ADVANCED FUNCTIONS
==================
FUNCTION ALIASING
=================

DEFINING THE SAME FUNCTION WITH ANOTHER NAME

def fun():
	jlasksfk
fun()

name = fun

name()
fun()

# function aliasing

def printMessage(name):
    print("Hey",name,"Good Morning.")

printMessage('Kumar')

# function aliasing
greets = printMessage

greets('Rakesh')

printMessage('Rahul')

wishes = greets

wishes('Ashwini')
============================================

Banking Application
	xyz

abc bank
	functionality-1



ANONYMOUS FUNCTION
==================

def function-name():
	function-body
	return

function-name()

==> anonymous function is also called as "nameless function"
keyword: lambda
Syntax:
	identifier = lambda argument_list : expression

==> lambda function can always return a value by default (without the return statement).

# anonymous function

# def square(n):
#     return n * n
#
# print(square(7))

square = lambda n : n ** 2

print("The Square of {} is = {}".format(9,square(9)))

why lambda function:
=====================
1) just for instant use.
2) when we want to send a function as an argument to the function, lambda function is the best option.
map(), filter(), reduce()

filter():
========
is an inbuilt function, which we can use to filter from the collection based on some condition.

syntax:
	filter(function, sequence/collection)

Here:
	function can use to define the condition to perform the filtering


# filter()

# WAP TO FILTER ONLY EVEN NUMBERS FROM THE LIST BY USING filter()

# def filterFunction(ld):
#     rl = list()
#     for i in ld:
#         if i % 2 == 0:
#             rl.append(i)
#     return rl
#
# listData = eval(input("Enter a list:"))
#
# print("The List Even elements = ",filterFunction(listData))

==============================================================

# filter() without lambda function

def isEven(ld):
    if ld % 2 == 0:
        return True
    else:
        return False

ld = [1,10,0,101,11,100,21,20,30,31]

result = list(filter(isEven,ld))

print(result)

====================================

# filter() with lambda function

l = [0,5,10,15,20,25,30,35,40]

result = tuple(filter(lambda  x : x % 2 == 0,l))

print(result)

=======================================

map() function:
===============
map() is an inbuilt method, which we can use to accept a collection/sequence
based on the condition it can modify the mapped element from the collection

Syntax:
	map(function, collection)

# map()

l = [1,3,5,7,9,11]

result =list(map(lambda x : x * x, l))

print(result)

====================================

reduce()
========
reduce() can accept a collection and reduce to the single element based on the condition.

Syntax:
	reduce(function, sequence/collection)


==> to use the reduce(), we should import "functools".
Syntax:
	from functools import *

from functools import *

l = [1,3,5,7,9,11,13,15,17,19,21,23,25]

result = reduce(lambda x,y : x + y,l)

print(result)