This book is for Secret Agents who have some exposure to Python. Our focus is on the Field Agents who are ready to do more sophisticated and complex programming in Python. We'll stick to simple statistics for the most part. A steady hand with a soldering iron is not required, but a skilled field agent should be able to assemble a working Arduino circuit to gather their own sensor data.What You Will LearnUpgrade Python to the latest version and discover its latest and greatest toolsUse Python libraries to extract data from log files that are designed more for people to read than for automated analysisSummarize log files and extract meaningful informationGather data from social networking sites and leverage your experience of analyzing log files to summarize the data you findExtract text and images from social networking sitesParse the complex and confusing data structures in a PDF file to extract meaningful text that we can analyzeConnect small, intelligent devices to our computer to use them as remote sensorsUse Python to analyze measurements from sensors to calibrate them and use sensors efficientlyIn Detail
Python is easy to learn and extensible programming language that allows any manner of secret agent to work with a variety of data. Agents from beginners to seasoned veterans will benefit from Python's simplicity and sophistication. The standard library provides numerous packages that move beyond simple beginner missions. The Python ecosystem of related packages and libraries supports deep information processing.
This book will guide you through the process of upgrading your Python-based toolset for intelligence gathering, analysis, and communication. You'll explore the ways Python is used to analyze web logs to discover the trails of activities that can be found in web and database servers. We'll also look at how we can use Python to discover details of the social network by looking at the data available from social networking websites.
Finally, you'll see how to extract history from PDF files, which opens up new sources of data, and you'll learn about the ways you can gather data using an Arduino-based sensor device.Style and approach
Each chapter will include a background briefing that covers an essential Python technology. After some in-depth exploration of the features, the chapter will conclude with a mission that is a concrete application of the Python tools and techniques covered.
Topics include:The pros and cons of braced initialization, noexcept specifications, perfect forwarding, and smart pointer make functionsThe relationships among std::move, std::forward, rvalue references, and universal referencesTechniques for writing clear, correct, effective lambda expressionsHow std::atomic differs from volatile, how each should be used, and how they relate to C++'s concurrency APIHow best practices in "old" C++ programming (i.e., C++98) require revision for software development in modern C++
Effective Modern C++ follows the proven guideline-based, example-driven format of Scott Meyers' earlier books, but covers entirely new material.
"After I learned the C++ basics, I then learned how to use C++ in production code from Meyer's series of Effective C++ books. Effective Modern C++ is the most important how-to book for advice on key guidelines, styles, and idioms to use modern C++ effectively and well. Don't own it yet? Buy this one. Now".
-- Herb Sutter, Chair of ISO C++ Standards Committee and C++ Software Architect at Microsoft
Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an experienced data programmer, it will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process.Create vectors, handle variables, and perform other basic functionsInput and output dataTackle data structures such as matrices, lists, factors, and data framesWork with probability, probability distributions, and random variablesCalculate statistics and confidence intervals, and perform statistical testsCreate a variety of graphic displaysBuild statistical models with linear regressions and analysis of variance (ANOVA)Explore advanced statistical techniques, such as finding clusters in your data
"Wonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language—one practical example at a time."—Jeffrey Ryan, software consultant and R package author
Learning Python, Second Edition, offers programmers a comprehensive learning tool for Python and object-oriented programming. Thoroughly updated for the numerous language and class presentation changes that have taken place since the release of the first edition in 1999, this guide introduces the basic elements of the latest release of Python 2.3 and covers new features, such as list comprehensions, nested scopes, and iterators/generators.
Beyond language features, this edition of Learning Python also includes new context for less-experienced programmers, including fresh overviews of object-oriented programming and dynamic typing, new discussions of program launch and configuration options, new coverage of documentation sources, and more. There are also new use cases throughout to make the application of language features more concrete.
The first part of Learning Python gives programmers all the information they'll need to understand and construct programs in the Python language, including types, operators, statements, classes, functions, modules and exceptions. The authors then present more advanced material, showing how Python performs common tasks by offering real applications and the libraries available for those applications. Each chapter ends with a series of exercises that will test your Python skills and measure your understanding.
Learning Python, Second Edition is a self-paced book that allows readers to focus on the core Python language in depth. As you work through the book, you'll gain a deep and complete understanding of the Python language that will help you to understand the larger application-level examples that you'll encounter on your own. If you're interested in learning Python--and want to do so quickly and efficiently--then Learning Python, Second Edition is your best choice.
Packed with examples and exercises, Natural Language Processing with Python will help you:
Extract information from unstructured text, either to guess the topic or identify "named entities"Analyze linguistic structure in text, including parsing and semantic analysisAccess popular linguistic databases, including WordNet and treebanksIntegrate techniques drawn from fields as diverse as linguistics and artificial intelligence
This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.
Complete with quizzes, exercises, and helpful illustrations, this easy-to-follow, self-paced tutorial gets you started with both Python 2.7 and 3.3— the latest releases in the 3.X and 2.X lines—plus all other releases in common use today. You’ll also learn some advanced language features that recently have become more common in Python code.Explore Python’s major built-in object types such as numbers, lists, and dictionariesCreate and process objects with Python statements, and learn Python’s general syntax modelUse functions to avoid code redundancy and package code for reuseOrganize statements, functions, and other tools into larger components with modulesDive into classes: Python’s object-oriented programming tool for structuring codeWrite large programs with Python’s exception-handling model and development toolsLearn advanced Python tools, including decorators, descriptors, metaclasses, and Unicode processing
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
Filled with practical, do-it-yourself gadgets, Arduino + Android Projects for the Evil Genius shows you how to create Arduino devices and control them with Android smartphones and tablets. Easy-to-find equipment and components are used for all the projects in the book.
This wickedly inventive guide covers the Android Open Application Development Kit (ADK) and USB interface and explains how to use them with the basic Arduino platform. Methods of communication between Android and Arduino that don't require the ADK--including sound, Bluetooth, and WiFi/Ethernet are also discussed. An Arduino ADK programming tutorial helps you get started right away.
Arduino + Android Projects for the Evil Genius:Contains step-by-step instructions and helpful illustrations Provides tips for customizing the projects Covers the underlying principles behind the projects Removes the frustration factor--all required parts are listed Provides all source code on the book's website
Build these and other devious devices:Bluetooth robot Android Geiger counter Android-controlled light show TV remote Temperature logger Ultrasonic range finder Home automation controller Remote power and lighting control Smart thermostat RFID door lock Signaling flags Delay timer
With SQLite, you'll discover how to develop a database-backed application that remains manageable in size and complexity. This book guides you every step of the way. You'll get a crash course in data modeling, become familiar with SQLite's dialect of the SQL database language, and much more.Learn how to maintain localized storage in a single file that requires no configurationBuild your own SQLite library or use a precompiled distribution in your applicationGet a primer on SQL, and learn how to use several language functions and extensionsWork with SQLite using a scripting language or a C-based language such as C# or Objective-CUnderstand the basics of database design, and learn how to transfer what you already know to SQLiteTake advantage of virtual tables and modules
"Complex SQL concepts explained clearly."
--D. Richard Hipp, creator of SQLite
Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3.
This book covers:Python data model: understand how special methods are the key to the consistent behavior of objectsData structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode ageFunctions as objects: view Python functions as first-class objects, and understand how this affects popular design patternsObject-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritanceControl flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.futures and asyncio packagesMetaprogramming: understand how properties, attribute descriptors, class decorators, and metaclasses work
Rather than impose development guidelines as other frameworks do, Flask leaves the business of extensions up to you. If you have Python experience, this book shows you how to take advantage of that creative freedom.Learn Flask’s basic application structure and write an example appWork with must-have components—templates, databases, web forms, and email supportUse packages and modules to structure a large application that scalesImplement user authentication, roles, and profilesBuild a blogging feature by reusing templates, paginating item lists, and working with rich textUse a Flask-based RESTful API to expose app functionality to smartphones, tablets, and other third-party clientsLearn how to run unit tests and enhance application performanceExplore options for deploying your web app to a production server
This book takes you step-by-step through many fun and educational possibilities. Take advantage of several preloaded programming languages. Use the Raspberry Pi with Arduino. Create Internet-connected projects. Play with multimedia. With Raspberry Pi, you can do all of this and more.Get acquainted with hardware features on the Pi’s board Learn enough Linux to move around the operating system Pick up the basics of Python and Scratch—and start programming Draw graphics, play sounds, and handle mouse events with the Pygame framework Use the Pi’s input and output pins to do some hardware hacking Discover how Arduino and the Raspberry Pi complement each other Integrate USB webcams and other peripherals into your projects Create your own Pi-based web server with Python
You’ll gain a strong foundation in the language, including best practices for testing, debugging, code reuse, and other development tips. This book also shows you how to use Python for applications in business, science, and the arts, using various Python tools and open source packages.Learn simple data types, and basic math and text operationsUse data-wrangling techniques with Python’s built-in data structuresExplore Python code structure, including the use of functionsWrite large programs in Python, with modules and packagesDive into objects, classes, and other object-oriented featuresExamine storage from flat files to relational databases and NoSQLUse Python to build web clients, servers, APIs, and servicesManage system tasks such as programs, processes, and threadsUnderstand the basics of concurrency and network programming
Python in easy steps begins by explaining how to install the free Python interpreter so you can quickly begin to create your own executable programs by copying the book's examples. It demonstrates all the Python language basics before moving on to provide examples of Object Oriented Programming (OOP) and CGI scripting to handle web form data. The book concludes by demonstrating how you can use your acquired knowledge to create and deploy graphical windowed applications.
Python in easy steps makes no assumption you have previous knowledge of any programming language so it's ideal for the newcomer to computer programming. It has an easy-to-follow style that will appeal to programmers moving from another programming language, and to the student who is studying Python programming at school or college, and to those seeking a career in computing who need a fundamental understanding of computer programming.
Python is the language used to program the Raspberry Pi - covered by Raspberry Pi in easy steps.
Ideal for enthusiasts, from students in robotics clubs to professional robotics scientists and engineers, each recipe describes a complete solution using ROS open source libraries and tools. You’ll learn how to complete tasks described in the recipes, as well as how to configure and recombine components for other tasks. If you’re familiar with Python, you’re ready to go.Learn fundamentals, including key ROS concepts, tools, and patternsProgram robots that perform an increasingly complex set of behaviors, using the powerful packages in ROSSee how to easily add perception and navigation abilities to your robotsIntegrate your own sensors, actuators, software libraries, and even a whole robot into the ROS ecosystemLearn tips and tricks for using ROS tools and community resources, debugging robot behavior, and using C++ in ROS
This book covers:Arrays and lists: the most common data structuresStacks and queues: more complex list-like data structuresLinked lists: how they overcome the shortcomings of arraysDictionaries: storing data as key-value pairsHashing: good for quick insertion and retrievalSets: useful for storing unique elements that appear only onceBinary Trees: storing data in a hierarchical mannerGraphs and graph algorithms: ideal for modeling networksAlgorithms: including those that help you sort or search dataAdvanced algorithms: dynamic programming and greedy algorithms
If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource.What You Will LearnExplore how to use different machine learning models to ask different questions of your dataLearn how to build neural networks using Keras and TheanoFind out how to write clean and elegant Python code that will optimize the strength of your algorithmsDiscover how to embed your machine learning model in a web application for increased accessibilityPredict continuous target outcomes using regression analysisUncover hidden patterns and structures in data with clusteringOrganize data using effective pre-processing techniquesGet to grips with sentiment analysis to delve deeper into textual and social media dataIn Detail
Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success.
Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization.Style and approach
Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.
Most of the recipes use the ggplot2 package, a powerful and flexible way to make graphs in R. If you have a basic understanding of the R language, you’re ready to get started.Use R’s default graphics for quick exploration of dataCreate a variety of bar graphs, line graphs, and scatter plotsSummarize data distributions with histograms, density curves, box plots, and other examplesProvide annotations to help viewers interpret dataControl the overall appearance of graphicsRender data groups alongside each other for easy comparisonUse colors in plotsCreate network graphs, heat maps, and 3D scatter plotsStructure data for graphing
Written by Mark Lutz—widely recognized as the world’s leading Python trainer—Python Pocket Reference is an ideal companion to O’Reilly’s classic Python tutorials, Learning Python and Programming Python, also written by Mark.
This fifth edition covers:Built-in object types, including numbers, lists, dictionaries, and moreStatements and syntax for creating and processing objectsFunctions and modules for structuring and reusing codePython’s object-oriented programming toolsBuilt-in functions, exceptions, and attributesSpecial operator overloading methodsWidely used standard library modules and extensionsCommand-line options and development toolsPython idioms and hintsThe Python SQL Database API
With this book, you learn the latest and most productive tools in the Android tools ecosystem, and the best practices for Android app development. You will be able to take away the labs' code as templates or frameworks to re-use and customize for your own similar apps.
Android Studio is an intuitive, feature-rich, and extremely forgiving Integrated Development Environment (IDE). This IDE is more productive and easier to use for your Android app creations than Eclipse. With this book you will quickly master Android Studio and maximize your Android development time. Source code on the remote web-hosting service is targeted to the latest Android Studio release, version 1.2.
Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming.
Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines.
• How to programmatically configure the Spring container and beans
• How to use annotations for dependency injection
• How to use collections and custom types
• How to customize and configure bean properties and bean lifecycle interfaces
• How to handle metadata using XML, annotations, and the Groovy bean reader
• How to use the new Spring Boot and Spring XD
After reading this book, you will have all you need to start using the Spring Framework effectively.
Projects and tutorials include:Controlling devices over BluetoothUsing Python and Arduino programming environments on EdisonTracking objects with a webcam and OpenCVResponding to voice commands and talking backUsing and configuring Linux on Edison
Through clear and concise instructions, you’ll learn how to get the most out of App Engine’s nearly unlimited computing power. This second edition is fully updated and expanded to cover Python 2.7 and Java 6 support, multithreading, asynchronous service APIs, and the use of frameworks such as Django 1.3 and webapp2.Understand how App Engine handles web requests and executes application codeLearn about new datastore features for queries and indexes, transactions, and data modelingCreate, manipulate, and serve large data files with the BlobstoreUse task queues to parallelize and distribute computation across the infrastructureEmploy scalable services for email, instant messaging, and communicating with web servicesTrack resource consumption, and optimize your application for speed and cost effectiveness
By reading this definitive tutorial and reference, you'll gain the knowledge and experience to create stunning, cutting-edge Android apps that can make you money, while keeping you agile enough to respond to changes in the future.
Bioinformatics Programming Using Python is perfect for anyone involved with bioinformatics -- researchers, support staff, students, and software developers interested in writing bioinformatics applications. You'll find it useful whether you already use Python, write code in another language, or have no programming experience at all. It's an excellent self-instruction tool, as well as a handy reference when facing the challenges of real-life programming tasks.Become familiar with Python's fundamentals, including ways to develop simple applicationsLearn how to use Python modules for pattern matching, structured text processing, online data retrieval, and database accessDiscover generalized patterns that cover a large proportion of how Python code is used in bioinformaticsLearn how to apply the principles and techniques of object-oriented programmingBenefit from the "tips and traps" section in each chapter