Struct rand::rngs::StdRng [−][src]
pub struct StdRng(_);
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 20 rounds. 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
impl SeedableRng for StdRng
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impl SeedableRng for StdRng
[src]type Seed = <Rng as SeedableRng>::Seed
Seed type, which is restricted to types mutably-dereferencable as u8
arrays (we recommend [u8; N]
for some N
). Read more
fn from_seed(seed: Self::Seed) -> Self
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fn from_rng<R: RngCore>(rng: R) -> Result<Self, Error>
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pub fn seed_from_u64(state: u64) -> Self
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pub fn from_entropy() -> Self
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impl CryptoRng for StdRng
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Auto Trait Implementations
impl RefUnwindSafe for StdRng
impl Send for StdRng
impl Sync for StdRng
impl Unpin for StdRng
impl UnwindSafe for StdRng
Blanket Implementations
impl<R> Rng for R where
R: RngCore + ?Sized,
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impl<R> Rng for R where
R: RngCore + ?Sized,
[src]fn gen<T>(&mut self) -> T where
Standard: Distribution<T>,
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Standard: Distribution<T>,
fn gen_range<T: SampleUniform, B1, B2>(&mut self, low: B1, high: B2) -> T where
B1: SampleBorrow<T> + Sized,
B2: SampleBorrow<T> + Sized,
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B1: SampleBorrow<T> + Sized,
B2: SampleBorrow<T> + Sized,
fn sample<T, D: Distribution<T>>(&mut self, distr: D) -> T
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fn sample_iter<T, D>(self, distr: D) -> DistIter<D, Self, T>ⓘ where
D: Distribution<T>,
Self: Sized,
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D: Distribution<T>,
Self: Sized,
fn fill<T: AsByteSliceMut + ?Sized>(&mut self, dest: &mut T)
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fn try_fill<T: AsByteSliceMut + ?Sized>(
&mut self,
dest: &mut T
) -> Result<(), Error>
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&mut self,
dest: &mut T
) -> Result<(), Error>