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data-transport/notebooks/mongodb.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Writing to mongodb\n",
"\n",
"Insure mongodb is actually installed on the system, The cell below creates a dataframe that will be stored within mongodb"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2.0.4\n"
]
}
],
"source": [
"#\n",
"# Writing to mongodb 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",
"mgw = transport.get.writer(provider=providers.MONGODB,db='demo',collection='friends')\n",
"mgw.write(_data)\n",
"print (transport.__version__)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Reading from mongodb\n",
"\n",
"The cell below reads the data that has been written by the cell above and computes the average age within a mongodb pipeline. The code in the background executes an aggregation using **db.runCommand**\n",
"\n",
"- Basic read of the designated collection **find=\\<collection>**\n",
"- Executing an aggregate pipeline against a collection **aggreate=\\<collection>**\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": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" name age\n",
"0 James Bond 55\n",
"1 Steve Rogers 150\n",
"--------- STATISTICS ------------\n",
" _id _counts _mean\n",
"0 0 2 102.5\n"
]
}
],
"source": [
"\n",
"import transport\n",
"from transport import providers\n",
"mgr = transport.get.reader(provider=providers.MONGODB,db='foo',collection='friends')\n",
"_df = mgr.read()\n",
"PIPELINE = [{\"$group\":{\"_id\":0,\"_counts\":{\"$sum\":1}, \"_mean\":{\"$avg\":\"$age\"}}}]\n",
"_sdf = mgr.read(aggregate='friends',pipeline=PIPELINE)\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": 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",
"pygments_lexer": "ipython3",
"version": "3.9.7"
}
},
"nbformat": 4,
"nbformat_minor": 2
}