参考项目
https://github.com/progschj/ThreadPool
源码分析
// 常规头文件保护宏, 避免重复 include
#ifndef THREAD_POOL_H
#define THREAD_POOL_H
// 线程池, 存储线程对象;
#include <vector>
// 任务队列, 双向都可操作队列, queue 不能删除首个元素
#include <queue>
// 智能指针
#include <memory>
// c++11 线程对象
#include <thread>
// 锁保护队列多线程任务添加, 删除的安全;
#include <mutex>
// 条件变量用来 condition wait 和 notify; 即事件的通知和阻塞等待
#include <condition_variable>
// future 用来获取更友好的封装任务(函数), 并获取返回值;
#include <future>
// function 任务队列
#include <functional>
// 非法场景抛出异常
#include <stdexcept>
// 为什么不用模板? 因为 enqueue 是模板, 可以兼容几乎所有场景;
class ThreadPool {
public:
// 设置线程池大小
ThreadPool(size_t);
// 添加函数, function 和 args
template<class F, class... Args>
auto enqueue(F&& f, Args&&... args) -> std::future<typename std::result_of<F(Args...)>::type>;
// 吸狗函数
~ThreadPool();
private:
// need to keep track of threads so we can join them
std::vector< std::thread > workers;
// the task queue
std::queue< std::function<void()> > tasks;
// synchronization
std::mutex queue_mutex;
std::condition_variable condition;
bool stop;
};
// the constructor just launches some amount of workers
inline ThreadPool::ThreadPool(size_t threads)
: stop(false)
{
for(size_t i = 0;i<threads;++i)
// 添加任务, 用 emplace_back 的形势, 避免某些类型不支持拷贝;
workers.emplace_back(
// lambda 捕获 this 对象, 用于操作任务队列;
[this]
{
// 死循环等待任务
for(;;)
{
// 任务获取 void() 类型 统一封装, 后面用 packaged_task 封装不同的
std::function<void()> task;
{
// 构建对象用于 condition
std::unique_lock<std::mutex> lock(this->queue_mutex);
// 等待线程池停止, 或者有任务;
this->condition.wait(lock, [this]{
return this->stop || !this->tasks.empty(); });
// 如果有任务 则 false, 即使停止也需要执行完任务之后再停止队列
// 如果请求停止, 且没有任务，则终止;
if(this->stop && this->tasks.empty())
return;
// 获取第一个任务;
task = std::move(this->tasks.front());
this->tasks.pop();
}
// 执行获取到任务;
task();
}
}
);
}
// add new work item to the pool
template<class F, class... Args>
auto ThreadPool::enqueue(F&& f, Args&&... args) -> std::future<typename std::result_of<F(Args...)>::type>
{
// 模板获取函数返回值类型
using return_type = typename std::result_of<F(Args...)>::type;
// 将对象通过 bind 打包成可调用对象, 并封装到 packeaged_task;
auto task = std::make_shared< std::packaged_task<return_type()> >(
std::bind(std::forward<F>(f), std::forward<Args>(args)...)
);
// 生成获取函数返回值的具柄对象;
std::future<return_type> res = task->get_future();
{
// 加锁添加元素;
std::unique_lock<std::mutex> lock(queue_mutex);
// don't allow enqueueing after stopping the pool
if(stop)
throw std::runtime_error("enqueue on stopped ThreadPool");
// 用 lambda 再封装是为了统一函数格式 void()
// task 是 shared_ptr, 避免拷贝;
tasks.emplace([task](){
(*task)(); });
}
// 提醒阻塞线程有新的任务;
condition.notify_one();
// 返回获取函数返回值的具柄, 这样可以获取返回值;
return res;
}
// the destructor joins all threads
inline ThreadPool::~ThreadPool()
{
{
// 加锁请求停止
std::unique_lock<std::mutex> lock(queue_mutex);
stop = true;
}
// 提醒所有阻塞线程, 需要停止线程池
condition.notify_all();
// join每个 thread 对象; 可以用 std::future 来作为 thread 对象, 让 std 管理生命周期;
// 除非开发者有更加细致的管理, 如 优先级, 栈, 添加属性之类的操作;
for(std::thread &worker: workers)
worker.join();
}
#endif
使用案例一
// create thread pool with 4 worker threads
ThreadPool pool(4);
// enqueue and store future
auto result = pool.enqueue([](int answer) {
return answer; }, 42);
// get result from future
std::cout << result.get() << std::endl;
使用案例二
#include <iostream>
#include <vector>
#include <chrono>
#include "ThreadPool.h"
int main()
{
ThreadPool pool(4);
std::vector< std::future<int> > results;
for(int i = 0; i < 8; ++i) {
results.emplace_back(
pool.enqueue([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;
})
);
}
for(auto && result: results)
std::cout << result.get() << ' ';
std::cout << std::endl;
return 0;
}
无注释版本
#ifndef THREAD_POOL_H
#define THREAD_POOL_H
#include <vector>
#include <queue>
#include <memory>
#include <thread>
#include <mutex>
#include <condition_variable>
#include <future>
#include <functional>
#include <stdexcept>
class ThreadPool {
public:
ThreadPool(size_t);
template<class F, class... Args>
auto enqueue(F&& f, Args&&... args)
-> std::future<typename std::result_of<F(Args...)>::type>;
~ThreadPool();
private:
// need to keep track of threads so we can join them
std::vector< std::thread > workers;
// the task queue
std::queue< std::function<void()> > tasks;
// synchronization
std::mutex queue_mutex;
std::condition_variable condition;
bool stop;
};
// the constructor just launches some amount of workers
inline ThreadPool::ThreadPool(size_t threads)
: stop(false)
{
for(size_t i = 0;i<threads;++i)
workers.emplace_back(
[this]
{
for(;;)
{
std::function<void()> task;
{
std::unique_lock<std::mutex> lock(this->queue_mutex);
this->condition.wait(lock,
[this]{
return this->stop || !this->tasks.empty(); });
if(this->stop && this->tasks.empty())
return;
task = std::move(this->tasks.front());
this->tasks.pop();
}
task();
}
}
);
}
// add new work item to the pool
template<class F, class... Args>
auto ThreadPool::enqueue(F&& f, Args&&... args)
-> std::future<typename std::result_of<F(Args...)>::type>
{
using return_type = typename std::result_of<F(Args...)>::type;
auto task = std::make_shared< std::packaged_task<return_type()> >(
std::bind(std::forward<F>(f), std::forward<Args>(args)...)
);
std::future<return_type> res = task->get_future();
{
std::unique_lock<std::mutex> lock(queue_mutex);
// don't allow enqueueing after stopping the pool
if(stop)
throw std::runtime_error("enqueue on stopped ThreadPool");
tasks.emplace([task](){
(*task)(); });
}
condition.notify_one();
return res;
}
// the destructor joins all threads
inline ThreadPool::~ThreadPool()
{
{
std::unique_lock<std::mutex> lock(queue_mutex);
stop = true;
}
condition.notify_all();
for(std::thread &worker: workers)
worker.join();
}
#endif
