Python for Google App Engine电子书

Python for Google App Engine

Table of Contents

Python for Google App Engine

Credits

About the Author

About the Reviewers

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Free access for Packt account holders

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

Downloading the color images of this book

Errata

Piracy

Questions

1. Getting Started

The cloud computing stack – SaaS, PaaS, and IaaS

Google Cloud Platform

Hosting + Compute

Storage

BigQuery

Services

What Google App Engine does

The runtime environment

The services

Making our first Python application

Download and installation

Installing on Windows

Installing on Mac OS X

Installing on Linux

App Engine Launcher

Creating the application

The app.yaml configuration file

The main.py application script

Running the development server

Uploading the application to App Engine

Google Developer Console

Development Console

Summary

2. A More Complex Application

Experimenting on the Notes application

Authenticating users

HTML templates with Jinja2

Handling forms

Persisting data in Datastore

Defining the models

Basic querying

Transactions

Using static files

Summary

3. Storing and Processing Users' Data

Uploading files to Google Cloud Storage

Installing Cloud Storage Client Library

Adding a form to upload images

Serving files from Cloud Storage

Serving files through Google's Content Delivery Network

Serving images

Serving other types of files

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

Advanced use of Datastore

More on properties – arrange composite data with StructuredProperty

More on queries – save space with projections and optimize iterations with mapping

Projection queries

Mapping

NDB asynchronous operations

Caching

Backup and restore functionalities

Indexing

Using Memcache

Breaking our application into modules

Summary

5. Storing Data in Google Cloud SQL

Creating a Cloud SQL instance

Configuring access

Setting the root password

Connecting to the instance with the MySQL console

Creating the notes database

Creating a dedicated user

Creating tables

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

Understanding how the Channel API works

Making our application real time

Implementing the server

The JavaScript code for clients

Tracking connections and disconnections

Summary

7. Building an Application with Django

Setting up the local environment

Configuring a virtual environment

Installing dependencies

Rewriting our application using Django 1.7

Using Google Cloud SQL as a database backend

Creating a reusable application in Django

Views and templates

Authenticating users with Django

Using the ORM and migrations system

Processing forms with the Forms API

Uploading files to Google Cloud Storage

Summary

8. Exposing a REST API with Google Cloud Endpoints

Reasons to use a REST API

Designing and building the API

Resources, URLs, HTTP verbs, and response code

Defining resource representations

Implementing API endpoints

Testing the API with API Explorer

Protecting an endpoint with OAuth2

Summary

Index