The author's take on the essence of Java as a new programming language and the thorough introduction to Java's features make this a worthwhile tutorial. Thinking in Java begins a little esoterically, with the author's reflections on why Java is new and better. (This book's choice of font for chapter headings is remarkably hard on the eyes.) The author outlines his thoughts on why Java will make you a better programmer, without all the complexity. The book is better when he presents actual language features. There's a tutorial to basic Java types, keywords, and operators. The guide includes extensive source code that is sometimes daunting (as with the author's sample code for all the Java operators in one listing.) As such, this text will be most useful for the experienced developer. The text then moves on to class design issues, when to use inheritance and composition, and related topics of information hiding and polymorphism. (The treatment of inner classes and scoping will likely seem a bit overdone for most readers.) The chapter on Java collection classes for both Java Developer's Kit (JDK) 1.1 and the new classes, such as sets, lists, and maps, are much better. There's material in this chapter that you are unlikely to find anywhere else. Chapters on exception handling and programming with type information are also worthwhile, as are the chapters on the new Swing interface classes and network programming. Although it adopts somewhat of a mixed-bag approach, Thinking in Java contains some excellent material for the object-oriented developer who wants to see what all the fuss is about with Java.

    The first edition of this book, Programming Perl, hit the shelves in 1990, and was quickly adopted as the undisputed bible of the language. Since then, Perl has grown with the times, and so has this book.Programming Perl is not just a book about Perl. It is also a unique introduction to the language and its culture, as one might expect only from its authors. Larry Wall is the inventor of Perl, and provides a unique perspective on the evolution of Perl and its future direction. Tom Christiansen was one of the first champions of the language, and lives and breathes the complexities of Perl internals as few other mortals do. Jon Orwant is the editor of The Perl Journal, which has brought together the Perl community as a common forum for new developments in Perl.Any Perl book can show the syntax of Perl's functions, but only this one is a comprehensive guide to all the nooks and crannies of the language. Any Perl book can explain typeglobs, pseudohashes, and closures, but only this one shows how they really work. Any Perl book can say that my is faster than local, but only this one explains why. Any Perl book can have a title, but only this book is affectionately known by all Perl programmers as "The Camel."This third edition of Programming Perl has been expanded to cover version 5.6 of this maturing language. New topics include threading, the compiler, Unicode, and other new features that have been added since the previous edition.

    There are currently a significant number of books on creating, documenting, and implementing software architecture, but precious few resources have addressed how to build a software architecture that aligns with a customer's overall business goals. In this new book, Luke Hohmann borrows from his extensive experience managing successful enterprise software projects to provide practical wisdom on creating and sustaining winning software solutions. This book helps technologists grasp the business ramifications of their decisions, and provides business-oriented software professionals (e.g. sales people and marketers) with better knowledge of how robust software can be built and maintained.

    However, data structures for these languages do not always translate well to functional languages such as Standard ML, Haskell, or Scheme. This book describes data structures from the point of view of functional languages, with examples, and presents design techniques that allow programmers to develop their own functional data structures. The author includes both classical data structures, such as red-black trees and binomial queues, and a host of new data structures developed exclusively for functional languages. All source code is given in Standard ML and Haskell, and most of the programs are easily adaptable to other functional languages. This handy reference for professional programmers working with functional languages can also be used as a tutorial or for self-study.

    As a modern application developer you need to understand the emerging field of data management, both RDBMS and NoSQL. Seven Databases in Seven Weeks takes you on a tour of some of the hottest open source databases today. In the tradition of Bruce A. Tate's Seven Languages in Seven Weeks, this book goes beyond your basic tutorial to explore the essential concepts at the core each technology. Redis, Neo4J, CouchDB, MongoDB, HBase, Riak and Postgres. With each database, you'll tackle a real-world data problem that highlights the concepts and features that make it shine. You'll explore the five data models employed by these databases-relational, key/value, columnar, document and graph-and which kinds of problems are best suited to each. You'll learn how MongoDB and CouchDB are strikingly different, and discover the Dynamo heritage at the heart of Riak. Make your applications faster with Redis and more connected with Neo4J. Use MapReduce to solve Big Data problems. Build clusters of servers using scalable services like Amazon's Elastic Compute Cloud (EC2). Discover the CAP theorem and its implications for your distributed data. Understand the tradeoffs between consistency and availability, and when you can use them to your advantage. Use multiple databases in concert to create a platform that's more than the sum of its parts, or find one that meets all your needs at once.Seven Databases in Seven Weeks will take you on a deep dive into each of the databases, their strengths and weaknesses, and how to choose the ones that fit your needs.What You Need: To get the most of of this book you'll have to follow along, and that means you'll need a *nix shell (Mac OSX or Linux preferred, Windows users will need Cygwin), and Java 6 (or greater) and Ruby 1.8.7 (or greater). Each chapter will list the downloads required for that database.

    Distinct from the details of implementation, algorithm, and data representation, an architecture holds the key to achieving system quality, is a reusable asset that can be applied to subsequent systems, and is crucial to a software organization's business strategy.Drawing on their own extensive experience, the authors cover the essential technical topics for designing, specifying, and validating a system. They also emphasize the importance of the business context in which large systems are designed. Their aim is to present software architecture in a real-world setting, reflecting both the opportunities and constraints that companies encounter. To that end, case studies that describe successful architectures illustrate key points of both technical and organizational discussions.Topics new to this edition include: Architecture design and analysis, including the Architecture Tradeoff Analysis Method (ATAM) Capturing quality requirements and achieving them through quality scenarios and tactics Using architecture reconstruction to recover undocumented architectures Documenting architectures using the Unified Modeling Language (UML) New case studies, including Web-based examples and a wireless Enterprise JavaBeans™ (EJB) system designed to support wearable computers The financial aspects of architectures, including use of the Cost Benefit Analysis Method (CBAM) to make decisions If you design, develop, or manage the building of large software systems (or plan to do so), or if you are interested in acquiring such systems for your corporation or government agency, use Software Architecture in Practice, Second Edition, to get up to speed on the current state of software architecture.

    And I mean all the time. Every day there’s a new cloud-based dating app; a new cloud-based gizmo for your house; a new cloud-based game; or a thousand other new things—all in the cloud.The cloud is everywhere! Everything is in the cloud! What does it mean! Let’s slow down. Take a deep breath. That’s good. Take another. Excellent. This book teaches you all about the cloud. I’ll let you in on a little secret: the cloud is not that hard to understand. It’s not. It’s just that nobody has taken the time to explain to you what the cloud is. They haven’t, have they?Deep down I think this is because they don’t understand the cloud either, but I do. I’ve been a programmer and writer for over 30 years. I’ve been in cloud computing since the very start, and I’m here to help you on your journey to understand the cloud. Consider me your tour guide. I’ll be with you every step of the way, but not in a creepy way.I take my time with this book. I go slow and easy, so you can build up an intuition about what the cloud really is, one idea at a time. When you finish reading, you’ll understand the cloud. When you hear someone say some new cool thing is in the cloud, you’ll understand exactly what they mean. That’s a promise. How do I deliver on that promise? I use lots and lots of pictures. I use lots and lots of examples. We’ll reveal the secret inner-workings of AWS, Netflix, Facebook Messenger, Amazon Kindle, Apple iCloud, Google Maps, Nest and cloud DVRs. You’ll learn by seeing and understanding; no matter if you're a complete beginner, someone who knows a little and wants to learn more, or a programmer looking to change their career to the cloud.The cloud is the future. You don't want to miss out on the future, do you? Read this book and we'll discover it together.I’m excited. This will be fun. Let’s get started!

    This book explains the technical aspects of hacking, including stack based overflows, heap based overflows, string exploits, return-into-libc, shellcode, and cryptographic attacks on 802.11b.

    With this practical guide, you’ll learn what it takes to design usable REST APIs that evolve over time. By focusing on solutions that cross a variety of domains, this book shows you how to create powerful and secure applications, using the tools designed for the world’s most successful distributed computing system: the World Wide Web.You’ll explore the concepts behind REST, learn different strategies for creating hypermedia-based APIs, and then put everything together with a step-by-step guide to designing a RESTful Web API.Examine API design strategies, including the collection pattern and pure hypermediaUnderstand how hypermedia ties representations together into a coherent APIDiscover how XMDP and ALPS profile formats can help you meet the Web API "semantic challenge"Learn close to two-dozen standardized hypermedia data formatsApply best practices for using HTTP in API implementationsCreate Web APIs with the JSON-LD standard and other the Linked Data approachesUnderstand the CoAP protocol for using REST in embedded systems

    Discover the “hidden gold” in Python’s standard library and start writing clean and Pythonic code today. Who Should Read This Book: If you’re wondering which lesser known parts in Python you should know about, you’ll get a roadmap with this book. Discover cool (yet practical!) Python tricks and blow your coworkers’ minds in your next code review. If you’ve got experience with legacy versions of Python, the book will get you up to speed with modern patterns and features introduced in Python 3 and backported to Python 2. If you’ve worked with other programming languages and you want to get up to speed with Python, you’ll pick up the idioms and practical tips you need to become a confident and effective Pythonista. If you want to make Python your own and learn how to write clean and Pythonic code, you’ll discover best practices and little-known tricks to round out your knowledge. What Python Developers Say About The Book: "I kept thinking that I wished I had access to a book like this when I started learning Python many years ago." — Mariatta Wijaya, Python Core Developer"This book makes you write better Python code!" — Bob Belderbos, Software Developer at Oracle"Far from being just a shallow collection of snippets, this book will leave the attentive reader with a deeper understanding of the inner workings of Python as well as an appreciation for its beauty." — Ben Felder, Pythonista"It's like having a seasoned tutor explaining, well, tricks!" — Daniel Meyer, Sr. Desktop Administrator at Tesla Inc.

    It's the expertise you need when your start-up gets an unexpected spike in web traffic, or when a new feature causes your mature application to fail. In this collection of essays and interviews, web veterans such as Theo Schlossnagle, Baron Schwartz, and Alistair Croll offer insights into this evolving field. You'll learn stories from the trenches--from builders of some of the biggest sites on the Web--on what's necessary to help a site thrive.Learn the skills needed in web operations, and why they're gained through experience rather than schoolingUnderstand why it's important to gather metrics from both your application and infrastructureConsider common approaches to database architectures and the pitfalls that come with increasing scaleLearn how to handle the human side of outages and degradationsFind out how one company avoided disaster after a huge traffic delugeDiscover what went wrong after a problem occurs, and how to prevent it from happening againContributors include:John AllspawHeather ChampMichael ChristianRichard CookAlistair CrollPatrick DeboisEric FlorenzanoPaul HammondJustin HuffAdam JacobJacob LoomisMatt MassieBrian MoonAnoop NagwaniSean PowerEric RiesTheo SchlossnagleBaron SchwartzAndrew Shafer

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    The study of type systems--and of programming languages from a type-theoretic perspective--has important applications in software engineering, language design, high-performance compilers, and security.This text provides a comprehensive introduction both to type systems in computer science and to the basic theory of programming languages. The approach is pragmatic and operational; each new concept is motivated by programming examples and the more theoretical sections are driven by the needs of implementations. Each chapter is accompanied by numerous exercises and solutions, as well as a running implementation, available via the Web. Dependencies between chapters are explicitly identified, allowing readers to choose a variety of paths through the material.The core topics include the untyped lambda-calculus, simple type systems, type reconstruction, universal and existential polymorphism, subtyping, bounded quantification, recursive types, kinds, and type operators. Extended case studies develop a variety of approaches to modeling the features of object-oriented languages.

    And it’s still short, profusely illustrated…and best of all–fun to read.If you’ve read it before, you’ll rediscover what made Don’t Make Me Think so essential to Web designers and developers around the world. If you’ve never read it, you’ll see why so many people have said it should be required reading for anyone working on Web sites.

    It is designed to be used in conjunction with code provided on an online repository. The book complements and explains the raw code in a way that is accessible to anyone who regularly practices the art of programming. The book can also be used in advanced programming courses in computer science and software engineering programs.The book contains 33 different styles for writing the term frequency task. The styles are grouped into nine categories: historical, basic, function composition, objects and object interactions, reflection and metaprogramming, adversity, data-centric, concurrency, and interactivity. The author verbalizes the constraints in each style and explains the example programs. Each chapter first presents the constraints of the style, next shows an example program, and then gives a detailed explanation of the code. Most chapters also have sections focusing on the use of the style in systems design as well as sections describing the historical context in which the programming style emerged.