Exploring Google (Cloud) APIs with Python & JavaScript

Exploring Google (Cloud) APIs
with Python & JavaScript
Wesley Chun
Developer Advocate, Google
Adjunct CS Faculty, Foothill College
G Suite Dev Show
goo.gl/JpBQ40
About the speaker
Developer Advocate, Google Cloud
● Mission: enable current and future
developers everywhere to be
successful using Google Cloud and
other Google developer tools & APIs
● Videos: host of the G Suite Dev Show
on YouTube
● Blogs: developers.googleblog.com &
gsuite-developers.googleblog.com
● Twitters: @wescpy, @GoogleDevs,
@GSuiteDevs
Previous experience / background
● Software engineer & architect for 20+ years
● One of the original Yahoo!Mail engineers
● Author of bestselling "Core Python" books
(corepython.com)
● Technical trainer, teacher, instructor since
1983 (Computer Science, C, Linux, Python)
● Fellow of the Python Software Foundation
● AB (Math/CS) & CMP (Music/Piano), UC
Berkeley and MSCS, UC Santa Barbara
● Adjunct Computer Science Faculty, Foothill
College (Silicon Valley)

Agenda
1
Introduction
2
Google Cloud
(GCP + G Suite)
3
Google APIs
4
Inspiration
5
Wrap-up
01
Introduction to
APIs
Why are you here?

&
Google APIs client
libraries for many
languages; demos in
developers.google.com/api-
client-library
cloud.google.com/apis/docs
/cloud-client-libraries
02
Google Cloud

Google Compute Engine, Google Cloud Storage
AWS EC2 & S3; Rackspace; Joyent
SaaS
Software as a Service
PaaS
Platform as a Service
IaaS
Infrastructure as a Service
Google Apps Script
Salesforce1/force.com
G Suite (Google Apps)
Yahoo!Mail, Hotmail, Salesforce, Netsuite, Oﬃce 365
Google App Engine, Cloud Functions
Heroku, Cloud Foundry, Engine Yard, AWS Lambda
Google BigQuery, Cloud SQL,
Cloud Datastore, NL, Vision, Pub/Sub
AWS Kinesis, RDS; Windows Azure SQL, Docker
Google Cloud Platform vs. G Suite
G Suite
APIs
GCP
APIs

03
Google APIs &
developer tools
(focusing on Cloud)
GCP data & storage services
Build, innovate, and scale with Google Cloud Platform

Storing Data: Cloud SQL
SQL servers in the cloud
High-performance, fully-managed
600MB to 416GB RAM; up to 64 vCPUs
Up to 10 TB storage; 40,000 IOPS
Types:
MySQL
Postgres
SQLServer (2019)
cloud.google.com/sql
Storing Data: Cloud Datastore
Cloud Datastore: a fully-
managed, highly-scalable
NoSQL database for your web
and mobile applications
cloud.google.com/datastore

Storing Data: Firebase
Firebase data is stored
as JSON & synchronized in
real-time to every
connected client; other
tools + FB == v2 mobile
development platform
firebase.google.com
Storing Data: Cloud Firestore
The best of both worlds: the
next generation of Cloud
Datastore (w/product rebrand)
plus features from the
Firebase realtime database
(For choosing between Firebase & Cloud Firestore: see
firebase.google.com/docs/firestore/rtdb-vs-firestore)
cloud.google.com/firestore

Cloud Firestore data model
collections subcollections
Cloud Firestore straightforward querying
github.com/GoogleCloudPlatform/python-docs-samples/blob/master/firestore/cloud-client/snippets.py

BigQuery: querying Shakespeare words
from google.cloud import bigquery
TITLE = "The most common words in all of Shakespeare's works"
QUERY = '''
SELECT LOWER(word) AS word, sum(word_count) AS count
FROM `bigquery-public-data.samples.shakespeare`
GROUP BY word ORDER BY count DESC LIMIT 10
'''
rsp = bigquery.Client().query(QUERY).result()
print('n*** Results for %r:n' % TITLE)
print('t'.join(col.name.upper() for col in rsp.schema)) # HEADERS
print('n'.join('t'.join(str(x) for x in row.values()) for row in rsp)) # DATA
Top 10 most common Shakespeare words
$ python bq_shake.py
*** Results for "The most common words in all of Shakespeare's works":
WORD COUNT
the 29801
and 27529
i 21029
to 20957
of 18514
a 15370
you 14010
my 12936
in 11722
that 11519

● BigQuery public data sets: cloud.google.com/bigquery/public-data
● Other public data sets: cloud.google.com/public-datasets (Google
Cloud) and research.google/tools/datasets (Google Research)
● COVID-19
○ Read the blog post announcement
○ How to use our data sets
○ JHU Coronavirus COVID-19 Global Cases data set
○ List of all COVID-19 data sets
● BigQuery sandbox (1TB/mo): cloud.google.com/bigquery/docs/sandbox
● Cloud Healthcare API: cloud.google.com/healthcare (read blog post)
BigQuery public data sets
GCP machine learning
Bringing AI/ML to developers of all skillsets

ML "building block" APIs
● Gain insights from data using GCP's
pre-trained machine learning models
● Leverage the same technology as Google
Translate, Photos, and Assistant
● Requires ZERO prior knowledge of ML
● If you can call an API, you can use AI/ML!
● cloud.google.com/products/ai/building-blocks
Vision Video
Intelligence
Speech
(S2T & T2S)
Natural
Language
Translation
from google.cloud import vision
image_uri = 'gs://cloud-samples-data/vision/using_curl/shanghai.jpeg'
client = vision.ImageAnnotatorClient()
image = vision.types.Image()
image.source.image_uri = image_uri
response = client.label_detection(image=image)
print('Labels (and confidence score):')
print('=' * 30)
for label in response.label_annotations:
print(f'{label.description} ({label.score*100.:.2f}%)')
Vision: label annotation/object detection

$ python3 label-detect.py
Labels (and confidence score):
==============================
People (95.05%)
Street (89.12%)
Mode of transport (89.09%)
Transport (85.13%)
Vehicle (84.69%)
Snapshot (84.11%)
Urban area (80.29%)
Infrastructure (73.14%)
Road (72.74%)
Pedestrian (68.90%)
Vision: label annotation/object detection
g.co/codelabs/vision-python
Cloud Vision
exercise
g.co/codelabs/vision-
python
(others at gcplab.me)

● What is it, and how does it work?
○ Google Cloud ML APIs use pre-trained models
○ Perhaps those models less suitable for your data
○ Further customize/train our models for your data
○ Without sophisticated ML background
○ Translate, Vision, Natural Language, Video Intelligence, Tables
○ cloud.google.com/automl
● Steps
a. Prep your training data
b. Create dataset
c. Import items into dataset
d. Create/train model
e. Evaluate/validate model
f. Make predictions
Cloud AutoML
Full Spectrum of AI & ML Offerings
App developer Data scientist,
developer
Data scientist, Researcher
(w/infrastructure access &
DevOps/SysAdmin skills)
ML EngineAuto ML
Build custom models,
use OSS SDK on fully-
managed infrastructure
ML APIs
App developer,
data scientist
Use/customize pre-built
models
Use pre-built/pre-
trained models
Build custom models, use/
extend OSS SDK, self-manage
training infrastructure

Google Cloud compute & serverless
4 opinionated logic-hosting containers in the cloud
>
Google Compute Engine configurable
VMs of all shapes & sizes, from
"micro" to 416 vCPUs, 11.75 TB RAM,
64 TB HDD/SSD plus Google Cloud
Storage for blobs/cloud data lake
(Debian, CentOS, CoreOS, SUSE, Red Hat Enterprise Linux,
Ubuntu, FreeBSD; Windows Server 2008 R2, 2012 R2, 2016)
cloud.google.com/compute
cloud.google.com/storage
Yeah, we got VMs & big disk… but why*?

Serverless: what & why
● What is serverless?
○ Misnomer
○ "No worries"
○ Developers focus on writing code & solving business problems*
● Why serverless?
○ Fastest growing segment of cloud... per analyst research*:
■ $1.9B (2016) and $4.25B (2018) ⇒ $7.7B (2021) and $14.93B (2023)
○ What if you go viral? Autoscaling: your new best friend
○ What if you don't? Code not running? You're not paying.
* in USD; source:Forbes (May 2018), MarketsandMarkets™ & CB Insights (Aug 2018)
Why does App Engine exist?
● Focus on app not DevOps
○ Web app
○ Mobile backend
○ Cloud service
● Enhance productivity
● Deploy globally
● Fully-managed
● Auto-scaling
● Pay-per-use
● Familiar languages

Hello World (Python "MVP")
app.yaml
runtime: python37
main.py
from flask import Flask
app = Flask(__name__)
@app.route('/')
def hello():
return 'Hello World!'
requirements.txt
Flask==1.0.2
Deploy:
$ gcloud app deploy
Access globally:
PROJECT_ID.appspot.com
Quickstart tutorial and open source repo at
cloud.google.com/appengine/docs/standard/python3/quickstart
Why does Cloud Functions exist?
● Don't have entire app?
○ No framework "overhead" (LAMP, MEAN...)
○ Deploy microservices
● Event-driven
○ Triggered via HTTP or background events
■ Pub/Sub, Cloud Storage, Firebase, etc.
○ Auto-scaling & highly-available; pay per use
● Flexible development environment
○ Cmd-line or developer console (in-browser)
● Cloud Functions for Firebase
○ Mobile app use-cases
● Available runtimes
○ JS/Node.js 6, 8, 10
○ Python 3.7
○ Go 1.11, 1.12
○ Java 8

main.py
def hello_world(request):
return 'Hello World!'
Deploy:
$ gcloud functions deploy hello --runtime python37 --trigger-http
Access globally (curl):
curl -X POST https://GCP_REGION-PROJECT_ID.cloudfunctions.net/hello
-H "Content-Type:application/json"
Access globally (browser):
GCP_REGION-PROJECT_ID.cloudfunctions.net/hello
Hello World (Python "MVP")
Quickstart tutorial and open source repo at
cloud.google.com/functions/docs/quickstart-python
Cloud Run
Fully-managed serverless
ContainerizedApps-aaS
No cluster to manage
Pay for what you use
Cloud Run on GKE
Serverless experience
Access custom nodes, GPUs, VPC
Simplicity of Cloud Run
With flexibility of GKE
Fully-managed Kubernetes cluster
Serverless containers, where you want them
Self-managed
Kubernetes cluster
Cloud Run compatible
With Knative open API
Runs on-prem or in other cloud on
Self-managed Kubernetes cluster
cloud.google.com/run

+JavaScript
-API “flavor”
+built-in
“flavor”
-OAuth2 (you)
!=
Google Apps Script
Apps Script overview
goo.gle/2VF8xeC
“Hello World!” in Apps Script

Sheets-bound “Hello World!”
Apps Script intro
goo.gl/1sXeuD
What can you do with this?

Accessing maps from
spreadsheets?!?
goo.gl/oAzBN9
This… with help from Google Maps & Gmail
function sendMap() {
var sheet = SpreadsheetApp.getActiveSheet();
var address = sheet.getRange("A2").getValue();
var map = Maps.newStaticMap().addMarker(address);
GmailApp.sendEmail('friend@example.com', 'Map',
'See below.', {attachments:[map]});
}
JS
Codelab and open source repo at
g.co/codelabs/apps-script-intro

G Suite & other Google APIs
Collaborate and be more productive with G Suite
G Suite: Google Drive
Drive API allows developers to read,
write, control permissions/sharing,
import/export files, and more!
developers.google.com/drive

Try our Node.js customized reporting tool codelab:
g.co/codelabs/sheets
Why use the Sheets API?
data visualization
customized reports
Sheets as a data source
Migrate SQL data to a Sheet
# read SQL data then create new spreadsheet & add rows into it
FIELDS = ('ID', 'Customer Name', 'Product Code',
'Units Ordered', 'Unit Price', 'Status')
cxn = sqlite3.connect('db.sqlite')
cur = cxn.cursor()
rows = cur.execute('SELECT * FROM orders').fetchall()
cxn.close()
rows.insert(0, FIELDS)
DATA = {'properties': {'title': 'Customer orders'}}
SHEET_ID = SHEETS.spreadsheets().create(body=DATA,
fields='spreadsheetId').execute().get('spreadsheetId')
SHEETS.spreadsheets().values().update(spreadsheetId=SHEET_ID, range='A1',
body={'values': rows}, valueInputOption='RAW').execute()
Migrate SQL data
to Sheets
goo.gl/N1RPwC

G Suite: Google Docs & Slides
Docs & Slides APIs give you access
to read or write documents and
presentations programmatically so
you can auto-generate them with data
integrated from various sources
developers.google.com/docs
developers.google.com/slides
● Not just for conversations
● Create microservice utilities
● Build chat bots to...
○ Automate workflows
○ Query for information
○ Other heavy-lifting
● Plain text or rich UI "cards"
● Very flexible ("any")
development environment
○ POST to HTTP port
Hangouts Chat bots
(bot framework & API)

"Hello World" (echo bot)
JavaScript: Google Apps Script
function onMessage(m) {
return {
'text': 'Hi ' + m.sender.displayName + '. You sent: ' + m.text,
'thread': {'name': m.thread.name}
};
}
Hangouts Chat bots
goo.gl/jt3FqK
Other Google APIs & platforms
● Firebase (mobile development platform + RT DB)
○ firebase.google.com
● Google Data Studio (data visualization, dashboards, etc.)
○ datastudio.google.com/overview
○ goo.gle/datastudio-course
● Actions on Google/Assistant/DialogFlow (voice apps)
○ developers.google.com/actions
● YouTube (Data, Analytics, and Livestreaming APIs)
○ developers.google.com/youtube
● Google Maps (Maps, Routes, and Places APIs)
○ developers.google.com/maps
● Flutter (native apps [Android, iOS, web] w/1 code base[!])
○ flutter.dev

04
All of Cloud
(inspiration)
Build powerful solutions
with GCP and G Suite
Custom intelligence in Gmail
Analyze G Suite data with GCP

Gmail message processing with GCP
Gmail
Cloud
Pub/Sub
Cloud
Functions
Cloud
Vision
G Suite GCP
Star
message
Message
notification
Trigger
function
Extract
images
Categorize
images

Inbox augmented with Cloud Function
● Gmail API: sets up notification forwarding to Cloud Pub/Sub
● developers.google.com/gmail/api/guides/push
● Pub/Sub: triggers logic hosted by Cloud Functions
● cloud.google.com/functions/docs/calling/pubsub
● Cloud Functions: "orchestrator" accessing GCP (and G Suite) APIs
● Combine all of the above to add custom intelligence to Gmail
● Deep dive code blog post
● cloud.google.com/blog/products/application-development/
adding-custom-intelligence-to-gmail-with-serverless-on-gcp
● Application source code
● github.com/GoogleCloudPlatform/cloud-functions-gmail-nodejs
App summary

Big data analysis to slide presentation
Access GCP tools from G Suite

Supercharge G Suite with GCP
G Suite GCP
BigQuery
Apps Script
Slides Sheets
Application
request
Big data
analytics
App summary
● Leverage GCP and build the "final mile" with G Suite
● Driven by Google Apps Script
● Google BigQuery for data analysis
● Google Sheets for visualization
● Google Slides for presentable results
● "Glued" together w/G Suite serverless
● Build this app (codelab): g.co/codelabs/bigquery-sheets-slides
● Video and blog post: bit.ly/2OcptaG
● Application source code: github.com/googlecodelabs/bigquery-sheets-slides
● Presented at Google Cloud NEXT (Jul 2018 [DEV229] & Apr 2019 [DEV212])
● cloud.withgoogle.com/next18/sf/sessions/session/156878
● cloud.withgoogle.com/next/sf/sessions?session=DEV212

05
Wrap-up
Summary & resources
Session Summary
● Google provides more than just apps
○ You may know Google for search, YouTube, Android, Chrome, and Gmail, but...
○ We've made much of our technology available to developers through our APIs
○ To help prevent all those wheel reinventions!
● Tour of Google APIs & developer tools
○ G Suite: not just a set of productivity apps… you can code them too!
○ GCP: compute, storage, networking, security, data & machine learning tools
○ Google Cloud serverless frees developers from infrastructure
■ 4 unique solutions so you can focus on building solutions
● Interesting possibilities using both Cloud platforms (GCP + G Suite)
● Many other Google developer products

● Documentation
○ GCP: cloud.google.com/{docs,appengine,functions,vision,automl,sql,compute.storage,
language,speech,text-to-speech,translate,video-intelligence,firestore,bigquery,filestore}
○ G Suite: developers.google.com/{gsuite,drive,calendar,gmail,docs,sheets,slides,apps-script}
● Introductory "codelabs" ([free] self-paced, hands-on tutorials)
○ G Suite REST APIs: g.co/codelabs/gsuite-apis-intro (featuring Drive API)
○ Apps Script: g.co/codelabs/apps-script-intro
○ App Engine: codelabs.developers.google.com/codelabs/cloud-app-engine-python
○ Cloud Vision: g.co/codelabs/vision-python (or C# or Ruby)
○ Cloud Functions: codelabs.developers.google.com/codelabs/cloud-starting-cloudfunctions
○ All others: gcplab.me (GCP) and g.co/codelabs (non-GCP)
● Videos: youtube.com/GoogleCloudPlatform (GCP), goo.gl/JpBQ40 (G Suite), and all others
● Code samples: github.com/GoogleCloudPlatform (GCP) and github.com/gsuitedevs (G Suite)
● GCP Free trial (new users) and Always Free (daily/monthly tier) - cloud.google.com/free
Compare with GCP at cloud.google.com/docs/compare/aws
Online resources
Thank you! Questions?
Wesley Chun
@wescpy
Progress bars: goo.gl/69EJVw
Slides: bit.ly/2SHybQg

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