Vulnerabilities | |||||
---|---|---|---|---|---|
Version | Suggest | Low | Medium | High | Critical |
2.3.0 | 0 | 0 | 0 | 0 | 0 |
2.2.0 | 0 | 0 | 0 | 0 | 0 |
2.1.1 | 0 | 0 | 0 | 0 | 0 |
2.1.0 | 0 | 0 | 0 | 0 | 0 |
2.0.2 | 0 | 0 | 0 | 0 | 0 |
2.0.1 | 0 | 0 | 0 | 0 | 0 |
2.0.0 | 0 | 0 | 0 | 0 | 0 |
1.9.0 | 0 | 0 | 0 | 0 | 0 |
1.8.0 | 0 | 0 | 0 | 0 | 0 |
1.7.0 | 0 | 0 | 0 | 0 | 0 |
1.6.0 | 0 | 0 | 0 | 0 | 0 |
1.5.0 | 0 | 0 | 0 | 0 | 0 |
1.4.1 | 0 | 0 | 0 | 0 | 0 |
1.4.0 | 0 | 0 | 0 | 0 | 0 |
1.3.5 | 0 | 0 | 0 | 0 | 0 |
1.3.4 | 0 | 0 | 0 | 0 | 0 |
1.3.3 | 0 | 0 | 0 | 0 | 0 |
1.3.2 | 0 | 0 | 0 | 0 | 0 |
1.3.1 | 0 | 0 | 0 | 0 | 0 |
1.3.0 | 0 | 0 | 0 | 0 | 0 |
1.2.4 | 0 | 0 | 0 | 0 | 0 |
1.2.3 | 0 | 0 | 0 | 0 | 0 |
1.2.2 | 0 | 0 | 0 | 0 | 0 |
1.2.1 | 0 | 0 | 0 | 0 | 0 |
1.2.0 | 0 | 0 | 0 | 0 | 0 |
1.1.0 | 0 | 0 | 0 | 0 | 0 |
1.0.0 | 0 | 0 | 0 | 0 | 0 |
2.3.0 - This version may not be safe as it has not been updated for a long time. Find out if your coding project uses this component and get notified of any reported security vulnerabilities with Meterian-X Open Source Security Platform
Maintain your licence declarations and avoid unwanted licences to protect your IP the way you intended.
Apache-2.0 - Apache License 2.0A simple and fast random number generator.
The implementation uses Wyrand, a simple and fast generator but not cryptographically secure.
Flip a coin:
if fastrand::bool() {
println!("heads");
} else {
println!("tails");
}
Generate a random i32
:
let num = fastrand::i32(..);
Choose a random element in an array:
let v = vec![1, 2, 3, 4, 5];
let i = fastrand::usize(..v.len());
let elem = v[i];
Sample values from an array with O(n)
complexity (n
is the length of array):
fastrand::choose_multiple([1, 4, 5], 2);
fastrand::choose_multiple(0..20, 12);
Shuffle an array:
let mut v = vec![1, 2, 3, 4, 5];
fastrand::shuffle(&mut v);
Generate a random Vec
or String
:
use std::iter::repeat_with;
let v: Vec<i32> = repeat_with(|| fastrand::i32(..)).take(10).collect();
let s: String = repeat_with(fastrand::alphanumeric).take(10).collect();
To get reproducible results on every run, initialize the generator with a seed:
// Pick an arbitrary number as seed.
fastrand::seed(7);
// Now this prints the same number on every run:
println!("{}", fastrand::u32(..));
To be more efficient, create a new Rng
instance instead of using the thread-local
generator:
use std::iter::repeat_with;
let rng = fastrand::Rng::new();
let mut bytes: Vec<u8> = repeat_with(|| rng.u8(..)).take(10_000).collect();
This crate aims to expose a core set of useful randomness primitives. For more niche algorithms, consider using the fastrand-contrib
crate alongside this one.
std
(enabled by default): Enables the std
library. This is required for the global
generator and global entropy. Without this feature, [Rng
] can only be instantiated using
the with_seed
method.js
: Assumes that WebAssembly targets are being run in a JavaScript environment.Licensed under either of
at your option.
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.