Posted by Wesley Chun (@wescpy), Developer Advocate, Google Cloud
Google Cloud Platform (GCP) provides infrastructure, serverless products, and APIs that help you build, innovate, and scale. G Suite provides a collection of productivity tools, developer APIs, extensibility frameworks and low-code platforms that let you integrate with G Suite applications, data, and users. While each solution is compelling on its own, users can get more power and flexibility by leveraging both together.
In the latest episode of the G Suite Dev Show, I'll show you one example of how you can take advantage of powerful GCP tools right from G Suite applications. BigQuery, for example, can help you surface valuable insight from massive amounts of data. However, regardless of "the tech" you use, you still have to justify and present your findings to management, right? You've already completed the big data analysis part, so why not go that final mile and tap into G Suite for its strengths? In the sample app covered in the video, we show you how to go from big data analysis all the way to an "exec-ready" presentation.
The sample application is meant to give you an idea of what's possible. While the video walks through the code a bit more, let's give all of you a high-level overview here. Google Apps Script is a G Suite serverless development platform that provides straightforward access to G Suite APIs as well as some GCP tools such as BigQuery. The first part of our app, the runQuery() function, issues a query to BigQuery from Apps Script then connects to Google Sheets to store the results into a new Sheet (note we left out CONSTANT variable definitions for brevity):
runQuery()
CONSTANT
function runQuery() { // make BigQuery request var request = {query: BQ_QUERY}; var queryResults = BigQuery.Jobs.query(request, PROJECT_ID); var jobId = queryResults.jobReference.jobId; queryResults = BigQuery.Jobs.getQueryResults(PROJECT_ID, jobId); var rows = queryResults.rows; // put results into a 2D array var data = new Array(rows.length); for (var i = 0; i < rows.length; i++) { var cols = rows[i].f; data[i] = new Array(cols.length); for (var j = 0; j < cols.length; j++) { data[i][j] = cols[j].v; } } // put array data into new Sheet var spreadsheet = SpreadsheetApp.create(QUERY_NAME); var sheet = spreadsheet.getActiveSheet(); var headers = queryResults.schema.fields; sheet.appendRow(headers); // header row sheet.getRange(START_ROW, START_COL, rows.length, headers.length).setValues(data); // return Sheet object for later use return spreadsheet; }
It returns a handle to the new Google Sheet which we can then pass on to the next component: using Google Sheets to generate a Chart from the BigQuery data. Again leaving out the CONSTANTs, we have the 2nd part of our app, the createColumnChart() function:
CONSTANTs
createColumnChart()
function createColumnChart(spreadsheet) { // create & put chart on 1st Sheet var sheet = spreadsheet.getSheets()[0]; var chart = sheet.newChart() .setChartType(Charts.ChartType.COLUMN) .addRange(sheet.getRange(START_CELL + ':' + END_CELL)) .setPosition(START_ROW, START_COL, OFFSET, OFFSET) .build(); sheet.insertChart(chart); // return Chart object for later use return chart; }
The chart is returned by createColumnChart() so we can use that plus the Sheets object to build the desired slide presentation from Apps Script with Google Slides in the 3rd part of our app, the createSlidePresentation() function:
createSlidePresentation()
function createSlidePresentation(spreadsheet, chart) { // create new deck & add title+subtitle var deck = SlidesApp.create(QUERY_NAME); var [title, subtitle] = deck.getSlides()[0].getPageElements(); title.asShape().getText().setText(QUERY_NAME); subtitle.asShape().getText().setText('via GCP and G Suite APIs:\n' + 'Google Apps Script, BigQuery, Sheets, Slides'); // add new slide and insert empty table var tableSlide = deck.appendSlide(SlidesApp.PredefinedLayout.BLANK); var sheetValues = spreadsheet.getSheets()[0].getRange( START_CELL + ':' + END_CELL).getValues(); var table = tableSlide.insertTable(sheetValues.length, sheetValues[0].length); // populate table with data in Sheets for (var i = 0; i < sheetValues.length; i++) { for (var j = 0; j < sheetValues[0].length; j++) { table.getCell(i, j).getText().setText(String(sheetValues[i][j])); } } // add new slide and add Sheets chart to it var chartSlide = deck.appendSlide(SlidesApp.PredefinedLayout.BLANK); chartSlide.insertSheetsChart(chart); // return Presentation object for later use return deck; }
Finally, we need a driver application that calls all three one after another, the createColumnChart() function:
function createBigQueryPresentation() { var spreadsheet = runQuery(); var chart = createColumnChart(spreadsheet); var deck = createSlidePresentation(spreadsheet, chart); }
We left out some detail in the code above but hope this pseudocode helps kickstart your own project. Seeking a guided tutorial to building this app one step-at-a-time? Do our codelab at g.co/codelabs/bigquery-sheets-slides. Alternatively, go see all the code by hitting our GitHub repo at github.com/googlecodelabs/bigquery-sheets-slides. After executing the app successfully, you'll see the fruits of your big data analysis captured in a presentable way in a Google Slides deck:
This isn't the end of the story as this is just one example of how you can leverage both platforms from Google Cloud. In fact, this was one of two sample apps featured in our Cloud NEXT '18 session this summer exploring interoperability between GCP & G Suite which you can watch here:
Stay tuned as more examples are coming. We hope these videos plus the codelab inspire you to build on your own ideas.
Posted by Wesley Chun (@wescpy), Developer Advocate, G Suite
While most chatbots respond to user requests in a synchronous way, there are scenarios when bots don't perform actions based on an explicit user request, such as for alerts or notifications. In today's DevByte video, I'm going to show you how to send messages asynchronously to rooms or direct messages (DMs) in Hangouts Chat, the team collaboration and communication tool in G Suite.
What comes to mind when you think of a bot in a chat room? Perhaps a user wants the last quarter's European sales numbers, or maybe, they want to look up local weather or the next movie showtime. Assuming there's a bot for whatever the request is, a user will either send a direct message (DM) to that bot or @mention the bot from within a chat room. The bot then fields the request (sent to it by the Hangouts Chat service), performs any necessary magic, and responds back to the user in that "space," the generic nomenclature for a room or DM.
Our previous DevByte video for the Hangouts Chat bot framework shows developers what bots and the framework are all about as well as how to build one of these types of bots, in both Python and JavaScript. However, recognize that these bots are responding synchronously to a user request. This doesn't suffice when users want to be notified when a long-running background job has completed, when a late bus or train will be arriving soon, or when one of their servers has just gone down. Recognize that such alerts can come from a bot but also perhaps a monitoring application. In the latest episode of the G Suite Dev Show, learn how to integrate this functionality in either type of application.
From the video, you can see that alerts and notifications are "out-of-band" messages, meaning they can come in at any time. The Hangouts Chat bot framework provides several ways to send asynchronous messages to a room or DM, generically referred to as a "space." The first is the HTTP-based REST API. The other way is using what are known as "incoming webhooks."
The REST API is used by bots to send messages into a space. Since a bot will never be a human user, a Google service account is required. Once you create a service account for your Hangouts Chat bot in the developers console, you can download its credentials needed to communicate with the API. Below is a short Python sample snippet that uses the API to send a message asynchronously to a space.
from apiclient import discovery from httplib2 import Http from oauth2client.service_account import ServiceAccountCredentials SCOPES = 'https://www.googleapis.com/auth/chat.bot' creds = ServiceAccountCredentials.from_json_keyfile_name( 'svc_acct.json', SCOPES) CHAT = discovery.build('chat', 'v1', http=creds.authorize(Http())) room = 'spaces/<ROOM-or-DM>' message = {'text': 'Hello world!'} CHAT.spaces().messages().create(parent=room, body=message).execute()
The alternative to using the API with service accounts is the concept of incoming webhooks. Webhooks are a quick and easy way to send messages into any room or DM without configuring a full bot, i.e., monitoring apps. Webhooks also allow you to integrate your custom workflows, such as when a new customer is added to the corporate CRM (customer relationship management system), as well as others mentioned above. Below is a Python snippet that uses an incoming webhook to communicate into a space asynchronously.
import requests import json URL = 'https://chat.googleapis.com/...&thread_key=T12345' message = {'text': 'Hello world!'} requests.post(URL, data=json.dumps(message))
Since incoming webhooks are merely endpoints you HTTP POST to, you can even use curl to send a message to a Hangouts Chat space from the command-line:
curl
curl \ -X POST \ -H 'Content-Type: application/json' \ 'https://chat.googleapis.com/...&thread_key=T12345' \ -d '{"text": "Hello!"}'
To get started, take a look at the Hangouts Chat developer documentation, especially the specific pages linked to above. We hope this video helps you take your bot development skills to the next level by showing you how to send messages to the Hangouts Chat service asynchronously.
Formatting spreadsheets is accomplished by creating a set of request commands in the form of JSON payloads, and sending them to the API. Here is a sample JavaScript Object made up of an array of requests (only one this time) to bold the first row of the default Sheet automatically created for you (whose ID is 0):
{"requests": [ {"repeatCell": { "range": { "sheetId": 0, "startRowIndex": 0, "endRowIndex": 1 }, "cell": { "userEnteredFormat": { "textFormat": { "bold": true } } }, "fields": "userEnteredFormat.textFormat.bold" }} ]}
SHEETS.spreadsheets().batchUpdate(spreadsheetId=SHEET_ID, body=requests).execute()
For more details on the code in the video, check out the deepdive blog post. As you can probably guess, the key challenge is in constructing the JSON payload to send to API calls—the common operations samples can really help you with this. You can also check out our JavaScript codelab where we guide you through writing a Node.js app that manages customer orders for a toy company, featuring the toy orders data we looked at today but in a relational database. While the resulting equivalent Sheet is featured prominently in today's video, we will revisit it again in an upcoming episode showing you how to generate slides with spreadsheet data using the new Google Slides API, so stay tuned for that!
We hope all these resources help developers enhance their next app using G Suite APIs! Please subscribe to our channel and tell us what topics you would like to see in other episodes of the G Suite Dev Show!
Posted by Wesley Chun (@wescpy), Developer Advocate, Google Apps
At Google I/O 2016, we launched a new Google Sheets API—click here to watch the entire announcement. The updated API includes many new features that weren’t available in previous versions, including access to functionality found in the Sheets desktop and mobile user interfaces. My latest DevByte video shows developers how to get data into and out of a Google Sheet programmatically, walking through a simple script that reads rows out of a relational database and transferring the data to a brand new Google Sheet.
Let’s take a sneak peek of the code covered in the video. Assuming that SHEETS has been established as the API service endpoint, SHEET_ID is the ID of the Sheet to write to, and data is an array with all the database rows, this is the only call developers need to make to write that raw data into the Sheet:
SHEETS
SHEET_ID
data
SHEETS.spreadsheets().values().update(spreadsheetId=SHEET_ID, range='A1', body=data, valueInputOption='RAW').execute()
rows = SHEETS.spreadsheets().values().get(spreadsheetId=SHEET_ID, range='Sheet1').execute().get('values', []) for row in rows: print(row)
If you’re ready to get started, take a look at the Python or other quickstarts in a variety of languages before checking out the DevByte. If you want a deeper dive into the code covered in the video, check out the post at my Python blog. Once you get going with the API, one of the challenges developers face is in constructing the JSON payload to send in API calls—the common operations samples can really help you with this. Finally, if you’re ready to get going with a meatier example, check out our JavaScript codelab where you’ll write a sample Node.js app that manages customer orders for a toy company, the database of which is used in this DevByte, preparing you for the codelab.
We hope all these resources help developers create amazing applications and awesome tools with the new Google Sheets API! Please subscribe to our channel, give us your feedback below, and tell us what topics you would like to see in future episodes!
Posted by Israel Shalom, Product Manager
Every day, hundreds of thousands of developers send millions of requests to Google APIs, from Maps to YouTube. Thousands of developers visit the console for credentials, quota, and more -- and we want to give them a better and more streamlined experience.
Starting today, we’ll gradually roll out the API Console at console.developers.google.com focusing entirely on your Google API experience. There, you’ll find a significantly cleaner, simpler interface: instead of 20+ sections in the navigation bar, you’ll see API Manager, Billing and Permissions only:
console.cloud.google.com will remain unchanged. It’ll point to Cloud console, which includes the entire suite of Google Cloud Platform services, just like before. And while the two are different destinations, your underlying resources remain the same: projects created on Cloud Console will still be accessible on API Console, and vice versa.
The purpose of the new API Console is to let you complete common API-related tasks quickly. For instance, we know that once you enable an API in a new project, the next step is usually to create credentials. That’s why we’ve built the credentials wizard: a quick and convenient way for you to figure out what kind of credentials you need, and add them right after enabling an API:
Over time, we will continue to tailor the API Console experience for the many developers out there who use Google’s APIs. So if you’re one of these users, we encourage you to try out API Console and use the feedback button to let us know what you think!
Originally posted to the Google Apps Developer blog
Posted by Edward Jones, Software Engineer, Google Apps Script and Wesley Chun, Developer Advocate, Google Apps
Have you ever wanted a server API that modifies cells in a Google Sheet, to execute a Google Apps Script app from outside of Google Apps, or a way to use Apps Script as an API platform? Today, we’re excited to announce you can do all that and more with the Google Apps Script Execution API.
The Execution API allows developers to execute scripts from any client (browser, server, mobile, or any device). You provide the authorization, and the Execution API will run your script. If you’re new to Apps Script, it’s simply JavaScript code hosted in the cloud that can access authorized Google Apps data using the same technology that powers add-ons. The Execution API extends the ability to execute Apps Script code and unlocks the power of Docs, Sheets, Forms, and other supported services for developers.
One of our launch partners, Pear Deck, used the new API to create an interactive presentation tool that connects students to teachers by converting slide decks into interactive experiences. Their app calls the Execution API to automatically generate a Google Doc customized for each student, so everyone gets a personalized set of notes from the presentation. Without the use of Apps Script, their app would be limited to using PDFs and other static file types. Check out the video below to see how it works.
Bruce McPherson, a Google Developer Expert (GDE) for Google Apps, says: “The Execution API is a great tool for enabling what I call ‘incremental transition’ from Microsoft Office (and VBA) to Apps (and Apps Script). A mature Office workflow may involve a number of processes currently orchestrated by VBA, with data in various formats and locations. It can be a challenge to move an entire workload in one step, especially an automated process with many moving parts. This new capability enables the migration of data and process in manageable chunks.” You can find some of Bruce’s sample migration code using the Execution API here.
The Google Apps Script Execution API is live and ready for you to use today. To get started, check out the developer documentation and quickstarts. We invite you to show us what you build with the Execution API!
[[GPPShare sharedInstance] shareDialog]
[[GPPShare sharedInstance] nativeShareDialog]
<script type="text/javascript"> // The API developer key obtained from the Google APIs Console. var developerKey = 'ABC123 ... '; // Use the API Loader script to load google.picker. function loadPicker() { gapi.load('picker', {'callback': createPicker}); } // Create and render a Picker object for searching images. function createPicker() { var picker = new google.picker.PickerBuilder(). addView(google.picker.ViewId.IMAGE_SEARCH). setDeveloperKey(developerKey). setCallback(pickerCallback). build(); picker.setVisible(true); } </script> <script type="text/javascript" src="https://apis.google.com/js/api.js?onload=loadPicker"> </script>
Google Analytics users can use the Core Reporting API to save time by building dashboards and automating complex reporting tasks. This API exposes over 250 data points (dimensions and metrics), and new data is added every few months. For many developers, it can be difficult to keep their applications up to date with all the latest data.
To make things easier, today we are launching the new Google Analytics Metadata API to simplify data discovery. The Metadata API contains all the queryable dimensions and metrics included in the Core Reporting API. We’ve also added attributes for each dimension and metric, such as the web or app name, full text description, grouping, metric calculations, deprecation status, and whether the data is queryable in segments. You can check out at a live Metadata API response here.
You now have programmatic access to generate the same list of dimensions and metrics we use to generate our public documentation.
When you create tools to query the Core Reporting API, you can use the Metadata API to automatically update your user interfaces. For example, Analytics Canvas, a popular third-party Google Analytics data extraction tool, uses the Metadata API to keep its query building interface up to date.
According to James Standen, founder of Analytics Canvas, "In the past, keeping Analytics Canvas up to date with the Google Analytics API dimensions and metrics required a lot of manual updating to our application. The new Metadata API automates this process, saving us time, and giving our users direct access to all the great new data the instant it's available. Users love it!"
To increase data transparency, we’ve also published a new data deprecation policy for dimensions and metrics. New data we release will be announced on our changelogs and automatically added to the Metadata API. Data we decide to remove will be marked as deprecated in the Metadata API, allowing developers to gracefully remove these values from their tools.
Our goal was to make this API super easy to use. To get started, take a look at our resources:
Questions? Comments? Simply want to share in the excitement? Join the analytics developer community in our Reporting API Developer forum.
Map<String, String> params = new HashMap<String, String>(); Channel request = new Channel() .setId("unique_subscription_ID") .setType("web_hook") .setAddress(String.format("https://my-host.com/notification")) .setParams(params); service.events().watch("my_calendar@my-host.com", request).execute();
changes = service.events().list("my_calendar@my-host.com") .setUpdatedMin(lastSynchonizationTime).execute();
Over the past year we’ve added many new features to Google Analytics. Today we are releasing all of this data in the Core Reporting API.
We're most excited about the ability to query for custom dimensions and metrics using the API.
Developers can use custom dimensions to send unique IDs into Google Analytics, and then use the core reporting API to retrieve these IDs along with other Google Analytics data.
For example, your content management system can pass a content ID as a custom dimension using the Google Analytics tracking code. Developers can then use the API to get a list of the most popular content by ID and display the list of most popular content on their website.
We've added more mobile dimensions and metrics, including those found in the Mobile App Analytics reports:
Some examples of questions this new data can answer are:
If you are sending Google Analytics multiple currencies, you now have the ability to access the local currency of the transactions with this new data:
We added new time-based dimensions to simplify working with reporting data:
Sample queries:
Finally, we've added two new traffic source dimensions, including one to return the full URL of the referral.
Sample query: the top 10 referrers based on visits (using full referrer).
For a complete list of the new data, take a look at the Core Reporting API changelog. For all the data definitions, check the Core Reporting API Dimensions and Metrics explorer. As always, you can check out this new data directly within our Query Explorer tool.
