random

Module nustd.random.

Nu surface for Python's random module.

random is a function module - module-level functions over a global RNG, no central class - so the Nu surface mirrors that: free functions (random, randint, choice, sample, ...). Two layers behind it: functions (the typed wrappers) and interactions (the atoms each wrapper builds). Import it the way you would the stdlib:

from nustd.random import randint, choice
import nustd.random as random     # then random.randint(1, 6)

Every function reads the global RNG. The effectful / stateful pieces (seed, shuffle, getstate / setstate) are deferred until the effect model lands.

Call

Name	Call	Meaning
choice	`random.choice(seq)`	A random element of `seq`: mirrors `random.choice()`. Non-deterministic.
choices	`random.choices(population, k)`	A `k`-sized list drawn with replacement: mirrors `random.choices()`. Non-deterministic.
expovariate	`random.expovariate(lambd)`	An exponential draw with rate `lambd`: mirrors `random.expovariate()`. Non-deterministic.
gauss	`random.gauss(mu, sigma)`	A Gaussian draw with mean `mu` and stdev `sigma`: mirrors `random.gauss()`. Non-deterministic.
getrandbits	`random.getrandbits(k)`	A non-negative int with `k` random bits: mirrors `random.getrandbits()`. Non-deterministic.
normalvariate	`random.normalvariate(mu, sigma)`	A normal draw with mean `mu` and stdev `sigma`: mirrors `random.normalvariate()`. Non-deterministic.
randint	`random.randint(a, b)`	A random int `N` with `a <= N <= b`: mirrors `random.randint()`. Non-deterministic.
random	`random.random()`	A random float in `[0.0, 1.0)`: mirrors `random.random()`. Non-deterministic.
randrange	`random.randrange(start, stop)`	A random int in `range(start, stop)`: mirrors `random.randrange()`. Non-deterministic.
sample	`random.sample(population, k)`	A `k`-sized list drawn without replacement: mirrors `random.sample()`. Non-deterministic.
triangular	`random.triangular(low, high)`	A triangular draw between `low` and `high`: mirrors `random.triangular()`. Non-deterministic.
uniform	`random.uniform(a, b)`	A random float in `[a, b]`: mirrors `random.uniform()`. Non-deterministic.

choice

A random element of seq: mirrors random.choice(). Non-deterministic.

random.choice(seq)

Path nustd.random.choice. Defined on nustd.random.functions, bound as a function. Builds Any.

Arguments

Name	Type	Default	Meaning
`seq`	`ListArg[object]`

Undocumented: example.

choices

A k-sized list drawn with replacement: mirrors random.choices(). Non-deterministic.

random.choices(population, k)

Path nustd.random.choices. Defined on nustd.random.functions, bound as a function. Builds List.

Arguments

Name	Type	Default	Meaning
`population`	`ListArg[object]`
`k`	`IntArg`

Undocumented: example.

expovariate

An exponential draw with rate lambd: mirrors random.expovariate(). Non-deterministic.

random.expovariate(lambd)

Path nustd.random.expovariate. Defined on nustd.random.functions, bound as a function. Builds Float.

Arguments

Name	Type	Default	Meaning
`lambd`	`FloatArg`

Undocumented: example.

gauss

A Gaussian draw with mean mu and stdev sigma: mirrors random.gauss(). Non-deterministic.

random.gauss(mu, sigma)

Path nustd.random.gauss. Defined on nustd.random.functions, bound as a function. Builds Float.

Arguments

Name	Type	Default	Meaning
`mu`	`FloatArg`
`sigma`	`FloatArg`

Undocumented: example.

getrandbits

A non-negative int with k random bits: mirrors random.getrandbits(). Non-deterministic.

random.getrandbits(k)

Path nustd.random.getrandbits. Defined on nustd.random.functions, bound as a function. Builds Int.

Arguments

Name	Type	Default	Meaning
`k`	`IntArg`

Undocumented: example.

normalvariate

A normal draw with mean mu and stdev sigma: mirrors random.normalvariate(). Non-deterministic.

random.normalvariate(mu, sigma)

Path nustd.random.normalvariate. Defined on nustd.random.functions, bound as a function. Builds Float.

Arguments

Name	Type	Default	Meaning
`mu`	`FloatArg`
`sigma`	`FloatArg`

Undocumented: example.

randint

A random int N with a <= N <= b: mirrors random.randint(). Non-deterministic.

random.randint(a, b)

Path nustd.random.randint. Defined on nustd.random.functions, bound as a function. Builds Int.

Arguments

Name	Type	Default	Meaning
`a`	`IntArg`
`b`	`IntArg`

Undocumented: example.

random

A random float in [0.0, 1.0): mirrors random.random(). Non-deterministic.

random.random()

Path nustd.random.random. Defined on nustd.random.functions, bound as a function. Builds Float.

Undocumented: example.

randrange

A random int in range(start, stop): mirrors random.randrange(). Non-deterministic.

random.randrange(start, stop)

Path nustd.random.randrange. Defined on nustd.random.functions, bound as a function. Builds Int.

Arguments

Name	Type	Default	Meaning
`start`	`IntArg`
`stop`	`IntArg`

Undocumented: example.

sample

A k-sized list drawn without replacement: mirrors random.sample(). Non-deterministic.

random.sample(population, k)

Path nustd.random.sample. Defined on nustd.random.functions, bound as a function. Builds List.

Arguments

Name	Type	Default	Meaning
`population`	`ListArg[object]`
`k`	`IntArg`

Undocumented: example.

triangular

A triangular draw between low and high: mirrors random.triangular(). Non-deterministic.

random.triangular(low, high)

Path nustd.random.triangular. Defined on nustd.random.functions, bound as a function. Builds Float.

Arguments

Name	Type	Default	Meaning
`low`	`FloatArg`
`high`	`FloatArg`

Undocumented: example.

uniform

A random float in [a, b]: mirrors random.uniform(). Non-deterministic.

random.uniform(a, b)

Path nustd.random.uniform. Defined on nustd.random.functions, bound as a function. Builds Float.

Arguments

Name	Type	Default	Meaning
`a`	`FloatArg`
`b`	`FloatArg`

Undocumented: example.

random

On this page