pub struct SmallRng(_);Expand description
A small-state, fast non-crypto PRNG
SmallRng may be a good choice when a PRNG with small state, cheap
initialization, good statistical quality and good performance are required.
Note that depending on the application, StdRng may be faster on many
modern platforms while providing higher-quality randomness. Furthermore,
SmallRng is not a good choice when:
- Security against prediction is important. Use
StdRnginstead. - Seeds with many zeros are provided. In such cases, it takes
SmallRngabout 10 samples to produce 0 and 1 bits with equal probability. Either provide seeds with an approximately equal number of 0 and 1 (for example by usingSeedableRng::from_entropyorSeedableRng::seed_from_u64), or useStdRnginstead.
The algorithm is deterministic but should not be considered reproducible due to dependence on platform and possible replacement in future library versions. For a reproducible generator, use a named PRNG from an external crate, e.g. rand_xoshiro or rand_chacha. Refer also to The Book.
The PRNG algorithm in SmallRng is chosen to be efficient on the current
platform, without consideration for cryptography or security. The size of
its state is much smaller than StdRng. The current algorithm is
Xoshiro256PlusPlus on 64-bit platforms and Xoshiro128PlusPlus on 32-bit
platforms. Both are also implemented by the rand_xoshiro crate.
Examples
Initializing SmallRng with a random seed can be done using SeedableRng::from_entropy:
use rand::{Rng, SeedableRng};
use rand::rngs::SmallRng;
// Create small, cheap to initialize and fast RNG with a random seed.
// The randomness is supplied by the operating system.
let mut small_rng = SmallRng::from_entropy();When initializing a lot of SmallRng’s, using thread_rng can be more
efficient:
use rand::{SeedableRng, thread_rng};
use rand::rngs::SmallRng;
// Create a big, expensive to initialize and slower, but unpredictable RNG.
// This is cached and done only once per thread.
let mut thread_rng = thread_rng();
// Create small, cheap to initialize and fast RNGs with random seeds.
// One can generally assume this won't fail.
let rngs: Vec<SmallRng> = (0..10)
.map(|_| SmallRng::from_rng(&mut thread_rng).unwrap())
.collect();Trait Implementations§
source§impl RngCore for SmallRng
impl RngCore for SmallRng
source§fn fill_bytes(&mut self, dest: &mut [u8])
fn fill_bytes(&mut self, dest: &mut [u8])
dest with random data. Read moresource§impl SeedableRng for SmallRng
impl SeedableRng for SmallRng
§type Seed = <Xoshiro256PlusPlus as SeedableRng>::Seed
type Seed = <Xoshiro256PlusPlus as SeedableRng>::Seed
u8
arrays (we recommend [u8; N] for some N). Read moresource§fn from_rng<R: RngCore>(rng: R) -> Result<Self, Error>
fn from_rng<R: RngCore>(rng: R) -> Result<Self, Error>
Rng. Read moresource§fn seed_from_u64(state: u64) -> Self
fn seed_from_u64(state: u64) -> Self
u64 seed. Read more