Book picks similar to
The Little Book of Python Anti-Patterns by QuantifiedCode


coding
computer-science
computer-science-programming
cs-or-tech-related

A Common-Sense Guide to Data Structures and Algorithms: Level Up Your Core Programming Skills


Jay Wengrow - 2017
    If you have received one of these copies, please contact the Pragmatic Bookshelf at support@pragprog.com, and we will replace it for you.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 as binary trees and graphs to help scale specialized applications such as social networks and mapping software. You'll even encounter a single keyword that can give your code a turbo boost. Jay Wengrow brings to this book the key teaching practices he developed as a web development bootcamp founder and educator.Use these techniques today to make your code faster and more scalable.

Computer Graphics with OpenGL


Donald Hearn - 2003
    The text converts all programming code into the C++ language.

Rails Antipatterns: Best Practice Ruby on Rails Refactoring


Chad Pytel - 2010
     Rails(TM) AntiPatterns identifies these widespread Rails code and design problems, explains why they're bad and why they happen--and shows exactly what to do instead.The book is organized into concise, modular chapters--each outlines a single common AntiPattern and offers detailed, cookbook-style code solutions that were previously difficult or impossible to find. Leading Rails developers Chad Pytel and Tammer Saleh also offer specific guidance for refactoring existing bad code or design to reflect sound object-oriented principles and established Rails best practices. With their help, developers, architects, and testers can dramatically improve new and existing applications, avoid future problems, and establish superior Rails coding standards throughout their organizations.This book will help you understand, avoid, and solve problems withModel layer code, from general object-oriented programming violations to complex SQL and excessive redundancy Domain modeling, including schema and database issues such as normalization and serialization View layer tools and conventions Controller-layer code, including RESTful code Service-related APIs, including timeouts, exceptions, backgrounding, and response codes Third-party code, including plug-ins and gems Testing, from test suites to test-driven development processes Scaling and deployment Database issues, including migrations and validations System design for "graceful degradation" in the real world

Building Cloud Apps with Microsoft Azure: Best Practices for DevOps, Data Storage, High Availability, and More (Developer Reference)


Scott Guthrie - 2014
    The patterns apply to the development process as well as to architecture and coding practices. The content is based on a presentation developed by Scott Guthrie and delivered by him at the Norwegian Developers Conference (NDC) in June of 2013 (part 1, part 2), and at Microsoft Tech Ed Australia in September 2013 (part 1, part 2). Many others updated and augmented the content while transitioning it from video to written form. Who should read this book Developers who are curious about developing for the cloud, are considering a move to the cloud, or are new to cloud development will find here a concise overview of the most important concepts and practices they need to know. The concepts are illustrated with concrete examples, and each chapter includes links to other resources that provide more in-depth information. The examples and the links to additional resources are for Microsoft frameworks and services, but the principles illustrated apply to other web development frameworks and cloud environments as well. Developers who are already developing for the cloud may find ideas here that will help make them more successful. Each chapter in the series can be read independently, so you can pick and choose topics that you're interested in. Anyone who watched Scott Guthrie's "Building Real World Cloud Apps with Windows Azure" presentation and wants more details and updated information will find that here. Assumptions This ebook expects that you have experience developing web applications by using Visual Studio and ASP.NET. Familiarity with C# would be helpful in places.

Professional Android 2 Application Development


Reto Meier - 2010
    This update to the bestselling first edition dives in to cover the exciting new features of the latest release of the Android mobile platform.Providing in-depth coverage of how to build mobile applications using the next major release of the Android SDK, this invaluable resource takes a hands-on approach to discussing Android with a series of projects, each of which introduces a new feature and highlights techniques and best practices to get the most out of Android.The Android SDK is a powerful, flexible, open source platform for mobile devices Shares helpful techniques and best practices to maximize the capabilities of Android Explains the possibilities of Android through the use of a series of detailed projects Demonstrates how to create real-world mobile applications for Android phones Includes coverage of the latest version of Android Providing concise and compelling examples, Professional Android Application Development is an updated guide aimed at helping you create mobile applications for mobile devices running the latest version of Android.

Programming Collective Intelligence: Building Smart Web 2.0 Applications


Toby Segaran - 2002
    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

Functional and Reactive Domain Modeling


Debasish Ghosh - 2016
    Domain modeling is a technique for creating a conceptual map of a problem space such as a business system or a scientific application, so that the developer can write the software more efficiently. The domain model doesn't present a solution to the problem, but instead describes the attributes, roles, and relationships of the entities involved, along with the constraints of the system.Reactive application design, which uses functional programming principles along with asynchronous non-blocking communication, promises to be a potent pattern for developing performant systems that are relatively easy to manage, maintain and evolve. Typically we call such models "reactive" because they are more responsive both to user requests and to system loads. But designing and implementing such models requires a different way of thinking. Because the core behaviors are implemented using pure functions, you can reason about the domain model just like mathematics, so your model becomes verifiable and robust.Functional and Reactive Domain Modeling teaches you how to think of the domain model in terms of pure functions and how to compose them to build larger abstractions. You will start with the basics of functional programming and gradually progress to the advanced concepts and patterns that you need to know to implement complex domain models. The book demonstrates how advanced FP patterns like algebraic data types, typeclass based design, and isolation of side-effects can make your model compose for readability and verifiability.On the subject of reactive modeling, the book focuses on higher order concurrency patterns like actors and futures. It uses the Akka framework as the reference implementation and demonstrates how advanced architectural patterns like event sourcing and CQRS can be put to great use in implementing scalable models. You will learn techniques that are radically different from the standard RDBMS based applications that are based on mutation of records. You'll also pick up important patterns like using asynchronous messaging for interaction based on non blocking concurrency and model persistence, which delivers the speed of in-memory processing along with suitable guarantees of reliability.

Coding Interview Questions


Narasimha Karumanchi - 2012
    Peeling Data Structures and Algorithms: * Programming puzzles for interviews * Campus Preparation * Degree/Masters Course Preparation * Instructor's * GATE Preparation * Big job hunters: Microsoft, Google, Amazon, Yahoo, Flip Kart, Adobe, IBM Labs, Citrix, Mentor Graphics, NetApp, Oracle, Webaroo, De-Shaw, Success Factors, Face book, McAfee and many more * Reference Manual for working people

Data Science from Scratch: First Principles with Python


Joel Grus - 2015
    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

MySQL Crash Course


Ben Forta - 2005
    And this book will teach you all you need to know to be immediately productive with MySQL. By working through 30 highly focused hands-on lessons, your MySQL Crash Course will be both easier and more effective than you'd have thought possible. Learn how to: Retrieve and sort data Filter data using comparisons, regular expressions, full text search, and much more Join relational data Create and alter tables Insert, update, and delete data Leverage the power of stored procedures and triggers Use views and Cursors Manage transactional processing Create user accounts and manage security via access control Ben Forta is Macromedia's Senior Technical Evangelist, and has almost 20 years of experience in the computer industry in product development, support, training, and product marketing. Ben is the author of the best-selling Sams Teach Yourself SQL in 10 Minutes (now in its third edition, and translated into over a dozen languages), ColdFusion Web Application Construction Kit, and Advanced ColdFusion Development (both published by Que Publishing), Sams Teach Yourself Regular Expressions in 10 Minutes, as well as books on SQL, Flash, JSP, HomeSite, WAP, Windows 2000, and other subjects.

Python for Data Analysis


Wes McKinney - 2011
    It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It's ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it's specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples

A Byte of Python


Swaroop C.H. - 2004
    An introduction to Python programming for beginners.

Exam Ref 70-480: Programming in HTML5 with JavaScript and CSS3


Rick Delorme - 2013
    Designed for experienced developers ready to advance their status, Exam Ref focuses on the critical-thinking and decision-making acumen needed for success at the Microsoft Specialist level.Focus on the expertise measured by these objectives:Implement and manipulate document structures and objectsImplement program flowAccess and secure dataUse CSS3 in applicationsThis Microsoft Exam Ref:Organizes its coverage by exam objectives.Features strategic, what-if scenarios to challenge you.Includes a 15% exam discount from Microsoft. (Limited time offer)

Python Programming: An Introduction to Computer Science


John Zelle - 2003
    It takes a fairly traditional approach, emphasizing problem solving, design, and programming as the core skills of computer science. However, these ideas are illustrated using a non-traditional language, namely Python. Although I use Python as the language, teaching Python is not the main point of this book. Rather, Python is used to illustrate fundamental principles of design and programming that apply in any language or computing environment. In some places, I have purposely avoided certain Python features and idioms that are not generally found in other languages. There are already many good books about Python on the market; this book is intended as an introduction to computing. Features include the following: *Extensive use of computer graphics. *Interesting examples. *Readable prose. *Flexible spiral coverage. *Just-in-time object coverage. *Extensive end-of-chapter problems.

Absolute Beginner's Guide to C


Greg Perry - 1993
    This bestseller talks to readers at their level, explaining every aspect of how to get started and learn the C language quickly. Readers also find out where to learn more about C. This book includes tear-out reference card of C functions and statements, a hierarchy chart, and other valuable information. It uses special icons, notes, clues, warnings, and rewards to make understanding easier. And the clear and friendly style presumes no programming knowledge.