advent16.ipynb

   1 {
   2  "cells": [
   3   {
   4    "cell_type": "code",
   5    "execution_count": 1,
   6    "metadata": {
   7     "collapsed": false
   8    },
   9    "outputs": [
  10     {
  11      "data": {
  12       "text/plain": [
  13        "['Sue 1: goldfish: 9, cars: 0, samoyeds: 9',\n",
  14        " 'Sue 2: perfumes: 5, trees: 8, goldfish: 8',\n",
  15        " 'Sue 3: pomeranians: 2, akitas: 1, trees: 5',\n",
  16        " 'Sue 4: goldfish: 10, akitas: 2, perfumes: 9',\n",
  17        " 'Sue 5: cars: 5, perfumes: 6, akitas: 9']"
  18       ]
  19      },
  20      "execution_count": 1,
  21      "metadata": {},
  22      "output_type": "execute_result"
  23     }
  24    ],
  25    "source": [
  26     "pi16 = [l.strip() for l in open('advent16.txt').readlines()]\n",
  27     "pi16[:5]"
  28    ]
  29   },
  30   {
  31    "cell_type": "code",
  32    "execution_count": 3,
  33    "metadata": {
  34     "collapsed": false
  35    },
  36    "outputs": [
  37     {
  38      "data": {
  39       "text/plain": [
  40        "{'cats': 3, 'goldfish': 6, 'pomeranians': 8}"
  41       ]
  42      },
  43      "execution_count": 3,
  44      "metadata": {},
  45      "output_type": "execute_result"
  46     }
  47    ],
  48    "source": [
  49     "aunts = {}\n",
  50     "for l in pi16:\n",
  51     "    ll = l.split(': ', 1)\n",
  52     "    n = int(ll[0].split(' ')[1])\n",
  53     "    items = ll[1].split(', ')\n",
  54     "    aunts[n] = {i.split(': ')[0].strip(): int(i.split(': ')[1]) for i in items}\n",
  55     "aunts[406]"
  56    ]
  57   },
  58   {
  59    "cell_type": "code",
  60    "execution_count": 4,
  61    "metadata": {
  62     "collapsed": true
  63    },
  64    "outputs": [],
  65    "source": [
  66     "target = {'children': 3,\n",
  67     "'cats': 7,\n",
  68     "'samoyeds': 2,\n",
  69     "'pomeranians': 3,\n",
  70     "'akitas': 0,\n",
  71     "'vizslas': 0,\n",
  72     "'goldfish': 5,\n",
  73     "'trees': 3,\n",
  74     "'cars': 2,\n",
  75     "'perfumes': 1}"
  76    ]
  77   },
  78   {
  79    "cell_type": "code",
  80    "execution_count": 5,
  81    "metadata": {
  82     "collapsed": true
  83    },
  84    "outputs": [],
  85    "source": [
  86     "def possible(aunt):\n",
  87     "    return all(aunts[aunt][item] == target[item] for item in aunts[aunt])"
  88    ]
  89   },
  90   {
  91    "cell_type": "code",
  92    "execution_count": 6,
  93    "metadata": {
  94     "collapsed": false
  95    },
  96    "outputs": [
  97     {
  98      "data": {
  99       "text/plain": [
 100        "[40]"
 101       ]
 102      },
 103      "execution_count": 6,
 104      "metadata": {},
 105      "output_type": "execute_result"
 106     }
 107    ],
 108    "source": [
 109     "list(aunt for aunt in aunts if possible(aunt))"
 110    ]
 111   },
 112   {
 113    "cell_type": "code",
 114    "execution_count": 7,
 115    "metadata": {
 116     "collapsed": true
 117    },
 118    "outputs": [],
 119    "source": [
 120     "def possible2(aunt):\n",
 121     "    possible = True\n",
 122     "    for item in aunts[aunt]:\n",
 123     "        if item == 'cats' or item == 'trees':\n",
 124     "            if aunts[aunt][item] <= target[item]:\n",
 125     "                possible = False\n",
 126     "        elif item == 'pomeranians' or item == 'goldfish':\n",
 127     "            if aunts[aunt][item] >= target[item]:\n",
 128     "                possible = False\n",
 129     "        else:\n",
 130     "            if aunts[aunt][item] != target[item]:\n",
 131     "                possible = False\n",
 132     "    return possible"
 133    ]
 134   },
 135   {
 136    "cell_type": "code",
 137    "execution_count": 8,
 138    "metadata": {
 139     "collapsed": false
 140    },
 141    "outputs": [
 142     {
 143      "data": {
 144       "text/plain": [
 145        "False"
 146       ]
 147      },
 148      "execution_count": 8,
 149      "metadata": {},
 150      "output_type": "execute_result"
 151     }
 152    ],
 153    "source": [
 154     "possible2(40)"
 155    ]
 156   },
 157   {
 158    "cell_type": "code",
 159    "execution_count": 9,
 160    "metadata": {
 161     "collapsed": false
 162    },
 163    "outputs": [
 164     {
 165      "data": {
 166       "text/plain": [
 167        "[241]"
 168       ]
 169      },
 170      "execution_count": 9,
 171      "metadata": {},
 172      "output_type": "execute_result"
 173     }
 174    ],
 175    "source": [
 176     "list(aunt for aunt in aunts if possible2(aunt))"
 177    ]
 178   },
 179   {
 180    "cell_type": "code",
 181    "execution_count": null,
 182    "metadata": {
 183     "collapsed": true
 184    },
 185    "outputs": [],
 186    "source": []
 187   }
 188  ],
 189  "metadata": {
 190   "kernelspec": {
 191    "display_name": "Python 3",
 192    "language": "python",
 193    "name": "python3"
 194   },
 195   "language_info": {
 196    "codemirror_mode": {
 197     "name": "ipython",
 198     "version": 3
 199    },
 200    "file_extension": ".py",
 201    "mimetype": "text/x-python",
 202    "name": "python",
 203    "nbconvert_exporter": "python",
 204    "pygments_lexer": "ipython3",
 205    "version": "3.4.3"
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 209  "nbformat_minor": 0
 210 }