Dynamic SQL using Python

DynamicSQL.ipynb

{
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   "cell_type": "code",
   "execution_count": 1,
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   "source": [
    "import pyodbc\n",
    "import pandas as pd\n",
    "import textwrap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#create connection to MS SQL server\n",
    "conn = pyodbc.connect('Driver={SQL Server};'\n",
    "                      'Server=VAIO\\SQLEXPRESS;'\n",
    "                      'Database=AdventureWorks2014;'\n",
    "                      'Trusted_Connection=yes;')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#define a dynamic component for the SQL query\n",
    "code='98011'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#compose SQL query\n",
    "sql_query_string = textwrap.dedent(\n",
    "    f\"\"\"\n",
    "        SELECT * \n",
    "        FROM Person.Address\n",
    "        WHERE PostalCode='{code}'\n",
    "    \"\"\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#run SQL query and create DataaFrame\n",
    "df = pd.read_sql(sql_query_string, conn)"
   ]
  }
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