RandX_Cpp17.hpp

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//----------------------------------------------------------------------------------------
//
//  RandX_Cpp17.hpp — 基于 Xoshiro 的伪随机数生成器封装库（C++17 / C++23）
//
//  原始算法：David Blackman & Sebastiano Vigna (http://prng.di.unimi.it/)
//  原始 C++ 封装：Ryo Suzuki (https://github.com/Reputeless/Xoshiro-cpp)
//
//========================================================================================
//
//  快速上手
//
//      #include “RandX_Cpp17.hpp”
//
//      // 最简用法：直接调用便捷函数（内部使用线程局部 Xoshiro256StarStar）
//      int   dice  = RandX::RandInt(1, 6);     // [1, 6] 闭区间整数
//      double coin = RandX::RandReal();         // [0.0, 1.0) 浮点数
//      bool  flag  = RandX::RandBool(0.3);      // 30% 概率为 true
//
//      std::vector<int> v = {10, 20, 30, 40};
//      auto& elem = RandX::RandElement(v);      // 随机取一个元素
//
//  扩展 API
//
//      auto sample = RandX::RandSample(v, 2);   // 无放回抽样 2 个
//      auto perm   = RandX::RandPermutation(10);// [0,10) 随机排列
//      auto token  = RandX::RandString(16);     // 16 位随机字符串
//      auto uuid   = RandX::RandUUID();         // UUID v4
//      auto byte   = RandX::RandBits<8>();      // [0, 256) 随机整数
//      auto exp    = RandX::RandExp(2.0);       // 指数分布 λ=2
//      auto poi    = RandX::RandPoisson(5.0);   // 泊松分布 μ=5
//
//  手动管理引擎
//
//      RandX::Xoshiro256StarStar rng{ RandX::RandomSeed() };
//      int val = RandX::RandInt(rng, 0, 99);
//
//      // 配合标准库 distribution（满足 UniformRandomBitGenerator）
//      std::normal_distribution<double> norm(0.0, 1.0);
//      double sample = norm(rng);
//
//  多流并行
//
//      auto s0 = RandX::MakeStreamEngine<RandX::Xoshiro256StarStar>(0);
//      auto s1 = RandX::MakeStreamEngine<RandX::Xoshiro256StarStar>(1);
//
//  序列化 / 反序列化
//
//      auto state = rng.serialize();
//      rng.deserialize(state);
//
//  跳跃
//
//      rng.jump();      // 前进 2^128 步（xoshiro256 系列）
//      rng.longJump();  // 前进 2^192 步
//      rng.discard(1000);
//
//  引擎选择指南
//
//      引擎                    输出   周期        状态   适用场景
//      ─────────────────────────────────────────────────────────────
//      Xoshiro256StarStar     64-bit  2^256-1    32B    通用首选，统计质量最优
//      Xoroshiro128StarStar   64-bit  2^128-1    16B    内存受限，统计更优
//      Xoshiro128StarStar     32-bit  2^128-1    16B    32 位平台，统计更优
//      Xoroshiro64StarStar    32-bit  2^64-1      8B    极端内存受限
//      SplitMix64             64-bit  2^64        8B    种子扩展 / 哈希，非通用 PRNG
//      SFC64                  64-bit  >= 2^64    32B    速度极快，通过 PractRand
//      RomuDuoJr              64-bit  >= 2^51    16B    极简极快，非关键模拟
//      ChaCha20               64-bit  无周期      48B+   密码学安全 CSPRNG（RFC 8439）
//
//  ⚠️ 安全声明
//  本库的 xoshiro/xoroshiro/SFC64/RomuDuoJr 引擎均非 CSPRNG。
//  状态可从输出逆推，不可用于密码/密钥/会话 token 等安全场景。
//  此类场景请使用 ChaCha20 引擎或 SecureRandomBytes()。
//
//----------------------------------------------------------------------------------------
 
# pragma once
# include <cstdint>
# include <array>
# include <cmath>
# include <limits>
# include <type_traits>
# include <random>
# include <algorithm>
# include <cassert>
# include <string>
# include <string_view>
# include <unordered_set>
# include <vector>
# include <stdexcept>
# include <chrono>    // std::chrono（RandomSeed 时间戳兜底用）
# include <atomic>    // std::atomic（RandomSeed 兜底计数）
# include <functional>// std::hash（RandomSeed 线程 Hash）
# include <thread>    // std::this_thread（RandomSeed 线程 ID）
# include <ios>       // std::ios_base::failbit（operator>> 所需）
# include <istream>   // std::basic_istream（operator>> 所需完整类型）
# include <ostream>   // std::basic_ostream（operator<< 所需完整类型）
# if defined(_MSC_VER) && (defined(__x86_64__) || defined(_M_X64))
#   include <immintrin.h>
#   include <intrin.h>
# endif
// ── A3 跨平台 OS 熵源头文件（条件包含） ──
# if defined(_WIN32) && __has_include(<bcrypt.h>)
// bcrypt.h 依赖 <windows.h> 提供的 ULONG/NTSTATUS 等类型（MSVC 和 MinGW 均需）
// NOMINMAX 阻止 <windows.h> 定义 min/max 宏（与引擎的 min()/max() 方法冲突）
#   ifndef WIN32_LEAN_AND_MEAN
#       define WIN32_LEAN_AND_MEAN
#   endif
#   ifndef NOMINMAX
#       define NOMINMAX
#   endif
#   include <windows.h>
#   include <bcrypt.h>
#   pragma comment(lib, "bcrypt.lib")  // 仅 MSVC 生效
// MinGW 不支持 #pragma comment(lib)，须手动添加 -lbcrypt 链接选项
#   if(defined(__MINGW32__) || defined(__MINGW64__)) && !defined(RANDX_SUPPRESS_LINK_HINT)
#       pragma message("RandX: MinGW 需手动链接 bcrypt（编译命令添加 -lbcrypt）")
#   endif
# elif defined(__linux__) && __has_include(<sys/random.h>)
#   include <sys/random.h>
#   include <cerrno>
# elif defined(__APPLE__)
#   include <TargetConditionals.h>
#   if TARGET_OS_IPHONE
#       if __has_include(<Security/SecRandom.h>)
#           include <Security/SecRandom.h>
#       endif
#   elif __has_include(<Security/Security.h>)
#       include <Security/Security.h>
#   endif
# endif
# include <chrono>   // std::chrono（RandomSeed 时间戳兜底用）
# include <cstring>  // std::memcpy（std::random_device 回退路径用）
# if __has_cpp_attribute(nodiscard) >= 201907L
#   define RANDX_NODISCARD_CXX20 [[nodiscard]]
# else
#   define RANDX_NODISCARD_CXX20
# endif
 
namespace RandX
{
    // 生成器的默认种子值
    inline constexpr std::uint64_t DefaultSeed = 1234567890ULL;
 
    // 将给定的 uint32 值 `i` 转换为 32 位浮点
    // 范围在 [0.0f, 1.0f) 的数值
    template <class Uint32, std::enable_if_t<std::is_same_v<Uint32, std::uint32_t>>* = nullptr>
    [[nodiscard]]
    inline constexpr float FloatFromBits(Uint32 i) noexcept;
 
    // 将给定的 uint64 值 `i` 转换为 64 位浮点
    // 范围在 [0.0, 1.0) 的数值
    template <class Uint64, std::enable_if_t<std::is_same_v<Uint64, std::uint64_t>>* = nullptr>
    [[nodiscard]]
    inline constexpr double DoubleFromBits(Uint64 i) noexcept;
 
    // ── 引擎基础设施（提前定义，供 EngineBase CRTP 基类使用） ──
    namespace detail
    {
        [[nodiscard]]
        inline constexpr std::uint64_t RotL(const std::uint64_t x, const int s) noexcept
        {
            const int count = s & 63;
            return count == 0 ? x : ((x << count) | (x >> (64 - count)));
        }
 
        [[nodiscard]]
        inline constexpr std::uint32_t RotL(const std::uint32_t x, const int s) noexcept
        {
            const int count = s & 31;
            return count == 0 ? x : ((x << count) | (x >> (32 - count)));
        }
 
        template <std::size_t N>
        [[nodiscard]]
        inline constexpr bool IsAllZero(const std::array<std::uint64_t, N>& state) noexcept
        {
            for (const auto& s : state) { if (s != 0) return false; }
            return true;
        }
 
        template <std::size_t N>
        [[nodiscard]]
        inline constexpr bool IsAllZero(const std::array<std::uint32_t, N>& state) noexcept
        {
            for (const auto& s : state) { if (s != 0) return false; }
            return true;
        }
 
        template <typename State>
        [[nodiscard]]
        inline constexpr bool IsValidState(const State& state) noexcept
        {
            return !IsAllZero(state);
        }
    }


    class SplitMix64
    {
    public:
 
        using state_type    = std::uint64_t;    
        using result_type   = std::uint64_t;    

        RANDX_NODISCARD_CXX20
        explicit constexpr SplitMix64(state_type state = DefaultSeed) noexcept;

        template <class SeedSeq,
            std::enable_if_t<!std::is_same_v<std::decay_t<SeedSeq>, SplitMix64>>* = nullptr>
        RANDX_NODISCARD_CXX20
        explicit constexpr SplitMix64(SeedSeq& seq);

        constexpr result_type operator()() noexcept;

        constexpr void discard(unsigned long long n) noexcept;

        template <std::size_t N>
        [[nodiscard]]
        constexpr std::array<std::uint64_t, N> generateSeedSequence() noexcept;

        [[nodiscard]]
        static constexpr result_type min() noexcept;

        [[nodiscard]]
        static constexpr result_type max() noexcept;

        [[nodiscard]]
        constexpr state_type serialize() const noexcept;

        constexpr void deserialize(state_type state) noexcept;
 
        [[nodiscard]]
        friend bool operator ==(const SplitMix64& lhs, const SplitMix64& rhs) noexcept
        {
            return (lhs.m_state == rhs.m_state);
        }
 
        [[nodiscard]]
        friend bool operator !=(const SplitMix64& lhs, const SplitMix64& rhs) noexcept
        {
            return (lhs.m_state != rhs.m_state);
        }
    
    private:
 
        state_type m_state;
    };
 
    // ── EngineBase CRTP 基类 ──
    // 为数组状态引擎提供公共接口：min/max/discard/serialize/比较/构造/jumpPoly
    // SplitMix64（标量状态）和 ChaCha20（CSPRNG）不继承此基类
    namespace detail
    {
        template <class Derived, class ResultType, std::size_t N>
        struct EngineBase
        {
            using result_type = ResultType;
            using state_type  = std::array<ResultType, N>;
 
            // --- 公共接口 ---
 
            [[nodiscard]]
            static constexpr result_type min() noexcept
            {
                return std::numeric_limits<result_type>::lowest();
            }
 
            [[nodiscard]]
            static constexpr result_type max() noexcept
            {
                return std::numeric_limits<result_type>::max();
            }
 
            constexpr void discard(unsigned long long z) noexcept
            {
                for (unsigned long long i = 0; i < z; ++i)
                    static_cast<Derived*>(this)->operator()();
            }
 
            [[nodiscard]]
            constexpr state_type serialize() const noexcept
            {
                return s_;
            }
 
            constexpr void deserialize(const state_type& s) noexcept
            {
                s_ = s;
                if (IsAllZero(s_))
                {
                    s_[0] = static_cast<ResultType>(1);
                }
                assert(!IsAllZero(s_) && "absorbing all-zero state");
            }
 
            // C++17: 手写比较运算符
            friend bool operator==(const EngineBase& lhs, const EngineBase& rhs) noexcept
            {
                return lhs.s_ == rhs.s_;
            }
 
            friend bool operator!=(const EngineBase& lhs, const EngineBase& rhs) noexcept
            {
                return lhs.s_ != rhs.s_;
            }
 
        protected:
 
            static constexpr int Bits = static_cast<int>(sizeof(ResultType) * 8);
 
            EngineBase() = default;
 
            // State 构造（用户直接传入，包含 Release/Debug 全零状态静默修正）
            explicit constexpr EngineBase(const state_type& state) noexcept
                : s_(state)
            {
                if (IsAllZero(s_))
                {
                    s_[0] = static_cast<ResultType>(1);
                }
                assert(!IsAllZero(s_) && "absorbing all-zero state");
            }
 
            // SeedSeq 构造（SFINAE 排除 state_type 和 Derived）
            template <class SeedSeq,
                std::enable_if_t<!std::is_same_v<std::decay_t<SeedSeq>, state_type>
                    && !std::is_same_v<std::decay_t<SeedSeq>, Derived>>* = nullptr>
            explicit constexpr EngineBase(SeedSeq& seq)
            {
                if constexpr (sizeof(result_type) == 8)
                {
                    std::array<std::uint32_t, N * 2> raw;
                    seq.generate(raw.begin(), raw.end());
                    for (std::size_t i = 0; i < N; ++i)
                        s_[i] = (static_cast<result_type>(raw[2 * i]) << 32) | raw[2 * i + 1];
                }
                else
                {
                    std::array<std::uint32_t, N> raw;
                    seq.generate(raw.begin(), raw.end());
                    for (std::size_t i = 0; i < N; ++i)
                        s_[i] = static_cast<result_type>(raw[i]);
                }
                if (IsAllZero(s_)) s_[0] = 1;
            }
 
            // 单值播种（SplitMix64 扩展，等价于 generateSeedSequence<N>）
            explicit constexpr EngineBase(std::uint64_t seed) noexcept
            {
                SplitMix64 sm{ seed };
                for (std::size_t i = 0; i < N; ++i)
                    s_[i] = static_cast<result_type>(sm());
                if (IsAllZero(s_)) s_[0] = 1;
            }
 
            // jump 多项式通用实现（constexpr，供 MakeStreamEngine 编译期调用）
            template <std::size_t K>
            constexpr void jumpPoly(const ResultType (&poly)[K]) noexcept
            {
                std::array<ResultType, N> acc{};
                for (std::size_t i = 0; i < K; ++i)
                    for (int b = 0; b < Bits; ++b)
                    {
                        if (poly[i] & (ResultType{ 1 } << b))
                            for (std::size_t j = 0; j < N; ++j)
                                acc[j] ^= s_[j];
                        static_cast<Derived*>(this)->operator()();
                    }
                s_ = acc;
            }
 
            state_type s_{};
        };
    }

    class Xoshiro256StarStar
        : public detail::EngineBase<Xoshiro256StarStar, std::uint64_t, 4>
    {
        using Base = detail::EngineBase<Xoshiro256StarStar, std::uint64_t, 4>;
    public:
 
        using typename Base::result_type;   
        using typename Base::state_type;    

        constexpr Xoshiro256StarStar() noexcept : Base(DefaultSeed) {}

        RANDX_NODISCARD_CXX20
        explicit constexpr Xoshiro256StarStar(std::uint64_t seed) noexcept
            : Base(seed) {}

        template <class SeedSeq,
            std::enable_if_t<!std::is_same_v<std::decay_t<SeedSeq>, Xoshiro256StarStar>>* = nullptr>
        RANDX_NODISCARD_CXX20
        explicit constexpr Xoshiro256StarStar(SeedSeq& seq)
            : Base(seq) {}

        RANDX_NODISCARD_CXX20
        explicit constexpr Xoshiro256StarStar(state_type state) noexcept
            : Base(state) {}

        constexpr result_type operator()() noexcept;

        constexpr void jump() noexcept;

        constexpr void longJump() noexcept;
    };

    class Xoroshiro128StarStar
        : public detail::EngineBase<Xoroshiro128StarStar, std::uint64_t, 2>
    {
        using Base = detail::EngineBase<Xoroshiro128StarStar, std::uint64_t, 2>;
    public:
 
        using typename Base::result_type;   
        using typename Base::state_type;    

        constexpr Xoroshiro128StarStar() noexcept : Base(DefaultSeed) {}

        RANDX_NODISCARD_CXX20
        explicit constexpr Xoroshiro128StarStar(std::uint64_t seed) noexcept
            : Base(seed) {}

        template <class SeedSeq,
            std::enable_if_t<!std::is_same_v<std::decay_t<SeedSeq>, Xoroshiro128StarStar>>* = nullptr>
        RANDX_NODISCARD_CXX20
        explicit constexpr Xoroshiro128StarStar(SeedSeq& seq)
            : Base(seq) {}

        RANDX_NODISCARD_CXX20
        explicit constexpr Xoroshiro128StarStar(state_type state) noexcept
            : Base(state) {}

        constexpr result_type operator()() noexcept;

        constexpr void jump() noexcept;

        constexpr void longJump() noexcept;
    };

    class Xoshiro128StarStar
        : public detail::EngineBase<Xoshiro128StarStar, std::uint32_t, 4>
    {
        using Base = detail::EngineBase<Xoshiro128StarStar, std::uint32_t, 4>;
    public:
 
        using typename Base::result_type;   
        using typename Base::state_type;    

        constexpr Xoshiro128StarStar() noexcept : Base(DefaultSeed) {}

        RANDX_NODISCARD_CXX20
        explicit constexpr Xoshiro128StarStar(std::uint64_t seed) noexcept
            : Base(seed) {}

        template <class SeedSeq,
            std::enable_if_t<!std::is_same_v<std::decay_t<SeedSeq>, Xoshiro128StarStar>>* = nullptr>
        RANDX_NODISCARD_CXX20
        explicit constexpr Xoshiro128StarStar(SeedSeq& seq)
            : Base(seq) {}

        RANDX_NODISCARD_CXX20
        explicit constexpr Xoshiro128StarStar(state_type state) noexcept
            : Base(state) {}

        constexpr result_type operator()() noexcept;

        constexpr void jump() noexcept;

        constexpr void longJump() noexcept;
    };

    class Xoroshiro64StarStar
        : public detail::EngineBase<Xoroshiro64StarStar, std::uint32_t, 2>
    {
        using Base = detail::EngineBase<Xoroshiro64StarStar, std::uint32_t, 2>;
    public:
 
        using typename Base::result_type;   
        using typename Base::state_type;    

        constexpr Xoroshiro64StarStar() noexcept : Base(DefaultSeed) {}

        RANDX_NODISCARD_CXX20
        explicit constexpr Xoroshiro64StarStar(std::uint64_t seed) noexcept
            : Base(seed) {}

        template <class SeedSeq,
            std::enable_if_t<!std::is_same_v<std::decay_t<SeedSeq>, Xoroshiro64StarStar>>* = nullptr>
        RANDX_NODISCARD_CXX20
        explicit constexpr Xoroshiro64StarStar(SeedSeq& seq)
            : Base(seq) {}

        RANDX_NODISCARD_CXX20
        explicit constexpr Xoroshiro64StarStar(state_type state) noexcept
            : Base(state) {}

        constexpr result_type operator()() noexcept;
    };
    class SFC64
        : public detail::EngineBase<SFC64, std::uint64_t, 4>
    {
        using Base = detail::EngineBase<SFC64, std::uint64_t, 4>;
    public:
 
        using typename Base::result_type;   
        using typename Base::state_type;    

        constexpr SFC64() noexcept : SFC64(DefaultSeed) {}

        RANDX_NODISCARD_CXX20
        explicit constexpr SFC64(std::uint64_t seed) noexcept;

        template <class SeedSeq,
            std::enable_if_t<!std::is_same_v<std::decay_t<SeedSeq>, SFC64>>* = nullptr>
        RANDX_NODISCARD_CXX20
        explicit constexpr SFC64(SeedSeq& seq);

        RANDX_NODISCARD_CXX20
        explicit constexpr SFC64(state_type state) noexcept
            : Base(state) {}

        constexpr result_type operator()() noexcept;
    };

    class RomuDuoJr
        : public detail::EngineBase<RomuDuoJr, std::uint64_t, 2>
    {
        using Base = detail::EngineBase<RomuDuoJr, std::uint64_t, 2>;
    public:
 
        using typename Base::result_type;   
        using typename Base::state_type;    

        constexpr RomuDuoJr() noexcept : Base(DefaultSeed) {}

        RANDX_NODISCARD_CXX20
        explicit constexpr RomuDuoJr(std::uint64_t seed) noexcept
            : Base(seed) {}

        template <class SeedSeq,
            std::enable_if_t<!std::is_same_v<std::decay_t<SeedSeq>, RomuDuoJr>>* = nullptr>
        RANDX_NODISCARD_CXX20
        explicit constexpr RomuDuoJr(SeedSeq& seq)
            : Base(seq) {}

        RANDX_NODISCARD_CXX20
        explicit constexpr RomuDuoJr(state_type state) noexcept
            : Base(state) {}

        constexpr result_type operator()() noexcept;
    };
 
    // ── 全 PRNG 引擎 TLS 可平凡析构（Trivially Destructible）编译期静态断言 ──
    static_assert(std::is_trivially_destructible_v<Xoshiro256StarStar>, "Xoshiro256StarStar must be trivially destructible for safe TLS.");
    static_assert(std::is_trivially_destructible_v<Xoroshiro128StarStar>, "Xoroshiro128StarStar must be trivially destructible for safe TLS.");
    static_assert(std::is_trivially_destructible_v<Xoshiro128StarStar>, "Xoshiro128StarStar must be trivially destructible for safe TLS.");
    static_assert(std::is_trivially_destructible_v<Xoroshiro64StarStar>, "Xoroshiro64StarStar must be trivially destructible for safe TLS.");
    static_assert(std::is_trivially_destructible_v<SplitMix64>, "SplitMix64 must be trivially destructible for safe TLS.");
    static_assert(std::is_trivially_destructible_v<SFC64>, "SFC64 must be trivially destructible for safe TLS.");
    static_assert(std::is_trivially_destructible_v<RomuDuoJr>, "RomuDuoJr must be trivially destructible for safe TLS.");

    class ChaCha20
    {
    public:
 
        using result_type = std::uint64_t;  
 
        ChaCha20(const ChaCha20&) = delete;
        ChaCha20& operator=(const ChaCha20&) = delete;
        ChaCha20(ChaCha20&& other) noexcept;
        ChaCha20& operator=(ChaCha20&& other) noexcept;
        ~ChaCha20() noexcept;

        ChaCha20();

        RANDX_NODISCARD_CXX20
        explicit ChaCha20(std::uint64_t seed);

        ChaCha20(const std::uint8_t* key, std::size_t keyLen,
                 const std::uint8_t* nonce, std::size_t nonceLen,
                 std::uint32_t counter = 0);

        result_type operator()();

        void discard(unsigned long long n);

        void reseed();

        RANDX_NODISCARD_CXX20
        static constexpr result_type min() noexcept { return 0; }

        RANDX_NODISCARD_CXX20
        static constexpr result_type max() noexcept { return UINT64_MAX; }
 
        // 不提供：serialize/deserialize, operator<</>>, jump/longJump（CSPRNG 安全约束）
 
    private:
 
        std::array<std::uint32_t, 12> m_state;   // key(8) + counter(1) + nonce(3)，常数省略（generateBlock 时补齐）
        std::array<std::uint8_t, 64>  m_buffer;  // 当前 block 的字节缓存
        std::size_t                   m_bufferPos;       // 缓存消费位置 [0, 64)，==64 时触发新 block
        std::uint64_t                 m_bytesSinceReseed; // 自上次 reseed 以来输出的字节数
        bool                          m_autoReseed{ false }; // 是否在满 1MB 后自动从 OS 熵重新播种（仅默认无参构造函数启用）
 
        void generateBlock();        // 跑一次 ChaCha20 block 函数填充 m_buffer
        void reseedIfNecessary();    // m_bytesSinceReseed >= 阈值时自动 reseed
    };
 
    // ── sizeof 守卫：防止引擎 ABI 意外变化 ──
    static_assert(sizeof(Xoshiro256StarStar) == 32, "Xoshiro256StarStar size changed");
    static_assert(sizeof(Xoroshiro128StarStar) == 16, "Xoroshiro128StarStar size changed");
    static_assert(sizeof(Xoshiro128StarStar) == 16, "Xoshiro128StarStar size changed");
    static_assert(sizeof(Xoroshiro64StarStar) == 8, "Xoroshiro64StarStar size changed");
    static_assert(sizeof(SFC64) == 32, "SFC64 size changed");
    static_assert(sizeof(RomuDuoJr) == 16, "RomuDuoJr size changed");
    static_assert(sizeof(SplitMix64) == 8, "SplitMix64 size changed");
}

 
namespace RandX
{
    template <class Uint32, std::enable_if_t<std::is_same_v<Uint32, std::uint32_t>>*>
    inline constexpr float FloatFromBits(const Uint32 i) noexcept
    {
        return (i >> 8) * 0x1.0p-24f;
    }
 
    template <class Uint64, std::enable_if_t<std::is_same_v<Uint64, std::uint64_t>>*>
    inline constexpr double DoubleFromBits(const Uint64 i) noexcept
    {
        return (i >> 11) * 0x1.0p-53;
    }
 
    namespace detail
    {
        // 安全擦除内存（volatile 防止编译器死存储消除）
        static void SecureWipe(void* ptr, std::size_t len) noexcept
        {
            volatile auto* p = static_cast<volatile std::uint8_t*>(ptr);
            while (len--) *p++ = 0;
        }
 
        // 尝试使用 RDRAND 获取 64 位硬件随机数
        [[nodiscard]]
        inline bool HardwareRand64(std::uint64_t& out) noexcept
        {
#if defined(__x86_64__) || defined(_M_X64)
    #if defined(__RDRND__)
            unsigned long long result;
            if (__builtin_ia32_rdrand64_step(&result))
            {
                out = result;
                return true;
            }
    #elif defined(_MSC_VER)
            int cpuInfo[4] = {0};
            __cpuid(cpuInfo, 1);
            if ((cpuInfo[2] & (1 << 30)) != 0)
            {
                unsigned long long result = 0;
                if (_rdrand64_step(&result))
                {
                    out = result;
                    return true;
                }
            }
    #endif
#endif
            (void)out;
            return false;
        }
 
        // ── A3 跨平台 OS 密码学熵源 ──
        // 用 OS 密码学 API 填充 [buf, buf+n) 字节；成功返回 true。
        // 平台优先级：Windows BCryptGenRandom → Linux getrandom → macOS SecRandomCopyBytes → std::random_device 兜底
        // 注：getrandom 可能短读，内部循环直至填满；BCryptGenRandom/SecRandomCopyBytes 一次填满
        [[nodiscard]]
        inline bool GetOsEntropyBytes(void* buf, std::size_t n) noexcept
        {
            if (n == 0) return true;
            auto* p = static_cast<std::uint8_t*>(buf);
 
#   if defined(_WIN32) && __has_include(<bcrypt.h>)
            // Windows: BCryptGenRandom（分块处理 >4GB 时的 ULONG 截断）
            // NTSTATUS >= 0 即 NT_SUCCESS（使用 BCRYPT_SUCCESS 宏或强转 NTSTATUS 判定）
            std::size_t filled = 0;
            while (filled < n)
            {
                const ULONG chunkSize = static_cast<ULONG>((std::min)(n - filled, static_cast<std::size_t>((std::numeric_limits<ULONG>::max)())));
                const auto status = ::BCryptGenRandom(nullptr, p + filled, chunkSize, BCRYPT_USE_SYSTEM_PREFERRED_RNG);
#   if defined(BCRYPT_SUCCESS)
                if (!BCRYPT_SUCCESS(status)) return false;
#   else
                if (static_cast<NTSTATUS>(status) < 0) return false;
#   endif
                filled += chunkSize;
            }
            return true;
 
#   elif defined(__linux__) && __has_include(<sys/random.h>)
            // Linux: getrandom（循环处理短读与 EINTR）
            std::size_t filled = 0;
            while (filled < n)
            {
                const ssize_t ret = ::getrandom(p + filled, n - filled, 0);
                if (ret < 0)
                {
                    if (errno == EINTR) continue;  // 被信号打断，重试
                    return false;                   // ENOSYS/EFAULT 等不可恢复错误
                }
                if (ret == 0) return false;
                filled += static_cast<std::size_t>(ret);
            }
            return true;
 
#   elif defined(__APPLE__) && __has_include(<Security/Security.h>)
            // macOS: SecRandomCopyBytes（一次调用填满）
            return (::SecRandomCopyBytes(kSecRandomDefault, n, p) == errSecSuccess);
 
#   else
            // 无可用 OS 密码学熵源 → 返回 false，SecureRandomBytes 将抛出异常
            // 非安全场景的播种请使用 RandomSeed()（含 random_device → 时间戳回退链）
            (void)p; (void)n;
            return false;
#   endif
        }
 
        // 返回 true 当且仅当编译期检测到 OS 密码学熵源 API（BCryptGenRandom/getrandom/SecRandomCopyBytes）
        // 返回 false 表示当前运行在 std::random_device 兜底路径，ChaCha20() 默认构造不保证密码学安全
        [[nodiscard]]
        inline bool HasCryptoGradeOsEntropy() noexcept
        {
#   if (defined(_WIN32) && __has_include(<bcrypt.h>)) || (defined(__linux__) && __has_include(<sys/random.h>)) || (defined(__APPLE__) && __has_include(<Security/Security.h>))
            return true;
#   else
            return false;
#   endif
        }
 
        // ── A4 ChaCha20 常数与辅助 ──
        // ChaCha20 常数 "expand 32-byte k"（RFC 8439 §2.3）
        inline constexpr std::uint32_t ChaCha20Constants[4] = {
            0x61707865u, 0x3320646eu, 0x79622d32u, 0x6b206574u
        };
        // 参考 NIST SP 800-90A reseed_interval 概念（SP 800-90A 涵盖 Hash/HMAC/CTR_DRBG，不含 ChaCha20；
        // 此处借用其"周期性强制 reseed 提供前向安全"思想，取保守阈值）
        inline constexpr std::uint64_t ChaCha20ReseedThreshold = 1ULL << 20;  // 1 MB
 
        // ChaCha20 quarter-round（仅 add/xor/rotl，常时间友好）
        static void ChaCha20QuarterRound(std::uint32_t& a, std::uint32_t& b,
                                         std::uint32_t& c, std::uint32_t& d) noexcept
        {
            a += b; d ^= a; d = RotL(d, 16);
            c += d; b ^= c; b = RotL(b, 12);
            a += b; d ^= a; d = RotL(d, 8);
            c += d; b ^= c; b = RotL(b, 7);
        }
    }

    //
    //  SplitMix64
    //
    inline constexpr SplitMix64::SplitMix64(const state_type state) noexcept
        : m_state(state) {}
 
    template <class SeedSeq, std::enable_if_t<!std::is_same_v<std::decay_t<SeedSeq>, SplitMix64>>*>
    inline constexpr SplitMix64::SplitMix64(SeedSeq& seq)
    {
        std::array<std::uint32_t, 2> seeds;
        seq.generate(seeds.begin(), seeds.end());
        m_state = (static_cast<std::uint64_t>(seeds[0]) << 32) | seeds[1];
    }
 
    inline constexpr SplitMix64::result_type SplitMix64::operator()() noexcept
    {
        std::uint64_t z = (m_state += 0x9e3779b97f4a7c15);
        z = (z ^ (z >> 30)) * 0xbf58476d1ce4e5b9;
        z = (z ^ (z >> 27)) * 0x94d049bb133111eb;
        return z ^ (z >> 31);
    }
 
    template <std::size_t N>
    inline constexpr std::array<std::uint64_t, N> SplitMix64::generateSeedSequence() noexcept
    {
        std::array<std::uint64_t, N> seeds = {};
 
        for (auto& seed : seeds)
        {
            seed = operator()();
        }
 
        return seeds;
    }
 
    inline constexpr SplitMix64::result_type SplitMix64::min() noexcept
    {
        return std::numeric_limits<result_type>::lowest();
    }
 
    inline constexpr SplitMix64::result_type SplitMix64::max() noexcept
    {
        return std::numeric_limits<result_type>::max();
    }
 
    inline constexpr SplitMix64::state_type SplitMix64::serialize() const noexcept
    {
        return m_state;
    }
 
    inline constexpr void SplitMix64::deserialize(const state_type state) noexcept
    {
        m_state = state;
    }
 
    inline constexpr void SplitMix64::discard(const unsigned long long n) noexcept
    {
        for (unsigned long long i = 0; i < n; ++i) { operator()(); }
    }

    //
    //  xoshiro256**
    //
    inline constexpr Xoshiro256StarStar::result_type Xoshiro256StarStar::operator()() noexcept
    {
        const std::uint64_t result = detail::RotL(s_[1] * 5, 7) * 9;
        const std::uint64_t t = s_[1] << 17;
        s_[2] ^= s_[0];
        s_[3] ^= s_[1];
        s_[1] ^= s_[2];
        s_[0] ^= s_[3];
        s_[2] ^= t;
        s_[3] = detail::RotL(s_[3], 45);
        return result;
    }
 
    inline constexpr void Xoshiro256StarStar::jump() noexcept
    {
        constexpr std::uint64_t p[] = {
            0x180ec6d33cfd0aba, 0xd5a61266f0c9392c,
            0xa9582618e03fc9aa, 0x39abdc4529b1661c };
        jumpPoly(p);
    }
 
    inline constexpr void Xoshiro256StarStar::longJump() noexcept
    {
        constexpr std::uint64_t p[] = {
            0x76e15d3efefdcbbf, 0xc5004e441c522fb3,
            0x77710069854ee241, 0x39109bb02acbe635 };
        jumpPoly(p);
    }

    //
    //  xoroshiro128**
    //
    inline constexpr Xoroshiro128StarStar::result_type Xoroshiro128StarStar::operator()() noexcept
    {
        const std::uint64_t s0 = s_[0];
        std::uint64_t s1 = s_[1];
        const std::uint64_t result = detail::RotL(s0 * 5, 7) * 9;
        s1 ^= s0;
        s_[0] = detail::RotL(s0, 24) ^ s1 ^ (s1 << 16);
        s_[1] = detail::RotL(s1, 37);
        return result;
    }
 
    inline constexpr void Xoroshiro128StarStar::jump() noexcept
    {
        constexpr std::uint64_t p[] = { 0xdf900294d8f554a5, 0x170865df4b3201fc };
        jumpPoly(p);
    }
 
    inline constexpr void Xoroshiro128StarStar::longJump() noexcept
    {
        constexpr std::uint64_t p[] = { 0xd2a98b26625eee7b, 0xdddf9b1090aa7ac1 };
        jumpPoly(p);
    }

    //
    //  xoshiro128**
    //
    inline constexpr Xoshiro128StarStar::result_type Xoshiro128StarStar::operator()() noexcept
    {
        const std::uint32_t result = detail::RotL(s_[1] * 5, 7) * 9;
        const std::uint32_t t = s_[1] << 9;
        s_[2] ^= s_[0];
        s_[3] ^= s_[1];
        s_[1] ^= s_[2];
        s_[0] ^= s_[3];
        s_[2] ^= t;
        s_[3] = detail::RotL(s_[3], 11);
        return result;
    }
 
    inline constexpr void Xoshiro128StarStar::jump() noexcept
    {
        constexpr std::uint32_t p[] = { 0x8764000bu, 0xf542d2d3u, 0x6fa035c3u, 0x77f2db5bu };
        jumpPoly(p);
    }
 
    inline constexpr void Xoshiro128StarStar::longJump() noexcept
    {
        constexpr std::uint32_t p[] = { 0xb523952eu, 0x0b6f099fu, 0xccf5a0efu, 0x1c580662u };
        jumpPoly(p);
    }

    //
    //  xoroshiro64**
    //
    inline constexpr Xoroshiro64StarStar::result_type Xoroshiro64StarStar::operator()() noexcept
    {
        const std::uint32_t s0 = s_[0];
        std::uint32_t s1 = s_[1];
 
        const std::uint32_t result = detail::RotL(s0 * 0x9E3779BB, 5) * 5;
 
        s1 ^= s0;
        s_[0] = detail::RotL(s0, 26) ^ s1 ^ (s1 << 9);
        s_[1] = detail::RotL(s1, 13);
 
        return result;
    }

    //
    //  SFC64 (Small Fast Counter)
    //
    inline constexpr SFC64::SFC64(const std::uint64_t seed) noexcept
        : Base()
    {
        // 使用 SplitMix64 播种 + 12 轮预热
        SplitMix64 sm{ seed };
        s_[0] = sm();
        s_[1] = sm();
        s_[2] = sm();
        s_[3] = 1;
        // 全零状态会导致输出可预测，强制修正
        if ((s_[0] | s_[1] | s_[2]) == 0) s_[0] = 0x9E3779B97F4A7C15ULL;
        for (int i = 0; i < 12; ++i) { operator()(); }
    }
 
    template <class SeedSeq, std::enable_if_t<!std::is_same_v<std::decay_t<SeedSeq>, SFC64>>*>
    inline constexpr SFC64::SFC64(SeedSeq& seq)
        : Base()
    {
        std::array<std::uint32_t, 8> seeds;
        seq.generate(seeds.begin(), seeds.end());
        s_[0] = (static_cast<std::uint64_t>(seeds[0]) << 32) | seeds[1];
        s_[1] = (static_cast<std::uint64_t>(seeds[2]) << 32) | seeds[3];
        s_[2] = (static_cast<std::uint64_t>(seeds[4]) << 32) | seeds[5];
        s_[3] = 1;
        // 全零状态会导致输出可预测，强制修正
        if ((s_[0] | s_[1] | s_[2]) == 0) s_[0] = 0x9E3779B97F4A7C15ULL;
        // 与种子构造函数一致：12 轮预热
        for (int i = 0; i < 12; ++i) { operator()(); }
    }
 
    inline constexpr SFC64::result_type SFC64::operator()() noexcept
    {
        const std::uint64_t tmp = s_[0] + s_[1] + s_[3]++;
        s_[0] = s_[1] ^ (s_[1] >> 11);
        s_[1] = s_[2] + (s_[2] << 3);
        s_[2] = detail::RotL(s_[2], 24) + tmp;
        return tmp;
    }

    //
    //  RomuDuoJr
    //
    inline constexpr RomuDuoJr::result_type RomuDuoJr::operator()() noexcept
    {
        const std::uint64_t xp = s_[0];
        s_[0] = 15241094284759029579ULL * s_[1];
        s_[1] = detail::RotL(s_[1] - xp, 27);
        return xp;
    }

    //
    //  多流接口（并行计算）
    //
 
    // 从同一种子创建第 streamId 个不重叠子序列的引擎
    // 每个流之间间隔 2^128 步（xoshiro256）或 2^64 步（xoroshiro128/xoshiro128）
    // 注意：Xoroshiro64 系列无 jump 函数，不支持多流
    namespace detail
    {
        template <class Engine, class = void>
        struct HasJump : std::false_type {};
        template <class Engine>
        struct HasJump<Engine, std::void_t<decltype(std::declval<Engine&>().jump())>> : std::true_type {};
 
        template <class Engine, class = void>
        struct HasLongJump : std::false_type {};
        template <class Engine>
        struct HasLongJump<Engine, std::void_t<decltype(std::declval<Engine&>().longJump())>> : std::true_type {};
    }
 
    namespace detail
    {
        // 字符类型检测（char/wchar_t/char16_t/char32_t，C++20+ 追加 char8_t）
        template <class T>
        struct is_character : std::bool_constant<
            std::is_same_v<T, char>
            || std::is_same_v<T, wchar_t>
            || std::is_same_v<T, char16_t>
            || std::is_same_v<T, char32_t>
#   if defined(__cpp_char8_t) || (defined(_MSVC_LANG) && _MSVC_LANG >= 202002L)
            || std::is_same_v<T, char8_t>
#   endif
        > {};
 
        template <class T>
        inline constexpr bool is_character_v = is_character<T>::value;
 
        // 检测 It 是否为 random_access 迭代器（void_t 包装避免硬错误）
        template <class It, class = void>
        struct is_random_access_iterator : std::false_type {};
 
        template <class It>
        struct is_random_access_iterator<It, std::void_t<
            typename std::iterator_traits<It>::iterator_category>>
            : std::is_base_of<std::random_access_iterator_tag,
                typename std::iterator_traits<It>::iterator_category> {};
 
        // 检测 It 是否为 input_iterator（正向检测，自动排除 output_iterator_tag）
        template <class It, class = void>
        struct is_input_iterator : std::false_type {};
 
        template <class It>
        struct is_input_iterator<It, std::void_t<
            typename std::iterator_traits<It>::iterator_category>>
            : std::is_base_of<std::input_iterator_tag,
                typename std::iterator_traits<It>::iterator_category> {};
 
        template <class It>
        inline constexpr bool is_random_access_iterator_v =
            is_random_access_iterator<It>::value;
 
        template <class It>
        inline constexpr bool is_input_iterator_v =
            is_input_iterator<It>::value;
 
        // 检测 C 是否为 random_access 容器
        template <class C, class = void>
        struct is_random_access_container : std::false_type {};
 
        template <class C>
        struct is_random_access_container<C, std::void_t<
            decltype(std::begin(std::declval<C&>())),
            decltype(std::end(std::declval<C&>()))>>
            : is_random_access_iterator<decltype(std::begin(std::declval<C&>()))> {};
 
        template <class C>
        inline constexpr bool is_random_access_container_v =
            is_random_access_container<C>::value;
 
        template <class Engine>
        [[nodiscard]]
        inline std::uint64_t Generate64Bits(Engine& engine)
        {
            if (sizeof(typename Engine::result_type) >= 8)
            {
                return static_cast<std::uint64_t>(engine());
            }
            const std::uint64_t lo = static_cast<std::uint64_t>(engine());
            const std::uint64_t hi = static_cast<std::uint64_t>(engine());
            return (hi << 32) | lo;
        }
 
        // 检测 *first = T 合法性 + T 为数值类型（RandFill 用）
        template <class It, class T, class = void>
        struct is_rand_fillable : std::false_type {};
 
        template <class It, class T>
        struct is_rand_fillable<It, T, std::void_t<
            decltype(*std::declval<It&>() = std::declval<T>())
        >> : std::bool_constant<
            std::is_integral_v<T> || std::is_floating_point_v<T>
        > {};
 
        template <class It, class T>
        inline constexpr bool is_rand_fillable_v = is_rand_fillable<It, T>::value;
 
        // 检测 state_type 是否为可索引容器（排除标量如 SplitMix64 的 uint64_t）
        template <class S, class = void>
        struct is_indexable_state : std::false_type {};
 
        template <class S>
        struct is_indexable_state<S, std::void_t<
            decltype(std::declval<const S&>().size()),
            decltype(std::declval<S&>()[std::size_t{}]),
            typename S::value_type
        >> : std::is_same<
            decltype(std::declval<const S&>().size()),
            std::size_t> {};
 
        template <class S>
        inline constexpr bool is_indexable_state_v = is_indexable_state<S>::value;
 
        // 可序列化引擎检测（serialize/deserialize/state_type + state_type 为可索引容器）
        template <class E, class = void>
        struct is_serializable_engine : std::false_type {};
 
        template <class E>
        struct is_serializable_engine<E, std::void_t<
            decltype(std::declval<const E&>().serialize()),
            decltype(std::declval<E&>().deserialize(
                std::declval<typename E::state_type>())),
            typename E::state_type
        >> : std::bool_constant<
            std::is_same_v<
                decltype(std::declval<const E&>().serialize()),
                typename E::state_type>
            && is_indexable_state_v<typename E::state_type>
        > {};
 
        template <class E>
        inline constexpr bool is_serializable_engine_v = is_serializable_engine<E>::value;
    }
 
    template <class Engine, std::enable_if_t<detail::HasJump<Engine>::value>* = nullptr>
    [[nodiscard]]
    inline constexpr Engine MakeStreamEngine(std::uint64_t streamId, std::uint64_t seed = DefaultSeed)
    {
        Engine rng{ seed };
        if constexpr (detail::HasLongJump<Engine>::value)
        {
            const std::uint64_t longJumps = streamId >> 32;
            const std::uint64_t shortJumps = streamId & 0xFFFFFFFFULL;
            for (std::uint64_t i = 0; i < longJumps; ++i)
                rng.longJump();
            for (std::uint64_t i = 0; i < shortJumps; ++i)
                rng.jump();
        }
        else
        {
            for (std::uint64_t i = 0; i < streamId; ++i)
                rng.jump();
        }
        return rng;
    }

    //
    //  便捷工具函数
    //
 
    // 生成非确定性的 64 位种子（优先硬件 RNG，用于统计 PRNG 播种）
    // 优先级链：RDRAND (x86_64) → detail::GetOsEntropyBytes → std::random_device → 时间戳回退
    [[nodiscard]]
    inline std::uint64_t RandomSeed()
    {
        std::uint64_t hw;
        if (detail::HardwareRand64(hw))
            return hw;
        if (detail::GetOsEntropyBytes(&hw, sizeof(hw)))
            return hw;
        std::random_device rd;
        try
        {
            return (static_cast<std::uint64_t>(rd()) << 32) | rd();
        }
        catch (...)
        {
            // 最终兜底：多维熵源（非密码学，仅保证 RandomSeed 永不抛异常，且防止 MSVC 15.6ms 时钟窗口下并发种子碰撞）
            const auto t1 = std::chrono::high_resolution_clock::now().time_since_epoch().count();
            const auto t2 = std::chrono::steady_clock::now().time_since_epoch().count();
            const auto threadId = std::hash<std::thread::id>{}(std::this_thread::get_id());
            static std::atomic<std::uint64_t> counter{0};
            std::uint64_t stackVar = 0;
            const std::uint64_t addr = reinterpret_cast<std::uint64_t>(&stackVar);
 
            const std::uint64_t rawSeed = static_cast<std::uint64_t>(t1) ^ static_cast<std::uint64_t>(t2)
                                          ^ threadId ^ addr ^ counter.fetch_add(1, std::memory_order_relaxed);
            SplitMix64 sm{ rawSeed };
            return sm();
        }
    }
 
    // 默认线程局部引擎，使用 RandomSeed() 播种（含 RDRAND → OS API → random_device → 时间戳回退链）
    [[nodiscard]]
    inline Xoshiro256StarStar& DefaultEngine()
    {
        thread_local Xoshiro256StarStar engine{ RandomSeed() };
        return engine;
    }

    inline void ResetThreadLocalEngine()
    {
        DefaultEngine() = Xoshiro256StarStar{ RandomSeed() };
    }


    inline void SecureRandomBytes(void* buf, std::size_t n)
    {
        if (n == 0) return;
        if (!detail::GetOsEntropyBytes(buf, n))
            throw std::runtime_error("SecureRandomBytes: OS entropy source failed");
    }

    [[nodiscard]]
    inline std::uint64_t SecureSeed()
    {
        std::uint64_t seed;
        SecureRandomBytes(&seed, sizeof(seed));
        return seed;
    }

    [[nodiscard]]
    inline bool IsOsCryptoEntropyAvailable() noexcept
    {
        return detail::HasCryptoGradeOsEntropy();
    }

    //
    //  ChaCha20 (RFC 8439) — CSPRNG 引擎实现
    //
    //  状态矩阵布局（16 × uint32，常数省略存于 m_state[0..11]）：
    //    0  1  2  3      "expa"  "nd 3"  "2-by"  "te k"   ← 常数（generateBlock 时补齐）
    //    4  5  6  7      key[0]  key[1]  key[2]  key[3]   ← m_state[0..3]
    //    8  9 10 11      key[4]  key[5]  key[6]  key[7]   ← m_state[4..7]
    //   12 13 14 15      ctr    nonce[0] nonce[1] nonce[2]← m_state[8..11]
    //
    //  生成流程：operator() → reseedIfNecessary → (缓存耗尽时)generateBlock → 取 8 字节
    //
 
    inline ChaCha20::ChaCha20(ChaCha20&& other) noexcept
        : m_state(other.m_state),
          m_buffer(other.m_buffer),
          m_bufferPos(other.m_bufferPos),
          m_bytesSinceReseed(other.m_bytesSinceReseed),
          m_autoReseed(other.m_autoReseed)
    {
        detail::SecureWipe(other.m_state.data(), sizeof(other.m_state));
        detail::SecureWipe(other.m_buffer.data(), sizeof(other.m_buffer));
        other.reseed();
    }
 
    inline ChaCha20& ChaCha20::operator=(ChaCha20&& other) noexcept
    {
        if (this != &other)
        {
            detail::SecureWipe(m_state.data(), sizeof(m_state));
            detail::SecureWipe(m_buffer.data(), sizeof(m_buffer));
 
            m_state = other.m_state;
            m_buffer = other.m_buffer;
            m_bufferPos = other.m_bufferPos;
            m_bytesSinceReseed = other.m_bytesSinceReseed;
            m_autoReseed = other.m_autoReseed;
 
            detail::SecureWipe(other.m_state.data(), sizeof(other.m_state));
            detail::SecureWipe(other.m_buffer.data(), sizeof(other.m_buffer));
            other.reseed();
        }
        return *this;
    }
 
    inline ChaCha20::~ChaCha20() noexcept
    {
        detail::SecureWipe(m_state.data(), sizeof(m_state));
        detail::SecureWipe(m_buffer.data(), sizeof(m_buffer));
    }
 
    // 构造方式 1：从 OS 熵自动播种（密码学安全，默认）
    inline ChaCha20::ChaCha20()
        : m_state{}, m_buffer{}, m_bufferPos(64), m_bytesSinceReseed(0), m_autoReseed(true)
    {
        reseed();  // 从 OS 熵获取 key + nonce，重置 counter
    }
 
    // 构造方式 2：显式种子（仅测试/复现，非密码学安全）
    // 用 SplitMix64 将 64-bit 种子扩展为 32 字节 key + 12 字节 nonce
    inline ChaCha20::ChaCha20(const std::uint64_t seed)
        : m_state{}, m_buffer{}, m_bufferPos(64), m_bytesSinceReseed(0), m_autoReseed(false)
    {
        SplitMix64 sm{ seed };
        // key: 前 4 次 SplitMix64 输出，每次 8 字节按小端序拆为 2 个 uint32
        for (int i = 0; i < 4; ++i)
        {
            const std::uint64_t v = sm();
            m_state[i * 2]     = static_cast<std::uint32_t>(v);
            m_state[i * 2 + 1] = static_cast<std::uint32_t>(v >> 32);
        }
        // nonce: 第 5 次输出（8 字节）+ 第 6 次输出低 4 字节（丢弃高 4 字节）
        {
            const std::uint64_t v5 = sm();
            m_state[9]  = static_cast<std::uint32_t>(v5);
            m_state[10] = static_cast<std::uint32_t>(v5 >> 32);
        }
        m_state[11] = static_cast<std::uint32_t>(sm());
        m_state[8]  = 0;  // counter 初值 = 0
    }
 
    // 构造方式 3：直接指定 key + nonce + counter
    inline ChaCha20::ChaCha20(const std::uint8_t* key, std::size_t keyLen,
                              const std::uint8_t* nonce, std::size_t nonceLen,
                              const std::uint32_t counter)
        : m_state{}, m_buffer{}, m_bufferPos(64), m_bytesSinceReseed(0), m_autoReseed(false)
    {
        if (keyLen != 32)
            throw std::invalid_argument("ChaCha20: key must be 32 bytes");
        if (nonceLen != 12)
            throw std::invalid_argument("ChaCha20: nonce must be 12 bytes");
        // key → m_state[0..7]（小端序）
        for (int i = 0; i < 8; ++i)
        {
            m_state[i] = static_cast<std::uint32_t>(key[i * 4])
                       | (static_cast<std::uint32_t>(key[i * 4 + 1]) << 8)
                       | (static_cast<std::uint32_t>(key[i * 4 + 2]) << 16)
                       | (static_cast<std::uint32_t>(key[i * 4 + 3]) << 24);
        }
        // nonce → m_state[9..11]（小端序）
        for (int i = 0; i < 3; ++i)
        {
            m_state[9 + i] = static_cast<std::uint32_t>(nonce[i * 4])
                           | (static_cast<std::uint32_t>(nonce[i * 4 + 1]) << 8)
                           | (static_cast<std::uint32_t>(nonce[i * 4 + 2]) << 16)
                           | (static_cast<std::uint32_t>(nonce[i * 4 + 3]) << 24);
        }
        m_state[8] = counter;  // counter
    }
 
    // 生成一个 ChaCha20 block（64 字节）填充 m_buffer
    inline void ChaCha20::generateBlock()
    {
        if (m_state[8] == 0xFFFFFFFFU)
        {
            throw std::overflow_error("ChaCha20: 32-bit block counter overflow");
        }
 
        // 构造完整 16-word 状态：常数 + key + counter + nonce
        std::array<std::uint32_t, 16> state{};
        state[0] = detail::ChaCha20Constants[0];
        state[1] = detail::ChaCha20Constants[1];
        state[2] = detail::ChaCha20Constants[2];
        state[3] = detail::ChaCha20Constants[3];
        for (int i = 0; i < 8; ++i) state[4 + i] = m_state[i];  // key
        state[12] = m_state[8];                                  // counter
        state[13] = m_state[9];                                  // nonce[0]
        state[14] = m_state[10];                                 // nonce[1]
        state[15] = m_state[11];                                 // nonce[2]
 
        std::array<std::uint32_t, 16> working = state;
 
        // 20 轮 = 10 次 double-round（列轮 + 对角轮）
        for (int i = 0; i < 10; ++i)
        {
            // 列轮 QR 顺序：(0,4,8,12) (1,5,9,13) (2,6,10,14) (3,7,11,15)
            detail::ChaCha20QuarterRound(working[0],  working[4],  working[8],  working[12]);
            detail::ChaCha20QuarterRound(working[1],  working[5],  working[9],  working[13]);
            detail::ChaCha20QuarterRound(working[2],  working[6],  working[10], working[14]);
            detail::ChaCha20QuarterRound(working[3],  working[7],  working[11], working[15]);
            // 对角轮 QR 顺序：(0,5,10,15) (1,6,11,12) (2,7,8,13) (3,4,9,14)
            detail::ChaCha20QuarterRound(working[0],  working[5],  working[10], working[15]);
            detail::ChaCha20QuarterRound(working[1],  working[6],  working[11], working[12]);
            detail::ChaCha20QuarterRound(working[2],  working[7],  working[8],  working[13]);
            detail::ChaCha20QuarterRound(working[3],  working[4],  working[9],  working[14]);
        }
 
        // 加初始状态后按小端序输出 64 字节到 m_buffer
        for (int i = 0; i < 16; ++i)
        {
            const std::uint32_t v = working[i] + state[i];
            m_buffer[i * 4 + 0] = static_cast<std::uint8_t>(v);
            m_buffer[i * 4 + 1] = static_cast<std::uint8_t>(v >> 8);
            m_buffer[i * 4 + 2] = static_cast<std::uint8_t>(v >> 16);
            m_buffer[i * 4 + 3] = static_cast<std::uint8_t>(v >> 24);
        }
 
        ++m_state[8];   // 递增 counter（2^20 字节阈值远早于 2^32 回绕，自动 reseed 防止复用）
        m_bufferPos = 0;
    }
 
    // 自上次 reseed 以来输出字节数达到阈值时自动 reseed（前向安全）
    inline void ChaCha20::reseedIfNecessary()
    {
        if (m_autoReseed && m_bytesSinceReseed >= detail::ChaCha20ReseedThreshold)
            reseed();
    }
 
    // 从 OS 熵重新播种：32 字节新 key + 12 字节新 nonce，重置 counter=0、缓存标记耗尽
    inline void ChaCha20::reseed()
    {
        std::array<std::uint8_t, 44> seed;  // 32(key) + 12(nonce)
        SecureRandomBytes(seed.data(), seed.size());
        // key → m_state[0..7]（小端序）
        for (int i = 0; i < 8; ++i)
        {
            m_state[i] = static_cast<std::uint32_t>(seed[i * 4])
                       | (static_cast<std::uint32_t>(seed[i * 4 + 1]) << 8)
                       | (static_cast<std::uint32_t>(seed[i * 4 + 2]) << 16)
                       | (static_cast<std::uint32_t>(seed[i * 4 + 3]) << 24);
        }
        // nonce → m_state[9..11]（小端序）
        for (int i = 0; i < 3; ++i)
        {
            m_state[9 + i] = static_cast<std::uint32_t>(seed[32 + i * 4])
                           | (static_cast<std::uint32_t>(seed[32 + i * 4 + 1]) << 8)
                           | (static_cast<std::uint32_t>(seed[32 + i * 4 + 2]) << 16)
                           | (static_cast<std::uint32_t>(seed[32 + i * 4 + 3]) << 24);
        }
        m_state[8] = 0;            // counter 重置
        m_bufferPos = 64;          // 强制下次 operator() 触发新 block
        m_bytesSinceReseed = 0;
        detail::SecureWipe(seed.data(), seed.size());   // 擦除栈上密钥材料
        detail::SecureWipe(m_buffer.data(), m_buffer.size()); // 擦除旧 keystream
    }
 
    // 生成一个 64-bit 随机数（从缓存取 8 字节，缓存耗尽时生成新 block）
    inline ChaCha20::result_type ChaCha20::operator()()
    {
        reseedIfNecessary();
        if (m_bufferPos == 64)
            generateBlock();
        // 从缓存取 8 字节，小端序组装为 uint64_t
        std::uint64_t result = 0;
        for (int i = 0; i < 8; ++i)
            result |= static_cast<std::uint64_t>(m_buffer[m_bufferPos + i]) << (8 * i);
        m_bufferPos += 8;
        m_bytesSinceReseed += 8;
        return result;
    }
 
    inline void ChaCha20::discard(const unsigned long long n)
    {
        for (unsigned long long i = 0; i < n; ++i) operator()();
    }
 
    // 重置默认引擎的种子（用于测试复现）
    inline void Reseed(std::uint64_t seed)
    {
        DefaultEngine() = Xoshiro256StarStar{ seed };
    }
 
    // 重置为真随机种子
    inline void ReseedRandom()
    {
        DefaultEngine() = Xoshiro256StarStar{ RandomSeed() };
    }


    template <class T = int, std::enable_if_t<std::is_integral_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandInt(T min, T max)
    {
        return RandInt(DefaultEngine(), min, max);
    }

    template <class T = int, std::enable_if_t<std::is_integral_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandInt(T max)
    {
        assert(max >= T{0});
        return RandInt<T>(T{0}, max);
    }

    template <class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandReal(T min = T{0}, T max = T{1})
    {
        return RandReal(DefaultEngine(), min, max);
    }

    template <class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandCanonical() noexcept
    {
        return RandCanonical<T>(DefaultEngine());
    }

    [[nodiscard]]
    inline double RandCanonicalDouble() noexcept
    {
        return RandCanonical<double>();
    }

    [[nodiscard]]
    inline float RandCanonicalFloat() noexcept
    {
        return RandCanonical<float>();
    }

    [[nodiscard]]
    inline bool RandBool(double p = 0.5)
    {
        assert(std::isfinite(p) && p >= 0.0 && p <= 1.0);
        std::bernoulli_distribution dist(p);
        return dist(DefaultEngine());
    }

    template <class Engine>
    [[nodiscard]]
    inline bool RandBool(Engine& engine, double p = 0.5)
    {
        assert(std::isfinite(p) && p >= 0.0 && p <= 1.0);
        std::bernoulli_distribution dist(p);
        return dist(engine);
    }

    [[nodiscard]]
    inline bool RandBernoulli(double p = 0.5)
    {
        assert(p >= 0.0 && p <= 1.0);
        return RandBool(p);
    }

    template <class Engine>
    [[nodiscard]]
    inline bool RandBernoulli(Engine& engine, double p = 0.5)
    {
        assert(p >= 0.0 && p <= 1.0);
        return RandBool(engine, p);
    }

    template <class CharT,
        std::enable_if_t<detail::is_character_v<CharT>>* = nullptr>
    [[nodiscard]]
    inline CharT RandChar(CharT min, CharT max)
    {
        assert(min <= max);
        using IntT = std::int64_t;
        std::uniform_int_distribution<IntT> dist(
            static_cast<IntT>(min), static_cast<IntT>(max));
        return static_cast<CharT>(dist(DefaultEngine()));
    }

    template <class CharT,
        std::enable_if_t<detail::is_character_v<CharT>>* = nullptr>
    [[nodiscard]]
    inline CharT RandChar(CharT max)
    {
        return RandChar<CharT>(CharT{}, max);
    }

    template <class CharT, class Engine,
        std::enable_if_t<detail::is_character_v<CharT>>* = nullptr>
    [[nodiscard]]
    inline CharT RandChar(Engine& engine, CharT min, CharT max)
    {
        assert(min <= max);
        using IntT = std::int64_t;
        std::uniform_int_distribution<IntT> dist(
            static_cast<IntT>(min), static_cast<IntT>(max));
        return static_cast<CharT>(dist(engine));
    }

    template <class CharT, class Engine,
        std::enable_if_t<detail::is_character_v<CharT>>* = nullptr>
    [[nodiscard]]
    inline CharT RandChar(Engine& engine, CharT max)
    {
        return RandChar<CharT>(engine, CharT{}, max);
    }

    //
    //  RandChar / RandString 预设字符集
    //
    //  提供常用字符集枚举，避免手写 ASCII 范围或字符串。
    //
 
    // 预设字符集枚举
    enum class CharSet
    {
        Alphanumeric,  // [A-Za-z0-9]    62 个
        Alpha,         // [A-Za-z]        52 个
        Lower,         // [a-z]           26 个
        Upper,         // [A-Z]           26 个
        Digit,         // [0-9]           10 个
        Hex,           // [0-9a-f]        16 个
        Printable,     // [!-~]           94 个可打印 ASCII
        Base64,        // [A-Za-z0-9+/]   64 个（RFC 4648 §4 标准变体）
        Base64UrlSafe, // [A-Za-z0-9-_]   64 个（RFC 4648 §5 URL-safe 变体）
    };
 
    namespace detail
    {
        // RandSample 分支选择阈值：n·K < size 时用 hash-set（实测交叉点 n≈N/127，K=64 留 2× 裕度）
        inline constexpr std::uint64_t HashSetThresholdK = 64;
 
        // 返回预设字符集的字符串视图（零拷贝，指向静态存储）
        [[nodiscard]]
        inline std::string_view CharSetString(CharSet cs) noexcept
        {
            switch (cs)
            {
            case CharSet::Alphanumeric:
                return "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789";
            case CharSet::Alpha:
                return "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz";
            case CharSet::Lower:
                return "abcdefghijklmnopqrstuvwxyz";
            case CharSet::Upper:
                return "ABCDEFGHIJKLMNOPQRSTUVWXYZ";
            case CharSet::Digit:
                return "0123456789";
            case CharSet::Hex:
                return "0123456789abcdef";
            case CharSet::Printable:
                return "!\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\]^_`abcdefghijklmnopqrstuvwxyz{|}~";
            case CharSet::Base64:
                return "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/";
            case CharSet::Base64UrlSafe:
                return "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789-_";
            }
            return "";
        }
    }

    [[nodiscard]]
    inline char RandChar(CharSet cs)
    {
        const auto charset = detail::CharSetString(cs);
        if (charset.empty())
            throw std::invalid_argument("RandChar: charset is empty");
        auto& rng = DefaultEngine();
        std::uniform_int_distribution<std::size_t> dist(0, charset.size() - 1);
        return charset[dist(rng)];
    }

    template <class Engine>
    [[nodiscard]]
    inline char RandChar(Engine& engine, CharSet cs)
    {
        const auto charset = detail::CharSetString(cs);
        if (charset.empty())
            throw std::invalid_argument("RandChar: charset is empty");
        std::uniform_int_distribution<std::size_t> dist(0, charset.size() - 1);
        return charset[dist(engine)];
    }


    template <class Container,
        std::enable_if_t<detail::is_random_access_container_v<Container>>* = nullptr>
    [[nodiscard]]
    inline decltype(auto) RandElement(Container& c)
    {
        if (std::empty(c))
            throw std::invalid_argument("RandElement: empty container");
        return c[RandInt<std::size_t>(static_cast<std::size_t>(std::size(c) - 1))];
    }

    template <class Container,
        std::enable_if_t<detail::is_random_access_container_v<std::decay_t<Container>>>* = nullptr>
    [[nodiscard]]
    inline typename std::iterator_traits<decltype(std::begin(std::declval<Container&>()))>::value_type RandElement(Container&& c)
    {
        if (std::empty(c))
            throw std::invalid_argument("RandElement: empty container");
        return c[RandInt<std::size_t>(static_cast<std::size_t>(std::size(c) - 1))];
    }

    template <class It,
        std::enable_if_t<detail::is_random_access_iterator_v<It>>* = nullptr>
    [[nodiscard]]
    inline It RandElement(It first, It last)
    {
        using Diff = typename std::iterator_traits<It>::difference_type;
        const Diff n = std::distance(first, last);
        if (n <= 0)
            throw std::invalid_argument("RandElement: empty range");
        return std::next(first, RandInt<Diff>(Diff{0}, n - 1));
    }

    template <class It,
        std::enable_if_t<detail::is_input_iterator_v<It>
            && !detail::is_random_access_iterator_v<It>>* = nullptr>
    [[nodiscard]]
    inline typename std::iterator_traits<It>::value_type RandElement(It first, It last)
    {
        if (first == last)
            throw std::invalid_argument("RandElement: empty range");
        typename std::iterator_traits<It>::value_type selected = *first;
        ++first;
        for (typename std::iterator_traits<It>::difference_type i = 1;
            first != last; ++first, ++i)
        {
            if (RandInt<typename std::iterator_traits<It>::difference_type>(0, i) == 0)
                selected = *first;
        }
        return selected;
    }

    template <class It, class Engine,
        std::enable_if_t<detail::is_random_access_iterator_v<It>>* = nullptr>
    [[nodiscard]]
    inline It RandElement(Engine& engine, It first, It last)
    {
        using Diff = typename std::iterator_traits<It>::difference_type;
        const Diff n = std::distance(first, last);
        if (n <= 0)
            throw std::invalid_argument("RandElement: empty range");
        return std::next(first, RandInt<Diff>(engine, Diff{0}, n - 1));
    }

    template <class It, class Engine,
        std::enable_if_t<detail::is_input_iterator_v<It>
            && !detail::is_random_access_iterator_v<It>>* = nullptr>
    [[nodiscard]]
    inline typename std::iterator_traits<It>::value_type RandElement(Engine& engine, It first, It last)
    {
        if (first == last)
            throw std::invalid_argument("RandElement: empty range");
        typename std::iterator_traits<It>::value_type selected = *first;
        ++first;
        for (typename std::iterator_traits<It>::difference_type i = 1;
            first != last; ++first, ++i)
        {
            if (RandInt<typename std::iterator_traits<It>::difference_type>(
                engine, typename std::iterator_traits<It>::difference_type{0}, i) == 0)
                selected = *first;
        }
        return selected;
    }
 


    template <class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandNormal(T mean = T{0}, T stddev = T{1})
    {
        if (!std::isfinite(mean) || !std::isfinite(stddev) || stddev <= T{0})
            throw std::invalid_argument("RandNormal: invalid mean or stddev");
        std::normal_distribution<T> dist(mean, stddev);
        return dist(DefaultEngine());
    }

    template <class Engine, class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandNormal(Engine& engine, T mean = T{0}, T stddev = T{1})
    {
        if (!std::isfinite(mean) || !std::isfinite(stddev) || stddev <= T{0})
            throw std::invalid_argument("RandNormal: invalid mean or stddev");
        std::normal_distribution<T> dist(mean, stddev);
        return dist(engine);
    }

    template <class Container,
        std::enable_if_t<detail::is_random_access_container_v<Container>>* = nullptr>
    inline void RandShuffle(Container&& c)
    {
        std::shuffle(c.begin(), c.end(), DefaultEngine());
    }

    template <class It, class T,
        std::enable_if_t<detail::is_rand_fillable_v<It, T>>* = nullptr>
    inline void RandFill(It first, It last, T min, T max)
    {
        assert(min <= max);
        auto& rng = DefaultEngine();
        if constexpr (std::is_integral_v<T>)
        {
            std::uniform_int_distribution<T> dist(min, max);
            for (; first != last; ++first) *first = dist(rng);
        }
        else
        {
            std::uniform_real_distribution<T> dist(min, max);
            for (; first != last; ++first) *first = dist(rng);
        }
    }

    template <class It, class T, class Engine,
        std::enable_if_t<detail::is_rand_fillable_v<It, T>>* = nullptr>
    inline void RandFill(Engine& engine, It first, It last, T min, T max)
    {
        assert(min <= max);
        if constexpr (std::is_integral_v<T>)
        {
            std::uniform_int_distribution<T> dist(min, max);
            for (; first != last; ++first) *first = dist(engine);
        }
        else
        {
            std::uniform_real_distribution<T> dist(min, max);
            for (; first != last; ++first) *first = dist(engine);
        }
    }

    template <class T,
        std::enable_if_t<std::is_integral_v<T>>* = nullptr>
    [[nodiscard]]
    inline std::vector<T> RandVector(T min, T max, std::size_t n)
    {
        assert(min <= max);
        std::vector<T> v;
        v.reserve(n);
        auto& rng = DefaultEngine();
        std::uniform_int_distribution<T> dist(min, max);
        for (std::size_t i = 0; i < n; ++i)
            v.push_back(dist(rng));
        return v;
    }

    template <class T,
        std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline std::vector<T> RandVector(T min, T max, std::size_t n)
    {
        assert(min <= max);
        std::vector<T> v;
        v.reserve(n);
        auto& rng = DefaultEngine();
        std::uniform_real_distribution<T> dist(min, max);
        for (std::size_t i = 0; i < n; ++i)
            v.push_back(dist(rng));
        return v;
    }

    template <class T, class Engine,
        std::enable_if_t<std::is_integral_v<T>>* = nullptr>
    [[nodiscard]]
    inline std::vector<T> RandVector(Engine& engine, T min, T max, std::size_t n)
    {
        assert(min <= max);
        std::vector<T> v;
        v.reserve(n);
        std::uniform_int_distribution<T> dist(min, max);
        for (std::size_t i = 0; i < n; ++i)
            v.push_back(dist(engine));
        return v;
    }

    template <class T, class Engine,
        std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline std::vector<T> RandVector(Engine& engine, T min, T max, std::size_t n)
    {
        assert(min <= max);
        std::vector<T> v;
        v.reserve(n);
        std::uniform_real_distribution<T> dist(min, max);
        for (std::size_t i = 0; i < n; ++i)
            v.push_back(dist(engine));
        return v;
    }

    template <class WeightContainer>
    [[nodiscard]]
    inline typename WeightContainer::size_type RandWeighted(const WeightContainer& weights)
    {
        assert(!weights.empty() && std::all_of(weights.begin(), weights.end(), [](auto w) { return w >= 0; }) && std::any_of(weights.begin(), weights.end(), [](auto w) { return w > 0; }));
        using Size = typename WeightContainer::size_type;
        std::discrete_distribution<Size> dist(weights.begin(), weights.end());
        return dist(DefaultEngine());
    }

    template <class Engine, class WeightContainer>
    [[nodiscard]]
    inline typename WeightContainer::size_type RandWeighted(Engine& engine, const WeightContainer& weights)
    {
        assert(!weights.empty() && std::all_of(weights.begin(), weights.end(), [](auto w) { return w >= 0; }) && std::any_of(weights.begin(), weights.end(), [](auto w) { return w > 0; }));
        using Size = typename WeightContainer::size_type;
        std::discrete_distribution<Size> dist(weights.begin(), weights.end());
        return dist(engine);
    }

    template <class IntType>
    [[nodiscard]]
    inline IntType RandWeighted(std::discrete_distribution<IntType>& dist)
    {
        return dist(DefaultEngine());
    }

    template <class Engine, class IntType>
    [[nodiscard]]
    inline IntType RandWeighted(Engine& engine, std::discrete_distribution<IntType>& dist)
    {
        return dist(engine);
    }

    template <class T, class Engine, std::enable_if_t<std::is_integral_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandInt(Engine& engine, T min, T max)
    {
        assert(min <= max);
        using DistType = std::conditional_t<(sizeof(T) < sizeof(short)),
            std::conditional_t<std::is_signed_v<T>, int, unsigned int>, T>;
        std::uniform_int_distribution<DistType> dist(static_cast<DistType>(min), static_cast<DistType>(max));
        return static_cast<T>(dist(engine));
    }

    template <typename T = double, class Engine,
              typename std::enable_if_t<std::is_floating_point_v<T>, int> = 0>
    [[nodiscard]] inline constexpr T RandCanonical(Engine& engine) noexcept
    {
        using ResultType = typename Engine::result_type;
        constexpr std::size_t Bits = sizeof(ResultType) * 8;
 
        if constexpr (std::is_same_v<T, double>)
        {
            if constexpr (Bits >= 64)
            {
                const std::uint64_t r = static_cast<std::uint64_t>(engine());
                return static_cast<double>(r >> 11) * 0x1.0p-53;
            }
            else
            {
                const std::uint64_t high = static_cast<std::uint64_t>(engine());
                const std::uint64_t low  = static_cast<std::uint64_t>(engine());
                const std::uint64_t r = (high << 32) | low;
                return static_cast<double>(r >> 11) * 0x1.0p-53;
            }
        }
        else if constexpr (std::is_same_v<T, float>)
        {
            if constexpr (Bits >= 64)
            {
                const std::uint64_t r = static_cast<std::uint64_t>(engine());
                return static_cast<float>(r >> 40) * 0x1.0p-24f;
            }
            else
            {
                const std::uint32_t r = static_cast<std::uint32_t>(engine());
                return static_cast<float>(r >> 8) * 0x1.0p-24f;
            }
        }
        else
        {
            return std::generate_canonical<T, std::numeric_limits<T>::digits>(engine);
        }
    }

    template <class T = double, class Engine, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandReal(Engine& engine, T min = T{0}, T max = T{1})
    {
        assert(std::isfinite(min) && std::isfinite(max) && min <= max);
        if (min == T{0} && max == T{1})
        {
            return RandCanonical<T>(engine);
        }
        std::uniform_real_distribution<T> dist(min, max);
        T val = dist(engine);
        if (val >= max) val = std::nextafter(max, min);
        return val;
    }

    //
    //  扩展便捷 API
    //

    template <class Container,
        std::enable_if_t<detail::is_random_access_container_v<Container>>* = nullptr>
    [[nodiscard]]
    inline auto RandSample(const Container& c, std::size_t n)
    {
        using T = typename std::iterator_traits<decltype(std::begin(c))>::value_type;
        using Size = std::size_t;
        std::vector<T> pool(std::begin(c), std::end(c));
        const Size size = pool.size();
        if (n >= size) return pool;
        auto& rng = DefaultEngine();
        for (Size i = 0; i < n; ++i)
        {
            std::uniform_int_distribution<Size> dist(i, size - 1);
            const Size j = dist(rng);
            auto tmp = std::move(pool[i]);
            pool[i] = std::move(pool[j]);
            pool[j] = std::move(tmp);
        }
        pool.resize(n);
        return pool;
    }
 
    // ============================================================
    // RandSample 迭代器版
    // 路径 1：随机访问迭代器 —— hash-set / 索引数组双分支
    // 路径 2：输入迭代器 —— reservoir sampling (Algorithm R, i+1 修复)
    // ============================================================
 
    // 路径 1：随机访问迭代器（hash-set / 索引数组双分支）
    template <class It,
        std::enable_if_t<detail::is_random_access_iterator_v<It>>* = nullptr>
    [[nodiscard]]
    inline std::vector<typename std::iterator_traits<It>::value_type>
    RandSample(It first, It last, typename std::iterator_traits<It>::difference_type n)
    {
        using Diff = typename std::iterator_traits<It>::difference_type;
        using T = typename std::iterator_traits<It>::value_type;
        const Diff size = std::distance(first, last);
        if (n <= 0 || size <= 0)
            return {};
        if (n >= size)
            return std::vector<T>(first, last);
 
        auto& rng = DefaultEngine();
 
        // 分支选择：n·K < size 时 hash-set 内存优（O(n)）；否则索引数组常数优（O(N)）
        const auto sizeU = static_cast<std::uint64_t>(size);
        // 线性阈值：n·K < size 时用 hash-set（实测交叉点 n≈N/127，K=64 留 2× 裕度）
        if (static_cast<std::uint64_t>(n) * detail::HashSetThresholdK < sizeU)
        {
            // hash-set 分支：O(n) 内存，O(n) 期望时间
            std::unordered_set<Diff> selected;
            selected.reserve(static_cast<std::size_t>(n));
            std::vector<T> result;
            result.reserve(static_cast<std::size_t>(n));
            while (result.size() < static_cast<std::size_t>(n))
            {
                std::uniform_int_distribution<Diff> dist(Diff{0}, static_cast<Diff>(sizeU - 1));
                const Diff idx = dist(rng);
                if (selected.insert(idx).second)
                    result.push_back(first[idx]);
            }
            return result;
        }
 
        // 索引数组分支：O(N) 内存，O(N) 时间，无碰撞
        std::vector<Diff> indices(static_cast<std::size_t>(size));
        for (Diff i = 0; i < size; ++i)
            indices[static_cast<std::size_t>(i)] = i;
 
        // Fisher-Yates 前 n 步：j ∈ [i, size-1]
        for (Diff i = 0; i < n; ++i)
        {
            std::uniform_int_distribution<Diff> dist(i, static_cast<Diff>(size - 1));
            const Diff j = dist(rng);
            std::swap(indices[static_cast<std::size_t>(i)],
                      indices[static_cast<std::size_t>(j)]);
        }
 
        std::vector<T> result;
        result.reserve(static_cast<std::size_t>(n));
        for (Diff i = 0; i < n; ++i)
            result.push_back(first[indices[static_cast<std::size_t>(i)]]);
        return result;
    }
 
    // 路径 2：输入迭代器（reservoir sampling, Algorithm R, i+1 修复）
    template <class It,
        std::enable_if_t<detail::is_input_iterator_v<It>
            && !detail::is_random_access_iterator_v<It>>* = nullptr>
    [[nodiscard]]
    inline std::vector<typename std::iterator_traits<It>::value_type>
    RandSample(It first, It last, typename std::iterator_traits<It>::difference_type n)
    {
        using Diff = typename std::iterator_traits<It>::difference_type;
        using T = typename std::iterator_traits<It>::value_type;
        if (n <= 0)
            return {};
 
        std::vector<T> reservoir;
        reservoir.reserve(static_cast<std::size_t>(n));
 
        // 填满蓄水池
        Diff i = 0;
        for (; i < n && first != last; ++i, ++first)
            reservoir.push_back(*first);
 
        if (first == last)
            return reservoir;  // 元素不足 n，返回全部
 
        // Algorithm R：第 i 个元素（i >= n，0-indexed）以 n/(i+1) 概率替换蓄水池随机位置
        // 关键：j ∈ [0, i]（闭区间），uniform_int_distribution(0, i) 正好是 [0, i] 闭区间
        auto& rng = DefaultEngine();
        for (; first != last; ++i, ++first)
        {
            std::uniform_int_distribution<Diff> dist(Diff{0}, i);
            const Diff j = dist(rng);
            if (j < n)
                reservoir[static_cast<std::size_t>(j)] = *first;
        }
        return reservoir;
    }
 
    // 引擎重载 —— 随机访问迭代器
    template <class It, class Engine,
        std::enable_if_t<detail::is_random_access_iterator_v<It>>* = nullptr>
    [[nodiscard]]
    inline std::vector<typename std::iterator_traits<It>::value_type>
    RandSample(Engine& engine, It first, It last, typename std::iterator_traits<It>::difference_type n)
    {
        using Diff = typename std::iterator_traits<It>::difference_type;
        using T = typename std::iterator_traits<It>::value_type;
        const Diff size = std::distance(first, last);
        if (n <= 0 || size <= 0)
            return {};
        if (n >= size)
            return std::vector<T>(first, last);
 
        const auto sizeU = static_cast<std::uint64_t>(size);
        // 线性阈值：n·K < size 时用 hash-set（实测交叉点 n≈N/127，K=64 留 2× 裕度）
        if (static_cast<std::uint64_t>(n) * detail::HashSetThresholdK < sizeU)
        {
            std::unordered_set<Diff> selected;
            selected.reserve(static_cast<std::size_t>(n));
            std::vector<T> result;
            result.reserve(static_cast<std::size_t>(n));
            while (result.size() < static_cast<std::size_t>(n))
            {
                std::uniform_int_distribution<Diff> dist(Diff{0}, static_cast<Diff>(sizeU - 1));
                const Diff idx = dist(engine);
                if (selected.insert(idx).second)
                    result.push_back(first[idx]);
            }
            return result;
        }
 
        std::vector<Diff> indices(static_cast<std::size_t>(size));
        for (Diff i = 0; i < size; ++i)
            indices[static_cast<std::size_t>(i)] = i;
 
        for (Diff i = 0; i < n; ++i)
        {
            std::uniform_int_distribution<Diff> dist(i, static_cast<Diff>(size - 1));
            const Diff j = dist(engine);
            std::swap(indices[static_cast<std::size_t>(i)],
                      indices[static_cast<std::size_t>(j)]);
        }
 
        std::vector<T> result;
        result.reserve(static_cast<std::size_t>(n));
        for (Diff i = 0; i < n; ++i)
            result.push_back(first[indices[static_cast<std::size_t>(i)]]);
        return result;
    }
 
    // 引擎重载 —— 输入迭代器（reservoir）
    template <class It, class Engine,
        std::enable_if_t<detail::is_input_iterator_v<It>
            && !detail::is_random_access_iterator_v<It>>* = nullptr>
    [[nodiscard]]
    inline std::vector<typename std::iterator_traits<It>::value_type>
    RandSample(Engine& engine, It first, It last, typename std::iterator_traits<It>::difference_type n)
    {
        using Diff = typename std::iterator_traits<It>::difference_type;
        using T = typename std::iterator_traits<It>::value_type;
        if (n <= 0)
            return {};
 
        std::vector<T> reservoir;
        reservoir.reserve(static_cast<std::size_t>(n));
 
        Diff i = 0;
        for (; i < n && first != last; ++i, ++first)
            reservoir.push_back(*first);
 
        if (first == last)
            return reservoir;
 
        // Algorithm R：j ∈ [0, i] 闭区间
        for (; first != last; ++i, ++first)
        {
            std::uniform_int_distribution<Diff> dist(Diff{0}, i);
            const Diff j = dist(engine);
            if (j < n)
                reservoir[static_cast<std::size_t>(j)] = *first;
        }
        return reservoir;
    }

    [[nodiscard]]
    inline std::vector<std::size_t> RandPermutation(std::size_t n)
    {
        std::vector<std::size_t> perm(n);
        for (std::size_t i = 0; i < n; ++i) perm[i] = i;
        if (n < 2) return perm;
        auto& rng = DefaultEngine();
        for (std::size_t i = n - 1; i > 0; --i)
        {
            std::uniform_int_distribution<std::size_t> dist(0, i);
            const std::size_t j = dist(rng);
            auto tmp = perm[i];
            perm[i] = perm[j];
            perm[j] = tmp;
        }
        return perm;
    }


    [[nodiscard]]
    inline std::string RandString(std::size_t length, std::string_view charset = "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789")
    {
        if (charset.empty())
            throw std::invalid_argument("RandString: charset is empty");
        std::string result(length, '\0');
        auto& rng = DefaultEngine();
        std::uniform_int_distribution<std::size_t> dist(0, charset.size() - 1);
        for (std::size_t i = 0; i < length; ++i)
            result[i] = charset[dist(rng)];
        return result;
    }

    [[nodiscard]]
    inline std::string RandString(std::size_t n, CharSet cs)
    {
        return RandString(n, detail::CharSetString(cs));
    }

    template <class Engine>
    [[nodiscard]]
    inline std::string RandString(Engine& engine, std::size_t n, std::string_view charset)
    {
        if (charset.empty())
            throw std::invalid_argument("RandString: charset is empty");
        std::string result(n, '\0');
        std::uniform_int_distribution<std::size_t> dist(0, charset.size() - 1);
        for (std::size_t i = 0; i < n; ++i)
            result[i] = charset[dist(engine)];
        return result;
    }

    template <class Engine>
    [[nodiscard]]
    inline std::string RandString(Engine& engine, std::size_t n, CharSet cs)
    {
        return RandString(engine, n, detail::CharSetString(cs));
    }

    template <class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandExp(T lambda = T{1})
    {
        if (!std::isfinite(lambda) || lambda <= T{0})
            throw std::invalid_argument("RandExp: lambda must be positive");
        std::exponential_distribution<T> dist(lambda);
        return dist(DefaultEngine());
    }

    template <class Engine, class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandExp(Engine& engine, T lambda = T{1})
    {
        if (!std::isfinite(lambda) || lambda <= T{0})
            throw std::invalid_argument("RandExp: lambda must be positive");
        std::exponential_distribution<T> dist(lambda);
        return dist(engine);
    }

    template <class T = int, std::enable_if_t<std::is_integral_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandPoisson(double mean = 1.0)
    {
        if (!std::isfinite(mean) || mean < 0.0)
            throw std::invalid_argument("RandPoisson: mean must be non-negative");
        if (mean == 0.0) return T{0};
        std::poisson_distribution<T> dist(mean);
        return dist(DefaultEngine());
    }

    template <class Engine, class T = int, std::enable_if_t<std::is_integral_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandPoisson(Engine& engine, double mean = 1.0)
    {
        if (!std::isfinite(mean) || mean < 0.0)
            throw std::invalid_argument("RandPoisson: mean must be non-negative");
        if (mean == 0.0) return T{0};
        std::poisson_distribution<T> dist(mean);
        return dist(engine);
    }

    template <class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandGamma(T alpha = T{1}, T beta = T{1})
    {
        if (!std::isfinite(alpha) || !std::isfinite(beta) || alpha <= T{0} || beta <= T{0})
            throw std::invalid_argument("RandGamma: alpha and beta must be positive");
        std::gamma_distribution<T> dist(alpha, beta);
        return dist(DefaultEngine());
    }

    template <class Engine, class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandGamma(Engine& engine, T alpha = T{1}, T beta = T{1})
    {
        if (!std::isfinite(alpha) || !std::isfinite(beta) || alpha <= T{0} || beta <= T{0})
            throw std::invalid_argument("RandGamma: alpha and beta must be positive");
        std::gamma_distribution<T> dist(alpha, beta);
        return dist(engine);
    }

    template <class T = int, std::enable_if_t<std::is_integral_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandBinomial(T t = 1, double p = 0.5)
    {
        if (t < 0 || !std::isfinite(p) || p < 0.0 || p > 1.0)
            throw std::invalid_argument("RandBinomial: invalid t or p");
        std::binomial_distribution<T> dist(t, p);
        return dist(DefaultEngine());
    }

    template <class Engine, class T = int, std::enable_if_t<std::is_integral_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandBinomial(Engine& engine, T t = 1, double p = 0.5)
    {
        if (t < 0 || !std::isfinite(p) || p < 0.0 || p > 1.0)
            throw std::invalid_argument("RandBinomial: invalid t or p");
        std::binomial_distribution<T> dist(t, p);
        return dist(engine);
    }

    template <class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandLogNormal(T mean = T{0}, T stddev = T{1})
    {
        if (!std::isfinite(mean) || !std::isfinite(stddev) || stddev <= T{0})
            throw std::invalid_argument("RandLogNormal: invalid mean or stddev");
        std::lognormal_distribution<T> dist(mean, stddev);
        return dist(DefaultEngine());
    }

    template <class Engine, class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandLogNormal(Engine& engine, T mean = T{0}, T stddev = T{1})
    {
        if (!std::isfinite(mean) || !std::isfinite(stddev) || stddev <= T{0})
            throw std::invalid_argument("RandLogNormal: invalid mean or stddev");
        std::lognormal_distribution<T> dist(mean, stddev);
        return dist(engine);
    }

    template <class T = int, std::enable_if_t<std::is_integral_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandGeometric(double p = 0.5)
    {
        if (!std::isfinite(p) || p <= 0.0 || p > 1.0)
            throw std::invalid_argument("RandGeometric: p must be in (0, 1]");
        std::geometric_distribution<T> dist(p);
        return dist(DefaultEngine());
    }

    template <class Engine, class T = int, std::enable_if_t<std::is_integral_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandGeometric(Engine& engine, double p = 0.5)
    {
        if (!std::isfinite(p) || p <= 0.0 || p > 1.0)
            throw std::invalid_argument("RandGeometric: p must be in (0, 1]");
        std::geometric_distribution<T> dist(p);
        return dist(engine);
    }

    template <class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandCauchy(T a = T{0}, T b = T{1})
    {
        if (!std::isfinite(a) || !std::isfinite(b) || b <= T{0})
            throw std::invalid_argument("RandCauchy: invalid a or b");
        std::cauchy_distribution<T> dist(a, b);
        return dist(DefaultEngine());
    }

    template <class Engine, class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandCauchy(Engine& engine, T a = T{0}, T b = T{1})
    {
        if (!std::isfinite(a) || !std::isfinite(b) || b <= T{0})
            throw std::invalid_argument("RandCauchy: invalid a or b");
        std::cauchy_distribution<T> dist(a, b);
        return dist(engine);
    }

    template <class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandWeibull(T a = T{1}, T b = T{1})
    {
        if (!std::isfinite(a) || !std::isfinite(b) || a <= T{0} || b <= T{0})
            throw std::invalid_argument("RandWeibull: invalid a or b");
        std::weibull_distribution<T> dist(a, b);
        return dist(DefaultEngine());
    }

    template <class Engine, class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandWeibull(Engine& engine, T a = T{1}, T b = T{1})
    {
        if (!std::isfinite(a) || !std::isfinite(b) || a <= T{0} || b <= T{0})
            throw std::invalid_argument("RandWeibull: invalid a or b");
        std::weibull_distribution<T> dist(a, b);
        return dist(engine);
    }

    template <class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandExtremeValue(T a = T{0}, T b = T{1})
    {
        if (!std::isfinite(a) || !std::isfinite(b) || b <= T{0})
            throw std::invalid_argument("RandExtremeValue: invalid a or b");
        std::extreme_value_distribution<T> dist(a, b);
        return dist(DefaultEngine());
    }

    template <class Engine, class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandExtremeValue(Engine& engine, T a = T{0}, T b = T{1})
    {
        if (!std::isfinite(a) || !std::isfinite(b) || b <= T{0})
            throw std::invalid_argument("RandExtremeValue: invalid a or b");
        std::extreme_value_distribution<T> dist(a, b);
        return dist(engine);
    }

    template <class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandChiSquared(T n = T{1})
    {
        if (!std::isfinite(n) || n <= T{0})
            throw std::invalid_argument("RandChiSquared: n must be positive");
        std::chi_squared_distribution<T> dist(n);
        return dist(DefaultEngine());
    }

    template <class Engine, class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandChiSquared(Engine& engine, T n = T{1})
    {
        if (!std::isfinite(n) || n <= T{0})
            throw std::invalid_argument("RandChiSquared: n must be positive");
        std::chi_squared_distribution<T> dist(n);
        return dist(engine);
    }

    template <class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandStudentT(T n = T{1})
    {
        if (!std::isfinite(n) || n <= T{0})
            throw std::invalid_argument("RandStudentT: n must be positive");
        std::student_t_distribution<T> dist(n);
        return dist(DefaultEngine());
    }

    template <class Engine, class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandStudentT(Engine& engine, T n = T{1})
    {
        if (!std::isfinite(n) || n <= T{0})
            throw std::invalid_argument("RandStudentT: n must be positive");
        std::student_t_distribution<T> dist(n);
        return dist(engine);
    }

    template <class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandFisherF(T m = T{1}, T n = T{1})
    {
        if (!std::isfinite(m) || !std::isfinite(n) || m <= T{0} || n <= T{0})
            throw std::invalid_argument("RandFisherF: invalid m or n");
        std::fisher_f_distribution<T> dist(m, n);
        return dist(DefaultEngine());
    }

    template <class Engine, class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandFisherF(Engine& engine, T m = T{1}, T n = T{1})
    {
        if (!std::isfinite(m) || !std::isfinite(n) || m <= T{0} || n <= T{0})
            throw std::invalid_argument("RandFisherF: invalid m or n");
        std::fisher_f_distribution<T> dist(m, n);
        return dist(engine);
    }

    template <class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandBeta(T a = T{1}, T b = T{1})
    {
        return RandBeta(DefaultEngine(), a, b);
    }

    template <class Engine, class T = double, std::enable_if_t<std::is_floating_point_v<T>>* = nullptr>
    [[nodiscard]]
    inline T RandBeta(Engine& engine, T a = T{1}, T b = T{1})
    {
        if (!std::isfinite(a) || !std::isfinite(b) || a <= T{0} || b <= T{0})
            throw std::invalid_argument("RandBeta: invalid a or b");
        std::gamma_distribution<T> distA(a, T{1});
        std::gamma_distribution<T> distB(b, T{1});
        const T x = distA(engine);
        const T y = distB(engine);
        const T sum = x + y;
        if (sum == T{0} || !std::isfinite(sum))
        {
            if (std::isinf(x) && !std::isinf(y)) return T{1};
            if (!std::isinf(x) && std::isinf(y)) return T{0};
            const double ratio = 1.0 / (1.0 + (static_cast<double>(b) / static_cast<double>(a)));
            return RandBool(engine, ratio) ? T{1} : T{0};
        }
        return x / sum;
    }

    template <int N, class T = std::uint64_t, std::enable_if_t<std::is_integral_v<T> && (N > 0) && (N <= 64) && (N <= static_cast<int>(sizeof(T) * 8))>* = nullptr>
    [[nodiscard]]
    inline T RandBits() noexcept
    {
        return RandBits<N, T>(DefaultEngine());
    }

    template <int N, class T = std::uint64_t, class Engine, std::enable_if_t<std::is_integral_v<T> && (N > 0) && (N <= 64) && (N <= static_cast<int>(sizeof(T) * 8))>* = nullptr>
    [[nodiscard]]
    inline T RandBits(Engine& engine) noexcept
    {
        if constexpr (N == 64)
            return static_cast<T>(engine());
        else
            return static_cast<T>(engine() & ((N >= 64) ? ~std::uint64_t{0} : ((std::uint64_t{1} << (N & 63)) - 1)));
    }

    template <class Engine>
    [[nodiscard]]
    inline std::string RandUUID(Engine& engine)
    {
        static constexpr char hex[] = "0123456789abcdef";
        std::string uuid(36, '-');
        const std::uint64_t u1 = detail::Generate64Bits(engine);
        const std::uint64_t u2 = detail::Generate64Bits(engine);
 
        for (int i = 0; i < 8; ++i)
            uuid[i] = hex[(u1 >> (i * 4)) & 0xFU];
        for (int i = 0; i < 4; ++i)
            uuid[9 + i] = hex[(u1 >> ((8 + i) * 4)) & 0xFU];
        uuid[14] = '4';
        for (int i = 1; i < 4; ++i)
            uuid[14 + i] = hex[(u1 >> ((12 + i) * 4)) & 0xFU];
        uuid[19] = hex[8 + ((u2 >> 0) & 0x3U)];
        for (int i = 1; i < 4; ++i)
            uuid[19 + i] = hex[(u2 >> (i * 4)) & 0xFU];
        for (int i = 0; i < 12; ++i)
            uuid[24 + i] = hex[(u2 >> ((4 + i) * 4)) & 0xFU];
 
        return uuid;
    }
 
    [[nodiscard]]
    inline std::string RandUUID()
    {
        return RandUUID(DefaultEngine());
    }

    //
    //  静态断言：确认引擎满足 UniformRandomBitGenerator 要求
    //
 
    static_assert(std::is_same_v<SplitMix64::result_type, std::uint64_t>);
    static_assert(std::is_same_v<Xoshiro256StarStar::result_type, std::uint64_t>);
    static_assert(std::is_same_v<Xoroshiro128StarStar::result_type, std::uint64_t>);
    static_assert(std::is_same_v<Xoshiro128StarStar::result_type, std::uint32_t>);
    static_assert(std::is_same_v<Xoroshiro64StarStar::result_type, std::uint32_t>);
    static_assert(std::is_same_v<SFC64::result_type, std::uint64_t>);
    static_assert(std::is_same_v<RomuDuoJr::result_type, std::uint64_t>);
    static_assert(std::is_same_v<ChaCha20::result_type, std::uint64_t>);
    static_assert(SplitMix64::min() < SplitMix64::max());
    static_assert(Xoshiro256StarStar::min() < Xoshiro256StarStar::max());
    static_assert(Xoroshiro128StarStar::min() < Xoroshiro128StarStar::max());
    static_assert(Xoshiro128StarStar::min() < Xoshiro128StarStar::max());
    static_assert(Xoroshiro64StarStar::min() < Xoroshiro64StarStar::max());
    static_assert(SFC64::min() < SFC64::max());
    static_assert(RomuDuoJr::min() < RomuDuoJr::max());
    static_assert(ChaCha20::min() < ChaCha20::max());
 
    // ========================================================================
    // 流式运算符 operator<< / operator>>
    // 仅对 state_type 为可索引容器类的引擎生效（is_serializable_engine_v）
    // SplitMix64（state_type = uint64_t 标量）不支持，由 is_indexable_state_v 排除
    // 格式兼容 std::random_engine：空格分隔的十进制数序列
    // ========================================================================
 
    // 流式输出引擎状态
    template <class CharT, class Traits, class Engine,
        std::enable_if_t<detail::is_serializable_engine_v<Engine>>* = nullptr>
    std::basic_ostream<CharT, Traits>&
    operator<<(std::basic_ostream<CharT, Traits>& os, const Engine& engine)
    {
        typename std::basic_ostream<CharT, Traits>::sentry ok(os);
        if (!ok) return os;
 
        const auto flags = os.flags();
        os.setf(std::ios_base::dec, std::ios_base::basefield);
 
        auto state = engine.serialize();
        auto it = state.begin();
        if (it != state.end())
        {
            os << *it;
            for (++it; it != state.end(); ++it)
                os << os.widen(' ') << *it;
        }
 
        os.flags(flags);
        return os;
    }
 
    // 流式恢复引擎状态
    // 若解析失败（读取不足、流错误或状态非法/全零），setstate(failbit) 且引擎状态保持不变
    // （与 std::random_engine 一致：先读取到临时 state，全部成功才 deserialize）
    template <class CharT, class Traits, class Engine,
        std::enable_if_t<detail::is_serializable_engine_v<Engine>>* = nullptr>
    std::basic_istream<CharT, Traits>&
    operator>>(std::basic_istream<CharT, Traits>& is, Engine& engine)
    {
        typename std::basic_istream<CharT, Traits>::sentry ok(is);
        if (!ok) return is;
 
        const auto flags = is.flags();
        is.setf(std::ios_base::dec, std::ios_base::basefield);
        is.setf(std::ios_base::skipws);
 
        typename Engine::state_type state{};
        std::size_t i = 0;
        for (; i < state.size() && is; ++i)
            is >> state[i];
 
        if (i == state.size() && is && detail::IsValidState(state))
        {
            engine.deserialize(state);
        }
        else
        {
            is.setstate(std::ios_base::failbit);
        }
 
        is.flags(flags);
        return is;
    }
 
}
 
#undef RANDX_NODISCARD_CXX20