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])
Fill
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
Seed type, which is restricted to types mutably-dereferenceable as
u8
arrays (we recommend [u8; N] for some N). Read moreSource§fn from_seed(seed: <StdRng as SeedableRng>::Seed) -> StdRng
fn from_seed(seed: <StdRng as SeedableRng>::Seed) -> StdRng
Create a new PRNG using the given seed. Read more
Source§fn from_rng<R>(rng: R) -> Result<StdRng, Error>where
R: RngCore,
fn from_rng<R>(rng: R) -> Result<StdRng, Error>where
R: RngCore,
Create a new PRNG seeded from another
Rng. Read moreSource§fn seed_from_u64(state: u64) -> Self
fn seed_from_u64(state: u64) -> Self
Create a new PRNG using a
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> AsyncTaskResult for T
impl<T> AsyncTaskResult for T
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
Mutably borrows from an owned value. Read more
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<T> Downcast for Twhere
T: Any,
impl<T> Downcast for Twhere
T: Any,
Source§fn into_any(self: Box<T>) -> Box<dyn Any>
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fn as_any_mut(&mut self) -> &mut (dyn Any + 'static)
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Source§impl<T> DowncastSync for T
impl<T> DowncastSync for T
Source§impl<Q, K> Equivalent<K> for Q
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Source§fn equivalent(&self, key: &K) -> bool
fn equivalent(&self, key: &K) -> bool
Compare self to
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T: 'static,
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Converts
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Source§impl<T> Pointable for T
impl<T> Pointable for T
Source§impl<R> Rng for R
impl<R> Rng for R
Source§fn gen<T>(&mut self) -> Twhere
Standard: Distribution<T>,
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Source§fn gen_range<T, R>(&mut self, range: R) -> Twhere
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fn gen_range<T, R>(&mut self, range: R) -> Twhere
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Generate a random value in the given range. Read more
Source§fn sample<T, D>(&mut self, distr: D) -> Twhere
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Sample a new value, using the given distribution. Read more
Source§fn sample_iter<T, D>(self, distr: D) -> DistIter<D, Self, T> ⓘwhere
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Create an iterator that generates values using the given distribution. Read more
Source§fn gen_bool(&mut self, p: f64) -> bool
fn gen_bool(&mut self, p: f64) -> bool
Return a bool with a probability
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
Return a bool with a probability of
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true. I.e. gen_ratio(2, 3) has chance of 2 in 3, or about 67%, of
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