Python Tutorial

What is Python?

Python is a programming language easy to learn and powerful. There are two primary factors why we have to use Python^® is software quality and developer productivity. It’s commonly used in a variety of domains like Web programming, Internet Scripting, database, numeric and scientific programming, Gaming thus it also known as general purpose language.

The major technical strengths of this language are readability, easy to use and learn, it’s free and supported object-oriented, it is portable.

Python Training has dynamically typed language so every operation can be done on the fly. Python codes can be shipped or placed on the web more securely as it execution involves Python^® Virtual Machine ( PVM ) and bytecode compilation which is platform independent.

Python^® can communicate to other parts of the application using the variety of component integration. For an example using CPython component, python can call C/C++ libraries and can be called from C/C++ programs. It will also have support for accessing java objects, .NET objects through Jython, IronPython respectively.

As in Python, everything is the object, every operation seems to be easier than other scripting languages. Python^® codes are equal to one third and one-fifth of C/C++ and Java programs in term of a number of lines. It has powerful memory management to reuse garbage collections.

Python supports different types of objects like numbers, string, tuples, list, the dictionary to store data and do operations on stored data. It has common methods and operations on sequence objects ( list, string, tuples ) like indexing, slicing, extended slicing.

Python is a popular programming language.

It was created in 1991 by Guido van Rossum. It is used for:

• web development (server-side),
• software development,
• mathematics,
• system scripting.

Why Python?

There are innumerable python courses in Bangalore. All you need is to pick one to receive training and you are more than good to go. By learning this course, you will avail yourself of multiple benefits, some of which are as follows-

• Testing short code snippets become easy with Python‘s interactive mode. There is also an integrated development and learning environment (IDLE) for python.
• New modules can be added to python for its extension.
• To get a programmable interface, applications can be embedded with python.
• A lot of operating systems including Unix, Mac OS, and Linux support this programming language.
• Python is also heavily used in the data analytics domain. Tasks like getting data from databases, XML files, from the web and from text files can easily be performed using python. And that is probably the reason why python training in data analytics in Bangalore is quite a rage.

Python Syntax

The syntax of the Python language is the set of rules that define how a Python program will be written and interpreted in a runtime.

Example: 

>>>X=1
>>>If x<0.5:
Print(“the proper identification is important”)  

Description:

In the above example, the value 1 is assigned to x and if the condition is used in the above example  In the if condition the proper identification is important in this otherwise it shows indent error.

PYTHON VARIABLE

A Python variable is a reserved memory location to store values. In other words, a variable in a python program gives data to the computer for processing. Every value in Python has a datatype. Different data types in Python are Numbers, List, Tuple, Strings, Dictionary, etc

Example:

>>x = 10
>>y = x+5

PYTHON CASTING

Python casting which Is a simple process to convert into one type to another type and it done with functions such as int() or float() or str().

Example:

>>>X = 10
>>>Type(x)
<type’ int’>
>>>Str(x)
‘10’
>>>Float(x)
10.0

Description:

• The ‘x’ value is 10 in the integer form which it converts into string by using the function str (x). Now, the  x =‘10’ is in the  string
• After casting string value is converted into float by using the function float(x).

PYTHON STRING

A string is traditionally a sequence of characters, either as a literal constant or as some kind of variable. String literals in python are surrounded by either single quotation marks or double quotation marks.  strings in Python are arrays of bytes representing Unicode characters.

Example:

>>>Print(“it is a string”)
it is a string
>>>X = “it is a string”
>>Y = ’12’

Description:

• In the above example, the  print(“it is a string”) is  used for printing the string in the output .
• The second example it stores the value “it is a string” ( string type)  in a variable named ‘X’. 
• The value ‘12’ is a string type which is stored in a variable named Y

PYTHON OPERATORS

Operators are the constructs that can manipulate the value of operands. Operators are different types. they are,

Operator Data Types:

• Arithmetic Operators
• Comparison (Relational) Operators
• Assignment Operators
• Logical Operators
• Bitwise Operators
• Membership Operators
• Identity Operators

Example:

>>>A,b=4,2
>>>C= a+b
>>>c
6
>>>D=a-b
>>>D
2
>>>E=a*b
>>>E
8
>>>f= a/b
>>>f
2

Description:

• The value 4 and 2 is stored in the variable A and b
• The addition of the a and  b value is stored in the variable c
• The subraction of the a and b is stored in the variable D
• The multiplication of the a and b is stored in the variable E

PYTHON LIST

List is collection of different objects which are ordered as well as mutable. Since the declaration of all values follows the same syntax “var = value”, based on the value representation the type of the var is determined.

Representation of List data type ->

Creation of list data:

To create a list data type we can just give an empty square braces to a varVar = [] # creates an empty list objects and referred to Var.

Also, we can call the list function call to create a list object

Var = list() # this also creates the same empty list

To create a list with static values, we have to give comma separated objects within square braces.

Var = [1,2,’apple’,’baby’]

The same way we can pass an iterable to the list function call

Var = list(“iterable”) # -> [‘I’,’t’,’e’,’r’,’a’,’b’,’l’,’e’]

Adding elements into a list object:

To add the element to an existing list object we have two methods to perform this operation.

Append and insert:

Append -> used to add the object to the last index of the list object we can use this method

Insert -> used to add the objects to a specific index in the list object.

Syntax for append and insert methods are

Append -> obj.append(value)

Insert -> obj.insert(index,value)

Example usage:

>>> a = [1,2,’apple’,’baby’]
>>> print(a)
[1, 2, ‘apple’, ‘baby’]
>>> a.append(‘value’)
>>> print(a)
[1, 2, ‘apple’, ‘baby’, ‘value’]
>>> a.append(‘data’)
>>> print(a)
[1, 2, ‘apple’, ‘baby’, ‘value’, ‘data’]
>>> a.insert(1,’text’)
>>> print(a)
[1, ‘text’, 2, ‘apple’, ‘baby’, ‘value’, ‘data’]
>>>
When we give index value greater than the length of the list object, the values/objects will be appended to the list
>>> a.insert(100,’last’)
>>> print(a)
[1, ‘text’, 2, ‘apple’, ‘baby’, ‘value’, ‘data’, ‘last’]

Accessing any values from a list object

To access any element or object from a list we can just do indexing

Syntax-> obj[index]

We can either do forward or reverse indexing. Forward indexing starts from 0 to len(obj)-1.
Reverse indexing starts from -1 from the last index.

>>> print(a)
[1, ‘text’, 2, ‘apple’, ‘baby’, ‘value’, ‘data’, ‘last’]
>>> print(a[0])
1
>>> print(a[5])
‘value’
>>> print(a[-1])
‘last’
>>> print(a[-3])
‘value’
We can also use for loop to access each values from a list.
>>> print(a)
[1, ‘text’, 2, ‘apple’, ‘baby’, ‘value’, ‘data’, ‘last’]
>>> for i in a:
print(i,end = ‘ ‘)
1 text 2 apple baby value data last
>>>

Modify a value from list :

If we need to modify an value in a list, just refer to the index element and give a new value to it

Syntax -> obj[index] = New_Value

>>> print(a)
[1, ‘text’, 2, ‘apple’, ‘baby’, ‘value’, ‘data’, ‘last’]
>>> a[2] = ‘modified’
>>> print(a)
[1, ‘text’, ‘modified’, ‘apple’, ‘baby’, ‘value’, ‘data’, ‘last’]
>>>

Remove element from a list:

To delete any element from a list we can either use the built in ‘del’ keyword or we can use the built-in object methods of list -> pop, remove

Del -> del obj[index] # deletes specific index value from list

Pop -> index based removal of values/objects from a list

Remove -> value based removal

Syntax->

Obj.pop([index]) -> if index is specified, the particular index element will be removed from the list, else last index will be removed

Obj.remove(value) -> first occurrence of value from the list will be removed off.

>>> del a[0]
>>> print(a)
[‘text’, 2, ‘apple’, ‘baby’, ‘value’, ‘data’, ‘last’]
>>> a.pop() # removes the last index
‘last’
>>> a.pop(3) # removes the third index element
‘baby’
>>> print(a)
[‘text’, 2, ‘apple’, ‘value’, ‘data’]
>>>
Also there is another method available with list object from 3.x version of python, clear method
Clear -> used to delete all the available values in the list and makes it empty
>>> a
[‘text’, 2, ‘apple’, ‘value’, ‘data’]
>>> a.clear()
>>> print(a)
[]
>>

Merge two different list into one.

To ad two list into one we can use the built-in extend method in list objects.

Syntax-> obj.extend(another_list)

>>> x = [1,2,3,4]
>>> y = [5,6,7,8]
>>>
>>> x.extend(y)
>>>
>>> print(x)
[1, 2, 3, 4, 5, 6, 7, 8]
>>

PYTHON TUPLES

Tuple is also the collection of objects but immutable(unchangeable). The representation of the tuple object is normal parenthesis.

Syntax-> var = value
a = (1,2,3,4)
a = tuple(5,6,7,8)

In tuple object we will not be able to any set of write operations.

Only read attributes are available in python tuple objects

Accessing elements in a tuple

To access element in the tuple we can use the indexing.

Also we can iterate over them using for loop also.

Example:

>>> a = 1,2,3,4
>>>
>>> a[0]
1
>>> for i in a:
print(i)
1
2
3
4
>>

PYTHON DICTIONARY

Dictionary data type is also a collection which uses Key value pair. If we have access any values we must use the specific key for it.

Representation of dict data type -> {}

Creation of Dictionary:

To create a dictionary we can use the empty braces or call the direct function call

>>> d = {}
>>> print(d)
{}
>>> x = dict()
>>> print(x)
{}
>>

To create a static dictionary we can use the following syntax:

Syntax -> {key:value,key1:value1,key2:value2,….}
Also in dict function call we can pass an iterator with two index elements which acts as a key value pair for dict object creation
Syntax-> dict([(k,v),’kv’,[‘k’,’v’]])
dict(key = value, key1 = val1, ….)

Examples:

>>> d = {‘key’:’value’,’k’:’v’,’k1′:’v1′}
>>> x = dict([‘kv’,(‘k1′,’v1’),[‘a’,’apple’]])
>>> print(d)
{‘key’: ‘value’, ‘k’: ‘v’, ‘k1’: ‘v1’}
>>> print(x)
{‘k’: ‘v’, ‘k1’: ‘v1’, ‘a’: ‘apple’}
>>

All keys in the dictionary must be immutable data type. If we pass an mutable object as dictionary key it will raise an error

Adding elements into a dictionary:

To add elements into an existing dictionary we can use the following syntax

Syntax -> obj[key] = value

Examples:

>>> d[‘d’]=’data’
>>> print(d)
{‘key’: ‘value’, ‘k’: ‘v’, ‘k1’: ‘v1’, ‘d’: ‘data’}
>>> d[‘t’]=’test’
>>> print(d)
{‘key’: ‘value’, ‘k’: ‘v’, ‘k1’: ‘v1’, ‘d’: ‘data’, ‘t’: ‘test’}
>>

PYTHON SET

Set is also a data type in python which is unchangeable and holds unique value, ad unordered.

Representation -> {}

The difference between dictionary and set is,

Dictionary will hold key-value pairs

Set data type will hold only unique keys

Accessing an element from the set:

To access any element from a set element we cannot use the same indexing concept since the set element are unordered. But we can use the for loop to iterate over the existing values in a set.

Examples:

>>> s = {1,2,3,4,5}
>>>
>>> s
{1, 2, 3, 4, 5}
>>> s[0] # throws Type error only
>>> for i in s:
print(i)
1
2
3
4
5

You can note that in the above accessing through index is not allowed but using a for loop we can access the elements.

Also we cannot change any objects inside a set element after declaration.

Adding element into a set element is simply carried out with the help of add and update method of a set object.

Add() -> add one element to the set element

Update() -> adds more thean one element to the set element

Examples:

>>> print(s)
{1, 2, 3, 4, 5}
>>> s.add(‘6’)
>>> s
{‘6’, 1, 2, 3, 4, 5}
>>> s.update([‘a’,’b’,’c’,’d’])
>>> s
{‘6’, 1, 2, 3, 4, 5, ‘d’, ‘c’, ‘b’, ‘a’}
>>>

Deleting an entry from a list element

To delete we do have different methods, either we can use remove or discard method of set object. Also we can use the pop element to remove the random element . And also we can the base del keyword to delete any set object itself.

Examples:

>>> print(s)
{‘6’, 1, 2, 3, 4, 5, ‘d’, ‘c’, ‘b’, ‘a’}
>>> s.remove(‘6’)
>>> print(s)
{1, 2, 3, 4, 5, ‘d’, ‘c’, ‘b’, ‘a’}
>>> s.pop()
1
>>> s.pop()
2
>>> s.discard(‘d’)
>>> print(s)
{3, 4, 5, ‘c’, ‘b’, ‘a’}
>>

Other data types must have atleast one index to be True condition

Python Decision Making

Python if/else statement:

Generally if we want to write any algorithms or automate an logic, we will be utilizing three different ways to handle the logic

Based on condition -> if statement

Based on iteration -> for statement

Iteration based on cnd -> while statement

if/else block

Used for writing condition or validation based logics in python

Syntax

If condition:

Stmts

Here indentation plays a major role in writing the blocks of statements. So maintain a proper indentation to segregate the blocks.

What are the conditional statements we can use in if block

We can directly use the Boolean values (True/False)

We can use any Expression or function which returns Boolean value

< , > , <= , >= , == , !=

We can use the direct data type with value also a True condition.

Numerical -> except 0 all are True condition

Other data types must have atleast one index to be True condition

Examples:

if True:

print(“Hello”)

print(“hi”)

if False:

print(“Not executed”)

if True:

print(“hello”)

n = 10

if n<=10:

print(“True”)

if n>10:

print(“Greater”)

a = []

if a:

print(“Hello”)

# if/else block

n=15

if n<10:

print(“Lesser”)

else:

print(“Greater”)

if n<=10 and n%5==0:

print(“success”)

elif n>10 and n%5==0:

print(“Cnd1”)

else:

print(“not satisfied”)

n=18

a,b,c = 1,2,3

if a>b and a>c:

print(“A is bigger”)

elif b>c:

print(“B is big”)

else:

print(“C is big”)

s = ‘qwytgnvb’

if ‘a’ in s or ‘e’ in s or ‘i’ in s or ‘o’ in s or ‘u’ in s:

print(“Vowels present”)

else:

print(“No vowels”)

Input_list = [ 2,4,6]
For x in input_list:
Print(x)

2
4
6

For x in Input_data:
Print(x)

0, “D”
1, “h”
2,”o”
3, “n”
4, “I”

Input_data = [“cat”, “dog”,”goat”]
For x, y in enumerate(Input_data):
Print(x)
Print(y)
Note: “x” will carry index of the input and “y” carries its value

0
1
2
“cat”
“dog”
“goat”

Input_data = “Dhoni”For x , y in enumerate(Input_data):
If x == “h”:
Print(“in the loop)
Else:
Print(“Not in the loop”)

Output:Not in the loop
Possible Solution:
If x == 2

Input_data = [“cat”,”dog”,”goat”,”cow”]
For x in Input_data:
If x == “dog”:
Print(“Animal is “ , x)
Else:
Print(“please loop again”)

Please loop again
Animal is dog
Please loop again

For x in Input_data:If x == “dog”:
Print(“Animal is “, x)
Return
Else:
Print(“please loop again”)

Input_data = [“a”,”b”,”c”,”d”]
For x in Input_data:
If x == “b”:
Continue
Print(x)
Output:
a
c
d

Print(“Looping”)
data_input += 1

Looping
Looping
Looping
Looping
Looping
Looping

Break-in a while:

Input_data = 1
While Input_data < 6:
Print(“looping”)
If Input_data == 3:
Break
Input_data += 1

Output:

Looping
Looping
Looping

Continue:

Continue statement does execute the process excluding the condition statement. (Reference in For Loop Topic)

Code:Def Run();
Print(“running”)
Run()
Output:
Running

Def Cricket(Name, Team):Print(Name , “plays for”, Team)
Cricket(“Dhoni”, “CSK”)

Dhoni plays for CSK

Def Cricket(Name , Team = “CSK):
Print(Name , “plays for “, Team)
Cricket(“Dhoni”)

Dhoni plays for CSK

Def Cricket(name,team):Print(name, “plays for “, team)
Cricket(“csk”, “dhoni”)

Csk plays for dhoni.

To avoid those trouble we will be opting for  below keyword arguments.
Def Cricket(name, team):Print(name,”plays for “, team)

Cricket(team = “CSK”, name = “Dhoni”)

Output:

Dhoni plays for CSK.

NOTE:

Even though order were not proper between arguments and calling, values or data’s will be assigned to proper variable using keywords match.

*args and **Kwargs

* args is used to call function with multiple data’s

**Kwargs is used to call function with multiple data’s along with keywords.

Def Score(*runs): 

Examples:
Print(runs)
Score(25, 37, 58)
Output:
(25,37,58)

Note:
Even though only one data assigned inside function definition, we can pass n number of arguments because arguments inside function definition is added along with “*”

Output of *args always in tuple format

Def Score(**runs):

Examples:
Print(runs)Score(India=372, Pakisthan = 290)
Output:
{India:372, Pakisthan:290}
Note:
Output of **kwargs will be always in dictionary.

Function with Return Statements.

Descriptions:

Return statements is used in function to send back some acknowledgement back to function with data.

Examples:

Def Cricket(name):
Print(name)
Return “Success”
C = Cricket(“Dhoni”)
Print( C)

Output:

Dhoni
Success

Note:
if nothing is passed after return statement and if you still print the calling or calling object you will get output as none.

Append:
Input.append(“cow”)
Output:
[“cat”, “dog”,”goat”,”cow”]
Extend:
Input.extend([“cow”,”ant”])
Output:
[“cat”,”dog”,”goat”,”cow”,”ant”]
Pop:
Input.pop()
Output:
[“cat”,”dog”]
Remove:
Input.remove(“dog”)
Output:
[“cat”, “goat”]

def __next__(self):#under MyNum Class
if self.val <= 100:
x = self.val
self.a += 1
return x
else:
raise StopIteration

user_defined = datetime.datetime(2020, 6, 1)
print(user_defined.strftime(“%B”))
#output:June
User_date = datetime.datetime(2020, 5, 17)
print(user_date)
#output: 2020-05-17 00:00:00

Seperators: x = {
“name”: “Siva”,
“age”: 23,
}
print(json.dumps(x, indent=4, separators=(“. “, ” = “))) #indent is using for spacing

{
 “name” = “Siva”.
 “age” = 23.
}

x = {
“name”: “Siva”,
“age”: 23,
}
print(json.dumps(x, sort_keys=True))

{
“age”: 23,
“name”: “Siva”,
}

Writing a file:
Var = open (“filename.txt”, “w”)
Var.write(“Writing onto the file”)
Var.close()
Output:
Open “filename.txt” and you can see the following string.
Writing onto the file.

Var = open(“filename.txt”, “r”)
Var.read()
Output:
“it reads the content from the file”

Var = open(“filename.txt”, “a”)
Var.write(“content into the file”)
Var.close()

Var = open(“filename.txt”, “w+)
Var.write(“Content on the file”)
Print(Var.read())
Var.close()
Output:
Open a file and you can see the content.
But but, you can’t see the same in print(var.read()) line