documentation ...

pull/19/head
Steve Nyemba 4 months ago
parent d0472ccee5
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{
"cells": [
{
"cell_type": "markdown",
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"#### Extract Transform Load (ETL) from Code\n",
"\n",
"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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"execution_count": 2,
"metadata": {},
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"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>location_id</th>\n",
" <th>address_1</th>\n",
" <th>address_2</th>\n",
" <th>city</th>\n",
" <th>state_province</th>\n",
" <th>postal_code</th>\n",
" <th>country</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2600 Middlefield Road</td>\n",
" <td>NaN</td>\n",
" <td>Redwood City</td>\n",
" <td>CA</td>\n",
" <td>94063</td>\n",
" <td>US</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>24 Second Avenue</td>\n",
" <td>NaN</td>\n",
" <td>San Mateo</td>\n",
" <td>CA</td>\n",
" <td>94401</td>\n",
" <td>US</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>3</td>\n",
" <td>24 Second Avenue</td>\n",
" <td>NaN</td>\n",
" <td>San Mateo</td>\n",
" <td>CA</td>\n",
" <td>94403</td>\n",
" <td>US</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>4</td>\n",
" <td>24 Second Avenue</td>\n",
" <td>NaN</td>\n",
" <td>San Mateo</td>\n",
" <td>CA</td>\n",
" <td>94401</td>\n",
" <td>US</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>5</td>\n",
" <td>24 Second Avenue</td>\n",
" <td>NaN</td>\n",
" <td>San Mateo</td>\n",
" <td>CA</td>\n",
" <td>94401</td>\n",
" <td>US</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" id location_id address_1 address_2 city \\\n",
"0 1 1 2600 Middlefield Road NaN Redwood City \n",
"1 2 2 24 Second Avenue NaN San Mateo \n",
"2 3 3 24 Second Avenue NaN San Mateo \n",
"3 4 4 24 Second Avenue NaN San Mateo \n",
"4 5 5 24 Second Avenue NaN San Mateo \n",
"\n",
" state_province postal_code country \n",
"0 CA 94063 US \n",
"1 CA 94401 US \n",
"2 CA 94403 US \n",
"3 CA 94401 US \n",
"4 CA 94401 US "
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
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"source": [
"#\n",
"# Writing to Google Bigquery database\n",
"#\n",
"import transport\n",
"from transport import providers\n",
"import pandas as pd\n",
"import os\n",
"\n",
"#\n",
"#\n",
"source = {\"provider\": \"http\", \"url\": \"https://raw.githubusercontent.com/codeforamerica/ohana-api/master/data/sample-csv/addresses.csv\"}\n",
"target = [{\"provider\": \"files\", \"path\": \"addresses.csv\", \"delimiter\": \",\"}, {\"provider\": \"sqlite\", \"database\": \"sample.db3\", \"table\": \"addresses\"}]\n",
"\n",
"_handler = transport.get.etl (source=source,target=target)\n",
"_data = _handler.read() #-- all etl begins with data being read\n",
"_data.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Extract Transform Load (ETL) from CLI\n",
"\n",
"The documentation for this is available at https://healthcareio.the-phi.com/data-transport \"Docs\" -> \"Terminal CLI\"\n",
"\n",
"The entire process is documented including how to generate an ETL configuration file."
]
},
{
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"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
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