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data-transport/notebooks/mysql.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Writing to MySQL\n",
"\n",
"1. Insure MySQL is actually installed on the system, \n",
"2. There is a database called demo created on the said system\n",
"\n",
"The cell below creates a dataframe that will be stored within postgreSQL"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2.0.4\n"
]
}
],
"source": [
"#\n",
"# Writing to PostgreSQL database\n",
"#\n",
"import transport\n",
"from transport import providers\n",
"import pandas as pd\n",
"_data = pd.DataFrame({\"name\":['James Bond','Steve Rogers','Steve Nyemba'],'age':[55,150,44]})\n",
"myw = transport.get.writer(provider=providers.MYSQL,database='demo',table='friends',auth_file=\"/home/steve/auth-mysql.json\")\n",
"myw.write(_data,if_exists='replace') #-- default is append\n",
"print (transport.__version__)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Reading from MySQL\n",
"\n",
"The cell below reads the data that has been written by the cell above and computes the average age within a MySQL (simple query). \n",
"\n",
"- Basic read of the designated table (friends) created above\n",
"- Execute an aggregate SQL against the table\n",
"\n",
"**NOTE**\n",
"\n",
"By design **read** object are separated from **write** objects in order to avoid accidental writes to the database.\n",
"Read objects are created with **transport.get.reader** whereas write objects are created with **transport.get.writer**"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" name age\n",
"0 James Bond 55\n",
"1 Steve Rogers 150\n",
"2 Steve Nyemba 44\n",
"--------- STATISTICS ------------\n",
" _counts AVG(age)\n",
"0 3 83.0\n"
]
}
],
"source": [
"\n",
"import transport\n",
"from transport import providers\n",
"myr = transport.get.reader(provider=providers.MYSQL,database='demo',table='friends',auth_file='/home/steve/auth-mysql.json')\n",
"_df = myr.read()\n",
"_query = 'SELECT COUNT(*) _counts, AVG(age) from friends'\n",
"_sdf = myr.read(sql=_query)\n",
"print (_df)\n",
"print ('--------- STATISTICS ------------')\n",
"print (_sdf)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"An **auth-file** is a file that contains database parameters used to access the database. \n",
"For code in shared environments, we recommend \n",
"\n",
"1. Having the **auth-file** stored on disk \n",
"2. and the location of the file is set to an environment variable.\n",
"\n",
"To generate a template of the **auth-file** open the **file generator wizard** found at visit https://healthcareio.the-phi.com/data-transport"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'host': 'klingon.io',\n",
" 'port': 3306,\n",
" 'username': 'me',\n",
" 'password': 'foobar',\n",
" 'provider': 'mysql',\n",
" 'database': 'demo',\n",
" 'table': 'friends'}"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"{\n",
" \"host\":\"klingon.io\",\"port\":3306,\"username\":\"me\",\"password\":\"foobar\", \"provider\":\"mysql\",\n",
" \"database\":\"demo\",\"table\":\"friends\"\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": null,
"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",
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