c++11/14、c++17/20 最简单的线程池

Posted on Edited on

c++11 最基础最简单的：

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#pragma once
#include<vector>
#include<queue>
#include<memory>
#include<thread>
#include<mutex>
#include<condition_variable>
#include<future>
#include<functional>
#include<stdexcept>
#include<type_traits>

class ThreadPool
{
public:
    ThreadPool();
    ThreadPool(int num);
    ~ThreadPool();

    template<class F, class... Args>
    std::future<int> enqueue(F& f, Args&... args);

private:
    std::vector <std::thread> workers; //thread array

    std::queue<std::function<void()>>tasks; //task queue

    std::mutex queue_mutex;
    std::condition_variable cond;
    bool stop;
};

inline ThreadPool::ThreadPool()
{
}

ThreadPool::ThreadPool(int num) :stop(false)
{
    for (size_t i = 0; i < num; i++)
    {
        auto thread = [this] {
            for (;;)
            {
                std::function<void()> task;
                {
                    std::unique_lock<std::mutex> lock(this->queue_mutex);
                    this->cond.wait(lock, [this] {
                        return this->stop || !this->tasks.empty();//stop 或许任务队列不为空时唤醒。
                        }
                    );

                    if (stop && tasks.empty())
                        return;
                    task = std::move(tasks.front());
                    tasks.pop();//有点类似bfs的思路
                }

                task();
            }
        };
        workers.emplace_back(thread);

    }
}

inline ThreadPool::~ThreadPool()
{
    {
        std::unique_lock<std::mutex> lock(queue_mutex);
        stop = true;
    }
    cond.notify_all();

    for (auto& worker : workers)
    {
        worker.join();
    }
}


//}

template<class F, class... Args>
std::future<int> ThreadPool::enqueue(F& f, Args&... args)
{
    std::function<decltype(f(args...))()> func = 
        std::bind(std::forward<F>(f), std::forward<Args>(args)...); // 连接函数和参数定义，特殊函数类型，避免左右值错误

    auto task = std::make_shared< std::packaged_task<int()> >(
     func
        );

    std::function<void()> warpper_func = [task](){(*task)();};
      std::unique_lock<std::mutex> lock(queue_mutex);
      tasks.emplace(warpper_func);
     cond.notify_one();
    return task->get_future();
}

test:

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int main()
{ 
ThreadPool pool(4);
    std::vector<std::future<int>>results;

    for (size_t i = 0; i < 8; i++)
    {
        auto tp = [i] {
            std::cout << "hello " << i << std::endl;
           // std::this_thread::sleep_for(std::chrono::seconds(1));
            std::cout << "world " << i << std::endl;
            return i * i;

        };
        results.emplace_back(
            pool.enqueue((tp))
        );

    }


  
    for (auto&& result : results)
        std::cout << result.get() << ' ';
    std::cout << std::endl;

    return 0;
}

C++11/14 一般性的线程池

上面我们有很多不足，比如限定了task function的返回值，而且逻辑不够优美。我们接着进行优化！

关于task function的 return type 是未定的问题，c++11 给出了两种方式。一个是decltype(expr),另外一个是std::result_of. 都可以通过尾置返回值类型进行处理。

我们首先使用decltype. 完整代码如下：

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#pragma once
#include<vector>
#include<queue>
#include<memory>
#include<thread>
#include<mutex>
#include<condition_variable>
#include<future>
#include<functional>
#include<stdexcept>
#include<type_traits>

class ThreadPool
{
public:
	ThreadPool();
	ThreadPool(int num);
	~ThreadPool();
	template<class F, class... Args>
	auto enqueue(F&& f, Args&&... args)
//		->std::future<decltype(f(args...))>;
private:
	std::vector <std::thread> workers; //thread array

	std::queue<std::function<void()>>tasks; //task queue

	std::mutex queue_mutex;
	std::condition_variable cond;
	bool stop;
};

inline ThreadPool::ThreadPool()
{
}

ThreadPool::ThreadPool(int num) :stop(false)
{
    for (size_t i = 0; i < num; i++)
    {
        auto thread = [this] {
            for (;;)
            {
                std::function<void()> task;
                {
                    std::unique_lock<std::mutex> lock(this->queue_mutex);
                    this->cond.wait(lock, [this] {
                        return this->stop || !this->tasks.empty();//stop 或许任务队列不为空时唤醒。
                        }
                    );

                    if (stop && tasks.empty())
                        return;
                    task = std::move(tasks.front());
                    tasks.pop();//有点类似bfs的思路
                }

                task();
            }
        };
        workers.emplace_back(thread);

    }
}

inline ThreadPool::~ThreadPool()
{
	{
		std::unique_lock<std::mutex> lock(queue_mutex);
		stop = true;
	}
	cond.notify_all();

	for (auto& worker : workers)
	{
		worker.join();
	}
}


template<class F, class... Args>
auto ThreadPool::enqueue(F&& f, Args&&... args)
-> std::future<decltype(f(args...))>
{
	using ret_type = std::future<decltype(f(args...))>;
	std::function<decltype(f(args...))()> func =
		std::bind(std::forward<F>(f), std::forward<Args>(args)...); // 连接函数和参数定义，特殊函数类型，避免左右值错误

	auto task = std::make_shared< std::packaged_task<decltype(f(args...))()> >(
		func
		);

	std::function<void()> warpper_func = [task]() {(*task)(); };
	ret_type res = task->get_future();
	if (stop)
		throw std::runtime_error("enqueue on stopped ThreadPool");
	std::unique_lock<std::mutex> lock(queue_mutex);
	tasks.emplace(warpper_func);
	cond.notify_one();
	return res;
}

优化版createthread 单独抽出来组成一个接口。

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#pragma once
#include<vector>
#include<queue>
#include<memory>
#include<thread>
#include<mutex>
#include<condition_variable>
#include<future>
#include<functional>
#include<stdexcept>
#include<type_traits>
#include <utility>

class ThreadPool
{
public:
	ThreadPool();
	ThreadPool(int num);
	~ThreadPool();

	void CreateThread(void);

	//template<class F, class...Args>
	//auto enqueue(F&& f, Args&&...args)->std::future<typename std::_Forced_result_type<F(Args...)>::type>;
	template<class F, class... Args>
	auto enqueue(F &&f, Args&&... args)
	->std::future<decltype(f(args...))>;
private:
	std::vector <std::thread> workers; //thread array

	std::queue<std::function<void()>>tasks; //task queue

	std::mutex queue_mutex;
	std::condition_variable cond;
	bool stop;
};

inline ThreadPool::ThreadPool()
{
}

inline void ThreadPool::CreateThread(void)
{
	for (;;)
	{
		std::function<void()> task;
		{
			std::unique_lock<std::mutex> lock(this->queue_mutex);
			this->cond.wait(lock, [this] {
				return this->stop || !this->tasks.empty();//stop 或许任务队列不为空时唤醒。
				}
			);

			if (stop && tasks.empty())
				return;
			task = std::move(tasks.front());
			tasks.pop();//有点类似bfs的思路
		}

		task();
	}
}

ThreadPool::ThreadPool(int num) :stop(false)
{
	for (size_t i = 0; i < num; i++)
	{
		auto thread = std::bind(&ThreadPool::CreateThread,this);//&，this 不能丢
		workers.emplace_back(thread);

		//或者直接下面
		//workers.emplace_back(std::bind(&ThreadPool::CreateThread, this));

	}
}

inline ThreadPool::~ThreadPool()
{
	{
		std::unique_lock<std::mutex> lock(queue_mutex);
		stop = true;
	}
	cond.notify_all();

	for (auto& worker : workers)
	{
		worker.join();
	}
}


template<class F, class... Args>
auto ThreadPool::enqueue(F&& f, Args&&... args)
->std::future<decltype(f(args...))>
{
	using ret_type = std::future< decltype(f(args...))>; //typename 此处加不加均可以的，下面同
	std::function< decltype(f(args...))()> func =
		std::bind(std::forward<F>(f), std::forward<Args>(args)...); // 连接函数和参数定义，特殊函数类型，避免左右值错误

	auto task = std::make_shared< std::packaged_task< decltype(f(args...))()> >(
		func
		);

	std::function<void()> warpper_func = [task]() {(*task)(); };
	ret_type res = task->get_future();
	if (stop)
		throw std::runtime_error("enqueue on stopped ThreadPool");
	std::unique_lock<std::mutex> lock(queue_mutex);
	tasks.emplace(warpper_func);
	cond.notify_one();
	return res;
}

test 代码：

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int main()
{
    ThreadPool pool(4);
    std::vector<std::future<int>>results;

    for (int i = 0; i < 8; i++)
    {
        auto tp = [i] {
            std::cout << "hello " << i << std::endl;
            std::this_thread::sleep_for(std::chrono::seconds(1));
            std::cout << "world " << i << std::endl;
            return i * i;

        };
        auto ans = pool.enqueue(std::move(tp));
        results.emplace_back(std::move(ans));

    }

  
    for (auto&& result : results)
        std::cout << result.get() << ' ';
    std::cout << std::endl;

    return 0;
}

那我们现在采用第二种方式。

需要更改的地方如下：

enqueue 的声明：

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template<class F, class... Args>
	auto enqueue(F&& f, Args&&... args)
	->std::future<typename std::result_of<F(Args...)>::type>;

enqueue 的定义：

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template<class F, class... Args>
auto ThreadPool::enqueue(F&& f, Args&&... args)
->std::future<typename std::result_of<F(Args...)>::type>
{
	using ret_type = std::future<typename std::result_of<F(Args...)>::type>; //typename 此处加不加均可以的，下面同
	std::function<typename std::result_of<F(Args...)>::type()> func =
		std::bind(std::forward<F>(f), std::forward<Args>(args)...); // 连接函数和参数定义，特殊函数类型，避免左右值错误

	auto task = std::make_shared< std::packaged_task<typename std::result_of<F(Args...)>::type()> >(
		func
		);

	std::function<void()> warpper_func = [task]() {(*task)(); };
	ret_type res = task->get_future();
	if (stop)
		throw std::runtime_error("enqueue on stopped ThreadPool");
	std::unique_lock<std::mutex> lock(queue_mutex);
	tasks.emplace(warpper_func);
	cond.notify_one();
	return res;
}