{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = set([1,2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['__and__',\n",
       " '__class__',\n",
       " '__class_getitem__',\n",
       " '__contains__',\n",
       " '__delattr__',\n",
       " '__dir__',\n",
       " '__doc__',\n",
       " '__eq__',\n",
       " '__format__',\n",
       " '__ge__',\n",
       " '__getattribute__',\n",
       " '__gt__',\n",
       " '__hash__',\n",
       " '__iand__',\n",
       " '__init__',\n",
       " '__init_subclass__',\n",
       " '__ior__',\n",
       " '__isub__',\n",
       " '__iter__',\n",
       " '__ixor__',\n",
       " '__le__',\n",
       " '__len__',\n",
       " '__lt__',\n",
       " '__ne__',\n",
       " '__new__',\n",
       " '__or__',\n",
       " '__rand__',\n",
       " '__reduce__',\n",
       " '__reduce_ex__',\n",
       " '__repr__',\n",
       " '__ror__',\n",
       " '__rsub__',\n",
       " '__rxor__',\n",
       " '__setattr__',\n",
       " '__sizeof__',\n",
       " '__str__',\n",
       " '__sub__',\n",
       " '__subclasshook__',\n",
       " '__xor__',\n",
       " 'add',\n",
       " 'clear',\n",
       " 'copy',\n",
       " 'difference',\n",
       " 'difference_update',\n",
       " 'discard',\n",
       " 'intersection',\n",
       " 'intersection_update',\n",
       " 'isdisjoint',\n",
       " 'issubset',\n",
       " 'issuperset',\n",
       " 'pop',\n",
       " 'remove',\n",
       " 'symmetric_difference',\n",
       " 'symmetric_difference_update',\n",
       " 'union',\n",
       " 'update']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.pop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{2}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://leetcode.com/problems/keys-and-rooms\n",
    "\n",
    "\n",
    "\n",
    "Runtime: 68 ms, faster than 50.42% of Python3 online submissions for Keys and Rooms.\n",
    "Memory Usage: 14.9 MB, less than 62.37% of Python3 online submissions for Keys and Rooms.\n",
    "\n",
    "\n",
    "\n",
    "```python\n",
    "class Solution:\n",
    "    def canVisitAllRooms(self, rooms: List[List[int]]) -> bool:\n",
    "        allRooms = len(rooms)\n",
    "        keySet = set()\n",
    "        tempKeys = set([0])\n",
    "        while len(tempKeys):\n",
    "            key = tempKeys.pop()\n",
    "            moreKeys = set(rooms[key])\n",
    "            keySet.update({key})\n",
    "            tempKeys.update(moreKeys-keySet)\n",
    "        if len(keySet) == allRooms:\n",
    "            return True\n",
    "        else:\n",
    "            return False\n",
    "```\n",
    "\n",
    "\n",
    "Spent 15 minutes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "    "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}