Architecture Patterns with PythonAs Python continues to grow in popularity, projects are becoming larger and more complex. Many Python developers are taking an interest in high-level software design patterns such as hexagonal/clean architecture, event-driven architecture, and the strategic patterns prescribed by domain-driven design (DDD). But translating those patterns into Python isn't always straightforward.
With this hands-on guide, Harry Percival and Bob Gregory from MADE.com introduce proven architectural design patterns to help Python developers manage application complexity - and get the most value out of their test suites.
Each pattern is illustrated with concrete examples in beautiful, idiomatic Python, avoiding some of the verbosity of Java and C# syntax. Patterns include: Dependency inversion and its links to ports and adapters (hexagonal/clean architecture); Domain-driven design's distinction between Entities, Value Objects, and Aggregates; Repository and Unit of Work patterns for persistent storag ...
Practical MATLAB Modeling with SimulinkEmploy the essential and hands-on tools and functions of MATLAB's ordinary differential equation (ODE) and partial differential equation (PDE) packages, which are explained and demonstrated via interactive examples and case studies. This book contains dozens of simulations and solved problems via m-files/scripts and Simulink models which help you to learn programming and modeling of more difficult, complex problems that involve the use of ODEs and PDEs.
You'll become efficient with many of the built-in tools and functions of MATLAB/Simulink while solving more complex engineering and scientific computing problems that require and use differential equations. Practical MATLAB Modeling with Simulink explains various practical issues of programming and modelling.
After reading and using this book, you'll be proficient at using MATLAB and applying the source code from the book's examples as templates for your own projects in data science or engineering. ...
Spring Boot Persistence Best PracticesThis book is a collection of developer code recipes and best practices for persisting data using Spring, particularly Spring Boot. The book is structured around practical recipes, where each recipe discusses a performance case or performance-related case, and almost every recipe has one or more applications. Mainly, when we try to accomplish something (e.g., read some data from the database), there are several approaches to do it, and, in order to choose the best way, you have to know the implied trades-off from a performance perspective. You'll see that in the end, all these penalties slow down the application. Besides presenting the arguments that favor a certain choice, the application is written in Spring Boot style which is quite different than plain Hibernate.
Persistence is an important set of techniques and technologies for accessing and using data, and this book demonstrates that data is mobile regardless of specific applications and contexts. In Java development, persisten ...
Fundamentals of C++ ProgrammingThis book does not attempt to cover all the facets of the C++ programming language. Experienced programmers should look elsewhere for books that cover C++ in much more detail. The focus here is on introducing programming techniques and developing good habits. To that end, our approach avoids some of the more esoteric features of C++ and concentrates on the programming basics that transfer directly to other imperative programming languages such as Java, C#, and Python. We stick with the basics and explore more advanced features of C++ only when necessary to handle the problem at hand. ...
Fundamentals of Python ProgrammingThis book does not attempt to cover all the facets of the Python programming language. Experienced programmers should look elsewhere for books that cover Python in much more detail. The focus here is on introducing programming techniques and developing good habits. To that end, our approach avoids some of the more esoteric features of Python and concentrates on the programming basics that transfer directly to other imperative programming languages such as Java, C#, and C++ . We stick with the basics and explore more advanced features of Python only when necessary to handle the problem at hand. ...
React and React Native, 3rd EditionReact and React Native, Facebook's innovative User Interface (UI) libraries, are designed to help you build robust cross-platform web and mobile applications. This updated third edition is improved and updated to cover the latest version of React. The book particularly focuses on the latest developments in the React ecosystem, such as modern Hook implementations, code splitting using lazy components and Suspense, user interface framework components using Material-UI, and Apollo. In terms of React Native, the book has been updated to version 0.62 and demonstrates how to apply native UI components for your existing mobile apps using NativeBase.
You will begin by learning about the essential building blocks of React components. Next, you'll progress to working with higher-level functionalities in application development, before putting this knowledge to use by developing user interface components for the web and for native platforms. In the concluding chapters, you'll learn how to brin ...
Succeeding with AICompanies small and large are initiating AI projects, investing vast sums of money on software, developers, and data scientists. Too often, these AI projects focus on technology at the expense of actionable or tangible business results, resulting in scattershot results and wasted investment. Succeeding with AI sets out a blueprint for AI projects to ensure they are predictable, successful, and profitable. It's filled with practical techniques for running data science programs that ensure they're cost effective and focused on the right business goals.
Succeeding with AI requires talent, tools, and money. So why do many well-funded, state-of-the-art projects fail to deliver meaningful business value? Because talent, tools, and money aren't enough: You also need to know how to ask the right questions. In this unique book, AI consultant Veljko Krunic reveals a tested process to start AI projects right, so you'll get the results you want.
Succeeding with AI sets out a framework for pl ...
Mastering Large Datasets with PythonModern data science solutions need to be clean, easy to read, and scalable. In Mastering Large Datasets with Python, author J.T. Wolohan teaches you how to take a small project and scale it up using a functionally influenced approach to Python coding. You'll explore methods and built-in Python tools that lend themselves to clarity and scalability, like the high-performing parallelism method, as well as distributed technologies that allow for high data throughput. The abundant hands-on exercises in this practical tutorial will lock in these essential skills for any large-scale data science project.
Programming techniques that work well on laptop-sized data can slow to a crawl - or fail altogether - when applied to massive files or distributed datasets. By mastering the powerful map and reduce paradigm, along with the Python-based tools that support it, you can write data-centric applications that scale efficiently without requiring codebase rewrites as your requirements change.
Ma ...
Startups in ActionThe growing pains of a startup's initial year in business require a keen awareness of uncertainties and a willingness to adapt in order to survive. Today's new founders greatly benefit from taking a behind-the-scenes look at successful companies such as Etsy, HotelTonight, Fiverr, and more in regards to how they overcame the challenges of their first year. Startups in Action is your curated source for critical insights and inspiration from those who have been there before.
This book documents the month-to-month journeys of these companies in their first year, zeroing in on key decisions that helped them recover from missteps, and adapt to complications, to eventually grow and succeed. Were the founders full-time from the beginning? How long did it take them to build a working prototype? How many end-users did they have in the first year? The answers to these questions are of interest to those who are just starting out and want to learn by example. Collected from interviews with the ...
IoT Machine Learning Applications in Telecom, Energy, and AgricultureApply machine learning using the Internet of Things (IoT) in the agriculture, telecom, and energy domains with case studies. This book begins by covering how to set up the software and hardware components including the various sensors to implement the case studies in Python.
The case study section starts with an examination of call drop with IoT in the telecoms industry, followed by a case study on energy audit and predictive maintenance for an industrial machine, and finally covers techniques to predict cash crop failure in agribusiness. The last section covers pitfalls to avoid while implementing machine learning and IoT in these domains.
After reading this book, you will know how IoT and machine learning are used in the example domains and have practical case studies to use and extend. You will be able to create enterprise-scale applications using Raspberry Pi 3 B+ and Arduino Mega 2560 with Python. ...