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</pre><pre class="rust"><code><span class="comment">// Copyright 2018 Developers of the Rand project.
// Copyright 2013-2017 The Rust Project Developers.
//
// Licensed under the Apache License, Version 2.0 &lt;LICENSE-APACHE or
// https://www.apache.org/licenses/LICENSE-2.0&gt; or the MIT license
// &lt;LICENSE-MIT or https://opensource.org/licenses/MIT&gt;, at your
// option. This file may not be copied, modified, or distributed
// except according to those terms.
</span><span class="doccomment">//! Utilities for random number generation
//!
//! Rand provides utilities to generate random numbers, to convert them to
//! useful types and distributions, and some randomness-related algorithms.
//!
//! # Quick Start
//!
//! To get you started quickly, the easiest and highest-level way to get
//! a random value is to use [`random()`]; alternatively you can use
//! [`thread_rng()`]. The [`Rng`] trait provides a useful API on all RNGs, while
//! the [`distributions`] and [`seq`] modules provide further
//! functionality on top of RNGs.
//!
//! ```
//! use rand::prelude::*;
//!
//! if rand::random() { // generates a boolean
//! // Try printing a random unicode code point (probably a bad idea)!
//! println!(&quot;char: {}&quot;, rand::random::&lt;char&gt;());
//! }
//!
//! let mut rng = rand::thread_rng();
//! let y: f64 = rng.gen(); // generates a float between 0 and 1
//!
//! let mut nums: Vec&lt;i32&gt; = (1..100).collect();
//! nums.shuffle(&amp;mut rng);
//! ```
//!
//! # The Book
//!
//! For the user guide and further documentation, please read
//! [The Rust Rand Book](https://rust-random.github.io/book).
</span><span class="attribute">#![doc(
html_logo_url = <span class="string">&quot;https://www.rust-lang.org/logos/rust-logo-128x128-blk.png&quot;</span>,
html_favicon_url = <span class="string">&quot;https://www.rust-lang.org/favicon.ico&quot;</span>,
html_root_url = <span class="string">&quot;https://rust-random.github.io/rand/&quot;
</span>)]
#![deny(missing_docs)]
#![deny(missing_debug_implementations)]
#![doc(test(attr(allow(unused_variables), deny(warnings))))]
#![no_std]
#![cfg_attr(feature = <span class="string">&quot;simd_support&quot;</span>, feature(stdsimd))]
#![cfg_attr(doc_cfg, feature(doc_cfg))]
#![allow(
clippy::float_cmp,
clippy::neg_cmp_op_on_partial_ord,
)]
#[cfg(feature = <span class="string">&quot;std&quot;</span>)] </span><span class="kw">extern crate </span>std;
<span class="attribute">#[cfg(feature = <span class="string">&quot;alloc&quot;</span>)] </span><span class="kw">extern crate </span>alloc;
<span class="attribute">#[allow(unused)]
</span><span class="macro">macro_rules! </span>trace { ($(<span class="macro-nonterminal">$x</span>:tt)<span class="kw-2">*</span>) =&gt; (
<span class="attribute">#[cfg(feature = <span class="string">&quot;log&quot;</span>)] </span>{
<span class="macro">log::trace!</span>($(<span class="macro-nonterminal">$x</span>)<span class="kw-2">*</span>)
}
) }
<span class="attribute">#[allow(unused)]
</span><span class="macro">macro_rules! </span>debug { ($(<span class="macro-nonterminal">$x</span>:tt)<span class="kw-2">*</span>) =&gt; (
<span class="attribute">#[cfg(feature = <span class="string">&quot;log&quot;</span>)] </span>{
<span class="macro">log::debug!</span>($(<span class="macro-nonterminal">$x</span>)<span class="kw-2">*</span>)
}
) }
<span class="attribute">#[allow(unused)]
</span><span class="macro">macro_rules! </span>info { ($(<span class="macro-nonterminal">$x</span>:tt)<span class="kw-2">*</span>) =&gt; (
<span class="attribute">#[cfg(feature = <span class="string">&quot;log&quot;</span>)] </span>{
<span class="macro">log::info!</span>($(<span class="macro-nonterminal">$x</span>)<span class="kw-2">*</span>)
}
) }
<span class="attribute">#[allow(unused)]
</span><span class="macro">macro_rules! </span>warn { ($(<span class="macro-nonterminal">$x</span>:tt)<span class="kw-2">*</span>) =&gt; (
<span class="attribute">#[cfg(feature = <span class="string">&quot;log&quot;</span>)] </span>{
<span class="macro">log::warn!</span>($(<span class="macro-nonterminal">$x</span>)<span class="kw-2">*</span>)
}
) }
<span class="attribute">#[allow(unused)]
</span><span class="macro">macro_rules! </span>error { ($(<span class="macro-nonterminal">$x</span>:tt)<span class="kw-2">*</span>) =&gt; (
<span class="attribute">#[cfg(feature = <span class="string">&quot;log&quot;</span>)] </span>{
<span class="macro">log::error!</span>($(<span class="macro-nonterminal">$x</span>)<span class="kw-2">*</span>)
}
) }
<span class="comment">// Re-exports from rand_core
</span><span class="kw">pub use </span>rand_core::{CryptoRng, Error, RngCore, SeedableRng};
<span class="comment">// Public modules
</span><span class="kw">pub mod </span>distributions;
<span class="kw">pub mod </span>prelude;
<span class="kw">mod </span>rng;
<span class="kw">pub mod </span>rngs;
<span class="kw">pub mod </span>seq;
<span class="comment">// Public exports
</span><span class="attribute">#[cfg(all(feature = <span class="string">&quot;std&quot;</span>, feature = <span class="string">&quot;std_rng&quot;</span>))]
</span><span class="kw">pub use </span><span class="kw">crate</span>::rngs::thread::thread_rng;
<span class="kw">pub use </span>rng::{Fill, Rng};
<span class="attribute">#[cfg(all(feature = <span class="string">&quot;std&quot;</span>, feature = <span class="string">&quot;std_rng&quot;</span>))]
</span><span class="kw">use </span><span class="kw">crate</span>::distributions::{Distribution, Standard};
<span class="doccomment">/// Generates a random value using the thread-local random number generator.
///
/// This is simply a shortcut for `thread_rng().gen()`. See [`thread_rng`] for
/// documentation of the entropy source and [`Standard`] for documentation of
/// distributions and type-specific generation.
///
/// # Provided implementations
///
/// The following types have provided implementations that
/// generate values with the following ranges and distributions:
///
/// * Integers (`i32`, `u32`, `isize`, `usize`, etc.): Uniformly distributed
/// over all values of the type.
/// * `char`: Uniformly distributed over all Unicode scalar values, i.e. all
/// code points in the range `0...0x10_FFFF`, except for the range
/// `0xD800...0xDFFF` (the surrogate code points). This includes
/// unassigned/reserved code points.
/// * `bool`: Generates `false` or `true`, each with probability 0.5.
/// * Floating point types (`f32` and `f64`): Uniformly distributed in the
/// half-open range `[0, 1)`. See notes below.
/// * Wrapping integers (`Wrapping&lt;T&gt;`), besides the type identical to their
/// normal integer variants.
///
/// Also supported is the generation of the following
/// compound types where all component types are supported:
///
/// * Tuples (up to 12 elements): each element is generated sequentially.
/// * Arrays (up to 32 elements): each element is generated sequentially;
/// see also [`Rng::fill`] which supports arbitrary array length for integer
/// types and tends to be faster for `u32` and smaller types.
/// * `Option&lt;T&gt;` first generates a `bool`, and if true generates and returns
/// `Some(value)` where `value: T`, otherwise returning `None`.
///
/// # Examples
///
/// ```
/// let x = rand::random::&lt;u8&gt;();
/// println!(&quot;{}&quot;, x);
///
/// let y = rand::random::&lt;f64&gt;();
/// println!(&quot;{}&quot;, y);
///
/// if rand::random() { // generates a boolean
/// println!(&quot;Better lucky than good!&quot;);
/// }
/// ```
///
/// If you&#39;re calling `random()` in a loop, caching the generator as in the
/// following example can increase performance.
///
/// ```
/// use rand::Rng;
///
/// let mut v = vec![1, 2, 3];
///
/// for x in v.iter_mut() {
/// *x = rand::random()
/// }
///
/// // can be made faster by caching thread_rng
///
/// let mut rng = rand::thread_rng();
///
/// for x in v.iter_mut() {
/// *x = rng.gen();
/// }
/// ```
///
/// [`Standard`]: distributions::Standard
</span><span class="attribute">#[cfg(all(feature = <span class="string">&quot;std&quot;</span>, feature = <span class="string">&quot;std_rng&quot;</span>))]
#[cfg_attr(doc_cfg, doc(cfg(all(feature = <span class="string">&quot;std&quot;</span>, feature = <span class="string">&quot;std_rng&quot;</span>))))]
#[inline]
</span><span class="kw">pub fn </span>random&lt;T&gt;() -&gt; T
<span class="kw">where </span>Standard: Distribution&lt;T&gt; {
thread_rng().gen()
}
<span class="attribute">#[cfg(test)]
</span><span class="kw">mod </span>test {
<span class="kw">use super</span>::<span class="kw-2">*</span>;
<span class="doccomment">/// Construct a deterministic RNG with the given seed
</span><span class="kw">pub fn </span>rng(seed: u64) -&gt; <span class="kw">impl </span>RngCore {
<span class="comment">// For tests, we want a statistically good, fast, reproducible RNG.
// PCG32 will do fine, and will be easy to embed if we ever need to.
</span><span class="kw">const </span>INC: u64 = <span class="number">11634580027462260723</span>;
rand_pcg::Pcg32::new(seed, INC)
}
<span class="attribute">#[test]
#[cfg(all(feature = <span class="string">&quot;std&quot;</span>, feature = <span class="string">&quot;std_rng&quot;</span>))]
</span><span class="kw">fn </span>test_random() {
<span class="kw">let </span>_n: usize = random();
<span class="kw">let </span>_f: f32 = random();
<span class="kw">let </span>_o: <span class="prelude-ty">Option</span>&lt;<span class="prelude-ty">Option</span>&lt;i8&gt;&gt; = random();
<span class="attribute">#[allow(clippy::type_complexity)]
</span><span class="kw">let </span>_many: (
(),
(usize, isize, <span class="prelude-ty">Option</span>&lt;(u32, (bool,))&gt;),
(u8, i8, u16, i16, u32, i32, u64, i64),
(f32, (f64, (f64,))),
) = random();
}
}
</code></pre></div>
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