Remove vendored dependencies

While it appears that by now we actually can get successful builds
without Cargo insisting on Internet access by virtue of using the
--frozen flag, maintaining vendored dependencies is somewhat of a pain
point. This state will also get worse with upcoming changes that replace
argparse in favor of structopt and pull in a slew of new dependencies by
doing so. Then there is also the repository structure aspect, which is
non-standard due to the way we vendor dependencies and a potential
source of confusion.
In order to fix these problems, this change removes all the vendored
dependencies we have.

Delete subrepo argparse/:argparse
Delete subrepo base32/:base32
Delete subrepo cc/:cc
Delete subrepo cfg-if/:cfg-if
Delete subrepo getrandom/:getrandom
Delete subrepo lazy-static/:lazy-static
Delete subrepo libc/:libc
Delete subrepo nitrokey-sys/:nitrokey-sys
Delete subrepo nitrokey/:nitrokey
Delete subrepo rand/:rand

1 files changed, 0 insertions, 720 deletions

diff --git a/rand/src/lib.rs b/rand/src/lib.rs
deleted file mode 100644
index b4167c3..0000000
--- a/rand/src/lib.rs
+++ /dev/null
@@ -1,720 +0,0 @@
-// Copyright 2018 Developers of the Rand project.
-// Copyright 2013-2017 The Rust Project Developers.
-//
-// 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.
-
-//! Utilities for random number generation
-//!
-//! Rand provides utilities to generate random numbers, to convert them to
-//! useful types and distributions, and some randomness-related algorithms.
-//!
-//! # Quick Start
-//!
-//! To get you started quickly, the easiest and highest-level way to get
-//! a random value is to use [`random()`]; alternatively you can use
-//! [`thread_rng()`]. The [`Rng`] trait provides a useful API on all RNGs, while
-//! the [`distributions`] and [`seq`] modules provide further
-//! functionality on top of RNGs.
-//!
-//! ```
-//! use rand::prelude::*;
-//!
-//! if rand::random() { // generates a boolean
-//!     // Try printing a random unicode code point (probably a bad idea)!
-//!     println!("char: {}", rand::random::<char>());
-//! }
-//!
-//! let mut rng = rand::thread_rng();
-//! let y: f64 = rng.gen(); // generates a float between 0 and 1
-//!
-//! let mut nums: Vec<i32> = (1..100).collect();
-//! nums.shuffle(&mut rng);
-//! ```
-//!
-//! # The Book
-//!
-//! For the user guide and futher documentation, please read
-//! [The Rust Rand Book](https://rust-random.github.io/book).
-
-
-#![doc(html_logo_url = "https://www.rust-lang.org/logos/rust-logo-128x128-blk.png",
-       html_favicon_url = "https://www.rust-lang.org/favicon.ico",
-       html_root_url = "https://rust-random.github.io/rand/")]
-
-#![deny(missing_docs)]
-#![deny(missing_debug_implementations)]
-#![doc(test(attr(allow(unused_variables), deny(warnings))))]
-
-#![cfg_attr(not(feature="std"), no_std)]
-#![cfg_attr(all(feature="simd_support", feature="nightly"), feature(stdsimd))]
-
-#![allow(clippy::excessive_precision, clippy::unreadable_literal, clippy::float_cmp)]
-
-#[cfg(all(feature="alloc", not(feature="std")))]
-extern crate alloc;
-
-#[cfg(feature = "getrandom")]
-use getrandom_package as getrandom;
-
-#[allow(unused)]
-macro_rules! trace { ($($x:tt)*) => (
-    #[cfg(feature = "log")] {
-        log::trace!($($x)*)
-    }
-) }
-#[allow(unused)]
-macro_rules! debug { ($($x:tt)*) => (
-    #[cfg(feature = "log")] {
-        log::debug!($($x)*)
-    }
-) }
-#[allow(unused)]
-macro_rules! info { ($($x:tt)*) => (
-    #[cfg(feature = "log")] {
-        log::info!($($x)*)
-    }
-) }
-#[allow(unused)]
-macro_rules! warn { ($($x:tt)*) => (
-    #[cfg(feature = "log")] {
-        log::warn!($($x)*)
-    }
-) }
-#[allow(unused)]
-macro_rules! error { ($($x:tt)*) => (
-    #[cfg(feature = "log")] {
-        log::error!($($x)*)
-    }
-) }
-
-// Re-exports from rand_core
-pub use rand_core::{RngCore, CryptoRng, SeedableRng, Error};
-
-// Public exports
-#[cfg(feature="std")] pub use crate::rngs::thread::thread_rng;
-
-// Public modules
-pub mod distributions;
-pub mod prelude;
-pub mod rngs;
-pub mod seq;
-
-
-use core::{mem, slice};
-use core::num::Wrapping;
-use crate::distributions::{Distribution, Standard};
-use crate::distributions::uniform::{SampleUniform, UniformSampler, SampleBorrow};
-
-/// An automatically-implemented extension trait on [`RngCore`] providing high-level
-/// generic methods for sampling values and other convenience methods.
-///
-/// This is the primary trait to use when generating random values.
-///
-/// # Generic usage
-///
-/// The basic pattern is `fn foo<R: Rng + ?Sized>(rng: &mut R)`. Some
-/// things are worth noting here:
-///
-/// - Since `Rng: RngCore` and every `RngCore` implements `Rng`, it makes no
-///   difference whether we use `R: Rng` or `R: RngCore`.
-/// - The `+ ?Sized` un-bounding allows functions to be called directly on
-///   type-erased references; i.e. `foo(r)` where `r: &mut RngCore`. Without
-///   this it would be necessary to write `foo(&mut r)`.
-///
-/// An alternative pattern is possible: `fn foo<R: Rng>(rng: R)`. This has some
-/// trade-offs. It allows the argument to be consumed directly without a `&mut`
-/// (which is how `from_rng(thread_rng())` works); also it still works directly
-/// on references (including type-erased references). Unfortunately within the
-/// function `foo` it is not known whether `rng` is a reference type or not,
-/// hence many uses of `rng` require an extra reference, either explicitly
-/// (`distr.sample(&mut rng)`) or implicitly (`rng.gen()`); one may hope the
-/// optimiser can remove redundant references later.
-///
-/// Example:
-///
-/// ```
-/// # use rand::thread_rng;
-/// use rand::Rng;
-///
-/// fn foo<R: Rng + ?Sized>(rng: &mut R) -> f32 {
-///     rng.gen()
-/// }
-///
-/// # let v = foo(&mut thread_rng());
-/// ```
-pub trait Rng: RngCore {
-    /// Return a random value supporting the [`Standard`] distribution.
-    ///
-    /// # Example
-    ///
-    /// ```
-    /// use rand::{thread_rng, Rng};
-    ///
-    /// let mut rng = thread_rng();
-    /// let x: u32 = rng.gen();
-    /// println!("{}", x);
-    /// println!("{:?}", rng.gen::<(f64, bool)>());
-    /// ```
-    ///
-    /// # Arrays and tuples
-    ///
-    /// The `rng.gen()` method is able to generate arrays (up to 32 elements)
-    /// and tuples (up to 12 elements), so long as all element types can be
-    /// generated.
-    ///
-    /// For arrays of integers, especially for those with small element types
-    /// (< 64 bit), it will likely be faster to instead use [`Rng::fill`].
-    ///
-    /// ```
-    /// use rand::{thread_rng, Rng};
-    ///
-    /// let mut rng = thread_rng();
-    /// let tuple: (u8, i32, char) = rng.gen(); // arbitrary tuple support
-    ///
-    /// let arr1: [f32; 32] = rng.gen();        // array construction
-    /// let mut arr2 = [0u8; 128];
-    /// rng.fill(&mut arr2);                    // array fill
-    /// ```
-    ///
-    /// [`Standard`]: distributions::Standard
-    #[inline]
-    fn gen<T>(&mut self) -> T
-    where Standard: Distribution<T> {
-        Standard.sample(self)
-    }
-
-    /// Generate a random value in the range [`low`, `high`), i.e. inclusive of
-    /// `low` and exclusive of `high`.
-    ///
-    /// This function is optimised for the case that only a single sample is
-    /// made from the given range. See also the [`Uniform`] distribution
-    /// type which may be faster if sampling from the same range repeatedly.
-    ///
-    /// # Panics
-    ///
-    /// Panics if `low >= high`.
-    ///
-    /// # Example
-    ///
-    /// ```
-    /// use rand::{thread_rng, Rng};
-    ///
-    /// let mut rng = thread_rng();
-    /// let n: u32 = rng.gen_range(0, 10);
-    /// println!("{}", n);
-    /// let m: f64 = rng.gen_range(-40.0f64, 1.3e5f64);
-    /// println!("{}", m);
-    /// ```
-    ///
-    /// [`Uniform`]: distributions::uniform::Uniform
-    fn gen_range<T: SampleUniform, B1, B2>(&mut self, low: B1, high: B2) -> T
-    where
-        B1: SampleBorrow<T> + Sized,
-        B2: SampleBorrow<T> + Sized,
-    {
-        T::Sampler::sample_single(low, high, self)
-    }
-
-    /// Sample a new value, using the given distribution.
-    ///
-    /// ### Example
-    ///
-    /// ```
-    /// use rand::{thread_rng, Rng};
-    /// use rand::distributions::Uniform;
-    ///
-    /// let mut rng = thread_rng();
-    /// let x = rng.sample(Uniform::new(10u32, 15));
-    /// // Type annotation requires two types, the type and distribution; the
-    /// // distribution can be inferred.
-    /// let y = rng.sample::<u16, _>(Uniform::new(10, 15));
-    /// ```
-    fn sample<T, D: Distribution<T>>(&mut self, distr: D) -> T {
-        distr.sample(self)
-    }
-
-    /// Create an iterator that generates values using the given distribution.
-    ///
-    /// Note that this function takes its arguments by value. This works since
-    /// `(&mut R): Rng where R: Rng` and
-    /// `(&D): Distribution where D: Distribution`,
-    /// however borrowing is not automatic hence `rng.sample_iter(...)` may
-    /// need to be replaced with `(&mut rng).sample_iter(...)`.
-    ///
-    /// # Example
-    ///
-    /// ```
-    /// use rand::{thread_rng, Rng};
-    /// use rand::distributions::{Alphanumeric, Uniform, Standard};
-    ///
-    /// let rng = thread_rng();
-    ///
-    /// // Vec of 16 x f32:
-    /// let v: Vec<f32> = rng.sample_iter(Standard).take(16).collect();
-    ///
-    /// // String:
-    /// let s: String = rng.sample_iter(Alphanumeric).take(7).collect();
-    ///
-    /// // Combined values
-    /// println!("{:?}", rng.sample_iter(Standard).take(5)
-    ///                              .collect::<Vec<(f64, bool)>>());
-    ///
-    /// // Dice-rolling:
-    /// let die_range = Uniform::new_inclusive(1, 6);
-    /// let mut roll_die = rng.sample_iter(die_range);
-    /// while roll_die.next().unwrap() != 6 {
-    ///     println!("Not a 6; rolling again!");
-    /// }
-    /// ```
-    fn sample_iter<T, D>(self, distr: D) -> distributions::DistIter<D, Self, T>
-    where D: Distribution<T>, Self: Sized {
-        distr.sample_iter(self)
-    }
-
-    /// Fill `dest` entirely with random bytes (uniform value distribution),
-    /// where `dest` is any type supporting [`AsByteSliceMut`], namely slices
-    /// and arrays over primitive integer types (`i8`, `i16`, `u32`, etc.).
-    ///
-    /// On big-endian platforms this performs byte-swapping to ensure
-    /// portability of results from reproducible generators.
-    ///
-    /// This uses [`fill_bytes`] internally which may handle some RNG errors
-    /// implicitly (e.g. waiting if the OS generator is not ready), but panics
-    /// on other errors. See also [`try_fill`] which returns errors.
-    ///
-    /// # Example
-    ///
-    /// ```
-    /// use rand::{thread_rng, Rng};
-    ///
-    /// let mut arr = [0i8; 20];
-    /// thread_rng().fill(&mut arr[..]);
-    /// ```
-    ///
-    /// [`fill_bytes`]: RngCore::fill_bytes
-    /// [`try_fill`]: Rng::try_fill
-    fn fill<T: AsByteSliceMut + ?Sized>(&mut self, dest: &mut T) {
-        self.fill_bytes(dest.as_byte_slice_mut());
-        dest.to_le();
-    }
-
-    /// Fill `dest` entirely with random bytes (uniform value distribution),
-    /// where `dest` is any type supporting [`AsByteSliceMut`], namely slices
-    /// and arrays over primitive integer types (`i8`, `i16`, `u32`, etc.).
-    ///
-    /// On big-endian platforms this performs byte-swapping to ensure
-    /// portability of results from reproducible generators.
-    ///
-    /// This is identical to [`fill`] except that it uses [`try_fill_bytes`]
-    /// internally and forwards RNG errors.
-    ///
-    /// # Example
-    ///
-    /// ```
-    /// # use rand::Error;
-    /// use rand::{thread_rng, Rng};
-    ///
-    /// # fn try_inner() -> Result<(), Error> {
-    /// let mut arr = [0u64; 4];
-    /// thread_rng().try_fill(&mut arr[..])?;
-    /// # Ok(())
-    /// # }
-    ///
-    /// # try_inner().unwrap()
-    /// ```
-    ///
-    /// [`try_fill_bytes`]: RngCore::try_fill_bytes
-    /// [`fill`]: Rng::fill
-    fn try_fill<T: AsByteSliceMut + ?Sized>(&mut self, dest: &mut T) -> Result<(), Error> {
-        self.try_fill_bytes(dest.as_byte_slice_mut())?;
-        dest.to_le();
-        Ok(())
-    }
-
-    /// Return a bool with a probability `p` of being true.
-    ///
-    /// See also the [`Bernoulli`] distribution, which may be faster if
-    /// sampling from the same probability repeatedly.
-    ///
-    /// # Example
-    ///
-    /// ```
-    /// use rand::{thread_rng, Rng};
-    ///
-    /// let mut rng = thread_rng();
-    /// println!("{}", rng.gen_bool(1.0 / 3.0));
-    /// ```
-    ///
-    /// # Panics
-    ///
-    /// If `p < 0` or `p > 1`.
-    ///
-    /// [`Bernoulli`]: distributions::bernoulli::Bernoulli
-    #[inline]
-    fn gen_bool(&mut self, p: f64) -> bool {
-        let d = distributions::Bernoulli::new(p).unwrap();
-        self.sample(d)
-    }
-
-    /// Return a bool with a probability of `numerator/denominator` of being
-    /// true. I.e. `gen_ratio(2, 3)` has chance of 2 in 3, or about 67%, of
-    /// returning true. If `numerator == denominator`, then the returned value
-    /// is guaranteed to be `true`. If `numerator == 0`, then the returned
-    /// value is guaranteed to be `false`.
-    ///
-    /// See also the [`Bernoulli`] distribution, which may be faster if
-    /// sampling from the same `numerator` and `denominator` repeatedly.
-    ///
-    /// # Panics
-    ///
-    /// If `denominator == 0` or `numerator > denominator`.
-    ///
-    /// # Example
-    ///
-    /// ```
-    /// use rand::{thread_rng, Rng};
-    ///
-    /// let mut rng = thread_rng();
-    /// println!("{}", rng.gen_ratio(2, 3));
-    /// ```
-    ///
-    /// [`Bernoulli`]: distributions::bernoulli::Bernoulli
-    #[inline]
-    fn gen_ratio(&mut self, numerator: u32, denominator: u32) -> bool {
-        let d = distributions::Bernoulli::from_ratio(numerator, denominator).unwrap();
-        self.sample(d)
-    }
-}
-
-impl<R: RngCore + ?Sized> Rng for R {}
-
-/// Trait for casting types to byte slices
-///
-/// This is used by the [`Rng::fill`] and [`Rng::try_fill`] methods.
-pub trait AsByteSliceMut {
-    /// Return a mutable reference to self as a byte slice
-    fn as_byte_slice_mut(&mut self) -> &mut [u8];
-
-    /// Call `to_le` on each element (i.e. byte-swap on Big Endian platforms).
-    fn to_le(&mut self);
-}
-
-impl AsByteSliceMut for [u8] {
-    fn as_byte_slice_mut(&mut self) -> &mut [u8] {
-        self
-    }
-
-    fn to_le(&mut self) {}
-}
-
-macro_rules! impl_as_byte_slice {
-    () => {};
-    ($t:ty) => {
-        impl AsByteSliceMut for [$t] {
-            fn as_byte_slice_mut(&mut self) -> &mut [u8] {
-                if self.len() == 0 {
-                    unsafe {
-                        // must not use null pointer
-                        slice::from_raw_parts_mut(0x1 as *mut u8, 0)
-                    }
-                } else {
-                    unsafe {
-                        slice::from_raw_parts_mut(self.as_mut_ptr()
-                            as *mut u8,
-                            self.len() * mem::size_of::<$t>()
-                        )
-                    }
-                }
-            }
-
-            fn to_le(&mut self) {
-                for x in self {
-                    *x = x.to_le();
-                }
-            }
-        }
-
-        impl AsByteSliceMut for [Wrapping<$t>] {
-            fn as_byte_slice_mut(&mut self) -> &mut [u8] {
-                if self.len() == 0 {
-                    unsafe {
-                        // must not use null pointer
-                        slice::from_raw_parts_mut(0x1 as *mut u8, 0)
-                    }
-                } else {
-                    unsafe {
-                        slice::from_raw_parts_mut(self.as_mut_ptr()
-                            as *mut u8,
-                            self.len() * mem::size_of::<$t>()
-                        )
-                    }
-                }
-            }
-
-            fn to_le(&mut self) {
-                for x in self {
-                    *x = Wrapping(x.0.to_le());
-                }
-            }
-        }
-    };
-    ($t:ty, $($tt:ty,)*) => {
-        impl_as_byte_slice!($t);
-        // TODO: this could replace above impl once Rust #32463 is fixed
-        // impl_as_byte_slice!(Wrapping<$t>);
-        impl_as_byte_slice!($($tt,)*);
-    }
-}
-
-impl_as_byte_slice!(u16, u32, u64, usize,);
-#[cfg(not(target_os = "emscripten"))] impl_as_byte_slice!(u128);
-impl_as_byte_slice!(i8, i16, i32, i64, isize,);
-#[cfg(not(target_os = "emscripten"))] impl_as_byte_slice!(i128);
-
-macro_rules! impl_as_byte_slice_arrays {
-    ($n:expr,) => {};
-    ($n:expr, $N:ident) => {
-        impl<T> AsByteSliceMut for [T; $n] where [T]: AsByteSliceMut {
-            fn as_byte_slice_mut(&mut self) -> &mut [u8] {
-                self[..].as_byte_slice_mut()
-            }
-
-            fn to_le(&mut self) {
-                self[..].to_le()
-            }
-        }
-    };
-    ($n:expr, $N:ident, $($NN:ident,)*) => {
-        impl_as_byte_slice_arrays!($n, $N);
-        impl_as_byte_slice_arrays!($n - 1, $($NN,)*);
-    };
-    (!div $n:expr,) => {};
-    (!div $n:expr, $N:ident, $($NN:ident,)*) => {
-        impl_as_byte_slice_arrays!($n, $N);
-        impl_as_byte_slice_arrays!(!div $n / 2, $($NN,)*);
-    };
-}
-impl_as_byte_slice_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,);
-impl_as_byte_slice_arrays!(!div 4096, N,N,N,N,N,N,N,);
-
-/// Generates a random value using the thread-local random number generator.
-///
-/// This is simply a shortcut for `thread_rng().gen()`. See [`thread_rng`] for
-/// documentation of the entropy source and [`Standard`] for documentation of
-/// distributions and type-specific generation.
-///
-/// # Examples
-///
-/// ```
-/// let x = rand::random::<u8>();
-/// println!("{}", x);
-///
-/// let y = rand::random::<f64>();
-/// println!("{}", y);
-///
-/// if rand::random() { // generates a boolean
-///     println!("Better lucky than good!");
-/// }
-/// ```
-///
-/// If you're calling `random()` in a loop, caching the generator as in the
-/// following example can increase performance.
-///
-/// ```
-/// use rand::Rng;
-///
-/// let mut v = vec![1, 2, 3];
-///
-/// for x in v.iter_mut() {
-///     *x = rand::random()
-/// }
-///
-/// // can be made faster by caching thread_rng
-///
-/// let mut rng = rand::thread_rng();
-///
-/// for x in v.iter_mut() {
-///     *x = rng.gen();
-/// }
-/// ```
-///
-/// [`Standard`]: distributions::Standard
-#[cfg(feature="std")]
-#[inline]
-pub fn random<T>() -> T
-where Standard: Distribution<T> {
-    thread_rng().gen()
-}
-
-#[cfg(test)]
-mod test {
-    use crate::rngs::mock::StepRng;
-    use super::*;
-    #[cfg(all(not(feature="std"), feature="alloc"))] use alloc::boxed::Box;
-
-    /// Construct a deterministic RNG with the given seed
-    pub fn rng(seed: u64) -> impl RngCore {
-        // For tests, we want a statistically good, fast, reproducible RNG.
-        // PCG32 will do fine, and will be easy to embed if we ever need to.
-        const INC: u64 = 11634580027462260723;
-        rand_pcg::Pcg32::new(seed, INC)
-    }
-
-    #[test]
-    fn test_fill_bytes_default() {
-        let mut r = StepRng::new(0x11_22_33_44_55_66_77_88, 0);
-
-        // check every remainder mod 8, both in small and big vectors.
-        let lengths = [0, 1, 2, 3, 4, 5, 6, 7,
-                       80, 81, 82, 83, 84, 85, 86, 87];
-        for &n in lengths.iter() {
-            let mut buffer = [0u8; 87];
-            let v = &mut buffer[0..n];
-            r.fill_bytes(v);
-
-            // use this to get nicer error messages.
-            for (i, &byte) in v.iter().enumerate() {
-                if byte == 0 {
-                    panic!("byte {} of {} is zero", i, n)
-                }
-            }
-        }
-    }
-
-    #[test]
-    fn test_fill() {
-        let x = 9041086907909331047;    // a random u64
-        let mut rng = StepRng::new(x, 0);
-
-        // Convert to byte sequence and back to u64; byte-swap twice if BE.
-        let mut array = [0u64; 2];
-        rng.fill(&mut array[..]);
-        assert_eq!(array, [x, x]);
-        assert_eq!(rng.next_u64(), x);
-
-        // Convert to bytes then u32 in LE order
-        let mut array = [0u32; 2];
-        rng.fill(&mut array[..]);
-        assert_eq!(array, [x as u32, (x >> 32) as u32]);
-        assert_eq!(rng.next_u32(), x as u32);
-
-        // Check equivalence using wrapped arrays
-        let mut warray = [Wrapping(0u32); 2];
-        rng.fill(&mut warray[..]);
-        assert_eq!(array[0], warray[0].0);
-        assert_eq!(array[1], warray[1].0);
-    }
-
-    #[test]
-    fn test_fill_empty() {
-        let mut array = [0u32; 0];
-        let mut rng = StepRng::new(0, 1);
-        rng.fill(&mut array);
-        rng.fill(&mut array[..]);
-    }
-
-    #[test]
-    fn test_gen_range() {
-        let mut r = rng(101);
-        for _ in 0..1000 {
-            let a = r.gen_range(-4711, 17);
-            assert!(a >= -4711 && a < 17);
-            let a = r.gen_range(-3i8, 42);
-            assert!(a >= -3i8 && a < 42i8);
-            let a = r.gen_range(&10u16, 99);
-            assert!(a >= 10u16 && a < 99u16);
-            let a = r.gen_range(-100i32, &2000);
-            assert!(a >= -100i32 && a < 2000i32);
-            let a = r.gen_range(&12u32, &24u32);
-            assert!(a >= 12u32 && a < 24u32);
-
-            assert_eq!(r.gen_range(0u32, 1), 0u32);
-            assert_eq!(r.gen_range(-12i64, -11), -12i64);
-            assert_eq!(r.gen_range(3_000_000, 3_000_001), 3_000_000);
-        }
-    }
-
-    #[test]
-    #[should_panic]
-    fn test_gen_range_panic_int() {
-        let mut r = rng(102);
-        r.gen_range(5, -2);
-    }
-
-    #[test]
-    #[should_panic]
-    fn test_gen_range_panic_usize() {
-        let mut r = rng(103);
-        r.gen_range(5, 2);
-    }
-
-    #[test]
-    fn test_gen_bool() {
-        let mut r = rng(105);
-        for _ in 0..5 {
-            assert_eq!(r.gen_bool(0.0), false);
-            assert_eq!(r.gen_bool(1.0), true);
-        }
-    }
-
-    #[test]
-    fn test_rng_trait_object() {
-        use crate::distributions::{Distribution, Standard};
-        let mut rng = rng(109);
-        let mut r = &mut rng as &mut dyn RngCore;
-        r.next_u32();
-        r.gen::<i32>();
-        assert_eq!(r.gen_range(0, 1), 0);
-        let _c: u8 = Standard.sample(&mut r);
-    }
-
-    #[test]
-    #[cfg(feature="alloc")]
-    fn test_rng_boxed_trait() {
-        use crate::distributions::{Distribution, Standard};
-        let rng = rng(110);
-        let mut r = Box::new(rng) as Box<dyn RngCore>;
-        r.next_u32();
-        r.gen::<i32>();
-        assert_eq!(r.gen_range(0, 1), 0);
-        let _c: u8 = Standard.sample(&mut r);
-    }
-
-    #[test]
-    #[cfg(feature="std")]
-    fn test_random() {
-        // not sure how to test this aside from just getting some values
-        let _n : usize = random();
-        let _f : f32 = random();
-        let _o : Option<Option<i8>> = random();
-        let _many : ((),
-                     (usize,
-                      isize,
-                      Option<(u32, (bool,))>),
-                     (u8, i8, u16, i16, u32, i32, u64, i64),
-                     (f32, (f64, (f64,)))) = random();
-    }
-
-    #[test]
-    #[cfg(not(miri))] // Miri is too slow
-    fn test_gen_ratio_average() {
-        const NUM: u32 = 3;
-        const DENOM: u32 = 10;
-        const N: u32 = 100_000;
-
-        let mut sum: u32 = 0;
-        let mut rng = rng(111);
-        for _ in 0..N {
-            if rng.gen_ratio(NUM, DENOM) {
-                sum += 1;
-            }
-        }
-        // Have Binomial(N, NUM/DENOM) distribution
-        let expected = (NUM * N) / DENOM;   // exact integer
-        assert!(((sum - expected) as i32).abs() < 500);
-    }
-}