Make Uniform constructors return a result

- This is a breaking change.
- The new error type had to be made public, otherwise `Uniform` could
  not be extended for user-defined types by implementing
  `UniformSampler`.
- `rand_distr` was updated accordingly.
- Also forbid unsafe code for crates where none is used.

Fixes rust-random#1195, rust-random#1211.

CHANGELOG.md

@@ -8,6 +8,11 @@ A [separate changelog is kept for rand_core](rand_core/CHANGELOG.md).
 
 You may also find the [Upgrade Guide](https://rust-random.github.io/book/update.html) useful.
 
+## [0.9.0] - unreleased
+### Distributions
+- `{Uniform, UniformSampler}::{new, new_inclusive}` return a `Result` (instead of potentially panicking)
+- `Uniform` implements `TryFrom` instead of `From` for ranges
+
 ## [0.8.5] - 2021-08-20
 ### Fixes
 - Fix build on non-32/64-bit architectures (#1144)

Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "rand"
-version = "0.8.5"
+version = "0.9.0"
 authors = ["The Rand Project Developers", "The Rust Project Developers"]
 license = "MIT OR Apache-2.0"
 readme = "README.md"

examples/monte-carlo.rs

@@ -29,7 +29,7 @@
 use rand::distributions::{Distribution, Uniform};
 
 fn main() {
-    let range = Uniform::new(-1.0f64, 1.0);
+    let range = Uniform::new(-1.0f64, 1.0).unwrap();
     let mut rng = rand::thread_rng();
 
     let total = 1_000_000;

examples/monty-hall.rs

@@ -80,7 +80,7 @@ fn main() {
     let num_simulations = 10000;
 
     let mut rng = rand::thread_rng();
-    let random_door = Uniform::new(0u32, 3);
+    let random_door = Uniform::new(0u32, 3).unwrap();
 
     let (mut switch_wins, mut switch_losses) = (0, 0);
     let (mut keep_wins, mut keep_losses) = (0, 0);

rand_distr/CHANGELOG.md

@@ -7,6 +7,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ## [0.5.0] - unreleased
 - Remove unused fields from `Gamma`, `NormalInverseGaussian` and `Zipf` distributions (#1184)
   This breaks serialization compatibility with older versions.
+- Upgrade Rand
 
 ## [0.4.3] - 2021-12-30
 - Fix `no_std` build (#1208)

rand_distr/Cargo.toml

@@ -23,14 +23,14 @@ std_math = ["num-traits/std"]
 serde1 = ["serde", "rand/serde1"]
 
 [dependencies]
-rand = { path = "..", version = "0.8.0", default-features = false }
+rand = { path = "..", version = "0.9.0", default-features = false }
 num-traits = { version = "0.2", default-features = false, features = ["libm"] }
 serde = { version = "1.0.103", features = ["derive"], optional = true }
 
 [dev-dependencies]
 rand_pcg = { version = "0.3.0", path = "../rand_pcg" }
 # For inline examples
-rand = { path = "..", version = "0.8.0", default-features = false, features = ["std_rng", "std", "small_rng"] }
+rand = { path = "..", version = "0.9.0", default-features = false, features = ["std_rng", "std", "small_rng"] }
 # Histogram implementation for testing uniformity
 average = { version = "0.13", features = [ "std" ] }
 # Special functions for testing distributions

rand_distr/src/binomial.rs

@@ -163,8 +163,8 @@ impl Distribution<u64> for Binomial {
             // return value
             let mut y: i64;
 
-            let gen_u = Uniform::new(0., p4);
-            let gen_v = Uniform::new(0., 1.);
+            let gen_u = Uniform::new(0., p4).unwrap();
+            let gen_v = Uniform::new(0., 1.).unwrap();
 
             loop {
                 // Step 1: Generate `u` for selecting the region. If region 1 is

rand_distr/src/hypergeometric.rs

@@ -251,7 +251,7 @@ impl Distribution<u64> for Hypergeometric {
                 x
             },
             RejectionAcceptance { m, a, lambda_l, lambda_r, x_l, x_r, p1, p2, p3 } => {
-                let distr_region_select = Uniform::new(0.0, p3);
+                let distr_region_select = Uniform::new(0.0, p3).unwrap();
                 loop {
                     let (y, v) = loop {
                         let u = distr_region_select.sample(rng);

rand_distr/src/unit_ball.rs

@@ -31,7 +31,7 @@ pub struct UnitBall;
 impl<F: Float + SampleUniform> Distribution<[F; 3]> for UnitBall {
     #[inline]
     fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> [F; 3] {
-        let uniform = Uniform::new(F::from(-1.).unwrap(), F::from(1.).unwrap());
+        let uniform = Uniform::new(F::from(-1.).unwrap(), F::from(1.).unwrap()).unwrap();
         let mut x1;
         let mut x2;
         let mut x3;

rand_distr/src/unit_circle.rs

@@ -35,7 +35,7 @@ pub struct UnitCircle;
 impl<F: Float + SampleUniform> Distribution<[F; 2]> for UnitCircle {
     #[inline]
     fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> [F; 2] {
-        let uniform = Uniform::new(F::from(-1.).unwrap(), F::from(1.).unwrap());
+        let uniform = Uniform::new(F::from(-1.).unwrap(), F::from(1.).unwrap()).unwrap();
         let mut x1;
         let mut x2;
         let mut sum;

rand_distr/src/unit_disc.rs

@@ -30,7 +30,7 @@ pub struct UnitDisc;
 impl<F: Float + SampleUniform> Distribution<[F; 2]> for UnitDisc {
     #[inline]
     fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> [F; 2] {
-        let uniform = Uniform::new(F::from(-1.).unwrap(), F::from(1.).unwrap());
+        let uniform = Uniform::new(F::from(-1.).unwrap(), F::from(1.).unwrap()).unwrap();
         let mut x1;
         let mut x2;
         loop {

rand_distr/src/unit_sphere.rs

@@ -34,7 +34,7 @@ pub struct UnitSphere;
 impl<F: Float + SampleUniform> Distribution<[F; 3]> for UnitSphere {
     #[inline]
     fn sample<R: Rng + ?Sized>(&self, rng: &mut R) -> [F; 3] {
-        let uniform = Uniform::new(F::from(-1.).unwrap(), F::from(1.).unwrap());
+        let uniform = Uniform::new(F::from(-1.).unwrap(), F::from(1.).unwrap()).unwrap();
         loop {
             let (x1, x2) = (uniform.sample(rng), uniform.sample(rng));
             let sum = x1 * x1 + x2 * x2;

rand_distr/src/weighted_alias.rs

@@ -221,8 +221,8 @@ impl<W: AliasableWeight> WeightedAliasIndex<W> {
 
         // Prepare distributions for sampling. Creating them beforehand improves
         // sampling performance.
-        let uniform_index = Uniform::new(0, n);
-        let uniform_within_weight_sum = Uniform::new(W::ZERO, weight_sum);
+        let uniform_index = Uniform::new(0, n).unwrap();
+        let uniform_within_weight_sum = Uniform::new(W::ZERO, weight_sum).unwrap();
 
         Ok(Self {
             aliases: aliases.aliases,
@@ -458,7 +458,7 @@ mod test {
             let random_weight_distribution = Uniform::new_inclusive(
                 W::ZERO,
                 W::MAX / W::try_from_u32_lossy(NUM_WEIGHTS).unwrap(),
-            );
+            ).unwrap();
             for _ in 0..NUM_WEIGHTS {
                 weights.push(rng.sample(&random_weight_distribution));
             }

src/distributions/distribution.rs

@@ -64,7 +64,7 @@ pub trait Distribution<T> {
     ///     .collect();
     ///
     /// // Dice-rolling:
-    /// let die_range = Uniform::new_inclusive(1, 6);
+    /// let die_range = Uniform::new_inclusive(1, 6).unwrap();
     /// let mut roll_die = die_range.sample_iter(&mut rng);
     /// while roll_die.next().unwrap() != 6 {
     ///     println!("Not a 6; rolling again!");
@@ -93,7 +93,7 @@ pub trait Distribution<T> {
     ///
     /// let mut rng = thread_rng();
     ///
-    /// let die = Uniform::new_inclusive(1, 6);
+    /// let die = Uniform::new_inclusive(1, 6).unwrap();
     /// let even_number = die.map(|num| num % 2 == 0);
     /// while !even_number.sample(&mut rng) {
     ///     println!("Still odd; rolling again!");
@@ -227,7 +227,7 @@ mod tests {
 
     #[test]
     fn test_distributions_map() {
-        let dist = Uniform::new_inclusive(0, 5).map(|val| val + 15);
+        let dist = Uniform::new_inclusive(0, 5).unwrap().map(|val| val + 15);
 
         let mut rng = crate::test::rng(212);
         let val = dist.sample(&mut rng);
@@ -240,6 +240,7 @@ mod tests {
             rng: &mut R,
         ) -> impl Iterator<Item = i32> + '_ {
             Uniform::new_inclusive(1, 6)
+                .unwrap()
                 .sample_iter(rng)
                 .filter(|x| *x != 5)
                 .take(10)

src/distributions/other.rs

@@ -80,9 +80,9 @@ impl Distribution<char> for Standard {
         // 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
+        // Uniform::new(0, 0x11_0000 - GAP_SIZE) can also be used, but it
         // seemed slower.
-        let range = Uniform::new(GAP_SIZE, 0x11_0000);
+        let range = Uniform::new(GAP_SIZE, 0x11_0000).unwrap();
 
         let mut n = range.sample(rng);
         if n <= 0xDFFF {

src/distributions/slice.rs

@@ -75,7 +75,7 @@ impl<'a, T> Slice<'a, T> {
             0 => Err(EmptySlice),
             len => Ok(Self {
                 slice,
-                range: Uniform::new(0, len),
+                range: Uniform::new(0, len).unwrap(),
             }),
         }
     }