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Diffstat (limited to 'vendor/rand-0.7.3/src/rngs/mod.rs')
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diff --git a/vendor/rand-0.7.3/src/rngs/mod.rs b/vendor/rand-0.7.3/src/rngs/mod.rs new file mode 100644 index 000000000..111219602 --- /dev/null +++ b/vendor/rand-0.7.3/src/rngs/mod.rs @@ -0,0 +1,116 @@ +// 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. + +//! Random number generators and adapters +//! +//! ## Background: Random number generators (RNGs) +//! +//! Computers cannot produce random numbers from nowhere. We classify +//! random number generators as follows: +//! +//! - "True" random number generators (TRNGs) use hard-to-predict data sources +//! (e.g. the high-resolution parts of event timings and sensor jitter) to +//! harvest random bit-sequences, apply algorithms to remove bias and +//! estimate available entropy, then combine these bits into a byte-sequence +//! or an entropy pool. This job is usually done by the operating system or +//! a hardware generator (HRNG). +//! - "Pseudo"-random number generators (PRNGs) use algorithms to transform a +//! seed into a sequence of pseudo-random numbers. These generators can be +//! fast and produce well-distributed unpredictable random numbers (or not). +//! They are usually deterministic: given algorithm and seed, the output +//! sequence can be reproduced. They have finite period and eventually loop; +//! with many algorithms this period is fixed and can be proven sufficiently +//! long, while others are chaotic and the period depends on the seed. +//! - "Cryptographically secure" pseudo-random number generators (CSPRNGs) +//! are the sub-set of PRNGs which are secure. Security of the generator +//! relies both on hiding the internal state and using a strong algorithm. +//! +//! ## Traits and functionality +//! +//! All RNGs implement the [`RngCore`] trait, as a consequence of which the +//! [`Rng`] extension trait is automatically implemented. Secure RNGs may +//! additionally implement the [`CryptoRng`] trait. +//! +//! All PRNGs require a seed to produce their random number sequence. The +//! [`SeedableRng`] trait provides three ways of constructing PRNGs: +//! +//! - `from_seed` accepts a type specific to the PRNG +//! - `from_rng` allows a PRNG to be seeded from any other RNG +//! - `seed_from_u64` allows any PRNG to be seeded from a `u64` insecurely +//! - `from_entropy` securely seeds a PRNG from fresh entropy +//! +//! Use the [`rand_core`] crate when implementing your own RNGs. +//! +//! ## Our generators +//! +//! This crate provides several random number generators: +//! +//! - [`OsRng`] is an interface to the operating system's random number +//! source. Typically the operating system uses a CSPRNG with entropy +//! provided by a TRNG and some type of on-going re-seeding. +//! - [`ThreadRng`], provided by the [`thread_rng`] function, is a handle to a +//! thread-local CSPRNG with periodic seeding from [`OsRng`]. Because this +//! is local, it is typically much faster than [`OsRng`]. It should be +//! secure, though the paranoid may prefer [`OsRng`]. +//! - [`StdRng`] is a CSPRNG chosen for good performance and trust of security +//! (based on reviews, maturity and usage). The current algorithm is ChaCha20, +//! which is well established and rigorously analysed. +//! [`StdRng`] provides the algorithm used by [`ThreadRng`] but without +//! periodic reseeding. +//! - [`SmallRng`] is an **insecure** PRNG designed to be fast, simple, require +//! little memory, and have good output quality. +//! +//! The algorithms selected for [`StdRng`] and [`SmallRng`] may change in any +//! release and may be platform-dependent, therefore they should be considered +//! **not reproducible**. +//! +//! ## Additional generators +//! +//! **TRNGs**: The [`rdrand`] crate provides an interface to the RDRAND and +//! RDSEED instructions available in modern Intel and AMD CPUs. +//! The [`rand_jitter`] crate provides a user-space implementation of +//! entropy harvesting from CPU timer jitter, but is very slow and has +//! [security issues](https://github.com/rust-random/rand/issues/699). +//! +//! **PRNGs**: Several companion crates are available, providing individual or +//! families of PRNG algorithms. These provide the implementations behind +//! [`StdRng`] and [`SmallRng`] but can also be used directly, indeed *should* +//! be used directly when **reproducibility** matters. +//! Some suggestions are: [`rand_chacha`], [`rand_pcg`], [`rand_xoshiro`]. +//! A full list can be found by searching for crates with the [`rng` tag]. +//! +//! [`Rng`]: crate::Rng +//! [`RngCore`]: crate::RngCore +//! [`CryptoRng`]: crate::CryptoRng +//! [`SeedableRng`]: crate::SeedableRng +//! [`thread_rng`]: crate::thread_rng +//! [`rdrand`]: https://crates.io/crates/rdrand +//! [`rand_jitter`]: https://crates.io/crates/rand_jitter +//! [`rand_chacha`]: https://crates.io/crates/rand_chacha +//! [`rand_pcg`]: https://crates.io/crates/rand_pcg +//! [`rand_xoshiro`]: https://crates.io/crates/rand_xoshiro +//! [`rng` tag]: https://crates.io/keywords/rng + +pub mod adapter; + +#[cfg(feature = "std")] mod entropy; +pub mod mock; // Public so we don't export `StepRng` directly, making it a bit + // more clear it is intended for testing. +#[cfg(feature = "small_rng")] mod small; +mod std; +#[cfg(feature = "std")] pub(crate) mod thread; + +#[allow(deprecated)] +#[cfg(feature = "std")] +pub use self::entropy::EntropyRng; + +#[cfg(feature = "small_rng")] pub use self::small::SmallRng; +pub use self::std::StdRng; +#[cfg(feature = "std")] pub use self::thread::ThreadRng; + +#[cfg(feature = "getrandom")] pub use rand_core::OsRng; |