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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

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Advanced use of Datastore

We have already learned a lot about Datastore so far, including how to define entity kinds with model classes, the property concept, and how to make simple queries.

There is a lot more we can do with the NDB Python API to optimize an application, as we will see shortly.

More on properties – arrange composite data with StructuredProperty

In our Notes application, we defined the CheckListItem model class to represent checkable items, and then we added a property to the Note model named checklist_items that references a list of that kind of entities. This is what we usually call a one-to-many relationship between notes and checklist items, and it is a common way to structure application data. By following this strategy, though, every time we add an item to a note, we have to create and store a new entity on Datastore. This is not a bad practice at all, but we have to take into consideration that we are charged for the use of Datastore depending on the number...

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