DSA-Python-Cap06-04-Select no SQLite.ipynb

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   "source": [
    "# <font color='blue'>Data Science Academy - Python Fundamentos - Capítulo 6</font>\n",
    "\n",
    "## Download: http://github.com/dsacademybr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Versão da Linguagem Python Usada Neste Jupyter Notebook: 3.8.8\n"
     ]
    }
   ],
   "source": [
    "# Versão da Linguagem Python\n",
    "from platform import python_version\n",
    "print('Versão da Linguagem Python Usada Neste Jupyter Notebook:', python_version())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Leitura de dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sqlite3\n",
    "import random\n",
    "import time\n",
    "import datetime\n",
    " \n",
    "# Criando uma conexão\n",
    "conn = sqlite3.connect('dsa.db')   \n",
    "\n",
    "# Criando um cursor\n",
    "c = conn.cursor()\n",
    " \n",
    "# Função para criar uma tabela\n",
    "def create_table():\n",
    "    c.execute('CREATE TABLE IF NOT EXISTS produtos(id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL, date TEXT, '\\\n",
    "              'prod_name TEXT, valor REAL)')\n",
    "\n",
    "# Função para inserir uma linha\n",
    "def data_insert():\n",
    "    c.execute(\"INSERT INTO produtos VALUES(002, '02-05-2020', 'teclado', 130 )\")\n",
    "    conn.commit()\n",
    "    c.close()\n",
    "    conn.close()\n",
    "    \n",
    "# Usando variáveis para inserir dados    \n",
    "def data_insert_var():\n",
    "    new_date = datetime.datetime.now()\n",
    "    new_prod_name = 'monitor'\n",
    "    new_valor = random.randrange(50,100)\n",
    "    c.execute(\"INSERT INTO produtos (date, prod_name, valor) VALUES (?, ?, ?, ?)\", \n",
    "              (new_date, new_prod_name, new_valor))\n",
    "    conn.commit()\n",
    "    \n",
    "# Leitura de dados\n",
    "def leitura_todos_dados():\n",
    "    c.execute(\"SELECT * FROM PRODUTOS\")\n",
    "    for linha in c.fetchall():\n",
    "        print(linha)\n",
    "        \n",
    "# Leitura de registros específicos\n",
    "def leitura_registros():\n",
    "    c.execute(\"SELECT * FROM PRODUTOS WHERE valor > 60.0\")\n",
    "    for linha in c.fetchall():\n",
    "        print(linha)      \n",
    "        \n",
    "# Leitura de colunas específicos\n",
    "def leitura_colunas():\n",
    "    c.execute(\"SELECT * FROM PRODUTOS\")\n",
    "    for linha in c.fetchall():\n",
    "        print(linha[3])         \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(10, '2020-05-02 14:32:11', 'Teclado', 90.0)\n",
      "(11, '2021-07-06 20:51:14.475529', 'Monitor', 92.0)\n",
      "(12, '2021-07-06 20:51:15.479652', 'Monitor', 56.0)\n",
      "(13, '2021-07-06 20:51:16.486842', 'Monitor', 62.0)\n",
      "(14, '2021-07-06 20:51:17.491347', 'Monitor', 80.0)\n",
      "(15, '2021-07-06 20:51:18.498449', 'Monitor', 73.0)\n",
      "(16, '2021-07-06 20:51:19.503444', 'Monitor', 88.0)\n",
      "(17, '2021-07-06 20:51:20.508122', 'Monitor', 92.0)\n",
      "(18, '2021-07-06 20:51:21.511482', 'Monitor', 55.0)\n",
      "(19, '2021-07-06 20:51:22.515474', 'Monitor', 82.0)\n",
      "(20, '2021-07-06 20:51:23.520584', 'Monitor', 61.0)\n"
     ]
    }
   ],
   "source": [
    "# Select nos dados\n",
    "leitura_todos_dados()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(10, '2020-05-02 14:32:11', 'Teclado', 90.0)\n",
      "(11, '2021-07-06 20:51:14.475529', 'Monitor', 92.0)\n",
      "(13, '2021-07-06 20:51:16.486842', 'Monitor', 62.0)\n",
      "(14, '2021-07-06 20:51:17.491347', 'Monitor', 80.0)\n",
      "(15, '2021-07-06 20:51:18.498449', 'Monitor', 73.0)\n",
      "(16, '2021-07-06 20:51:19.503444', 'Monitor', 88.0)\n",
      "(17, '2021-07-06 20:51:20.508122', 'Monitor', 92.0)\n",
      "(19, '2021-07-06 20:51:22.515474', 'Monitor', 82.0)\n",
      "(20, '2021-07-06 20:51:23.520584', 'Monitor', 61.0)\n"
     ]
    }
   ],
   "source": [
    "# Leitura de registros específicos\n",
    "leitura_registros()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "90.0\n",
      "92.0\n",
      "56.0\n",
      "62.0\n",
      "80.0\n",
      "73.0\n",
      "88.0\n",
      "92.0\n",
      "55.0\n",
      "82.0\n",
      "61.0\n"
     ]
    }
   ],
   "source": [
    "# Leitura de colunas específicas\n",
    "leitura_colunas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Encerrando a conexão\n",
    "c.close()\n",
    "conn.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fim"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Obrigado\n",
    "\n",
    "### Visite o Blog da Data Science Academy - <a href=\"http://blog.dsacademy.com.br\">Blog DSA</a>"
   ]
  }
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