day_3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [],
   "source": [
    "import polars as pl\n",
    "import polars.selectors as cs\n",
    "\n",
    "from pathlib import Path"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[WindowsPath('../data/input_1.txt'),\n",
       " WindowsPath('../data/input_2.txt'),\n",
       " WindowsPath('../data/input_3.txt')]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DATA_PATH = Path('..', 'data')\n",
    "list(DATA_PATH.glob('*'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(140, 1)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><style>\n",
       ".dataframe > thead > tr,\n",
       ".dataframe > tbody > tr {\n",
       "  text-align: right;\n",
       "  white-space: pre-wrap;\n",
       "}\n",
       "</style>\n",
       "<small>shape: (5, 1)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>column_1</th></tr><tr><td>str</td></tr></thead><tbody><tr><td>&quot;..............…</td></tr><tr><td>&quot;......429...83…</td></tr><tr><td>&quot;.........*...&amp;…</td></tr><tr><td>&quot;.........900..…</td></tr><tr><td>&quot;.............7…</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (5, 1)\n",
       "┌───────────────────────────────────┐\n",
       "│ column_1                          │\n",
       "│ ---                               │\n",
       "│ str                               │\n",
       "╞═══════════════════════════════════╡\n",
       "│ ................................… │\n",
       "│ ......429...836..$..............… │\n",
       "│ .........*...&...641..........92… │\n",
       "│ .........900....................… │\n",
       "│ .............707...233..........… │\n",
       "└───────────────────────────────────┘"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = (\n",
    "    pl\n",
    "    .read_csv(\n",
    "        DATA_PATH / 'input_3.txt',\n",
    "        has_header=False,\n",
    "    )\n",
    ")\n",
    "print(df.shape)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_row_col = (\n",
    "    df\n",
    "    .with_row_count('row')\n",
    "    .with_columns(\n",
    "        pl.col('column_1').str.split('')\n",
    "    )\n",
    "    .explode('column_1')\n",
    "    .filter(\n",
    "        pl.col('column_1') != ''\n",
    "    )\n",
    "    .with_columns(\n",
    "        pl.lit(1).alias('ones'),\n",
    "    )\n",
    "    .select([\n",
    "        pl.col('row'),\n",
    "        pl.col('ones').cum_sum().sub(1).over('row').alias('column'),\n",
    "        pl.col('column_1')\n",
    "    ])\n",
    "    .filter(\n",
    "        pl.col('column_1') != '.'\n",
    "    )\n",
    ")\n",
    "df_row_col_digit = (\n",
    "    df_row_col\n",
    "    .filter(\n",
    "        pl.col('column_1').str.contains('\\d')\n",
    "    )\n",
    "    .with_columns(\n",
    "        pl\n",
    "        .col('column')\n",
    "        .sub(pl.col('column').shift(1))\n",
    "        .ne(1)\n",
    "        .cum_sum()\n",
    "        .fill_null(0)\n",
    "        .alias('is_group')\n",
    "    )\n",
    ")\n",
    "df_row_col_symbol = (\n",
    "    df_row_col\n",
    "    .filter(\n",
    "        ~ pl.col('column_1').str.contains('\\d')\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><style>\n",
       ".dataframe > thead > tr,\n",
       ".dataframe > tbody > tr {\n",
       "  text-align: right;\n",
       "  white-space: pre-wrap;\n",
       "}\n",
       "</style>\n",
       "<small>shape: (1, 1)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>column_1</th></tr><tr><td>i32</td></tr></thead><tbody><tr><td>536202</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (1, 1)\n",
       "┌──────────┐\n",
       "│ column_1 │\n",
       "│ ---      │\n",
       "│ i32      │\n",
       "╞══════════╡\n",
       "│ 536202   │\n",
       "└──────────┘"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(\n",
    "    df_row_col_digit\n",
    "    .join(\n",
    "        df_row_col_symbol,\n",
    "        how='left',\n",
    "        left_on=(\n",
    "            pl.col('row'),\n",
    "            pl.col('column'),\n",
    "        ),\n",
    "        right_on=(\n",
    "            pl.col('row') + 1,\n",
    "            pl.col('column'),\n",
    "        ),\n",
    "        suffix='_up'\n",
    "    )\n",
    "    .join(\n",
    "        df_row_col_symbol,\n",
    "        how='left',\n",
    "        left_on=(\n",
    "            pl.col('row'),\n",
    "            pl.col('column'),\n",
    "        ),\n",
    "        right_on=(\n",
    "            pl.col('row') - 1,\n",
    "            pl.col('column'),\n",
    "        ),\n",
    "        suffix='_down'\n",
    "    )\n",
    "    .join(\n",
    "        df_row_col_symbol,\n",
    "        how='left',\n",
    "        left_on=(\n",
    "            pl.col('row'),\n",
    "            pl.col('column'),\n",
    "        ),\n",
    "        right_on=(\n",
    "            pl.col('row'),\n",
    "            pl.col('column') + 1,\n",
    "        ),\n",
    "        suffix='_left'\n",
    "    )\n",
    "    .join(\n",
    "        df_row_col_symbol,\n",
    "        how='left',\n",
    "        left_on=(\n",
    "            pl.col('row'),\n",
    "            pl.col('column'),\n",
    "        ),\n",
    "        right_on=(\n",
    "            pl.col('row'),\n",
    "            pl.col('column') - 1,\n",
    "        ),\n",
    "        suffix='_right'\n",
    "    )\n",
    "    .join(\n",
    "        df_row_col_symbol,\n",
    "        how='left',\n",
    "        left_on=(\n",
    "            pl.col('row'),\n",
    "            pl.col('column'),\n",
    "        ),\n",
    "        right_on=(\n",
    "            pl.col('row') + 1,\n",
    "            pl.col('column') + 1,\n",
    "        ),\n",
    "        suffix='_up_left'\n",
    "    )\n",
    "    .join(\n",
    "        df_row_col_symbol,\n",
    "        how='left',\n",
    "        left_on=(\n",
    "            pl.col('row'),\n",
    "            pl.col('column'),\n",
    "        ),\n",
    "        right_on=(\n",
    "            pl.col('row') + 1,\n",
    "            pl.col('column') - 1,\n",
    "        ),\n",
    "        suffix='_up_right'\n",
    "    )\n",
    "    .join(\n",
    "        df_row_col_symbol,\n",
    "        how='left',\n",
    "        left_on=(\n",
    "            pl.col('row'),\n",
    "            pl.col('column'),\n",
    "        ),\n",
    "        right_on=(\n",
    "            pl.col('row') - 1,\n",
    "            pl.col('column') + 1,\n",
    "        ),\n",
    "        suffix='_down_left'\n",
    "    )\n",
    "    .join(\n",
    "        df_row_col_symbol,\n",
    "        how='left',\n",
    "        left_on=(\n",
    "            pl.col('row'),\n",
    "            pl.col('column'),\n",
    "        ),\n",
    "        right_on=(\n",
    "            pl.col('row') - 1,\n",
    "            pl.col('column') - 1,\n",
    "        ),\n",
    "        suffix='_down_right'\n",
    "    )\n",
    "    .with_columns(\n",
    "        (\n",
    "            pl.col('column_1_up').is_not_null()\n",
    "            | pl.col('column_1_down').is_not_null()\n",
    "            | pl.col('column_1_left').is_not_null()\n",
    "            | pl.col('column_1_right').is_not_null()\n",
    "            | pl.col('column_1_up_left').is_not_null()\n",
    "            | pl.col('column_1_up_right').is_not_null()\n",
    "            | pl.col('column_1_down_left').is_not_null()\n",
    "            | pl.col('column_1_down_right').is_not_null()\n",
    "        )\n",
    "        .alias('is_adjacent')\n",
    "    )\n",
    "    .filter(\n",
    "        pl.col('is_adjacent').any().over('is_group')\n",
    "    )\n",
    "    .group_by('is_group')\n",
    "    .agg(pl.col('column_1'))\n",
    "    .select(\n",
    "        pl.col('column_1').list.join('').cast(pl.Int32)\n",
    "    )\n",
    "    .sum()\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Part 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><style>\n",
       ".dataframe > thead > tr,\n",
       ".dataframe > tbody > tr {\n",
       "  text-align: right;\n",
       "  white-space: pre-wrap;\n",
       "}\n",
       "</style>\n",
       "<small>shape: (3_448, 3)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>row</th><th>column</th><th>number</th></tr><tr><td>u32</td><td>i32</td><td>i32</td></tr></thead><tbody><tr><td>0</td><td>44</td><td>411</td></tr><tr><td>0</td><td>45</td><td>411</td></tr><tr><td>0</td><td>46</td><td>411</td></tr><tr><td>0</td><td>68</td><td>363</td></tr><tr><td>0</td><td>69</td><td>363</td></tr><tr><td>0</td><td>70</td><td>363</td></tr><tr><td>0</td><td>73</td><td>134</td></tr><tr><td>0</td><td>74</td><td>134</td></tr><tr><td>0</td><td>75</td><td>134</td></tr><tr><td>0</td><td>85</td><td>463</td></tr><tr><td>0</td><td>86</td><td>463</td></tr><tr><td>0</td><td>87</td><td>463</td></tr><tr><td>&hellip;</td><td>&hellip;</td><td>&hellip;</td></tr><tr><td>139</td><td>81</td><td>579</td></tr><tr><td>139</td><td>82</td><td>579</td></tr><tr><td>139</td><td>83</td><td>579</td></tr><tr><td>139</td><td>95</td><td>900</td></tr><tr><td>139</td><td>96</td><td>900</td></tr><tr><td>139</td><td>97</td><td>900</td></tr><tr><td>139</td><td>99</td><td>463</td></tr><tr><td>139</td><td>100</td><td>463</td></tr><tr><td>139</td><td>101</td><td>463</td></tr><tr><td>139</td><td>116</td><td>909</td></tr><tr><td>139</td><td>117</td><td>909</td></tr><tr><td>139</td><td>118</td><td>909</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (3_448, 3)\n",
       "┌─────┬────────┬────────┐\n",
       "│ row ┆ column ┆ number │\n",
       "│ --- ┆ ---    ┆ ---    │\n",
       "│ u32 ┆ i32    ┆ i32    │\n",
       "╞═════╪════════╪════════╡\n",
       "│ 0   ┆ 44     ┆ 411    │\n",
       "│ 0   ┆ 45     ┆ 411    │\n",
       "│ 0   ┆ 46     ┆ 411    │\n",
       "│ 0   ┆ 68     ┆ 363    │\n",
       "│ …   ┆ …      ┆ …      │\n",
       "│ 139 ┆ 101    ┆ 463    │\n",
       "│ 139 ┆ 116    ┆ 909    │\n",
       "│ 139 ┆ 117    ┆ 909    │\n",
       "│ 139 ┆ 118    ┆ 909    │\n",
       "└─────┴────────┴────────┘"
      ]
     },
     "execution_count": 206,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_row_col_digit_number = (\n",
    "    df_row_col_digit\n",
    "    .join(\n",
    "        df_row_col_digit\n",
    "        .group_by('is_group')\n",
    "        .agg(pl.col('column_1'))\n",
    "        .select(\n",
    "            pl.col('is_group'),\n",
    "            pl.col('column_1').list.join('').cast(pl.Int32).alias('number')\n",
    "        ),\n",
    "        how='inner',\n",
    "        on=['is_group'],\n",
    "    )\n",
    "    .select('row', 'column', 'number')\n",
    ")\n",
    "df_row_col_digit_number"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><style>\n",
       ".dataframe > thead > tr,\n",
       ".dataframe > tbody > tr {\n",
       "  text-align: right;\n",
       "  white-space: pre-wrap;\n",
       "}\n",
       "</style>\n",
       "<small>shape: (1, 12)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>row</th><th>column</th><th>column_1</th><th>number_up</th><th>number_down</th><th>number_left</th><th>number_right</th><th>number_up_left</th><th>number_up_right</th><th>number_down_left</th><th>number_down_right</th><th>numbers</th></tr><tr><td>u32</td><td>i32</td><td>str</td><td>i32</td><td>i32</td><td>i32</td><td>i32</td><td>i32</td><td>i32</td><td>i32</td><td>i32</td><td>i32</td></tr></thead><tbody><tr><td>22237</td><td>21750</td><td>null</td><td>64067</td><td>69003</td><td>23246</td><td>22831</td><td>77684</td><td>88148</td><td>75875</td><td>77129</td><td>78272573</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (1, 12)\n",
       "┌───────┬────────┬──────────┬───────────┬───┬──────────────┬──────────────┬─────────────┬──────────┐\n",
       "│ row   ┆ column ┆ column_1 ┆ number_up ┆ … ┆ number_up_ri ┆ number_down_ ┆ number_down ┆ numbers  │\n",
       "│ ---   ┆ ---    ┆ ---      ┆ ---       ┆   ┆ ght          ┆ left         ┆ _right      ┆ ---      │\n",
       "│ u32   ┆ i32    ┆ str      ┆ i32       ┆   ┆ ---          ┆ ---          ┆ ---         ┆ i32      │\n",
       "│       ┆        ┆          ┆           ┆   ┆ i32          ┆ i32          ┆ i32         ┆          │\n",
       "╞═══════╪════════╪══════════╪═══════════╪═══╪══════════════╪══════════════╪═════════════╪══════════╡\n",
       "│ 22237 ┆ 21750  ┆ null     ┆ 64067     ┆ … ┆ 88148        ┆ 75875        ┆ 77129       ┆ 78272573 │\n",
       "└───────┴────────┴──────────┴───────────┴───┴──────────────┴──────────────┴─────────────┴──────────┘"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with pl.Config(tbl_rows=1000):\n",
    "    display(\n",
    "        df_row_col_symbol\n",
    "        .filter(\n",
    "            pl.col('column_1') == '*'\n",
    "        )\n",
    "        .join(\n",
    "            df_row_col_digit_number,\n",
    "            how='left',\n",
    "            left_on=(\n",
    "                pl.col('row'),\n",
    "                pl.col('column'),\n",
    "            ),\n",
    "            right_on=(\n",
    "                pl.col('row') + 1,\n",
    "                pl.col('column'),\n",
    "            ),\n",
    "            suffix='_up'\n",
    "        )\n",
    "        .join(\n",
    "            df_row_col_digit_number,\n",
    "            how='left',\n",
    "            left_on=(\n",
    "                pl.col('row'),\n",
    "                pl.col('column'),\n",
    "            ),\n",
    "            right_on=(\n",
    "                pl.col('row') - 1,\n",
    "                pl.col('column'),\n",
    "            ),\n",
    "            suffix='_down'\n",
    "        )\n",
    "        .join(\n",
    "            df_row_col_digit_number,\n",
    "            how='left',\n",
    "            left_on=(\n",
    "                pl.col('row'),\n",
    "                pl.col('column'),\n",
    "            ),\n",
    "            right_on=(\n",
    "                pl.col('row'),\n",
    "                pl.col('column') + 1,\n",
    "            ),\n",
    "            suffix='_left'\n",
    "        )\n",
    "        .join(\n",
    "            df_row_col_digit_number,\n",
    "            how='left',\n",
    "            left_on=(\n",
    "                pl.col('row'),\n",
    "                pl.col('column'),\n",
    "            ),\n",
    "            right_on=(\n",
    "                pl.col('row'),\n",
    "                pl.col('column') - 1,\n",
    "            ),\n",
    "            suffix='_right'\n",
    "        )\n",
    "        .join(\n",
    "            df_row_col_digit_number,\n",
    "            how='left',\n",
    "            left_on=(\n",
    "                pl.col('row'),\n",
    "                pl.col('column'),\n",
    "            ),\n",
    "            right_on=(\n",
    "                pl.col('row') + 1,\n",
    "                pl.col('column') + 1,\n",
    "            ),\n",
    "            suffix='_up_left'\n",
    "        )\n",
    "        .join(\n",
    "            df_row_col_digit_number,\n",
    "            how='left',\n",
    "            left_on=(\n",
    "                pl.col('row'),\n",
    "                pl.col('column'),\n",
    "            ),\n",
    "            right_on=(\n",
    "                pl.col('row') + 1,\n",
    "                pl.col('column') - 1,\n",
    "            ),\n",
    "            suffix='_up_right'\n",
    "        )\n",
    "        .join(\n",
    "            df_row_col_digit_number,\n",
    "            how='left',\n",
    "            left_on=(\n",
    "                pl.col('row'),\n",
    "                pl.col('column'),\n",
    "            ),\n",
    "            right_on=(\n",
    "                pl.col('row') - 1,\n",
    "                pl.col('column') + 1,\n",
    "            ),\n",
    "            suffix='_down_left'\n",
    "        )\n",
    "        .join(\n",
    "            df_row_col_digit_number,\n",
    "            how='left',\n",
    "            left_on=(\n",
    "                pl.col('row'),\n",
    "                pl.col('column'),\n",
    "            ),\n",
    "            right_on=(\n",
    "                pl.col('row') - 1,\n",
    "                pl.col('column') - 1,\n",
    "            ),\n",
    "            suffix='_down_right'\n",
    "        )\n",
    "        .rename({\n",
    "            'number': 'number_up'\n",
    "        })\n",
    "        .with_columns(\n",
    "            pl\n",
    "            .concat_list(\n",
    "                cs.contains('number')\n",
    "            )\n",
    "            .list\n",
    "            .eval(\n",
    "                pl.element().drop_nulls().unique()\n",
    "            )\n",
    "            .alias('numbers')\n",
    "        )\n",
    "        .filter(\n",
    "            pl.col('numbers').list.len() == 2\n",
    "        )\n",
    "        .with_columns(\n",
    "            pl.col('numbers').list[0] * pl.col('numbers').list[1]\n",
    "        )\n",
    "        .sum()\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "pruebas2",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
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