Apply rustfmt and fix Clippy warnings

.github/workflows/benches.yml

@@ -0,0 +1,23 @@
+name: Benches
+
+on:
+  pull_request:
+    paths:
+      - ".github/workflows/benches.yml"
+      - "benches/**"
+
+jobs:
+  benches:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: dtolnay/rust-toolchain@master
+        with:
+          toolchain: nightly
+          components: clippy, rustfmt
+      - name: Rustfmt
+        run: cargo fmt --all -- --check
+      - name: Clippy
+        run: cargo clippy --all --all-targets -- -D warnings
+      - name: Build
+        run: RUSTFLAGS=-Dwarnings cargo build --all-targets

.github/workflows/test.yml

@@ -72,8 +72,6 @@ jobs:
         if: ${{ matrix.variant == 'minimal_versions' }}
         run: |
           cargo generate-lockfile -Z minimal-versions
-          # Overrides for dependencies with incorrect requirements (may need periodic updating)
-          cargo update -p regex --precise 1.5.1
       - name: Maybe nightly
         if: ${{ matrix.toolchain == 'nightly' }}
         run: |

.github/workflows/workspace.yml

@@ -0,0 +1,33 @@
+name: Workspace
+
+on:
+  pull_request:
+    paths-ignore:
+      - README.md
+      - "benches/**"
+  push:
+    branches: master
+    paths-ignore:
+      - README.md
+      - "benches/**"
+
+jobs:
+  clippy:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: dtolnay/rust-toolchain@master
+        with:
+          toolchain: 1.78.0
+          components: clippy
+      - run: cargo clippy --all --all-targets -- -D warnings
+
+  rustfmt:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: dtolnay/rust-toolchain@master
+        with:
+          toolchain: stable
+          components: rustfmt
+      - run: cargo fmt --all -- --check

Cargo.toml

@@ -58,12 +58,12 @@ unbiased = []
 
 [workspace]
 members = [
-    "benches",
     "rand_core",
     "rand_distr",
     "rand_chacha",
     "rand_pcg",
 ]
+exclude = ["benches"]
 
 [dependencies]
 rand_core = { path = "rand_core", version = "=0.9.0-alpha.1", default-features = false }

benches/benches/generators.rs

@@ -50,7 +50,6 @@ gen_bytes!(gen_bytes_chacha8, ChaCha8Rng::from_os_rng());
 gen_bytes!(gen_bytes_chacha12, ChaCha12Rng::from_os_rng());
 gen_bytes!(gen_bytes_chacha20, ChaCha20Rng::from_os_rng());
 gen_bytes!(gen_bytes_std, StdRng::from_os_rng());
-#[cfg(feature = "small_rng")]
 gen_bytes!(gen_bytes_small, SmallRng::from_thread_rng());
 gen_bytes!(gen_bytes_os, UnwrapErr(OsRng));
 gen_bytes!(gen_bytes_thread, thread_rng());
@@ -81,7 +80,6 @@ gen_uint!(gen_u32_chacha8, u32, ChaCha8Rng::from_os_rng());
 gen_uint!(gen_u32_chacha12, u32, ChaCha12Rng::from_os_rng());
 gen_uint!(gen_u32_chacha20, u32, ChaCha20Rng::from_os_rng());
 gen_uint!(gen_u32_std, u32, StdRng::from_os_rng());
-#[cfg(feature = "small_rng")]
 gen_uint!(gen_u32_small, u32, SmallRng::from_thread_rng());
 gen_uint!(gen_u32_os, u32, UnwrapErr(OsRng));
 gen_uint!(gen_u32_thread, u32, thread_rng());
@@ -95,7 +93,6 @@ gen_uint!(gen_u64_chacha8, u64, ChaCha8Rng::from_os_rng());
 gen_uint!(gen_u64_chacha12, u64, ChaCha12Rng::from_os_rng());
 gen_uint!(gen_u64_chacha20, u64, ChaCha20Rng::from_os_rng());
 gen_uint!(gen_u64_std, u64, StdRng::from_os_rng());
-#[cfg(feature = "small_rng")]
 gen_uint!(gen_u64_small, u64, SmallRng::from_thread_rng());
 gen_uint!(gen_u64_os, u64, UnwrapErr(OsRng));
 gen_uint!(gen_u64_thread, u64, thread_rng());

rand_chacha/src/chacha.rs

@@ -8,8 +8,10 @@
 
 //! The ChaCha random number generator.
 
-#[cfg(not(feature = "std"))] use core;
-#[cfg(feature = "std")] use std as core;
+#[cfg(not(feature = "std"))]
+use core;
+#[cfg(feature = "std")]
+use std as core;
 
 use self::core::fmt;
 use crate::guts::ChaCha;
@@ -27,7 +29,8 @@ const BLOCK_WORDS: u8 = 16;
 #[repr(transparent)]
 pub struct Array64<T>([T; 64]);
 impl<T> Default for Array64<T>
-where T: Default
+where
+    T: Default,
 {
     #[rustfmt::skip]
     fn default() -> Self {
@@ -54,7 +57,8 @@ impl<T> AsMut<[T]> for Array64<T> {
     }
 }
 impl<T> Clone for Array64<T>
-where T: Copy + Default
+where
+    T: Copy + Default,
 {
     fn clone(&self) -> Self {
         let mut new = Self::default();
@@ -275,20 +279,25 @@ macro_rules! chacha_impl {
         #[cfg(feature = "serde1")]
         impl Serialize for $ChaChaXRng {
             fn serialize<S>(&self, s: S) -> Result<S::Ok, S::Error>
-            where S: Serializer {
+            where
+                S: Serializer,
+            {
                 $abst::$ChaChaXRng::from(self).serialize(s)
             }
         }
         #[cfg(feature = "serde1")]
         impl<'de> Deserialize<'de> for $ChaChaXRng {
             fn deserialize<D>(d: D) -> Result<Self, D::Error>
-            where D: Deserializer<'de> {
+            where
+                D: Deserializer<'de>,
+            {
                 $abst::$ChaChaXRng::deserialize(d).map(|x| Self::from(&x))
             }
         }
 
         mod $abst {
-            #[cfg(feature = "serde1")] use serde::{Deserialize, Serialize};
+            #[cfg(feature = "serde1")]
+            use serde::{Deserialize, Serialize};
 
             // The abstract state of a ChaCha stream, independent of implementation choices. The
             // comparison and serialization of this object is considered a semver-covered part of
@@ -353,7 +362,8 @@ chacha_impl!(
 mod test {
     use rand_core::{RngCore, SeedableRng};
 
-    #[cfg(feature = "serde1")] use super::{ChaCha12Rng, ChaCha20Rng, ChaCha8Rng};
+    #[cfg(feature = "serde1")]
+    use super::{ChaCha12Rng, ChaCha20Rng, ChaCha8Rng};
 
     type ChaChaRng = super::ChaCha20Rng;
 

rand_chacha/src/guts.rs

@@ -12,7 +12,9 @@
 use ppv_lite86::{dispatch, dispatch_light128};
 
 pub use ppv_lite86::Machine;
-use ppv_lite86::{vec128_storage, ArithOps, BitOps32, LaneWords4, MultiLane, StoreBytes, Vec4, Vec4Ext, Vector};
+use ppv_lite86::{
+    vec128_storage, ArithOps, BitOps32, LaneWords4, MultiLane, StoreBytes, Vec4, Vec4Ext, Vector,
+};
 
 pub(crate) const BLOCK: usize = 16;
 pub(crate) const BLOCK64: u64 = BLOCK as u64;
@@ -140,14 +142,18 @@ fn add_pos<Mach: Machine>(m: Mach, d: Mach::u32x4, i: u64) -> Mach::u32x4 {
 #[cfg(target_endian = "little")]
 fn d0123<Mach: Machine>(m: Mach, d: vec128_storage) -> Mach::u32x4x4 {
     let d0: Mach::u64x2 = m.unpack(d);
-    let incr = Mach::u64x2x4::from_lanes([m.vec([0, 0]), m.vec([1, 0]), m.vec([2, 0]), m.vec([3, 0])]);
+    let incr =
+        Mach::u64x2x4::from_lanes([m.vec([0, 0]), m.vec([1, 0]), m.vec([2, 0]), m.vec([3, 0])]);
     m.unpack((Mach::u64x2x4::from_lanes([d0, d0, d0, d0]) + incr).into())
 }
 
 #[allow(clippy::many_single_char_names)]
 #[inline(always)]
 fn refill_wide_impl<Mach: Machine>(
-    m: Mach, state: &mut ChaCha, drounds: u32, out: &mut [u32; BUFSZ],
+    m: Mach,
+    state: &mut ChaCha,
+    drounds: u32,
+    out: &mut [u32; BUFSZ],
 ) {
     let k = m.vec([0x6170_7865, 0x3320_646e, 0x7962_2d32, 0x6b20_6574]);
     let b = m.unpack(state.b);

rand_core/src/blanket_impls.rs

@@ -1,4 +1,5 @@
-#[cfg(feature = "alloc")] use alloc::boxed::Box;
+#[cfg(feature = "alloc")]
+use alloc::boxed::Box;
 
 use crate::{CryptoRng, RngCore, TryCryptoRng, TryRngCore};
 

rand_core/src/block.rs

@@ -56,7 +56,8 @@
 use crate::impls::{fill_via_u32_chunks, fill_via_u64_chunks};
 use crate::{CryptoRng, RngCore, SeedableRng, TryRngCore};
 use core::fmt;
-#[cfg(feature = "serde1")] use serde::{Deserialize, Serialize};
+#[cfg(feature = "serde1")]
+use serde::{Deserialize, Serialize};
 
 /// A trait for RNGs which do not generate random numbers individually, but in
 /// blocks (typically `[u32; N]`). This technique is commonly used by

rand_core/src/impls.rs

@@ -199,7 +199,7 @@ macro_rules! impl_try_rng_from_rng_core {
 macro_rules! impl_try_crypto_rng_from_crypto_rng {
     ($t:ty) => {
         $crate::impl_try_rng_from_rng_core!($t);
-        
+
         impl $crate::TryCryptoRng for $t {}
 
         /// Check at compile time that `$t` implements `CryptoRng`

rand_core/src/lib.rs

@@ -32,23 +32,28 @@
 #![deny(missing_docs)]
 #![deny(missing_debug_implementations)]
 #![doc(test(attr(allow(unused_variables), deny(warnings))))]
+#![allow(unexpected_cfgs)]
 #![cfg_attr(doc_cfg, feature(doc_cfg))]
 #![no_std]
 
-#[cfg(feature = "alloc")] extern crate alloc;
-#[cfg(feature = "std")] extern crate std;
+#[cfg(feature = "alloc")]
+extern crate alloc;
+#[cfg(feature = "std")]
+extern crate std;
 
 use core::fmt;
 
 mod blanket_impls;
 pub mod block;
 pub mod impls;
 pub mod le;
-#[cfg(feature = "getrandom")] mod os;
-
-#[cfg(feature = "getrandom")] pub use getrandom;
-#[cfg(feature = "getrandom")] pub use os::OsRng;
+#[cfg(feature = "getrandom")]
+mod os;
 
+#[cfg(feature = "getrandom")]
+pub use getrandom;
+#[cfg(feature = "getrandom")]
+pub use os::OsRng;
 
 /// The core of a random number generator.
 ///
@@ -213,14 +218,18 @@ pub trait TryRngCore {
 
     /// Wrap RNG with the [`UnwrapErr`] wrapper.
     fn unwrap_err(self) -> UnwrapErr<Self>
-    where Self: Sized {
+    where
+        Self: Sized,
+    {
         UnwrapErr(self)
     }
 
     /// Convert an [`RngCore`] to a [`RngReadAdapter`].
     #[cfg(feature = "std")]
     fn read_adapter(&mut self) -> RngReadAdapter<'_, Self>
-    where Self: Sized {
+    where
+        Self: Sized,
+    {
         RngReadAdapter { inner: self }
     }
 }

rand_distr/src/binomial.rs

@@ -10,11 +10,11 @@
 //! The binomial distribution.
 
 use crate::{Distribution, Uniform};
-use rand::Rng;
-use core::fmt;
 use core::cmp::Ordering;
+use core::fmt;
 #[allow(unused_imports)]
 use num_traits::Float;
+use rand::Rng;
 
 /// The binomial distribution `Binomial(n, p)`.
 ///
@@ -110,21 +110,21 @@ impl Distribution<u64> for Binomial {
         // Threshold for preferring the BINV algorithm. The paper suggests 10,
         // Ranlib uses 30, and GSL uses 14.
         const BINV_THRESHOLD: f64 = 10.;
-        
+
         // Same value as in GSL.
         // It is possible for BINV to get stuck, so we break if x > BINV_MAX_X and try again.
         // It would be safer to set BINV_MAX_X to self.n, but it is extremely unlikely to be relevant.
         // When n*p < 10, so is n*p*q which is the variance, so a result > 110 would be 100 / sqrt(10) = 31 standard deviations away.
-        const BINV_MAX_X : u64 = 110;
+        const BINV_MAX_X: u64 = 110;
 
         if (self.n as f64) * p < BINV_THRESHOLD && self.n <= (i32::MAX as u64) {
             // Use the BINV algorithm.
             let s = p / q;
             let a = ((self.n + 1) as f64) * s;
-            
+
             result = 'outer: loop {
                 let mut r = q.powi(self.n as i32);
-                let mut u: f64 = rng.gen();
+                let mut u: f64 = rng.random();
                 let mut x = 0;
 
                 while u > r {
@@ -136,7 +136,6 @@ impl Distribution<u64> for Binomial {
                     r *= a / (x as f64) - s;
                 }
                 break x;
-
             }
         } else {
             // Use the BTPE algorithm.
@@ -238,7 +237,7 @@ impl Distribution<u64> for Binomial {
                                     break;
                                 }
                             }
-                        },
+                        }
                         Ordering::Greater => {
                             let mut i = y;
                             loop {
@@ -248,8 +247,8 @@ impl Distribution<u64> for Binomial {
                                     break;
                                 }
                             }
-                        },
-                        Ordering::Equal => {},
+                        }
+                        Ordering::Equal => {}
                     }
                     if v > f {
                         continue;
@@ -366,7 +365,7 @@ mod test {
     fn binomial_distributions_can_be_compared() {
         assert_eq!(Binomial::new(1, 1.0), Binomial::new(1, 1.0));
     }
-    
+
     #[test]
     fn binomial_avoid_infinite_loop() {
         let dist = Binomial::new(16000000, 3.1444753148558566e-10).unwrap();