C++高级技术详解

C++高级技术详解

目录

1. 模板 (Templates)
2. 右值和移动语义 (Rvalue and Move Semantics)
3. 定位 new (Placement new)
4. 强类型 (Strong Types)
5. 智能指针 (Smart Pointers)
6. 容器和算法 (Containers and Algorithms)
7. Lambda表达式
8. 常量表达式 (constexpr)
9. 多线程和并发 (Multithreading and Concurrency)
10. 现代C++特性：模块、概念、协程和范围

环境配置

在Visual Studio Code中开发C++需要：

1. 安装C++扩展
2. 配置编译器（GCC、Clang或MSVC）
3. 创建tasks.json和launch.json配置文件

// tasks.json{ \"version\": \"2.0.0\", \"tasks\": [{ \"type\": \"cppbuild\", \"label\": \"C++ build\", \"command\": \"g++\", \"args\": [ \"-std=c++20\", \"-g\", \"${file}\", \"-o\", \"${fileDirname}/${fileBasenameNoExtension}\" ] }]}

模板 (Templates)

1.1 函数模板

函数模板允许编写通用函数，可以处理不同类型的参数。

#include #include // 基本函数模板template<typename T>T max(T a, T b) { return (a > b) ? a : b;}// 多参数模板template<typename T, typename U>auto add(T a, U b) -> decltype(a + b) { return a + b;}// 可变参数模板template<typename T>void print(T t) { std::cout << t << std::endl;}template<typename T, typename... Args>void print(T t, Args... args) { std::cout << t << \" \"; print(args...);}int main() { std::cout << max(10, 20) << std::endl;  // 20 std::cout << max(10.5, 20.3) << std::endl; // 20.3 std::cout << add(10, 20.5) << std::endl; // 30.5 print(\"Hello\", \"World\", 123, 45.6); // Hello World 123 45.6 return 0;}

1.2 类模板

#include #include // 基本类模板template<typename T>class Stack {private: std::vector<T> elements; public: void push(const T& elem) { elements.push_back(elem); } T pop() { if (elements.empty()) { throw std::runtime_error(\"Stack is empty\"); } T elem = elements.back(); elements.pop_back(); return elem; } bool empty() const { return elements.empty(); }};// 模板特化template<>class Stack<bool> {private: std::vector<unsigned char> elements; size_t bit_count = 0; public: void push(bool value) { // 位压缩实现 if (bit_count % 8 == 0) { elements.push_back(0); } if (value) { elements.back() |= (1 << (bit_count % 8)); } bit_count++; } // ... 其他方法};// 部分特化template<typename T>class Stack<T*> { // 指针类型的特殊实现};int main() { Stack<int> intStack; intStack.push(10); intStack.push(20); std::cout << intStack.pop() << std::endl; // 20 return 0;}

1.3 模板元编程

#include // 编译时计算阶乘template<int N>struct Factorial { static constexpr int value = N * Factorial<N - 1>::value;};template<>struct Factorial<0> { static constexpr int value = 1;};// SFINAE (Substitution Failure Is Not An Error)template<typename T>typename std::enable_if<std::is_integral<T>::value, bool>::typeis_odd(T i) { return i % 2 == 1;}// C++17 if constexprtemplate<typename T>auto process(T value) { if constexpr (std::is_integral_v<T>) { return value * 2; } else if constexpr (std::is_floating_point_v<T>) { return value / 2.0; } else { return value; }}int main() { std::cout << \"5! = \" << Factorial<5>::value << std::endl; // 120 std::cout << is_odd(5) << std::endl; // 1 std::cout << process(10) << std::endl; // 20 std::cout << process(10.0) << std::endl; // 5.0 return 0;}

右值和移动语义

2.1 左值和右值

#include #include #include #include // 理解左值和右值void processValue(int& x) { std::cout << \"左值引用: \" << x << std::endl;}void processValue(int&& x) { std::cout << \"右值引用: \" << x << std::endl;}// 万能引用template<typename T>void universalRef(T&& x) { if (std::is_lvalue_reference<T>::value) { std::cout << \"接收到左值\" << std::endl; } else { std::cout << \"接收到右值\" << std::endl; }}int main() { int a = 10; processValue(a); // 左值引用: 10 processValue(20); // 右值引用: 20 processValue(std::move(a)); // 右值引用: 10 universalRef(a); // 接收到左值 universalRef(20); // 接收到右值 return 0;}

2.2 移动构造和移动赋值

#include #include #include class String {private: char* data; size_t size; public: // 构造函数 String(const char* str = \"\") { size = strlen(str); data = new char[size + 1]; strcpy(data, str); std::cout << \"构造函数: \" << data << std::endl; } // 拷贝构造 String(const String& other) { size = other.size; data = new char[size + 1]; strcpy(data, other.data); std::cout << \"拷贝构造: \" << data << std::endl; } // 移动构造 String(String&& other) noexcept { data = other.data; size = other.size; other.data = nullptr; other.size = 0; std::cout << \"移动构造: \" << data << std::endl; } // 拷贝赋值 String& operator=(const String& other) { if (this != &other) { delete[] data; size = other.size; data = new char[size + 1]; strcpy(data, other.data); std::cout << \"拷贝赋值: \" << data << std::endl; } return *this; } // 移动赋值 String& operator=(String&& other) noexcept { if (this != &other) { delete[] data; data = other.data; size = other.size; other.data = nullptr; other.size = 0; std::cout << \"移动赋值: \" << data << std::endl; } return *this; } ~String() { delete[] data; } const char* c_str() const { return data ? data : \"\"; }};// 完美转发template<typename T>void relay(T&& arg) { process(std::forward<T>(arg));}int main() { String s1(\"Hello\"); String s2(s1);  // 拷贝构造 String s3(std::move(s1)); // 移动构造 String s4(\"World\"); s4 = String(\"Temp\"); // 移动赋值 std::vector<String> vec; vec.push_back(String(\"Test\")); // 移动构造 return 0;}

定位 new

定位new允许在已分配的内存上构造对象。

#include #include #include class MyClass {private: int value; public: MyClass(int v) : value(v) { std::cout << \"构造 MyClass: \" << value << std::endl; } ~MyClass() { std::cout << \"析构 MyClass: \" << value << std::endl; } void print() const { std::cout << \"Value: \" << value << std::endl; }};// 内存池实现template<typename T, size_t N>class MemoryPool {private: alignas(T) char buffer[sizeof(T) * N]; bool used[N] = {false}; public: T* allocate() { for (size_t i = 0; i < N; ++i) { if (!used[i]) { used[i] = true; return reinterpret_cast<T*>(&buffer[sizeof(T) * i]); } } throw std::bad_alloc(); } void deallocate(T* ptr) { size_t index = (reinterpret_cast<char*>(ptr) - buffer) / sizeof(T); if (index < N) { used[index] = false; } }};int main() { // 基本用法 char buffer[sizeof(MyClass)]; MyClass* obj = new (buffer) MyClass(42); obj->print(); obj->~MyClass(); // 手动调用析构函数 // 使用内存池 MemoryPool<MyClass, 10> pool; MyClass* p1 = pool.allocate(); new (p1) MyClass(100); MyClass* p2 = pool.allocate(); new (p2) MyClass(200); p1->print(); p2->print(); p1->~MyClass(); p2->~MyClass(); pool.deallocate(p1); pool.deallocate(p2); return 0;}

强类型

强类型通过类型系统增强代码的安全性和表达力。

#include #include // 强类型包装器template<typename T, typename Tag>class StrongType {private: T value; public: explicit StrongType(T val) : value(val) {} T& get() { return value; } const T& get() const { return value; } // 显式转换 explicit operator T() const { return value; }};// 使用标签区分不同的类型struct DistanceTag {};struct SpeedTag {};struct TimeTag {};using Distance = StrongType<double, DistanceTag>;using Speed = StrongType<double, SpeedTag>;using Time = StrongType<double, TimeTag>;// 类型安全的操作Speed operator/(const Distance& d, const Time& t) { return Speed(d.get() / t.get());}Distance operator*(const Speed& s, const Time& t) { return Distance(s.get() * t.get());}// 枚举类（强类型枚举）enum class Color : uint8_t { Red = 1, Green = 2, Blue = 3};enum class Status { Success, Failure, Pending};// 类型特征template<typename T>struct is_strong_type : std::false_type {};template<typename T, typename Tag>struct is_strong_type<StrongType<T, Tag>> : std::true_type {};int main() { Distance d(100.0); // 100米 Time t(10.0); // 10秒 Speed s = d / t; // 10米/秒 std::cout << \"速度: \" << s.get() << \" m/s\" << std::endl; // 编译错误：类型不匹配 // Speed s2 = d + t; // 枚举类使用 Color c = Color::Red; // int colorValue = c; // 编译错误：需要显式转换 int colorValue = static_cast<int>(c); // 类型检查 static_assert(is_strong_type<Speed>::value); static_assert(!is_strong_type<double>::value); return 0;}

智能指针

5.1 unique_ptr

#include #include #include class Resource {private: std::string name; public: Resource(const std::string& n) : name(n) { std::cout << \"Resource \" << name << \" 创建\" << std::endl; } ~Resource() { std::cout << \"Resource \" << name << \" 销毁\" << std::endl; } void use() { std::cout << \"使用 Resource \" << name << std::endl; }};// 自定义删除器struct FileDeleter { void operator()(FILE* fp) const { if (fp) { std::cout << \"关闭文件\" << std::endl; fclose(fp); } }};// 工厂函数std::unique_ptr<Resource> createResource(const std::string& name) { return std::make_unique<Resource>(name);}int main() { // 基本用法 { std::unique_ptr<Resource> ptr1 = std::make_unique<Resource>(\"Res1\"); ptr1->use(); // 转移所有权 std::unique_ptr<Resource> ptr2 = std::move(ptr1); // ptr1 现在为空 if (!ptr1) { std::cout << \"ptr1 已经为空\" << std::endl; } } // 数组 std::unique_ptr<int[]> arr = std::make_unique<int[]>(10); for (int i = 0; i < 10; ++i) { arr[i] = i * i; } // 自定义删除器 std::unique_ptr<FILE, FileDeleter> file(fopen(\"test.txt\", \"w\")); if (file) { fprintf(file.get(), \"Hello, World!\"); } // 容器中使用 std::vector<std::unique_ptr<Resource>> resources; resources.push_back(std::make_unique<Resource>(\"Vec1\")); resources.push_back(std::make_unique<Resource>(\"Vec2\")); return 0;}

5.2 shared_ptr

#include #include #include #include class Node {public: int value; std::shared_ptr<Node> next; std::weak_ptr<Node> parent; // 避免循环引用 Node(int val) : value(val) { std::cout << \"Node \" << value << \" 创建\" << std::endl; } ~Node() { std::cout << \"Node \" << value << \" 销毁\" << std::endl; }};// 多线程共享资源void worker(std::shared_ptr<std::vector<int>> data, int id) { std::cout << \"Worker \" << id << \" 开始处理，引用计数: \"  << data.use_count() << std::endl; // 模拟工作 std::this_thread::sleep_for(std::chrono::milliseconds(100)); data->push_back(id);}// 自定义分配器和删除器template<typename T>struct ArrayDeleter { void operator()(T* p) const { delete[] p; }};int main() { // 基本用法 { std::shared_ptr<Node> head = std::make_shared<Node>(1); std::shared_ptr<Node> second = std::make_shared<Node>(2); head->next = second; second->parent = head; // weak_ptr 避免循环引用 std::cout << \"head 引用计数: \" << head.use_count() << std::endl; std::cout << \"second 引用计数: \" << second.use_count() << std::endl; } // 多线程共享 auto sharedData = std::make_shared<std::vector<int>>(); std::vector<std::thread> threads; for (int i = 0; i < 5; ++i) { threads.emplace_back(worker, sharedData, i); } for (auto& t : threads) { t.join(); } std::cout << \"数据大小: \" << sharedData->size() << std::endl; // 别名构造函数 struct Person { std::string name; int age; }; auto person = std::make_shared<Person>(Person{\"Alice\", 25}); std::shared_ptr<std::string> name(person, &person->name); return 0;}

5.3 weak_ptr

#include #include #include // 缓存系统示例template<typename Key, typename Value>class Cache {private: std::map<Key, std::weak_ptr<Value>> cache; public: std::shared_ptr<Value> get(const Key& key) { auto it = cache.find(key); if (it != cache.end()) { // 尝试获取强引用 if (auto sp = it->second.lock()) { std::cout << \"缓存命中: \" << key << std::endl; return sp; } else { // 对象已经被销毁，移除缓存项 cache.erase(it); } } std::cout << \"缓存未命中: \" << key << std::endl; return nullptr; } void put(const Key& key, std::shared_ptr<Value> value) { cache[key] = value; }};// 观察者模式class Observer {public: virtual void update() = 0; virtual ~Observer() = default;};class Subject {private: std::vector<std::weak_ptr<Observer>> observers; public: void attach(std::shared_ptr<Observer> observer) { observers.push_back(observer); } void notify() { // 清理已经失效的观察者 auto it = observers.begin(); while (it != observers.end()) { if (auto sp = it->lock()) { sp->update(); ++it; } else { it = observers.erase(it); } } }};class ConcreteObserver : public Observer {private: std::string name; public: ConcreteObserver(const std::string& n) : name(n) {} void update() override { std::cout << name << \" 收到更新通知\" << std::endl; }};int main() { // 缓存示例 Cache<std::string, std::string> cache; { auto data = std::make_shared<std::string>(\"重要数据\"); cache.put(\"key1\", data); auto retrieved = cache.get(\"key1\"); if (retrieved) { std::cout << \"获取到: \" << *retrieved << std::endl; } } // data 已经销毁 auto retrieved = cache.get(\"key1\"); if (!retrieved) { std::cout << \"数据已经被销毁\" << std::endl; } // 观察者模式 Subject subject; auto obs1 = std::make_shared<ConcreteObserver>(\"观察者1\"); auto obs2 = std::make_shared<ConcreteObserver>(\"观察者2\"); subject.attach(obs1); subject.attach(obs2); subject.notify(); obs1.reset(); // 销毁观察者1 std::cout << \"\\n销毁观察者1后：\" << std::endl; subject.notify(); return 0;}

容器和算法

6.1 STL容器

#include #include #include #include #include #include #include #include #include #include #include // 自定义比较器struct Person { std::string name; int age; bool operator<(const Person& other) const { return age < other.age; }};// 自定义哈希函数struct PersonHash { size_t operator()(const Person& p) const { return std::hash<std::string>()(p.name) ^ std::hash<int>()(p.age); }};struct PersonEqual { bool operator()(const Person& a, const Person& b) const { return a.name == b.name && a.age == b.age; }};int main() { // 序列容器 std::vector<int> vec = {1, 2, 3, 4, 5}; vec.push_back(6); vec.emplace_back(7); // 原地构造 std::deque<int> deq = {10, 20, 30}; deq.push_front(5); deq.push_back(40); std::list<int> lst = {100, 200, 300}; lst.splice(lst.begin(), vec); // 移动元素 // 关联容器 std::set<Person> people = { {\"Alice\", 25}, {\"Bob\", 30}, {\"Charlie\", 20} }; std::map<std::string, int> scores = { {\"Alice\", 95}, {\"Bob\", 87}, {\"Charlie\", 92} }; // 无序容器 std::unordered_map<Person, std::string, PersonHash, PersonEqual> info; info[{\"Alice\", 25}] = \"Engineer\"; info[{\"Bob\", 30}] = \"Manager\"; // 容器适配器 std::priority_queue<int> pq; pq.push(10); pq.push(30); pq.push(20); while (!pq.empty()) { std::cout << pq.top() << \" \"; // 30 20 10 pq.pop(); } std::cout << std::endl; // C++11 array std::array<int, 5> arr = {1, 2, 3, 4, 5}; std::cout << \"Array size: \" << arr.size() << std::endl; return 0;}

6.2 STL算法

#include #include #include #include #include #include #include int main() { std::vector<int> vec = {5, 2, 8, 1, 9, 3, 7, 4, 6}; // 排序算法 std::sort(vec.begin(), vec.end()); std::cout << \"排序后: \"; std::copy(vec.begin(), vec.end(),  std::ostream_iterator<int>(std::cout, \" \")); std::cout << std::endl; // 部分排序 std::partial_sort(vec.begin(), vec.begin() + 3, vec.end(), std::greater<int>()); std::cout << \"前3个最大值: \"; std::copy(vec.begin(), vec.begin() + 3,  std::ostream_iterator<int>(std::cout, \" \")); std::cout << std::endl; // 查找算法 auto it = std::find(vec.begin(), vec.end(), 5); if (it != vec.end()) { std::cout << \"找到5在位置: \" << std::distance(vec.begin(), it) << std::endl; } // 二分查找（需要有序） std::sort(vec.begin(), vec.end()); bool found = std::binary_search(vec.begin(), vec.end(), 5); std::cout << \"二分查找5: \" << (found ? \"找到\" : \"未找到\") << std::endl; // 变换算法 std::vector<int> squared; std::transform(vec.begin(), vec.end(), std::back_inserter(squared),  [](int x) { return x * x; }); // 累积算法 int sum = std::accumulate(vec.begin(), vec.end(), 0); int product = std::accumulate(vec.begin(), vec.end(), 1, std::multiplies<int>()); std::cout << \"和: \" << sum << \", 积: \" << product << std::endl; // 分区算法 auto pivot = std::partition(vec.begin(), vec.end(),  [](int x) { return x % 2 == 0; }); std::cout << \"偶数: \"; std::copy(vec.begin(), pivot, std::ostream_iterator<int>(std::cout, \" \")); std::cout << \"\\n奇数: \"; std::copy(pivot, vec.end(), std::ostream_iterator<int>(std::cout, \" \")); std::cout << std::endl; // 排列组合 std::vector<int> perm = {1, 2, 3}; do { std::copy(perm.begin(), perm.end(),  std::ostream_iterator<int>(std::cout, \" \")); std::cout << std::endl; } while (std::next_permutation(perm.begin(), perm.end())); // 随机算法 std::random_device rd; std::mt19937 gen(rd()); std::shuffle(vec.begin(), vec.end(), gen); return 0;}

6.3 自定义迭代器

#include #include #include template<typename T>class CircularBuffer {private: T* buffer; size_t capacity; size_t size; size_t head; public: class iterator { private: T* ptr; T* begin; T* end; public: using iterator_category = std::forward_iterator_tag; using value_type = T; using difference_type = std::ptrdiff_t; using pointer = T*; using reference = T&; iterator(T* p, T* b, T* e) : ptr(p), begin(b), end(e) {} reference operator*() { return *ptr; } pointer operator->() { return ptr; } iterator& operator++() { ptr++; if (ptr == end) ptr = begin; return *this; } iterator operator++(int) { iterator tmp = *this; ++(*this); return tmp; } bool operator==(const iterator& other) const { return ptr == other.ptr; } bool operator!=(const iterator& other) const { return !(*this == other); } }; CircularBuffer(size_t cap) : capacity(cap), size(0), head(0) { buffer = new T[capacity]; } ~CircularBuffer() { delete[] buffer; } void push(const T& value) { buffer[(head + size) % capacity] = value; if (size < capacity) { size++; } else { head = (head + 1) % capacity; } } iterator begin() { return iterator(&buffer[head], buffer, buffer + capacity); } iterator end() { return iterator(&buffer[(head + size) % capacity], buffer, buffer + capacity); }};int main() { CircularBuffer<int> cb(5); for (int i = 0; i < 8; ++i) { cb.push(i); } std::cout << \"循环缓冲区内容: \"; for (auto it = cb.begin(); it != cb.end(); ++it) { std::cout << *it << \" \"; } std::cout << std::endl; // 使用STL算法 auto minmax = std::minmax_element(cb.begin(), cb.end()); std::cout << \"最小值: \" << *minmax.first  << \", 最大值: \" << *minmax.second << std::endl; return 0;}

Lambda表达式

7.1 基础Lambda

#include #include #include #include int main() { // 基本语法 auto simple = []() { std::cout << \"Hello Lambda!\" << std::endl; }; simple(); // 带参数 auto add = [](int a, int b) { return a + b; }; std::cout << \"3 + 4 = \" << add(3, 4) << std::endl; // 捕获列表 int x = 10; int y = 20; // 值捕获 auto captureByValue = [x, y]() { std::cout << \"x = \" << x << \", y = \" << y << std::endl; }; // 引用捕获 auto captureByRef = [&x, &y]() { x++; y++; std::cout << \"x = \" << x << \", y = \" << y << std::endl; }; // 混合捕获 auto mixedCapture = [x, &y]() { // x++; // 错误：值捕获是只读的 y++; // 可以修改引用捕获的变量 }; // 捕获所有 auto captureAll = [=]() { std::cout << x + y << std::endl; }; auto captureAllRef = [&]() { x++; y++; }; // mutable lambda auto mutableLambda = [x]() mutable { x++; // 现在可以修改值捕获的副本 return x; }; std::cout << \"mutable结果: \" << mutableLambda() << std::endl; std::cout << \"原始x: \" << x << std::endl; // x未改变 // 返回类型推导 auto divide = [](double a, double b) -> double { return a / b; }; // 泛型lambda (C++14) auto genericAdd = [](auto a, auto b) { return a + b; }; std::cout << genericAdd(3, 4) << std::endl; // int std::cout << genericAdd(3.5, 4.5) << std::endl; // double std::cout << genericAdd(std::string(\"Hello\"), std::string(\" World\")) << std::endl; // string return 0;}

7.2 高级Lambda用法

#include #include #include #include #include // 递归lambdaauto factorial = [](auto& self, int n) -> int { return n <= 1 ? 1 : n * self(self, n - 1);};// 使用std::function实现递归std::function<int(int)> fib = [&](int n) { return n <= 1 ? n : fib(n - 1) + fib(n - 2);};// Lambda作为模板参数template<typename Func>void repeat(int n, Func f) { for (int i = 0; i < n; ++i) { f(i); }}// 返回lambda的函数auto makeMultiplier(int factor) { return [factor](int x) { return x * factor; };}// 状态lambdaauto makeCounter() { return [count = 0]() mutable { return ++count; };}// 初始化捕获 (C++14)auto makeUniqueCapture() { return [ptr = std::make_unique<int>(42)]() { return *ptr; };}int main() { // 使用递归lambda std::cout << \"5! = \" << factorial(factorial, 5) << std::endl; std::cout << \"fib(10) = \" << fib(10) << std::endl; // Lambda与STL std::vector<int> vec = {5, 2, 8, 1, 9, 3, 7, 4, 6}; // 排序 std::sort(vec.begin(), vec.end(),  [](int a, int b) { return a > b; }); // 查找 auto it = std::find_if(vec.begin(), vec.end(), [](int x) { return x > 5; }); // 计数 int count = std::count_if(vec.begin(), vec.end(), [](int x) { return x % 2 == 0; }); std::cout << \"偶数个数: \" << count << std::endl; // 变换 std::vector<int> squared; std::transform(vec.begin(), vec.end(), std::back_inserter(squared),  [](int x) { return x * x; }); // 使用lambda工厂 auto times3 = makeMultiplier(3); auto times5 = makeMultiplier(5); std::cout << \"4 * 3 = \" << times3(4) << std::endl; std::cout << \"4 * 5 = \" << times5(4) << std::endl; // 状态lambda auto counter1 = makeCounter(); auto counter2 = makeCounter(); std::cout << \"Counter1: \" << counter1() << \", \" << counter1() << std::endl; std::cout << \"Counter2: \" << counter2() << \", \" << counter2() << std::endl; // 模板中使用 repeat(5, [](int i) { std::cout << \"Iteration \" << i << std::endl; }); // IIFE (Immediately Invoked Function Expression) int result = [](int x, int y) { return x + y; }(10, 20); std::cout << \"IIFE结果: \" << result << std::endl; return 0;}

7.3 Lambda与并发

#include #include #include #include #include #include int main() { // Lambda与线程 std::vector<std::thread> threads; for (int i = 0; i < 5; ++i) { threads.emplace_back([i]() { std::cout << \"线程 \" << i << \" 运行中\\n\"; std::this_thread::sleep_for(std::chrono::milliseconds(100)); }); } for (auto& t : threads) { t.join(); } // Lambda与async std::vector<int> data = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}; auto sum_part = [](const std::vector<int>& v, size_t start, size_t end) { return std::accumulate(v.begin() + start, v.begin() + end, 0); }; size_t mid = data.size() / 2; auto future1 = std::async(std::launch::async, sum_part, std::ref(data), 0, mid); auto future2 = std::async(std::launch::async, sum_part, std::ref(data), mid, data.size()); int total = future1.get() + future2.get(); std::cout << \"并行求和结果: \" << total << std::endl; // 并行算法与lambda std::vector<int> vec(1000000); std::iota(vec.begin(), vec.end(), 1); auto start = std::chrono::high_resolution_clock::now(); // 并行版本 int sum = std::reduce(std::execution::par, vec.begin(), vec.end(), 0, [](int a, int b) { return a + b; }); auto end = std::chrono::high_resolution_clock::now(); auto duration = std::chrono::duration_cast<std::chrono::microseconds>(end - start); std::cout << \"并行求和: \" << sum << \" 用时: \" << duration.count() << \"μs\" << std::endl; return 0;}

常量表达式

8.1 constexpr基础

#include #include #include // constexpr变量constexpr int square(int x) { return x * x;}// constexpr递归constexpr int factorial(int n) { return n <= 1 ? 1 : n * factorial(n - 1);}// constexpr类class Point {private: double x_, y_; public: constexpr Point(double x, double y) : x_(x), y_(y) {} constexpr double x() const { return x_; } constexpr double y() const { return y_; } constexpr Point move(double dx, double dy) const { return Point(x_ + dx, y_ + dy); } constexpr double distance() const { return x_ * x_ + y_ * y_; // 简化版，实际应该开方 }};// constexpr if (C++17)template<typename T>constexpr auto getValue(T t) { if constexpr (std::is_pointer_v<T>) { return *t; } else { return t; }}// 编译时字符串template<size_t N>struct ConstString { char data[N]; constexpr ConstString(const char (&str)[N]) { for (size_t i = 0; i < N; ++i) { data[i] = str[i]; } }};// 编译时排序template<typename T, size_t N>constexpr std::array<T, N> sort(std::array<T, N> arr) { for (size_t i = 0; i < N - 1; ++i) { for (size_t j = 0; j < N - i - 1; ++j) { if (arr[j] > arr[j + 1]) { T temp = arr[j]; arr[j] = arr[j + 1]; arr[j + 1] = temp; } } } return arr;}int main() { // 编译时计算 constexpr int val = square(5); constexpr int fact = factorial(5); // 用作数组大小 int arr[square(4)]; // constexpr对象 constexpr Point p1(3.0, 4.0); constexpr Point p2 = p1.move(1.0, 2.0); constexpr double dist = p2.distance(); // 编译时数组 constexpr std::array<int, 5> unsorted = {5, 2, 8, 1, 9}; constexpr auto sorted = sort(unsorted); for (auto val : sorted) { std::cout << val << \" \"; } std::cout << std::endl; // constexpr if使用 int x = 10; int* px = &x; std::cout << getValue(x) << std::endl; // 10 std::cout << getValue(px) << std::endl; // 10 // 静态断言 static_assert(square(5) == 25, \"Square计算错误\"); static_assert(factorial(5) == 120, \"Factorial计算错误\"); return 0;}

8.2 constexpr与模板元编程

#include #include #include // 编译时斐波那契template<int N>struct Fibonacci { static constexpr int value = Fibonacci<N-1>::value + Fibonacci<N-2>::value;};template<>struct Fibonacci<0> { static constexpr int value = 0;};template<>struct Fibonacci<1> { static constexpr int value = 1;};// constexpr版本constexpr int fib(int n) { return n <= 1 ? n : fib(n - 1) + fib(n - 2);}// 编译时类型选择template<bool B, typename T, typename F>struct conditional { using type = T;};template<typename T, typename F>struct conditional<false, T, F> { using type = F;};// constexpr实现template<bool B, typename T, typename F>constexpr auto conditional_v(T t, F f) { if constexpr (B) { return t; } else { return f; }}// 编译时循环template<size_t... Is>constexpr auto make_index_array(std::index_sequence<Is...>) { return std::array<size_t, sizeof...(Is)>{Is...};}template<size_t N>constexpr auto make_index_array() { return make_index_array(std::make_index_sequence<N>{});}// 编译时字符串哈希constexpr size_t hash(const char* str) { size_t h = 0; for (size_t i = 0; str[i] != \'\\0\'; ++i) { h = h * 31 + str[i]; } return h;}// 编译时switchtemplate<size_t N>constexpr auto compile_time_switch(size_t i) { if constexpr (N == 0) { return \"Zero\"; } else if constexpr (N == 1) { return \"One\"; } else if constexpr (N == 2) { return \"Two\"; } else { return \"Other\"; }}int main() { // 比较模板元编程和constexpr constexpr int fib10_tmp = Fibonacci<10>::value; constexpr int fib10_cxp = fib(10); std::cout << \"模板: \" << fib10_tmp << std::endl; std::cout << \"constexpr: \" << fib10_cxp << std::endl; // 编译时数组生成 constexpr auto indices = make_index_array<10>(); for (auto i : indices) { std::cout << i << \" \"; } std::cout << std::endl; // 编译时字符串哈希 constexpr size_t h1 = hash(\"Hello\"); constexpr size_t h2 = hash(\"World\"); switch (hash(\"Hello\")) { case h1: std::cout << \"匹配 Hello\" << std::endl; break; case h2: std::cout << \"匹配 World\" << std::endl; break; } // constexpr lambda (C++17) constexpr auto square_lambda = [](int x) constexpr { return x * x; }; constexpr int squared = square_lambda(5); std::cout << \"5的平方: \" << squared << std::endl; return 0;}

多线程和并发

9.1 线程基础

#include #include #include #include #include // 全局互斥锁std::mutex cout_mutex;// 线程安全打印void safe_print(const std::string& msg) { std::lock_guard<std::mutex> lock(cout_mutex); std::cout << msg << std::endl;}// 工作函数void worker(int id, int iterations) { for (int i = 0; i < iterations; ++i) { safe_print(\"线程 \" + std::to_string(id) +  \" 迭代 \" + std::to_string(i)); std::this_thread::sleep_for(std::chrono::milliseconds(100)); }}// 线程局部存储thread_local int tls_value = 0;void tls_demo(int id) { tls_value = id; std::this_thread::sleep_for(std::chrono::milliseconds(100)); safe_print(\"线程 \" + std::to_string(id) + \" TLS值: \" + std::to_string(tls_value));}// RAII线程包装class JoinThread {private: std::thread t; public: template<typename... Args> explicit JoinThread(Args&&... args) : t(std::forward<Args>(args)...) {} ~JoinThread() { if (t.joinable()) { t.join(); } } JoinThread(JoinThread&&) = default; JoinThread& operator=(JoinThread&&) = default; std::thread& get() { return t; }};int main() { // 基本线程创建 std::thread t1([]() { std::cout << \"Hello from thread!\" << std::endl; }); t1.join(); // 带参数的线程 std::thread t2(worker, 1, 3); std::thread t3(worker, 2, 3); t2.join(); t3.join(); // 获取硬件并发数 unsigned int n = std::thread::hardware_concurrency(); std::cout << \"硬件并发数: \" << n << std::endl; // 线程ID std::thread t4([]() { std::cout << \"线程ID: \" << std::this_thread::get_id() << std::endl; }); t4.join(); // 线程局部存储 std::vector<std::thread> threads; for (int i = 0; i < 5; ++i) { threads.emplace_back(tls_demo, i); } for (auto& t : threads) { t.join(); } // 使用RAII包装 { JoinThread jt([]() { std::this_thread::sleep_for(std::chrono::seconds(1)); std::cout << \"RAII线程完成\" << std::endl; }); // 自动join } return 0;}

9.2 同步原语

#include #include #include #include #include #include #include // 线程安全队列template<typename T>class ThreadSafeQueue {private: mutable std::mutex mut; std::queue<T> data_queue; std::condition_variable data_cond; public: void push(T value) { { std::lock_guard<std::mutex> lk(mut); data_queue.push(std::move(value)); } data_cond.notify_one(); } T pop() { std::unique_lock<std::mutex> lk(mut); data_cond.wait(lk, [this] { return !data_queue.empty(); }); T value = std::move(data_queue.front()); data_queue.pop(); return value; } bool try_pop(T& value) { std::lock_guard<std::mutex> lk(mut); if (data_queue.empty()) { return false; } value = std::move(data_queue.front()); data_queue.pop(); return true; }};// 读写锁示例class SharedData {private: mutable std::shared_mutex mutex_; std::vector<int> data_; public: void write(int value) { std::unique_lock lock(mutex_); data_.push_back(value); } std::vector<int> read() const { std::shared_lock lock(mutex_); return data_; }};// 递归锁class RecursiveCounter {private: mutable std::recursive_mutex mutex_; int count_ = 0; public: void increment() { std::lock_guard<std::recursive_mutex> lock(mutex_); ++count_; } void add(int n) { std::lock_guard<std::recursive_mutex> lock(mutex_); for (int i = 0; i < n; ++i) { increment(); // 递归调用，需要递归锁 } } int get() const { std::lock_guard<std::recursive_mutex> lock(mutex_); return count_; }};// 原子操作class AtomicCounter {private: std::atomic<int> count_{0}; public: void increment() { count_.fetch_add(1, std::memory_order_relaxed); } int get() const { return count_.load(std::memory_order_relaxed); } void reset() { count_.store(0, std::memory_order_relaxed); }};// 自旋锁class SpinLock {private: std::atomic_flag flag = ATOMIC_FLAG_INIT; public: void lock() { while (flag.test_and_set(std::memory_order_acquire)) { // 自旋等待 } } void unlock() { flag.clear(std::memory_order_release); }};// 生产者-消费者模型void producer(ThreadSafeQueue<int>& queue, int id) { for (int i = 0; i < 5; ++i) { queue.push(id * 100 + i); std::this_thread::sleep_for(std::chrono::milliseconds(100)); }}void consumer(ThreadSafeQueue<int>& queue, int id) { for (int i = 0; i < 5; ++i) { int value = queue.pop(); std::cout << \"消费者 \" << id << \" 获取: \" << value << std::endl; }}int main() { // 测试线程安全队列 ThreadSafeQueue<int> queue; std::thread prod1(producer, std::ref(queue), 1); std::thread prod2(producer, std::ref(queue), 2); std::thread cons1(consumer, std::ref(queue), 1); std::thread cons2(consumer, std::ref(queue), 2); prod1.join(); prod2.join(); cons1.join(); cons2.join(); // 测试原子计数器 AtomicCounter counter; std::vector<std::thread> threads; for (int i = 0; i < 10; ++i) { threads.emplace_back([&counter]() { for (int j = 0; j < 1000; ++j) { counter.increment(); } }); } for (auto& t : threads) { t.join(); } std::cout << \"原子计数器值: \" << counter.get() << std::endl; // 避免死锁 std::mutex m1, m2; std::thread t1([&]() { std::scoped_lock lock(m1, m2); // C++17 std::cout << \"线程1获取两个锁\" << std::endl; }); std::thread t2([&]() { std::scoped_lock lock(m2, m1); // 顺序不同但不会死锁 std::cout << \"线程2获取两个锁\" << std::endl; }); t1.join(); t2.join(); return 0;}

9.3 异步编程

#include #include #include #include #include #include // 异步任务int compute(int x) { std::this_thread::sleep_for(std::chrono::seconds(1)); if (x < 0) { throw std::runtime_error(\"负数输入\"); } return x * x;}// Promise和Futurevoid producer_promise(std::promise<int> prom) { try { // 模拟工作 std::this_thread::sleep_for(std::chrono::seconds(1)); prom.set_value(42); } catch (...) { prom.set_exception(std::current_exception()); }}// Packaged taskclass TaskManager {private: std::vector<std::packaged_task<int()>> tasks; std::vector<std::future<int>> futures; public: void add_task(std::packaged_task<int()> task) { futures.push_back(task.get_future()); tasks.push_back(std::move(task)); } void run_all() { for (auto& task : tasks) { std::thread(std::move(task)).detach(); } } std::vector<int> get_results() { std::vector<int> results; for (auto& fut : futures) { results.push_back(fut.get()); } return results; }};// 并行算法实现template<typename Iterator, typename T>T parallel_accumulate(Iterator first, Iterator last, T init) { const size_t length = std::distance(first, last); if (length < 1000) { return std::accumulate(first, last, init); } const size_t num_threads = std::thread::hardware_concurrency(); const size_t block_size = length / num_threads; std::vector<std::future<T>> futures; Iterator block_start = first; for (size_t i = 0; i < num_threads - 1; ++i) { Iterator block_end = block_start; std::advance(block_end, block_size); futures.push_back( std::async(std::launch::async,[block_start, block_end, init]() { return std::accumulate(block_start, block_end, init);}) ); block_start = block_end; } // 最后一个块 T last_result = std::accumulate(block_start, last, init); // 收集结果 T result = init; for (auto& fut : futures) { result += fut.get(); } return result + last_result;}// 异步任务链std::future<int> create_async_chain() { return std::async(std::launch::async, []() { return 10; }).then([](std::future<int> f) { // C++20 特性 return f.get() * 2; }).then([](std::future<int> f) { return f.get() + 5; });}int main() { // std::async基本用法 auto future1 = std::async(std::launch::async, compute, 5); auto future2 = std::async(std::launch::deferred, compute, 10); std::cout << \"异步结果1: \" << future1.get() << std::endl; std::cout << \"延迟结果2: \" << future2.get() << std::endl; // 异常处理 auto future3 = std::async(std::launch::async, compute, -1); try { std::cout << future3.get() << std::endl; } catch (const std::exception& e) { std::cout << \"捕获异常: \" << e.what() << std::endl; } // Promise和Future std::promise<int> prom; std::future<int> fut = prom.get_future(); std::thread t(producer_promise, std::move(prom)); std::cout << \"Promise结果: \" << fut.get() << std::endl; t.join(); // Shared future std::promise<int> prom2; std::shared_future<int> shared_fut = prom2.get_future().share(); auto waiter = [shared_fut](int id) { std::cout << \"线程 \" << id << \" 等待结果: \"  << shared_fut.get() << std::endl; }; std::thread t1(waiter, 1); std::thread t2(waiter, 2); std::thread t3(waiter, 3); prom2.set_value(100); t1.join(); t2.join(); t3.join(); // 并行累加 std::vector<int> vec(10000000); std::iota(vec.begin(), vec.end(), 1); auto start = std::chrono::high_resolution_clock::now(); long long sum = parallel_accumulate(vec.begin(), vec.end(), 0LL); auto end = std::chrono::high_resolution_clock::now(); auto duration = std::chrono::duration_cast<std::chrono::milliseconds>(end - start); std::cout << \"并行累加结果: \" << sum  << \" 用时: \" << duration.count() << \"ms\" << std::endl; return 0;}

现代C++特性

10.1 模块 (C++20)

// math.ixx - 模块接口文件export module math;import <iostream>;import <cmath>;export namespace math { double add(double a, double b) { return a + b; } double multiply(double a, double b) { return a * b; } class Calculator { private: double result = 0; public: void add(double x) { result += x; } void multiply(double x) { result *= x; } double get_result() const { return result; } void reset() { result = 0; } };}// 模块实现单元module math;// 私有实现细节namespace detail { void log_operation(const std::string& op) { std::cout << \"执行操作: \" << op << std::endl; }}// main.cpp - 使用模块import math;import <iostream>;int main() { std::cout << \"5 + 3 = \" << math::add(5, 3) << std::endl; std::cout << \"5 * 3 = \" << math::multiply(5, 3) << std::endl; math::Calculator calc; calc.add(10); calc.multiply(2); std::cout << \"结果: \" << calc.get_result() << std::endl; return 0;}