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+{
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+ "cells": [
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+ {
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+ "cell_type": "markdown",
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+ "metadata": {},
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+ "source": [
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+ "#### Extract Transform Load (ETL) from Code\n",
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+ "\n",
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+ "The example below reads data from an http source (github) and will copy the data to a csv file and to a database. This example illustrates the one-to-many ETL features.\n"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 2,
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "data": {
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+ "text/html": [
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+ "<div>\n",
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+ "<style scoped>\n",
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+ " .dataframe tbody tr th:only-of-type {\n",
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+ " vertical-align: middle;\n",
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+ " }\n",
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+ "\n",
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+ " .dataframe tbody tr th {\n",
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+ " vertical-align: top;\n",
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+ " }\n",
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+ "\n",
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+ " .dataframe thead th {\n",
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+ " text-align: right;\n",
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+ " }\n",
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+ "</style>\n",
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+ "<table border=\"1\" class=\"dataframe\">\n",
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+ " <thead>\n",
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+ " <tr style=\"text-align: right;\">\n",
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+ " <th></th>\n",
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+ " <th>id</th>\n",
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+ " <th>location_id</th>\n",
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+ " <th>address_1</th>\n",
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+ " <th>address_2</th>\n",
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+ " <th>city</th>\n",
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+ " <th>state_province</th>\n",
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+ " <th>postal_code</th>\n",
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+ " <th>country</th>\n",
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+ " </tr>\n",
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+ " </thead>\n",
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+ " <tbody>\n",
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+ " <tr>\n",
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+ " <th>0</th>\n",
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+ " <td>1</td>\n",
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+ " <td>1</td>\n",
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+ " <td>2600 Middlefield Road</td>\n",
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+ " <td>NaN</td>\n",
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+ " <td>Redwood City</td>\n",
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+ " <td>CA</td>\n",
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+ " <td>94063</td>\n",
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+ " <td>US</td>\n",
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+ " </tr>\n",
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+ " <tr>\n",
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+ " <th>1</th>\n",
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+ " <td>2</td>\n",
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+ " <td>2</td>\n",
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+ " <td>24 Second Avenue</td>\n",
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+ " <td>NaN</td>\n",
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+ " <td>San Mateo</td>\n",
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+ " <td>CA</td>\n",
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+ " <td>94401</td>\n",
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+ " <td>US</td>\n",
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+ " </tr>\n",
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+ " <tr>\n",
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+ " <th>2</th>\n",
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+ " <td>3</td>\n",
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+ " <td>3</td>\n",
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+ " <td>24 Second Avenue</td>\n",
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+ " <td>NaN</td>\n",
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+ " <td>San Mateo</td>\n",
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+ " <td>CA</td>\n",
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+ " <td>94403</td>\n",
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+ " <td>US</td>\n",
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+ " </tr>\n",
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+ " <tr>\n",
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+ " <th>3</th>\n",
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+ " <td>4</td>\n",
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+ " <td>4</td>\n",
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+ " <td>24 Second Avenue</td>\n",
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+ " <td>NaN</td>\n",
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+ " <td>San Mateo</td>\n",
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+ " <td>CA</td>\n",
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+ " <td>94401</td>\n",
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+ " <td>US</td>\n",
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+ " </tr>\n",
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+ " <tr>\n",
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+ " <th>4</th>\n",
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+ " <td>5</td>\n",
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+ " <td>5</td>\n",
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+ " <td>24 Second Avenue</td>\n",
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+ " <td>NaN</td>\n",
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+ " <td>San Mateo</td>\n",
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+ " <td>CA</td>\n",
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+ " <td>94401</td>\n",
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+ " <td>US</td>\n",
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+ " </tr>\n",
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+ " </tbody>\n",
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+ "</table>\n",
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+ "</div>"
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+ ],
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+ "text/plain": [
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+ " id location_id address_1 address_2 city \\\n",
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+ "0 1 1 2600 Middlefield Road NaN Redwood City \n",
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+ "1 2 2 24 Second Avenue NaN San Mateo \n",
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+ "2 3 3 24 Second Avenue NaN San Mateo \n",
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+ "3 4 4 24 Second Avenue NaN San Mateo \n",
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+ "4 5 5 24 Second Avenue NaN San Mateo \n",
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+ "\n",
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+ " state_province postal_code country \n",
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+ "0 CA 94063 US \n",
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+ "1 CA 94401 US \n",
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+ "2 CA 94403 US \n",
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+ "3 CA 94401 US \n",
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+ "4 CA 94401 US "
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+ ]
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+ },
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+ "execution_count": 2,
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+ "metadata": {},
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+ "output_type": "execute_result"
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+ }
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+ ],
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+ "source": [
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+ "#\n",
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+ "# Writing to Google Bigquery database\n",
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+ "#\n",
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+ "import transport\n",
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+ "from transport import providers\n",
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+ "import pandas as pd\n",
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+ "import os\n",
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+ "\n",
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+ "#\n",
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+ "#\n",
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+ "source = {\"provider\": \"http\", \"url\": \"https://raw.githubusercontent.com/codeforamerica/ohana-api/master/data/sample-csv/addresses.csv\"}\n",
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+ "target = [{\"provider\": \"files\", \"path\": \"addresses.csv\", \"delimiter\": \",\"}, {\"provider\": \"sqlite\", \"database\": \"sample.db3\", \"table\": \"addresses\"}]\n",
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+ "\n",
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+ "_handler = transport.get.etl (source=source,target=target)\n",
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+ "_data = _handler.read() #-- all etl begins with data being read\n",
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+ "_data.head()"
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+ ]
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+ },
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+ {
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+ "cell_type": "markdown",
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+ "metadata": {},
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+ "source": [
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+ "#### Extract Transform Load (ETL) from CLI\n",
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+ "\n",
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+ "The documentation for this is available at https://healthcareio.the-phi.com/data-transport \"Docs\" -> \"Terminal CLI\"\n",
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+ "\n",
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+ "The entire process is documented including how to generate an ETL configuration file."
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": null,
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+ "metadata": {},
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+ "outputs": [],
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+ "source": []
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+ }
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+ ],
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+ "metadata": {
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+ "kernelspec": {
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+ "display_name": "Python 3",
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+ "language": "python",
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+ "name": "python3"
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+ },
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+ "language_info": {
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+ "codemirror_mode": {
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+ "name": "ipython",
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+ "version": 3
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+ },
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+ "file_extension": ".py",
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+ "mimetype": "text/x-python",
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+ "name": "python",
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+ "nbconvert_exporter": "python",
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+ "pygments_lexer": "ipython3",
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+ "version": "3.9.7"
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+ }
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+ },
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+ "nbformat": 4,
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+ "nbformat_minor": 2
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+}
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