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    // Copyright 2018 Developers of the Rand project.
    // Copyright 2017-2018 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.

    //! Random number generation traits
    //!
    //! This crate is mainly of interest to crates publishing implementations of
    //! [`RngCore`]. Other users are encouraged to use the [`rand`] crate instead
    //! which re-exports the main traits and error types.
    //!
    //! [`RngCore`] is the core trait implemented by algorithmic pseudo-random number
    //! generators and external random-number sources.
    //!
    //! [`SeedableRng`] is an extension trait for construction from fixed seeds and
    //! other random number generators.
    //!
    //! [`Error`] is provided for error-handling. It is safe to use in `no_std`
    //! environments.
    //!
    //! The [`impls`] and [`le`] sub-modules include a few small functions to assist
    //! implementation of [`RngCore`].
    //!
    //! [`rand`]: https://docs.rs/rand

    #![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="alloc", not(feature="std")), feature(alloc))]

    #[cfg(feature="std")] extern crate core;
    #[cfg(all(feature = "alloc", not(feature="std")))] extern crate alloc;
    #[cfg(feature="serde1")] extern crate serde;
    #[cfg(feature="serde1")] #[macro_use] extern crate serde_derive;

    use core::default::Default;
    use core::convert::AsMut;
    use core::ptr::copy_nonoverlapping;

    #[cfg(all(feature="alloc", not(feature="std")))] use alloc::boxed::Box;

    pub use error::Error;

    mod error;
    pub mod block;
    pub mod impls;
    pub mod le;

    /// The core of a random number generator.
    ///
    /// This trait encapsulates the low-level functionality common to all
    /// generators, and is the "back end", to be implemented by generators.
    /// End users should normally use the `Rng` trait from the [`rand`] crate,
    /// which is automatically implemented for every type implementing `RngCore`.
    ///
    /// Three different methods for generating random data are provided since the
    /// optimal implementation of each is dependent on the type of generator. There
    /// is no required relationship between the output of each; e.g. many
    /// implementations of [`fill_bytes`] consume a whole number of `u32` or `u64`
    /// values and drop any remaining unused bytes.
    ///
    /// The [`try_fill_bytes`] method is a variant of [`fill_bytes`] allowing error
    /// handling; it is not deemed sufficiently useful to add equivalents for
    /// [`next_u32`] or [`next_u64`] since the latter methods are almost always used
    /// with algorithmic generators (PRNGs), which are normally infallible.
    ///
    /// Algorithmic generators implementing [`SeedableRng`] should normally have
    /// *portable, reproducible* output, i.e. fix Endianness when converting values
    /// to avoid platform differences, and avoid making any changes which affect
    /// output (except by communicating that the release has breaking changes).
    ///
    /// Typically implementators will implement only one of the methods available
    /// in this trait directly, then use the helper functions from the
    /// [`impls`] module to implement the other methods.
    ///
    /// It is recommended that implementations also implement:
    ///
    /// - `Debug` with a custom implementation which *does not* print any internal
    ///   state (at least, [`CryptoRng`]s should not risk leaking state through
    ///   `Debug`).
    /// - `Serialize` and `Deserialize` (from Serde), preferably making Serde
    ///   support optional at the crate level in PRNG libs.
    /// - `Clone`, if possible.
    /// - *never* implement `Copy` (accidental copies may cause repeated values).
    /// - *do not* implement `Default` for pseudorandom generators, but instead
    ///   implement [`SeedableRng`], to guide users towards proper seeding.
    ///   External / hardware RNGs can choose to implement `Default`.
    /// - `Eq` and `PartialEq` could be implemented, but are probably not useful.
    ///
    /// # Example
    ///
    /// A simple example, obviously not generating very *random* output:
    ///
    /// ```
    /// #![allow(dead_code)]
    /// use rand_core::{RngCore, Error, impls};
    ///
    /// struct CountingRng(u64);
    ///
    /// impl RngCore for CountingRng {
    ///     fn next_u32(&mut self) -> u32 {
    ///         self.next_u64() as u32
    ///     }
    ///
    ///     fn next_u64(&mut self) -> u64 {
    ///         self.0 += 1;
    ///         self.0
    ///     }
    ///
    ///     fn fill_bytes(&mut self, dest: &mut [u8]) {
    ///         impls::fill_bytes_via_next(self, dest)
    ///     }
    ///
    ///     fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
    ///         Ok(self.fill_bytes(dest))
    ///     }
    /// }
    /// ```
    ///
    /// [`rand`]: https://docs.rs/rand
    /// [`try_fill_bytes`]: RngCore::try_fill_bytes
    /// [`fill_bytes`]: RngCore::fill_bytes
    /// [`next_u32`]: RngCore::next_u32
    /// [`next_u64`]: RngCore::next_u64
    pub trait RngCore {
        /// Return the next random `u32`.
        ///
        /// RNGs must implement at least one method from this trait directly. In
        /// the case this method is not implemented directly, it can be implemented
        /// using `self.next_u64() as u32` or via
        /// [`fill_bytes`][impls::next_u32_via_fill].
        fn next_u32(&mut self) -> u32;

        /// Return the next random `u64`.
        ///
        /// RNGs must implement at least one method from this trait directly. In
        /// the case this method is not implemented directly, it can be implemented
        /// via [`next_u32`][impls::next_u64_via_u32] or via
        /// [`fill_bytes`][impls::next_u64_via_fill].
        fn next_u64(&mut self) -> u64;

        /// Fill `dest` with random data.
        ///
        /// RNGs must implement at least one method from this trait directly. In
        /// the case this method is not implemented directly, it can be implemented
        /// via [`next_u*`][impls::fill_bytes_via_next] or
        /// via [`try_fill_bytes`][RngCore::try_fill_bytes]; if this generator can
        /// fail the implementation must choose how best to handle errors here
        /// (e.g. panic with a descriptive message or log a warning and retry a few
        /// times).
        ///
        /// This method should guarantee that `dest` is entirely filled
        /// with new data, and may panic if this is impossible
        /// (e.g. reading past the end of a file that is being used as the
        /// source of randomness).
        fn fill_bytes(&mut self, dest: &mut [u8]);

        /// Fill `dest` entirely with random data.
        ///
        /// This is the only method which allows an RNG to report errors while
        /// generating random data thus making this the primary method implemented
        /// by external (true) RNGs (e.g. `OsRng`) which can fail. It may be used
        /// directly to generate keys and to seed (infallible) PRNGs.
        ///
        /// Other than error handling, this method is identical to [`fill_bytes`];
        /// thus this may be implemented using `Ok(self.fill_bytes(dest))` or
        /// `fill_bytes` may be implemented with
        /// `self.try_fill_bytes(dest).unwrap()` or more specific error handling.
        ///
        /// [`fill_bytes`]: RngCore::fill_bytes
        fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error>;
    }

    /// A marker trait used to indicate that an [`RngCore`] or [`BlockRngCore`]
    /// implementation is supposed to be cryptographically secure.
    ///
    /// *Cryptographically secure generators*, also known as *CSPRNGs*, should
    /// satisfy an additional properties over other generators: given the first
    /// *k* bits of an algorithm's output
    /// sequence, it should not be possible using polynomial-time algorithms to
    /// predict the next bit with probability significantly greater than 50%.
    ///
    /// Some generators may satisfy an additional property, however this is not
    /// required by this trait: if the CSPRNG's state is revealed, it should not be
    /// computationally-feasible to reconstruct output prior to this. Some other
    /// generators allow backwards-computation and are consided *reversible*.
    ///
    /// Note that this trait is provided for guidance only and cannot guarantee
    /// suitability for cryptographic applications. In general it should only be
    /// implemented for well-reviewed code implementing well-regarded algorithms.
    ///
    /// Note also that use of a `CryptoRng` does not protect against other
    /// weaknesses such as seeding from a weak entropy source or leaking state.
    ///
    /// [`BlockRngCore`]: block::BlockRngCore
    pub trait CryptoRng {}

    /// A random number generator that can be explicitly seeded.
    ///
    /// This trait encapsulates the low-level functionality common to all
    /// pseudo-random number generators (PRNGs, or algorithmic generators).
    ///
    /// [`rand`]: https://docs.rs/rand
    pub trait SeedableRng: Sized {
        /// Seed type, which is restricted to types mutably-dereferencable as `u8`
        /// arrays (we recommend `[u8; N]` for some `N`).
        ///
        /// It is recommended to seed PRNGs with a seed of at least circa 100 bits,
        /// which means an array of `[u8; 12]` or greater to avoid picking RNGs with
        /// partially overlapping periods.
        ///
        /// For cryptographic RNG's a seed of 256 bits is recommended, `[u8; 32]`.
        ///
        ///
        /// # Implementing `SeedableRng` for RNGs with large seeds
        ///
        /// Note that the required traits `core::default::Default` and
        /// `core::convert::AsMut<u8>` are not implemented for large arrays
        /// `[u8; N]` with `N` > 32. To be able to implement the traits required by
        /// `SeedableRng` for RNGs with such large seeds, the newtype pattern can be
        /// used:
        ///
        /// ```
        /// use rand_core::SeedableRng;
        ///
        /// const N: usize = 64;
        /// pub struct MyRngSeed(pub [u8; N]);
        /// pub struct MyRng(MyRngSeed);
        ///
        /// impl Default for MyRngSeed {
        ///     fn default() -> MyRngSeed {
        ///         MyRngSeed([0; N])
        ///     }
        /// }
        ///
        /// impl AsMut<[u8]> for MyRngSeed {
        ///     fn as_mut(&mut self) -> &mut [u8] {
        ///         &mut self.0
        ///     }
        /// }
        ///
        /// impl SeedableRng for MyRng {
        ///     type Seed = MyRngSeed;
        ///
        ///     fn from_seed(seed: MyRngSeed) -> MyRng {
        ///         MyRng(seed)
        ///     }
        /// }
        /// ```
        type Seed: Sized + Default + AsMut<[u8]>;

        /// Create a new PRNG using the given seed.
        ///
        /// PRNG implementations are allowed to assume that bits in the seed are
        /// well distributed. That means usually that the number of one and zero
        /// bits are roughly equal, and values like 0, 1 and (size - 1) are unlikely.
        /// Note that many non-cryptographic PRNGs will show poor quality output
        /// if this is not adhered to. If you wish to seed from simple numbers, use
        /// `seed_from_u64` instead.
        ///
        /// All PRNG implementations should be reproducible unless otherwise noted:
        /// given a fixed `seed`, the same sequence of output should be produced
        /// on all runs, library versions and architectures (e.g. check endianness).
        /// Any "value-breaking" changes to the generator should require bumping at
        /// least the minor version and documentation of the change.
        ///
        /// It is not required that this function yield the same state as a
        /// reference implementation of the PRNG given equivalent seed; if necessary
        /// another constructor replicating behaviour from a reference
        /// implementation can be added.
        ///
        /// PRNG implementations should make sure `from_seed` never panics. In the
        /// case that some special values (like an all zero seed) are not viable
        /// seeds it is preferable to map these to alternative constant value(s),
        /// for example `0xBAD5EEDu32` or `0x0DDB1A5E5BAD5EEDu64` ("odd biases? bad
        /// seed"). This is assuming only a small number of values must be rejected.
        fn from_seed(seed: Self::Seed) -> Self;

        /// Create a new PRNG using a `u64` seed.
        ///
        /// This is a convenience-wrapper around `from_seed` to allow construction
        /// of any `SeedableRng` from a simple `u64` value. It is designed such that
        /// low Hamming Weight numbers like 0 and 1 can be used and should still
        /// result in good, independent seeds to the PRNG which is returned.
        ///
        /// This **is not suitable for cryptography**, as should be clear given that
        /// the input size is only 64 bits.
        ///
        /// Implementations for PRNGs *may* provide their own implementations of
        /// this function, but the default implementation should be good enough for
        /// all purposes. *Changing* the implementation of this function should be
        /// considered a value-breaking change.
        fn seed_from_u64(mut state: u64) -> Self {
            // We use PCG32 to generate a u32 sequence, and copy to the seed
            const MUL: u64 = 6364136223846793005;
            const INC: u64 = 11634580027462260723;

            let mut seed = Self::Seed::default();
            for chunk in seed.as_mut().chunks_mut(4) {
                // We advance the state first (to get away from the input value,
                // in case it has low Hamming Weight).
                state = state.wrapping_mul(MUL).wrapping_add(INC);

                // Use PCG output function with to_le to generate x:
                let xorshifted = (((state >> 18) ^ state) >> 27) as u32;
                let rot = (state >> 59) as u32;
                let x = xorshifted.rotate_right(rot).to_le();

                unsafe {
                    let p = &x as *const u32 as *const u8;
                    copy_nonoverlapping(p, chunk.as_mut_ptr(), chunk.len());
                }
            }

            Self::from_seed(seed)
        }

        /// Create a new PRNG seeded from another `Rng`.
        ///
        /// This may be useful when needing to rapidly seed many PRNGs from a master
        /// PRNG, and to allow forking of PRNGs. It may be considered deterministic.
        ///
        /// The master PRNG should be at least as high quality as the child PRNGs.
        /// When seeding non-cryptographic child PRNGs, we recommend using a
        /// different algorithm for the master PRNG (ideally a CSPRNG) to avoid
        /// correlations between the child PRNGs. If this is not possible (e.g.
        /// forking using small non-crypto PRNGs) ensure that your PRNG has a good
        /// mixing function on the output or consider use of a hash function with
        /// `from_seed`.
        ///
        /// Note that seeding `XorShiftRng` from another `XorShiftRng` provides an
        /// extreme example of what can go wrong: the new PRNG will be a clone
        /// of the parent.
        ///
        /// PRNG implementations are allowed to assume that a good RNG is provided
        /// for seeding, and that it is cryptographically secure when appropriate.
        /// As of `rand` 0.7 / `rand_core` 0.5, implementations overriding this
        /// method should ensure the implementation satisfies reproducibility
        /// (in prior versions this was not required).
        ///
        /// [`rand`]: https://docs.rs/rand
        /// [`rand_os`]: https://docs.rs/rand_os
        fn from_rng<R: RngCore>(mut rng: R) -> Result<Self, Error> {
            let mut seed = Self::Seed::default();
            rng.try_fill_bytes(seed.as_mut())?;
            Ok(Self::from_seed(seed))
        }

        /// Creates a new instance of the RNG seeded via [`getrandom`].
        ///
        /// This method is the recommended way to construct non-deterministic PRNGs
        /// since it is convenient and secure.
        ///
        /// In case the overhead of using [`getrandom`] to seed *many* PRNGs is an
        /// issue, one may prefer to seed from a local PRNG, e.g.
        /// `from_rng(thread_rng()).unwrap()`.
        ///
        /// # Panics
        ///
        /// If [`getrandom`] is unable to provide secure entropy this method will panic.
        ///
        /// [`getrandom`]: https://docs.rs/getrandom
        #[cfg(feature="getrandom")]
        fn from_entropy() -> Self {
            let mut seed = Self::Seed::default();
            if let Err(err) = getrandom::getrandom(seed.as_mut()) {
                panic!("from_entropy failed: {}", err);
            }
            Self::from_seed(seed)
        }
    }

    // Implement `RngCore` for references to an `RngCore`.
    // Force inlining all functions, so that it is up to the `RngCore`
    // implementation and the optimizer to decide on inlining.
    impl<'a, R: RngCore + ?Sized> RngCore for &'a mut R {
        #[inline(always)]
        fn next_u32(&mut self) -> u32 {
            (**self).next_u32()
        }

        #[inline(always)]
        fn next_u64(&mut self) -> u64 {
            (**self).next_u64()
        }

        #[inline(always)]
        fn fill_bytes(&mut self, dest: &mut [u8]) {
            (**self).fill_bytes(dest)
        }

        #[inline(always)]
        fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
            (**self).try_fill_bytes(dest)
        }
    }

    // Implement `RngCore` for boxed references to an `RngCore`.
    // Force inlining all functions, so that it is up to the `RngCore`
    // implementation and the optimizer to decide on inlining.
    #[cfg(feature="alloc")]
    impl<R: RngCore + ?Sized> RngCore for Box<R> {
        #[inline(always)]
        fn next_u32(&mut self) -> u32 {
            (**self).next_u32()
        }

        #[inline(always)]
        fn next_u64(&mut self) -> u64 {
            (**self).next_u64()
        }

        #[inline(always)]
        fn fill_bytes(&mut self, dest: &mut [u8]) {
            (**self).fill_bytes(dest)
        }

        #[inline(always)]
        fn try_fill_bytes(&mut self, dest: &mut [u8]) -> Result<(), Error> {
            (**self).try_fill_bytes(dest)
        }
    }

    #[cfg(feature="std")]
    impl std::io::Read for RngCore {
        fn read(&mut self, buf: &mut [u8]) -> Result<usize, std::io::Error> {
            self.try_fill_bytes(buf)?;
            Ok(buf.len())
        }
    }

    // Implement `CryptoRng` for references to an `CryptoRng`.
    impl<'a, R: CryptoRng + ?Sized> CryptoRng for &'a mut R {}

    // Implement `CryptoRng` for boxed references to an `CryptoRng`.
    #[cfg(feature="alloc")]
    impl<R: CryptoRng + ?Sized> CryptoRng for Box<R> {}

    #[cfg(test)]
    mod test {
        use super::*;

        #[test]
        fn test_seed_from_u64() {
            struct SeedableNum(u64);
            impl SeedableRng for SeedableNum {
                type Seed = [u8; 8];
                fn from_seed(seed: Self::Seed) -> Self {
                    let mut x = [0u64; 1];
                    le::read_u64_into(&seed, &mut x);
                    SeedableNum(x[0])
                }
            }

            const N: usize = 8;
            const SEEDS: [u64; N] = [0u64, 1, 2, 3, 4, 8, 16, -1i64 as u64];
            let mut results = [0u64; N];
            for (i, seed) in SEEDS.iter().enumerate() {
                let SeedableNum(x) = SeedableNum::seed_from_u64(*seed);
                results[i] = x;
            }

            for (i1, r1) in results.iter().enumerate() {
                let weight = r1.count_ones();
                // This is the binomial distribution B(64, 0.5), so chance of
                // weight < 20 is binocdf(19, 64, 0.5) = 7.8e-4, and same for
                // weight > 44.
                assert!(weight >= 20 && weight <= 44);

                for (i2, r2) in results.iter().enumerate() {
                    if i1 == i2 { continue; }
                    let diff_weight = (r1 ^ r2).count_ones();
                    assert!(diff_weight >= 20);
                }
            }

            // value-breakage test:
            assert_eq!(results[0], 5029875928683246316);
        }
    }

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