asynchronous 相关问题

异步编程是用于推迟具有高延迟或低优先级的操作的策略，通常旨在提高软件的性能，响应性和/或可组合性。这些策略通常使用事件驱动编程和回调的某种组合来使用，并且可选地通过协同程序和/或线程来使用并发。

如何重用 Goroutine 而不是创建新的 Goroutine 来实现异步调用

对于这个用例，它似乎可能是有效的：这是简化的代码，但你应该明白 - func Log(v 接口{}){ 1. 获取 json - json marshal 一些大对象 v 2.写大...

go asynchronous goroutine pool

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所以我想用 Playwright 做一些非常简单的事情，我只需要从我用 csv 制作的数组访问网站 var csvsync = require('csvsync'); var fs = require('fs'); var csv = fs。

javascript node.js asynchronous playwright

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从不同线程调用同一函数时如何防止竞争条件？

希望获得有关如何使用以下代码避免竞争条件的一些指导？我的班级 { private bool isRunning; private async void MyEvent() //EventHandler { 等待R...

c# multithreading asynchronous async-await race-condition

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在 Blazor Server 中，我可以强制异步方法在其他生命周期方法运行之前完成（即 OnInitialized）

我有一个 Blazor 服务器应用程序，我想在请求或刷新之间保留一些数据等。在我看来，使用 ProtectedLocalStorage 是最好的选择。我希望能够...

c# asp.net-core asynchronous blazor blazor-server-side

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如何在同一会话中多次使用同一电视马拉松客户端

我有这个电视马拉松代码：从 telethon 导入 TelegramClient 导入异步 api_id = “” api_hash =“” 会话=“约翰” 用户名 = 'Hello_World' # 例如 asy...

python asynchronous client python-asyncio telethon

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python3 asyncio 等待回调

我正在尝试弄清楚如何使用 rospy actionlib 和 asyncio 来异步等待操作结果。为了这个目的我尝试过编写一个动作执行生成器但没有成功...

python-3.x asynchronous python-asyncio rospy

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使用多个线程改变结果

我正在尝试利用多线程来优化 C++ 代码的运行时间。我尝试了几种不同的解决方案。我有这个使用 boost 的代码： #包括 #包括我正在尝试利用多线程来优化 C++ 代码的运行时间。我尝试了几种不同的解决方案。我有这个使用 boost 的代码： #include <iostream> #include <vector> #include <chrono> #include <atomic> #include <thread> #include <boost/asio.hpp> #include <boost/bind/bind.hpp> void Test::boost_worker_task() { char new_state[3][3]; MyEngine::random_start_state(new_state); MyEngine::solve_game(new_state); ++games_solved_counter; } void Test::run(const unsigned int games_to_solve, const bool use_mul_thread) { MyEngine::init_rand(); const auto start = std::chrono::high_resolution_clock::now(); const unsigned int num_threads = use_mul_thread ? std::thread::hardware_concurrency() : 1; std::cout << "Using " << num_threads << " threads to solve " << games_to_solve << " games" << std::endl; boost::asio::io_service io_service; boost::asio::thread_pool pool(num_threads); for (unsigned int i = 0; i < games_to_solve; ++i) { io_service.post([] { return Test::boost_worker_task(); }); } // Run and wait for all tasks to complete io_service.run(); pool.join(); const auto end = std::chrono::high_resolution_clock::now(); const std::chrono::duration<double, std::milli> elapsed = end - start; std::cout << "Solved " << games_solved_counter << " games!" << std::endl; std::cout << "Elapsed time: " << elapsed.count() / 1000.0 << " seconds" << std::endl; std::cout << "Elapsed time: " << elapsed.count() << " milliseconds\n" << std::endl; } 还有这段代码： #include <iostream> #include <vector> #include <thread> #include <mutex> #include <chrono> #include <atomic> #include <future> std::atomic<int> games_solved(0); void TestMulThread::worker_task(const unsigned int num_iterations, std::mutex& games_solved_mutex) { for (unsigned int i = 0; i < num_iterations; ++i) { char new_state[3][3]; MyEngine::random_start_state(new_state); MyEngine::solve_game(new_state); ++games_solved; } } void TestMulThread::run(const unsigned int total_games_to_solve) { MyEngine::init_rand(); const auto start_time = std::chrono::high_resolution_clock::now(); const unsigned int num_threads = std::thread::hardware_concurrency(); const unsigned int games_per_thread = total_games_to_solve / num_threads; const unsigned int remaining_games = total_games_to_solve % games_per_thread; std::cout << "Using " << num_threads << " threads to solve " << total_games_to_solve << " games" << std::endl; // Distribute the remaining games std::vector<unsigned int> games_for_each_thread(num_threads, games_per_thread); for (unsigned int i = 0; i < remaining_games; ++i) { games_for_each_thread[i]++; } std::vector<std::future<void>> futures; std::mutex games_solved_mutex; for (unsigned int i = 0; i < num_threads; ++i) { futures.push_back(std::async(std::launch::async, worker_task, games_for_each_thread[i], std::ref(games_solved_mutex))); } for (auto& future : futures) { future.get(); } const auto end_time = std::chrono::high_resolution_clock::now(); const auto elapsed_time = std::chrono::duration_cast<std::chrono::milliseconds>(end_time - start_time).count(); std::cout << "Solved " << games_solved << " games!" << std::endl; std::cout << "Elapsed time: " << elapsed_time / 1000.0 << " seconds" << std::endl; std::cout << "Elapsed time: " << elapsed_time << " milliseconds\n" << std::endl; } 我的问题有两个： boost 版本的运行速度比第二个代码慢得多。它甚至比使用简单的 for 循环并且不尝试利用多个线程运行得更慢。我知道尝试并行运行任务可能会导致不同类型的开销，但第二个代码运行速度非常快，我想了解原因。使用 Visual Studio 时，第二个代码片段运行得非常快（使用 Release 和 -O2 标志进行编译作为 C++ 优化），但是当我使用 g++ 在我的 Linux 机器上编译并运行相同的代码时，它的运行速度再次比使用 for 慢。循环运行相同数量的游戏。我尝试使用一些不同的设置进行编译，例如： g++ -O2 -o test Test.cpp -std=c++20 -lpthread g++ -O2 -o test Test.cpp -std=c++20 -pthread 对于为什么会出现这种情况有什么想法吗？谢谢！第一个程序从不使用线程池。除了加入。您不知道/显示 hardware_concurrency 的值，因此您无法知道您正在将苹果与苹果进行比较。如果至少修复第一个，则两者之间的性能匹配：住在Coliru 文件test.h #pragma once #include <atomic> namespace Test { static void boost_worker_task(); static void run(unsigned, bool); static inline std::atomic_uint games_solved_counter{0}; }; // namespace Test namespace TestMulThread { static void worker_task(unsigned); static void run(unsigned); static inline std::atomic_uint games_solved{0}; }; // namespace TestMulThread struct MyEngine { using State = char[3][3]; static void init_rand(); static void random_start_state(State&); static void solve_game(State&); }; 文件test.cpp #include "test.h" #include <boost/asio.hpp> #include <iostream> #include <random> #include <thread> using namespace std::chrono_literals; static constexpr auto now = std::chrono::high_resolution_clock::now; void MyEngine::init_rand() {} void MyEngine::random_start_state(State&) {} void MyEngine::solve_game(State&) { thread_local static std::mt19937 prng{std::random_device{}()}; thread_local static std::uniform_int_distribution work(3, 8); std::this_thread::sleep_for(1ms * work(prng)); }; void TestMulThread::worker_task(unsigned num_iterations) { MyEngine::init_rand(); for (unsigned int i = 0; i < num_iterations; ++i) { char new_state[3][3]; MyEngine::random_start_state(new_state); MyEngine::solve_game(new_state); ++games_solved; } } void TestMulThread::run(unsigned total_games_to_solve) { auto start_time = now(); unsigned num_threads = std::thread::hardware_concurrency(); unsigned games_per_thread = total_games_to_solve / num_threads; unsigned remaining_games = total_games_to_solve % games_per_thread; std::cout << "Using " << num_threads << " threads to solve " << total_games_to_solve << " games" << std::endl; // Distribute the remaining games std::vector games_for_each_thread(num_threads, games_per_thread); for (unsigned int i = 0; i < remaining_games; ++i) { games_for_each_thread[i]++; } std::vector<std::future<void>> futures; for (unsigned i = 0; i < num_threads; ++i) futures.push_back(std::async(std::launch::async, worker_task, games_for_each_thread[i])); for (auto& future : futures) future.get(); auto elapsed_time = now() - start_time; std::cout << "Solved " << games_solved << " games!" << std::endl; std::cout << "Elapsed time: " << elapsed_time / 1.s << " seconds" << std::endl; std::cout << "Elapsed time: " << elapsed_time / 1ms << " milliseconds\n" << std::endl; } void Test::boost_worker_task() { char new_state[3][3]; MyEngine::random_start_state(new_state); MyEngine::solve_game(new_state); ++games_solved_counter; } void Test::run(unsigned games_to_solve, bool threaded) { auto const start = now(); unsigned num_threads = threaded ? std::thread::hardware_concurrency() : 1; std::cout << "Using " << num_threads << " threads to solve " << games_to_solve << " games" << std::endl; boost::asio::thread_pool pool(num_threads); for (unsigned i = 0; i < games_to_solve; ++i) post(pool, Test::boost_worker_task); // Run and wait for all tasks to complete pool.join(); auto elapsed = now() - start; std::cout << "Solved " << games_solved_counter << " games!" << std::endl; std::cout << "Elapsed time: " << elapsed / 1.s << " seconds" << std::endl; std::cout << "Elapsed time: " << elapsed / 1ms << " milliseconds\n" << std::endl; } int main() { // auto N = 10'000u; Test::run(N, true); TestMulThread::run(N); } 打印，在线： Using 4 threads to solve 10000 games Solved 10000 games! Elapsed time: 14.04 seconds Elapsed time: 14039 milliseconds Using 4 threads to solve 10000 games Solved 10000 games! Elapsed time: 14.1067 seconds Elapsed time: 14106 milliseconds 对我来说是本地的： Using 8 threads to solve 10000 games Solved 10000 games! Elapsed time: 6.99751 seconds Elapsed time: 6997 milliseconds Using 8 threads to solve 10000 games Solved 10000 games! Elapsed time: 7.03147 seconds Elapsed time: 7031 milliseconds

c++ multithreading asynchronous boost future

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如何在Python循环中使用异步处理错误？

我正在使用 Etherscan API 收集从许多地址发送的最后一次交易的日期。我做了 python 循环来做到这一点。您可以在下面看到代码从日期时间导入日期时间从 etherscan 导入

python api loops asynchronous error-handling

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使用 Fetch API 时无法读取 null 的属性（读取“值”）

我想从api获取一些产品，问题是模板不会等待异步函数运行，也不会等待产品属性填充获取的数据，因为它是一个异步函数...

vue.js asynchronous async-await fetch-api

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Python 并行异步处理来自 iterable 的 api 调用

我正在为 Google Workspace 创建一个自动化脚本，它会获取某个组织部门的直接子级，然后同时获取所有这些 OU 的子级。在寻找...