What are the advantages of using C++ lambda expressions for multi-threaded programming?

The advantages of lambda expressions in C multi-threaded programming include simplicity, flexibility, ease of parameter passing, and parallelism. Practical case: Use lambda expressions to create multi-threads and print thread IDs in different threads, demonstrating the simplicity and ease of use of this method.

Advantages of using C lambda expressions to implement multi-threaded programming

Introduction

lambda expressions are a powerful feature introduced in C 11 that can represent function objects within a block. In multi-threaded programming, lambda expressions provide a concise and powerful way to define parallel tasks.

Advantages

The main advantages of using lambda expressions for multi-threaded programming include:

• Simplicity: Lambda expressions are concise and easy to read, thus simplifying multi-threaded code.
• Flexibility: lambda expressions can capture external variables, allowing dynamic access to data.
• Easy to pass parameters: Lambda expressions can be easily passed as parameters to other functions and threads.
• Parallelism: Lambda expressions can be executed simultaneously, improving application performance.

Practical case

The following example shows how to use lambda expressions to create a multi-threaded program in C:

#include <iostream>
#include <thread>
#include <vector>

int main() {
    // 创建一个 vector 来存储线程
    std::vector<std::thread> threads;

    // 使用 lambda 表达式定义并行任务
    auto task = [](const int &n) {
        std::cout << "Thread " << n << " is running." << std::endl;
    };

    // 创建并启动线程
    for (int i = 0; i < 10; i++) {
        threads.emplace_back(std::thread(task, i));
    }

    // 等待线程完成
    for (auto &thread : threads) {
        thread.join();
    }

    return 0;
}

Run Result :

Thread 0 is running.
Thread 1 is running.
Thread 2 is running.
...
Thread 9 is running.

In this example, a lambda expression is used to define a parallel task that prints the ID of the thread. The program creates 10 threads and uses lambda expressions to execute these tasks in parallel. Using lambda expressions, we write concise and understandable multi-threaded code.

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