Resolução Data Challenge - Bruno Santos Silveira

case1.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "3d878b00",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>STORE_CODE</th>\n",
+       "      <th>PRODUCT_CODE</th>\n",
+       "      <th>DATE</th>\n",
+       "      <th>SALES_VALUE</th>\n",
+       "      <th>SALES_QTY</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1</td>\n",
+       "      <td>18</td>\n",
+       "      <td>2019-01-01</td>\n",
+       "      <td>708.5</td>\n",
+       "      <td>65.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>18</td>\n",
+       "      <td>2019-01-02</td>\n",
+       "      <td>1297.1</td>\n",
+       "      <td>119.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1</td>\n",
+       "      <td>18</td>\n",
+       "      <td>2019-01-03</td>\n",
+       "      <td>1144.5</td>\n",
+       "      <td>105.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1</td>\n",
+       "      <td>18</td>\n",
+       "      <td>2019-01-04</td>\n",
+       "      <td>1090.0</td>\n",
+       "      <td>100.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1</td>\n",
+       "      <td>18</td>\n",
+       "      <td>2019-01-05</td>\n",
+       "      <td>893.8</td>\n",
+       "      <td>82.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  STORE_CODE  PRODUCT_CODE        DATE  SALES_VALUE  SALES_QTY\n",
+       "0          1            18  2019-01-01        708.5       65.0\n",
+       "1          1            18  2019-01-02       1297.1      119.0\n",
+       "2          1            18  2019-01-03       1144.5      105.0\n",
+       "3          1            18  2019-01-04       1090.0      100.0\n",
+       "4          1            18  2019-01-05        893.8       82.0"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import mysql.connector\n",
+    "from mysql.connector import Error\n",
+    "import warnings\n",
+    "warnings.filterwarnings('ignore', category=UserWarning)\n",
+    "\n",
+    "def retrieve_data(product_code=None, store_code=None, date=None):\n",
+    "  \"\"\"\n",
+    "    Busca dados de vendas de forma dinâmica com filtros flexíveis.\n",
+    "\n",
+    "    Parâmetros:\n",
+    "    ----------\n",
+    "    product_code : int, opcional\n",
+    "    store_code : int, opcional\n",
+    "    date : list (str), opcional -> Ex: ['2019-01-01', '2019-01-31']\n",
+    "  \"\"\"\n",
+    "  # Configurações de conexão com o banco de dados\n",
+    "  db_config = {\n",
+    "    'host': '35.199.115.174'\n",
+    "    ,'user': 'looqbox-challenge'\n",
+    "    ,'password': 'looq-challenge'\n",
+    "    ,'database': 'looqbox-challenge'\n",
+    "  }\n",
+    "\n",
+    "  conn = None\n",
+    "  try:\n",
+    "    conn = mysql.connector.connect(**db_config)\n",
+    "\n",
+    "    # Inicialização da Query base trazendo todas as colunas\n",
+    "    query = \"SELECT * FROM data_product_sales WHERE 1=1\"\n",
+    "    params = []\n",
+    "\n",
+    "    # Construção dinâmica das cláusulas WHERE\n",
+    "    if product_code is not None:\n",
+    "      query += \" AND product_code = %s\"\n",
+    "      params.append(product_code)\n",
+    "    \n",
+    "    if store_code is not None:\n",
+    "      query += \" AND store_code = %s\"\n",
+    "      params.append(store_code)\n",
+    "\n",
+    "    if date is not None and isinstance(date, list) and len(date) == 2:\n",
+    "      query += \" AND date BETWEEN %s AND %s\"\n",
+    "      params.append(date[0])\n",
+    "      params.append(date[1])\n",
+    "\n",
+    "    # Execução e conversão direta para DateFrame Pandas\n",
+    "    df = pd.read_sql(query, conn, params=params)\n",
+    "    return df\n",
+    "  \n",
+    "  except Error as e:\n",
+    "    print(f\"Erro ao conectar ou executar query: {e}\")\n",
+    "    return pd.DataFrame()\n",
+    "  finally:\n",
+    "    if conn and conn.is_connected():\n",
+    "      conn.close()\n",
+    "\n",
+    "teste = retrieve_data(date = ['2019-01-01', '2019-01-31'])\n",
+    "display(teste.head())"
+   ]
+  }
+ ],
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