| // 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. |
| |
| //! The implementations of the `Standard` distribution for other built-in types. |
| |
| use core::char; |
| use core::num::Wrapping; |
| #[cfg(feature = "alloc")] |
| use alloc::string::String; |
| |
| use crate::distributions::{Distribution, Standard, Uniform}; |
| #[cfg(feature = "alloc")] |
| use crate::distributions::DistString; |
| use crate::Rng; |
| |
| #[cfg(feature = "serde1")] |
| use serde::{Serialize, Deserialize}; |
| #[cfg(feature = "min_const_gen")] |
| use core::mem::{self, MaybeUninit}; |
| |
| |
| // ----- Sampling distributions ----- |
| |
| /// Sample a `u8`, uniformly distributed over ASCII letters and numbers: |
| /// a-z, A-Z and 0-9. |
| /// |
| /// # Example |
| /// |
| /// ``` |
| /// use rand::{Rng, thread_rng}; |
| /// use rand::distributions::Alphanumeric; |
| /// |
| /// let mut rng = thread_rng(); |
| /// let chars: String = (0..7).map(|_| rng.sample(Alphanumeric) as char).collect(); |
| /// println!("Random chars: {}", chars); |
| /// ``` |
| /// |
| /// The [`DistString`] trait provides an easier method of generating |
| /// a random `String`, and offers more efficient allocation: |
| /// ``` |
| /// use rand::distributions::{Alphanumeric, DistString}; |
| /// let string = Alphanumeric.sample_string(&mut rand::thread_rng(), 16); |
| /// println!("Random string: {}", string); |
| /// ``` |
| /// |
| /// # Passwords |
| /// |
| /// Users sometimes ask whether it is safe to use a string of random characters |
| /// as a password. In principle, all RNGs in Rand implementing `CryptoRng` are |
| /// suitable as a source of randomness for generating passwords (if they are |
| /// properly seeded), but it is more conservative to only use randomness |
| /// directly from the operating system via the `getrandom` crate, or the |
| /// corresponding bindings of a crypto library. |
| /// |
| /// When generating passwords or keys, it is important to consider the threat |
| /// model and in some cases the memorability of the password. This is out of |
| /// scope of the Rand project, and therefore we defer to the following |
| /// references: |
| /// |
| /// - [Wikipedia article on Password Strength](https://en.wikipedia.org/wiki/Password_strength) |
| /// - [Diceware for generating memorable passwords](https://en.wikipedia.org/wiki/Diceware) |
| #[derive(Debug, Clone, Copy)] |
| #[cfg_attr(feature = "serde1", derive(Serialize, Deserialize))] |
| pub struct Alphanumeric; |
| |
| |
| // ----- Implementations of distributions ----- |
| |
| impl Distribution<char> for Standard { |
| #[inline] |
| fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> char { |
| // A valid `char` is either in the interval `[0, 0xD800)` or |
| // `(0xDFFF, 0x11_0000)`. All `char`s must therefore be in |
| // `[0, 0x11_0000)` but not in the "gap" `[0xD800, 0xDFFF]` which is |
| // reserved for surrogates. This is the size of that gap. |
| const GAP_SIZE: u32 = 0xDFFF - 0xD800 + 1; |
| |
| // Uniform::new(0, 0x11_0000 - GAP_SIZE) can also be used but it |
| // seemed slower. |
| let range = Uniform::new(GAP_SIZE, 0x11_0000); |
| |
| let mut n = range.sample(rng); |
| if n <= 0xDFFF { |
| n -= GAP_SIZE; |
| } |
| unsafe { char::from_u32_unchecked(n) } |
| } |
| } |
| |
| /// Note: the `String` is potentially left with excess capacity; optionally the |
| /// user may call `string.shrink_to_fit()` afterwards. |
| #[cfg(feature = "alloc")] |
| impl DistString for Standard { |
| fn append_string<R: Rng + ?Sized>(&self, rng: &mut R, s: &mut String, len: usize) { |
| // A char is encoded with at most four bytes, thus this reservation is |
| // guaranteed to be sufficient. We do not shrink_to_fit afterwards so |
| // that repeated usage on the same `String` buffer does not reallocate. |
| s.reserve(4 * len); |
| s.extend(Distribution::<char>::sample_iter(self, rng).take(len)); |
| } |
| } |
| |
| impl Distribution<u8> for Alphanumeric { |
| fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> u8 { |
| const RANGE: u32 = 26 + 26 + 10; |
| const GEN_ASCII_STR_CHARSET: &[u8] = b"ABCDEFGHIJKLMNOPQRSTUVWXYZ\ |
| abcdefghijklmnopqrstuvwxyz\ |
| 0123456789"; |
| // We can pick from 62 characters. This is so close to a power of 2, 64, |
| // that we can do better than `Uniform`. Use a simple bitshift and |
| // rejection sampling. We do not use a bitmask, because for small RNGs |
| // the most significant bits are usually of higher quality. |
| loop { |
| let var = rng.next_u32() >> (32 - 6); |
| if var < RANGE { |
| return GEN_ASCII_STR_CHARSET[var as usize]; |
| } |
| } |
| } |
| } |
| |
| #[cfg(feature = "alloc")] |
| impl DistString for Alphanumeric { |
| fn append_string<R: Rng + ?Sized>(&self, rng: &mut R, string: &mut String, len: usize) { |
| unsafe { |
| let v = string.as_mut_vec(); |
| v.extend(self.sample_iter(rng).take(len)); |
| } |
| } |
| } |
| |
| impl Distribution<bool> for Standard { |
| #[inline] |
| fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> bool { |
| // We can compare against an arbitrary bit of an u32 to get a bool. |
| // Because the least significant bits of a lower quality RNG can have |
| // simple patterns, we compare against the most significant bit. This is |
| // easiest done using a sign test. |
| (rng.next_u32() as i32) < 0 |
| } |
| } |
| |
| macro_rules! tuple_impl { |
| // use variables to indicate the arity of the tuple |
| ($($tyvar:ident),* ) => { |
| // the trailing commas are for the 1 tuple |
| impl< $( $tyvar ),* > |
| Distribution<( $( $tyvar ),* , )> |
| for Standard |
| where $( Standard: Distribution<$tyvar> ),* |
| { |
| #[inline] |
| fn sample<R: Rng + ?Sized>(&self, _rng: &mut R) -> ( $( $tyvar ),* , ) { |
| ( |
| // use the $tyvar's to get the appropriate number of |
| // repeats (they're not actually needed) |
| $( |
| _rng.gen::<$tyvar>() |
| ),* |
| , |
| ) |
| } |
| } |
| } |
| } |
| |
| impl Distribution<()> for Standard { |
| #[allow(clippy::unused_unit)] |
| #[inline] |
| fn sample<R: Rng + ?Sized>(&self, _: &mut R) -> () { |
| () |
| } |
| } |
| tuple_impl! {A} |
| tuple_impl! {A, B} |
| tuple_impl! {A, B, C} |
| tuple_impl! {A, B, C, D} |
| tuple_impl! {A, B, C, D, E} |
| tuple_impl! {A, B, C, D, E, F} |
| tuple_impl! {A, B, C, D, E, F, G} |
| tuple_impl! {A, B, C, D, E, F, G, H} |
| tuple_impl! {A, B, C, D, E, F, G, H, I} |
| tuple_impl! {A, B, C, D, E, F, G, H, I, J} |
| tuple_impl! {A, B, C, D, E, F, G, H, I, J, K} |
| tuple_impl! {A, B, C, D, E, F, G, H, I, J, K, L} |
| |
| #[cfg(feature = "min_const_gen")] |
| #[cfg_attr(doc_cfg, doc(cfg(feature = "min_const_gen")))] |
| impl<T, const N: usize> Distribution<[T; N]> for Standard |
| where Standard: Distribution<T> |
| { |
| #[inline] |
| fn sample<R: Rng + ?Sized>(&self, _rng: &mut R) -> [T; N] { |
| let mut buff: [MaybeUninit<T>; N] = unsafe { MaybeUninit::uninit().assume_init() }; |
| |
| for elem in &mut buff { |
| *elem = MaybeUninit::new(_rng.gen()); |
| } |
| |
| unsafe { mem::transmute_copy::<_, _>(&buff) } |
| } |
| } |
| |
| #[cfg(not(feature = "min_const_gen"))] |
| macro_rules! array_impl { |
| // recursive, given at least one type parameter: |
| {$n:expr, $t:ident, $($ts:ident,)*} => { |
| array_impl!{($n - 1), $($ts,)*} |
| |
| impl<T> Distribution<[T; $n]> for Standard where Standard: Distribution<T> { |
| #[inline] |
| fn sample<R: Rng + ?Sized>(&self, _rng: &mut R) -> [T; $n] { |
| [_rng.gen::<$t>(), $(_rng.gen::<$ts>()),*] |
| } |
| } |
| }; |
| // empty case: |
| {$n:expr,} => { |
| impl<T> Distribution<[T; $n]> for Standard { |
| fn sample<R: Rng + ?Sized>(&self, _rng: &mut R) -> [T; $n] { [] } |
| } |
| }; |
| } |
| |
| #[cfg(not(feature = "min_const_gen"))] |
| array_impl! {32, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T, T,} |
| |
| impl<T> Distribution<Option<T>> for Standard |
| where Standard: Distribution<T> |
| { |
| #[inline] |
| fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Option<T> { |
| // UFCS is needed here: https://github.com/rust-lang/rust/issues/24066 |
| if rng.gen::<bool>() { |
| Some(rng.gen()) |
| } else { |
| None |
| } |
| } |
| } |
| |
| impl<T> Distribution<Wrapping<T>> for Standard |
| where Standard: Distribution<T> |
| { |
| #[inline] |
| fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> Wrapping<T> { |
| Wrapping(rng.gen()) |
| } |
| } |
| |
| |
| #[cfg(test)] |
| mod tests { |
| use super::*; |
| use crate::RngCore; |
| #[cfg(feature = "alloc")] use alloc::string::String; |
| |
| #[test] |
| fn test_misc() { |
| let rng: &mut dyn RngCore = &mut crate::test::rng(820); |
| |
| rng.sample::<char, _>(Standard); |
| rng.sample::<bool, _>(Standard); |
| } |
| |
| #[cfg(feature = "alloc")] |
| #[test] |
| fn test_chars() { |
| use core::iter; |
| let mut rng = crate::test::rng(805); |
| |
| // Test by generating a relatively large number of chars, so we also |
| // take the rejection sampling path. |
| let word: String = iter::repeat(()) |
| .map(|()| rng.gen::<char>()) |
| .take(1000) |
| .collect(); |
| assert!(!word.is_empty()); |
| } |
| |
| #[test] |
| fn test_alphanumeric() { |
| let mut rng = crate::test::rng(806); |
| |
| // Test by generating a relatively large number of chars, so we also |
| // take the rejection sampling path. |
| let mut incorrect = false; |
| for _ in 0..100 { |
| let c: char = rng.sample(Alphanumeric).into(); |
| incorrect |= !(('0'..='9').contains(&c) || |
| ('A'..='Z').contains(&c) || |
| ('a'..='z').contains(&c) ); |
| } |
| assert!(!incorrect); |
| } |
| |
| #[test] |
| fn value_stability() { |
| fn test_samples<T: Copy + core::fmt::Debug + PartialEq, D: Distribution<T>>( |
| distr: &D, zero: T, expected: &[T], |
| ) { |
| let mut rng = crate::test::rng(807); |
| let mut buf = [zero; 5]; |
| for x in &mut buf { |
| *x = rng.sample(&distr); |
| } |
| assert_eq!(&buf, expected); |
| } |
| |
| test_samples(&Standard, 'a', &[ |
| '\u{8cdac}', |
| '\u{a346a}', |
| '\u{80120}', |
| '\u{ed692}', |
| '\u{35888}', |
| ]); |
| test_samples(&Alphanumeric, 0, &[104, 109, 101, 51, 77]); |
| test_samples(&Standard, false, &[true, true, false, true, false]); |
| test_samples(&Standard, None as Option<bool>, &[ |
| Some(true), |
| None, |
| Some(false), |
| None, |
| Some(false), |
| ]); |
| test_samples(&Standard, Wrapping(0i32), &[ |
| Wrapping(-2074640887), |
| Wrapping(-1719949321), |
| Wrapping(2018088303), |
| Wrapping(-547181756), |
| Wrapping(838957336), |
| ]); |
| |
| // We test only sub-sets of tuple and array impls |
| test_samples(&Standard, (), &[(), (), (), (), ()]); |
| test_samples(&Standard, (false,), &[ |
| (true,), |
| (true,), |
| (false,), |
| (true,), |
| (false,), |
| ]); |
| test_samples(&Standard, (false, false), &[ |
| (true, true), |
| (false, true), |
| (false, false), |
| (true, false), |
| (false, false), |
| ]); |
| |
| test_samples(&Standard, [0u8; 0], &[[], [], [], [], []]); |
| test_samples(&Standard, [0u8; 3], &[ |
| [9, 247, 111], |
| [68, 24, 13], |
| [174, 19, 194], |
| [172, 69, 213], |
| [149, 207, 29], |
| ]); |
| } |
| } |