The Rise of Functional Programming

Functional programming (FP) used to be an obscure paradigm that few software developers had heard of but today almost every major programming language - Java, C#, Python, Javascript - has borrowed concepts or implemented features from FP to make development faster and easier.

Functional programming is a programming paradigm for developing software using functions only. Following the FP philosophy means avoiding things like shared states, mutable data and side effects. Unlike procedures that depend on a local or global state, outputs in FP depend only on the arguments passed to the function. Taking out side effects, or state changes that don't depend on function inputs, makes software behave more predictably, which is a major selling point for many FP coders.

Side effects: Side effects are any state changes that occur outside of a called function aside from the returned value like modifying a global variable, printing onto console.

Higher order functions: Higher order functions are the functions that take other functions as arguments and they can also return functions. The higher order function map() offers a better alternative to iterating over lists. For example, this simple map written in Python takes a list of names and returns the character lengths of those names:

name_lengths = list(map(len, ["Bob", "Rob", "Bobby"]))

print(name_lengths) # [3, 3, 5]

Here the function "map" takes in another function "len" as the first argument and a list as the second argument. Then it applies the function over each element of the list to produce another list which gives us the length of each name.

The non-functional approach would look like this:

name_lengths = []

for name in names:

name_lengths.append(len(name))

print(name_lengths)

Notice that even for this simple program the functional approach took 2 less lines of code to write. As programs become more complex in logic functional approach becomes that much easier to write.

import functools

fib = lambda n: functools.reduce(lambda x,y: (x[1], x[0] + x[1]), range(n), (0, 1))[0]

print(fib(5)) #5

print(fib(8)) #21

The above program defines a one line function fib that prints the n-th fibonacci number using the higher-order function reduce. Try to figure out how it works by looking up how the reduce function works in python!

Declarative paradigm: Functional programming is a declarative paradigm, meaning that the program logic is expressed without explicitly describing the specific steps used to achieve the desired results. Declarative programs abstract away the how and focus on the what. SQL, for instance, uses a declarative approach. You do not specify how to get the tuples and attributes that you want. You simply write:
SELECT id, name FROM table. The inner details of how that is achieved is abstracted away.

The opposite approach is imperetive where you specify how to get what you want. Most traditional programming languages use this approach, like C, C++, Java. Here you have to specify procedurally how to achieve what you want.

With this you have a general idea of what FP is all about. If you want to learn more about FP you may try your hand at Haskell. There are some online resources available that may help you:

https://www.tryhaskell.org/

http://learnyouahaskell.com/chapters

Credits:

Author: Abhishek Bhattacharya

Github: https://github.com/ShinodaII

LinkedIn: https://www.linkedin.com/in/abhishek-bhattacharya1997/

Hi, I'm Abhishek and I am enthusiastic about any new technology. I recently got my Bachelor's Degree in Computer Applications and currently I am immersing myself in ML and Data Science. Feel free to connect with me on LinkedIn and chat about anything!

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