random

Random number generation functions. Python-compatible.

Available Functions

Functions

random.seed([a])

Initializes the random number generator.

Parameters:

• a (optional): Seed value (integer or float). If omitted, current time is used.

Returns: None

Example:

import random

random.seed(42)  # Reproducible random sequence
num = random.random()

random.randint(a, b)

Returns a random integer between a and b (inclusive).

Parameters:

• a: Minimum value (integer)
• b: Maximum value (integer)

Returns: Integer

Example:

import random

num = random.randint(1, 100)
print(num)  # Random number between 1 and 100

random.random()

Returns a random float between 0.0 and 1.0.

Returns: Float

Example:

import random

num = random.random()
print(num)  # Random float like 0.123456

random.uniform(a, b)

Returns a random float N such that a <= N <= b.

Parameters:

• a: Minimum value (number)
• b: Maximum value (number)

Returns: Float

Example:

import random

num = random.uniform(1.5, 5.5)
print(num)  # Random float between 1.5 and 5.5

random.choice(seq)

Returns a random element from a sequence.

Parameters:

• seq: List to choose from

Returns: Element from the list

Example:

import random

fruits = ["apple", "banana", "cherry", "date"]
fruit = random.choice(fruits)
print(fruit)  # Random fruit from the list

random.shuffle(x)

Shuffles a list in place.

Parameters:

• x: List to shuffle (modified in place)

Returns: None

Example:

import random

cards = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
random.shuffle(cards)
print(cards)  # [3, 7, 1, 9, 2, 5, 8, 4, 6, 10] (random order)

random.sample(population, k)

Returns k unique random elements from population.

Parameters:

• population: List to sample from
• k: Number of elements to return

Returns: List of k unique elements

Example:

import random

numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
sample = random.sample(numbers, 3)
print(sample)  # [4, 7, 2] (3 random unique elements)

random.randrange(start, stop[, step])

Returns a randomly selected element from a range.

Parameters:

• start: Start of range (or stop if only one argument)
• stop: End of range (exclusive)
• step (optional): Step value. Default: 1

Returns: Integer

Example:

import random

# Single argument (0 to stop)
num = random.randrange(100)  # 0-99

# With start and stop
num = random.randrange(10, 20)  # 10-19

# With step
num = random.randrange(0, 100, 5)  # 0, 5, 10, ..., 95

random.gauss(mu, sigma)

Returns a random float from a Gaussian (normal) distribution.

Parameters:

• mu: Mean of the distribution
• sigma: Standard deviation

Returns: Float

Example:

import random

# Generate values from normal distribution (mean=0, std=1)
value = random.gauss(0, 1)

random.normalvariate(mu, sigma)

Alias for gauss(). Returns a random float from a Gaussian distribution.

Parameters:

• mu: Mean of the distribution
• sigma: Standard deviation

Returns: Float

random.expovariate(lambd)

Returns a random float from an exponential distribution.

Parameters:

• lambd: Rate parameter (1.0 divided by the desired mean)

Returns: Float

Example:

import random

# Exponential with mean 5 (lambd = 1/5)
wait_time = random.expovariate(0.2)

random.choices(population, weights=None, k=1)

Weighted random sampling with replacement. Select k items from population with the given weights.

Parameters:

• population: List to sample from
• weights (optional): List of weights matching population length. Can be positional or keyword.
• k (optional): Number of items to select. Default: 1. Can be keyword only.

Returns: List of k selected items

Example:

import random

# Weighted selection
colors = ["red", "green", "blue"]
result = random.choices(colors, weights=[5, 3, 2], k=10)
print(result)  # 10 selections, red more likely

# Uniform selection (no weights)
result = random.choices(colors, k=5)

random.betavariate(alpha, beta)

Returns a random float from a beta distribution.

Parameters:

• alpha: Shape parameter (must be positive)
• beta: Shape parameter (must be positive)

Returns: Float in range [0, 1]

Example:

import random

# Beta distribution skewed toward 0
result = random.betavariate(0.5, 2.0)

random.gammavariate(alpha, beta)

Returns a random float from a gamma distribution.

Parameters:

• alpha: Shape parameter (must be positive)
• beta: Scale parameter (must be positive)

Returns: Float

Example:

import random

# Gamma distribution with shape=2, scale=3
result = random.gammavariate(2.0, 3.0)

random.triangular(low, high[, mode])

Returns a random float from a triangular distribution.

Parameters:

• low: Minimum value
• high: Maximum value
• mode (optional): Peak value. Defaults to the midpoint of low and high.

Returns: Float

Example:

import random

# Triangular between 0 and 10, peak at 7
result = random.triangular(0, 10, 7)

# Triangular between 0 and 1, peak at midpoint (0.5)
result = random.triangular(0, 1)

random.paretovariate(alpha)

Returns a random float from a Pareto distribution.

Parameters:

• alpha: Shape parameter (must be positive)

Returns: Float

Example:

import random

# Pareto distribution with shape parameter 2
result = random.paretovariate(2.0)

random.weibullvariate(alpha, beta)

Returns a random float from a Weibull distribution.

Parameters:

• alpha: Scale parameter (must be positive)
• beta: Shape parameter (must be positive)

Returns: Float

Example:

import random

# Weibull distribution with scale=1, shape=1.5
result = random.weibullvariate(1.0, 1.5)

Usage Example

import random

# Set seed for reproducibility
random.seed(42)

# Random integer
dice_roll = random.randint(1, 6)
print("Dice roll:", dice_roll)

# Random float
probability = random.random()
print("Probability:", probability)

# Random float in range
temperature = random.uniform(20.0, 30.0)
print("Temperature:", temperature)

# Random choice
colors = ["red", "green", "blue", "yellow", "purple"]
color = random.choice(colors)
print("Random color:", color)

# Random sample
lottery = random.sample(list(range(1, 50)), 6)
print("Lottery numbers:", lottery)

# Shuffle a deck
deck = list(range(1, 53))  # Cards 1-52
random.shuffle(deck)
print("Shuffled deck:", deck[:5], "...")  # First 5 cards