Hands-On MQTT Programming with Python. Work with the lightweight IoT protocol in Python

Gaston C. Hillar

MQTT is a lightweight messaging protocol for small sensors and mobile devices. This book explores the features of the latest versions of MQTT for IoT and M2M communications, how to use them with Python 3, and allow you to interact with sensors and actuators using Python.The book begins with the specific vocabulary of MQTT and its working modes, followed by installing a Mosquitto MQTT broker. You will use different utilities and diagrams to understand the most important concepts related to MQTT. You will learn to make all the necessary configuration to work with digital certificates for encrypting all data sent between the MQTT clients and the server. You will also work with the different Quality of Service levels and later analyze and compare their overheads.You will write Python 3.x code to control a vehicle with MQTT messages delivered through encrypted connections (TLS 1.2), and learn how leverage your knowledge of the MQTT protocol to build a solution based on requirements. Towards the end, you will write Python code to use the PubNub cloud-based real-time MQTT provider to monitor a surfing competition.In the end, you will have a solution that was built from scratch by analyzing the requirements and then write Python code that will run on water-proof IoT boards connected to multiple sensors in surfboards.

Microservices Development Cookbook. Design and build independently deployable modular services

Paul Osman

Microservices have become a popular choice for building distributed systems that power modern web and mobile apps. They enable you to deploy apps as a suite of independently deployable, modular, and scalable services. With over 70 practical, self-contained tutorials, the book examines common pain points during development and best practices for creating distributed microservices. Each recipe addresses a specific problem and offers a proven, best-practice solution with insights into how it works, so you can copy the code and configuration files and modify them for your own needs.You’ll start by understanding microservice architecture. Next, you'll learn to transition from a traditional monolithic app to a suite of small services that interact to ensure your client apps are running seamlessly. The book will then guide you through the patterns you can use to organize services, so you can optimize request handling and processing. In addition this, you’ll understand how to handle service-to-service interactions. As you progress, you’ll get up to speed with securing microservices and adding monitoring to debug problems. Finally, you’ll cover fault-tolerance and reliability patterns that help you use microservices to isolate failures in your apps.By the end of this book, you’ll have the skills you need to work with a team to break a large, monolithic codebase into independently deployable and scalable microservices.

Keras 2.x Projects. 9 projects demonstrating faster experimentation of neural network and deep learning applications using Keras

Giuseppe Ciaburro

Keras 2.x Projects explains how to leverage the power of Keras to build and train state-of-the-art deep learning models through a series of practical projects that look at a range of real-world application areas. To begin with, you will quickly set up a deep learning environment by installing the Keras library. Through each of the projects, you will explore and learn the advanced concepts of deep learning and will learn how to compute and run your deep learning models using the advanced offerings of Keras. You will train fully-connected multilayer networks, convolutional neural networks, recurrent neural networks, autoencoders and generative adversarial networks using real-world training datasets. The projects you will undertake are all based on real-world scenarios of all complexity levels, covering topics such as language recognition, stock volatility, energy consumption prediction, faster object classification for self-driving vehicles, and more. By the end of this book, you will be well versed with deep learning and its implementation with Keras. You will have all the knowledge you need to train your own deep learning models to solve different kinds of problems.

.NET Standard 2.0 Cookbook. Develop high quality, fast and portable applications by leveraging the power of .NET Standard Library

Fiqri Ismail

The .NET Standard is a standard that represents a set of APIs that all .NET platforms have to implement, making it easy for developers to access and use one common library for their development needs. This book begins with a quick refresher, helping you understand the mechanics of the new standard and offering insight into how it works. You’ll explore the core library concepts, such as working with collections, configurations, I/O, security, and multithreading. You’ll explore the iOS and Android libraries of Xamarin and we’ll guide you through creating a .NET Standard 2.0 library, which you’ll use with both Android and iOS applications. In the final chapters, you’ll learn the various debugging and diagnostics tools to deliver quality libraries and create a NuGet package of the .NET Standard 2.0 library. By the end of this book, you’ll be able to expand your current workflow to various .NET flavors and have the essential skills to create a .NET Standard 2.0 library from scratch to package and deliver it to the world.

Building Serverless Python Web Services with Zappa. Build and deploy serverless applications on AWS using Zappa

Abdulwahid Abdulhaque Barguzar

Serverless applications are becoming very popular these days, not just because they save developers the trouble of managing the servers, but also because they provide several other benefits such as cutting heavy costs and improving the overall performance of the application.This book will help you build serverless applications in a quick and efficient way. We begin with an introduction to AWS and the API gateway, the environment for serverless development, and Zappa. We then look at building, testing, and deploying apps in AWS with three different frameworks--Flask, Django, and Pyramid. Setting up a custom domain along with SSL certificates and configuring them with Zappa is also covered. A few advanced Zappa settings are also covered along with securing Zappa with AWS VPC.By the end of the book you will have mastered using three frameworks to build robust and cost-efficient serverless apps in Python.

Hands-On RESTful Web Services with TypeScript 3. Design and develop scalable RESTful APIs for your applications

Biharck Muniz Araújo

In the world of web development, leveraging data is the key to developing comprehensive applications, and RESTful APIs help you to achieve this systematically. This book will guide you in designing and developing web services with the power of TypeScript 3 and Node.js. You'll design REST APIs using best practices for request handling, validation, authentication, and authorization. You'll also understand how to enhance the capabilities of your APIs with ODMs, databases, models and views, as well as asynchronous callbacks. This book will guide you in securing your environment by testing your services and initiating test automation with different testing approaches. Furthermore, you'll get to grips with developing secure, testable, and more efficient code, and be able to scale and deploy TypeScript 3 and Node.js-powered RESTful APIs on cloud platforms such as the Google Cloud Platform. Finally, the book will help you explore microservices and give you an overview of what GraphQL can allow you to do.By the end of this book, you will be able to use RESTful web services to create your APIs for mobile and web apps and other platforms.

Learn Linux Shell Scripting - Fundamentals of Bash 4.4. A comprehensive guide to automating administrative tasks with the Bash shell

Sebastiaan Tammer

Shell scripts allow us to program commands in chains and have the system execute them as a scripted event, just like batch files. This book will start with an overview of Linux and Bash shell scripting, and then quickly deep dive into helping you set up your local environment, before introducing you to tools that are used to write shell scripts. The next set of chapters will focus on helping you understand Linux under the hood and what Bash provides the user. Soon, you will have embarked on your journey along the command line. You will now begin writing actual scripts instead of commands, and will be introduced to practical applications for scripts. The final set of chapters will deep dive into the more advanced topics in shell scripting. These advanced topics will take you from simple scripts to reusable, valuable programs that exist in the real world. The final chapter will leave you with some handy tips and tricks and, as regards the most frequently used commands, a cheat sheet containing the most interesting flags and options will also be provided.After completing this book, you should feel confident about starting your own shell scripting projects, no matter how simple or complex the task previously seemed. We aim to teach you how to script and what to consider, to complement the clear-cut patterns that you can use in your daily scripting challenges.

Regression Analysis with R. Design and develop statistical nodes to identify unique relationships within data at scale

Giuseppe Ciaburro

Regression analysis is a statistical process which enables prediction of relationships between variables. The predictions are based on the casual effect of one variable upon another. Regression techniques for modeling and analyzing are employed on large set of data in order to reveal hidden relationship among the variables.This book will give you a rundown explaining what regression analysis is, explaining you the process from scratch. The first few chapters give an understanding of what the different types of learning are – supervised and unsupervised, how these learnings differ from each other. We then move to covering the supervised learning in details covering the various aspects of regression analysis. The outline of chapters are arranged in a way that gives a feel of all the steps covered in a data science process – loading the training dataset, handling missing values, EDA on the dataset, transformations and feature engineering, model building, assessing the model fitting and performance, and finally making predictions on unseen datasets. Each chapter starts with explaining the theoretical concepts and once the reader gets comfortable with the theory, we move to the practical examples to support the understanding. The practical examples are illustrated using R code including the different packages in R such as R Stats, Caret and so on. Each chapter is a mix of theory and practical examples.By the end of this book you will know all the concepts and pain-points related to regression analysis, and you will be able to implement your learning in your projects.