Functional Programming in Python: When and How to Use It

Functional programming is a programming paradigm in which the primary method of computation is evaluation of functions. In this tutorial, you’ll explore functional programming in Python.

Functional programming typically plays a fairly small role in Python code. But it’s good to be familiar with it. At a minimum, you’ll probably encounter it from time to time when reading code written by others. You may even find situations where it’s advantageous to use Python’s functional programming capabilities in your own code.

In this tutorial, you’ll learn:

• What the functional programming paradigm entails
• What it means to say that functions are first-class citizens in Python
• How to define anonymous functions with the lambda keyword
• How to implement functional code using map(), filter(), and reduce()

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What Is Functional Programming?

A pure function is a function whose output value follows solely from its input values, without any observable side effects. In functional programming, a program consists entirely of evaluation of pure functions. Computation proceeds by nested or composed function calls, without changes to state or mutable data.

The functional paradigm is popular because it offers several advantages over other programming paradigms. Functional code is:

• High level: You’re describing the result you want rather than explicitly specifying the steps required to get there. Single statements tend to be concise but pack a lot of punch.
• Transparent: The behavior of a pure function depends only on its inputs and outputs, without intermediary values. That eliminates the possibility of side effects, which facilitates debugging.
• Parallelizable: Routines that don’t cause side effects can more easily run in parallel with one another.

Many programming languages support some degree of functional programming. In some languages, virtually all code follows the functional paradigm. Haskell is one such example. Python, by contrast, does support functional programming but contains features of other programming models as well.

While it’s true that an in-depth description of functional programming is somewhat complex, the goal here isn’t to present a rigorous definition but to show you what you can do by way of functional programming in Python.

How Well Does Python Support Functional Programming?

To support functional programming, it’s useful if a function in a given programming language has two abilities:

1. To take another function as an argument
2. To return another function to its caller

Python plays nicely in both these respects. As you’ve learned previously in this series, everything in a Python program is an object. All objects in Python have more or less equal stature, and functions are no exception.

In Python, functions are first-class citizens. That means functions have the same characteristics as values like strings and numbers. Anything you would expect to be able to do with a string or number you can do with a function as well.

For example, you can assign a function to a variable. You can then use that variable the same as you would use the function itself:

>>>

 1>>> def func():
 2...     print("I am function func()!")
 3...
 4
 5>>> func()
 6I am function func()!
 7
 8>>> another_name = func
 9>>> another_name()
10I am function func()!

The assignment another_name = func on line 8 creates a new reference to func() named another_name. You can then call the function by either name, func or another_name, as shown on lines 5 and 9.

You can display a function to the console with print(), include it as an element in a composite data object like a list, or even use it as a dictionary key:

>>>

>>> def func():
...     print("I am function func()!")
...

>>> print("cat", func, 42)
cat <function func at 0x7f81b4d29bf8> 42

>>> objects = ["cat", func, 42]
>>> objects[1]
<function func at 0x7f81b4d29bf8>
>>> objects[1]()
I am function func()!

>>> d = {"cat": 1, func: 2, 42: 3}
>>> d[func]
2

In this example, func() appears in all the same contexts as the values "cat" and 42, and the interpreter handles it just fine.

Note: What you can or can’t do with any object in Python depends to some extent on context. There are some operations, for example, that work for certain object types but not for others.

You can add two integer objects or concatenate two string objects with the plus operator (+). But the plus operator isn’t defined for function objects.

For present purposes, what matters is that functions in Python satisfy the two criteria beneficial for functional programming listed above. You can pass a function to another function as an argument:

>>>

 1>>> def inner():
 2...     print("I am function inner()!")
 3...
 4
 5>>> def outer(function):
 6...     function()
 7...
 8
 9>>> outer(inner)
10I am function inner()!

Read the full article at https://realpython.com/python-functional-programming/ »

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