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Python for Google App Engine

By : Pippi

4.1 (10)

Python for Google App Engine

4.1 (10)

By: Pippi

Overview of this book

If you are a Python developer, whether you have experience in web applications development or not, and want to rapidly deploy a scalable backend service or a modern web application on Google App Engine, then this book is for you.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Downloading the example code

Errata

Piracy

Questions

Free Chapter

1. Getting Started

1. Getting Started

The cloud computing stack – SaaS, PaaS, and IaaS

Google Cloud Platform

What Google App Engine does

Making our first Python application

Google Developer Console

Summary

2. A More Complex Application

2. A More Complex Application

Experimenting on the Notes application

Authenticating users

HTML templates with Jinja2

Handling forms

Persisting data in Datastore

Using static files

Summary

3. Storing and Processing Users' Data

3. Storing and Processing Users' Data

Uploading files to Google Cloud Storage

Transforming images with the Images service

Processing long jobs with the task queue

Scheduling tasks with Cron

Sending notification e-mails

Receiving users' data as e-mail messages

Summary

4. Improving Application Performance

4. Improving Application Performance

Advanced use of Datastore

Using Memcache

Breaking our application into modules

Summary

5. Storing Data in Google Cloud SQL

5. Storing Data in Google Cloud SQL

Creating a Cloud SQL instance

Connecting to the instance with the MySQL console

Connecting to the instance from our application

Loading and saving data

Using the local MySQL installation for development

Summary

6. Using Channels to Implement a Real-time Application

6. Using Channels to Implement a Real-time Application

Understanding how the Channel API works

Making our application real time

Implementing the server

Tracking connections and disconnections

Summary

7. Building an Application with Django

7. Building an Application with Django

Setting up the local environment

Rewriting our application using Django 1.7

Summary

8. Exposing a REST API with Google Cloud Endpoints

8. Exposing a REST API with Google Cloud Endpoints

Reasons to use a REST API

Designing and building the API

Implementing API endpoints

Testing the API with API Explorer

Protecting an endpoint with OAuth2

Summary

Index

Index

Customer Reviews

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Persisting data in Datastore

Even if users can log in and submit a note, our application isn't very useful until notes are stored somewhere. Google Cloud Datastore is the perfect place to store our notes. As part of App Engine's infrastructure, it takes care of data distribution and replication, so all we have to do is define store and retrieve our entities using the Python NDB (Next DB) Datastore API.

Note

There are currently two APIs available in the Python runtime to interact with Datastore: the DB Datastore API, also known as ext.db, and the NDB Datastore API. Even if both the APIs store exactly the same data in Datastore, in this book, we will only use NDB; it is more recent, provides more features, and its API is slightly more robust.

An entity has one or more properties that in turn have a name and a type; each entity has a unique key that identifies it, and instead of storing different data in different tables as in a relational database, every entity in Datastore is categorized...

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