/rust/registry/src/index.crates.io-1949cf8c6b5b557f/rand-0.8.6/src/lib.rs
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1 | | // Copyright 2018 Developers of the Rand project. |
2 | | // Copyright 2013-2017 The Rust Project Developers. |
3 | | // |
4 | | // Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or |
5 | | // https://www.apache.org/licenses/LICENSE-2.0> or the MIT license |
6 | | // <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your |
7 | | // option. This file may not be copied, modified, or distributed |
8 | | // except according to those terms. |
9 | | |
10 | | //! Utilities for random number generation |
11 | | //! |
12 | | //! Rand provides utilities to generate random numbers, to convert them to |
13 | | //! useful types and distributions, and some randomness-related algorithms. |
14 | | //! |
15 | | //! # Quick Start |
16 | | //! |
17 | | //! To get you started quickly, the easiest and highest-level way to get |
18 | | //! a random value is to use [`random()`]; alternatively you can use |
19 | | //! [`thread_rng()`]. The [`Rng`] trait provides a useful API on all RNGs, while |
20 | | //! the [`distributions`] and [`seq`] modules provide further |
21 | | //! functionality on top of RNGs. |
22 | | //! |
23 | | //! ``` |
24 | | //! use rand::prelude::*; |
25 | | //! |
26 | | //! if rand::random() { // generates a boolean |
27 | | //! // Try printing a random unicode code point (probably a bad idea)! |
28 | | //! println!("char: {}", rand::random::<char>()); |
29 | | //! } |
30 | | //! |
31 | | //! let mut rng = rand::thread_rng(); |
32 | | //! let y: f64 = rng.gen(); // generates a float between 0 and 1 |
33 | | //! |
34 | | //! let mut nums: Vec<i32> = (1..100).collect(); |
35 | | //! nums.shuffle(&mut rng); |
36 | | //! ``` |
37 | | //! |
38 | | //! # The Book |
39 | | //! |
40 | | //! For the user guide and further documentation, please read |
41 | | //! [The Rust Rand Book](https://rust-random.github.io/book). |
42 | | |
43 | | #![doc( |
44 | | html_logo_url = "https://www.rust-lang.org/logos/rust-logo-128x128-blk.png", |
45 | | html_favicon_url = "https://www.rust-lang.org/favicon.ico", |
46 | | html_root_url = "https://rust-random.github.io/rand/" |
47 | | )] |
48 | | #![deny(missing_docs)] |
49 | | #![deny(missing_debug_implementations)] |
50 | | #![doc(test(attr(allow(unused_variables), deny(warnings))))] |
51 | | #![no_std] |
52 | | #![cfg_attr(feature = "nightly", feature(trusted_len))] |
53 | | #![cfg_attr(docsrs, feature(doc_cfg))] |
54 | | #![allow( |
55 | | clippy::float_cmp, |
56 | | clippy::neg_cmp_op_on_partial_ord, |
57 | | )] |
58 | | |
59 | | #[cfg(feature = "std")] extern crate std; |
60 | | #[cfg(feature = "alloc")] extern crate alloc; |
61 | | |
62 | | // Re-exports from rand_core |
63 | | pub use rand_core::{CryptoRng, Error, RngCore, SeedableRng}; |
64 | | |
65 | | // Public modules |
66 | | pub mod distributions; |
67 | | pub mod prelude; |
68 | | mod rng; |
69 | | pub mod rngs; |
70 | | pub mod seq; |
71 | | |
72 | | // Public exports |
73 | | #[cfg(all(feature = "std", feature = "std_rng"))] |
74 | | pub use crate::rngs::thread::thread_rng; |
75 | | pub use rng::{Fill, Rng}; |
76 | | |
77 | | #[cfg(all(feature = "std", feature = "std_rng"))] |
78 | | use crate::distributions::{Distribution, Standard}; |
79 | | |
80 | | /// Generates a random value using the thread-local random number generator. |
81 | | /// |
82 | | /// This is simply a shortcut for `thread_rng().gen()`. See [`thread_rng`] for |
83 | | /// documentation of the entropy source and [`Standard`] for documentation of |
84 | | /// distributions and type-specific generation. |
85 | | /// |
86 | | /// # Provided implementations |
87 | | /// |
88 | | /// The following types have provided implementations that |
89 | | /// generate values with the following ranges and distributions: |
90 | | /// |
91 | | /// * Integers (`i32`, `u32`, `isize`, `usize`, etc.): Uniformly distributed |
92 | | /// over all values of the type. |
93 | | /// * `char`: Uniformly distributed over all Unicode scalar values, i.e. all |
94 | | /// code points in the range `0...0x10_FFFF`, except for the range |
95 | | /// `0xD800...0xDFFF` (the surrogate code points). This includes |
96 | | /// unassigned/reserved code points. |
97 | | /// * `bool`: Generates `false` or `true`, each with probability 0.5. |
98 | | /// * Floating point types (`f32` and `f64`): Uniformly distributed in the |
99 | | /// half-open range `[0, 1)`. See notes below. |
100 | | /// * Wrapping integers (`Wrapping<T>`), besides the type identical to their |
101 | | /// normal integer variants. |
102 | | /// |
103 | | /// Also supported is the generation of the following |
104 | | /// compound types where all component types are supported: |
105 | | /// |
106 | | /// * Tuples (up to 12 elements): each element is generated sequentially. |
107 | | /// * Arrays (up to 32 elements): each element is generated sequentially; |
108 | | /// see also [`Rng::fill`] which supports arbitrary array length for integer |
109 | | /// types and tends to be faster for `u32` and smaller types. |
110 | | /// * `Option<T>` first generates a `bool`, and if true generates and returns |
111 | | /// `Some(value)` where `value: T`, otherwise returning `None`. |
112 | | /// |
113 | | /// # Examples |
114 | | /// |
115 | | /// ``` |
116 | | /// let x = rand::random::<u8>(); |
117 | | /// println!("{}", x); |
118 | | /// |
119 | | /// let y = rand::random::<f64>(); |
120 | | /// println!("{}", y); |
121 | | /// |
122 | | /// if rand::random() { // generates a boolean |
123 | | /// println!("Better lucky than good!"); |
124 | | /// } |
125 | | /// ``` |
126 | | /// |
127 | | /// If you're calling `random()` in a loop, caching the generator as in the |
128 | | /// following example can increase performance. |
129 | | /// |
130 | | /// ``` |
131 | | /// use rand::Rng; |
132 | | /// |
133 | | /// let mut v = vec![1, 2, 3]; |
134 | | /// |
135 | | /// for x in v.iter_mut() { |
136 | | /// *x = rand::random() |
137 | | /// } |
138 | | /// |
139 | | /// // can be made faster by caching thread_rng |
140 | | /// |
141 | | /// let mut rng = rand::thread_rng(); |
142 | | /// |
143 | | /// for x in v.iter_mut() { |
144 | | /// *x = rng.gen(); |
145 | | /// } |
146 | | /// ``` |
147 | | /// |
148 | | /// [`Standard`]: distributions::Standard |
149 | | #[cfg(all(feature = "std", feature = "std_rng"))] |
150 | | #[cfg_attr(docsrs, doc(cfg(all(feature = "std", feature = "std_rng"))))] |
151 | | #[inline] |
152 | 0 | pub fn random<T>() -> T |
153 | 0 | where Standard: Distribution<T> { |
154 | 0 | thread_rng().gen() |
155 | 0 | } |
156 | | |
157 | | #[cfg(test)] |
158 | | mod test { |
159 | | use super::*; |
160 | | |
161 | | /// Construct a deterministic RNG with the given seed |
162 | | pub fn rng(seed: u64) -> impl RngCore { |
163 | | // For tests, we want a statistically good, fast, reproducible RNG. |
164 | | // PCG32 will do fine, and will be easy to embed if we ever need to. |
165 | | const INC: u64 = 11634580027462260723; |
166 | | rand_pcg::Pcg32::new(seed, INC) |
167 | | } |
168 | | |
169 | | #[test] |
170 | | #[cfg(all(feature = "std", feature = "std_rng"))] |
171 | | fn test_random() { |
172 | | let _n: usize = random(); |
173 | | let _f: f32 = random(); |
174 | | let _o: Option<Option<i8>> = random(); |
175 | | #[allow(clippy::type_complexity)] |
176 | | let _many: ( |
177 | | (), |
178 | | (usize, isize, Option<(u32, (bool,))>), |
179 | | (u8, i8, u16, i16, u32, i32, u64, i64), |
180 | | (f32, (f64, (f64,))), |
181 | | ) = random(); |
182 | | } |
183 | | } |