Whiptail输入框取消不起作用

Question

我已经为新用户创建了一个循环来完成一些虚拟机设置功能，这些功能包括添加主机名，IP地址等等。但是，如果我点击任何一个内的“取消”按钮鞭尾窗，它只是移动到循环中的下一个whiptail元素。如果选择Cancel，如何将其设置为取消循环并返回主菜单窗口？

while true
do

OPTION=$(whiptail --title "Configuration Menu" --menu "Choose an option" 20 78 10 \
"1"     "Show current configuration." \
"2"     "Setup Wizard." \
...
"0"     "EXIT" 3>&1 1>&2 2>&3)

exitstatus=$?

case "$OPTION" in
 ...
 2)
    # Setup hostname
    HOSTNAME=$(whiptail --inputbox "Hostname" 8 78 `hostname` --title "Serial Number" 3>&1 1>&2 2>&3)
    ...
    # IP address configuration
    IP_CONFIG=$(whiptail --title "Network Configuration" --radiolist "Choose a configuration option" 20 78 10 \
        "DHCP" "Use Dynamic Host Protocol" ON \
        "STATIC" "Configure Static IP" OFF 3>&1 1>&2 2>&3)
     ...
 ;;
esac

以下是主菜单的样子：

如果在第一个输入框中单击“取消”时...

我被发送到下一个whiptail元素而不是取消到主菜单：

Answer 1

好的，想通了。我必须将每个案例选项包装在其自己的exitstatus = 0测试中：

2)
      # Setup serial number
      SERIAL=$(whiptail --inputbox "Serial Number" 8 78 `hostname` --title "Serial Number" 3>&1 1>&2 2>&3)
      exitstatus=$?
      if [ $exitstatus = 0 ]; then
         ...
      else
         break
      fi
      ;;
...

Answer 2

使用退出循环的# Let's begin by importing some libraries we'll need import numpy as np from __future__ import print_function # So that this notebook becomes both Python 2 and Python 3 compatible # And creating some random data size = 10 np.random.seed(0) x_data = np.arange(size) y_data = np.cumsum(np.random.randn(size) * 100.0) from bqplot import pyplot as plt # Creating a new Figure and setting it's title plt.figure(title='My Second Chart') # Let's assign the scatter plot to a variable scatter_plot = plt.scatter(x_data, y_data) # Let's show the plot plt.show() # then enable modification and attach a callback function: def foo(change): print('This is a trait change. Foo was called by the fact that we moved the Scatter') print('In fact, the Scatter plot sent us all the new data: ') print('To access the data, try modifying the function and printing the data variable') global pdata pdata = [scatter_plot.x,scatter_plot.y] # First, we hook up our function `foo` to the colors attribute (or Trait) of the scatter plot scatter_plot.observe(foo, ['y','x']) scatter_plot.enable_move = True 。 break在whiptail选择中返回1，因此请对此进行测试，如果是<Cancel>则为{<1}}：

break