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Hands-On RESTful Python Web Services - Second Edition

By : Gaston C. Hillar

2.3 (3)

Hands-On RESTful Python Web Services

2.3 (3)

By: Gaston C. Hillar

Overview of this book

Python is the language of choice for millions of developers worldwide that builds great web services in RESTful architecture. This second edition of Hands-On RESTful Python Web Services will cover the best tools you can use to build engaging web services. This book shows you how to develop RESTful APIs using the most popular Python frameworks and all the necessary stacks with Python, combined with related libraries and tools. You’ll learn to incorporate all new features of Python 3.7, Flask 1.0.2, Django 2.1, Tornado 5.1, and also a new framework, Pyramid. As you advance through the chapters, you will get to grips with each of these frameworks to build various web services, and be shown use cases and best practices covering when to use a particular framework. You’ll then successfully develop RESTful APIs with all frameworks and understand how each framework processes HTTP requests and routes URLs. You’ll also discover best practices for validation, serialization, and deserialization. In the concluding chapters, you will take advantage of specific features available in certain frameworks such as integrated ORMs, built-in authorization and authentication, and work with asynchronous code. At the end of each framework, you will write tests for RESTful APIs and improve code coverage. By the end of the book, you will have gained a deep understanding of the stacks needed to build RESTful web services.

Preface

Preface

Who this book is for

What this book covers

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Developing RESTful APIs and Microservices with Flask 1.0.2

Developing RESTful APIs and Microservices with Flask 1.0.2

Designing a RESTful API to interact with a simple data source

Understanding the tasks performed by each HTTP method

Understanding microservices

Working with lightweight virtual environments

Setting up a virtual environment with Flask and Flask-RESTful

Declaring status codes for the responses with an enumerable

Creating the model

Using a dictionary as a repository

Configuring output fields

Working with resourceful routing on top of Flask pluggable views

Configuring resource routing and endpoints

Making HTTP requests to the Flask API

Test your knowledge

Summary

Working with Models, SQLAlchemy, and Hyperlinked APIs in Flask

Working with Models, SQLAlchemy, and Hyperlinked APIs in Flask

Designing a RESTful API to interact with a PostgreSQL 10.5 database

Understanding the tasks performed by each HTTP method

Installing packages with the requirements.txt file to simplify our common tasks

Creating the database

Configuring the database

Creating models with their relationships

Creating schemas to validate, serialize, and deserialize models

Combining blueprints with resourceful routing

Understanding and configuring resourceful routing

Registering the blueprint and running migrations

Verifying the contents of the PostgreSQL database

Creating and retrieving related resources

Test your knowledge

Summary

Improving Our API and Adding Authentication to it with Flask

Improving Our API and Adding Authentication to it with Flask

Improving unique constraints in the models

Understanding the differences between the PUT and the PATCH methods

Updating fields for a resource with the PATCH method

Coding a generic pagination class

Adding pagination features

Understanding the steps to add authentication and permissions

Adding a user model

Creating schemas to validate, serialize, and deserialize users

Adding authentication to resources

Creating resource classes to handle users

Running migrations to generate the user table

Composing requests with the necessary authentication

Test your knowledge

Summary

Testing and Deploying an API in a Microservice with Flask

Testing and Deploying an API in a Microservice with Flask

Setting up unit tests with pytest

Creating a database for testing

Creating fixtures to perform setup and teardown tasks for running clean tests

Writing the first round of unit tests

Running unit tests with pytest and checking testing coverage

Improving testing coverage

Understanding strategies for deployments and scalability

Test your knowledge

Summary

Developing RESTful APIs with Django 2.1

Developing RESTful APIs with Django 2.1

Designing a RESTful API to interact with a simple SQLite database

Understanding the tasks performed by each HTTP method

Setting up the virtual environment with Django REST framework

Creating the models

Managing serialization and deserialization

Understanding status codes for the responses

Writing API views

Making HTTP requests to the Django API

Test your knowledge

Summary

Working with Class-Based Views and Hyperlinked APIs in Django 2.1

Working with Class-Based Views and Hyperlinked APIs in Django 2.1

Using model serializers to eliminate duplicate code

Working with wrappers to write API views

Using the default parsing and rendering options and moving beyond JSON

Browsing the API

Designing a RESTful API to interact with a complex PostgreSQL 10.5 database

Understanding the tasks performed by each HTTP method

Declaring relationships with the models

Installing packages with the requirements.txt file to work with PostgreSQL

Configuring the database

Running migrations

Verifying the contents of the PostgreSQL database

Managing serialization and deserialization with relationships and hyperlinks

Creating class-based views and using generic classes

Taking advantage of generic class-based views

Working with endpoints for the API

Browsing an API with relationships

Creating and retrieving related resources

Test your knowledge

Summary

Improving Our API and Adding Authentication to it with Django

Improving Our API and Adding Authentication to it with Django

Adding unique constraints to the models

Updating a single field for a resource with the PATCH method

Taking advantage of pagination

Customizing pagination classes

Understanding authentication, permissions, and throttling

Adding security-related data to the models

Creating a customized permission class for object-level permissions

Persisting the user that makes a request and configuring permission policies

Setting a default value for a new required field in migrations

Composing requests with the necessary authentication

Browsing the API with authentication credentials

Test your knowledge

Summary

Throttling, Filtering, Testing, and Deploying an API with Django 2.1

Throttling, Filtering, Testing, and Deploying an API with Django 2.1

Installing packages with the requirements.txt file to work with filters, throttling, and tests

Understanding filtering, searching, and ordering classes

Configuring filtering, searching, and ordering for views

Executing HTTP requests to test filtering, searching, and ordering

Filtering, searching and ordering in the Browsable API

Understanding throttling classes and goals

Configuring throttling policies

Executing HTTP requests to test throttling policies

Setting up unit tests with pytest

Writing the first round of unit tests

Running unit tests with pytest

Improving testing coverage

Running Django RESTful APIs on the cloud

Test your knowledge

Summary

Developing RESTful APIs with Pyramid 1.10

Developing RESTful APIs with Pyramid 1.10

Designing a RESTful API to interact with a simple data source

Setting up the virtual environment with Pyramid 1.10

Creating a new Pyramid project based on a template

Creating the model

Using a dictionary as a repository

Creating a Marshmallow schema to validate, serialize, and deserialize the model

Working with view callables and view configurations

Understanding and configuring view handlers

Making HTTP requests to the API with command-line tools

Test your knowledge

Summary

Developing RESTful APIs with Tornado 5.1.1

Developing RESTful APIs with Tornado 5.1.1

Designing a RESTful API to interact with slow sensors and actuators

Understanding the tasks performed by each HTTP method

Setting up a virtual environment with Tornado 5.1.1

Creating classes that represent a drone

Writing request handlers

Mapping URL patterns to request handlers

Making HTTP requests to the Tornado API

Test your knowledge

Summary

Working with Asynchronous Code, Testing, and Deploying an API with Tornado

Working with Asynchronous Code, Testing, and Deploying an API with Tornado

Understanding synchronous and asynchronous execution

Refactoring code to take advantage of asynchronous decorators

Mapping URL patterns to asynchronous request handlers

Making HTTP requests to the Tornado non-blocking API

Setting up unit tests with pytest

Writing the first round of unit tests

Running unit tests with pytest and checking testing coverage

Improving testing coverage

Understanding strategies for deploying Tornado APIs to the cloud

Test your knowledge

Summary

Assessment

Assessment

Chapter 1

Chapter 2

Chapter 3

Chapter 4

Chapter 5

Chapter 6

Chapter 7

Chapter 8

Chapter 9

Chapter 10

Chapter 11

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Understanding microservices

In the last few years, many large and complex applications started shifting from a monolithic architecture to a microservices architecture. Instead of working with large and extremely complex web services, the microservices architecture proposes developing a collection of smaller, loosely-coupled services to implement all the features required by complex applications in a way that enables and simplifies continuous delivery.

RESTful APIs are essential pieces of the microservices architecture, and Python is extremely popular when shifting to this architecture. Each microservice can encapsulate a RESTful API that fulfills a specific and limited purpose. The microservice is self-contained, it is easy to maintain, and it helps to support continuous delivery.

As happens with any architecture, there are several ways to implement the microservices architecture. We will learn to encapsulate a RESTful API developed with Flask and Python into a microservice. This way, we will be able to leverage our skills by developing RESTful APIs and using them as the essential pieces to build self-contained and easy-to-maintain microservices.

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