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| ||'''Function''' ||'''Meaning''' || ||`betavariate()` || || ||`choice()` || || ||`choices()` || || ||`expovariate()` || || ||`gammavariate()` || || ||`gauss(mu, sigma)` ||return a [[Python/Builtins/Types#Float|float]] from the Gaussian distribution characterized by ''mu'' and ''sigma''|| ||`getrandbits()` || || ||`lognormvariate()` || || ||`normalvariate(mu, sigma)`||return a float from the normal distribution characterized by ''mu'' and ''sigma'' || ||`paretovariate()` || || ||`randbytes()` || || ||`randint()` || || ||`random()` ||return a float between 0 and 1, inclusive of 0 || ||`randrange()` || || ||`sample()` || || ||`seed()` || || ||`shuffle()` || || ||`triangular()` || || ||`uniform(a, b)` ||return a float between ''a'' and ''b'', inclusive (except when floating point rounding hits the high value) || ||`vonmisesvariate()` || || ||`weibullvariate()` || || |
||'''Function''' ||'''Meaning''' || ||`betavariate()` || || ||`binomialvariate(n, p)` ||return the [[Python/Builtins/Types#Int|int]] expected number of successes given a binomial distribution over probability `p` (between 0 and 1) and given `n` trials|| ||`choice(it)` ||return a random element of [[Python/Collections/Abc#Sequence|sequence]] `it` || ||`choices()` || || ||`expovariate()` || || ||`gammavariate()` || || ||`gauss(mu, sigma)` ||return a [[Python/Builtins/Types#Float|float]] from the Gaussian distribution characterized by ''mu'' and ''sigma'' || ||`getrandbits()` || || ||`lognormvariate()` || || ||`normalvariate(mu, sigma)`||return a float from the normal distribution characterized by ''mu'' and ''sigma'' || ||`paretovariate()` || || ||`randbytes()` || || ||`randint(a, b)` ||return an int from a discrete uniform distribution between ''a'' and ''b'', inclusive || ||`random()` ||return a float between 0 and 1, inclusive of 0 || ||`randrange()` ||return an int from a range; takes same arguments as `range()` (i.e. `range(10)`; `range(1,11,2)`) || ||`sample()` || || ||`seed()` || || ||`shuffle(it)` ||randomize the order of elements in [[Python/Collections/Abc#MutableSequence|mutable sequence]] `it` in place || ||`triangular()` || || ||`uniform(a, b)` ||return a float between ''a'' and ''b'', inclusive (except when floating point rounding hits the high value) || ||`vonmisesvariate()` || || ||`weibullvariate()` || || |
Python Random
random is a module for pseudo-random number generation.
Contents
Usage
Function |
Meaning |
betavariate() |
|
binomialvariate(n, p) |
return the int expected number of successes given a binomial distribution over probability p (between 0 and 1) and given n trials |
choice(it) |
return a random element of sequence it |
choices() |
|
expovariate() |
|
gammavariate() |
|
gauss(mu, sigma) |
return a float from the Gaussian distribution characterized by mu and sigma |
getrandbits() |
|
lognormvariate() |
|
normalvariate(mu, sigma) |
return a float from the normal distribution characterized by mu and sigma |
paretovariate() |
|
randbytes() |
|
randint(a, b) |
return an int from a discrete uniform distribution between a and b, inclusive |
random() |
return a float between 0 and 1, inclusive of 0 |
randrange() |
return an int from a range; takes same arguments as range() (i.e. range(10); range(1,11,2)) |
sample() |
|
seed() |
|
shuffle(it) |
randomize the order of elements in mutable sequence it in place |
triangular() |
|
uniform(a, b) |
return a float between a and b, inclusive (except when floating point rounding hits the high value) |
vonmisesvariate() |
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weibullvariate() |
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See also
Python random module documentation
Python Module of the Day article for random