def sum(x,y):
    return x + y
result = sum(3,4)
print(result)

double = lambda x: x * 2
a = [1,2,3,4,5,6,7]
print(double(a))

# Map Function
my_list = [1, 2, 3, 4, 5]

def square(x):
    return  x>3

result = map(square,my_list)
print(list(result))
# 
result = filter(square,my_list)
print(list(result))

# 
print(list(map(lambda x:x>3, [1, 2, 3, 4, 5])))
print(list(filter(lambda x:x>3, [1, 2, 3, 4, 5])))


new_list = list(map(lambda x: x * 2 , my_list))

# Output: [2, 10, 8, 12, 16, 22, 6, 24]
print(new_list)

# reduce function The reduce function, reduce(function, iterable) applies two arguments cumulatively to the items of iterable, from left to right
from functools import reduce
numbers = [1, 2, 3, 4, 5]
result = reduce(lambda x,y: x+y, numbers)
print(result)

# filter function filter(function,iterable) creates a new list from the elmeents for which the function
my_list = [1, 2, 3, 4, 5, 6]
def big(x):
    return x>3

new_list = list(filter(big, my_list))

# print(new_list)
new_list = list(filter(lambda x: (x%2 == 0) , my_list))
print(new_list)

subjects = [['Antham', 'Telugu', 2], ['Love Ke Funday', 'Hindi', 2.5], ['Kanupapa', 'Telugu', 1.6], ['Vismayam', 'Malayalam', 2]]

subjects.sort(key = lambda x: x[1])
print(subjects)
# subjects.sort(key = lambda x: x[2], reverse = False)
# print(subjects)

subjects = sorted(subjects, key = lambda x: x[2])
print(subjects)