kev/Drawer/Module/GeoSigmaDraw/AsyncWorker.h

#include <functional>
#include <mutex>
#include <condition_variable>
#include <atomic>
#include <future>
#include <queue>

/**
 * 异步任务执行类，它的主要作用是让任务都在一个后台线程中排队执行，避免业务代码中到处加锁
 */
class AsyncWorker
{
public:
	AsyncWorker()
		: done(false)
	{
		worker_thread = std::thread(&AsyncWorker::workerLoop, this);
	}

	~AsyncWorker()
	{
		{
			std::lock_guard<std::mutex> lock(queue_mutex);
			done = true;
		}
		cond_var.notify_all();
		if (worker_thread.joinable())
		{
			worker_thread.join();
		}
	}

	template <typename Func>
	auto postTask(Func task) -> std::future<decltype(task())>
	{
		using result_type = decltype(task());
		auto packaged_task = std::make_shared<std::packaged_task<result_type()>>(task);
		std::future<result_type> result = packaged_task->get_future();
		{
			std::lock_guard<std::mutex> lock(queue_mutex);
			task_queue.push([packaged_task] { (*packaged_task)(); });
		}
		cond_var.notify_one();
		return result;
	}

private:
	void workerLoop()
	{
		while (true)
		{
			std::function<void()> task;
			{
				std::unique_lock<std::mutex> lock(queue_mutex);
				cond_var.wait(lock, [this] { return !task_queue.empty() || done; });
				if (done && task_queue.empty())
				{
					return;
				}
				task = std::move(task_queue.front());
				task_queue.pop();
			}
			task();
		}
	}

	std::thread worker_thread;
	std::queue<std::function<void()>> task_queue;
	std::mutex queue_mutex;
	/*
	 * 根据 cppreference 的说法，std::condition_variable 只能  std::unique_lock 的情况下生效，
	 * 这里采用 std::condition_variable_any
	 * The condition_variable_any class is a generalization of std::condition_variable.
	 * Whereas std::condition_variable works only on std::unique_lock<std::mutex>, 
	 * condition_variable_any can operate on any lock that meets the BasicLockable requirements.
	 */
	std::condition_variable_any cond_var;
	std::atomic<bool> done;
};