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This tutorial showed you how to randomly select an element from a list in Python. There are multiple simple ways to achieve this goal, all of which involve importing Python modules.

This tutorial will cover solutions that require the random, , secretsand modules.NumPy

Please note that all of these solutions that will be presented will use a pseudo-random number generator (PRNG).

randomSelect a random element from a list in Python using the module

The most commonly used randomization module is randomthe module. This module implements pseudo-random utility functions to support operations involving randomization.

Let's say we want to randomly pick a name from a list, like voting.

["John", "Juan", "Jane", "Jack", "Jill", "Jean"]

To pick a random name from this list, we will use random.choice()which will select an element from the available data given.

import random

names = ["John", "Juan", "Jane", "Jack", "Jill", "Jean"]


def selectRandom(names):
    return random.choice(names)


print("The name selected is: ", selectRandom(names))

Of course, the output will be variable and random, so it could be namesany of the six names stored in the variable .

secretsSelect a random element from a list using the module in Python

secretsThe module serves essentially randomthe same purpose as . However, secretsa cryptographically secure method of implementing a PRNG is provided.

In real life applications, such as storing passwords, authentication, encryption and decryption, and tokens. It is much safer secretsthan using random, as it is only suitable for operations that simulate or do not handle sensitive data.

In this problem, the values ​​provided by both modules are the same because we are not handling any sensitive data and this is for simulation purposes.

In this example, we will use the same nameslist. secretsThere is also a version of the function choice()that produces the random.choice()same variable output as .

import secrets

names = ["John", "Juan", "Jane", "Jack", "Jill", "Jean"]


def selectRandom(names):
    return secrets.choice(names)


print("The name selected is: ", selectRandom(names))

NumPySelect a random element from a list in Python using the module

NumPyThe module also has utility functions for randomization, and some extensibility tools as choice()arguments to its functions.

Again, we will use the same list namesto demonstrate the function numpy.random.choice().

import numpy

names = ["John", "Juan", "Jane", "Jack", "Jill", "Jean"]


def selectRandom(names):
    return numpy.random.choice(names)


print("The name selected is: ", selectRandom(names))

This function will return the same variable output as produced by the other two modules.

NumPyAdditional arguments are provided choice()to generate multiple outputs in the form of a list.

The second parameter accepts an integer value that determines how many random items to return. Suppose we want namesto return 4 random elements from the list.

def selectRandom(names):
    return numpy.random.choice(names, 4)


print("The names selected are: ", selectRandom(names))

Sample output:

The names selected are: ['John', 'Jill', 'Jill', 'Jill']

In the random results, it is possible for the same element to be repeated more than once.

If you want the resulting items to be unique, we can pass a third booleanparameter to perform random sampling without replacement.

def selectRandom(names):
    return numpy.random.choice(names, 4, False)

Output example:

The names selected are: ['Jill', 'John', 'Jack', 'Jean']

This function will always produce a unique list without any repeated elements.

If we add a third argument, one major drawback is the running time of the function, since it will perform an extra task to check for duplicate elements and replace them with elements that are not yet present in the result.

To summarize, selecting random items from a Python list can be achieved by using one of these three modules: random, , secretsor NumPy. Each module has its advantages and disadvantages.

If you want to have a cryptographically secure PRNG approach, then secretsis the best module. If your purpose is just for simulation or non-sensitive data manipulation, then use randomor NumPy. If you want more than one random result in the result, then use NumPy.