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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.
+
+//! 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 ChaCha12,
+//! 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
+
+#[cfg_attr(doc_cfg, doc(cfg(feature = "std")))]
+#[cfg(feature = "std")] pub mod adapter;
+
+pub mod mock; // Public so we don't export `StepRng` directly, making it a bit
+ // more clear it is intended for testing.
+
+#[cfg(all(feature = "small_rng", target_pointer_width = "64"))]
+mod xoshiro256plusplus;
+#[cfg(all(feature = "small_rng", not(target_pointer_width = "64")))]
+mod xoshiro128plusplus;
+#[cfg(feature = "small_rng")] mod small;
+
+#[cfg(feature = "std_rng")] mod std;
+#[cfg(all(feature = "std", feature = "std_rng"))] pub(crate) mod thread;
+
+#[cfg(feature = "small_rng")] pub use self::small::SmallRng;
+#[cfg(feature = "std_rng")] pub use self::std::StdRng;
+#[cfg(all(feature = "std", feature = "std_rng"))] pub use self::thread::ThreadRng;
+
+#[cfg_attr(doc_cfg, doc(cfg(feature = "getrandom")))]
+#[cfg(feature = "getrandom")] pub use rand_core::OsRng;