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   "source": [
    "#### 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"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>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"
    }
   ],
   "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."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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