{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": "# Usage of the EventClass - demonstration on concrete class **LogEvent**\n"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "EventClass is merely an abstract class and serves as an interface for all EventClasses."
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "The LogEvent class extends an abstract base class and includes the following fields:\n",
    "- extra_data\n",
    "- metadata\n",
    "- original\n",
    "\n",
    "LogEvent validates extra_data and checks whether all entries are in the `DELIVERED` state before setting itself to `DELIVERED`."
   ]
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-07-04T08:26:18.587612Z",
     "start_time": "2025-07-04T08:26:18.568644Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import pickle\n",
    "\n",
    "from tinycss2 import serialize\n",
    "\n",
    "from logprep.ng.event.log_event import LogEvent\n",
    "from logprep.ng.event.event_state import EventStateType\n",
    "from logprep.ng.abc.event import Event\n",
    "\n",
    "\n",
    "class DummyEvent(Event):\n",
    "    __slots__ = Event.__slots__"
   ],
   "outputs": [],
   "execution_count": 2
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "**Set LogEvent to delivered with SUCCESS**"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-07-04T08:26:20.589331Z",
     "start_time": "2025-07-04T08:26:20.585603Z"
    }
   },
   "cell_type": "code",
   "source": [
    "child1 = DummyEvent({\"c1\": 1})\n",
    "child2 = DummyEvent({\"c2\": 2})\n",
    "child1.state.current_state = EventStateType.DELIVERED\n",
    "child2.state.current_state = EventStateType.DELIVERED\n",
    "\n",
    "log_event = LogEvent(\n",
    "    data={\"parent\": \"yes\"},\n",
    "    original=b\"...\",\n",
    "    extra_data=[child1, child2],\n",
    ")\n",
    "log_event.state.current_state = EventStateType.STORED_IN_OUTPUT\n",
    "log_event.state.next_state(success=True)\n",
    "\n",
    "print(log_event.state.current_state)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "delivered\n"
     ]
    }
   ],
   "execution_count": 3
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "**Set LogEvent to delivered FAILING**\n"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-07-04T08:26:22.613362Z",
     "start_time": "2025-07-04T08:26:22.528342Z"
    }
   },
   "cell_type": "code",
   "source": [
    "child1 = DummyEvent({\"c1\": 1})\n",
    "child2 = DummyEvent({\"c2\": 2})\n",
    "child1.state.current_state = EventStateType.DELIVERED\n",
    "child2.state.current_state = EventStateType.PROCESSING\n",
    "\n",
    "log_event = LogEvent(\n",
    "    data={\"parent\": \"yes\"},\n",
    "    original=b\"...\",\n",
    "    extra_data=[child1, child2],\n",
    ")\n",
    "log_event.state.current_state = EventStateType.STORED_IN_OUTPUT\n",
    "log_event.state.next_state(success=True)\n",
    "\n",
    "print(log_event.state.current_state)"
   ],
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "Cannot assign DELIVERED state: not all extra_data events are DELIVERED.",
     "output_type": "error",
     "traceback": [
      "\u001B[31m---------------------------------------------------------------------------\u001B[39m",
      "\u001B[31mValueError\u001B[39m                                Traceback (most recent call last)",
      "\u001B[36mCell\u001B[39m\u001B[36m \u001B[39m\u001B[32mIn[4]\u001B[39m\u001B[32m, line 12\u001B[39m\n\u001B[32m      6\u001B[39m log_event = LogEvent(\n\u001B[32m      7\u001B[39m     data={\u001B[33m\"\u001B[39m\u001B[33mparent\u001B[39m\u001B[33m\"\u001B[39m: \u001B[33m\"\u001B[39m\u001B[33myes\u001B[39m\u001B[33m\"\u001B[39m},\n\u001B[32m      8\u001B[39m     original=\u001B[33mb\u001B[39m\u001B[33m\"\u001B[39m\u001B[33m...\u001B[39m\u001B[33m\"\u001B[39m,\n\u001B[32m      9\u001B[39m     extra_data=[child1, child2],\n\u001B[32m     10\u001B[39m )\n\u001B[32m     11\u001B[39m log_event.state.current_state = EventStateType.STORED_IN_OUTPUT\n\u001B[32m---> \u001B[39m\u001B[32m12\u001B[39m \u001B[43mlog_event\u001B[49m\u001B[43m.\u001B[49m\u001B[43mstate\u001B[49m\u001B[43m.\u001B[49m\u001B[43mnext_state\u001B[49m\u001B[43m(\u001B[49m\u001B[43msuccess\u001B[49m\u001B[43m=\u001B[49m\u001B[38;5;28;43;01mTrue\u001B[39;49;00m\u001B[43m)\u001B[49m\n\u001B[32m     14\u001B[39m \u001B[38;5;28mprint\u001B[39m(log_event.state.current_state)\n",
      "\u001B[36mFile \u001B[39m\u001B[32m~/dev/bwi/Logprep/logprep/ng/event/log_event.py:69\u001B[39m, in \u001B[36mLogEvent._next_state_validation_helper\u001B[39m\u001B[34m(self, success)\u001B[39m\n\u001B[32m     65\u001B[39m \u001B[38;5;28;01mdef\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[34m_next_state_validation_helper\u001B[39m(\n\u001B[32m     66\u001B[39m     \u001B[38;5;28mself\u001B[39m, *, success: \u001B[38;5;28mbool\u001B[39m | \u001B[38;5;28;01mNone\u001B[39;00m = \u001B[38;5;28;01mNone\u001B[39;00m\n\u001B[32m     67\u001B[39m ) -> EventStateType | \u001B[38;5;28;01mNone\u001B[39;00m:\n\u001B[32m     68\u001B[39m     new_state: EventStateType = \u001B[38;5;28mself\u001B[39m._origin_state_next_state_fn(success=success)\n\u001B[32m---> \u001B[39m\u001B[32m69\u001B[39m     \u001B[38;5;28;43mself\u001B[39;49m\u001B[43m.\u001B[49m\u001B[43m_validate_state\u001B[49m\u001B[43m(\u001B[49m\u001B[43mnew_state\u001B[49m\u001B[43m)\u001B[49m\n\u001B[32m     70\u001B[39m     \u001B[38;5;28;01mreturn\u001B[39;00m new_state\n",
      "\u001B[36mFile \u001B[39m\u001B[32m~/dev/bwi/Logprep/logprep/ng/event/log_event.py:75\u001B[39m, in \u001B[36mLogEvent._validate_state\u001B[39m\u001B[34m(self, state_type)\u001B[39m\n\u001B[32m     73\u001B[39m \u001B[38;5;28;01mif\u001B[39;00m state_type == EventStateType.DELIVERED:\n\u001B[32m     74\u001B[39m     \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28mall\u001B[39m(e.state.current_state == EventStateType.DELIVERED \u001B[38;5;28;01mfor\u001B[39;00m e \u001B[38;5;129;01min\u001B[39;00m \u001B[38;5;28mself\u001B[39m.extra_data):\n\u001B[32m---> \u001B[39m\u001B[32m75\u001B[39m         \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mValueError\u001B[39;00m(\n\u001B[32m     76\u001B[39m             \u001B[33m\"\u001B[39m\u001B[33mCannot assign DELIVERED state: not all extra_data events are DELIVERED.\u001B[39m\u001B[33m\"\u001B[39m\n\u001B[32m     77\u001B[39m         )\n",
      "\u001B[31mValueError\u001B[39m: Cannot assign DELIVERED state: not all extra_data events are DELIVERED."
     ]
    }
   ],
   "execution_count": 4
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "**Pickable / Hashable**"
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": [
    "The class and all its subclasses must be **picklable** and **hashable**.\n",
    "\n",
    "- **Pickable**: means that an object can be **serialized** and **deserialized** using Python’s pickle module, allowing it to be saved to disk or transferred between processes.\n",
    "\n",
    "- **Hashable**: means that an object can be used as a key in dictionaries, stored in sets or other hash-based containers, and used in equality comparisons with other objects.\n",
    "To be hashable, the object must have a stable __hash__() implementation and a consistent __eq__() behavior."
   ]
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "**EQUALITY**"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-07-04T08:27:37.254605Z",
     "start_time": "2025-07-04T08:27:37.251798Z"
    }
   },
   "cell_type": "code",
   "source": [
    "log_event = LogEvent(\n",
    "    data={\"log\": \"yes\"},\n",
    "    original=b\"...\",\n",
    ")\n",
    "\n",
    "other_equal_log_event = LogEvent(data={\"log\": \"yes\"}, original=b\"...\")\n",
    "\n",
    "print(log_event==other_equal_log_event)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n"
     ]
    }
   ],
   "execution_count": 5
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-07-04T08:28:02.280946Z",
     "start_time": "2025-07-04T08:28:02.278234Z"
    }
   },
   "cell_type": "code",
   "source": [
    "other_not_equal_log_event = LogEvent(data={\"log\": \"no\"}, original=b\"...\")\n",
    "print(log_event==other_not_equal_log_event)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "False\n"
     ]
    }
   ],
   "execution_count": 6
  },
  {
   "metadata": {},
   "cell_type": "markdown",
   "source": "**PICKLABILITY**"
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-07-04T08:28:21.369226Z",
     "start_time": "2025-07-04T08:28:21.366961Z"
    }
   },
   "cell_type": "code",
   "source": [
    "import pickle\n",
    "serialized = pickle.dumps(log_event)\n",
    "\n",
    "print(serialized)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "b'\\x80\\x04\\x95\\xb1\\x01\\x00\\x00\\x00\\x00\\x00\\x00\\x8c\\x1alogprep.ng.event.log_event\\x94\\x8c\\x08LogEvent\\x94\\x93\\x94)\\x81\\x94N}\\x94(\\x8c\\x08original\\x94C\\x03...\\x94\\x8c\\nextra_data\\x94]\\x94\\x8c\\x08metadata\\x94N\\x8c\\x06_state\\x94\\x8c\\x1clogprep.ng.event.event_state\\x94\\x8c\\nEventState\\x94\\x93\\x94)\\x81\\x94}\\x94(\\x8c\\rcurrent_state\\x94h\\x0b\\x8c\\x0eEventStateType\\x94\\x93\\x94\\x8c\\treceiving\\x94\\x85\\x94R\\x94\\x8c\\nnext_state\\x94\\x8c\\x08builtins\\x94\\x8c\\x07getattr\\x94\\x93\\x94h\\x03\\x8c\\x1d_next_state_validation_helper\\x94\\x86\\x94R\\x94ub\\x8c\\x1b_origin_state_next_state_fn\\x94\\x8c\\tfunctools\\x94\\x8c\\x07partial\\x94\\x93\\x94h\\x0b\\x8c\\x15EventState.next_state\\x94\\x93\\x94\\x85\\x94R\\x94(h\"h\\x0e\\x85\\x94}\\x94Nt\\x94b\\x8c\\x04data\\x94}\\x94\\x8c\\x03log\\x94\\x8c\\x03yes\\x94s\\x8c\\x06errors\\x94]\\x94\\x8c\\x08warnings\\x94]\\x94u\\x86\\x94b.'\n"
     ]
    }
   ],
   "execution_count": 7
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-07-04T08:28:48.841672Z",
     "start_time": "2025-07-04T08:28:48.838316Z"
    }
   },
   "cell_type": "code",
   "source": [
    "copy_log_event = pickle.loads(serialized)\n",
    "print(\"Comparison between original and deserialized object.\\n Result (is equal):\", log_event == copy_log_event, end=\"\\n\\n\")\n",
    "\n",
    "print(copy_log_event)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Comparison between original and deserialized object.\n",
      " Result (is equal): True\n",
      "\n",
      "LogEvent(data={'log': 'yes'}, state=receiving)\n"
     ]
    }
   ],
   "execution_count": 8
  }
 ],
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