Packed with practical recipes written and tested with Python 3.3, this unique cookbook is for experienced Python programmers who want to focus on modern tools and idioms.Inside, you’ll find complete recipes for more than a dozen topics, covering the core Python language as well as tasks common to a wide variety of application domains. Each recipe contains code samples you can use in your projects right away, along with a discussion about how and why the solution works.Topics include:Data Structures and AlgorithmsStrings and TextNumbers, Dates, and TimesIterators and GeneratorsFiles and I/OData Encoding and ProcessingFunctionsClasses and ObjectsMetaprogrammingModules and PackagesNetwork and Web ProgrammingConcurrencyUtility Scripting and System AdministrationTesting, Debugging, and ExceptionsC Extensions

    This one's a keeper." --Robert C. Martin "If you want to be an expert in the state of the art in TDD, you need to understand the ideas in this book."--Michael Feathers Test-Driven Development (TDD) is now an established technique for delivering better software faster. TDD is based on a simple idea: Write tests for your code before you write the code itself. However, this simple idea takes skill and judgment to do well. Now there's a practical guide to TDD that takes you beyond the basic concepts. Drawing on a decade of experience building real-world systems, two TDD pioneers show how to let tests guide your development and "grow" software that is coherent, reliable, and maintainable. Steve Freeman and Nat Pryce describe the processes they use, the design principles they strive to achieve, and some of the tools that help them get the job done. Through an extended worked example, you'll learn how TDD works at multiple levels, using tests to drive the features and the object-oriented structure of the code, and using Mock Objects to discover and then describe relationships between objects. Along the way, the book systematically addresses challenges that development teams encounter with TDD--from integrating TDD into your processes to testing your most difficult features. Coverage includes - Implementing TDD effectively: getting started, and maintaining your momentum throughout the project - Creating cleaner, more expressive, more sustainable code - Using tests to stay relentlessly focused on sustaining quality - Understanding how TDD, Mock Objects, and Object-Oriented Design come together in the context of a real software development project - Using Mock Objects to guide object-oriented designs - Succeeding where TDD is difficult: managing complex test data, and testing persistence and concurrency

    Multicore machines and 64-bit operating systems are now standard even for casual users, and Java itself has introduced new features to manage applications. The base JVM has kept pace with those developments and offers a very different performance profile in its current versions. By guiding you through this changing landscape, Java Performance: The Definitive Guide helps you gain the best performance from your Java applications.You’ll explore JVM features that traditionally affected performance—including the just-in-time compiler, garbage collection, and language features—before diving in to aspects of Java 7 and 8 designed for maximum performance in today's applications. You’ll learn features such as the G1 garbage collector to maximize your application’s throughput without causing it to pause, and the Java Flight Recorder, which enables you to see application performance details without the need for separate, specialized profiling tools.Whether you’re new to Java and need to understand the basics of tuning the JVM, or a seasoned developer looking to eek out that last 10% of application performance, this is the book you want.

    Who are these people, what motivates them, and why should you care?Consider these facts: Everything around us is turning into computers. Your typewriter is gone, replaced by a computer. Your phone has turned into a computer. So has your camera. Soon your TV will. Your car was not only designed on computers, but has more processing power in it than a room-sized mainframe did in 1970. Letters, encyclopedias, newspapers, and even your local store are being replaced by the Internet.Hackers & Painters: Big Ideas from the Computer Age, by Paul Graham, explains this world and the motivations of the people who occupy it. In clear, thoughtful prose that draws on illuminating historical examples, Graham takes readers on an unflinching exploration into what he calls “an intellectual Wild West.”The ideas discussed in this book will have a powerful and lasting impact on how we think, how we work, how we develop technology, and how we live. Topics include the importance of beauty in software design, how to make wealth, heresy and free speech, the programming language renaissance, the open-source movement, digital design, internet startups, and more.

    Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.With this handbook, you’ll learn how to use: * IPython and Jupyter: provide computational environments for data scientists using Python * NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python * Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python * Matplotlib: includes capabilities for a flexible range of data visualizations in Python * Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

    I'm going to share that mindset with you — along with hundreds of actionable techniques and proven habits — so you can shortcut those years.Introducing The Effective Engineer — the only book designed specifically for today's software engineers, based on extensive interviews with engineering leaders at top tech companies, and packed with hundreds of techniques to accelerate your career.For two years, I embarked on a quest seeking an answer to one question:How do the most effective engineers make their efforts, their teams, and their careers more successful?I interviewed and collected stories from engineering VPs, directors, managers, and other leaders at today's top software companies: established, household names like Google, Facebook, Twitter, and LinkedIn; rapidly growing mid-sized companies like Dropbox, Square, Box, Airbnb, and Etsy; and startups like Reddit, Stripe, Instagram, and Lyft.These leaders shared stories about the most valuable insights they've learned and the most common and costly mistakes that they've seen engineers — sometimes themselves — make.This is just a small sampling of the hard questions I posed to them:- What engineering qualities correlate with future success?- What have you done that has paid off the highest returns?- What separates the most effective engineers you've worked with from everyone else?- What's the most valuable lesson your team has learned in the past year?- What advice do you give to new engineers on your team? Everyone's story is different, but many of the lessons share common themes.You'll get to hear stories like:- How did Instagram's team of 5 engineers build and support a service that grew to over 40 million users by the time the company was acquired?- How and why did Quora deploy code to production 40 to 50 times per day?- How did the team behind Google Docs become the fastest acquisition to rewrite its software to run on Google's infrastructure?- How does Etsy use continuous experimentation to design features that are guaranteed to increase revenue at launch?- How did Facebook's small infrastructure team effectively operate thousands of database servers?- How did Dropbox go from barely hiring any new engineers to nearly tripling its team size year-over-year? What's more, I've distilled their stories into actionable habits and lessons that you can follow step-by-step to make your career and your team more successful.The skills used by effective engineers are all learnable.And I'll teach them to you. With The Effective Engineer, I'll teach you a unifying framework called leverage — the value produced per unit of time invested — that you can use to identify the activities that produce disproportionate results.Here's a sneak peek at some of the lessons you'll learn. You'll learn how to:- Prioritize the right projects and tasks to increase your impact.- Earn more leeway from your peers and managers on your projects.- Spend less time maintaining and fixing software and more time building and shipping new features.- Produce more accurate software estimates.- Validate your ideas cheaply to reduce wasted work.- Navigate organizational and people-related bottlenecks.- Find the appropriate level of code reviews, testing, abstraction, and technical debt to balance speed and quality.- Shorten your debugging workflow to increase your iteration speed.

    You’ll learn everything from the basics of database integration and the use of JavaScript to browser-automation tools like Selenium, and advanced topics such as NoSQL, Web Sockets, and async programming.Ideal for beginners, this book teaches a development methodology that leads to peace of mind, cleaner code, and better web apps.

    This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    Full of insights, arguments and philosophical perspectives, the book covers an amazing array of topics. Beginning in antiquity with Democritus, it progresses through logic and set theory, computability and complexity theory, quantum computing, cryptography, the information content of quantum states and the interpretation of quantum mechanics. There are also extended discussions about time travel, Newcomb's Paradox, the anthropic principle and the views of Roger Penrose. Aaronson's informal style makes this fascinating book accessible to readers with scientific backgrounds, as well as students and researchers working in physics, computer science, mathematics and philosophy.

    This book helps you learn the fundamentals of Clojure with examples relating it to the languages you know already, in the domains and topics you work with every day. See how this JVM language can help eliminate unnecessary complexity from your programming practice and open up new options for solving the most challenging problems. Clojure Programming demonstrates the language's flexibility by showing how it can be used for common tasks like web programming and working with databases, up through more demanding applications that require safe, effective concurrency and parallelism, data and statistical analysis, and more. This in-depth look helps tie together the full Clojure development experience, from how to organize your project and an introduction to Clojure build tooling, to a tutorial on how to make the most of Clojure’s REPL during development, and how to deploy your finished application in a cloud environment.Learn how to use Clojure without losing your investment in the Java platform Understand the advantages of Clojure as an efficient Lisp for the JVM See how Clojure is used today in several practical domains Discover how Clojure eliminates the need for many verbose and complicated design patterns Deploy large web applications across tens or hundreds of cloud nodes with Clojure

    This book will help those familiar the command line and basic shell scripting start using Ansible to provision and manage anywhere from one to thousands of servers.The book begins with fundamentals, like installing Ansible, setting up a basic inventory file, and basic concepts, then guides you through Ansible's many uses, including ad-hoc commands, basic and advanced playbooks, application deployments, custom modules, and special cases like running ansible in 'pull' mode when you have thousands of servers to manage (or more). Everything is explained with pertinent real-world examples, often using Vagrant-managed virtual machines.

    For years, Joel Spolsky has done exactly this at www.joelonsoftware.com. Now, for the first time, you can own a collection of the most important essays from his site in one book, with exclusive commentary and new insights from joel.

    "Machine learning," the process of automating tasks once considered the domain of highly-trained analysts and mathematicians, is the key to efficiently extracting useful information from this sea of raw data. Machine Learning in Action is a unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. In it, the author uses the flexible Python programming language to show how to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization and simplification.

    Uniquely organized around concepts and use cases, this updated fifth edition features a reorganized section on concurrency, threading, and parallel programming—including in-depth coverage of C# 5.0’s new asynchronous functions.Shaped by more than 20 expert reviewers, including Microsoft’s Eric Lippert, Stephen Toub, Chris Burrows, and Jon Skeet, this book has all you need to stay on track with C# 5.0. It’s widely known as the definitive reference on the language.Get up to speed on C# language basics, including syntax, types, and variablesExplore advanced topics such as unsafe code and type varianceDig deep into LINQ via three chapters dedicated to the topicLearn about code contracts, dynamic programming, and parallel programmingWork with .NET features, including reflection, assemblies, memory management, security, I/O, XML, collections, networking, and native interoperability"C# 5.0 in a Nutshell is one of the few books I keep on my desk as a quick reference." —Scott Guthrie, Microsoft"Whether you’re a novice programmer or an expert who wants to improve your knowledge of modern asynchronous programming techniques, this book has the information you need to get the job done in C#." —Eric Lippert, Microsoft