State Machines in Python - Part 3.ipynb

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   "source": [
    "# State Machines in Python - Part 3\n",
    "\n",
    "## Entry and Exit Actions\n",
    "\n",
    "Below you the code from the signal light we had before. We just applied a slight change: The states `on` and `off` are now also detailed by dictionaries. Now they can specify entry actions, that are called when the state is entered. We just move the actions that we had previously on the transitions into the states.\n",
    "\n",
    "Note that this also works for exit action, using the dictionary key `exit`, and you can have as many actions as you like, by separating them with a `;`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
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\" style=\"max-width:100%;\" />"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from stmpy import Machine, Driver\n",
    "\n",
    "import ipywidgets as widgets\n",
    "from IPython.display import display\n",
    "\n",
    "\n",
    "class SignalLight:\n",
    "\n",
    "    def on_button_switch(self, b):\n",
    "        self.stm.send('switch')  # <---- here we send a message\n",
    "\n",
    "    def on_button_terminate(self, b):\n",
    "        self.stm.driver.stop()  # <---- here we stop the driver\n",
    "\n",
    "    def __init__(self):\n",
    "        # load images and store them\n",
    "        self.yellow_on = open(\"images/yellow_on.png\", \"rb\").read()\n",
    "        self.yellow_off = open(\"images/yellow_off.png\", \"rb\").read()\n",
    "\n",
    "        # display the user interface\n",
    "        # a button\n",
    "        self.button_switch = widgets.Button(description=\"Send 'switch'\")\n",
    "        self.button_switch.on_click(self.on_button_switch)\n",
    "        # another button\n",
    "        self.button_terminate = widgets.Button(description=\"Stop the Driver\")\n",
    "        self.button_terminate.on_click(self.on_button_terminate)\n",
    "        # an image of a yellow light\n",
    "        self.yellow = widgets.Image(\n",
    "            value=self.yellow_off, format='png', width=50, height=50)\n",
    "        # display everything\n",
    "        display(self.yellow, self.button_switch, self.button_terminate)\n",
    "\n",
    "    def turn_yellow_on(self):\n",
    "        # switch on the yellow light\n",
    "        self.yellow.set_trait(name='value', value=self.yellow_on)\n",
    "\n",
    "    def turn_yellow_off(self):\n",
    "        # switch off the yellow light\n",
    "        self.yellow.set_trait(name='value', value=self.yellow_off)\n",
    "\n",
    "\n",
    "signal = SignalLight()\n",
    "\n",
    "t0 = {'source': 'initial',\n",
    "      'target': 'off'}\n",
    "\n",
    "# Change 1: effect is removed\n",
    "t1 = {'trigger': 't',\n",
    "      'source': 'off',\n",
    "      'target': 'on'}\n",
    "\n",
    "# Change 2: effect is removed here, too\n",
    "t2 = {'trigger': 't',\n",
    "      'source': 'on',\n",
    "      'target': 'off'}\n",
    "\n",
    "# Change 3: We declare dicts for the states\n",
    "off = {'name': 'off',\n",
    "       'entry': 'turn_yellow_off; start_timer(\"t\", 1000)'\n",
    "       }\n",
    "\n",
    "on = {'name': 'on',\n",
    "      'entry': 'turn_yellow_on; start_timer(\"t\", 1000)'\n",
    "      }\n",
    "\n",
    "# Change 4: We pass the set of states to the state machine\n",
    "machine = Machine(name='signal', transitions=[\n",
    "                  t0, t1, t2], obj=signal, states=[on, off])\n",
    "signal.stm = machine\n",
    "\n",
    "driver = Driver()\n",
    "driver.add_machine(machine)\n",
    "driver.start()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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