This makes the book random-access: Items are easy to browse and study in whatever order the reader needs. I will be recommending "Effective Python" to students as an admirably compact source of mainstream advice on a very broad range of topics for the intermediate Python programmer. " Brandon Rhodes, software engineer at Dropbox and chair of PyCon 2016-2017" It s easy to start coding with Python, which is why the language is so popular. However, Python s unique strengths, charms, and expressiveness can be hard to grasp, and there are hidden pitfalls that can easily trip you up. " Effective Python " will help you master a truly Pythonic approach to programming, harnessing Python s full power to write exceptionally robust and well-performing code. Using the concise, scenario-driven style pioneered in Scott Meyers best-selling "Effective C++, " Brett Slatkin brings together 59 Python best practices, tips, and shortcuts, and explains them with realistic code examples. Drawing on years of experience building Python infrastructure at Google, Slatkin uncovers little-known quirks and idioms that powerfully impact code behavior and performance. You ll learn the best way to accomplish key tasks, so you can write code that s easier to understand, maintain, and improve. Key features includeActionable guidelines for all major areas of Python 3.x and 2.x development, with detailed explanations and examples Best practices for writing functions that clarify intention, promote reuse, and avoid bugs Coverage of how to accurately express behaviors with classes and objects Guidance on how to avoid pitfalls with metaclasses and dynamic attributes More efficient approaches to concurrency and parallelism Better techniques and idioms for using Python s built-in modules Tools and best practices for collaborative development Solutions for debugging, testing, and optimization in order to improve quality and performance "

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    Based on the authors' intensive summer C++ courses at Stanford University, Accelerated C++ covers virtually every concept that most professional C++ programmers will ever use -- but it turns the traditional C++ curriculum upside down, starting with the high-level C++ data structures and algorithms that let you write robust programs immediately. Once you're getting results, Accelerated C++ takes you under the hood, introducing complex language features such as memory management in context, and explaining exactly how and when to use them. From start to finish, the book concentrates on solving problems, rather than learning language and library features for their own sake. The result: You'll be writing real-world programs in no time -- and outstanding code faster than you ever imagined.

    And in a perfect world, those who produce the best code are the most successful. But in our perfectly messy world, success also depends on how you work with people to get your job done.In this highly entertaining book, Brian Fitzpatrick and Ben Collins-Sussman cover basic patterns and anti-patterns for working with other people, teams, and users while trying to develop software. It's valuable information from two respected software engineers whose popular video series, "Working with Poisonous People," has attracted hundreds of thousands of viewers.You'll learn how to deal with imperfect people--those irrational and unpredictable beings--in the course of your work. And you'll discover why playing well with others is at least as important as having great technical skills. By internalizing the techniques in this book, you'll get more software written, be more influential, be happier in your career.

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    The book begins by introducing the unique features and concepts of Go. Then, you'll get hands-on experience writing real-world applications including websites and network servers, as well as techniques to manipulate and convert data at speeds that will make your friends jealous.

    Ideal for processing large datasets, the Apache Hadoop framework is an open source implementation of the MapReduce algorithm on which Google built its empire. This comprehensive resource demonstrates how to use Hadoop to build reliable, scalable, distributed systems: programmers will find details for analyzing large datasets, and administrators will learn how to set up and run Hadoop clusters. Complete with case studies that illustrate how Hadoop solves specific problems, this book helps you:Use the Hadoop Distributed File System (HDFS) for storing large datasets, and run distributed computations over those datasets using MapReduce Become familiar with Hadoop's data and I/O building blocks for compression, data integrity, serialization, and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster, or run Hadoop in the cloud Use Pig, a high-level query language for large-scale data processing Take advantage of HBase, Hadoop's database for structured and semi-structured data Learn ZooKeeper, a toolkit of coordination primitives for building distributed systems If you have lots of data -- whether it's gigabytes or petabytes -- Hadoop is the perfect solution. Hadoop: The Definitive Guide is the most thorough book available on the subject. "Now you have the opportunity to learn about Hadoop from a master-not only of the technology, but also of common sense and plain talk." -- Doug Cutting, Hadoop Founder, Yahoo!

    Be part of the solution. With this practical book, you'll learn 10 easy-to-follow guidelines for delivering software that's easy to maintain and adapt. These guidelines have been derived from analyzing hundreds of real-world systems.Written by consultants from the Software Improvement Group (SIG), this book provides clear and concise explanations, with advice for turning the guidelines into practice. Examples are written in Java, but this guide is equally useful for developers working in other programming languages.10 Coding Guidelines- Write short units of code: limit the length of methods and constructors- Write simple units of code: limit the number of branch points per method- Write code once, rather than risk copying buggy code- Keep unit interfaces small by extracting parameters into objects- Separate concerns to avoid building large classes- Couple architecture components loosely- Balance the number and size of top-level components in your code- Keep your codebase as small as possible- Automate tests for your codebase- Write clean code, avoiding "code smells" that indicate deeper problemsWhy you should read this bookTaken in isolation, the guidelines presented in this book are well-known. In fact, many well-known tools for code analysis check a number of the guidelines presented here. The following three characteristics set this book apart from other books on software development: We have selected the ten most important guidelines from experience.We teach how to comply with these ten guidelines.We present statistics and examples from real-world systems.This book is part our Training on Software Maintainability - and subsequent Certification on Quality Software Development program. For more information about this program, please contact training@sig.eu.

    It has become popular in recent years because of its simplicity, conciseness, and clarity. This book teaches functional programming as a way of thinking and problem solving, using Haskell, the most popular purely functional language. Rather than using the conventional (boring) mathematical examples commonly found in other programming language textbooks, the author uses examples drawn from multimedia applications, including graphics, animation, and computer music, thus rewarding the reader with working programs for inherently more interesting applications. Aimed at both beginning and advanced programmers, this tutorial begins with a gentle introduction to functional programming and moves rapidly on to more advanced topics. Details about progamming in Haskell are presented in boxes throughout the text so they can be easily found and referred to.

    And this may sound weirdly obvious, but every single one of those pieces of software was written by a programmer. Programmers are thus among the most quietly influential people on the planet. As we live in a world made of software, they're the architects. The decisions they make guide our behavior. When they make something newly easy to do, we do a lot more of it. If they make it hard or impossible to do something, we do less of it.If we want to understand how today's world works, we ought to understand something about coders. Who exactly are the people that are building today's world? What makes them tick? What type of personality is drawn to writing software? And perhaps most interestingly -- what does it do to them?One of the first pieces of coding a newbie learns is the program to make the computer say "Hello, world!" Like that piece of code, Clive Thompson's book is a delightful place to begin to understand this vocation, which is both a profession and a way of life, and which essentially didn't exist little more than a generation ago, but now is considered just about the only safe bet we can make about what the future holds. Thompson takes us close to some of the great coders of our time, and unpacks the surprising history of the field, beginning with the first great coders, who were women. Ironically, if we're going to traffic in stereotypes, women are arguably "naturally" better at coding than men, but they were written out of the history, and shoved out of the seats, for reasons that are illuminating. Now programming is indeed, if not a pure brotopia, at least an awfully homogenous community, which attracts people from a very narrow band of backgrounds and personality types. As Thompson learns, the consequences of that are significant - not least being a fetish for disruption at scale that doesn't leave much time for pondering larger moral issues of collateral damage. At the same time, coding is a marvelous new art form that has improved the world in innumerable ways, and Thompson reckons deeply, as no one before him has, with what great coding in fact looks like, who creates it, and where they come from. To get as close to his subject has he can, he picks up the thread of his own long-abandoned coding practice, and tries his mightiest to up his game, with some surprising results.More and more, any serious engagement with the world demands an engagement with code and its consequences, and to understand code, we must understand coders. In that regard, Clive Thompson's Hello, World! is a marvelous and delightful master class.

    Algorithms in a Nutshell describes a large number of existing algorithms for solving a variety of problems, and helps you select and implement the right algorithm for your needs -- with just enough math to let you understand and analyze algorithm performance. With its focus on application, rather than theory, this book provides efficient code solutions in several programming languages that you can easily adapt to a specific project. Each major algorithm is presented in the style of a design pattern that includes information to help you understand why and when the algorithm is appropriate. With this book, you will:Solve a particular coding problem or improve on the performance of an existing solutionQuickly locate algorithms that relate to the problems you want to solve, and determine why a particular algorithm is the right one to useGet algorithmic solutions in C, C++, Java, and Ruby with implementation tipsLearn the expected performance of an algorithm, and the conditions it needs to perform at its bestDiscover the impact that similar design decisions have on different algorithmsLearn advanced data structures to improve the efficiency of algorithmsWith Algorithms in a Nutshell, you'll learn how to improve the performance of key algorithms essential for the success of your software applications.

    At long last you'll be united with the programming language you've been longing for: Clojure!As a Lisp-style functional programming language, Clojure lets you write robust and elegant code, and because it runs on the Java Virtual Machine, you can take advantage of the vast Java ecosystem. Clojure for the Brave and True offers a "dessert-first" approach: you'll start playing with real programs immediately, as you steadily acclimate to the abstract but powerful features of Lisp and functional programming. Inside you'll find an offbeat, practical guide to Clojure, filled with quirky sample programs that catch cheese thieves and track glittery vampires.Learn how to: Wield Clojure's core functions Use Emacs for Clojure development Write macros to modify Clojure itself Use Clojure's tools to simplify concurrency and parallel programmingClojure for the Brave and True assumes no prior experience with Clojure, the Java Virtual Machine, or functional programming. Are you ready, brave reader, to meet your true destiny? Grab your best pair of parentheses—you're about to embark on an epic journey into the world of Clojure!

    It features excellent examples and access to Addison Wesley's database Web site that includes further teaching, tutorials and many useful student resources.

    Domain-driven design (DDD) combined with functional programming is the innovative combo that will get you there. In this pragmatic, down-to-earth guide, you'll see how applying the core principles of functional programming can result in software designs that model real-world requirements both elegantly and concisely - often more so than an object-oriented approach. Practical examples in the open-source F# functional language, and examples from familiar business domains, show you how to apply these techniques to build software that is business-focused, flexible, and high quality.Domain-driven design is a well-established approach to designing software that ensures that domain experts and developers work together effectively to create high-quality software. This book is the first to combine DDD with techniques from statically typed functional programming. This book is perfect for newcomers to DDD or functional programming - all the techniques you need will be introduced and explained.Model a complex domain accurately using the F# type system, creating compilable code that is also readable documentation---ensuring that the code and design never get out of sync. Encode business rules in the design so that you have "compile-time unit tests," and eliminate many potential bugs by making illegal states unrepresentable. Assemble a series of small, testable functions into a complete use case, and compose these individual scenarios into a large-scale design. Discover why the combination of functional programming and DDD leads naturally to service-oriented and hexagonal architectures. Finally, create a functional domain model that works with traditional databases, NoSQL, and event stores, and safely expose your domain via a website or API.Solve real problems by focusing on real-world requirements for your software.What You Need: The code in this book is designed to be run interactively on Windows, Mac and Linux.You will need a recent version of F# (4.0 or greater), and the appropriate .NET runtime for your platform.Full installation instructions for all platforms at fsharp.org.

    It won’t crush you. It’s light as a feather (because I haven’t finished it yet—hehe). And there’s a reason this book will stay light: because Ruby is simple to learn.[Why’s (Poignant) Guide to Ruby is released under the Attribution-ShareAlike License. So, yes, please distribute it and print it and read it leisurely in your housecoat.]