filter, map, reduce - Python tutorial in Tamil
Python includes a number of predefined built-in functions that can be utilized by the end-user by simply calling them. These functions not only make programmers’ jobs easier, but they help establish a common coding environment. In this tutorial, you’ll learn about three of Python’s most powerful functions: map(), filter(), and reduce().
Functional programming’s three pillars are map, filter, and reduce functions. While Python isn’t exactly a functional programming language, it does have a lot of features that make it so. The map, filter, and reduce functions in Python are discussed in this article, as well as how they correspond to functional programming principles.
A programming paradigm that uses functions to define computation is known as functional programming. The concept of an unchangeable state is one of functional programming’s key defining traits.
Computation is done through statements in imperative programming, which is arguably the most prevalent programming paradigm you’re already familiar with. These are commands that affect the value of a variable, and thus the state of the computation after they are executed. A for loop, for example, can execute a statement repeatedly, altering the value of a variable each time
The functions map(), filter(), and reduce() all do the same thing: They each take a function and a list of elements, and then return the result of applying the function to each element in the list.
The map() function is a higher-order function. As previously stated, this function accepts another function and a sequence of ‘iterables’ as parameters and provides output after applying the function to each iterable in the sequence.
The filter() function is used to generate an output list of values that return true when the function is called.This function like map(), can take user-defined functions and lambda functions as parameters.
The reduce() function applies a provided function to ‘iterables’ and returns a single value, as the name implies.