pub struct StdRng(/* private fields */);
Expand description
The standard RNG. The PRNG algorithm in StdRng
is chosen to be efficient
on the current platform, to be statistically strong and unpredictable
(meaning a cryptographically secure PRNG).
The current algorithm used is the ChaCha block cipher with 12 rounds. Please see this relevant rand issue for the discussion. This may change as new evidence of cipher security and performance becomes available.
The algorithm is deterministic but should not be considered reproducible due to dependence on configuration and possible replacement in future library versions. For a secure reproducible generator, we recommend use of the rand_chacha crate directly.
Trait Implementations§
Source§impl RngCore for StdRng
impl RngCore for StdRng
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 StdRng
impl SeedableRng for StdRng
Source§type Seed = <ChaCha12Rng as SeedableRng>::Seed
type Seed = <ChaCha12Rng 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 moreSource§fn from_entropy() -> Self
fn from_entropy() -> Self
impl CryptoRng for StdRng
impl Eq for StdRng
impl StructuralPartialEq for StdRng
Auto Trait Implementations§
impl Freeze for StdRng
impl RefUnwindSafe for StdRng
impl Send for StdRng
impl Sync for StdRng
impl Unpin for StdRng
impl UnwindSafe for StdRng
Blanket Implementations§
Source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
Source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Source§impl<T> CloneToUninit for Twhere
T: Clone,
impl<T> CloneToUninit for Twhere
T: Clone,
Source§impl<T> CryptoRngCore for T
impl<T> CryptoRngCore for T
Source§impl<R> Rng for R
impl<R> Rng for R
Source§fn gen<T>(&mut self) -> Twhere
Standard: Distribution<T>,
fn gen<T>(&mut self) -> Twhere
Standard: Distribution<T>,
Source§fn gen_range<T, R>(&mut self, range: R) -> Twhere
T: SampleUniform,
R: SampleRange<T>,
fn gen_range<T, R>(&mut self, range: R) -> Twhere
T: SampleUniform,
R: SampleRange<T>,
Source§fn sample<T, D: Distribution<T>>(&mut self, distr: D) -> T
fn sample<T, D: Distribution<T>>(&mut self, distr: D) -> T
Source§fn sample_iter<T, D>(self, distr: D) -> DistIter<D, Self, T> ⓘwhere
D: Distribution<T>,
Self: Sized,
fn sample_iter<T, D>(self, distr: D) -> DistIter<D, Self, T> ⓘwhere
D: Distribution<T>,
Self: Sized,
Source§fn gen_bool(&mut self, p: f64) -> bool
fn gen_bool(&mut self, p: f64) -> bool
p
of being true. Read moreSource§fn gen_ratio(&mut self, numerator: u32, denominator: u32) -> bool
fn gen_ratio(&mut self, numerator: u32, denominator: u32) -> bool
numerator/denominator
of being
true. I.e. gen_ratio(2, 3)
has chance of 2 in 3, or about 67%, of
returning true. If numerator == denominator
, then the returned value
is guaranteed to be true
. If numerator == 0
, then the returned
value is guaranteed to be false
. Read moreLayout§
Note: Most layout information is completely unstable and may even differ between compilations. The only exception is types with certain repr(...)
attributes. Please see the Rust Reference's “Type Layout” chapter for details on type layout guarantees.
Size: 320 bytes