Question

我有一个计算斐波那契数的函数。我正在尝试添加一个发送信号的功能，该信号指示我需要暂停该功能的运行。收到信号后，我将存储到目前为止计算出的所有数字。

当用户想要恢复该功能时，我可以加载文件并从停止的地方开始计算。

这是我的代码

<p>{‌{currentStatus}}</p>

<script>
import { eventBus } from "../../main";

export default {
  data: function() {
    return {
      currentStatus: "Server Details are currently not updated"
    };
  },
  create() {
    eventBus.$on("statChanges", stat => {
      this.currentStatus = stat;
    });
  }
};
</script>

该功能开始运行后，我无法确定的部分是如何使用此MAX = 100000 fibo_series = [0] * MAX import pickle def fib(start_value=0, stop_value=1000, stop_signal=False): if not stop_signal: for i in range(start_value, stop_value): if i == 0: fibo_series[i] = 0 elif i == 1 or i == 2: fibo_series[i] = 1 else: fibo_series[i] = fibo_series[i-1] + fibo_series[i-2] return fibo_series[i] else: with open('fibo_series.pkl', 'wb') as f: pickle.dump(fibo_series, f) def reload_fib(): with open('fibo_series.pkl', 'rb') as f: fibo_series = pickle.load(f) start_value = fibo_series[1:].index(0) + 1 stop_value = len(fibo_series) return fib(start_value, stop_value, stop_signal=False)。函数启动后，值stop_signal将被锁定。我知道要暂停功能的唯一方法是终止它，这不是我要执行的操作。

我该如何实现？

Answer 1

我不确定停止和运行的条件是什么，但是一个简单的解决方法是为这两个函数使用全局变量。这并不比使用线程库锁更好，但是如果您的工作只是使用一个进程并且不需要复杂性，那么您可以尝试。

    long_weekend  weekday         Date   Public_Holiday? Weekend?
            1        5     2015-01-10              no      yes
            0        0     2015-01-12              no       no
            0        1     2015-01-13              no       no
            0        2     2015-01-14              no       no
            0        3     2015-01-15              no       no
            0        4     2015-01-16              no       no
            1        5     2015-01-17              no      yes
            1        6     2015-01-18              no      yes
            0        0     2015-01-19              no       no
            0        1     2015-01-20              no       no
            0        2     2015-01-21              no       no
            0        3     2015-01-22              no       no
            1        4     2015-01-23              yes      no
            1        5     2015-01-24              no      yes
            1        6     2015-01-25              no      yes
            0        1     2015-01-27              no       no
            0        2     2015-01-28              no       no
            0        3     2015-01-29              no       no
            0        4     2015-01-30              no       no
            1        5     2015-01-31              no      yes
            0        0     2015-02-02              no       no
            0        1     2015-02-03              no       no
            0        2     2015-02-04              no       no
            0        3     2015-02-05              no       no
            0        4     2015-02-06              no       no
            1        5     2015-02-07              no      yes
            1        6     2015-02-08              no      yes
            1        0     2015-02-09              yes      no
            0        1     2015-02-10              no       no
            0        2     2015-02-11              no       no

然后，每当用户想要停止执行时，都可以设置全局变量import threading import time MAX = 100000 fibo_series = [0] * MAX import pickle stop_signal = False def fib(start_value=0, stop_value=1000): for i in range(start_value, stop_value): if (not stop_signal): print('here', i) time.sleep(1) if i == 0: fibo_series[i] = 0 elif i == 1 or i == 2: fibo_series[i] = 1 else: fibo_series[i] = fibo_series[i-1] + fibo_series[i-2] else: break return fibo_series[i] print('exiting... stop_signal: ', stop_signal) with open('fibo_series.pkl', 'wb') as f: pickle.dump(fibo_series, f) def reload_fib(): with open('fibo_series.pkl', 'rb') as f: fibo_series = pickle.load(f) start_value = fibo_series[1:].index(0) + 1 stop_value = len(fibo_series) global stop_signal stop_signal = False return fib(start_value, stop_value) x = threading.Thread(target=fib ) x.start() time.sleep(10) stop_signal = True print('finished...')

，输出为：

stop_signal=True

我希望这会有所帮助。

在python中启动和暂停进程

1 个答案: