random

Pseudo-random numbers from a Mersenne Twister generator. Module-level functions use a shared generator in the current VM; Random creates independent state. This generator is for simulations and games, not cryptographic secrets.

API	Behavior
`seed(value)`	Seed with an integer, or `None` for the clock. Integer seeds use the low 32 bits.
`random()`	Float in `[0.0, 1.0)`.
`randint(a, b)`	Integer including both endpoints; require `a <= b`.
`uniform(a, b)`	Float between the endpoints; floating-point rounding can affect the boundary.
`choice(sequence)`	One item from a nonempty list, tuple, or string.
`shuffle(items)`	Shuffle a list in place; return `None`.
`choices(population, weights=None, k=1)`	List of `k` selections with replacement; population and weights are lists or tuples.
`getstate()`, `setstate(state)`	Save/restore the generator's state as bytes.
`Random(value=None)`	New generator, optionally initialized with an integer seed or saved state bytes.

For weighted choices, supply finite nonnegative weights with matching length and total greater than 1e-6; use a nonnegative k. Unseeded generators initialize from the clock on first use.

Repeatable independent draws

from random import Random

rng = Random(7)
state = rng.getstate()
rolls = [rng.randint(1, 6) for _ in range(5)]
rng.setstate(state)
assert rolls == [rng.randint(1, 6) for _ in range(5)]

loot = rng.choices(['coin', 'gem'], weights=[9, 1], k=3)
assert len(loot) == 3
assert all([item in ['coin', 'gem'] for item in loot])

State bytes use pocketpy's internal representation, not CPython's state tuple. Do not assume sequences or saved states are interchangeable with CPython or across future runtime versions.

A generator can also be pickled:

import pickle
from random import Random

original = Random(7)
restored = pickle.loads(pickle.dumps(original))
assert original.random() == restored.random()