Powerful Google developer tools for immediate impact! (2023-24 C)

Powerful Google developer tools for immediate impact! (2023-24 C)

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  Sudbury :: Spr2024 Wesley Chun Principal, CyberWeb @wescpy@ Powerful Google developer tools for immediate impact! Where to run your code, store your data, and analyze your data Principal Consultant, CyberWeb ● Mission: produce accelerated Python developers, enable developers to be successful using Google Cloud and other Google developer tools & APIs ● Focus: Python, Google Cloud (GCP) & Google Workspace (GWS) APIs; GAE migrations; Google X-product sol'ns ● Services: technical consulting, training, engineering, speaking, code samples, hands-on tutorials, public technical content (blogs, social, etc.) About the speaker Previous experience / background ● Software Engineer & Developer Advocate ○ Google, Sun, HP, Cisco, EMC, Xilinx & ○ Original Yahoo!Mail engineer/SWE ● Technical trainer, teacher, instructor ○ Teaching Math, Linux, Python since '83 ○ Adjunct CS Faculty at local SV colleges ● Python community member ○ Popular Core Python series author ○ Python Software Foundation Fellow ● AB (Math/CS) & CMP (Music/Piano), UC Berkeley and MSCS, UC Santa Barbara ● Adjunct Computer Science Faculty, Foothill College (Silicon Valley) GWS Dev Show goo.gl/JpBQ40 GAE migration bit.ly/3xk2Swi
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  Impactful developer tools:why & agenda ● People know Google for search, YouTube, Chrome, Android, Gmail ● Google also has an extensive set of developer tools, APIs & platforms ● Many of these developer services part of Google Cloud ● Cloud computing has taken industry by storm & its skills are in-demand ● Look at most impactful tools for work/school projects you can use today! Cloud computing & Google Cloud 1 Where to run your code 2 Google APIs primer 3 Where to analyze your data 4 5 Where to store your data 7 Wrap-up 6 Inspiration 01 Cloud computing & Google Cloud Intro and overview
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  Getting things doneusing someone else’s computers, especially where someone else worries about maintenance, provisioning, system administration, security, networking, failure recovery, upgrades, etc. Google Compute Engine, Cloud Storage AWS EC2 & S3; Rackspace; Joyent Cloud service levels/"pillars" SaaS Software as a Service PaaS Platform as a Service IaaS Infrastructure as a Service Google BigQuery, Cloud SQL, Vertex AI, Cloud Datastore, NL, Vision, Pub/Sub AWS Kinesis, RDS; Windows Azure SQL, Docker Google Apps Script Salesforce Platform (formerly force.com) Google Workspace (was G Suite/Google Apps) Yahoo!Mail, Hotmail, Salesforce, Netsuite, Office 365 Google App Engine, Cloud Functions Heroku, Cloud Foundry, Engine Yard, AWS Lambda
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  Summary of responsibility SaaS Softwareas a Service Applications Data Runtime Middleware OS Virtualization Servers Storage Networking Applications Data Runtime Middleware OS Virtualization Servers Storage Networking IaaS Infrastructure as a Service Applications Data Runtime Middleware OS Virtualization Servers Storage Networking PaaS Platform as a Service Managed by YOU Managed by cloud vendor Applications Data Runtime Middleware OS Virtualization Servers Storage Networking on-prem all you, no cloud Theme - Spec/Reqs Logistics - Design app Space - Provision HW Food - Build & serve app Manage - Manage app on-prem (DIY) IaaS (Compute Engine) PaaS (App Engine) SaaS (Google Workspace (formerly G Suite)) Pick theme Plan party Find space Cook On-call Pick theme Plan party Rent hall Cook On-call Pick theme Plan party Rent hall Hire Caterer Hire manager Pick theme Hire planner Rent hall Hire caterer Hire manager Imagine you’re hosting a party...
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  formerly ( ) 02 Where torun your code Serverless simplifies it all!
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  > Google ComputeEngine configurable VMs of all shapes & sizes, from "micro" to 416 vCPUs, 11.776 TB RAM, 256 TB HDD/SSD plus Google Cloud Storage for data lake "blobs" (Debian, CentOS, CoreOS, SUSE, Red Hat Enterprise Linux, Ubuntu, FreeBSD; Windows Server 2008 R2, 2012 R2, 2016, 1803, 1809, 1903/2019, 1909) cloud.google.com/compute cloud.google.com/storage Yeah, there are VMs & big disk… but why*? Serverless: what & why ● What is serverless? ○ Misnomer (a "PMM") :-) ○ "No worries" ○ Developers focus on writing code & solving business problems* ○ Servers (physical & virtual) completely abstracted away from the user* ● Why serverless? ○ Fastest growing segment of cloud... per analyst research: ■ $1.9B (2016) & $4.25B (2018) ⇒ $7.7B (2021), $14.93B (2023), and $21.1B (2025)^ ■ $4.18B (2018) & $6.05B (2020) ⇒ $31.53B (2026), $53.08B (2028), and $86.94B (2030)† ○ What if you go viral? Autoscaling: your new best friend ○ What if you don't? Code not running? You're not paying. * Forbes (May 2018) ^ (in USD) CB Insights (Sep 2018), MarketsandMarkets™ (Jan 2019) † (in USD) Reports and Data (Jan 2020, Oct 2021, and Jun 2022)
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  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 Workspace (was 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 Serverless: PaaS-y compute/processing Google Apps Script Salesforce Platform (formerly force.com) Google App Engine App-hosting in the cloud ("Serverless 1.0") cloud.google.com/appengine
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  Why does AppEngine exist? ● Focus on code not DevOps ○ Web app or mobile backend ● Enhance productivity ● Deploy globally ● Fully-managed ● Auto-scaling ● Pay-per-use ● Familiar languages ● Test w/local dev server ● "Bundled" services like DB, caching, tasks, storage, etc. Hello World (Python "MVP") app.yaml runtime: python39 main.py from flask import Flask app = Flask(__name__) @app.route('/') def hello(): return 'Hello World!' requirements.txt flask Deploy: $ gcloud app deploy Access globally: PROJECT_ID.appspot.com cloud.google.com/appengine/docs/standard/python3/quickstart
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  Google Cloud Functions Function-hostingin the cloud ("Serverless 2.0") cloud.google.com/functions Why does Cloud Functions exist? ● Don't have entire app? ○ No framework "overhead" (LAMP, MEAN...) ○ Deploy short utilities (alerts, ETL...), monoliths → loosely-coupled microservices, event-driven tasks ● 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) ○ Develop/test locally with Functions Framework ● Cloud Functions for Firebase ○ Mobile app use-cases
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  main.py def hello_world(request): return 'HelloWorld!' Deploy: $ gcloud functions deploy hello --runtime python39 --trigger-http Access globally (curl): $ curl REGION-PROJECT_ID.cloudfunctions.net/hello Access globally (browser): https://REGION-PROJECT_ID.cloudfunctions.net/hello Hello World (Python "MVP") cloud.google.com/functions/docs/quickstart-python Google Cloud Run Container-hosting in the cloud ("Serverless 2.0") cloud.run
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  The rise ofcontainers... ● Any language ● Any library ● Any binary ● Ecosystem of base images ● Industry standard FLEXIBILITY “We can’t be locked in.” “How can we use existing binaries?” “Why do I have to choose between containers and serverless?” “Can you support language _______ ?” Serverless inaccessible for some... CONVENIENCE
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  Cloud Run: code,build, deploy .js .rb .go .sh .py ... ● Any language, library, binary ○ HTTP port, stateless ● Bundle into container ○ Build with Docker OR Cloud Build ○ Image ⇒ Container/Artifact Registry ● Deploy to Cloud Run (managed or GKE) ● GitOps: CD push-to-deploy from Git ○ See documentation & announcement ○ CI/CD with GitHub Actions tutorial ● Cloud Buildpacks: Docker, Dockerfiles, and knowledge of containers optional State HTTP Hello World (Python "MVP") main.py import os from flask import Flask app = Flask(__name__) @app.route('/') def hello_world(): return 'Hello World!' if __name__ == '__main__': app.run(debug=True, host='0.0.0.0', port=int(os.environ.get('PORT', 8080))) cloud.google.com/run/docs/quickstarts/build-and-deploy requirements.txt flask
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  Hello World (Python"MVP") Dockerfile FROM python:3-slim WORKDIR /app COPY . . RUN pip install -r requirements.txt CMD ["python", "main.py"] .dockerignore Dockerfile README.md *.pyc *.pyo .git/ __pycache__ Build (think docker build and docker push) then deploy (think docker run): $ gcloud builds submit --tag gcr.io/PROJ_ID/IMG_NAME $ gcloud run deploy SVC_NAME --image gcr.io/PROJ_ID/IMG_NAME OR… Build and Deploy (1-line combination of above commands): $ gcloud run deploy SVC_NAME --source . Access globally: SVC_NAME-HASH-REG_ABBR.a.run.app Docker & Dockerfile OPTIONAL!! ● Build containers easily & securely without creating/managing Dockerfiles ● Open source, open standard; based on CNCF Buildpacks spec v3 ● Used by GCF Functions Framework to deploy locally-developed functions ● Supports most common development tools ○ Go 1.10+ ○ Node.js 10+ ○ Python 3.7+ ○ Java 8 & 11 ○ .NET Core 3.1+ ● Blog posts ○ See cloud.google.com/blog/products/containers-kubernetes/google-cloud-now-supports-buildpacks and cloud.google.com/blog/products/serverless/build-and-deploy-an-app-to-cloud-run-with-a-single-command Deploy to Cloud Run with Buildpacks github.com/GoogleCloudPlatform/buildpacks $ ls index.js package.json $ gcloud run deploy myapp --source . $ ls main.py requirements.txt $ gcloud run deploy myapp --source . Node.js, Go, Python, etc.? It's the same command!
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  Flexibility in options Cloud Functions App Engine Cloud Run local server ●"Nebulous" sample web app ○ Flask/Python 2 or 3 ○ Express/Node.js 10+ ○ Uses Cloud Translation API ● Deployable to on-prem server ● Also GCP serverless compute ○ App Engine ○ Cloud Functions ○ Cloud Run ● With only config changes ● No changes to app code Cloud Translation My "Google Translate" MVP goo.gle/2Y0ph5q youtu.be/eTotLOVR7MQ Google Apps Script Customized serverless JS runtime for automation, and extension and integration with Google Workspace (formerly G Suite) and other Google & external services
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  “Hello World!” inApps Script Sheets-bound “Hello World!” Apps Script intro goo.gl/1sXeuD t.co/rqHT2gYN6z
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  What can youdo 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('[email protected]', 'Map', 'See below.', {attachments:[map]}); } JS g.co/codelabs/apps-script-intro
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  03 Google APIs primer Howto access & use Google APIs
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  General steps 1. Goto Cloud Console 2. Login to Google/Gmail account (Workspace domain may require admin approval) 3. Create project (per application) 4. Enable APIs to use 5. Enable billing (CC, Free Trial, etc.) 6. Download client library(ies) 7. Create & download credentials 8. Write code* 9. Run code (may need to authorize) Google APIs: how to use *In your code 1. Import API client library 2. Create API client object 3. Use client to make API Calls Costs & pricing ● GCP & GMP: pay-per-use (CC req'd) ● GWS: "subscription" (incl. $0USD/mo.) ● GMP: $200/mo. free usage ● GCP Free Trial: $300/1Q ● GCP "Always Free" tier ○ Some products have free tier ○ Daily or monthly quota ○ Must exceed to incur billing ● More on both programs at cloud.google.com/free
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  Cloud/GCP console console.cloud.google.com ● Hubof all developer activity ● Applications == projects ○ New project for new apps ○ Projects have a billing acct ● Manage billing accounts ○ Financial instrument required ○ Personal or corporate credit cards, Free Trial, and education grants ● Access GCP product settings ● Manage users & security ● Manage APIs in devconsole ● View application statistics ● En-/disable Google APIs ● Obtain application credentials Using Google APIs goo.gl/RbyTFD API manager aka Developers Console (devconsole) console.developers.google.com
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  Client libraries andcredentials types ● Two different client library types ○ Platform-level client libraries (lower-level) ■ Multiple product groups as a "lowest-common denominator" ■ Install: developers.google.com/api-client-library ○ Product-level client libraries (higher-level) ■ Custom client libraries made specifically for 1 product or product group ■ Found on product or product group page(s) ● Three different credentials types ○ Simple: API keys (access public data) ■ Simplest form of authorization: an API key; tied to a project ○ Authorized: OAuth client IDs (access data owned by [human] user) ■ Provides additional layer of security via OAuth2 (RFC 6749) ○ Authorized: service accounts (access data owned by an app/robot user) ■ Provides additional layer of security via OAuth2 or JWT (RFC 7519) Blog series: dev.to/wescpy & Google APIs client libraries for many languages; demos in developers.google.com/api- client-library cloud.google.com/apis/docs /cloud-client-libraries
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  OAuth2 or API key HTTP-basedREST APIs 1 HTTP 2 Google APIs request-response workflow ● Application makes request ● Request received by service ● Process data, return response ● Results sent to application (typical client-server model) 04 How to analyze your data AI/ML services via API
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  AI & machinelearning Puppy or muffin? Source: twistedsifter.com/2016/03/ puppy-or-bagel-meme-gallery
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  Machine learning islearning from rules plus experience. Inference Phase Training Phase answers data model ("rules") Machine Learning Model predictions (new) data
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  Vertex AI task-specificmodels: 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 Machine Learning: Cloud Vision & Video Intelligence Google Cloud Vision & Video Intelligence APIs enable developers to extract metadata & understand the content of images & videos, making them searchable & discoverable. cloud.google.com/vision cloud.google.com/video-intelligence
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  from google.cloud importvision 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(label.description, '(%.2f%%)' % (label.score*100.)) 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
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  Google Photos The apphas a search bar?!? blog.google/products/photos/smarter-photo-albums-without-work Global view Problem ● 1B ppl depend on seafood ● 85% at/over-fishing or recovering ● 20% caught illegal, undoc'd, unreg'd ● Analysts monitoring unscalable One solution ● globalfishingwatch.org/map ● Machine-learning classifiers: ○ Ship type: cargo, tug, sail, fishing ○ Ship size ○ Gear: longline, purse seine, trawl ○ Movement tracking: when and where vessels are fishing
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  quickdraw.withgoogle.com Cloud Vision demo:Quick Draw game experiments.withgoogle.com/quick-draw Machine Learning: Cloud Natural Language Google Cloud Natural Language API reveals the structure and meaning of text, performing sentiment analysis, content classification, entity extraction, and syntactical structure analysis; multi-lingual cloud.google.com/language
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  Simple sentiment &classification analysis from google.cloud import language TEXT = '''Google, headquartered in Mountain View, unveiled the new Android phone at the Consumer Electronics Show. Sundar Pichai said in his keynote that users love their new Android phones.''' NL = language.LanguageServiceClient() document = language.types.Document(content=TEXT, type=language.enums.Document.Type.PLAIN_TEXT) print('TEXT:', TEXT) # sentiment analysis sent = NL.analyze_sentiment(document).document_sentiment print('nSENTIMENT: score (%.2f), magnitude (%.2f)' % (sent.score, sent.magnitude)) print('nCATEGORIES:') # content classification categories = NL.classify_text(document).categories for cat in categories: print('* %s (%.2f)' % (cat.name[1:], cat.confidence)) Simple sentiment & classification analysis $ python nl_sent_simple.py TEXT: Google, headquartered in Mountain View, unveiled the new Android phone at the Consumer Electronics Show. Sundar Pichai said in his keynote that users love their new Android phones. SENTIMENT: score (0.20), magnitude (0.50) CATEGORIES: * Internet & Telecom (0.76) * Computers & Electronics (0.64) * News (0.56)
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  Machine Learning: AutoML AutoML:suite of cloud APIs for developers with limited machine learning expertise; take task-specific pre-trained model, perform additional training with your data to finetune that model (Translation, Vision, Natural Language, Video Intelligence, Tables) cloud.google.com/automl cloud.google.com/automl-tables import google.generativeai as genai from settings import API_KEY PROMPT = 'Describe a cat in a few sentences' MODEL = 'gemini-pro' print('** GenAI text: %r model & prompt %rn' % ( MODEL, PROMPT)) genai.configure(api_key=API_KEY) model = genai.GenerativeModel(MODEL) response = model.generate_content(PROMPT) print(response.text) Google AI: Gemini API ai.google.dev/tutorials Blog series: dev.to/wescpy
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  Full Spectrum ofAI & ML Offerings App developer Data scientist, developer Data scientist, Researcher (w/infrastructure access & DevOps/SysAdmin skills) Vertex AI platform Build custom models, use OSS SDK on fully- managed infrastructure Single-task model APIs App developer, data scientist Use or fine-tune pre-built models Use pre-built/pre- trained models Build custom models, use/ extend OSS SDK, self-manage training infrastructure LMM/large multimodal model API Auto ML Google and Jupyter Notebooks Users have many ways to access an indispensable data science tool ● Jupyter Notebook support on GCP ○ cloud.google.com/notebooks ○ Vertex AI Workbench ■ cloud.google.com/vertex-ai/docs/workbench ○ Colab Enterprise ■ cloud.google.com/colab ● Kaggle ○ kaggle.com ● Google Research CoLaboratory (Colab) ○ colab.research.google.com ● GCP-deprecated: Dataproc Hub, Datalab, Vertex AI managed & user-mgd
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  05 Where to store yourdata And more ways to analyze it Storage and Big Data Cloud Storage & Filestore Object/file-based storage Cloud SQL, AlloyDB, Spanner FM relational databases Cloud Datastore, BigTable FM scalable NoSQL DBs Firebase Realtime JSON/document store Cloud Firestore Document DB (Datastore + Firebase) BigQuery Data warehouse & analysis Cloud Pub/Sub Message queue service
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  Storing Data: CloudFirestore A fully-managed, highly-scalable NoSQL database for your web and mobile applications, combining Cloud Datastore with features from the Firebase realtime database (For choosing between Firebase & Cloud Firestore: see firebase.google.com/docs/firestore/rtdb-vs-firestore; for choosing between Firestore Datastore & Firestore Native modes: see cloud.google.com/datastore/docs/firestore-or-datastore) cloud.google.com/firestore Cloud Firestore: data model collections subcollections
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  Cloud Firestore: straightforwardqueries github.com/GoogleCloudPlatform/python-docs-samples/blob/master/firestore/cloud-client/snippets.py Storing and Analyzing Data: BigQuery Google BigQuery: fully-managed data warehouse for large-scale data analytics with built-in machine learning (BQML); issue SQL queries across multi-terabytes of data. BQ Sandbox lets anyone query up to 1TB/mo for free with no obligation cloud.google.com/bigquery
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  BigQuery: querying Shakespearewords 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 = BQ.jobs().query(body={'query': QUERY}, projectId=PROJ_ID).execute() print('n*** Results for %r:n' % TITLE) print('t'.join(col['name'].upper() # HEADERS for col in rsp['schema']['fields'])) print('n'.join('t'.join(str(col['v']) # DATA for col in row['f']) for row in rsp['rows'])) 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
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  ● BigQuery publicdata sets: cloud.google.com/bigquery/public-data ● BQ sandbox (1TB/mo free): cloud.google.com/bigquery/docs/sandbox (see blog post) ● Other public data sets: cloud.google.com/public-datasets (Google Cloud), research.google/tools/datasets (Google Research), and Kaggle (kaggle.com) ● COVID-19 BigQuery data sets ○ How to use our data sets (see blog post) ○ JHU Coronavirus COVID-19 Global Cases data set ○ List of all COVID-19 data sets ● Cloud Life Sciences API: cloud.google.com/life-sciences (see blog post) ● Cloud Healthcare API: cloud.google.com/healthcare (see blog post) BigQuery and public data sets Google Workspace: Google Sheets Sheets API gives you programmatic access to spreadsheets; perform (w/code) almost any action you can do from the web interface as a user developers.google.com/sheets
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  06 Inspiration Use multiple GoogleAPIs to create unique solutions Custom intelligence in Gmail Analyze Google Workspace (formerly G Suite) data with GCP
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  Gmail message processingwith GCP Gmail Cloud Pub/Sub Cloud Functions Cloud Vision Workspace (formerly G Suite) GCP Star message Message notification Trigger function Extract images Categorize images
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  Inbox augmented withCloud 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 Google Workspace/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
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  Big data analysisto slide presentation Access GCP tools from Google Workspace (formerly G Suite)
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  Store big dataresults Visualize big data results
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  Ingest data fromSheets Link to chart in Sheets
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  Supercharge Workspace (GSuite) with GCP Workspace (G Suite) GCP BigQuery Apps Script Slides Sheets Application request Big data analytics
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  App summary ● LeverageGCP and build the "final mile" with Google Workspace (formerly G Suite) ● Driven by Google Apps Script ● Google BigQuery for data analysis ● Google Sheets for visualization ● Google Slides for presentable results ● "Glued" together w/Google Workspace (formerly 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 07 Wrap-up Summary & resources
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  Summary: Google developertools & APIs ● Google provides more than just apps ○ More than search, YouTube, Android, Chrome, Gmail, and Docs ○ Google technology & integration available to developers via APIs ● Tour of Google (Cloud) APIs & developer tools ○ GWS: not just a set of productivity apps… you can code them too! ○ GCP: compute, storage, networking, security, data & machine learning tools ■ Serverless: frees developers from infrastructure ■ So you can focus on building solutions ● Interesting possibilities when using >1 Google product families/APIs ● With Google: run your apps, analyze & store your data Other Google APIs & platforms ● Google Workspace (G Suite) (code Gmail, Drive, Docs, Sheets, Slides!) ○ developers.google.com/gsuite ● Firebase (mobile development platform and RT DB plus ML-Kit) ○ firebase.google.com and firebase.google.com/docs/ml-kit ● 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
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  ● Documentation (mostAPIs have "Quickstarts") ○ GCP: cloud.google.com/{docs,appengine,functions,run,vision,automl,translate,language, speech,texttospeech,video-intelligence,firestore,bigquery,compute,storage,gpu,tpu} ○ GWS: developers.google.com/{gsuite,drive,calendar,gmail,docs,sheets,slides,apps-script} ● Introductory "codelabs" ([free] self-paced, hands-on tutorials) ○ GWS 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 Functions: codelabs.developers.google.com/codelabs/cloud-starting-cloudfunctions ○ Cloud Run: codelabs.developers.google.com/codelabs/cloud-run-hello-python3 ○ Others: g.co/codelabs (all Google codelabs) and g.co/codelabs/cloud (GCP-only) ● Videos: youtube.com/GoogleCloudPlatform (GCP) and goo.gl/JpBQ40 (GWS) ● Code samples: github.com/GoogleCloudPlatform (GCP) and github.com/googleworkspace (GWS) ● Cloud Free Trial (new users) and Always Free (daily/monthly tier) programs: cloud.google.com/free ● Know AWS/Azure? Compare with GCP products at cloud.google.com/docs/compare/aws ● Language support: cloud.google.com/{python,java,nodejs,go,php,ruby,dotnet} Resources (industry) ● Google Cloud (GCP) ○ Code samples for students: goo.gle/hackathon-toolkit ○ Videos: youtube.com/GoogleCloudPlatform ○ Codelabs (free, self-paced, hands-on tutorials): g.co/codelabs/cloud ○ Cloud Skills Boost/QwikLabs (free only for students): go.qwiklabs.com/hey-student ● GCP docs/quickstarts - cloud.google.com/{docs,appengine,functions,run,vision,automl,translate, language, speech,texttospeech,video-intelligence,firestore,bigquery,compute,storage,gpu,tpu} ● Like GCP? Wanna use it in class or your research lab? Send your profs to cloud.google.com/edu to apply for GCP teaching/research or Cloud Skills Boost/Qwiklabs/training credits! ● Know AWS/Azure? Compare w/GCP at cloud.google.com/docs/compare/aws ● GCP Free Trial (ignore) and Always Free (tier) - cloud.google.com/free ● Mobile apps: Firebase - firebase.google.com and Flutter - flutter.dev ● Workspace - developers.google.com/{workspace,drive,docs,sheets,slides} and goo.gl/JpBQ40 ● Other Google (non-GCP) codelabs: g.co/codelabs ● Developer Student Clubs - g.co/dev/dsc - Global Google student developer groups ● Internships & other career stuff - google.com/students Resources (students)
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  Prepare for careersin a cloud-first world. Ask your faculty to apply now. g.co/edu/cloudready Career Readiness track: certification On-demand Get free access to Architecting with Google Compute Engine specialization on-demand on Coursera. (100% discount) Self-paced labs Get free access to relevant Google Cloud quests & other Cloud Skills Boost self-paced labs powered by Qwiklabs. (100% discount: 10+ labs) Google Cloud Certified Prepare to take the exam and earn your Cloud certification. (100% discount for faculty, 50% discount for students per adherence to timelines and other criteria) Careers at Google (and other tech) Software Engineer (SWE): not the only technical role @Google ● Application Engineer ● Business Analyst ● Developer Advocate (DA) ● Developer Programs Engineer (DPE) ● Hardware Engineer ● Mechanical Engineer ● Network Engineer ● Product Manager (PM) ● Program Manager (PgM or TPM) ● Quantitative Analyst (Quant) ● Release Engineer ● Research Scientist ● Security Engineer ● Site Reliability Engineer (SRE) ● Software Engineer in Test (SET) ● System Administrator ● Technical Writer (TW) ● UX Content Strategist ● UX Designer ● UX Engineer ● Student careers: google.com/students ● Technical development guide: g.co/techdevguide ● Sample technical interview
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  Bring me toyour organization ... it is my job to help you! ● Engineering consulting ● Software development ● Technical seminars/tech talks ● Hands-on workshops ● Technical training courses ● Migration strategy & planning ● cyberwebconsulting.com ● appenginemigrations.com Slides you're looking at them now Work cyberwebconsulting.com Books corepython.com Blog dev.to/wescpy GWS+ML+Svrls (long multi-topic video) youtu.be/HFtEypXpoaY Nebulous serverless goo.gle/2Y0ph5q youtu.be/eTotLOVR7MQ Big data ⇒ slides bit.ly/2O9KqDd Progress bars goo.gl/69EJVw Thank you! Questions? Wesley Chun Principal Consultant, CyberWeb Python, GCP & GWS specialist CONTACT: @wescpy@