Python Random Module

The Python random module is part of the standard library and provides functions in order to generate random numbers or to work with elements randomly from data structures. It is widely used for tasks like simulation, games, and also generating test data.

This is a detailed explanation about its features:

1. Generating Random Numbers

The random module consists of various functions that may be used to generate numbers. This module generates number using the PRNG(pseudo-random number generator), so the generated number is determinate but apparently random.

Key Functions:

random()

• Returns a random floating-point number in the range [0.0, 1.0).
• Example:

import random
print(random.random()) # Output: 0.37444887175646646 (example)

uniform(a, b)

• Returns a random floating-point number in the range [a, b] or [b, a].
• Example:

print(random.uniform(10, 20)) # Output: 12.345 (example)

randint(a, b)

• Returns a random integer in the inclusive range [a, b].
• Example:

print(random.randint(1, 10)) # Output: 7 (example)

randrange(start, stop[, step])

• Returns a randomly selected integer from the range defined by start, stop, and step.
• Example:

print(random.randrange(0, 10, 2)) # Output: 2, 4, 6, or 8

getrandbits(k)

• Returns an integer with k random bits.
• Example:

print(random.getrandbits(4)) # Output: 0-15

2. Working with Sequences

The random module offers functions to pick or shuffle elements in sequences like lists or tuples.

choice(seq)

• Returns a random element from a non-empty sequence.
• Example:

colors = ['red', 'blue', 'green']
print(random.choice(colors)) # Output: 'blue' (example)

choices(population, weights=None, *, k=1)

• Returns a list of k random elements from the population with optional weighting.
• Example:

items = ['apple', 'banana', 'cherry']
print(random.choices(items, weights=[1, 2, 3], k=2))

sample(population, k)

• Returns a list of k unique elements chosen from the population.
• Example:

print(random.sample(range(1, 10), 3)) # Output: [4, 1, 9] (example)

shuffle(seq)

• Shuffles the elements of the sequence in place.
• Example:

nums = [1, 2, 3, 4, 5]
random.shuffle(nums)
print(nums) # Output:  [5, 1, 3, 4, 2](example)

3. Setting the Random Seed

• You can control the randomness using random.seed() for reproducibility.
• Example:

random.seed(42)
print(random.random()) # Output: 0.6394267984578837 (example)

4. Gaussian and Other Distributions

The random module also provides functions for generating numbers based on specific probability distributions.

gauss(mu, sigma)

• Returns a random number with a Gaussian (normal) distribution.
• Example:

print(random.gauss(0, 1)) # Mean=0, Std. Dev.=1

expovariate(lambd)

• Returns a random number with an exponential distribution.
• Example:

print(random.expovariate(1.5))

betavariate(alpha, beta)

• Returns a random number with a beta distribution.

gammavariate(alpha, beta)

• Returns a random number with a gamma distribution.

5. Notes on Randomness

• Pseudo-Randomness: Numbers are not truly random; they are generated deterministically based on the algorithm and seed.
• Cryptographic Security: For secure random numbers, use the secrets module.

Example Program: Dice Rolling Simulation

import random

def roll_dice():
    return random.randint(1, 6)

for _ in range(5):
    print(roll_dice())

This will simulate rolling a six-sided die five times.