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A Swift Kickstart, 2nd Edition
A Swift Kickstart, 2nd Edition

This is the perfect book for the experienced developer who wants to get serious about learning the Swift programming language. If you know at least one modern programming language, this book will teach you how to think and program in Swift. Swift's design is inspired by elements from object-oriented, functional, and generic programming. As the language matures and improves, this book changes to reflect the latest best practices and coding style. This second edition to the best-selling Swift introduction has been updated to the latest Swift 4 release. It's never been easier to get started with Swift as this edition supports the new iOS Swift Playgrounds along with improved support for Xcode playgrounds. This means you can code along on a Mac or an iPad. The book begins with an introduction to basic components of programming in Swift: functions, variables and constants, collections, and types from the Swift Standard Library. In the second part, create and use your own enumerations, ...
Swift Style
Swift Style

Apple's Swift programming language has finally reached stability, and developers are demanding to know how to program the language properly. Swift Style guides you through the ins and outs of Swift programming best practices. This is the first best practices book for serious, professional Swift programmers and for programmers who want to shine their skills to be hired in this demanding market. A style guide offers a consistent experience of well-crafted code that lets you focus on the code's underlying meaning, intent, and implementation. This book doesn't offer canonical answers on Swift coding style. It explores the areas of Swift where structure comes into play. Whether you're developing a personal style or a house style, there are always ways to enhance your code choices. You'll find here the ideas and principles to establish or enhance your own best style practices. Begin with simple syntactical styling. Strengthen code bracing for easy readability. Style your closures for s ...
Scalable Cloud Ops with Fugue
Scalable Cloud Ops with Fugue

Cloud computing represents the greatest shift in computing in more than a decade. But the promise of the cloud is unrealized. The cloud isn't just about shedding the physical data center - it's about shedding the data center mindset. Cloud infrastructure can be controlled via API calls. This means we can view it as a giant general-purpose computer - and program it. That's where the Fugue operating system and the Ludwig language come in. They automate the creation, operation, enforcement, and termination of infrastructure in the cloud. This definitive Fugue guide starts with a simple website and moves on to a more robust application with evolving infrastructure needs as you walk through the steps to harnessing the cloud. With Amazon Web Services, launch infrastructure quickly. Debug in design time. Automate deployment and enforcement of your cloud. Centralize your change control process and automate continuous auditing. Rest easy knowing configuration drift, unwanted changes, and inf ...
Functional Programming: A PragPub Anthology
Functional Programming: A PragPub Anthology

Functional programming is on the rise because it lets you write simpler, cleaner code, and its emphasis on immutability makes it ideal for maximizing the benefits of multiple cores and distributed solutions. So far nobody's invented the perfect functional language—each has its unique strengths. In Functional Programming: A PragPub Anthology, you'll investigate the philosophies, tools, and idioms of five different functional programming languages. See how Swift, the development language for iOS, encourages you to build highly scalable apps using functional techniques like map and reduce. Discover how Scala allows you to transition gently but deeply into functional programming without losing the benefits of the JVM, while with Lisp-based Clojure, you can plunge fully into the functional style. Learn about advanced functional concepts in Haskell, a pure functional language making powerful use of the type system with type inference and type classes. And see how functional programming ...
A Common-Sense Guide to Data Structures and Algorithms
A Common-Sense Guide to Data Structures and Algorithms

Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write code that runs faster and more efficiently, which is particularly important for today's web and mobile apps. This book takes a practical approach to data structures and algorithms, with techniques and real-world scenarios that you can use in your daily production code. Graphics and examples make these computer science concepts understandable and relevant. You can use these techniques with any language; examples in the book are in JavaScript, Python, and Ruby. Use Big O notation, the primary tool for evaluating algorithms, to measure and articulate the efficiency of your code, and modify your algorithm to make it faster. Find out how your choice of arrays, linked lists, and hash tables can dramatically affect the code you write. Use recursion to solve tricky problems and create algorithms that run exponentially faster than the alternatives. Dig into advanced data structures such a ...
Mastering Ruby Closures
Mastering Ruby Closures

Ruby developers use the Ruby language as the yardstick for expressivity, flexibility, and elegance - and a large part of this is due to blocks, lambdas, and procs. These language features make Ruby one of the most beautiful and pleasant languages to work with. Learn how to understand and craft code that will take you closer to Ruby mastery. Start with the basics of closures and then dive into blocks, as you learn about the patterns that involve blocks, and how they are used in real-world code. Then create and use procs and lambdas. Finally, build your own lazy enumerables with advanced Ruby features such as fibers and generators. Along the way, work with computer science concepts such as closures, free variables and first-class functions. Spot a closure easily. Identify the patterns where you can effectively use blocks and re-implement common standard library methods using them. Trace through how Symbol#to_proc works and find out the different ways of calling procs. This succinct gu ...
Seeking SRE
Seeking SRE

Organizations - big and small - have started to realize just how crucial system and application reliability is to their business. At the same time, they've also learned just how difficult it is to maintain that reliability while iterating at the speed demanded by the marketplace. Site Reliability Engineering (SRE) is a proven approach to this challenge. SRE is a large and rich topic to discuss. Google led the way with Site Reliability Engineering, the wildly successful O'Reilly book that described Google's creation of the discipline and the implementation that has allowed them to operate at a planetary scale. Inspired by that earlier work, this book explores a very different part of the SRE space. The more than two dozen chapters in Seeking SRE bring you into some of the important conversations going on in the SRE world right now. Listen as engineers and other leaders in the field discuss different ways of implementing SRE and SRE principles in a wide variety of settings; how SRE ...
Streaming Systems
Streaming Systems

Streaming data is a big deal in big data these days, and for good reason. Businesses crave ever more timely data, and streaming is a good way to achieve lower latency. Plus, streaming is a much easier way to tame the massive, unbounded data sets that are increasingly common today. Expanded from co-author Tyler Akidau's popular series of blog posts "Streaming 101" and "Streaming 102", this practical book shows data engineers, data scientists, and developers how to work with streaming or event-time data in a conceptual and platform-agnostic way. You'll go from "101"-level understanding of stream processing to a nuanced grasp of the what, where, when, and how of processing real-time data streams. Dive deep into topics including watermarks and windowing, as well as state and timers in the context of stream processing. Although the book uses Apache Beam code snippets to make examples concrete, it presents a general and broad explanation of streaming that's not tied to a specific frame ...
Stream Processing with Apache Flink
Stream Processing with Apache Flink

Get started with Apache Flink, the open source framework that enables you to process streaming data - such as user interactions, sensor data, and machine logs - as it arrives. With this practical guide, you'll learn how to use Apache Flink's stream processing APIs to implement, continuously run, and maintain real-world applications. Authors Fabian Hueske, one of Flink's creators, and Vasia Kalavri, a core contributor to Flink's graph processing API (Gelly), explains the fundamental concepts of parallel stream processing and shows you how streaming analytics differs from traditional batch data analysis. Software engineers, data engineers, and system administrators will learn the basics of Flink's DataStream API, including the structure and components of a common Flink streaming application.Solve real-world problems with Apache Flink's DataStream API;Set up an environment for developing stream processing applications for Flink;Design streaming applications an ...
Natural Language Processing with PyTorch
Natural Language Processing with PyTorch

Natural Language Processing (NLP) offers unbounded opportunities for solving interesting problems in artificial intelligence, making it the latest frontier for developing intelligent, deep learning-based applications. If you're a developer or researcher ready to dive deeper into this rapidly growing area of artificial intelligence, this practical book shows you how to use the PyTorch deep learning framework to implement recently discovered NLP techniques. To get started, all you need is a machine learning background and experience programming with Python. Authors Delip Rao and Goku Mohandas provide you with a solid grounding in PyTorch, and deep learning algorithms, for building applications involving semantic representation of text. Each chapter includes several code examples and illustrations.Get extensive introductions to NLP, deep learning, and PyTorch;Understand traditional NLP methods, including NLTK, SpaCy, and gensim;Explore embeddings: high quality ...
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