Python Tutorial | Python Tutorial for Beginners | Python Training | Edureka

www.edureka.co/pythonEDUREKA PYTHON CERTIFICATION TRAINING
What is Hadoop?

Agenda
➢ Python Introduction
➢ Who uses Python?
➢ Python Features
➢ Operators in Python
➢ Datatypes in Python
➢ Flow Control
➢ Functions in Python
➢ File Handling in Python

Python Introduction

Python Introduction
➢ Python is an interpreted, object-oriented, high-level programming language
with dynamic semantics
➢ Python was created by Guido Rossum in 1989 and is very easy to learn
Procedure
Oriented
Object
Oriented
Easy to
Learn
High Level
Language

Who uses Python?

Who Uses Python?
The popular YouTube video
sharing service is largely
written in Python.
C O M P A N I E S U S I N G P Y T H O N
Google makes extensive use of
Python in its web search
systems.
The Raspberry Pi single-
board computer promotes
Python as its educational
language.
Dropbox storage service
codes both its server and
desktop client software
primarily in Python.
BitTorrent peer-to-peer file
sharing system began its life
as a Python program.
NASA, Los Alamos, Fermilab,
JPL, and others use Python
for scientific programming
tasks.
The NSA uses Python for
cryptography and
intelligence analysis.
Netflix and Yelp have both
documented the role of
Python in their software
infrastructures.

Python Features

Python Features
Simple and Easy to Learn
Free and Open Source
Python is a simple and easy to learn, read & write
Python is an example of a FLOSS (Free/Libre and Open Source
Software) which means one can freely distribute copies of this
software, read it's source code, modify it, etc.

Python Features
High-level Language
Portable
One does not need to bother about the low-level details
like memory allocation, etc. while writing Python
script
Supported by many platforms like Linux, Windows, FreeBSD,
Macintosh, Solaris, OS/2, Amiga, AROS, AS/400, BeOS, OS/390,
PlayStation, Windows CE, etc.
a=3
b=5
sum=a+b
print(sum)
01001010110110
11101100001101
10110101100101
0101011010
compile

Python Features
Python code can invoke C and C++ libraries, can be called from and C++
programs, can integrate with Java
and .NET components
Python supports procedure-oriented programming as well as
object-oriented programming.
Supports different Programming Paradigm
Object
Oriented
Procedure
Oriented
C/C++ Extensible

Zen of Python
C/C++

Installation Steps

Python Installation
Go to www.python.org1
Under Downloads tab,
select the latest Python
version for Windows
2

Open the installer and click on Run3
Python Installation

4 Select ‘Add Python 3.6 to PATH’
5 Click on Install Now
Python Installation

6 Start IDLE which is a Python GUI & start scripting
Python Installation

C/C++
IDLE stands for integrated
Development and Learning
Environment
Python Installation

Operators in Python

Arithmetic Operators
Assignment Operators
Comparison Operators
Logical Operators
Bitwise Operators
Identity Operators
Special Operators
Operators in Python
1
2
3
4
5
6
7

Logical Operators
Bitwise Operators
Identity Operators
Special Operators
1
2
3
4
5
6
7
+
Add two operands or unary plus
-
Subtract two operands or unary subtract
*
Multiply two operands
/
Divide left operand with the right and result
is in float
>> 2 + 3
5
>> +2
>> 3 – 1
2
>> -2
>> 2 * 3
6
>> 6 / 3
2.0

Logical Operators
Bitwise Operators
Identity Operators
Special Operators
1
2
3
4
5
6
7
**
Left operand raised to the power of right
% Remainder of the division of left operand
by the right
// division that results into whole number
adjusted to the left in the number line
>> 2 + 3
5
>> +2
>> 3 – 1
2
>> -2
>> 2 * 3
6

Logical Operators
Bitwise Operators
Identity Operators
Arithmetic Operators1
Assignment Operators2
3
4
5
6
Special Operators7
/=
x = x / <right operand>
%=
x = x % <right operand>
//=
x = x // <right operand>
**=
x = x ** <right operand>
>> x/=5
>> print(x)
1.0
>> x%=5
>> print(x)
0
>> x //= 2
>> print(x)
2
>> x**= 5
>> print(x)
32
>> x = 5

Logical Operators
Bitwise Operators
Identity Operators
3
4
5
6
Special Operators7
&=
x = x & <right operand>
|=
x = x | <right operand>
^=
x = x ^ <right operand>
>>=
x = x >> <right operand>
>> x&=2
>> print(x)
0
>> x|=2
>> print(x)
>> 7
>> x ^= 2
>> print(x)
7
>> x >>=
2
>> print(x)
1
>> x = 5

Logical Operators
Bitwise Operators
Identity Operators
Comparison Operators3
4
5
6
Special Operators7
>
True if left operand is greater than the right
<
True if left operand is less than the right
==
True if left operand is equal to right
!=
True if left operand is not equal to the right
>> 2 > 3
False
>> 2 < 3
True
>>2 == 2
True
>> x >>=
2
>>print(x)
1

Logical Operators

Logical Operators
Bitwise Operators
Identity Operators
Logical Operators4
5
6
Special Operators7
and
Returns x if x is False , y otherwise
or
Returns y if x is False, x otherwise
not
Returns True if x is True, False otherwise
>> 2 and
3
3
>> 2 or 3
2
>> not 1
False

Bitwise Operators

Bitwise Operators
Identity Operators
Logical Operators4
Bitwise Operators5
6
Membership Operators7
a | b
Perform OR operation on each bit of the no.
a & b Perform AND operation on each bit of the
number
a ^ b Perform XOR operation on each bit of
the number
111 7
101 5
111 7
111 7
101 5
111 5
111 7
101 5
111 2

Bitwise Operators
Identity Operators
Logical Operators4
6
a >> b
Shift a right by b bits
a << b
Shift a left by b bits
3 >> 2 = 0
0011 0000
3 << 2 = 12
0011 1100Bitwise Operators5

Identity Operators

Identity Operators
Logical Operators4
Bitwise Operators5
Identity Operators6
is
True if the operands are identical (refer to
the same object)
is not True if the operands are not identical (do
not refer to the same object)
>> x = 5
>> x is 5
True
>> x = 5
>> x is not 5
False

Membership Operators

Membership Operators
Logical Operators4
Bitwise Operators5
Identity Operators6
is
True if the operands are identical (refer to the
same object)
is not True if the operands are not identical (do not
refer to the same object)
>> 3 in x
True
>> 3 not in x
False
X = [1, 2, 3, 4, 5]

Datatypes

Datatype
C/C++
➢ No need to declare variables before using them
➢ Python is a loosely typed language. Therefore, no need to define the datatype of variables
Datatype
Numbers Strings Tuples Lists Dictionaries Sets
Immutable Mutable

Datatype
Tuples
Numbers
Strings
Lists
Dictionaries
Sets
Mutable
Immutable

Datatype
Tuples
Numbers
Strings
Lists
Dictionaries
Sets
Mutable
Immutable
➢ Strings are sequences of one-character strings
Example:
sample = ‘Welcome to Python Tutorial’
or
sample = “Welcome to Python Tutorial”
➢ Multi-line strings can be denoted using triple quotes, ''' or ""“
Example:
sample = “””Don’t Go Gentle into the good Night
Rage! Rage, against the dying light”””

Datatype
Tuples
Numbers
Strings
Lists
Dictionaries
Sets
Mutable
Immutable
Sequence Operations:
➢ Concatenation:
➢ Repetition
➢ Slicing
➢ Indexing
‘Python’ ‘Tutorial’ ‘Edureka Tutorial’
‘Edureka’ 2 ‘EdurekaEdureka’
**
string1 = ‘Edureka’ string1[2:7] ‘ureka’
string1 = ‘Edureka’ string1[-1] + string[1] ‘da’

Datatype
Tuples
Numbers
Strings
Lists
Dictionaries
Sets
Mutable
Immutable
Type Specific Method:
➢ find():
➢ replace()
➢ split()
➢ count()
str = ‘Edureka’ str.find ( ‘ureka’ ) ‘ureka’
str = ‘Edureka’ str.replace ( ‘Ed’,’E’ ) ‘Eureka’
str = ‘E, d, u, r, e, k, a’ s.split ( ‘,’ )
[‘E’, ‘d’, ‘u’, ‘r’, ‘e’, ‘k’,
‘a’]
str = ‘Edureka’ str.count(‘e’, beg=2, end=6) 2

Datatype
Tuples
Numbers
Strings
Lists
Dictionaries
Sets
Mutable
Immutable
Type Specific Method:
➢ upper():
➢ max()
➢ min()
➢ isalpha()
str = ‘edureka’ str.upper () ‘EDUREKA’
str = ‘Edureka’ max (str) ‘u’
min ( str ) ‘a’
str = ‘Edureka’
str = ‘Edureka’
str.isalpha() True

Datatype
Tuples
Numbers
Strings
Lists
Dictionaries
Sets
Mutable
Immutable ➢ A tuple is a sequence of immutable Python objects like floating number, string
literals, etc.
➢ The tuples can’t be changed unlike lists
➢ Tuples are defined using curve braces
myTuple = ( ‘Edureka’ , 2.4, 5, ‘Python’ )

Datatype
Tuples
Numbers
Strings
Lists
Dictionaries
Sets
Mutable
Immutable
➢ Concatenation:
➢ Repetition
➢ Slicing
➢ Indexing
tup = ( ‘a’ , ‘b’ , ‘c’ ) tup +( ‘d’ ) ( ‘a’ , ‘b’ , ‘c’ , ‘d’ )
tup = ( ‘a’ , ‘b’ , ‘c’ ) tup[1:2] ( ‘b’ , ‘c’ )
tup = ( ‘a’ , ‘b’ , ‘c’ ) tup[0] ‘a’
tup = ( ‘a’ , ‘b’ , ‘c’ ) tup * 2 (‘a’ , ‘b’ , ‘c’ , ‘a’ , ‘b’ ,
‘c’ )

Datatype
Tuples
Numbers
Strings
Lists
Dictionaries
Sets
Mutable
Immutable ➢ A list is a sequence of mutable Python objects like floating number, string literals,
etc.
➢ The lists can be modified
➢ Tuples are defined using square braces
myList = [ ‘Edureka’ , 2.4, 5, ‘Python’ ]

Datatype
Tuples
Numbers
Strings
Lists
Dictionaries
Sets
Mutable
Immutable
➢ Concatenation:
➢ Repetition
➢ Slicing
➢ Indexing
[ ‘1’ , ‘b’ , 2.5 ] ‘d’ [ 1 , ‘b’ , 2.5 , ‘d’ ]
[ ‘a’ , ‘b’ , 2.5 ] 2 [‘a’ , ‘b’ , ‘a’ , ‘b’ ]
**
list = [‘a’ , ‘b’ , ‘c’ ,’d’] list[1:3] ( ‘b’ , ‘c’, ‘d’ )
list = [‘a’ , ‘b’ , ‘c’] list[0] ‘a’

Datatype
Tuples
Numbers
Strings
Lists
Dictionaries
Sets
Mutable
Immutable
Type Specific Method
➢ append(value)
➢ extend(list)
➢ insert(index, value)
➢ pop()
list = [1, ‘a’, 2.5] List.append (‘d’ ) [ 1 , ‘a’ , 2.5 , ‘d’ ]
list = [1, ‘a’, 2.5] list.extend ( [‘c’, ‘d’] ) [1 , ‘a’ , 2.5 , ‘c’, ‘d’]
list = [1, ‘a’, 2.5] List.insert(2,’b’) [1, ’a’, ‘b’ , 2.5 ]
list = [‘a’ , ‘b’ , ‘c’] List.pop() [ ‘a’, ‘b’ ]

Datatype
Tuples
Numbers
Strings
Lists
Dictionaries
Sets
Mutable
Immutable
➢ Dictionaries are perhaps the most flexible built-in data type in Python
➢ Dictionaries, items are stored and fetched by key, instead of by positional
offset
Key
Value
myDict = { 1: ‘Josh’ , 2: ‘Bob’, 3: ‘James’ }

Datatype
Tuples
Numbers
Strings
Lists
Dictionaries
Sets
Mutable
Immutable
➢ empty dictionary
➢ dictionary with integer keys
➢ dictionary with mixed keys
➢ from sequence having each item as a pair
myDict = {}
myDict = {1: 'apple', 2: 'ball'}
myDict = {'name': 'John', 1: [2, 4, 3]}
myDict = dict([(1,'apple'), (2,'ball')])
Dictionary Examples

Datatype
Tuples
Numbers
Strings
Lists
Dictionaries
Sets
Mutable
Immutable
➢ Accessing Dictionary
➢ len()
➢ key()
➢ values()
myDict = {1: 'apple', 2: 'ball'} myDict [1] ‘apple’
len(myDict) 2
myDict = {1: 'apple', 2: 'ball'} myDict.key() [1, 2]
myDict = {1: 'apple', 2: 'ball'} myDict.values() [‘apple’, ‘ball’]
Dictionary Methods

Datatype
Tuples
Numbers
Strings
Lists
Dictionaries
Sets
Mutable
Immutable
➢ items()
➢ get()
➢ update()
➢ pop()
myDict = {1: 'apple', 2: 'ball'} myDict.items() [(1, ‘apple’), (2, ball)]
myDict.get(1) ‘apple’
myDict = {1: ‘a', 2: ‘b'} myDict.update(3: ’c’) {1: ’a’, 2: ‘b’, 3: ‘c’}
myDict = {1: 'apple', 2: 'ball'} myDict. pop(2) {1: ‘apple’}
Dictionary Methods

Datatype
Tuples
Numbers
Strings
Lists
Dictionaries
Sets
Mutable
Immutable
➢ A set is an unordered collection of items
➢ Every element is unique (no duplicates) and must be immutable (which cannot
be changed)
mySet = {1, 2, 3}

Datatype
Tuples
Numbers
Strings
Lists
Dictionaries
Sets
Mutable
Immutable
Sets Methods
➢ Creating set
➢ Union
➢ intersection
➢ difference
myS1 = {1, 2, ‘c’}
myS2 = {1, ‘b’, ‘c’}
mySet = {1, 2, 3, 3} {1, 2, 3}
myS1 | myS2 {1, 2, ‘c’, ‘b’}
myS1 = {1, 2, ‘c’}
myS2 = {1, ‘b’, c’’}
myS1 & myS2 {1, ‘c’}
myS1 = {1, 2, ‘c’}
myS2 = {1, b’’, ‘c’}
myS1 - myS2 { 2 }

Flow Control

Flow Control
If.. else..
while
If… elif…
else
for
if
break
continue
Flow
Control

Flow Control
Syntax:
if (condition):
statements 1 …
else:
statements 2 …
CHECK
CONDITION
EXECUTE BLOCK 1
EXECUTE BLOCK 2
START
1. If statement

CHECK
CONDITION 1
Flow Control
2. if… elif…else statement
CHECK
CONDITION 1
EXECUTE BLOCK 1
EXECUTE BLOCK 2
START
Syntax:
if (condition 1):
statements 1 …
elif (condition 2):
statements 2 …
else
statements 3 … EXECUTE BLOCK 3

Flow Control
LOOPS REPEAT ACTIONS
SO YOU DON’T HAVE TO ...
For
While
Repeat things until the
loop condition is true
Repeat things till the
given number of times

Flow Control
3. while statement
CHECK
CONDITION 1
EXECUTE BLOCK 1
START
Syntax:
while (condition is True):
statements1…
repeat
EXIT LOOP

Flow Control
4. for statement
check if
Count < 10
Count = 0
START
Syntax:
for iterator name in iterating sequence:
execute statements…
Add 1 to Count
Execute Statements
Exit loop
repeat

Flow Control
Syntax:
break Check Loop
Condition
START
repeat
EXIT LOOP
Check Break
Condition
EXIT LOOP
Execute Block
5. for statement

Flow Control
6. continue
Syntax:
continue
Check Loop
Condition
START
repeat
EXIT LOOP
Check Continue
Condition
Skip Next
Statement
Execute Block

Functions in Python

Function
A function is a block of organized, reusable sets of instructions that is used
to perform some related actions.
Why do we use functions?
➢ Re – usability of code minimizes redundancy
➢ Procedural decomposition makes things organized
Function
Built-in
Function
User Defined
Function

Function
User Defined Function
Syntax:
def func_name (arg1, arg2, arg3, ….):
statements…
return [expression]
Example:
def add ( a, b )
sum = a + b
return sum
adding two number
defining function
Input variable
print variable
output

Function – Pass By Reference
Call by Object Reference:
Python supports call by value where the value is always an object reference, not the value of the object
defining function
print the modified list
output
Modifying list
calling the function
both list are pointing to different
object reference
print the initial list

Function
Call by Object Reference
defining function
print the list
output
appending elements to list
calling the function
both input_list & myList pointing
to same list object reference

File Handling in Python

File Handling & I/O Methods
A file or a computer file is a chunk
of logically related data or
information which can be used by
computer programs.
Search Quality
open ( filename, mode )
write( )
close( )
read( )
File Operations in Python
Opening a file
Reading a file
Writing a file
Closing a file

File Handling & I/O Methods
open file
write file
read file
close file
open in
Read + write
mode
output

Summary

Summary
What is Python? Python FeaturesWho uses Python?
Python Installation DatatypePython Operators

Summary
Flow Control File HandlingFunctions

Thank You…
Questions/Queries/Feedback

Python Tutorial | Python Tutorial for Beginners | Python Training | Edureka

More Related Content

What's hot (20)

Similar to Python Tutorial | Python Tutorial for Beginners | Python Training | Edureka (20)

More from Edureka! (20)

Recently uploaded (20)

Python Tutorial | Python Tutorial for Beginners | Python Training | Edureka