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  • Book Overview & Buying Python for Google App Engine
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Python for Google App Engine

Python for Google App Engine

By : Pippi
4.1 (10)
Buy this Book
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Python for Google App Engine

Python for Google App Engine

4.1 (10)
By: Pippi
Buy this Book

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.
Table of Contents (10 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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Downloading the example code
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Errata
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Piracy
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Questions
Free Chapter
1
1. Getting Started
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1. Getting Started
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The cloud computing stack – SaaS, PaaS, and IaaS
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Google Cloud Platform
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What Google App Engine does
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Making our first Python application
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Google Developer Console
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Summary
2
2. A More Complex Application
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2. A More Complex Application
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Experimenting on the Notes application
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Authenticating users
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HTML templates with Jinja2
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Handling forms
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Persisting data in Datastore
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Using static files
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Summary
3
3. Storing and Processing Users' Data
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3. Storing and Processing Users' Data
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Uploading files to Google Cloud Storage
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Transforming images with the Images service
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Processing long jobs with the task queue
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Scheduling tasks with Cron
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Sending notification e-mails
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Receiving users' data as e-mail messages
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Summary
4
4. Improving Application Performance
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4. Improving Application Performance
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Advanced use of Datastore
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Using Memcache
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Breaking our application into modules
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Summary
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5. Storing Data in Google Cloud SQL
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5. Storing Data in Google Cloud SQL
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Creating a Cloud SQL instance
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Connecting to the instance with the MySQL console
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Connecting to the instance from our application
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Loading and saving data
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Using the local MySQL installation for development
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Summary
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6. Using Channels to Implement a Real-time Application
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6. Using Channels to Implement a Real-time Application
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Understanding how the Channel API works
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Making our application real time
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Implementing the server
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Tracking connections and disconnections
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Summary
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7. Building an Application with Django
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7. Building an Application with Django
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Setting up the local environment
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Rewriting our application using Django 1.7
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Summary
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8. Exposing a REST API with Google Cloud Endpoints
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8. Exposing a REST API with Google Cloud Endpoints
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Reasons to use a REST API
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Designing and building the API
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Implementing API endpoints
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Testing the API with API Explorer
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Protecting an endpoint with OAuth2
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Summary
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Index
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Index

Google Cloud Platform

Google Cloud Platform is designed to offer developers tools and services needed to build and run web applications on Google's reliable and highly scalable infrastructure. The platform consists of several cloud computing products that can be composed and used according to our needs, so it's important to know what these building blocks can do for us, as developers, and how they do so.

As we can learn from the main documentation page at https://cloud.google.com, Google classifies Google Cloud Platform's components into four groups: Hosting + Compute, Storage, Big Data, and services.

Hosting + Compute

There are two options if we want to host an application on Google Cloud Platform:

  • Google App Engine: This is Google's PaaS and it will be covered in detail later in this chapter.
  • Google Compute Engine: This is Google's IaaS and lets users run virtual machines on Google's infrastructure with a variety of hardware and software configurations.

Storage

Google Cloud Platform provides several options to store and access users' data:

Google Cloud Storage: This is a highly available and scalable file storage service with versioning and caching. We will learn how to use Cloud Storage in Chapter 3, Storing and Processing User's Data.

Google Cloud SQL: This is a fully managed MySQL relational database; replication, security and availability are Google's responsibilities. Chapter 5, Storing Data in Google Cloud SQL, is entirely dedicated to this service.

Google Cloud Datastore: This is a managed schemaless database that stores nonrelational data objects called entities; it scales automatically, supports transactions, and can be queried with SQL-like syntax. We will start using it in Chapter 2, A More Complex Application, and learn how to get the most out of it in Chapter 4, Improving Application Performance.

BigQuery

BigQuery is a tool provided by Google Cloud Platform that allows to perform queries using an SQL-like syntax against a huge amount of data in a matter of seconds. Before it can be analyzed, data must be streamed into BigQuery through its API or uploaded to Google Cloud Storage.

Services

Instead of writing code from scratch, we can easily add functionalities to our applications using some of Google's services through APIs that are very well integrated within Google Cloud Platform:

  • The Translate API: This can translate text between dozens of languages programmatically, from within our applications.
  • The Prediction API: This predicts future trends using Google's machine learning algorithms and can be used from within our applications or through a Representational State Transfer (REST) API. REST is a stateless architecture style that describes how a system can communicate with another through a network; we will delve into more details on REST in Chapter 8, Exposing a REST API with Google Cloud Endpoints.
  • Google Cloud Endpoints: Using this tool, it's easy to create applications that expose REST services, providing also Denial-of-Service (DoS) protection and OAuth2 authentication. We will learn how to use them in Chapter 8, Exposing a REST API with Google Cloud Endpoints.
  • Google Cloud DNS: This is global Domain Name System (DNS) service that runs on Google's infrastructure and provides high volume serving that is programmable from within our applications.
  • Google Cloud Pub/Sub: This is middleware that provides many-to-many, asynchronous messaging between services that either run on Google Cloud Platform or externally.

All the tools and services provided by Google Cloud Platform are billed with a pay-per-use model so that applications can scale up or down as needed and we only pay for resources we actually use. A handy calculator is provided to have a precise idea of the costs depending on the services and resources we think we will need. Google Cloud Platform offers a certain amount of resources we can use without paying anything; usually, these free quotas are well suited to host web applications with low traffic at no cost.

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