Import Data

Notice the lines below containing .dataSource.getSetting.  These lines are referencing the static text values and parameterized text from the Designer Settings tab.

function importData(context) {
    // Step 1: Make use of passed in contextual information to create a rowset object. Here, I am simply assigning tableId, maxRows and columnNames to variables to be used elsewhere in this script.
    var rowset = context.getRowset();
    rowset.setSmartParsingEnabled(true);
    var tableId = rowset.getTableId();
    var dataSource = context.getDataSource();
    var googleKey = dataSource.getSetting("Google API Key").getValue();
    var uberKey = dataSource.getSetting("Uber Server Token").getValue();
    var startAddress = dataSource.getSetting("Start Address").getValue();
    var endAddress = dataSource.getSetting("End Address").getValue();
    var startGeoCode = convertAddressToGeoCode(startAddress, googleKey);
    var endGeoCode = convertAddressToGeoCode(endAddress, googleKey);
    if (tableId === 'prices') {
        // Step 2: Create a https request that will return data - in this case, Yahoo Finance will return JSON.
        var url = 'https://api.uber.com/v1/estimates/pr...tart_latitude=' + startGeoCode[0] + '&start_longitude=' + startGeoCode[1] + '&end_latitude=' + endGeoCode[0] + '&end_longitude=' +
            endGeoCode[1] + '&server_token=' + uberKey;
        var method = 'GET';
        var headers = {
            'Content-Type': 'text/json'
        };
        var body = '';
        // Step 3: Send https request and receive response. Normally you would want to check that the response contains a success message first before looking at the rows.
        var response = ai.https.request(url, method, body, headers);
        // Step 4: Parse the https response body.
        var data = parseData(response.getBody());
        var rows = parseRows(data);
        // Step 5: Process each row to extract the cell values for each column and add them as an array to the rowset in the expected column order.   
        addRows(rowset, rows);
    }
    if (tableId === 'times') {
        // Step 2: Create a https request that will return data - in this case, Yahoo Finance will return JSON.
        var url = 'https://api.uber.com/v1/estimates/ti...tart_latitude=' + startGeoCode[0] + '&start_longitude=' + startGeoCode[1] + '&server_token=' + uberKey;
        var method = 'GET';
        var headers = {
            'Content-Type': 'text/json'
        };
        var body = '';
        // Step 3: Send https request and receive response. Normally you would want to check that the response contains a success message first before looking at the rows.
        var response = ai.https.request(url, method, body, headers);
        // Step 4: Parse the https response body.
        var data = parseData(response.getBody());
        var rows = parseTimeRows(data);
        // Step 5: Process each row to extract the cell values for each column and add them as an array to the rowset in the expected column order.   
        addRows(rowset, rows);
    }
}



function getColumnRemoteIds(columns) {
    var columnIds = [];
    for (var i = 0; i < columns.length; i++) {
        columnIds.push(columns[i].getId());
    }
    return columnIds;
}



function parseData(responseJSON) {
    return JSON.parse(responseJSON);
}



function parseRows(json) {
    return json.prices;
}



function parseTimeRows(json) {
    return json.times;
}



function addRows(rowset, rows) {
    var columnRemoteIds = getColumnRemoteIds(rowset.getColumns());
    for (var i = 0; i < rows.length; i++) {
        var cells = [];
        var row = rows[i];
        for (var x = 0; x < columnRemoteIds.length; x++) {
            var propName = columnRemoteIds[x];
            cells.push(row[propName]);
        }
        rowset.addRow(cells);
    }
}