Functional Programming in Python 🐍
📅️ Published: July 3, 2019 • 🕣 1 min read
reduce are generally used to perform functional programming related tasks in Python.
Let’s take a quick look on them.
- Anonymous functions
- No function name,
- They can be passed as function arguments/objects.
returnstatment, evaluated exrpession is returned automatically.
- Single line function.
double = lambda x: x*x print(double(34)) elementList = [34, 56, 78, 90, 0, 12] doubleList = lambda elementList: [e*e for e in elementList] print(doubleList(elementList))
- applies a function to all the items in an input list.
myList = ["bhupesh", "varshney", "is", "a", "developer"] capitalize = list(map(lambda x: x.upper(), myList)) print(capitalize)
- creates a list of elements for which a function returns
mylist = [23, 45, 6, 8, 10, 16] evenList = list(filter(lambda x: x%2 == 0, mylist)) print(evenList)
- accepts a function and a sequence(list/set etc) and returns a single value calculated.
- Initially, the function is called with the first two items from the sequence and the result is returned.
- The function is then called again with the result obtained in step 1 and the next value in the sequence. This process keeps repeating until there are items in the sequence.
from functools import reduce li = [5, 8, 10, 20, 50, 100] sum = reduce((lambda x, y: x + y), li) print(sum)