Python for Google App Engine -- Table of Contents -- Python for Google App Engine -- Credits -- About the Author -- About the Reviewers -- www.PacktPub.com -- Support files, eBooks, discount offers, and more -- Why subscribe? -- 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.