# Random numbers in Python

I use the random module to extract random numbers in the Python language. The library contains several random number generators.

import random

## How to generate a random number

This function is a random generator that extracts an integer between the included start and end values.

random.randint(start, end)

Example

This script extracts a random number from 0 to 10.

>>> random.randint(0,10)

One of the possible results is the following:

>>> 2

## The methods of the random module

The random module has many other useful features.

• betavariate(alfa,beta)
Generate a random number in the beta distribution.
• choice(seq)
Select a random element in a sequence.

>>> seq=[1,2,3,4,5]
>>> random.choice(seq)
2

• choices(population, weigth=none, *, cum_weigths=none, k=1)
Select k elements from a population with reintegration.

>>> seq=["a","b","c","d","e"]
>>> random.choices(seq,k=3)
['a', 'c', 'e']

• expovariate(lambd)
Generate a random number in an exponential distribution.
• gammavariate(alfa, beta)
Generate a random number in a gamma distribution.
• gauss(mu, sigma)
Generate a random number in a Gaussian distribution.
• getrandbits(k)
Generate an integer random number with k bits.

>>> random.getrandbits(3)
4

• getstate()
Returns the internal status.
• lognormvariate(mu, sigma)
Generate a random number in a normal logarithmic distribution.
• normalvariate(mu, sigma)
Generate a random number in a normal distribution.
• paretovariate(alpha)
Generate a random number in a Pareto distribution.
• randint()
Generate a random integer from x to y (inclusive).

>>> random.randint(0,10)
2

• random()
Generate a random number from 0 to 1.

>>> random.random()
0.5357514603916116

• randrange( x, y [,step] )
Generate a random number from x to y (excluded) with step step equal to one of default.

>>> random.randrange(0,10)
7

• sample( population, k )
Select k elements of a population without repetitions.

>>> random.sample(["a", "b", "c"], 2) ['c', 'a']

• seed(a=None, version=2)
Initializes the internal status.
• setstate(state)
Restores the internal state of an object.
• shuffle( population )
Change the order of items in a population.

>>> x=[1,2,3,4,5,6,7,8,9,10]
>>> random.shuffle(x)
>>> x
[8, 5, 6, 1, 3, 10, 7, 9, 4, 2]

• triangular(low=0.0 , high=1.0, mode=None)
Generate a random number in a triangular distribution.
• uniform(x, y)
Generate a real random number in the range (a,b).

>>> random.uniform(0,4)
1.940039451527575

• vonmisesvariate(mu, kappa)
Generate a random number in a circular data distribution.
• weibullvariate(alpha, beta)
Generate a random number in a Weibull distribution.

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