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
StdRng
instead. - Seeds with many zeros are provided. In such cases, it takes
SmallRng
about 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_entropy
orSeedableRng::seed_from_u64
), or useStdRng
instead.
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
sourceimpl SeedableRng for SmallRng
impl SeedableRng for SmallRng
type Seed = <Xoshiro256PlusPlus as SeedableRng>::Seed
type Seed = <Xoshiro256PlusPlus as SeedableRng>::Seed
Seed type, which is restricted to types mutably-dereferencable as u8
arrays (we recommend [u8; N]
for some N
). Read more
sourcefn from_rng<R: RngCore>(rng: R) -> Result<Self, Error>
fn from_rng<R: RngCore>(rng: R) -> Result<Self, Error>
Create a new PRNG seeded from another Rng
. Read more
sourcefn seed_from_u64(state: u64) -> Self
fn seed_from_u64(state: u64) -> Self
Create a new PRNG using a u64
seed. Read more
sourcefn from_entropy() -> Self
fn from_entropy() -> Self
impl Eq for SmallRng
impl StructuralEq for SmallRng
impl StructuralPartialEq for SmallRng
Auto Trait Implementations
impl RefUnwindSafe for SmallRng
impl Send for SmallRng
impl Sync for SmallRng
impl Unpin for SmallRng
impl UnwindSafe for SmallRng
Blanket Implementations
sourceimpl<T> BorrowMut<T> for T where
T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
const: unstable · sourcefn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
sourceimpl<T> ToOwned for T where
T: Clone,
impl<T> ToOwned for T where
T: Clone,
type Owned = T
type Owned = T
The resulting type after obtaining ownership.
sourcefn clone_into(&self, target: &mut T)
fn clone_into(&self, target: &mut T)
toowned_clone_into
)Uses borrowed data to replace owned data, usually by cloning. Read more