{
"cells": [
{
"cell_type": "code",
"execution_count": 31,
"id": "cc9bf87d-5b60-4dac-a52c-d2ab8de6de2f",
"metadata": {},
"outputs": [],
"source": [
"import mysql.connector\n",
"from mysql.connector import Error\n",
"\n",
"import pandas as pd\n"
]
},
{
"cell_type": "markdown",
"id": "342b00b9-ad17-4d2f-aba5-afece48e1aa1",
"metadata": {},
"source": [
"Short demo of the work of Python MySQL connectivity in the context of a Jupyter Labs Notebook."
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "5fcb85d1-36a2-41c1-8388-8049cfb8117c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Requirement already satisfied: mysql-connector in /home/dekhtyar/.local/lib/python3.8/site-packages (2.2.9)\n"
]
}
],
"source": [
"!pip install mysql-connector"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "a6b5bacd-c5b4-4ff7-9129-2fa7a82c3689",
"metadata": {},
"outputs": [],
"source": [
"# setup\n",
"\n",
"pwdfileName = 'pss' ## I am \"hiding\" my password in the pss file\n",
"pwdfile = open(pwdfileName,'r') ## opening the password file for reading\n",
"p = pwdfile.read()[:-1] ## extracting the password\n",
"\n",
"\n",
"hostName = 'mysql.labthreesixfive.com'\n",
"portName = '3306'\n",
"userName = 'dekhtyar'\n",
"passString = p\n",
"\n",
"dbName = 'DEMOS'\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "07adf0b8-2936-47d7-add8-cf78a6511de4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Connected to mysql.labthreesixfive.com\n"
]
}
],
"source": [
"### set up MySQL connection\n",
"\n",
"try:\n",
" \n",
" conn = mysql.connector.connect(host = hostName, port = portName, database = dbName,\n",
" user = userName, password = passString)\n",
" if conn.is_connected():\n",
" print('Connected to ',hostName)\n",
" p=''\n",
"except Error as e:\n",
" print('Connection Error:', e)\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "f03fc79c-844b-494d-8908-e2f0c524a1b5",
"metadata": {},
"outputs": [],
"source": [
"# let's see what's in the DEMOS database\n",
"\n",
"c1 = conn.cursor()\n",
"\n",
"c1.execute('show tables')\n",
"tbl = pd.DataFrame(c1)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "fd829318-c960-45ef-944b-bdcc3f2dcfb7",
"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>0</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Classes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Menus</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Restaurants</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>ServesDishes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>ctmp</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>tmp</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>tst</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" 0\n",
"0 Classes\n",
"1 Menus\n",
"2 Restaurants\n",
"3 ServesDishes\n",
"4 ctmp\n",
"5 tmp\n",
"6 tst"
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tbl"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "2fcd77b1-df23-4ac9-bf90-ab740158fe3d",
"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>Table</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Classes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Menus</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Restaurants</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>ServesDishes</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>ctmp</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>tmp</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>tst</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Table\n",
"0 Classes\n",
"1 Menus\n",
"2 Restaurants\n",
"3 ServesDishes\n",
"4 ctmp\n",
"5 tmp\n",
"6 tst"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tbl.columns=['Table']\n",
"\n",
"tbl"
]
},
{
"cell_type": "markdown",
"id": "e28be021-177b-4485-a7e0-8b6f46314dbf",
"metadata": {},
"source": [
"Let's print the contents of each table"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "290b22bb-f4e8-478f-80b7-26e75334cc20",
"metadata": {},
"outputs": [
{
"ename": "AttributeError",
"evalue": "'NoneType' object has no attribute 'unread_result'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-29-d9918f74f835>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mc2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfetchall\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m~/.local/lib/python3.8/site-packages/mysql/connector/cursor_cext.py\u001b[0m in \u001b[0;36mfetchall\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 608\u001b[0m \"\"\"\n\u001b[1;32m 609\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_check_executed\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 610\u001b[0;31m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_cnx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munread_result\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 611\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 612\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mAttributeError\u001b[0m: 'NoneType' object has no attribute 'unread_result'"
]
}
],
"source": [
"c2.fetchall()"
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "5d53bb41-5b93-4078-8136-276892c4548b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[{'class': 'CSC 365', 'section': 7, 'startDate': None, 'startTime': None}, {'class': 'CSC 365', 'section': 8, 'startDate': datetime.date(2024, 4, 2), 'startTime': datetime.timedelta(seconds=43800)}]\n",
"------ Classes----------\n",
"\n",
"{'class': 'CSC 365', 'section': 7, 'startDate': None, 'startTime': None}\n",
"{'class': 'CSC 365', 'section': 8, 'startDate': datetime.date(2024, 4, 2), 'startTime': datetime.timedelta(seconds=43800)}\n",
"----------------------\n",
"\n",
"\n",
"[{'Id': 1, 'Name': 'Chicken Burrito', 'DishType': 'Main Dish'}, {'Id': 2, 'Name': 'Crunchwrap Supreme', 'DishType': 'Main Dish'}, {'Id': 3, 'Name': 'Gyros Sandwich', 'DishType': 'Main Dish'}, {'Id': 4, 'Name': 'Chicken Kebab', 'DishType': 'Main Dish'}, {'Id': 5, 'Name': 'Lentil Soup', 'DishType': 'Soup'}, {'Id': 6, 'Name': 'Hummus', 'DishType': 'Appetizer'}, {'Id': 7, 'Name': 'Diet Coke', 'DishType': 'Drink'}]\n",
"------ Menus----------\n",
"\n",
"{'Id': 1, 'Name': 'Chicken Burrito', 'DishType': 'Main Dish'}\n",
"{'Id': 2, 'Name': 'Crunchwrap Supreme', 'DishType': 'Main Dish'}\n",
"{'Id': 3, 'Name': 'Gyros Sandwich', 'DishType': 'Main Dish'}\n",
"{'Id': 4, 'Name': 'Chicken Kebab', 'DishType': 'Main Dish'}\n",
"{'Id': 5, 'Name': 'Lentil Soup', 'DishType': 'Soup'}\n",
"{'Id': 6, 'Name': 'Hummus', 'DishType': 'Appetizer'}\n",
"{'Id': 7, 'Name': 'Diet Coke', 'DishType': 'Drink'}\n",
"----------------------\n",
"\n",
"\n",
"[{'Id': 1, 'Name': 'Petra', 'Address': 'Higuera St.', 'Cuisine': 'Mediterrenean', 'HealthScore': 92, 'Yelp': 4.5}, {'Id': 2, 'Name': 'Taco Bell', 'Address': 'Broad St.', 'Cuisine': 'Fast Mexican', 'HealthScore': 81, 'Yelp': 4.0}, {'Id': 3, 'Name': 'Taco Bell', 'Address': 'San Luis Obispo', 'Cuisine': 'Fast Mexican', 'HealthScore': 91, 'Yelp': 4.2}, {'Id': 4, 'Name': 'Hellahot', 'Address': 'San Luis Obispo', 'Cuisine': 'Tennessee Chicken', 'HealthScore': 91, 'Yelp': 4.2}, {'Id': 10, 'Name': 'Taco Bell', 'Address': 'Santa Rosa', 'Cuisine': 'Fast Mexican', 'HealthScore': 81, 'Yelp': 4.0}, {'Id': 11, 'Name': 'Chipotle', 'Address': 'San Luis Obispo', 'Cuisine': 'Mexican', 'HealthScore': 91, 'Yelp': 4.2}]\n",
"------ Restaurants----------\n",
"\n",
"{'Id': 1, 'Name': 'Petra', 'Address': 'Higuera St.', 'Cuisine': 'Mediterrenean', 'HealthScore': 92, 'Yelp': 4.5}\n",
"{'Id': 2, 'Name': 'Taco Bell', 'Address': 'Broad St.', 'Cuisine': 'Fast Mexican', 'HealthScore': 81, 'Yelp': 4.0}\n",
"{'Id': 3, 'Name': 'Taco Bell', 'Address': 'San Luis Obispo', 'Cuisine': 'Fast Mexican', 'HealthScore': 91, 'Yelp': 4.2}\n",
"{'Id': 4, 'Name': 'Hellahot', 'Address': 'San Luis Obispo', 'Cuisine': 'Tennessee Chicken', 'HealthScore': 91, 'Yelp': 4.2}\n",
"{'Id': 10, 'Name': 'Taco Bell', 'Address': 'Santa Rosa', 'Cuisine': 'Fast Mexican', 'HealthScore': 81, 'Yelp': 4.0}\n",
"{'Id': 11, 'Name': 'Chipotle', 'Address': 'San Luis Obispo', 'Cuisine': 'Mexican', 'HealthScore': 91, 'Yelp': 4.2}\n",
"----------------------\n",
"\n",
"\n",
"[{'RestaurantId': 2, 'DishId': 1, 'Price': Decimal('4.99')}, {'RestaurantId': 2, 'DishId': 2, 'Price': Decimal('5.49')}, {'RestaurantId': 3, 'DishId': 1, 'Price': Decimal('4.99')}, {'RestaurantId': 3, 'DishId': 3, 'Price': Decimal('6.99')}]\n",
"------ ServesDishes----------\n",
"\n",
"{'RestaurantId': 2, 'DishId': 1, 'Price': Decimal('4.99')}\n",
"{'RestaurantId': 2, 'DishId': 2, 'Price': Decimal('5.49')}\n",
"{'RestaurantId': 3, 'DishId': 1, 'Price': Decimal('4.99')}\n",
"{'RestaurantId': 3, 'DishId': 3, 'Price': Decimal('6.99')}\n",
"----------------------\n",
"\n",
"\n",
"[]\n",
"------ ctmp----------\n",
"\n",
"----------------------\n",
"\n",
"\n",
"[{'id': 1, 'val': 'Bob', 'f': 5}, {'id': 2, 'val': 'Alice', 'f': 5}, {'id': 1, 'val': 'Chuck', 'f': 5}, {'id': 1, 'val': 'This is a long string', 'f': 6}, {'id': 10, 'val': 'WOW', 'f': 5}]\n",
"------ tmp----------\n",
"\n",
"{'id': 1, 'val': 'Bob', 'f': 5}\n",
"{'id': 2, 'val': 'Alice', 'f': 5}\n",
"{'id': 1, 'val': 'Chuck', 'f': 5}\n",
"{'id': 1, 'val': 'This is a long string', 'f': 6}\n",
"{'id': 10, 'val': 'WOW', 'f': 5}\n",
"----------------------\n",
"\n",
"\n",
"[]\n",
"------ tst----------\n",
"\n",
"----------------------\n",
"\n",
"\n"
]
}
],
"source": [
"for t in tbl['Table']:\n",
" c2 = conn.cursor(dictionary = True)\n",
" c2.execute('SELECT * FROM '+ t)\n",
" records = c2.fetchall()\n",
" print(records)\n",
" print('------ '+t+'----------\\n')\n",
" for r in records:\n",
" print(r)\n",
" print('----------------------\\n\\n')\n",
" c2.close()\n",
" \n",
" # print(records)\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "579da83b-549a-4e7e-bcf1-dfee4234719d",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[]"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"records"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "3d7a6030-7d41-451a-9a3f-e5cab2949a64",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[{'Id': 3, 'Name': 'Gyros Sandwich', 'DishType': 'Main Dish'},\n",
" {'Id': 4, 'Name': 'Chicken Kebab', 'DishType': 'Main Dish'},\n",
" {'Id': 5, 'Name': 'Lentil Soup', 'DishType': 'Soup'},\n",
" {'Id': 6, 'Name': 'Hummus', 'DishType': 'Appetizer'},\n",
" {'Id': 7, 'Name': 'Diet Coke', 'DishType': 'Drink'}]"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"c3.fetchall()"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "4941dd79-b90b-4c09-bd69-03d42259cc96",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'Id': 1, 'Name': 'Chicken Burrito', 'DishType': 'Main Dish'}\n",
"{'Id': 2, 'Name': 'Crunchwrap Supreme', 'DishType': 'Main Dish'}\n",
"Chicken Burrito\n"
]
}
],
"source": [
"## Let's use fetch_one()\n",
"\n",
"c3 = conn.cursor(dictionary=True)\n",
"\n",
"query = 'SELECT * FROM Menus'\n",
"\n",
"c3.execute(query)\n",
"\n",
"\n",
"\n",
"rec1 = c3.fetchone()\n",
"rec2 = c3.fetchone()\n",
"#rec3 = c3.fetchone()\n",
"#rec4 = c3.fetchone()\n",
"\n",
"print(rec1)\n",
"print(rec2)\n",
"\n",
"print(rec1[\"Name\"])\n"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "d651d9c5-69d4-46d2-a525-1dde78c37dad",
"metadata": {},
"outputs": [],
"source": [
"## Let's use fetch_one()\n",
"\n",
"c11 = conn.cursor(dictionary=True)\n",
"\n",
"query = 'SELECT * FROM Menus'\n",
"\n",
"c11.execute(query)\n",
"\n",
"data = pd.DataFrame(c11)\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "2a370f8a-7c72-49cd-888f-5f2c6b71fc42",
"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>Id</th>\n",
" <th>Name</th>\n",
" <th>DishType</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>Chicken Burrito</td>\n",
" <td>Main Dish</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>Crunchwrap Supreme</td>\n",
" <td>Main Dish</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>Gyros Sandwich</td>\n",
" <td>Main Dish</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>Chicken Kebab</td>\n",
" <td>Main Dish</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>Lentil Soup</td>\n",
" <td>Soup</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>6</td>\n",
" <td>Hummus</td>\n",
" <td>Appetizer</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>7</td>\n",
" <td>Diet Coke</td>\n",
" <td>Drink</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Id Name DishType\n",
"0 1 Chicken Burrito Main Dish\n",
"1 2 Crunchwrap Supreme Main Dish\n",
"2 3 Gyros Sandwich Main Dish\n",
"3 4 Chicken Kebab Main Dish\n",
"4 5 Lentil Soup Soup\n",
"5 6 Hummus Appetizer\n",
"6 7 Diet Coke Drink"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "f2303d72-54b9-4cd8-9b86-ae74a6de82ec",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"list"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"type(records)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "905e004b-e4dc-4152-a161-1bbb60f800c6",
"metadata": {},
"outputs": [],
"source": [
"\n",
"#### FIX THIS IN CLASS INSERT INTO RESTAURANTS OR MENUS\n",
"\n",
"c4 = conn.cursor()\n",
"# (3, 'Chemistry', 'and Biochemistry', 'COSAM', 180, '206')\n",
"\n",
"insert = \"INSERT INTO Departments VALUES(4, 'Physics', 'Physics', 'COSAM', 180, '204')\"\n",
"\n",
"c4.execute(insert)\n",
"\n",
"c4.execute(\"SELECT * FROM Departments\")\n",
"\n",
"r = pd.DataFrame(c4)\n",
"\n",
"r\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9589905b-8004-4cdd-8a00-36da2f9e2eee",
"metadata": {},
"outputs": [],
"source": [
"c5 = conn.cursor()\n",
"\n",
"stm = \"DELETE FROM st where val = '''ab'''\"\n",
"\n",
"stm2 = 'SELECT * FROM st'\n",
"\n",
"c5.execute(stm)\n",
"#c5.execute(stm2)\n",
"#d = pd.DataFrame(c5)\n",
"\n",
"\n",
"#d\n",
"\n"
]
},
{
"cell_type": "markdown",
"id": "b6244a23-3024-4bf3-b6ac-17e2b268eb70",
"metadata": {},
"source": [
"run the cell below at the very end of your session to close the connection"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9cf1423f-5262-4efb-be39-1b80566c969a",
"metadata": {},
"outputs": [],
"source": [
"c5.execute(\"commit\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "fc590047-1e58-4372-9da3-e99e1bd883d8",
"metadata": {},
"outputs": [],
"source": [
"if conn.is_connected():\n",
" c2.close()\n",
" c1.close()\n",
" c3.close()\n",
" conn.close()\n",
" print('Done')\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "102b78c7-042c-443f-9ba3-e3ac95c943a5",
"metadata": {},
"outputs": [],
"source": [
"conn.close()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "370992eb-3f0d-4433-87d4-636acc26667f",
"metadata": {},
"outputs": [],
"source": [
"\n",
"try:\n",
" \n",
" conn = mysql.connector.connect(host = hostName, port = portName, database = dbName,\n",
" user = userName, password = passString)\n",
" if conn.is_connected():\n",
" print('Connected to ',hostName)\n",
" p=''\n",
" \n",
" c5 = conn.cursor()\n",
"\n",
" stm = \"DELETE FROM st where val = '''ab'''\"\n",
"\n",
" stm2 = 'SELECT * FROM st'\n",
" c5.execute(stm)\n",
" c5.execute(stm2)\n",
" print(\"Query\")\n",
" d = pd.DataFrame(c5)\n",
" print(d)\n",
" \n",
"except Error as e:\n",
" print('Connection Error:', e)\n",
" \n",
"finally:\n",
" c5.close()\n",
" conn.close()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0f4094fe-6bfa-47f6-a131-f29f36851ed6",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.8"
}
},
"nbformat": 4,
"nbformat_minor": 5
}