Bump MSRV to 1.51.0

.github/workflows/test.yml

@@ -23,7 +23,7 @@ jobs:
         env:
           RUSTDOCFLAGS: --cfg doc_cfg
         # --all builds all crates, but with default features for other crates (okay in this case)
-        run: cargo deadlinks --ignore-fragments -- --all --features nightly,serde1,getrandom,small_rng,min_const_gen
+        run: cargo deadlinks --ignore-fragments -- --all --features nightly,serde1,getrandom,small_rng
 
   test:
     runs-on: ${{ matrix.os }}
@@ -47,7 +47,7 @@ jobs:
             # Test both windows-gnu and windows-msvc; use beta rust on one
           - os: ubuntu-latest
             target: x86_64-unknown-linux-gnu
-            toolchain: 1.36.0 # MSRV
+            toolchain: 1.51.0 # MSRV
           - os: ubuntu-latest
             deps: sudo apt-get update ; sudo apt install gcc-multilib
             target: i686-unknown-linux-gnu
@@ -77,21 +77,15 @@ jobs:
           cargo test --target ${{ matrix.target }} --all-features
           cargo test --target ${{ matrix.target }} --benches --features=nightly
           cargo test --target ${{ matrix.target }} --manifest-path rand_distr/Cargo.toml --benches
-          cargo test --target ${{ matrix.target }} --lib --tests --no-default-features --features min_const_gen
+          cargo test --target ${{ matrix.target }} --lib --tests --no-default-features
       - name: Test rand
         run: |
           cargo test --target ${{ matrix.target }} --lib --tests --no-default-features
           cargo build --target ${{ matrix.target }} --no-default-features --features alloc,getrandom,small_rng
           cargo test --target ${{ matrix.target }} --lib --tests --no-default-features --features=alloc,getrandom,small_rng
           cargo test --target ${{ matrix.target }} --examples
-      - name: Test rand (all stable features, non-MSRV)
-        if: ${{ matrix.toolchain != '1.36.0' }}
-        run: |
-          cargo test --target ${{ matrix.target }} --features=serde1,log,small_rng,min_const_gen
-      - name: Test rand (all stable features, MSRV)
-        if: ${{ matrix.toolchain == '1.36.0' }}
+      - name: Test rand (all stable features)
         run: |
-          # const generics are not stable on 1.36.0
           cargo test --target ${{ matrix.target }} --features=serde1,log,small_rng
       - name: Test rand_core
         run: |

Cargo.toml

@@ -28,7 +28,7 @@ features = ["small_rng", "serde1"]
 [features]
 # Meta-features:
 default = ["std", "std_rng"]
-nightly = [] # enables performance optimizations requiring nightly rust
+nightly = [] # some additions requiring nightly Rust
 serde1 = ["serde", "rand_core/serde1"]
 
 # Option (enabled by default): without "std" rand uses libcore; this option
@@ -50,10 +50,6 @@ std_rng = ["rand_chacha"]
 # Option: enable SmallRng
 small_rng = []
 
-# Option: for rustc ≥ 1.51, enable generating random arrays of any size
-# using min-const-generics
-min_const_gen = []
-
 [workspace]
 members = [
     "rand_core",

README.md

@@ -125,11 +125,9 @@ Optionally, the following dependencies can be enabled:
 Additionally, these features configure Rand:
 
 -   `small_rng` enables inclusion of the `SmallRng` PRNG
--   `nightly` enables some optimizations requiring nightly Rust
+-   `nightly` includes some additions requiring nightly Rust
 -   `simd_support` (experimental) enables sampling of SIMD values
     (uniformly random SIMD integers and floats), requiring nightly Rust
--   `min_const_gen` enables generating random arrays of 
-    any size using min-const-generics, requiring Rust ≥ 1.51.
 
 Note that nightly features are not stable and therefore not all library and
 compiler versions will be compatible. This is especially true of Rand's

src/distributions/mod.rs

@@ -162,11 +162,9 @@ use crate::Rng;
 /// 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;
+/// *   Arrays: each element is generated sequentially;
 ///     see also [`Rng::fill`] which supports arbitrary array length for integer
 ///     and float types and tends to be faster for `u32` and smaller types.
-///     When using `rustc` ≥ 1.51, enable the `min_const_gen` feature to support
-///     arrays larger than 32 elements.
 ///     Note that [`Rng::fill`] and `Standard`'s array support are *not* equivalent:
 ///     the former is optimised for integer types (using fewer RNG calls for
 ///     element types smaller than the RNG word size), while the latter supports

src/distributions/other.rs

@@ -20,7 +20,6 @@ use crate::Rng;
 
 #[cfg(feature = "serde1")]
 use serde::{Serialize, Deserialize};
-#[cfg(feature = "min_const_gen")]
 use core::mem::{self, MaybeUninit};
 #[cfg(feature = "simd_support")]
 use core::simd::*;
@@ -236,8 +235,6 @@ 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>
 {
@@ -253,30 +250,6 @@ where Standard: Distribution<T>
     }
 }
 
-#[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>
 {

src/rng.rs

@@ -68,11 +68,9 @@ pub trait Rng: RngCore {
     ///
     /// # Arrays and tuples
     ///
-    /// The `rng.gen()` method is able to generate arrays (up to 32 elements)
+    /// The `rng.gen()` method is able to generate arrays
     /// and tuples (up to 12 elements), so long as all element types can be
     /// generated.
-    /// When using `rustc` ≥ 1.51, enable the `min_const_gen` feature to support
-    /// arrays larger than 32 elements.
     ///
     /// For arrays of integers, especially for those with small element types
     /// (< 64 bit), it will likely be faster to instead use [`Rng::fill`].
@@ -392,8 +390,6 @@ macro_rules! impl_fill {
 impl_fill!(u16, u32, u64, usize, u128,);
 impl_fill!(i8, i16, i32, i64, isize, i128,);
 
-#[cfg_attr(doc_cfg, doc(cfg(feature = "min_const_gen")))]
-#[cfg(feature = "min_const_gen")]
 impl<T, const N: usize> Fill for [T; N]
 where [T]: Fill
 {
@@ -402,32 +398,6 @@ where [T]: Fill
     }
 }
 
-#[cfg(not(feature = "min_const_gen"))]
-macro_rules! impl_fill_arrays {
-    ($n:expr,) => {};
-    ($n:expr, $N:ident) => {
-        impl<T> Fill for [T; $n] where [T]: Fill {
-            fn try_fill<R: Rng + ?Sized>(&mut self, rng: &mut R) -> Result<(), Error> {
-                self[..].try_fill(rng)
-            }
-        }
-    };
-    ($n:expr, $N:ident, $($NN:ident,)*) => {
-        impl_fill_arrays!($n, $N);
-        impl_fill_arrays!($n - 1, $($NN,)*);
-    };
-    (!div $n:expr,) => {};
-    (!div $n:expr, $N:ident, $($NN:ident,)*) => {
-        impl_fill_arrays!($n, $N);
-        impl_fill_arrays!(!div $n / 2, $($NN,)*);
-    };
-}
-#[cfg(not(feature = "min_const_gen"))]
-#[rustfmt::skip]
-impl_fill_arrays!(32, N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,N,);
-#[cfg(not(feature = "min_const_gen"))]
-impl_fill_arrays!(!div 4096, N,N,N,N,N,N,N,);
-
 #[cfg(test)]
 mod test {
     use super::*;

src/seq/index.rs

@@ -267,9 +267,7 @@ where R: Rng + ?Sized {
 /// sometimes be useful to have the indices themselves so this is provided as
 /// an alternative.
 ///
-/// This implementation uses `O(length + amount)` space and `O(length)` time
-/// if the "nightly" feature is enabled, or `O(length)` space and
-/// `O(length + amount * log length)` time otherwise.
+/// This implementation uses `O(length + amount)` space and `O(length)` time.
 ///
 /// Panics if `amount > length`.
 #[cfg(feature = "std")]
@@ -300,9 +298,7 @@ where
 ///
 /// This implementation uses the algorithm described by Efraimidis and Spirakis
 /// in this paper: https://doi.org/10.1016/j.ipl.2005.11.003
-/// It uses `O(length + amount)` space and `O(length)` time if the
-/// "nightly" feature is enabled, or `O(length)` space and `O(length
-/// + amount * log length)` time otherwise.
+/// It uses `O(length + amount)` space and `O(length)` time.
 ///
 /// Panics if `amount > length`.
 #[cfg(feature = "std")]
@@ -347,63 +343,33 @@ where
     }
     impl<N> Eq for Element<N> {}
 
-    #[cfg(feature = "nightly")]
-    {
-        let mut candidates = Vec::with_capacity(length.as_usize());
-        let mut index = N::zero();
-        while index < length {
-            let weight = weight(index.as_usize()).into();
-            if !(weight >= 0.) {
-                return Err(WeightedError::InvalidWeight);
-            }
-
-            let key = rng.gen::<f64>().powf(1.0 / weight);
-            candidates.push(Element { index, key });
-
-            index += N::one();
+    let mut candidates = Vec::with_capacity(length.as_usize());
+    let mut index = N::zero();
+    while index < length {
+        let weight = weight(index.as_usize()).into();
+        if !(weight >= 0.) {
+            return Err(WeightedError::InvalidWeight);
         }
 
-        // Partially sort the array to find the `amount` elements with the greatest
-        // keys. Do this by using `select_nth_unstable` to put the elements with
-        // the *smallest* keys at the beginning of the list in `O(n)` time, which
-        // provides equivalent information about the elements with the *greatest* keys.
-        let (_, mid, greater)
-            = candidates.select_nth_unstable(length.as_usize() - amount.as_usize());
-
-        let mut result: Vec<N> = Vec::with_capacity(amount.as_usize());
-        result.push(mid.index);
-        for element in greater {
-            result.push(element.index);
-        }
-        Ok(IndexVec::from(result))
-    }
-
-    #[cfg(not(feature = "nightly"))]
-    {
-        use alloc::collections::BinaryHeap;
+        let key = rng.gen::<f64>().powf(1.0 / weight);
+        candidates.push(Element { index, key });
 
-        // Partially sort the array such that the `amount` elements with the largest
-        // keys are first using a binary max heap.
-        let mut candidates = BinaryHeap::with_capacity(length.as_usize());
-        let mut index = N::zero();
-        while index < length {
-            let weight = weight(index.as_usize()).into();
-            if !(weight >= 0.) {
-                return Err(WeightedError::InvalidWeight);
-            }
+        index += N::one();
+    }
 
-            let key = rng.gen::<f64>().powf(1.0 / weight);
-            candidates.push(Element { index, key });
+    // Partially sort the array to find the `amount` elements with the greatest
+    // keys. Do this by using `select_nth_unstable` to put the elements with
+    // the *smallest* keys at the beginning of the list in `O(n)` time, which
+    // provides equivalent information about the elements with the *greatest* keys.
+    let (_, mid, greater)
+        = candidates.select_nth_unstable(length.as_usize() - amount.as_usize());
 
-            index += N::one();
-        }
-
-        let mut result: Vec<N> = Vec::with_capacity(amount.as_usize());
-        while result.len() < amount.as_usize() {
-            result.push(candidates.pop().unwrap().index);
-        }
-        Ok(IndexVec::from(result))
+    let mut result: Vec<N> = Vec::with_capacity(amount.as_usize());
+    result.push(mid.index);
+    for element in greater {
+        result.push(element.index);
     }
+    Ok(IndexVec::from(result))
 }
 
 /// Randomly sample exactly `amount` indices from `0..length`, using Floyd's