Python: random library cheatsheet

From basic random number generation to advanced techniques like Gaussian distribution, discover how Python random library adds controlled randomness to Python projects.

The random library in Python provides functions and classes for generating random numbers and data.

random(): Generating a random floating-point number between 0 and 1.

random_num = random.random()

randint() : Generating a random integer within a specified range.

import random 
random_int = random.randint(start, end)

uniform(): Generating a random floating-point number within a specified range.

import random 
random_float = random.uniform(start, end)

choice():Selecting a random item from a sequence (list, tuple, string, etc.).

import random 
random_item = random.choice(sequence)

shuffle():Shuffling the elements of a list randomly. It change the list. It is an inplace operation. You cannot assign it a new variable.

import random 
random.shuffle(my_list)

sample(population,k):Chooses k unique random elements from a population sequence or set.

• Returns a new list containing elements from the population while leaving the original population unchanged.
• To choose a sample from a range of integers, use range() for the population argument. This is especially fast and space efficient for sampling from a large population: sample(range(10000000), 60)

import random 
random_sample = random.sample(population, k)

randrange():Generating a random integer from a range with a specified step.

import random 
random_num = random.randrange(start, stop, step)

seed()Setting a seed value to ensure reproducibility of random results.

import random 
random.seed(seed_value)

random.seed()(Module-Level Seed): Setting the seed value for the entire random module.

import random 
random.seed(seed_value)