Struct breez_sdk_core::bitcoin::util::key::secp256k1::rand::prelude::SmallRng

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pub struct SmallRng(/* private fields */);
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 using SeedableRng::from_entropy or SeedableRng::seed_from_u64), or use StdRng 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§

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impl Clone for SmallRng

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fn clone(&self) -> SmallRng

Returns a copy of the value. Read more
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fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source. Read more
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impl Debug for SmallRng

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fn fmt(&self, f: &mut Formatter<'_>) -> Result<(), Error>

Formats the value using the given formatter. Read more
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impl PartialEq for SmallRng

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fn eq(&self, other: &SmallRng) -> bool

Tests for self and other values to be equal, and is used by ==.
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fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.
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impl RngCore for SmallRng

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fn next_u32(&mut self) -> u32

Return the next random u32. Read more
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fn next_u64(&mut self) -> u64

Return the next random u64. Read more
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fn fill_bytes(&mut self, dest: &mut [u8])

Fill dest with random data. Read more
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fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error>

Fill dest entirely with random data. Read more
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impl SeedableRng for SmallRng

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type Seed = <Xoshiro256PlusPlus as SeedableRng>::Seed

Seed type, which is restricted to types mutably-dereferenceable as u8 arrays (we recommend [u8; N] for some N). Read more
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fn from_seed(seed: <SmallRng as SeedableRng>::Seed) -> SmallRng

Create a new PRNG using the given seed. Read more
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fn from_rng<R>(rng: R) -> Result<SmallRng, Error>
where R: RngCore,

Create a new PRNG seeded from another Rng. Read more
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fn seed_from_u64(state: u64) -> Self

Create a new PRNG using a u64 seed. Read more
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fn from_entropy() -> Self

Creates a new instance of the RNG seeded via getrandom. Read more
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impl Eq for SmallRng

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impl StructuralPartialEq for SmallRng

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fn borrow(&self) -> &T

Immutably borrows from an owned value. Read more
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fn borrow_mut(&mut self) -> &mut T

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unsafe fn clone_to_uninit(&self, dst: *mut T)

🔬This is a nightly-only experimental API. (clone_to_uninit)
Performs copy-assignment from self to dst. Read more
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fn equivalent(&self, key: &K) -> bool

Compare self to key and return true if they are equal.
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fn equivalent(&self, key: &K) -> bool

Checks if this value is equivalent to the given key. Read more
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fn equivalent(&self, key: &K) -> bool

Compare self to key and return true if they are equal.
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fn gen_biguint(&mut self, bit_size: usize) -> BigUint

Generate a random BigUint of the given bit size.
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fn gen_bigint(&mut self, bit_size: usize) -> BigInt

Generate a random BigInt of the given bit size.
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fn gen_biguint_below(&mut self, bound: &BigUint) -> BigUint

Generate a random BigUint less than the given bound. Fails when the bound is zero.
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fn gen_biguint_range(&mut self, lbound: &BigUint, ubound: &BigUint) -> BigUint

Generate a random BigUint within the given range. The lower bound is inclusive; the upper bound is exclusive. Fails when the upper bound is not greater than the lower bound.
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fn gen_bigint_range(&mut self, lbound: &BigInt, ubound: &BigInt) -> BigInt

Generate a random BigInt within the given range. The lower bound is inclusive; the upper bound is exclusive. Fails when the upper bound is not greater than the lower bound.
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impl<R> RandPrime for R
where R: Rng + ?Sized,

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fn gen_prime(&mut self, bit_size: usize) -> BigUint

Generate a random prime number with as many bits as given.
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fn gen<T>(&mut self) -> T

Return a random value supporting the Standard distribution. Read more
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fn gen_range<T, R>(&mut self, range: R) -> T
where T: SampleUniform, R: SampleRange<T>,

Generate a random value in the given range. Read more
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fn sample<T, D>(&mut self, distr: D) -> T
where D: Distribution<T>,

Sample a new value, using the given distribution. Read more
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fn sample_iter<T, D>(self, distr: D) -> DistIter<D, Self, T>
where D: Distribution<T>, Self: Sized,

Create an iterator that generates values using the given distribution. Read more
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fn fill<T>(&mut self, dest: &mut T)
where T: Fill + ?Sized,

Fill any type implementing Fill with random data Read more
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fn try_fill<T>(&mut self, dest: &mut T) -> Result<(), Error>
where T: Fill + ?Sized,

Fill any type implementing Fill with random data Read more
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fn gen_bool(&mut self, p: f64) -> bool

Return a bool with a probability p of being true. Read more
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fn gen_ratio(&mut self, numerator: u32, denominator: u32) -> bool

Return a bool with a probability of 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 more
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