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// Copyright 2018 Developers of the Rand project. // // Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or // https://www.apache.org/licenses/LICENSE-2.0> or the MIT license // <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your // option. This file may not be copied, modified, or distributed // except according to those terms. //! A small fast RNG use rand_core::{Error, RngCore, SeedableRng}; #[cfg(target_pointer_width = "64")] type Rng = super::xoshiro256plusplus::Xoshiro256PlusPlus; #[cfg(not(target_pointer_width = "64"))] type Rng = super::xoshiro128plusplus::Xoshiro128PlusPlus; /// 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](https://rust-random.github.io/book/guide-rngs.html). /// /// 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(); /// # let v: u32 = small_rng.gen(); /// ``` /// /// 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(); /// ``` /// /// [`StdRng`]: crate::rngs::StdRng /// [`thread_rng`]: crate::thread_rng /// [rand_chacha]: https://crates.io/crates/rand_chacha /// [rand_xoshiro]: https://crates.io/crates/rand_xoshiro #[cfg_attr(doc_cfg, doc(cfg(feature = "small_rng")))] #[derive(Clone, Debug, PartialEq, Eq)] pub struct SmallRng(Rng); impl RngCore for SmallRng { #[inline(always)] fn next_u32(&mut self) -> u32 { self.0.next_u32() } #[inline(always)] fn next_u64(&mut self) -> u64 { self.0.next_u64() } #[inline(always)] fn fill_bytes(&mut self, dest: &mut [u8]) { self.0.fill_bytes(dest); } #[inline(always)] fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> { self.0.try_fill_bytes(dest) } } impl SeedableRng for SmallRng { type Seed = <Rng as SeedableRng>::Seed; #[inline(always)] fn from_seed(seed: Self::Seed) -> Self { SmallRng(Rng::from_seed(seed)) } #[inline(always)] fn from_rng<R: RngCore>(rng: R) -> Result<Self, Error> { Rng::from_rng(rng).map(SmallRng) } }