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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