aboutsummaryrefslogtreecommitdiff
path: root/rand/src/rngs/mod.rs
diff options
context:
space:
mode:
Diffstat (limited to 'rand/src/rngs/mod.rs')
-rw-r--r--rand/src/rngs/mod.rs119
1 files changed, 0 insertions, 119 deletions
diff --git a/rand/src/rngs/mod.rs b/rand/src/rngs/mod.rs
deleted file mode 100644
index abf3243..0000000
--- a/rand/src/rngs/mod.rs
+++ /dev/null
@@ -1,119 +0,0 @@
-// 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].
-//!
-//! [`SmallRng`]: rngs::SmallRng
-//! [`StdRng`]: rngs::StdRng
-//! [`OsRng`]: rngs::OsRng
-//! [`ThreadRng`]: rngs::ThreadRng
-//! [`mock::StepRng`]: rngs::mock::StepRng
-//! [`adapter::ReadRng`]: rngs::adapter::ReadRng
-//! [`adapter::ReseedingRng`]: rngs::adapter::ReseedingRng
-//! [`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;