphism.
Eg2: + operator acts as concatenation and arithmetic addition
Eg3: * operator acts as multiplication and repetition operator
Eg4: The Same method with different implementations in Parent class and child
classes.(overriding)
Related to polymorphism the following 4 topics are important
1. Duck Typing Philosophy of Python
2. Overloading
1. Operator Overloading
2. Method Overloading
3. Constructor Overloading
3. Overriding
1. Method overriding
2. constructor overriding
1. Duck Typing Philosophy of Python:
In Python we cannot specify the type explicitly. Based on provided value at runtime the type will
be considered automatically. Hence Python is considered as Dynamically Typed Programming
Language.
def f1(obj):
obj.talk()
What is the type of obj? We cannot decide at the beginning. At runtime we can pass any type.Then
how we can decide the type?
At runtime if 'it walks like a duck and talks like a duck,it must be duck'. Python follows this
principle. This is called Duck Typing Philosophy of Python.

nd
Demo Program:
1) class Duck:
2) def talk(self):
3) print('Quack.. Quack..')
4)
5) class Dog:
6) def talk(self):
7) print('Bow Bow..')
8)
9) class Cat:
10) def talk(self):
11) print('Moew Moew ..')
12)
13) class Goat:
14) def talk(self):
15) print('Myaah Myaah ..')
16)
17) def f1(obj):
18) obj.talk()
19)
20) l=[Duck(),Cat(),Dog(),Goat()]
21) for obj in l:
22) f1(obj)
Output:
Quack.. Quack..
Moew Moew ..
Bow Bow..
Myaah Myaah ..
The problem in this approach is if obj does not contain talk() method then we will get
AttributeError
Eg:
1) class Duck:
2) def talk(self):
4)
5) class Dog:
6) def bark(self):
8) def f1(obj):
9) obj.talk()
10)
11) d=Duck()
12) f1(d)
13)

nd
14) d=Dog()
15) f1(d)
Output:
Quack.. Quack..
Traceback (most recent call last):
File "test.py", line 22, in <module>
f1(d)
File "test.py", line 13, in f1
obj.talk()
AttributeError: 'Dog' object has no attribute 'talk'
But we can solve this problem by using hasattr() function.
hasattr(obj,'attributename')
attributename can be method name or variable name
Demo Program with hasattr() function:
1) class Duck:
2) def talk(self):
4)
5) class Human:
6) def talk(self):
7) print('Hello Hi...')
8)
9) class Dog:
10) def bark(self):
12)
13) def f1(obj):
14) if hasattr(obj,'talk'):
15) obj.talk()
16) elif hasattr(obj,'bark'):
17) obj.bark()
18)
19) d=Duck()
20) f1(d)
21)
22) h=Human()
23) f1(h)
24)
25) d=Dog()
26) f1(d)
27) Myaah Myaah Myaah...

nd
Overloading:
We can use same operator or methods for different purposes.
Eg1: + operator can be used for Arithmetic addition and String concatenation
print(10+20)#30
print('durga'+'soft')#durgasoft
Eg2: * operator can be used for multiplication and string repetition purposes.
print(10*20)#200
print('durga'*3)#durgadurgadurga
Eg3: We can use deposit() method to deposit cash or cheque or dd
deposit(cash)
deposit(cheque)
deposit(dd)
There are 3 types of overloading
1. Operator Overloading
2. Method Overloading
3. Constructor Overloading
1. Operator Overloading:
We can use the same operator for multiple purposes, which is nothing but operator overloading.
Python supports operator overloading.
Eg1: + operator can be used for Arithmetic addition and String concatenation
print(10+20)#30
print('durga'+'soft')#durgasoft
Eg2: * operator can be used for multiplication and string repetition purposes.
print(10*20)#200
print('durga'*3)#durgadurgadurga
Demo program to use + operator for our class objects:
1) class Book:
2) def __init__(self,pages):
3) self.pages=pages
4)
5) b1=Book(100)
6) b2=Book(200)
7) print(b1+b2)

nd
Traceback (most recent call last):
File "test.py", line 7, in <module>
print(b1+b2)
TypeError: unsupported operand type(s) for +: 'Book' and 'Book'
We can overload + operator to work with Book objects also. i.e Python supports Operator
Overloading.
For every operator Magic Methods are available. To overload any operator we have to override
that Method in our class.
Internally + operator is implemented by using __add__() method.This method is called magic
method for + operator. We have to override this method in our class.
Demo program to overload + operator for our Book class objects:
1) class Book:
2) def __init__(self,pages):
3) self.pages=pages
4)
5) def __add__(self,other):
6) return self.pages+other.pages
7)
8) b1=Book(100)
9) b2=Book(200)
10) print('The Total Number of Pages:',b1+b2)
Output: The Total Number of Pages: 300
The following is the list of operators and corresponding magic methods.
+ ---> object.__add__(self,other)
- ---> object.__sub__(self,other)
* ---> object.__mul__(self,other)
/ ---> object.__div__(self,other)
// ---> object.__floordiv__(self,other)
% ---> object.__mod__(self,other)
** ---> object.__pow__(self,other)
+= ---> object.__iadd__(self,other)
-= ---> object.__isub__(self,other)
*= ---> object.__imul__(self,other)
/= ---> object.__idiv__(self,other)
//= ---> object.__ifloordiv__(self,other)
%= ---> object.__imod__(self,other)
**= ---> object.__ipow__(self,other)
< ---> object.__lt__(self,other)
<= ---> object.__le__(self,other)
> ---> object.__gt__(self,other)
>= ---> object.__ge__(self,other)

nd
== ---> object.__eq__(self,other)
!= ---> object.__ne__(self,other)
Overloading > and <= operators for Student class objects:
1) class Student:
2) def __init__(self,name,marks):
3) self.name=name
4) self.marks=marks
5) def __gt__(self,other):
6) return self.marks>other.marks
7) def __le__(self,other):
8) return self.marks<=other.marks
9)
10)
11) print("10>20 =",10>20)
12) s1=Student("Durga",100)
13) s2=Student("Ravi",200)
14) print("s1>s2=",s1>s2)
15) print("s1<s2=",s1<s2)
16) print("s1<=s2=",s1<=s2)
17) print("s1>=s2=",s1>=s2)
Output:
10>20 = False
s1>s2= False
s1<s2= True
s1<=s2= True
s1>=s2= False
Program to overload multiplication operator to work on Employee objects:
1) class Employee:
2) def __init__(self,name,salary):
3) self.name=name
4) self.salary=salary
5) def __mul__(self,other):
6) return self.salary*other.days
7)
8) class TimeSheet:
9) def __init__(self,name,days):
10) self.name=name
11) self.days=days
12)
13) e=Employee('Durga',500)
14) t=TimeSheet('Durga',25)
15) print('This Month Salary:',e*t)
Output: This Month Salary: 12500

nd
2. Method Overloading:
If 2 methods having same name but different type of arguments then those methods are said to
be overloaded methods.
Eg: m1(int a)
m1(double d)
But in Python Method overloading is not possible.
If we are trying to declare multiple methods with same name and different number of arguments
then Python will always consider only last method.
Demo Program:
1) class Test:
2) def m1(self):
3) print('no-arg method')
4) def m1(self,a):
5) print('one-arg method')
6) def m1(self,a,b):
7) print('two-arg method')
8)
9) t=Test()
10) #t.m1()
11) #t.m1(10)
12) t.m1(10,20)
Output: two-arg method
In the above program python will consider only last method.
How we can handle overloaded method requirements in Python:
Most of the times, if method with variable number of arguments required then we can handle
with default arguments or with variable number of argument methods.
Demo Program with Default Arguments:
1) class Test:
2) def sum(self,a=None,b=None,c=None):
3) if a!=None and b!= None and c!= None:
4) print('The Sum of 3 Numbers:',a+b+c)
5) elif a!=None and b!= None:
6) print('The Sum of 2 Numbers:',a+b)
7) else:
8) print('Please provide 2 or 3 arguments')
9)
10) t=Test()

nd
11) t.sum(10,20)
12) t.sum(10,20,30)
13) t.sum(10)
Output:
The Sum of 2 Numbers: 30
The Sum of 3 Numbers: 60
Please provide 2 or 3 arguments
Demo Program with Variable Number of Arguments:
1) class Test:
2) def sum(self,*a):
3) total=0
4) for x in a:
5) total=total+x
6) print('The Sum:',total)
7)
8)
9) t=Test()
10) t.sum(10,20)
11) t.sum(10,20,30)
12) t.sum(10)
13) t.sum()
3. Constructor Overloading:
Constructor overloading is not possible in Python.
If we define multiple constructors then the last constructor will be considered.
1) class Test:
3) print('No-Arg Constructor')
4)
5) def __init__(self,a):
6) print('One-Arg constructor')
7)
8) def __init__(self,a,b):
9) print('Two-Arg constructor')
10) #t1=Test()
11) #t1=Test(10)
12) t1=Test(10,20)
Output: Two-Arg constructor

nd
In the above program only Two-Arg Constructor is available.
But based on our requirement we can declare constructor with default arguments and variable
number of arguments.
Constructor with Default Arguments:
1) class Test:
2) def __init__(self,a=None,b=None,c=None):
3) print('Constructor with 0|1|2|3 number of arguments')
4)
5) t1=Test()
6) t2=Test(10)
7) t3=Test(10,20)
8) t4=Test(10,20,30)
Output:
Constructor with 0|1|2|3 number of arguments
Constructor with Variable Number of Arguments:
1) class Test:
2) def __init__(self,*a):
3) print('Constructor with variable number of arguments')
4)
5) t1=Test()
6) t2=Test(10)
7) t3=Test(10,20)
8) t4=Test(10,20,30)
9) t5=Test(10,20,30,40,50,60)
Output:
Constructor with variable number of arguments

nd
Method overriding:
What ever members available in the parent class are bydefault available to the child class through
inheritance. If the child class not satisfied with parent class implementation then child class is
allowed to redefine that method in the child class based on its requirement. This concept is called
overriding.
Overriding concept applicable for both methods and constructors.
Demo Program for Method overriding:
1) class P:
2) def property(self):
3) print('Gold+Land+Cash+Power')
4) def marry(self):
5) print('Appalamma')
6) class C(P):
7) def marry(self):
8) print('Katrina Kaif')
9)
10) c=C()
11) c.property()
12) c.marry()
Output:
Gold+Land+Cash+Power
Katrina Kaif
From Overriding method of child class,we can call parent class method also by using super()
method.
1) class P:
2) def property(self):
3) print('Gold+Land+Cash+Power')
4) def marry(self):
5) print('Appalamma')
6) class C(P):
7) def marry(self):
8) super().marry()
9) print('Katrina Kaif')
10)
11) c=C()
12) c.property()
13) c.marry()
Output:
Gold+Land+Cash+Power
Appalamma
Katrina Kaif

nd
Demo Program for Constructor overriding:
1) class P:
3) print('Parent Constructor')
4)
5) class C(P):
7) print('Child Constructor')
8)
9) c=C()
Output: Child Constructor
In the above example,if child class does not contain constructor then parent class constructor will
be executed
From child class constuctor we can call parent class constructor by using super() method.
Demo Program to call Parent class constructor by using super():
1) class Person:
2) def __init__(self,name,age):
3) self.name=name
4) self.age=age
5)
6) class Employee(Person):
7) def __init__(self,name,age,eno,esal):
8) super().__init__(name,age)
9) self.eno=eno
10) self.esal=esal
11)
13) print('Employee Name:',self.name)
14) print('Employee Age:',self.age)
15) print('Employee Number:',self.eno)
16) print('Employee Salary:',self.esal)
17)
18) e1=Employee('Durga',48,872425,26000)
19) e1.display()
20) e2=Employee('Sunny',39,872426,36000)
21) e2.display()
Output:
Employee Name: Durga
Employee Age: 48
Employee Name: Sunny
Employee Age: 39

nd

1 DURGASOFT, # 202, 2nd
Regular Expressions
If we want to represent a group of Strings according to a particular format/pattern then we
should go for Regular Expressions.
i.e Regualr Expressions is a declarative mechanism to represent a group of Strings accroding to
particular format/pattern.
Eg 1: We can write a regular expression to represent all mobile numbers
Eg 2: We can write a regular expression to represent all mail ids.
The main important application areas of Regular Expressions are
1. To develop validation frameworks/validation logic
2. To develop Pattern matching applications (ctrl-f in windows, grep in UNIX etc)
3. To develop Translators like compilers, interpreters etc
4. To develop digital circuits
5. To develop communication protocols like TCP/IP, UDP etc.
We can develop Regular Expression Based applications by using python module: re
This module contains several inbuilt functions to use Regular Expressions very easily in our
applications.
1. compile()
re module contains compile() function to compile a pattern into RegexObject.
pattern = re.compile("ab")
2. finditer():
Returns an Iterator object which yields Match object for every Match
matcher = pattern.finditer("abaababa")
On Match object we can call the following methods.
1. start()  Returns start index of the match
2. end()  Returns end+1 index of the match
3. group()  Returns the matched string

Eg:
1) import re count=0
2) pattern=re.compile("ab")
3) matcher=pattern.finditer("abaababa")
4) for match in matcher:
5) count+=1
6) print(match.start(),"...",match.end(),"...",match.group())
7) print("The number of occurrences: ",count)
Output:
0 ... 2 ... ab
3 ... 5 ... ab
5 ... 7 ... ab
The number of occurrences: 3
Note: We can pass pattern directly as argument to finditer() function.
Eg:
1) import re
2) count=0
3) matcher=re.finditer("ab","abaababa")
5) count+=1
6) print(match.start(),"...",match.end(),"...",match.group())
7) print("The number of occurrences: ",count)
Output:
0 ... 2 ... ab
3 ... 5 ... ab
5 ... 7 ... ab
The number of occurrences: 3
Character classes:
We can use character classes to search a group of characters
1. [abc]===>Either a or b or c
2. [^abc] ===>Except a and b and c
3. [a-z]==>Any Lower case alphabet symbol
4. [A-Z]===>Any upper case alphabet symbol
5. [a-zA-Z]==>Any alphabet symbol
6. [0-9] Any digit from 0 to 9
7. [a-zA-Z0-9]==>Any alphanumeric character
8. [^a-zA-Z0-9]==>Except alphanumeric characters(Special Characters)

Eg:
1) import re
2) matcher=re.finditer("x","a7b@k9z")
4) print(match.start(),"......",match.group())
x = [abc]
0 ...... a
2 ...... b
x = [^abc]
1 ...... 7
3 ...... @
4 ...... k
5 ...... 9
6 ...... z
x = [a-z]
0 ...... a
2 ...... b
4 ...... k
6 ...... z
x = [0-9]
1 ...... 7
5 ...... 9
x = [a-zA-Z0-9]
0 ...... a
1 ...... 7
2 ...... b
4 ...... k
5 ...... 9
6 ...... z
x = [^a-zA-Z0-9]
3 ...... @
Pre defined Character classes:
s  Space character
S  Any character except space character
d  Any digit from 0 to 9
D  Any character except digit
w  Any word character [a-zA-Z0-9]
W  Any character except word character (Special Characters)
.  Any character including special characters

Eg:
1) import re
2) matcher=re.finditer("x","a7b k@9z")
x = s:
3 ......
x = S:
0 ...... a
1 ...... 7
2 ...... b
4 ...... k
5 ...... @
6 ...... 9
7 ...... z
x = d:
1 ...... 7
6 ...... 9
x = D:
0 ...... a
2 ...... b
3 ......
4 ...... k
5 ...... @
7 ...... z
x = w:
0 ...... a
1 ...... 7
2 ...... b
4 ...... k
6 ...... 9
7 ...... z
x = W:
3 ......
5 ...... @
x = .
0 ...... a
1 ...... 7
2 ...... b
3 ......

4 ...... k
5 ...... @
6 ...... 9
7 ...... z
Qunatifiers:
We can use quantifiers to specify the number of occurrences to match.
a  Exactly one 'a'
a+  Atleast one 'a'
a*  Any number of a's including zero number
a?  Atmost one 'a' ie either zero number or one number
a{m}  Exactly m number of a's
a{m,n}  Minimum m number of a's and Maximum n number of a's
Eg:
1) import re
2) matcher=re.finditer("x","abaabaaab")
x = a:
0 ...... a
2 ...... a
3 ...... a
5 ...... a
6 ...... a
7 ...... a
x = a+:
0 ...... a
2 ...... aa
5 ...... aaa
x = a*:
0 ...... a
1 ......
2 ...... aa
4 ......
5 ...... aaa
8 ......
9 ......

x = a?:
0 ...... a
1 ......
2 ...... a
3 ...... a
4 ......
5 ...... a
6 ...... a
7 ...... a
8 ......
9 ......
x = a{3}:
5 ...... aaa
x = a{2,4}:
2 ...... aa
5 ...... aaa
Note:
^x  It will check whether target string starts with x or not
x$  It will check whether target string ends with x or not
Important functions of re module:
1. match()
2. fullmatch()
3. search()
4.findall()
5.finditer()
6. sub()
7.subn()
8. split()
9. compile()
1. match():
We can use match function to check the given pattern at beginning of target string.
If the match is available then we will get Match object, otherwise we will get None.
Eg:
1) import re
2) s=input("Enter pattern to check: ")
3) m=re.match(s,"abcabdefg")
4) if m!= None:
5) print("Match is available at the beginning of the String")
6) print("Start Index:",m.start(), "and End Index:",m.end())

7) else:
8) print("Match is not available at the beginning of the String")
Output:
Enter pattern to check: abc
Match is available at the beginning of the String
Start Index: 0 and End Index: 3
Enter pattern to check: bde
Match is not available at the beginning of the String
2. fullmatch():
We can use fullmatch() function to match a pattern to all of target string. i.e complete string
should be matched according to given pattern.
If complete string matched then this function returns Match object otherwise it returns None.
Eg:
1) import re
3) m=re.fullmatch(s,"ababab")
4) if m!= None:
5) print("Full String Matched")
6) else:
7) print("Full String not Matched")
Output:
Enter pattern to check: ab
Full String not Matched
Enter pattern to check: ababab
Full String Matched
3. search():
We can use search() function to search the given pattern in the target string.
If the match is available then it returns the Match object which represents first occurrence of the
match.
If the match is not available then it returns None

Eg:
1) import re
3) m=re.search(s,"abaaaba")
4) if m!= None:
5) print("Match is available")
6) print("First Occurrence of match with start index:",m.start(),"and end index:",m.end())
7) else:
8) print("Match is not available")
Output:
Enter pattern to check: aaa
Match is available
First Occurrence of match with start index: 2 and end index: 5
Enter pattern to check: bbb
Match is not available
4. findall():
To find all occurrences of the match.
This function returns a list object which contains all occurrences.
Eg:
1) import re
2) l=re.findall("[0-9]","a7b9c5kz")
3) print(l)
Output: ['7', '9', '5']
5. finditer():
Returns the iterator yielding a match object for each match.
On each match object we can call start(), end() and group() functions.
Eg:
1) import re
2) itr=re.finditer("[a-z]","a7b9c5k8z")
3) for m in itr:
4) print(m.start(),"...",m.end(),"...",m.group())

Output:
0 ... 1 ... a
2 ... 3 ... b
4 ... 5 ... c
6 ... 7 ... k
8 ... 9 ... z
6. sub():
sub means substitution or replacement
re.sub(regex,replacement,targetstring)
In the target string every matched pattern will be replaced with provided replacement.
Eg:
1) import re
2) s=re.sub("[a-z]","#","a7b9c5k8z")
3) print(s)
Output: #7#9#5#8#
Every alphabet symbol is replaced with # symbol
7. subn():
It is exactly same as sub except it can also returns the number of replacements.
This function returns a tuple where first element is result string and second element is number of
replacements.
(resultstring, number of replacements)
Eg:
1) import re
2) t=re.subn("[a-z]","#","a7b9c5k8z")
3) print(t)
4) print("The Result String:",t[0])
5) print("The number of replacements:",t[1])
Output:
('#7#9#5#8#', 5)
The Result String: #7#9#5#8#
The number of replacements: 5

8. split():
If we want to split the given target string according to a particular pattern then we should go for
split() function.
This function returns list of all tokens.
Eg:
1) import re
2) l=re.split(",","sunny,bunny,chinny,vinny,pinny")
3) print(l)
4) for t in l:
5) print(t)
Output:
['sunny', 'bunny', 'chinny', 'vinny', 'pinny']
sunny
bunny
chinny
vinny
pinny
Eg:
1) import re
2) l=re.split(".","www.durgasoft.com")
3) for t in l:
4) print(t)
Output:
www
durgasoft
com
^ symbol:
We can use ^ symbol to check whether the given target string starts with our provided pattern or
not.
Eg:
res=re.search("^Learn",s)
if the target string starts with Learn then it will return Match object,otherwise returns None.

test.py:
1) import re
2) s="Learning Python is Very Easy"
3) res=re.search("^Learn",s)
4) if res != None:
5) print("Target String starts with Learn")
6) else:
7) print("Target String Not starts with Learn")
Output: Target String starts with Learn
$ symbol:
We can use $ symbol to check whether the given target string ends with our provided pattern or
not
Eg: res=re.search("Easy$",s)
If the target string ends with Easy then it will return Match object,otherwise returns None.
test.py:
1) import re
3) res=re.search("Easy$",s)
4) if res != None:
5) print("Target String ends with Easy")
6) else:
7) print("Target String Not ends with Easy")
Output: Target String ends with Easy
Note: If we want to ignore case then we have to pass 3rd argument re.IGNORECASE for search()
function.
Eg: res = re.search("easy$",s,re.IGNORECASE)
test.py:
1) import re
3) res=re.search("easy$",s,re.IGNORECASE)
4) if res != None:
5) print("Target String ends with Easy by ignoring case")
6) else:
7) print("Target String Not ends with Easy by ignoring case")

Output: Target String ends with Easy by ignoring case
App1: Write a Regular Expression to represent all Yava language identifiers
Rules:
1. The allowed characters are a-z,A-Z,0-9,#
2. The first character should be a lower case alphabet symbol from a to k
3. The second character should be a digit divisible by 3
4. The length of identifier should be atleast 2.
[a-k][0369][a-zA-Z0-9#]*
App2: Write a python program to check whether the given string is Yava
language identifier or not?
1) import re
2) s=input("Enter Identifier:")
3) m=re.fullmatch("[a-k][0369][a-zA-Z0-9#]*",s)
4) if m!= None:
5) print(s,"is valid Yava Identifier")
6) else:
7) print(s,"is invalid Yava Identifier")
Output:
Enter Identifier:a6kk9z##
a6kk9z## is valid Yava Identifier
Enter Identifier:k9b876
k9b876 is valid Yava Identifier
Enter Identifier:k7b9
k7b9 is invalid Yava Identifier
App3: Write a Regular Expression to represent all 10 digit mobile numbers.
Rules:
1. Every number should contains exactly 10 digits
2. The first digit should be 7 or 8 or 9
[7-9][0-9][0-9][0-9][0-9][0-9][0-9][0-9][0-9][0-9]
or

[7-9][0-9]{9}
or
[7-9]d{9}
App4: Write a Python Program to check whether the given number
is valid mobile number or not?
1) import re
2) n=input("Enter number:")
3) m=re.fullmatch("[7-9]d{9}",n)
4) if m!= None:
5) print("Valid Mobile Number")
6) else:
7) print("Invalid Mobile Number")
Output:
Enter number:9898989898
Valid Mobile Number
Enter number:6786786787
Invalid Mobile Number
Enter number:898989
Invalid Mobile Number
App5: Write a python program to extract all mobile numbers present in
input.txt where numbers are mixed with normal text data
1) import re
2) f1=open("input.txt","r")
3) f2=open("output.txt","w")
4) for line in f1:
5) list=re.findall("[7-9]d{9}",line)
6) for n in list:
7) f2.write(n+"n")
8) print("Extracted all Mobile Numbers into output.txt")
9) f1.close()
10) f2.close()

Web Scraping by using Regular Expressions:
The process of collecting information from web pages is called web scraping. In web scraping to
match our required patterns like mail ids, mobile numbers we can use regular expressions.
Eg:
1) import re,urllib
2) import urllib.request
3) sites="google rediff".split()
4) print(sites)
5) for s in sites:
6) print("Searching...",s)
7) u=urllib.request.urlopen("http://"+s+".com")
8) text=u.read()
9) title=re.findall("<title>.*</title>",str(text),re.I)
10) print(title[0])
Eg: Program to get all phone numbers of redbus.in by using web
scraping and regular expressions
1) import re,urllib
2) import urllib.request
3) u=urllib.request.urlopen("https://www.redbus.in/info/contactus")
4) text=u.read()
5) numbers=re.findall("[0-9-]{7}[0-9-]+",str(text),re.I)
7) print(n)
Q. Write a Python Program to check whether the given mail id is
valid gmail id or not?
1) import re
2) s=input("Enter Mail id:")
3) m=re.fullmatch("w[a-zA-Z0-9_.]*@gmail[.]com",s)
4) if m!=None:
5) print("Valid Mail Id");
6) else:
7) print("Invalid Mail id")
Output:
Enter Mail id:durgatoc@gmail.com
Valid Mail Id

Enter Mail id:durgatoc
Invalid Mail id
Enter Mail id:durgatoc@yahoo.co.in
Invalid Mail id
Q. Write a python program to check whether given car registration
number is valid Telangana State Registration number or not?
1) import re
2) s=input("Enter Vehicle Registration Number:")
3) m=re.fullmatch("TS[012][0-9][A-Z]{2}d{4}",s)
4) if m!=None:
5) print("Valid Vehicle Registration Number");
6) else:
7) print("Invalid Vehicle Registration Number")
Output:
Enter Vehicle Registration Number:TS07EA7777
Valid Vehicle Registration Number
Enter Vehicle Registration Number:TS07KF0786
Valid Vehicle Registration Number
Enter Vehicle Registration Number:AP07EA7898
Invalid Vehicle Registration Number
Q. Python Program to check whether the given mobile number is
valid OR not (10 digit OR 11 digit OR 12 digit)
1) import re
2) s=input("Enter Mobile Number:")
3) m=re.fullmatch("(0|91)?[7-9][0-9]{9}",s)
4) if m!=None:
5) print("Valid Mobile Number");
6) else:
7) print("Invalid Mobile Number")
Summary table and some more examples.

Multi Threading
Multi Tasking:
Executing several tasks simultaneously is the concept of multitasking.
There are 2 types of Multi Tasking
1. Process based Multi Tasking
2. Thread based Multi Tasking
1. Process based Multi Tasking:
Executing several tasks simmultaneously where each task is a seperate independent process is
called process based multi tasking.
Eg: while typing python program in the editor we can listen mp3 audio songs from the same
system. At the same time we can download a file from the internet. All these taks are executing
simultaneously and independent of each other. Hence it is process based multi tasking.
This type of multi tasking is best suitable at operating system level.
2. Thread based MultiTasking:
Executing several tasks simultaneously where each task is a seperate independent part of the
same program, is called Thread based multi tasking, and each independent part is called a Thread.
This type of multi tasking is best suitable at programmatic level.
Note: Whether it is process based or thread based, the main advantage of multi tasking is to
improve performance of the system by reducing response time.
The main important application areas of multi threading are:
1. To implement Multimedia graphics
2. To develop animations
3. To develop video games
4. To develop web and application servers
etc...
Note: Where ever a group of independent jobs are available, then it is highly recommended to
execute simultaneously instead of executing one by one.For such type of cases we should go for
Multi Threading.
Python provides one inbuilt module "threading" to provide support for developing threads. Hence
developing multi threaded Programs is very easy in python.

Every Python Program by default contains one thread which is nothing but MainThread.
Q.Program to print name of current executing thread:
1) import threading
2) print("Current Executing Thread:",threading.current_thread().getName())
o/p: Current Executing Thread: MainThread
Note: threading module contains function current_thread() which returns the current executing
Thread object. On this object if we call getName() method then we will get current executing
thread name.
The ways of Creating Thread in Python:
We can create a thread in Python by using 3 ways
1. Creating a Thread without using any class
2. Creating a Thread by extending Thread class
3. Creating a Thread without extending Thread class
1. Creating a Thread without using any class:
1) from threading import *
2) def display():
4) print("Child Thread")
5) t=Thread(target=display) #creating Thread object
6) t.start() #starting of Thread
8) print("Main Thread")
If multiple threads present in our program, then we cannot expect execution order and hence we
cannot expect exact output for the multi threaded programs. B'z of this we cannot provide exact
output for the above program.It is varied from machine to machine and run to run.
Note: Thread is a pre defined class present in threading module which can be used to create our
own Threads.
2. Creating a Thread by extending Thread class
We have to create child class for Thread class. In that child class we have to override run() method
with our required job. Whenever we call start() method then automatically run() method will be
executed and performs our job.
2) class MyThread(Thread):

3) def run(self):
5) print("Child Thread-1")
6) t=MyThread()
7) t.start()
9) print("Main Thread-1")
3. Creating a Thread without extending Thread class:
2) class Test:
5) print("Child Thread-2")
6) obj=Test()
7) t=Thread(target=obj.display)
8) t.start()
10) print("Main Thread-2")
Without multi threading:
2) import time
3) def doubles(numbers):
5) time.sleep(1)
6) print("Double:",2*n)
7) def squares(numbers):
9) time.sleep(1)
10) print("Square:",n*n)
11) numbers=[1,2,3,4,5,6]
12) begintime=time.time()
13) doubles(numbers)
14) squares(numbers)
15) print("The total time taken:",time.time()-begintime)
With multithreading:
2) import time
3) def doubles(numbers):
5) time.sleep(1)
6) print("Double:",2*n)
7) def squares(numbers):

9) time.sleep(1)
10) print("Square:",n*n)
11)
12) numbers=[1,2,3,4,5,6]
13) begintime=time.time()
14) t1=Thread(target=doubles,args=(numbers,))
15) t2=Thread(target=squares,args=(numbers,))
16) t1.start()
17) t2.start()
18) t1.join()
19) t2.join()
20) print("The total time taken:",time.time()-begintime)
Setting and Getting Name of a Thread:
Every thread in python has name. It may be default name generated by Python or Customized
Name provided by programmer.
We can get and set name of thread by using the following Thread class methods.
t.getName()  Returns Name of Thread
t.setName(newName)  To set our own name
Note: Every Thread has implicit variable "name" to represent name of Thread.
Eg:
2) print(current_thread().getName())
3) current_thread().setName("Pawan Kalyan")
4) print(current_thread().getName())
5) print(current_thread().name)
Output:
MainThread
Pawan Kalyan
Pawan Kalyan
Thread Identification Number (ident):
For every thread internally a unique identification number is available. We can access this id by
using implicit variable "ident"
2) def test():
4) t=Thread(target=test)

5) t.start()
6) print("Main Thread Identification Number:",current_thread().ident)
7) print("Child Thread Identification Number:",t.ident)
Output:
Child Thread
Main Thread Identification Number: 2492
Child Thread Identification Number: 2768
active_count():
This function returns the number of active threads currently running.
Eg:
2) import time
3) def display():
4) print(current_thread().getName(),"...started")
5) time.sleep(3)
6) print(current_thread().getName(),"...ended")
7) print("The Number of active Threads:",active_count())
8) t1=Thread(target=display,name="ChildThread1")
11) t1.start()
12) t2.start()
13) t3.start()
15) time.sleep(5)
Output:
The Number of active Threads: 1
ChildThread1 ...started
ChildThread1 ...ended
enumerate() function:
This function returns a list of all active threads currently running.
Eg:

2) import time
3) def display():
5) time.sleep(3)
10) t1.start()
11) t2.start()
12) t3.start()
13) l=enumerate()
14) for t in l:
15) print("Thread Name:",t.name)
16) time.sleep(5)
17) l=enumerate()
18) for t in l:
19) print("Thread Name:",t.name)
Output:
Thread Name: MainThread
Thread Name: ChildThread1
Thread Name: MainThread
isAlive():
isAlive() method checks whether a thread is still executing or not.
Eg:
2) import time
3) def display():
5) time.sleep(3)

9) t1.start()
10) t2.start()
11)
12) print(t1.name,"is Alive :",t1.isAlive())
14) time.sleep(5)
Output:
ChildThread1 is Alive : True
ChildThread2 is Alive : True
ChildThread1 is Alive : False
ChildThread2 is Alive : False
join() method:
If a thread wants to wait until completing some other thread then we should go for join() method.
Eg:
2) import time
3) def display():
5) print("Seetha Thread")
6) time.sleep(2)
7)
8) t=Thread(target=display)
9) t.start()
10) t.join()#This Line executed by Main Thread
12) print("Rama Thread")
In the above example Main Thread waited until completing child thread. In this case output is:
Seetha Thread
Seetha Thread
Seetha Thread
Seetha Thread
Seetha Thread
Seetha Thread
Seetha Thread

Seetha Thread
Seetha Thread
Seetha Thread
Rama Thread
Rama Thread
Rama Thread
Rama Thread
Rama Thread
Rama Thread
Rama Thread
Rama Thread
Rama Thread
Rama Thread
Note: We can call join() method with time period also.
t.join(seconds)
In this case thread will wait only specified amount of time.
Eg:
2) import time
3) def display():
5) print("Seetha Thread")
6) time.sleep(2)
7)
8) t=Thread(target=display)
9) t.start()
10) t.join(5)#This Line executed by Main Thread
12) print("Rama Thread")
In this case Main Thread waited only 5 seconds.
Output:
Seetha Thread
Seetha Thread
Seetha Thread
Rama Thread
Rama Thread
Rama Thread
Rama Thread
Rama Thread
Rama Thread
Rama Thread

Rama Thread
Rama Thread
Rama Thread
Seetha Thread
Seetha Thread
Seetha Thread
Seetha Thread
Seetha Thread
Seetha Thread
Seetha Thread
Summary of all methods related to threading module and Thread
Daemon Threads:
The threads which are running in the background are called Daemon Threads.
The main objective of Daemon Threads is to provide support for Non Daemon Threads( like main
thread)
Eg: Garbage Collector
Whenever Main Thread runs with low memory, immediately PVM runs Garbage Collector to
destroy useless objects and to provide free memory,so that Main Thread can continue its
execution without having any memory problems.
We can check whether thread is Daemon or not by using t.isDaemon() method of Thread class or
by using daemon property.
Eg:
2) print(current_thread().isDaemon()) #False
3) print(current_thread().daemon) #False
We can change Daemon nature by using setDaemon() method of Thread class.
t.setDaemon(True)
But we can use this method before starting of Thread.i.e once thread started,we cannot change its
Daemon nature,otherwise we will get
RuntimeException:cannot set daemon status of active thread
Eg:
2) print(current_thread().isDaemon())

3) current_thread().setDaemon(True)
RuntimeError: cannot set daemon status of active thread
Default Nature:
By default Main Thread is always non-daemon.But for the remaining threads Daemon nature will
be inherited from parent to child.i.e if the Parent Thread is Daemon then child thread is also
Daemon and if the Parent Thread is Non Daemon then ChildThread is also Non Daemon.
Eg:
2) def job():
4) t=Thread(target=job)
5) print(t.isDaemon())#False
6) t.setDaemon(True)
7) print(t.isDaemon()) #True
Note: Main Thread is always Non-Daemon and we cannot change its Daemon Nature b'z it is
already started at the beginning only.
Whenever the last Non-Daemon Thread terminates automatically all Daemon Threads will be
terminated.
Eg:
2) import time
3) def job():
5) print("Lazy Thread")
6) time.sleep(2)
7)
8) t=Thread(target=job)
9) #t.setDaemon(True)===>Line-1
10) t.start()
11) time.sleep(5)
12) print("End Of Main Thread")
In the above program if we comment Line-1 then both Main Thread and Child Threads are Non
Daemon and hence both will be executed until their completion.
In this case output is:
Lazy Thread
Lazy Thread
Lazy Thread

End Of Main Thread
Lazy Thread
Lazy Thread
Lazy Thread
Lazy Thread
Lazy Thread
Lazy Thread
Lazy Thread
If we are not commenting Line-1 then Main Thread is Non-Daemon and Child Thread is Daemon.
Hence whenever MainThread terminates automatically child thread will be terminated. In this
case output is
Lazy Thread
Lazy Thread
Lazy Thread
End of Main Thread
Synchronization:
If multiple threads are executing simultaneously then there may be a chance of data inconsistency
problems.
Eg:
2) import time
3) def wish(name):
5) print("Good Evening:",end='')
6) time.sleep(2)
7) print(name)
8) t1=Thread(target=wish,args=("Dhoni",))
9) t2=Thread(target=wish,args=("Yuvraj",))
10) t1.start()
11) t2.start()
Output:
Good Evening:Good Evening:Yuvraj
Dhoni
Good Evening:Good Evening:Yuvraj
Dhoni
....
We are getting irregular output b'z both threads are executing simultaneously wish() function.
To overcome this problem we should go for synchronization.

In synchronization the threads will be executed one by one so that we can overcome data
inconsistency problems.
Synchronization means at a time only one Thread
The main application areas of synchronization are
1. Online Reservation system
2. Funds Transfer from joint accounts
etc
In Python, we can implement synchronization by using the following
1. Lock
2. RLock
3. Semaphore
Synchronization By using Lock concept:
Locks are the most fundamental synchronization mechanism provided by threading module.
We can create Lock object as follows
l=Lock()
The Lock object can be hold by only one thread at a time.If any other thread required the same
lock then it will wait until thread releases lock.(similar to common wash rooms,public telephone
booth etc)
A Thread can acquire the lock by using acquire() method.
l.acquire()
A Thread can release the lock by using release() method.
l.release()
Note: To call release() method compulsory thread should be owner of that lock.i.e thread should
has the lock already,otherwise we will get Runtime Exception saying
RuntimeError: release unlocked lock
Eg:
2) l=Lock()
3) #l.acquire() ==>1
4) l.release()
If we are commenting line-1 then we will get
RuntimeError: release unlocked lock
Eg:

2) import time
3) l=Lock()
4) def wish(name):
5) l.acquire()
8) time.sleep(2)
9) print(name)
10) l.release()
11)
14) t3=Thread(target=wish,args=("Kohli",))
15) t1.start()
16) t2.start()
17) t3.start()
In the above program at a time only one thread is allowed to execute wish() method and hence we
will get regular output.
Problem with Simple Lock:
The standard Lock object does not care which thread is currently holding that lock.If the lock is
held and any thread attempts to acquire lock, then it will be blocked,even the same thread is
already holding that lock.
Eg:
2) l=Lock()
3) print("Main Thread trying to acquire Lock")
4) l.acquire()
5) print("Main Thread trying to acquire Lock Again")
6) l.acquire()
Output:
Main Thread trying to acquire Lock
Main Thread trying to acquire Lock Again
--
In the above Program main thread will be blocked b'z it is trying to acquire the lock second time.
Note: To kill the blocking thread from windows command prompt we have to use ctrl+break. Here
ctrl+C won't work.
If the Thread calls recursive functions or nested access to resources,then the thread may trying to
acquire the same lock again and again,which may block our thread.

Hence Traditional Locking mechanism won't work for executing recursive functions.
To overcome this problem, we should go for RLock(Reentrant Lock). Reentrant means the thread
can acquire the same lock again and again.If the lock is held by other threads then only the thread
will be blocked.
Reentrant facility is available only for owner thread but not for other threads.
Eg:
2) l=RLock()
3) print("Main Thread trying to acquire Lock")
4) l.acquire()
5) print("Main Thread trying to acquire Lock Again")
6) l.acquire()
In this case Main Thread won't be Locked b'z thread can acquire the lock any number of times.
This RLock keeps track of recursion level and hence for every acquire() call compulsory release()
call should be available. i.e the number of acquire() calls and release() calls should be matched
then only lock will be released.
Eg:
l=RLock()
l.acquire()
l.acquire()
l.release()
l.release()
After 2 release() calls only the Lock will be released.
Note:
1. Only owner thread can acquire the lock multiple times
2. The number of acquire() calls and release() calls should be matched.
Demo Program for synchronization by using RLock:
2) import time
3) l=RLock()
4) def factorial(n):
5) l.acquire()
6) if n==0:
7) result=1
8) else:
9) result=n*factorial(n-1)
10) l.release()
11) return result

12)
13) def results(n):
14) print("The Factorial of",n,"is:",factorial(n))
15)
16) t1=Thread(target=results,args=(5,))
17) t2=Thread(target=results,args=(9,))
18) t1.start()
19) t2.start()
Output:
The Factorial of 5 is: 120
The Factorial of 9 is: 362880
In the above program instead of RLock if we use normal Lock then the thread will be blocked.
Difference between Lock and RLock:
table
Lock:
1. Lock object can be acquired by only one thread at a time.Even owner thread also cannot acquire
multiple times.
2. Not suitable to execute recursive functions and nested access calls
3. In this case Lock object will takes care only Locked or unlocked and it never takes care about
owner thread and recursion level.
RLock:
1. RLock object can be acquired by only one thread at a time, but owner thread can acquire same
lock object multiple times.
2. Best suitable to execute recursive functions and nested access calls
3. In this case RLock object will takes care whether Locked or unlocked and owner thread
information, recursiion level.
Synchronization by using Semaphore:
In the case of Lock and RLock,at a time only one thread is allowed to execute.
Sometimes our requirement is at a time a particular number of threads are allowed to access(like
at a time 10 memebers are allowed to access database server,4 members are allowed to access
Network connection etc).To handle this requirement we cannot use Lock and RLock concepts and
we should go for Semaphore concept.
Semaphore can be used to limit the access to the shared resources with limited capacity.
Semaphore is advanced Synchronization Mechanism.

We can create Semaphore object as follows.
s=Semaphore(counter)
Here counter represents the maximum number of threads are allowed to access simultaneously.
The default value of counter is 1.
Whenever thread executes acquire() method,then the counter value will be decremented by 1 and
if thread executes release() method then the counter value will be incremented by 1.
i.e for every acquire() call counter value will be decremented and for every release() call counter
value will be incremented.
Case-1: s=Semaphore()
In this case counter value is 1 and at a time only one thread is allowed to access. It is exactly same
as Lock concept.
Case-2: s=Semaphore(3)
In this case Semaphore object can be accessed by 3 threads at a time.The remaining threads have
to wait until releasing the semaphore.
Eg:
2) import time
3) s=Semaphore(2)
4) def wish(name):
5) s.acquire()
8) time.sleep(2)
9) print(name)
10) s.release()
11)
15) t4=Thread(target=wish,args=("Rohit",))
16) t5=Thread(target=wish,args=("Pandya",))
17) t1.start()
18) t2.start()
19) t3.start()
20) t4.start()
21) t5.start()
In the above program at a time 2 threads are allowed to access semaphore and hence 2 threads
are allowed to execute wish() function.

BoundedSemaphore:
Normal Semaphore is an unlimited semaphore which allows us to call release() method any
number of times to increment counter.The number of release() calls can exceed the number of
acquire() calls also.
Eg:
2) s=Semaphore(2)
3) s.acquire()
4) s.acquire()
5) s.release()
6) s.release()
7) s.release()
8) s.release()
9) print("End")
It is valid because in normal semaphore we can call release() any number of times.
BounedSemaphore is exactly same as Semaphore except that the number of release() calls should
not exceed the number of acquire() calls,otherwise we will get
ValueError: Semaphore released too many times
Eg:
2) s=BoundedSemaphore(2)
3) s.acquire()
4) s.acquire()
5) s.release()
6) s.release()
7) s.release()
8) s.release()
9) print("End")
ValueError: Semaphore released too many times
It is invalid b'z the number of release() calls should not exceed the number of acquire() calls in
BoundedSemaphore.
Note: To prevent simple programming mistakes, it is recommended to use BoundedSemaphore
over normal Semaphore.
Difference between Lock and Semaphore:

At a time Lock object can be acquired by only one thread, but Semaphore object can be acquired
by fixed number of threads specified by counter value.
Conclusion:
The main advantage of synchronization is we can overcome data inconsistency problems.But the
main disadvantage of synchronization is it increases waiting time of threads and creates
performance problems. Hence if there is no specific requirement then it is not recommended to
use synchronization.
Inter Thread Communication:
Some times as the part of programming requirement, threads are required to communicate with
each other. This concept is nothing but interthread communication.
Eg: After producing items Producer thread has to communicate with Consumer thread to notify
about new item.Then consumer thread can consume that new item.
In Python, we can implement interthread communication by using the following ways
1. Event
2. Condition
3. Queue
etc
Interthread communication by using Event Objects:
Event object is the simplest communication mechanism between the threads. One thread signals
an event and other thereds wait for it.
We can create Event object as follows...
event = threading.Event()
Event manages an internal flag that can set() or clear()
Threads can wait until event set.
Methods of Event class:
1.set()  internal flag value will become True and it represents GREEN signal for all waiting
threads.
2. clear()  inernal flag value will become False and it represents RED signal for all waiting
threads.
3. isSet()  This method can be used whether the event is set or not

4. wait()|wait(seconds)  Thread can wait until event is set
Pseudo Code:
event = threading.Event()
#consumer thread has to wait until event is set
event.wait()
#producer thread can set or clear event
event.set()
event.clear()
Demo Program-1:
2) import time
3) def producer():
4) time.sleep(5)
5) print("Producer thread producing items:")
6) print("Producer thread giving notification by setting event")
7) event.set()
8) def consumer():
9) print("Consumer thread is waiting for updation")
10) event.wait()
11) print("Consumer thread got notification and consuming items")
12)
13) event=Event()
14) t1=Thread(target=producer)
15) t2=Thread(target=consumer)
16) t1.start()
17) t2.start()
Output:
Consumer thread is waiting for updation
Producer thread producing items
Producer thread giving notification by setting event
Consumer thread got notification and consuming items
Demo Program-2:
2) import time
3) def trafficpolice():
4) while True:
5) time.sleep(10)
6) print("Traffic Police Giving GREEN Signal")

7) event.set()
8) time.sleep(20)
9) print("Traffic Police Giving RED Signal")
10) event.clear()
11) def driver():
12) num=0
13) while True:
14) print("Drivers waiting for GREEN Signal")
15) event.wait()
16) print("Traffic Signal is GREEN...Vehicles can move")
17) while event.isSet():
18) num=num+1
19) print("Vehicle No:",num,"Crossing the Signal")
20) time.sleep(2)
21) print("Traffic Signal is RED...Drivers have to wait")
22) event=Event()
23) t1=Thread(target=trafficpolice)
24) t2=Thread(target=driver)
25) t1.start()
26) t2.start()
In the above program driver thread has to wait until Trafficpolice thread sets event.ie until giving
GREEN signal.Once Traffic police thread sets event(giving GREEN signal),vehicles can cross the
signal.Once traffic police thread clears event (giving RED Signal)then the driver thread has to wait.
Interthread communication by using Condition Object:
Condition is the more advanced version of Event object for interthread communication.A
condition represents some kind of state change in the application like producing item or
consuming item. Threads can wait for that condition and threads can be notified once condition
happend.i.e Condition object allows one or more threads to wait until notified by another thread.
Condition is always associated with a lock (ReentrantLock).
A condition has acquire() and release() methods that call the corresponding methods of the
associated lock.
We can create Condition object as follows
condition = threading.Condition()
Methods of Condition:
1. acquire()  To acquire Condition object before producing or consuming items.i.e thread
acquiring internal lock.
2. release()  To release Condition object after producing or consuming items. i.e thread releases
internal lock
3. wait()|wait(time)  To wait until getting Notification or time expired

4. notify()  To give notification for one waiting thread
5. notifyAll()  To give notification for all waiting threads
Case Study:
The producing thread needs to acquire the Condition before producing item to the resource and
notifying the consumers.
#Producer Thread
...generate item..
condition.acquire()
...add item to the resource...
condition.notify()#signal that a new item is available(notifyAll())
condition.release()
The Consumer must acquire the Condition and then it can consume items from the resource
#Consumer Thread
condition.acquire()
condition.wait()
consume item
condition.release()
Demo Program-1:
2) def consume(c):
3) c.acquire()
4) print("Consumer waiting for updation")
5) c.wait()
6) print("Consumer got notification & consuming the item")
7) c.release()
8)
9) def produce(c):
10) c.acquire()
11) print("Producer Producing Items")
12) print("Producer giving Notification")
13) c.notify()
14) c.release()
15)
16) c=Condition()
17) t1=Thread(target=consume,args=(c,))
18) t2=Thread(target=produce,args=(c,))
19) t1.start()
20) t2.start()

Output:
Consumer waiting for updation
Producer Producing Items
Producer giving Notification
Consumer got notification & consuming the item
Demo Program-2:
2) import time
3) import random
4) items=[]
5) def produce(c):
6) while True:
7) c.acquire()
8) item=random.randint(1,100)
9) print("Producer Producing Item:",item)
10) items.append(item)
12) c.notify()
13) c.release()
14) time.sleep(5)
15)
16) def consume(c):
17) while True:
18) c.acquire()
20) c.wait()
21) print("Consumer consumed the item",items.pop())
22) c.release()
23) time.sleep(5)
24)
25) c=Condition()
26) t1=Thread(target=consume,args=(c,))
27) t2=Thread(target=produce,args=(c,))
28) t1.start()
29) t2.start()
Output:
Producer Producing Item: 49
Consumer consumed the item 49
.....
In the above program Consumer thread expecting updation and hence it is responsible to call
wait() method on Condition object.
Producer thread performing updation and hence it is responsible to call notify() or notifyAll() on
Condition object.

Interthread communication by using Queue:
Queues Concept is the most enhanced Mechanism for interthread communication and to share
data between threads.
Queue internally has Condition and that Condition has Lock.Hence whenever we are using Queue
we are not required to worry about Synchronization.
If we want to use Queues first we should import queue module.
import queue
We can create Queue object as follows
q = queue.Queue()
Important Methods of Queue:
1. put(): Put an item into the queue.
2. get(): Remove and return an item from the queue.
Producer Thread uses put() method to insert data in the queue. Internally this method has logic to
acquire the lock before inserting data into queue. After inserting data lock will be released
automatically.
put() method also checks whether the queue is full or not and if queue is full then the Producer
thread will entered in to waiting state by calling wait() method internally.
Consumer Thread uses get() method to remove and get data from the queue. Internally this
method has logic to acquire the lock before removing data from the queue.Once removal
completed then the lock will be released automatically.
If the queue is empty then consumer thread will entered into waiting state by calling wait()
method internally.Once queue updated with data then the thread will be notified automatically.
Note:
The queue module takes care of locking for us which is a great advantage.
Eg:
2) import time
3) import random
4) import queue
5) def produce(q):

6) while True:
7) item=random.randint(1,100)
8) print("Producer Producing Item:",item)
9) q.put(item)
11) time.sleep(5)
12) def consume(q):
13) while True:
15) print("Consumer consumed the item:",q.get())
16) time.sleep(5)
17)
18) q=queue.Queue()
19) t1=Thread(target=consume,args=(q,))
20) t2=Thread(target=produce,args=(q,))
21) t1.start()
22) t2.start()
Output:
Producer Producing Item: 58
Consumer consumed the item: 58
Types of Queues:
Python Supports 3 Types of Queues.
1. FIFO Queue:
q = queue.Queue()
This is Default Behaviour. In which order we put items in the queue, in the same order the items
will come out (FIFO-First In First Out).
Eg:
1) import queue
2) q=queue.Queue()
3) q.put(10)
4) q.put(5)
5) q.put(20)
6) q.put(15)
7) while not q.empty():
8) print(q.get(),end=' ')
Output: 10 5 20 15

2. LIFO Queue:
The removal will be happend in the reverse order of insertion(Last In First Out)
Eg:
1) import queue
2) q=queue.LifoQueue()
3) q.put(10)
4) q.put(5)
5) q.put(20)
6) q.put(15)
Output: 15 20 5 10
3. Priority Queue:
The elements will be inserted based on some priority order.
1) import queue
2) q=queue.PriorityQueue()
3) q.put(10)
4) q.put(5)
5) q.put(20)
6) q.put(15)
Output: 5 10 15 20
Eg 2: If the data is non-numeric, then we have to provide our data in the form of tuple.
(x,y)
x is priority
y is our element
1) import queue
2) q=queue.PriorityQueue()
3) q.put((1,"AAA"))
4) q.put((3,"CCC"))
5) q.put((2,"BBB"))
6) q.put((4,"DDD"))
8) print(q.get()[1],end=' ')

Output: AAA BBB CCC DDD
Good Programming Practices with usage of Locks:
Case-1:
It is highly recommended to write code of releasing locks inside finally block.The advantage is lock
will be released always whether exception raised or not raised and whether handled or not
handled.
l=threading.Lock()
l.acquire()
try:
perform required safe operations
finally:
l.release()
Demo Program:
2) import time
3) l=Lock()
4) def wish(name):
5) l.acquire()
6) try:
9) time.sleep(2)
10) print(name)
11) finally:
12) l.release()
13)
17) t1.start()
18) t2.start()
19) t3.start()
Case-2:
It is highly recommended to acquire lock by using with statement. The main advantage of with
statement is the lock will be released automatically once control reaches end of with block and we
are not required to release explicitly.
This is exactly same as usage of with statement for files.

Example for File:
with open('demo.txt','w') as f:
f.write("Hello...")
Example for Lock:
lock=threading.Lock()
with lock:
perform required safe operations
lock will be released automatically
Demo Program:
2) import time
3) lock=Lock()
4) def wish(name):
5) with lock:
8) time.sleep(2)
9) print(name)
13) t1.start()
14) t2.start()
15) t3.start()
Q. What is the advantage of using with statement to acquire a lock in threading?
Lock will be released automatically once control reaches end of with block and We are not
required to release explicitly.
Note: We can use with statement in multithreading for the following cases:
1. Lock
2. RLock
3. Semaphore
4. Condition

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Python Database Programming
Storage Areas
As the Part of our Applications, we required to store our Data like Customers Information, Billing
Information, Calls Information etc..
To store this Data, we required Storage Areas. There are 2 types of Storage Areas.
1) Temporary Storage Areas
2) Permanent Storage Areas
1.Temporary Storage Areas:
These are the Memory Areas where Data will be stored temporarily.
Eg: Python objects like List, Tuple, Dictionary.
Once Python program completes its execution then these objects will be destroyed automatically
and data will be lost.
2. Permanent Storage Areas:
Also known as Persistent Storage Areas. Here we can store Data permanently.
Eg: File Systems, Databases, Data warehouses, Big Data Technologies etc
File Systems:
File Systems can be provided by Local operating System. File Systems are best suitable to store
very less Amount of Information.
Limitations:
1) We cannot store huge Amount of Information.
2) There is no Query Language support and hence operations will become very complex.
3) There is no Security for Data.
4) There is no Mechanism to prevent duplicate Data. Hence there may be a chance of Data
Inconsistency Problems.
To overcome the above Problems of File Systems, we should go for Databases.
Databases:
1) We can store Huge Amount of Information in the Databases.

nd
2) Query Language Support is available for every Database and hence we can perform Database
Operations very easily.
3) To access Data present in the Database, compulsory username and pwd must be required.
Hence Data is secured.
4) Inside Database Data will be stored in the form of Tables. While developing Database Table
Schemas, Database Admin follow various Normalization Techniques and can implement various
Constraints like Unique Key Constrains, Primary Key Constraints etc which prevent Data
Duplication. Hence there is no chance of Data Inconsistency Problems.
Limitations of Databases:
1) Database cannot hold very Huge Amount of Information like Terabytes of Data.
2) Database can provide support only for Structured Data (Tabular Data OR Relational Data) and
cannot provide support for Semi Structured Data (like XML Files) and Unstructured Data (like
Video Files, Audio Files, Images etc)
To overcome these Problems we should go for more Advanced Storage Areas like Big Data
Technologies, Data warehouses etc.
Python Database Programming:
Sometimes as the part of Programming requirement we have to connect to the database and we
have to perform several operations like creating tables, inserting data,updating data,deleting
data,selecting data etc.
We can use SQL Language to talk to the database and we can use Python to send those SQL
commands to the database.
Python provides inbuilt support for several databases like Oracle, MySql, SqlServer, GadFly, sqlite,
etc.
Python has seperate module for each database.
Eg: cx_Oralce module for communicating with Oracle database
pymssql module for communicating with Microsoft Sql Server
Standard Steps for Python database Programming:
1. Import database specific module
Eg: import cx_Oracle
2. Establish Connection between Python Program and database.
We can create this Connection object by using connect() function of the module.
con = cx_Oracle.connect(datbase information)
Eg: con=cx_Oracle.connect('scott/tiger@localhost')
3. To execute our sql queries and to hold results some special object is required, which is nothing
but Cursor object. We can create Cursor object by using cursor() method.

nd
cursor=con.cursor()
4. Execute SQL Queries By using Cursor object. For this we can use the following methods
i) execute(sqlquery)  To execute a single sql query
ii) executescript(sqlqueries)  To execute a string of sql queries seperated by semi-colon ';'
iii) executemany()  To execute a Parameterized query
Eg: cursor.execute("select * from employees")
5. commit or rollback changes based on our requirement in the case of DML
Queries(insert|update|delete)
commit()  Saves the changes to the database
rollback()  rolls all temporary changes back
6. Fetch the result from the Cursor object in the case of select queries
fetchone()  To fetch only one row
fetchall()  To fetch all rows and it returns a list of rows
fecthmany(n)  To fetch first n rows
Eg 1: data =cursor.fetchone()
print(data)
Eg 2: data=cursor.fetchall()
for row in data:
print(row)
7. close the resources
After completing our operations it is highly recommended to close the resources in the reverse
order of their opening by using close() methods.
cursor.close()
con.close()
Note: The following is the list of all important methods which can be used for python database
programming.
connect()
cursor()
execute()
executescript()
executemany()
commit()
rollback()
fetchone()
fetchall()
fetchmany(n)

nd
fetch
close()
These methods won't be changed from database to database and same for all databases.
Working with Oracle Database:
From Python Program if we want to communicate with any database,some translator must be
required to translate Python calls into Database specific calls and Database specific calls into
Python calls.This translator is nothing but Driver/Connector.
Diagram
For Oracle database the name of driver needed is cx_Oracle.
cx_Oracle is a Python extension module that enables access to Oracle Database.It can be used for
both Python2 and Python3. It can work with any version of Oracle database like 9,10,11 and 12.
Installing cx_Oracle:
From Normal Command Prompt (But not from Python console)execute the following command
D:python_classes>pip install cx_Oracle
Collecting cx_Oracle
Downloading cx_Oracle-6.0.2-cp36-cp36m-win32.whl (100kB)
100% |-----------| 102kB 256kB/s
Installing collected packages: cx-Oracle
Successfully installed cx-Oracle-6.0.2
How to Test Installation:
From python console execute the following command:
>>> help("modules")
In the output we can see cx_Oracle
....
_multiprocessing crypt ntpath timeit
_opcode csv nturl2path tkinter
_operator csvr numbers token
_osx_support csvw opcode tokenize
_overlapped ctypes operator trace
_pickle curses optparse traceback
_pydecimal custexcept os tracemalloc
_pyio cx_Oracle parser try
_random data pathlib tty
_sha1 datetime pdb turtle

nd
_sha256 dbm pick turtledemo
_sha3 decimal pickle types
_sha512 demo pickletools typing
_signal difflib pip unicodedata
_sitebuiltins dis pipes unittest
_socket distutils pkg_resources unpick
_sqlite3 doctest pkgutil update
_sre dummy_threading platform urllib
_ssl durgamath plistlib uu
_stat easy_install polymorph uuid
.....
App1: Program to connect with Oracle database and print its version.
1) import cx_Oracle
2) con=cx_Oracle.connect('scott/tiger@localhost')
3) print(con.version)
4) con.close()
Output:
D:python_classes>py db1.py
11.2.0.2.0
App2: Write a Program to create employees table in the oracle database :
employees(eno,ename,esal,eaddr)
1) import cx_Oracle
2) try:
4) cursor=con.cursor()
5) cursor.execute("create table employees(eno number,ename varchar2(10),esal number(10,2),eaddr varchar2(10))")
6) print("Table created successfully")
7) except cx_Oracle.DatabaseError as e:
8) if con:
9) con.rollback()
10) print("There is a problem with sql",e)
11) finally:
12) if cursor:
13) cursor.close()
14) if con:
15) con.close()
App3: Write a program to drop employees table from oracle database?
1) import cx_Oracle
2) try:
5) cursor.execute("drop table employees")
6) print("Table dropped successfully")
8) if con:
9) con.rollback()
11) finally:
12) if cursor:
13) cursor.close()
14) if con:
15) con.close()
App3: Write a program to insert a single row in the employees table.

nd
1) import cx_Oracle
2) try:
5) cursor.execute("insert into employees values(100,'Durga',1000,'Hyd')")
6) con.commit()
7) print("Record Inserted Successfully")
9) if con:
10) con.rollback()
12) finally:
13) if cursor:
14) cursor.close()
15) if con:
16) con.close()
Note: While performing DML Operations (insert|update|delte), compulsory we have to use
commit() method,then only the results will be reflected in the database.
App4: Write a program to insert multiple rows in the employees table by
using executemany() method.
1) import cx_Oracle
2) try:
5) sql="insert into employees values(:eno,:ename,:esal,:eaddr)"
6) records=[(200,'Sunny',2000,'Mumbai'),
7) (300,'Chinny',3000,'Hyd'),
8) (400,'Bunny',4000,'Hyd')]
9) cursor.executemany(sql,records)
10) con.commit()
11) print("Records Inserted Successfully")
13) if con:
14) con.rollback()
16) finally:
17) if cursor:
18) cursor.close()
19) if con:
20) con.close()
App5: Write a program to insert multiple rows in the employees table with
dynamic input from the keyboard?
1) import cx_Oracle
2) try:
5) while True:
6) eno=int(input("Enter Employee Number:"))
10) sql="insert into employees values(%d,'%s',%f,'%s')"
11) cursor.execute(sql %(eno,ename,esal,eaddr))
12) print("Record Inserted Successfully")
13) option=input("Do you want to insert one more record[Yes|No] :")
14) if option=="No":
15) con.commit()
16) break
18) if con:
19) con.rollback()
20) print("There is a problem with sql :",e)
21) finally:
22) if cursor:
23) cursor.close()
24) if con:
25) con.close()

nd
App6: Write a program to update employee salaries with increment for the
certain range with dynamic input.
Eg: Increment all employee salaries by 500 whose salary < 5000
1) import cx_Oracle
2) try:
5) increment=float(input("Enter Increment Salary:"))
6) salrange=float(input("Enter Salary Range:"))
7) sql="update employees set esal=esal+%f where esal<%f"
8) cursor.execute(sql %(increment,salrange))
9) print("Records Updated Successfully")
10) con.commit()
12) if con:
13) con.rollback()
15) finally:
16) if cursor:
17) cursor.close()
18) if con:
19) con.close()
App7: Write a program to delete employees whose salary greater provided
salary as dynamic input?
Eg: delete all employees whose salary > 5000
1) import cx_Oracle
2) try:
5) cutoffsalary=float(input("Enter CutOff Salary:"))
6) sql="delete from employees where esal>%f"
7) cursor.execute(sql %(cutoffsalary))
8) print("Records Deleted Successfully")
9) con.commit()
11) if con:
12) con.rollback()
14) finally:
15) if cursor:
16) cursor.close()
17) if con:
18) con.close()
App8: Write a program to select all employees info by using fetchone()
method?
1) import cx_Oracle
2) try:
5) cursor.execute("select * from employees")
6) row=cursor.fetchone()
7) while row is not None:
8) print(row)
9) row=cursor.fetchone()
11) if con:
12) con.rollback()
14) finally:
15) if cursor:
16) cursor.close()
17) if con:
18) con.close()

nd
App9: Write a program to select all employees info by using fetchall()
method?
1) import cx_Oracle
2) try:
6) data=cursor.fetchall()
7) for row in data:
8) print("Employee Number:",row[0])
9) print("Employee Name:",row[1])
10) print("Employee Salary:",row[2])
11) print("Employee Address:",row[3])
12) print()
13) print()
15) if con:
16) con.rollback()
18) finally:
19) if cursor:
20) cursor.close()
21) if con:
22) con.close()
App10: Write a program to select employees info by using fetchmany()
method and the required number of rows will be provided as dynamic input?
1) import cx_Oracle
2) try:
6) n=int(input("Enter the number of required rows:"))
7) data=cursor.fetchmany(n)
8) for row in data:
9) print(row)
11) if con:
12) con.rollback()
14) finally:
15) if cursor:
16) cursor.close()
17) if con:
18) con.close()
Output:
Enter the number of required rows:3
(100, 'Durga', 1500.0, 'Hyd')
(200, 'Sunny', 2500.0, 'Mumbai')
(300, 'Chinny', 3500.0, 'Hyd')
Enter the number of required rows:4
(100, 'Durga', 1500.0, 'Hyd')
(200, 'Sunny', 2500.0, 'Mumbai')
(300, 'Chinny', 3500.0, 'Hyd')
(400, 'Bunny', 4500.0, 'Hyd')
Working with Mysql database:
Current version: 5.7.19
Vendor: SUN Micro Systems/Oracle Corporation

nd
Open Source and Freeware
Default Port: 3306
Default user: root
Note: In MySQL, everything we have to work with our own databases, which are also known as
Logical Databases.
The following are 4 default databases available in mysql.
1. information_schema
2. mysql
3. performance_schema
4. test
Diagram
In the above diagram only one physical database is available and 4 logical databases are available.
Commonly used commands in MySql:
1. To know available databases:
mysql> show databases;
2. To create our own logical database
mysql> create database durgadb;
3. To drop our own database:
mysql> drop database durgadb;
4. To use a particular logical database
mysql> use durgadb; OR mysql> connect durgadb;
5. To create a table:
create table employees(eno int(5) primary key,ename varchar(10),esal double(10,2),eaddr
varchar(10));
6. To insert data:
insert into employees values(100,'Durga',1000,'Hyd');
insert into employees values(200,'Ravi',2000,'Mumbai');
In MySQL instead of single quotes we can use double quotes also.
Driver/Connector Information:
From Python program if we want to communicates with MySql database,compulsory some
translator is required to convert python specific calls into mysql database specific calls and mysql
database specific calls into python specific calls. This translator is nothing but Driver or Connector.

nd
Diagram
We have to download connector seperately from mysql database.
https://dev.mysql.com/downloads/connector/python/2.1.html
How to check installation:
From python console we have to use
help("modules")
In the list of modules,compulsory mysql should be there.
Note: In the case of Python3.4 we have to set PATH and PYTHONPATH explicitly
PATH=C:Python34
PYTHONPATH=C:Python34Libsite-packages
Q. Write a Program to create table,insert data and display data by using mysql database.
1) import mysql.connector
2) try:
3) con=mysql.connector.connect(host='localhost',database='durgadb',user='root',password='root')
5) cursor.execute("create table employees(eno int(5) primary key,ename varchar(10),esal double(10,2),eaddr varchar(
10))")
6) print("Table Created...")
7)
8) sql = "insert into employees(eno, ename, esal, eaddr) VALUES(%s, %s, %s, %s)"
9) records=[(100,'Sachin',1000,'Mumbai'),
10) (200,'Dhoni',2000,'Ranchi'),
11) (300,'Kohli',3000,'Delhi')]
12) cursor.executemany(sql,records)
13) con.commit()
14) print("Records Inserted Successfully...")
15)
18) for row in data:
19) print("Employee Number:",row[0])
20) print("Employee Name:",row[1])
21) print("Employee Salary:",row[2])
22) print("Employee Address:",row[3])
23) print()
24) print()
25) except mysql.connector.DatabaseError as e:
26) if con:
27) con.rollback()
29) finally:
30) if cursor:
31) cursor.close()
32) if con:
33) con.close()
Q. Write a Program to copy data present in employees table of mysql database into Oracle
database.
1) import mysql.connector
2) import cx_Oracle
3) try:
4) con=mysql.connector.connect(host='localhost',database='durgadb',user='root',password='root')

nd
8) list=[]
9) for row in data:
10) t=(row[0],row[1],row[2],row[3])
11) list.append(t)
12) except mysql.connector.DatabaseError as e:
13) if con:
14) con.rollback()
15) print("There is a problem with MySql :",e)
16) finally:
17) if cursor:
18) cursor.close()
19) if con:
20) con.close()
21)
22) try:
25) sql="insert into employees values(:eno,:ename,:esal,:eaddr)"
26) cursor.executemany(sql,list)
27) con.commit()
28) print("Records Copied from MySQL Database to Oracle Database Successfully")
30) if con:
31) con.rollback()
33) finally:
34) if cursor:
35) cursor.close()
36) if con:
37) con.close()
https://dev.mysql.com/downloads/connector/python/2.1.html
1) create table employees(eno int(5) primary key,ename varchar(10),esal double(10,2),eaddr varchar(10));
2)
3) insert into employees values(100,'Durga',1000,'Hyd');
4) insert into employees values(200,'Ravi',2000,'Mumbai');
5) insert into employees values(300,'Shiva',3000,'Hyd');

nd
Pattern Programs
Pattern-1:
* * * * * * * * * *
* * * * * * * * * *
* * * * * * * * * *
* * * * * * * * * *
* * * * * * * * * *
* * * * * * * * * *
* * * * * * * * * *
* * * * * * * * * *
* * * * * * * * * *
* * * * * * * * * *
1) n=int(input("Enter the number of rows: "))
3) print("* "*n)
Pattern-2:
1 1 1 1 1 1 1 1 1 1
2 2 2 2 2 2 2 2 2 2
3 3 3 3 3 3 3 3 3 3
4 4 4 4 4 4 4 4 4 4
5 5 5 5 5 5 5 5 5 5
6 6 6 6 6 6 6 6 6 6
7 7 7 7 7 7 7 7 7 7
8 8 8 8 8 8 8 8 8 8
9 9 9 9 9 9 9 9 9 9
10 10 10 10 10 10 10 10 10 10
3) for j in range(1,n+1):
4) print(i,end=" ")
5) print()
Pattern-3:
1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 7 8 9 10

nd
1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 7 8 9 10
4) print(j,end=" ")
5) print()
Pattern-4:
A A A A A A A A A A
B B B B B B B B B B
C C C C C C C C C C
D D D D D D D D D D
E E E E E E E E E E
F F F F F F F F F F
G G G G G G G G G G
H H H H H H H H H H
I I I I I I I I I I
J J J J J J J J J J
4) print(chr(64+i),end=" ")
5) print()
Pattern-5:
A B C D E F G H I J
A B C D E F G H I J
A B C D E F G H I J
A B C D E F G H I J
A B C D E F G H I J
A B C D E F G H I J
A B C D E F G H I J
A B C D E F G H I J
A B C D E F G H I J
A B C D E F G H I J

nd
4) print(chr(64+j),end=" ")
5) print()
Pattern-6:
10 10 10 10 10 10 10 10 10 10
9 9 9 9 9 9 9 9 9 9
8 8 8 8 8 8 8 8 8 8
7 7 7 7 7 7 7 7 7 7
6 6 6 6 6 6 6 6 6 6
5 5 5 5 5 5 5 5 5 5
4 4 4 4 4 4 4 4 4 4
3 3 3 3 3 3 3 3 3 3
2 2 2 2 2 2 2 2 2 2
1 1 1 1 1 1 1 1 1 1
4) print(n+1-i,end=" ")
5) print()
Pattern-6:
10 9 8 7 6 5 4 3 2 1
10 9 8 7 6 5 4 3 2 1
10 9 8 7 6 5 4 3 2 1
10 9 8 7 6 5 4 3 2 1
10 9 8 7 6 5 4 3 2 1
10 9 8 7 6 5 4 3 2 1
10 9 8 7 6 5 4 3 2 1
10 9 8 7 6 5 4 3 2 1
10 9 8 7 6 5 4 3 2 1
10 9 8 7 6 5 4 3 2 1
4) print(n+1-j,end=" ")
5) print()

nd
Pattern-7:
J J J J J J J J J J
I I I I I I I I I I
H H H H H H H H H H
G G G G G G G G G G
F F F F F F F F F F
E E E E E E E E E E
D D D D D D D D D D
C C C C C C C C C C
B B B B B B B B B B
A A A A A A A A A A
4) print(chr(65+n-i),end=" ")
5) print()
Pattern-8:
J I H G F E D C B A
J I H G F E D C B A
J I H G F E D C B A
J I H G F E D C B A
J I H G F E D C B A
J I H G F E D C B A
J I H G F E D C B A
J I H G F E D C B A
J I H G F E D C B A
J I H G F E D C B A
4) print(chr(65+n-j),end=" ")
5) print()
Pattern-9:
*
* *
* * *
* * * *
* * * * *
* * * * * *
* * * * * * *

nd
* * * * * * * *
* * * * * * * * *
* * * * * * * * * *
Code - 1:
1) n=int(input("Enter the number of rows:"))
4) print("*",end=" ")
5) print()
Code - 2:
1) n=int(input("Enter the number of rows:"))
3) print("* "*i)
Pattern-10:
1
2 2
3 3 3
4 4 4 4
5 5 5 5 5
6 6 6 6 6 6
7 7 7 7 7 7 7
8 8 8 8 8 8 8 8
9 9 9 9 9 9 9 9 9
10 10 10 10 10 10 10 10 10 10
4) print(i,end=" ")
5) print()
Pattern-11:
1
1 2
1 2 3
1 2 3 4
1 2 3 4 5
1 2 3 4 5 6
1 2 3 4 5 6 7
1 2 3 4 5 6 7 8

nd
1 2 3 4 5 6 7 8 9
1 2 3 4 5 6 7 8 9 10
4) print(j,end=" ")
5) print()
Pattern-12:
A
B B
C C C
D D D D
E E E E E
F F F F F F
G G G G G G G
H H H H H H H H
I I I I I I I I I
J J J J J J J J J J
5) print()
Pattern-13:
A
A B
A B C
A B C D
A B C D E
A B C D E F
A B C D E F G
A B C D E F G H
A B C D E F G H I
A B C D E F G H I J
5) print()

nd
 Squares
 Right Angled Triangle
 Reverse of Right Angled Triangle
Pattern-14:
* * * * * * * * * *
* * * * * * * * *
* * * * * * * *
* * * * * * *
* * * * * *
* * * * *
* * * *
* * *
* *
*
3) for j in range(1,n+2-i):
4) print("*",end=" ")
5) print()
Pattern-15:
1 1 1 1 1 1 1 1 1 1
2 2 2 2 2 2 2 2 2
3 3 3 3 3 3 3 3
4 4 4 4 4 4 4
5 5 5 5 5 5
6 6 6 6 6
7 7 7 7
8 8 8
9 9
10
4) print(i,end=" ")
5) print()

nd
Pattern-16:
1 2 3 4 5 6 7 8 9 10
1 2 3 4 5 6 7 8 9
1 2 3 4 5 6 7 8
1 2 3 4 5 6 7
1 2 3 4 5 6
1 2 3 4 5
1 2 3 4
1 2 3
1 2
1
4) print(j,end=" ")
5) print()
Pattern-17:
A A A A A A A A A A
B B B B B B B B B
C C C C C C C C
D D D D D D D
E E E E E E
F F F F F
G G G G
H H H
I I
J
5) print()
Pattern-18:
A B C D E F G H I J
A B C D E F G H I
A B C D E F G H
A B C D E F G
A B C D E F
A B C D E
A B C D

nd
A B C
A B
A
5) print()
Pattern-19:
10 10 10 10 10 10 10 10 10 10
9 9 9 9 9 9 9 9 9
8 8 8 8 8 8 8 8
7 7 7 7 7 7 7
6 6 6 6 6 6
5 5 5 5 5
4 4 4 4
3 3 3
2 2
1
4) print(n+1-i,end=" ")
5) print()
Pattern-20:
10 9 8 7 6 5 4 3 2 1
10 9 8 7 6 5 4 3 2
10 9 8 7 6 5 4 3
10 9 8 7 6 5 4
10 9 8 7 6 5
10 9 8 7 6
10 9 8 7
10 9 8
10 9
10
5) print()

nd
Pattern-21:
J J J J J J J J J J
I I I I I I I I I
H H H H H H H H
G G G G G G G
F F F F F F
E E E E E
D D D D
C C C
B B
A
4) print(chr(65+n-i),end=" ")
5) print()
Pattern-22:
J I H G F E D C B A
J I H G F E D C B
J I H G F E D C
J I H G F E D
J I H G F E
J I H G F
J I H G
J I H
J I
J
4) print(chr(65+n-j),end=" ")
5) print()
Pattern-23:
*
**
***
****
*****
******
*******

nd
********
*********
**********
3) print(" "*(n-i),"*"*i,end=" ")
4) print()
Pattern-24:
*
* *
* * *
* * * *
* * * * *
* * * * * *
* * * * * * *
* * * * * * * *
* * * * * * * * *
* * * * * * * * * *
3) print(" "*(n-i),end="")
5) print("*",end=" ")
6) print()
Pattern-25:
1
2 2
3 3 3
4 4 4 4
5 5 5 5 5
6 6 6 6 6 6
7 7 7 7 7 7 7
8 8 8 8 8 8 8 8

nd
9 9 9 9 9 9 9 9 9
10 10 10 10 10 10 10 10 10 10
3) print(" "*(n-i),(str(i)+" ")*i)
4) print()
Pattern-26:
1
1 2
1 2 3
1 2 3 4
1 2 3 4 5
1 2 3 4 5 6
1 2 3 4 5 6 7
1 2 3 4 5 6 7 8
1 2 3 4 5 6 7 8 9
1 2 3 4 5 6 7 8 9 10
3) print(" "*(n-i),end="")
5) print(j,end=" ")
6) print()
Pattern-27:
A
B B
C C C
D D D D
E E E E E
F F F F F F
G G G G G G G
H H H H H H H H

nd
3) print(" "*(n-i),(chr(64+i)+" ")*i)
4) print()
Pattern-28:
A
A B
A B C
A B C D
A B C D E
A B C D E F
A B C D E F G
A B C D E F G H
A B C D E F G H I
A B C D E F G H I J
3) print(" "*(n-i),end="")
6) print()
Pattern-29:
* * * * *
* * * *
* * *
* *
*
3) print(" "*(i-1),"* "*(n+1-i))
Pattern-30:
5 5 5 5 5
4 4 4 4
3 3 3
2 2
1

nd
3) print(" "*(i-1),(str(n+1-i)+" ")*(n+1-i))
Pattern-31:
1 2 3 4 5
1 2 3 4
1 2 3
1 2
1
3) print(" "*(i-1),end="")
5) print(j,end=" ")
6) print()
Pattern-32:
E E E E E
D D D D
C C C
B B
A
3) print(" "*(i-1),(str(chr(65+n-i))+" ")*(n+1-i))
Pattern-33:
A B C D E
A B C D
A B C
A B
A
3) print(" "*(i-1),end="")
4) for j in range(65,66+n-i):
5) print(chr(j),end=" ")
6) print()

nd
Pattern-34:
*
* * *
* * * * *
* * * * * * *
* * * * * * * * *
3) print(" "*(n-i),"* "*(2*i-1))
Pattern-35:
1
2 2 2
3 3 3 3 3
4 4 4 4 4 4 4
5 5 5 5 5 5 5 5 5
3) print(" "*(n-i),(str(i)+" ")*(2*i-1))
Pattern-36:
A
B B B
C C C C C
D D D D D D D
E E E E E E E E E
3) print(" "*(n-i),(str(chr(64+i)+" "))*(2*i-1))
Pattern-37:
A
C C C
E E E E E
G G G G G G G
I I I I I I I I I

nd
3) print(" "*(n-i),(str(chr(64+2*i-1)+" "))*(2*i-1))
Pattern-38:
1
1 2 3
1 2 3 4 5
1 2 3 4 5 6 7
1 2 3 4 5 6 7 8 9
3) print(" "*(n-i),end="")
4) for j in range(1,2*i):
5) print(j,end=" ")
6) print()
Pattern-39:
1
3 2 1
5 4 3 2 1
7 6 5 4 3 2 1
9 8 7 6 5 4 3 2 1
3) print(" "*(n-i),end="")
4) for j in range(2*i-1,0,-1):
5) print(j,end=" ")
6) print()
Pattern-40:
A
A B C
A B C D E
A B C D E F G
A B C D E F G H I
3) print(" "*(n-i),end="")
4) for j in range(65,65+2*i-1):

nd
6) print()
Pattern-41:
A
C B A
E D C B A
G F E D C B A
I H G F E D C B A
3) print(" "*(n-i),end="")
4) for j in range(65+2*i-2,64,-1):
6) print()
Pattern-42:
0
1 0 1
2 1 0 1 2
3 2 1 0 1 2 3
4 3 2 1 0 1 2 3 4
3) print(" "*(n-i),end="")
4) for j in range(1,i):
5) print(i-j,end=" ")
6) for k in range(0,i):
7) print(k,end=" ")
8) print()
Pattern-43:
A
B A B
C B A B C
D C B A B C D
E D C B A B C D E
3) print(" "*(n-i),end="")

nd
5) print(chr(i-j+65),end=" ")
7) print(chr(k+65),end=" ")
8) print()
Pattern-44:
1
1 2 1
1 2 3 2 1
1 2 3 4 3 2 1
1 2 3 4 5 4 3 2 1
3) print(" "*(n-i),end="")
5) print(j,end=" ")
6) for k in range(i-1,0,-1):
7) print(k,end=" ")
8) print()
Pattern-45:
A
A B A
A B C A B
A B C D A B C
A B C D E A B C D
3) print(" "*(n-i),end="")
7) print(chr(64+k),end=" ")
8) print()
Pattern-46:
1) n=int(input("Enter a number:"))
3) print(" "*(n-i),end="")

nd
6) print()
5
5 4
5 4 3
5 4 3 2
5 4 3 2 1
Pattern-47:
1) num=int(input("Enter a number:"))
2) for i in range(1,num+1):
3) print(" "*(i-1),end="")
4) for j in range(1,num+2-i):
5) print("*",end=" ")
6) for k in range(1,num+1-i):
7) print("*",end=" ")
8) print()
* * * * * * * * *
* * * * * * *
* * * * *
* * *
*
Pattern-48:
3) print(" "*(i-1),end="")
5) print(num+1-i,end=" ")
8) print()
5 5 5 5 5 5 5 5 5
4 4 4 4 4 4 4
3 3 3 3 3
2 2 2
1

nd
Pattern-49:
3) print(" "*(i-1),end="")
5) print(2*num+1-2*i,end=" ")
7) print(2*num+1-2*i,end=" ")
8) print()
9 9 9 9 9 9 9 9 9
7 7 7 7 7 7 7
5 5 5 5 5
3 3 3
1
Pattern-50:
3) print(" "*(i-1),end="")
5) print(j,end=" ")
7) print(num+k-i,end=" ")
8) print()
1 2 3 4 5 6 7
1 2 3 4 5
1 2 3
1
Pattern-51:
3) print(" "*(i-1),end="")
5) print(chr(65+num-i),end=" ")
8) print()

nd
E E E E E E E E E
D D D D D D D
C C C C C
B B B
A
Pattern-52:
3) print(" "*(i-1),end="")
5) print(chr(65+2*num-2*i),end=" ")
7) print(chr(65+2*num-2*i),end=" ")
8) print()
I I I I I I I I I
G G G G G G G
E E E E E
C C C
A
Pattern-53:
3) print(" "*(i-1),end="")
7) print(chr(68+k-i),end=" ")
8) print()
A B C D E F G
A B C D E
A B C
A
Pattern-54:
3) print(" "*(num-i),end="")
5) print(j,end=" ")

nd
6) print()
7) for k in range(1,num):
8) print(" "*k,end="")
9) for l in range(1,num+1-k):
10) print(l,end=" ")
11) print()
1
1 2
1 2 3
1 2 3 4
1 2 3 4 5
1 2 3 4
1 2 3
1 2
1
Pattern-55:
5) print("*",end=" ")
6) print()
10) print("*",end=" ")
11) print()
*
* *
* * *
* * * *
* * * * *
* * * *
* * *
* *
*
Pattern-56:

nd
5) print(num-j,end=" ")
6) print()
10) print(num-l,end=" ")
11) print()
4
4 3
4 3 2
4 3 2 1
4 3 2 1 0
4 3 2 1
4 3 2
4 3
4
Pattern-57:
5) print(num+j-i,end=" ")
6) print()
10) print(l+k-1,end=" ")
11) print()
3
2 3
1 2 3
0 1 2 3
1 2 3
2 3
3
Pattern-58:
5) print(chr(65+num+j-i),end=" ")

nd
6) print()
9) for l in range(0,num-k):
10) print(chr(65+k+l),end=" ")
11) print()
E
D E
C D E
B C D E
A B C D E
B C D E
C D E
D E
E
Pattern-59:
4) print("*",end=" ")
5) print()
6) for a in range(1,num+1):
7) for k in range(1,num+1-a):
8) print("*",end=" ")
9) print()
*
* *
* * *
* * * *
* * * * *
* * * *
* * *
* *
*
Pattern-60:
4) print(num-j,end=" ")
5) print()
7) for k in range(1,num+1-a):

nd
8) print(num-k,end=" ")
9) print()
4
4 3
4 3 2
4 3 2 1
4 3 2 1 0
4 3 2 1
4 3 2
4 3
4
Pattern-61:
4) print(num-i+j-1,end=" ")
5) print()
7) for k in range(0,num-a):
8) print(k+a,end=" ")
9) print()
4
3 4
2 3 4
1 2 3 4
0 1 2 3 4
1 2 3 4
2 3 4
3 4
4
Pattern-62:
5) print()
7) for k in range(0,num-a):
8) print(chr(65+a),end=" ")
9) print()

nd
E
D D
C C C
B B B B
A A A A A
B B B B
C C C
D D
E
Pattern-63:
3) print(chr(65+num-j),end=" ")
4) print()
6) for k in range(num-a,0,-1):
7) print(chr(64+k+a),end=" ")
8) print()
E
E D
E D C
E D C B
E D C B A
E D C B
E D C
E D
E
Pattern-64:
4) print(chr(64+num-i+j),end=" ")
5) print()
7) for k in range(1,num-a+1):
8) print(chr(64+k+a),end=" ")
9) print()

nd
E
D E
C D E
B C D E
A B C D E
B C D E
C D E
D E
E
Pattern-65:
5) print("*",end=" ")
6) print()
*
* *
* * *
* * * *
* * * * *
Pattern-66:
5) print(i,end=" ")
6) print()
1
2 2
3 3 3
4 4 4 4
5 5 5 5 5
Pattern-67:

nd
4) for j in range(1,1+i):
5) print(j,end=" ")
6) print()
1
1 2
1 2 3
1 2 3 4
1 2 3 4 5
Pattern-68:
6) print()
A
B B
C C C
D D D D
E E E E E
Pattern-69:
6) print()
A
A B
A B C
A B C D
A B C D E
Pattern-70:
3) print(" "*(i-1),end="")

nd
5) print("*",end=" ")
6) print()
* * * * *
* * * *
* * *
* *
*
Pattern-71:
3) print(" "*(i-1),end="")
5) print(num-i+1,end=" ")
6) print()
5 5 5 5 5
4 4 4 4
3 3 3
2 2
1
Pattern-72:
3) print(" "*(i-1),end="")
5) print(num+2-i-j,end=" ")
6) print()
5 4 3 2 1
4 3 2 1
3 2 1
2 1
1
Pattern-73:
3) print(" "*(i-1),end="")
6) print()

nd
E E E E E
D D D D
C C C
B B
A
Pattern-74:
3) print(" "*(i-1),end="")
5) print(chr(65+num+1-i-j),end=" ")
6) print()
E D C B A
D C B A
C B A
B A
A
Pattern-75:
3) print(" "*(i-1),end="")
6) print()
A B C D E
A B C D
A B C
A B
A
Pattern-76:
5) print("*",end=" ")
6) print()
7) for p in range(1,num):
8) print(" "*p,end="")

nd
9) for q in range(1,num+1-p):
10) print("*",end=" ")
11) print()
*
* *
* * *
* * * *
* * * * *
* * * *
* * *
* *
*
Pattern-77:
5) print(i,end=" ")
6) print()
10) print(num-p,end=" ")
11) print()
1
2 2
3 3 3
4 4 4 4
5 5 5 5 5
4 4 4 4
3 3 3
2 2
1
Pattern-78:
5) print(j,end=" ")
6) print()

nd
10) print(q+p,end=" ")
11) print()
1
1 2
1 2 3
1 2 3 4
1 2 3 4 5
2 3 4 5
3 4 5
4 5
5
Pattern-79:
5) print(j,end=" ")
6) print()
10) print(q,end=" ")
11) print()
1
1 2
1 2 3
1 2 3 4
1 2 3 4 5
1 2 3 4
1 2 3
1 2
1
Pattern-80:
6) print()

nd
10) print(chr(64+num-p),end=" ")
11) print()
A
B B
C C C
D D D D
E E E E E
D D D D
C C C
B B
A
Pattern-81:
6) print()
10) print(chr(64+q+p),end=" ")
11) print()
A
A B
A B C
A B C D
A B C D E
B C D E
C D E
D E
E
Pattern-82:
3) print(" "*(n-i),end="")
5) print(n-i+j,end=" ")

nd
6) for k in range(2,i+1):
7) print(n+1-k,end=" ")
8) print()
10) print(" "*i,end="")
11) for j in range(1+i,n+1):
12) print(j,end=" ")
13) for k in range(2,n+1-i):
14) print(n+1-k,end=" ")
15) print()
5
4 5 4
3 4 5 4 3
2 3 4 5 4 3 2
1 2 3 4 5 4 3 2 1
2 3 4 5 4 3 2
3 4 5 4 3
4 5 4
5
Pattern-83:
1) while True:
4) print(" "*(n-i),end="")
8) print(n-i+k,end=" ")
9) print()
11) print(" "*i,end="")
14) for k in range(2,n+1-i):
15) print(i+k,end=" ")
16) print()
5
5 4 5
5 4 3 4 5
5 4 3 2 3 4 5
5 4 3 2 1 2 3 4 5
5 4 3 2 3 4 5
5 4 3 4 5
5 4 5

nd
5
Pattern-84:
4) for j in range(i,i+1):
5) print("*",end=" ")
6) if i>=2:
7) print(" "*(2*i-4),end="")
8) for k in range(i,i+1):
9) print("*",end=" ")
10) print()
*
* *
* *
* *
* *
Pattern-85:
5) print(i,end=" ")
6) if i>=2:
7) print(" "*(2*i-4),end="")
9) print(i,end=" ")
10) print()
1
2 2
3 3
4 4
5 5
Pattern-86:

nd
6) if i>=2:
7) print(" "*(2*i-4),end="")
10) print()
5
4 4
3 3
2 2
1 1
Pattern-87:
5) print(chr(64+num+1-i),end=" ")
6) if i>=2:
7) print(" "*(2*i-4),end="")
9) print(chr(64+num+1-i),end=" ")
10) print()
E
D D
C C
B B
A A
Pattern-88:
6) if i>=2:
7) print(" "*(2*i-4),end="")
10) print()

nd
A
B B
C C
D D
E E
Pattern-89:
3) print(" "*(i-1),end="")
5) print("*",end=" ")
6) if i<=4:
7) print(" "*(2*num-2*i-2),end="")
9) print("*",end=" ")
10) print()
* *
* *
* *
* *
*
Pattern-90:
3) print(" "*(i-1),end="")
5) print(i,end=" ")
6) if i<num:
7) print(" "*(2*num-2*i-2),end="")
9) print(i,end=" ")
10) print()
1 1
2 2
3 3
4 4
5

nd
Pattern-91:
3) print(" "*(i-1),end="")
6) if i<=4:
7) print(" "*(2*num-2*i-2),end="")
10) print()
5 5
4 4
3 3
2 2
1
Pattern-92:
3) print(" "*(i-1),end="")
5) print(chr(64+num-i+1),end=" ")
6) if i<=4:
7) print(" "*(2*num-2*i-2),end="")
9) print(chr(64+num-i+1),end=" ")
10) print()
E E
D D
C C
B B
A
Pattern-93:
3) print(" "*(i-1),end="")
6) if i<=4:

nd
7) print(" "*(2*num-2*i-2),end="")
10) print()
A A
B B
C C
D D
E
Pattern-94:
3) print(" "*(i-1),end="")
4) for j in range(1,num+1):
5) print("*",end=" ")
6) print()
* * * * *
* * * * *
* * * * *
* * * * *
* * * * *
Pattern-95:
5) print("*",end=" ")
8) print("*",end=" ")
9) print()
* *
* * * *
* * * * * *
* * * * * * * *
* * * * * * * * * *

nd
Pattern-96:
4) if (i%2!=0 and j%2!=0 )or(i%2==0 and j%2==0):
5) print("1",end=" ")
6) else:
7) print("0",end=" ")
8) print()
1
0 1
1 0 1
0 1 0 1
1 0 1 0 1
0 1 0 1 0 1
1 0 1 0 1 0 1
Pattern-97:
3) print(" "*(2*num-i+3),end="")
5) print("*",end=" ")
6) print()
8) print(" "*(2*num-i+1),end="")
9) for j in range(-1,i+1):
10) print("*",end=" ")
11) print()
13) print(" "*(2*num-i),end="")
14) for j in range(-2,i+1):
15) print("*",end=" ")
16) print()
18) print(" "*((2*num)),end="")
19) print("* "*3)

nd
*
* *
* * *
* * * *
* * *
* * * *
* * * * *
* * * * * *
* * * * * * *
* * * * * * * *
* * * *
* * * * *
* * * * * *
* * * * * * *
* * * * * * * *
* * * * * * * * *
* * * * * * * * * *
* * * * * * * * * * *
* * *
* * *
* * *
* * *
* * *
* * *
Pattern-98:
1) num=int(input("Enter a number"))
3) print(" "*(2*num-i),end="")
5) print("*",end=" ")
6) print()
10) print("*",end=" ")
13) print("*",end=" ")
14) print()
*
* *
* * *
* * * *
* * * * *
* *

nd
* * * *
* * * * * *
* * * * * * * *
* * * * * * * * * *
Pattern-99:
1) n=int(input("Enter a number"))
2) for i in range(1,2*n+1):
3) if i%2==0:
4) print("*"*i,end=" ")
5) else:
6) print("*"*(i+1),end=" ")
7) print()
**
**
****
****
******
******
********
********
**********
**********
Pattern-100:
2) for a in range(1,n+1,2):
4) print(" "*(2*n-i-a),end="")
5) for j in range(1,i+a):
6) print("*",end=" ")
7) print()
8) for b in range(1,n+1):
9) print(" "*(n-2),end="")
10) print("* "*3)

nd
*
* *
* * *
* * * *
* * * * *
* * * * * *
* * * * * * *
* * * * * * * *
* * *
* * * *
* * * * *
* * * * * *
* * * * * * *
* * * * * * * *
* * * * * * * * *
* * * * * * * * * *
* * * * *
* * * * * *
* * * * * * *
* * * * * * * *
* * * * * * * * *
* * * * * * * * * *
* * * * * * * * * * *
* * * * * * * * * * * *
* * * * * * *
* * * * * * * *
* * * * * * * * *
* * * * * * * * * *
* * * * * * * * * * *
* * * * * * * * * * * *
* * * * * * * * * * * * *
* * * * * * * * * * * * * *
* * *
* * *
* * *
* * *
* * *
* * *
* * *
* * *

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