completed = StudentGroup([a_qiang, lao_wang], {'任务完成': True}) 这句python是什么语法

这句 Python 代码是使用了类和对象的语法。`StudentGroup` 是一个自定义的类，`completed` 是该类的一个实例对象。该实例对象被初始化时传入了两个参数：一个是名为 `a_qiang` 的对象，另一个是一个字典 `{'任务完成': True}`。这个字典是作为第二个参数传递给 `StudentGroup` 类的构造函数。

相关问题

代码优化 def process_data(data): # 处理数据逻辑 print("Processing data:", data) def push_data(data_queue:queue.Queue): while True: data_queue.put(str("123")) time.sleep(0.5) # Press the green button in the gutter to run the script. if __name__ == '__main__': print_hi('PyCharm') data_queue = queue.Queue() data_thread = threading.Thread(target=process_data, args=(data_queue,)) data_thread.start() # 创建线程池 executor = ThreadPoolExecutor(max_workers=5) # 从队列中获取数据并处理 while True: data = data_queue.get() if data: print('data = {}'.format(data)) # 提交任务到线程池 executor.submit(process_data, data)

在这段代码中，我们可以看到有一些可以进行优化的部分。

首先，`process_data`函数中的处理逻辑看起来很简单，可以直接在`push_data`函数中完成，避免创建多个线程来处理。因此，我们可以将`process_data`函数的内容移动到`push_data`函数中，然后将`process_data`函数从`ThreadPoolExecutor`中删除，直接在`executor.submit`中调用`push_data`函数即可。

其次，`push_data`函数中的无限循环可以使用`while`循环和`Event`对象来实现，避免在循环中使用`time.sleep`来等待一段时间。这样可以使程序更加高效和可控。

最后，我们可以使用`with`语句来自动管理线程池，避免手动关闭线程池时出现问题。

下面是优化后的代码：

import queue
import threading
from concurrent.futures import ThreadPoolExecutor, as_completed
from threading import Event

def push_data(data_queue: queue.Queue):
    while not stop_event.is_set():
        data = "123"
        data_queue.put(data)
        stop_event.wait(0.5)

def process_data(data):
    # 处理数据逻辑
    print("Processing data:", data)

if __name__ == '__main__':
    data_queue = queue.Queue()
    stop_event = Event()

    # 创建线程池
    with ThreadPoolExecutor(max_workers=5) as executor:
        # 启动数据生产线程
        t = threading.Thread(target=push_data, args=(data_queue,))
        t.start()

        # 从队列中获取数据并处理
        while not stop_event.is_set():
            try:
                data = data_queue.get(timeout=1)
            except queue.Empty:
                continue

            # 提交任务到线程池
            future = executor.submit(process_data, data)
            future.add_done_callback(lambda f: f.result())

    # 关闭数据生产线程
    stop_event.set()
    t.join()

在优化后的代码中，我们使用`while`循环和`Event`对象来实现线程的控制。`push_data`函数中的循环会在`stop_event`对象被设置时结束，而不需要使用`time.sleep`等待一段时间。同时，我们使用`with`语句来自动管理线程池，避免手动关闭线程池时出现问题。

给下列程序添加注释： void DWAPlannerROS::reconfigureCB(DWAPlannerConfig &config, uint32_t level) { if (setup_ && config.restore_defaults) { config = default_config_; config.restore_defaults = false; } if ( ! setup_) { default_config_ = config; setup_ = true; } // update generic local planner params base_local_planner::LocalPlannerLimits limits; limits.max_vel_trans = config.max_vel_trans; limits.min_vel_trans = config.min_vel_trans; limits.max_vel_x = config.max_vel_x; limits.min_vel_x = config.min_vel_x; limits.max_vel_y = config.max_vel_y; limits.min_vel_y = config.min_vel_y; limits.max_vel_theta = config.max_vel_theta; limits.min_vel_theta = config.min_vel_theta; limits.acc_lim_x = config.acc_lim_x; limits.acc_lim_y = config.acc_lim_y; limits.acc_lim_theta = config.acc_lim_theta; limits.acc_lim_trans = config.acc_lim_trans; limits.xy_goal_tolerance = config.xy_goal_tolerance; limits.yaw_goal_tolerance = config.yaw_goal_tolerance; limits.prune_plan = config.prune_plan; limits.trans_stopped_vel = config.trans_stopped_vel; limits.theta_stopped_vel = config.theta_stopped_vel; planner_util_.reconfigureCB(limits, config.restore_defaults); // update dwa specific configuration dp_->reconfigure(config); }

/**
* @brief Callback function for dynamic reconfiguration of DWA planner parameters
*
* @param config Reference to the configuration object that stores the updated parameters
* @param level The level of reconfiguration, unused in this function
*/
void DWAPlannerROS::reconfigureCB(DWAPlannerConfig &config, uint32_t level) {

// If the setup has been completed and restore_defaults flag is set, restore default configuration
if (setup_ && config.restore_defaults) {
config = default_config_;
config.restore_defaults = false;
}

// If setup has not been completed, store default configuration and set the setup flag to true
if ( ! setup_) {
default_config_ = config;
setup_ = true;
}

// Update generic local planner parameters
base_local_planner::LocalPlannerLimits limits;
limits.max_vel_trans = config.max_vel_trans;
limits.min_vel_trans = config.min_vel_trans;
limits.max_vel_x = config.max_vel_x;
limits.min_vel_x = config.min_vel_x;
limits.max_vel_y = config.max_vel_y;
limits.min_vel_y = config.min_vel_y;
limits.max_vel_theta = config.max_vel_theta;
limits.min_vel_theta = config.min_vel_theta;
limits.acc_lim_x = config.acc_lim_x;
limits.acc_lim_y = config.acc_lim_y;
limits.acc_lim_theta = config.acc_lim_theta;
limits.acc_lim_trans = config.acc_lim_trans;
limits.xy_goal_tolerance = config.xy_goal_tolerance;
limits.yaw_goal_tolerance = config.yaw_goal_tolerance;
limits.prune_plan = config.prune_plan;
limits.trans_stopped_vel = config.trans_stopped_vel;
limits.theta_stopped_vel = config.theta_stopped_vel;

// Call reconfigureCB function of the planner_util_ object with updated limits and restore_defaults flag
planner_util_.reconfigureCB(limits, config.restore_defaults);

// Call reconfigure function of the dp_ object with updated configuration
dp_->reconfigure(config);
}