Programowanie
JSF 2.0 Cookbook: LITE. Converters, Validators, and Security
Anghel Leonard
Practical, hands-on “Cookbook” approach. Full of clear, step-by-step instructions that you can apply straight away. Written for people who want to get maximum results without lots of background and theory reading. JSF developers who want to work with validators, converters and security features of JSF. You don’t need any prior knowledge of JSF to use these recipes.
Ivo Balbaert, Adrian Salceanu
Julia offers the high productivity and ease of use of Python and R with the lightning-fast speed of C++. There’s never been a better time to learn this language, thanks to its large-scale adoption across a wide range of domains, including fintech, biotech and artificial intelligence (AI).You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. This Learning Path walks you through two important collection types: arrays and matrices. You’ll be taken through how type conversions and promotions work, and in further chapters you'll study how Julia interacts with operating systems and other languages. You’ll also learn about the use of macros, what makes Julia suitable for numerical and scientific computing, and how to run external programs.Once you have grasped the basics, this Learning Path goes on to how to analyze the Iris dataset using DataFrames. While building a web scraper and a web app, you’ll explore the use of functions, methods, and multiple dispatches. In the final chapters, you'll delve into machine learning, where you'll build a book recommender system.By the end of this Learning Path, you’ll be well versed with Julia and have the skills you need to leverage its high speed and efficiency for your applications.This Learning Path includes content from the following Packt products:• Julia 1.0 Programming - Second Edition by Ivo Balbaert• Julia Programming Projects by Adrian Salceanu
Bogumił Kamiński, Przemysław Szufel
Julia, with its dynamic nature and high-performance, provides comparatively minimal time for the development of computational models with easy-to-maintain computational code. This book will be your solution-based guide as it will take you through different programming aspects with Julia.Starting with the new features of Julia 1.0, each recipe addresses a specific problem, providing a solution and explaining how it works. You will work with the powerful Julia tools and data structures along with the most popular Julia packages. You will learn to create vectors, handle variables, and work with functions. You will be introduced to various recipes for numerical computing, distributed computing, and achieving high performance. You will see how to optimize data science programs with parallel computing and memory allocation. We will look into more advanced concepts such as metaprogramming and functional programming. Finally, you will learn how to tackle issues while working with databases and data processing, and will learn about on data science problems, data modeling, data analysis, data manipulation, parallel processing, and cloud computing with Julia.By the end of the book, you will have acquired the skills to work more effectively with your data
Ivo Balbaert
The release of Julia 1.0 is now ready to change the technical world by combining the high productivity and ease of use of Python and R with the lightning-fast speed of C++. Julia 1.0 programming gives you a head start in tackling your numerical and data problems. You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. With the help of practical examples, this book walks you through two important collection types: arrays and matrices. In addition to this, you will be taken through how type conversions and promotions work. In the course of the book, you will be introduced to the homo-iconicity and metaprogramming concepts in Julia. You will understand how Julia provides different ways to interact with an operating system, as well as other languages, and then you'll discover what macros are. Once you have grasped the basics, you’ll study what makes Julia suitable for numerical and scientific computing, and learn about the features provided by Julia. By the end of this book, you will also have learned how to run external programs. This book covers all you need to know about Julia in order to leverage its high speed and efficiency for your applications.
Julia Cookbook. Over 40 recipes to get you up and running with programming using Julia
Jalem Raj Rohit
Want to handle everything that Julia can throw at you and get the most of it every day? This practical guide to programming with Julia for performing numerical computation will make you more productive and able work with data more efficiently. The book starts with the main features of Julia to help you quickly refresh your knowledge of functions, modules, and arrays. We’ll also show you how to utilize the Julia language to identify, retrieve, and transform data sets so you can perform data analysis and data manipulation.Later on, you’ll see how to optimize data science programs with parallel computing and memory allocation. You’ll get familiar with the concepts of package development and networking to solve numerical problems using the Julia platform.This book includes recipes on identifying and classifying data science problems, data modelling, data analysis, data manipulation, meta-programming, multidimensional arrays, and parallel computing. By the end of the book, you will acquire the skills to work more effectively with your data.
Julia High Performance. Design and develop high performing programs with Julia
Avik Sengupta
Julia is a high performance, high-level dynamic language designed to address the requirements of high-level numerical and scientific computing. Julia brings solutions to the complexities faced by developers while developing elegant and high performing code. Julia High Performance will take you on a journey to understand the performance characteristics of your Julia programs, and enables you to utilize the promise of near C levels of performance in Julia.You will learn to analyze and measure the performance of Julia code, understand how to avoid bottlenecks, and design your program for the highest possible performance. In this book, you will also see how Julia uses type information to achieve its performance goals, and how to use multuple dispatch to help the compiler to emit high performance machine code. Numbers and their arrays are obviously the key structures in scientific computing – you will see how Julia’s design makes them fast. The last chapter will give you a taste of Julia’s distributed computing capabilities.
Julia: High Performance Programming. Build powerful and fast systems with Julia
Ivo Balbaert, M E Sherrington, Avik Sengupta
In this learning path, you will learn to use an interesting and dynamic programming language—Julia! You will get a chance to tackle your numerical and data problems with Julia. You’ll begin the journey by setting up a running Julia platform before exploring its various built-in types. We’ll then move on to the various functions and constructs in Julia. We’ll walk through the two important collection types—arrays and matrices in Julia.You will dive into how Julia uses type information to achieve its performance goals, and how to use multiple dispatch to help the compiler emit high performance machine code. You will see how Julia’s design makes code fast, and you’ll see its distributed computing capabilities.By the end of this learning path, you will see how data works using simple statistics and analytics, and you’ll discover its high and dynamic performance—its real strength, which makes it particularly useful in highly intensive computing tasks. This learning path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:? Getting Started with Julia by Ivo Balvaert? Julia High Performance by Avik Sengupta? Mastering Julia by Malcolm Sherrington
Christopher Pecoraro , Vincenzo Gambino
Jamstack (JavaScript, API, and Markup) enables web developers to create and publish modern and maintainable websites and web apps focused on speed, security, and accessibility by using tools such as Gatsby, Sanity, and Netlify. Developers working with Jamstack will be able to put their knowledge to good use with this practical guide to static site generation and content management. This Jamstack book takes a hands-on approach to implementation and related methodologies that will have you up and running with modern web development in no time.Complete with step-by-step explanations of essential concepts, practical examples, and self-assessment questions, you'll begin by building an event and venue schema structure, and then expand the functionality, exploring all that the Jamstack has to offer. You’ll learn how an example Jamstack is built, build structured content using Sanity to create a schema, use GraphQL to expose the content, and employ Gatsby to build an event website using page and template components and Tailwind CSS Framework. Lastly, you’ll deploy the website to both, a Netlify server and the Microsoft Static Web Apps Service, and interact with it using Amazon Alexa.By the end of this book, you'll have gained the knowledge and skills you need to install, configure, build, extend, and deploy a simple events website using Jamstack.