Computer programming / software engineering Books

Book SynopsisEliminating security holes in iOS apps is critical for any developer who wants to protect their users from the bad guys. In iOS Application Security, mobile security expert David Thiel reveals common iOS coding mistakes that create serious security problems and shows you how to find and fix them. After a crash course on iOS application structure and Objective-C design patterns, you ll move on to spotting bad code and plugging the holes. You ll learn about: The iOS security model and the limits of its built-in protections The myriad ways sensitive data can leak into places it shouldn t, such as through the pasteboard How to implement encryption with the Keychain, the Data Protection API, and CommonCrypto Legacy flaws from C that still cause problems in modern iOS applications Privacy issues related to gathering user data and how to mitigate potential pitfalls Don t let your app s security leak become another headline. Whether you re looking to bolster your app s defenses or huntinTable of ContentsIntroductionPART I: IOS FUNDAMENTALS Chapter 1: The iOS Security ModelChapter 2: Objective-C for the LazyChapter 3: iOS Application AnatomyPART II: SECURITY TESTINGChapter 4: Building Your Test Platform Chapter 5: Debugging with lldb and FriendsChapter 6: Black-Box TestingPART III: SECURITY QUIRKS OF THE COCOA APIChapter 7: iOS NetworkingChapter 8: Interprocess CommunicationChapter 9: iOS-Targeted Web AppsChapter 10: Data LeakageChapter 11: Legacy Issues and Baggage from CChapter 12: Injection AttacksPART IV: KEEPING DATA SAFEChapter 13: Encryption and AuthenticationChapter 14: Mobile Privacy Concerns

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Book SynopsisProcessing is a free, beginner-friendly programming language designed to help non-programmers create interactive art with code. The SparkFun Guide to Processing, the first in the SparkFun Electronics series, will show you how to craft digital artwork and even combine that artwork with hardware so that it reacts to the world around you. Start with the basics of programming and animation as you draw colorful shapes and make them bounce around the screen. Then move on to a series of hands-on, step-by-step projects that will show you how to: Make detailed pixel art and scale it to epic proportions Write a maze game and build a MaKey MaKey controller with fruit buttons Play, record, and sample audio to create your own soundboard Fetch weather data from the Web and build a custom weather dashboard Create visualizations that change based on sound, light, and temperature readings With a little imagination and Processing as your paintbrush, you ll be on your way to coding your own galleryTrade Review"The book is well organized. I appreciated the introductory overview of the book as well as the section on the history of Processing in the first chapter."—Elie Zananiri, Senior Developer for ProcessingTable of ContentsForeword by Nathan SeidleIntroductionProject 0: Getting Started with ProcessingProject 1: Pixel ArtProject 2: Holiday CardProject 3: A First Dynamic SketchProject 4: Interactive Time-Based ArtProject 5: Enter the MatrixProject 6: Image Processing with CollageProject 7: Playing with TextProject 8: Two Drawing ProgramsProject 9: A Maze GameProject 10: Manipulating Movies and Capturing VideoProject 11: Audio Processing with MinimProject 12: Building a Weather Dashboard with JSON DataProject 13: Using Sensors with Processing and ArduinoIndex

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Book SynopsisLearn to use C#'s powerful set of core libraries to automate tedious yet important tasks like performing vulnerability scans, malware analysis, and incident response. With some help from Mono, you can write your own practical security tools that will run on Mac, Linux, and even mobile devices. Following a crash course in C# and some of its advanced features, you'll learn how to: -Write fuzzers that use the HTTP and XML libraries to scan for SQL and XSS injection -Generate shellcode in Metasploit to create cross-platform and cross-architecture payloads -Automate Nessus, OpenVAS, and sqlmap to scan for vulnerabilities and exploit SQL injections -Write a .NET decompiler for Mac and Linux -Parse and read offline registry hives to dump system information -Automate the security tools Arachni and Metasploit using their MSGPACK RPCs Streamline and simplify your work day with Gray Hat C# and C#'s extensive repertoire of powerful tools and libraries.Table of ContentsChapter 1: C# Crash CourseChapter 2: Fuzzing and Exploiting XSS and SQL InjectionChapter 3: Fuzzing SOAP EndpointsChapter 4: Writing Connect-Backs, Binds, and Metasploit PayloadsChapter 5: Automating NessusChapter 6: Automating NexposeChapter 7: Automating OpenVASChapter 8: Automating the Cuckoo SandboxChapter 9: Automating sqlmapChapter 10: Automating ClamAVChapter 11: Automating MetasploitChapter 12: Automating ArachniChapter 13: Decompiling and Reversing Managed AssembliesChapter 14: Reading Offline Windows NT Registry Hives

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Book SynopsisJava is the world's most popular programming language, but it's known for having a steep learning curve. The editors at No Starch Press have worked to lower that learning curve with Bryson Payne's latest book, Learn Java the Easy Way. Finally, a hands-on introduction to learning Java programming that will take you from absolute beginner to building Android and desktop apps. As you build you'll learn how to use conditions, loops, and variables; create reusable methods; build a graphical user interface (GUI) and animations; even how to debug your code and deal with common mistakes.Table of ContentsIntroduction Chapter 1: Getting to Know Java with JShellChapter 2: Build a Hi-Lo Guessing Game App!Chapter 3: Creating a GUI for Our Guessing GameChapter 4: Creating Your First Android AppChapter 5: Deciphering Secret MessagesChapter 6: Creating Advanced GUIs and Sharing Your AppChapter 7: Make a Secret Messages App to Share with Friends!Chapter 8: Draw Colorful, Object-Oriented Bubbles with Your Mouse!Chapter 9: Adding Animation and Collision Detection with TimersChapter 10: Making BubbleDraw a Multi-Touch Android AppAppendix A: Saving High Scores, Creating Settings Menus, and Sending Messages on Android Appendix B: DebuggingGlossarySolutions (online)

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Book SynopsisOpenSCAD is free, open-source 3D modelling software; its easy-to-use programming interface is great for beginners, because the simple design lets you quickly display and view the results of your code. In Learn to Program With 3D Printing, OpenSCAD's creator will teach you all you need to know to design, programme, and create amazing 3D-printed projects. Along the way, beginning programmers are introduced to essential programming concepts, like variables, loops, functions, and more. Co-authored by the software's primary creator Marius Kintel.Trade Review"An excellent resource for anyone looking to learn the powerful OpenSCAD language." —Ben Lutkevich, TechTarget"A concise but thorough foundation in OpenSCAD in particular and coding in general. And how better to learn than from the primary developer of the system plus an educator? Grab the book and make something cool today."—Joan Horvath, author and co-founder Nonscriptum LLC"Programming with OpenSCAD is a fast and clear reference for coders and designers who want to create parametric, customizable 3D models with OpenSCAD. Wait - you’ve never ever coded before? This book is for you too!! Everything is covered from the ground up in simple, friendly terms. OpenSCAD is a great entry point for coding and 3D modeling, and this book is an excellent guide and reference." —Dr. Laura Taalman (mathgrrl), 3D designer and professor of mathematics at James Madison University"Programming with OpenSCAD is a great way to get started designing objects to be made with a 3D printer using OpenSCAD. It introduces each new concept in a clear and concise way, always avoiding using language features ahead of explaining them, and requires no previous programming experience. Each chapter has exercises to reinforce learning and these soon become interesting objects to print on a 3D printer, so it is also a great beginner's introduction to 3D printing."—Chris "Nop Head" Palmer, author of NopSCADlib, RepRap Core Team member"This book opens up OpenSCAD to new audiences (students, teachers, makers), by being a systematic introduction into using OpenSCAD with well thought out 'design time' and 'big project' practices. With the knowledge gained, readers can create their own 3D-Objects, which they then can print and share. While doing so, students learn to think in 3D-Space and the concepts of computers programming, while always having a concrete visual representation of the end result in mind, making the learning concrete."—Michael Frey, OpenSCAD Contributor"A new language can be daunting, but this book gives you the fundamentals of 3D design and the techniques to easily create complex designs."—Michael “...AtOz” Marx, OpenSCAD Forum & Mailing-list Administrator"The book is built to provide everyone at any level of proficiency a great introduction to 3D design using OpenSCAD. If you’re considering learning OpenSCAD, this book could provide the guidance necessary to get up to speed in short order."—Kerry Stevenson, Fabbaloo"Highly recommended. A well-written, quick read that will get you going in no time!"—Electronut Labs, @electronutLabs"If you’re a complete newbie to using OpenSCAD, this would be a great book for you." —Pete Prodoehl, Rasterweb.netTable of ContentsIntroductionChapter 1: Three-Dimensional Drawing with OpenSCADChapter 2: More Ways to Transform ShapesChapter 3: 2D ShapesChapter 4: Using Loops and VariablesChapter 5: ModulesChapter 6: Flow Control with if StatementsChapter 7: Design and EngineeringAppendix A: OpenSCAD Language ReferenceAppendix B: Visual Command Reference

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Book SynopsisApp Inventor is a free, open-source visual blocks-based programming language that's perfect for beginners who want to learn important coding concepts. First created by Google, it's now maintained by MIT researchers. Each chapter shows you how to make cool apps like 'Hi, Mom' that lets you text people using voice recognition. You'll also make games like Frogger and Tic Tac Toe, as well as interactive video apps and more!Trade Review"The perfect DIY instruction manual and guide for creating apps, Learn To Program With App Inventor is an ideal and unreservedly recommended addition to personal, professional, community, highschool, college, and university library Computer Science & Technology collections." —Midwest Book ReviewTable of ContentsAcknowledgmentsIntroductionChapter 1: Hi, World!: Building Your First AppChapter 2: Practice Makes Perfect: Event-Driven ProgrammingChapter 3: Fruit Loot: Creating a Simple Animated GameChapter 4: Multiplication Station: Making Decisions with CodeChapter 5: Beat the Bus: Tracking Location with Maps and SensorsChapter 6: Tic Tac Toe: Using Loops to Create a GameChapter 7: Multiplication Station 2: Reusing Code with ProceduresChapter 8: Virtual Shades: Drawing and Dragging ImagesAppendix: App Inventor Components and Built-In Blocks

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Book SynopsisAutotools is the first book to offer programmers a tutorial-based guide to the GNU build system. The new and improved second edition of Autotools includes five new chapters on PkgConfig, unit testing with Autotest, internationalising with GNU, the portability of gnulib, and using Autotools with Windows. Leave the guesswork behind, and master the Autotools build system with Autotools!Table of ContentsIntroductionChapter 1: An End User’s Perspective on the GNU AutotoolsChapter 2: A Brief Introduction to the GNU AutotoolsChapter 3: Understanding the GNU Coding StandardsChapter 4: Configuring Your Project with AutoconfChapter 5: More Fun with Autoconf: Configuring User OptionsChapter 6: Automatic Makefiles with AutomakeChapter 7: Building Libraries with LibtoolChapter 8: Library Interface Versioning and Runtime Dynamic LinkingChapter 9: Unit Interpretation Testing with AutotestChapter 10: Finding Building Dependencies with pkg-configChapter 11: InternalizationChapter 12: LocalizationChapter 13: Maximum Portability with GnulibChapter 14: FLAIM: An Autotools ExampleChapter 15: FLAIM Part II: Pushing the EnvelopeChapter 16: Using the M4 Macro Processor with AutoconfChapter 17: Using Autotools with WindowsChapter 18: A Catalog of Tips and Reusable Solutions for Creating Great Projects

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Book SynopsisThis third volume in the Write Great Code series addresses the issues of creating readable and maintainable code that will generate awe from fellow programmers. No matter how efficient your code is, if it isn't readable and maintainable by others, then it's not great code. Great code must have a great design and must adhere to good coding standards. In this book, you'll learn things like coding styles, commenting, code layout, and other crucial coding tasks.Table of ContentsIntroduction Part I: Personal Software Engineering Chapter 1: Software Developer Metaphors Chapter 2: Productivity Chapter 3: Software Development Models Part II: An Introduction to UML Chapter 4: An Introduction to UML and Use Cases Chapter 5: UML Activity Diagrams Chapter 6: UML Class Diagrams Chapter 7: UML Interaction Diagrams Chapter 8: Miscellaneous UML Diagrams Part III: System Documentation Chapter 9: System Documentation Chapter 10: Requirements Documentation Chapter 11: Software Design Description Documentation Chapter 12: Software Test Documentation Afterword: Designing Great Code Glossary

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Book SynopsisFunctional programming is a way of thinking about programs that emphasizes functions, while avoiding state mutation. C# includes a number of functional features and libraries, enabling us to take advantage of these benefits. Functional Programming in C# teaches readers to apply functional thinking to real-world scenarios. They’ll start by learning the principles of functional programming, and how they translate in the C# language. By the end of this book, readers will be able to integrate functional techniques, making their C# programs robust and maintainable, and helping them to become more well rounded developers. Key Features: · Introduction to functional programming · Real-world examples · Integrate functional techniques · Become a well rounded developer This book is designed to help C# programmers with an OOP background understand functional thinking. About the Technology: Functional programming is a way of thinking about programs that emphasizes functions, while avoiding state mutation. It allows us to write elegant, intention-revealing code, that shines in testability and support for concurrency.

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Book SynopsisCompanies everywhere are moving everyday business processes over to the cloud, and AI is increasingly being given the reins in these tasks. As this massive digital transformation continues, the combination of serverless computing and AI promises to become the de facto standard for business-to-consumer platform development—and developers who can design, develop, implement, and maintain these systems will be in high demand! AI as a Service is a practical handbook to building and implementing serverless AI applications, without bogging you down with a lot of theory. Instead, you’ll find easy-to-digest instruction and two complete hands-on serverless AI builds in this must-have guide! Key features Cloud AI from development to production Applying cloud AI services to your existing platform Understanding orchestration patterns for cloud AI systems How to architect and build scalable, resilient data pipelines Audience For software developers with intermediate skills in at least one programming language and a basic understanding of IP networking and HTTP protocol. About the technology Artificial Intelligence (AI), a machine’s ability to learn and make predictions based on patterns it identifies, is already being leveraged by businesses around the world in areas like targeted product recommendations, financial forecasting and resource planning, customer service chatbots, healthcare diagnostics, data security, and more. Peter Elger is the founder and CEO of fourTheorem, a software solutions company providing expertise on architecture, development, DevOps, and machine learning. He is also the cofounder and CTO of two other companies: nearForm, a Node.js consultancy, and StitcherAds, a digital advertising platform. He is a regular conference speaker and coauthor of The Node Cookbook as well as several academic papers. Eoin Shanaghy is the cofounder and CTO fourTheorem and the founder of Showpiper, a machine learning-driven video content marketing startup. He previously created real-time trading applications for Fortis Bank and developed Hewlett-Packard's enterprise application server as well as 3G network management systems for Ericsson and Arantech (now Netscout). Johannes Ahlmann is the founder and CEO of Sensatus.io, a Machine Learning company specialized in large-scale Web Crawling, Market Intelligence and On-Premise AI solutions. He previously created Information Extraction solutions as Head of Data Science at ScrapingHub, and created responsive mobile solutions at Dell EMC.

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Book SynopsisPrivacy-Preserving Machine Learning is a practical guide to keeping ML data anonymous and secure. You'll learn the core principles behind different privacy preservation technologies, and how to put theory into practice for your own machine learning. Complex privacy-enhancing technologies are demystified through real world use cases forfacial recognition, cloud data storage, and more. Alongside skills for technical implementation, you'll learn about current and future machine learning privacy challenges and how to adapt technologies to your specific needs. By the time you're done, you'll be able to create machine learning systems that preserve user privacy without sacrificing data quality and model performance. Large-scale scandals such as the Facebook Cambridge Analytic a data breach have made many users wary of sharing sensitive and personal information. Demand has surged among machine learning engineers for privacy-preserving techniques that can keep users private details secure without adversely affecting the performance of models.Trade Review“An interesting and well-structured book about an emerging discipline that will certainly keep growing in importance.” Alain Couniot “Gives a deep and thorough introduction into preserving privacy while using personal data for machine learning and data mining.” HaraldKuhn “Makes for a great introduction to privacy-preserving techniques whichmake full use of machine learning.” Aditya Kaushik “An interesting book under a rising hot topic: privacy. I like the way using examples and figures to illustrate concepts.” XiangboMao “The only book, that I am aware of, which goes into depths of data privacy while making sure it doesn't get boring for readers.” VishweshRavi Shrimali “An interesting book under a rising hot topic: privacy.” XiangboMao “A great resource to understand privacy preserving ML.” DhivyaSivasubramanian “A great book to getting a deep theoretical overview of the landscape of privacy preserving approaches while also getting hands-on pragmatic experience.”Stephen Oates

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Book SynopsisEffective Data Science Infrastructure is a hands-on guide to assembling infrastructure for data science and machine learning applications. It reveals the processes used at Netflix and other data driven companies to manage their cutting edge data infrastructure. As you work through this easy-to-follow guide, you'll set up end-to end infrastructure from the ground up, with a fully customizable process you can easily adapt to your company. You'll learn how you can make data scientists more productive with your existing cloud infrastructure, a stack of open source software, and idiomatic Python. Throughout, you'll follow a human-centric approach focused on user experience and meeting the unique needs of data scientists. About the TechnologyTurning data science projects from small prototypes to sustainable business processes requires scalable and reliable infrastructure. This book lays out the workflows, components, and methods of the full infrastructure stack for data science, from data warehousing and scalable compute to modeling frameworks.Trade Review"Do not miss the opportunity to cover all key aspects of data science infrastructure on your next project." Jesús A. Juárez Guerrero "Useful book that provides tactical guidance on how to use Metaflow to streamline data science workflows but also includes great frameworks and abstractions to consider when defining your data science infrastructure stack." Sarah Catanzaro "This is the ultimate book to learn how to handle infrastructure in data science!" Ninoslav Cerkez "If you need a workflow management tool to glue your data code, look at metaflow. It's simple yet efficient." Mikael Dautrey

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Book SynopsisEffectively reading and understanding existing code is a developer's superpower. In this book, you'll master techniques for code profiling, advanced debugging, and log evaluation to find and fix bugs and performance problems. In How To Read Java: Understanding, debugging, and optimizing JVM applications you will learn how to: Determine what code does the first time you see it Expose code logic problems Evaluate heap dumps to find memory leaks Monitor CPU consumption to optimize execution Use thread dumps to find and solve deadlocks Easily follow a service-oriented or microservices system Properly use logging to better understand Java app execution Use Java debuggers efficiently How To Read Java: Understanding, debugging, and optimizing JVM applications teaches code investigation techniques that will help you understand how Java apps work, optimize them, and fix the bugs that break them. You'll go from the basics of debugging to advanced methods for locating problems in microservices architectures. Each new technique is explained with lively illustrations and engaging real-world examples. about the technology Tasks like searching for bugs, working through messy legacy code, and analyzing an application's readiness to support new features consume a lot of developer time. In fact, most developers spend more time trying to read and understand code than they do writing it! In this unique guide, you'll learn techniques like resolving deadlocks by examining thread dumps and locating memory leaks by inspecting the heap that will radically improve your efficiency when working with existing code in JVM languages like Java, Scala, and Kotlin.Trade Review"I have never seen a book on debugging as thorough as this book. Knowing more about the techniques listed in this book will make development more efficient for any developer." Becky Huett "This is a MUST-read book for any developer who is serious about debugging apps or software in general." Jean-Baptiste Bang Nteme "Vital in filling in a gap for the practicing programmer." Atul Shriniwas Khot

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Book SynopsisUnlike other books about assembly language and computer organisation, Introduction to Computer Organization is written with the understanding that most programmers will never have to write x86-64 assembly language or design hardware. By the end of the book readers should have a strong understanding of how binary is used to store data; how Boolean logic works, and how it's implemented in a computer; the basics of computer hardware; assembly language; program flow; and Input/Output.

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Book SynopsisA paper-based beginner-friendly workbook for students that teaches how to build a website - without the use of a computer. This is the perfect book for any beginner who finds it easier to engage with paper than with code on a computer screen. Also perfect for classrooms in socioeconomically disadvantaged areas that lack multiple computers or even reasonable Internet access. Numerous students can work simultaneously from this workbook then try their code on a shared computer either in the classroom or at home.Trade Review"It's a great workbook, and basically teaches people how to code without having to have a computer . . . it would be a great tool for people who don't have acess to a computer."—Sister Codes Podcast"A book you could actually hand to a kid and they could actually go through it . . . a workbook." —Kathy Nelson, Ordinarily Extraordinary Podcast"This workbook is everything you need to start coding, even without access to a computer. Sam took this complex, powerful skill and broke it down in ways that make it exciting and easy to learn. It is so organized and easy to understand, making it simple to follow along and apply the skills! The examples, practice activities, and self-checks are all engaging and relevant. I would recommend this to anyone who is learning to code and encourage educators to share this with their students (at any age!)." —Danielle Feeney, PhD, Assistant Professor of Instruction, Ohio UniversityTable of ContentsIntroductionPart I: HTMLPart II: CSSPart III: Applications/Exercises

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Book SynopsisLike the highly regarded first edition, this second edition of Understanding the Machine covers machine organisation and computer science topics like the CPU, machine architecture, memory and cache organisation, I/O and peripheral devices, and how the decoding and execution of machine instructions affects software performance. This edition has been updated to cover 64-bit machines, newer peripheral devices, larger memory systems, large-scale SSDs, and newer CPUs like those used in personal computers and tablets.Trade Review"Sooner or later it makes sense to get a grip on what happens underneath the interpreter and compiler, even below the abstraction layer that the operating system provides. . . . This book leads you a part of the way to this knowledge. In a clear and understandable writing that makes it a joy to read."—Thomas Manthey, Amazon ReviewerPraise for the first edition of Write Great Code, Volume 1:"Today's programmers can hardly keep up with the race against inhumane deadlines and new technologies; therefore, they rarely have a chance to learn the basics of computer architectures and the inner-working of their programming languages. This book fills in the gaps. I strongly recommend it." —InformIT.com Write Great Code "isn't your typical 'teach yourself to program' book. . . It's relevant to all languages, and all levels of programming experience. . . Run, don't walk, to buy and read this book." —Bay Area Large Installation System Administrators (BayLISA)5/5 stars: "[Write Great Code] fills in the blanks nicely and really could be part of a Computer Science degree required reading set... Once this book is read, you will have a greater understanding and appreciation for code that is written efficiently - and you may just know enough to do that yourself. At least you will have a great start at the art of crafting efficient software." —MacCompanion "Great fun to read." —VSJ Magazine "Write Great Code: Understanding the Machine should be on the required reading list for anyone who wants to develop terrific code in any language without having to learn assembly language." —WebServerTalkTable of ContentsChapter 1: What You Need to Know to Write Great CodeChapter 2: Numeric RepresentationChapter 3: Binary Arithmetic and Bit OperationsChapter 4: Floating-Point RepresentationChapter 5: Character RepresentationChapter 6: Memory Organization and AccessChapter 7: Composite Data Types and Memory ObjectsChapter 8: Boolean Logic and Digital DesignChapter 9: CPU ArchitectureChapter 10: Instruction Set ArchitectureChapter 11: Memory Architecture and OrganizationChapter 12: Input and OutputChapter 13: Computer Peripheral BusesChapter 14: Mass Storage Devices and FilesystemsChapter 15: Miscellaneous Input and Output DevicesAfterword: Thinking Low-Level, Writing High-LevelAppendix A: ASCII Character SetGlossary

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Book SynopsisDeep Learning for Complete Beginners: A Python-Based Introduction is for complete beginners in machine learning. It introduces fundamental concepts such as classes and labels, building a dataset, and what a model is and does before presenting classic machine learning models, neural networks, and modern convolutional neural networks. Experiments in Python - working with leading open-source toolkits and standard datasets - give the reader hands-on experience with each model and help them build intuition about how to transfer the examples in the book to their own projects.Trade Review"Practical Deep Learning with Python is the perfect book for someone looking to break into deep learning. This book achieves an ideal balance between explaining prerequisite introductory material and exploring nuanced subtleties of the methods described. The reader will come away with a solid foundational understanding of the content as well as the practical knowledge required to apply the methods to real-world problems. Deep learning will continue to enable many breakthroughs in artificial intelligence applications and this book covers all that is needed to springboard into this exciting field."—Matt Wilder, longtime neural network practitioner and owner of Wilder AI, a deep learning consulting company"Kneusel’s book tackles machine learning (classification) fantastically, helping anyone with an interest to learn and turning that interest into a skillset for future machine learning projects."–GeekDude, GeekTechStuffTable of ContentsForeword by Michael C. Mozer, PhDAcknowledgmentsIntroductionChapter 1: Getting StartedChapter 2: Using PythonChapter 3: Using NumPyChapter 4: Working With DataChapter 5: Building DatasetsChapter 6: Classical Machine LearningChapter 7: Experiments with Classical ModelsChapter 8: Introduction to Neural NetworksChapter 9: Training A Neural NetworkChapter 10: Experiments with Neural NetworksChapter 11: Evaluating ModelsChapter 12: Introduction to Convolutional Neural NetworksChapter 13: Experiments with Keras and MNISTChapter 14: Experiments with CIFAR-10Chapter 15: A Case Study: Classifying Audio SamplesChapter 16: Going FurtherIndex

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Book SynopsisIn Network Programming with Go readers learn how to leverage Go's concurrency and rich standard library to write robust network programs to create and handle network connections. Difficult concepts are explained with analogies, diagrammes, and examples as readers learn to solve common networking problems and write secure software. For professional developers and experienced Go programmers.Table of ContentsPart One: Network ArchitectureChapter 1: An Overview of Networked SystemsChapter 2: Domain Name Resolution and RoutingPart Two: Socket-Level ProgrammingChapter 3: Creating Reliable Data Streams with TCPChapter 4: Transmitting Data with TCPChapter 5: Simple and Unreliable UDPChapter 6: Ensuring UDP’s Reliability with TFTPChapter 7: UNIX Domain SocketsPart Three: Application-Level ProgrammingChapter 8: Writing HTTP ClientsChapter 9: Writing HTTP ServicesChapter 10: Creating a Custom HTTP/2 ServerChapter 11: Securely Traversing Untrusted NetworksPart Four: Service Architecture and the CloudChapter 12: Microservices and Data SerializationChapter 13: Structured Logging and MetricsChapter 14: Moving to the Cloud

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Book SynopsisDead Simple Python dives deep into the nuts and bolts of the Python programming language. It unpacks the technical 'whys' and 'hows' of the language's fundamental concepts and helps readers use these concepts to write idiomatic Python. Readers go from basics to project deployment in under 400 pages.Trade Review"An invaluable resource for those looking to learn the fundamentals of the Python programming language. . . . Dead Simple Python is an ideal choice for Python beginners who want to quickly advance from the bare basics to production-level coding."—Ben Lutkevich, TechTarget"Definitely a book that any Python programmer NEEDS to have on [their] bookshelf!"—Full Circle Magazine"Makes a good starting point for those contemplating a serious Python effort and who need to start with the basics."—Lee Teschler, Microcontroller Tips"The book that anyone who wants to become an expert Python programmer should read. . . . I don't believe that anyone who works through the material in this book will fail to become a competent and confident Python coder. It is quite a fantastic book."—Sandra Henry-Stocker, NetworkWorld"Reasonably paced and clear. . . . I expect that I’ll refer to the book the next time I start a small Python project."—Paul Floyd, ACCU"I especially enjoyed the practical approach to getting started with developing code using tools like virtual environments. It's a hefty book coming in at almost 700 pages but definitely worth adding to your library."—Paul Ferrill, freelancer for a variety of magazines and websitesTable of ContentsIntroductionPart 1: The Python EnvironmentChapter 1: The Python PhilosophyChapter 2: Your WorkbenchChapter 3: Syntax Crash CourseChapter 4: Project Structure and ImportsPart 2: Essential StructuresChapter 5: Variables and TypesChapter 6: Functions and LambdasChapter 7: Objects and ClassesChapter 8: Errors and ExceptionsPart 3: Data and FlowChapter 9: Collections and IterationChapter 10: Generators and ComprehensionsChapter 11: Text IO and Context ManagersChapter 12: Binary and SerializationPart 4: Advanced ConceptsChapter 13: Inheritance and MixinsChapter 14: Metaclasses and ABCsChapter 15: Inspection and GenericsChapter 16: Asynchrony and ConcurrencyChapter 17: Threading and ParallelismPart 5: Beyond the CodeChapter 18: Packaging and DistributionChapter 19: Debugging and AnalysisChapter 20: Testing and ProfilingChapter 21: The Parting of the WaysAppendix A: Special Attributes and MethodsAppendix B: Python Debugger (pdb) CommandsGlossary

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Book SynopsisAn accessible, visual, and creative approach to teaching Python programming using the Processing development environment. Readers learn the theoretical and technical workings of computer programming as they write code that produces intriguing and aesthetically-pleasing results. Based on a decade's worth of lecturing experience, the author covers what works best for those looking to learn programming fundamentals in a visual context.Trade Review"Learn Python Visually brings two very exciting threads together - using Python to code projects, and using Processing for making art. The book welcomes beginners by covering how to get started with the basics like shapes and color but extends the learning far by covering complex topics like object-orientation in an accessible fashion. I am excited to see what students, teachers, artists, anyone can make using this book."—Saber Khan, Education Community Director, Processing Foundation"Learn Python Visually might be one of the most creatively-minded, practical introductions to basic programming, presented in a rewarding environment, using a highly relevant language. . . . Its modern design is easy to follow and it finds a nice balance between being educational, and inspirational." —Dr. Rer. Nat. Ralf Biedert, Principal Engineer, Tobii AB"The sample programs are nicely selected and each deal with a different topic . . . [provides] the necessary detail, but still compact. I believe Learn Python Visually will be a rich source of inspiration."—Alfred Abusomwan, Techs BlogTable of ContentsAcknowledgmentsIntroductionChapter 1: Hello, World!Chapter 2: Drawing More Complicated ShapesChapter 3: Introduction to Strings and Working with TextChapter 4: Conditional StatementsChapter 5: Iteration and RandomnessChapter 6: Motion and TransformationChapter 7: Working with Lists and Reading DataChapter 8: Dictionaries and JSONChapter 9: Functions and Periodic MotionChapter 10: Object-Oriented Programming and PVectorChapter 11: Mouse and Keyboard InteractionAfterword

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Book SynopsisRandall Hyde's The Art of Assembly Language has been the go-to book for learning assembly language for decades. Hyde's latest work, Art of 64-bit Assembly Language is the 64-bit version of this popular text. This book guides you through the maze of assembly language programming by showing how to write assembly code that mimics operations in High-Level Languages. This leverages your HLL knowledge to rapidly understand x86-64 assembly language.Table of ContentsIntroductionChapter 1: Hello, World of Assembly LanguageChapter 2: Data Representation and OperationsChapter 3: Memory Access and OrganizationChapter 4: Constants, Variables, and Data TypesChapter 5: Procedures and ModulesChapter 6: ArithmeticChapter 7: Low-Level Control StructuresChapter 8: Advanced ArithmeticChapter 9: Numeric ConversionChapter 10: Table LookupsChapter 11: SIMD InstructionsChapter 12: Bit ManipulationChapter 13: Macros and the MASM Compile-Time LanguageChapter 14: The String InstructionsChapter 15: Managing Complex ProjectsChapter 16: Standalone Assembly Language ProgramsA: ASCII Character SetB: GlossaryC: Installing and Using Visual StudioD: The Windows Command-Line InterpreterE Answers to Questions

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Book SynopsisThe go-to dictionary (and encyclopedia) for crypto novices and experts alike. It covers technical terms found in modern software analysis, such as 'block cipher,' while providing context for historical references like the 'crypto wars,' sharing amusing anecdotes (ever hear of the 'Hasty Pudding Cipher'?), and describing major conferences in the field, including Eurocrypt and Real World Crypto. Includes descriptions of the field's most innovative techniques, like threshold cryptography, as well as those developed in the context of blockchain applications, in a broadly approachable way.Trade Review"Aumasson includes his own observations and editorial comments in the entries, which makes for a more interesting read than most dictionaries. . . . Readers also can use the dictionary for a crash course in the field and assemble a reading list of important texts." —Veronica Combs, Tech Republic"An opinionated mix of witty definitions, mentions of niche cryptographic constructions and obscure algorithms, historical curiosities, and cryptography nerd jokes . . . As written in its introduction, Crypto Dictionary is meant to be an entertaining read, so that 'any reader can open the book at a random page and discover a yet unknown notion, excavate an obscure concept, or read an anecdote about a familiar term.', and it perfectly fulfils this role." —Julien Voisin, Dustri.org"In terms of usefulness, I think Crypto Dictionary has definitely earned its place on my bookshelf next to Serious Cryptography. I can confidently say that I will be coming back to Crypto Dictionary over time as a starting point for researching 'new-to-me' concepts in cryptography. I would highly recommend this book to anyone with a general interest in cryptography or needing a basic guide to ‘translate’ crypto jargon to English."—Craig Young, Principal Security Researcher, Tripwire

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Book SynopsisThis fun, hands-on book will take your basic Python skills to the next level as you build voice-controlled apps to use in your daily life. Starting with a Python refresher and an introduction to speech-recognition/text-to-speech functionalities, you'll soon ease into more advanced topics, like making your own modules and building working voice-controlled apps. Each chapter scaffolds multiple projects that allow you to see real results from your code at a manageable pace, while end-of-chapter exercises strengthen your understanding of new concepts.Trade Review"Everything you need to build a voice interface to the digital world. Voice is a critical part of the coming metaverse and Dr. Liu helps us take this leap."—Shane Hadden, Financial Technology Lecturer, University of Kentucky"A solid book for anyone who wants to leverage the power of the Python programming language to add speech capabilities to their programs . . . Make Python Talk presents these speech software libraries with clarity and ease."—Al Sweigart, best-selling author of Automate the Boring Stuff with Python and many other No Starch Press titlesTable of ContentsIntroductionPart I: Getting StartedChapter 1: Install Python via Anaconda and SpyderChapter 2: Python RefresherPart II: Learning to TalkChapter 3: Speech RecognitionChapter 4: Make Python TalkChapter 5: Speaking ApplicationsChapter 6: Web Scraping Podcasts, Radios, and VideosChapter 7: Building a Virtual Personal AssistantChapter 8: Know-it-all VPAPart III: Interactive GamesChapter 9: Graphics and Animation with the turtle ModuleChapter 10: Tic-Tac-ToeChapter 11: Connect FourChapter 12: guess-the-word GameChapter 13: Smart Games: Adding IntelligencePart IV: Going FurtherChapter 14: Financial ApplicationsChapter 15: Stock Market WatchChapter 16: Use Other Languages: TranslatorChapter 17: Ultimate VPAAppendix A: Useful Speech ModulesAppendix B: Answers to End of Chapter ExercisesIndex

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Book SynopsisWritten for professional programmers or CS students, this book skips the stuff you don't need and keeps a laser focus on the C# type system. It explains not just what value types and reference types are, but why and how they behave as they do. In particular, by learning the underappreciated benefits of value types, you'll quickly be able to optimize the performance of your applications. The book also offers numerous real-world examples and detailed explanations of targeted techniques, best practices, and common pitfalls. You'll progress from simply writing runnable programs using correct C# syntax to developing modern, idiomatic, and efficient applications that take full advantage of C#'s highly scalable type system.Trade Review"A detailed analysis of low-level aspects of C# and .NET memory management and performance."—Jon Skeet, Senior Staff Engineer at Google and Convenor of the ECMA Technical Group for C# Standardization"Exceptionally 'user friendly' in organization and presentation, The C# Type System is the ideal DIY instruction manual that is unreservedly recommended for novice users and seasoned programmers alike."—Midwest Book ReviewTable of ContentsIntroductionChapter 1: Making the Most of the Type SystemChapter 2: Value and Reference TypesChapter 3: Reference and Value ParametersChapter 4: Implicit and Explicit CopyingChapter 5: Types of EqualityChapter 6: The Nature of ValuesChapter 7: Value Types and PolymorphismChapter 8: Performance and EfficiencyAfterwordAppendix: Further ReadingIndex

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Book SynopsisA Graphical Introduction to Programming teaches computer programming with the aid of 100 example programs, each of which integrates graphical or sound output. The Processing-language-based examples range from drawing a circle and animating bouncing balls to 3D graphics, audio visualization, and interactive games

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Book SynopsisThis book introduces fundamental concepts software developers need to know to flourish in a modern DevOps environment including infrastructure as code, configuration management, security, containerization and orchestration, monitoring and alerting, and troubleshooting. Readers will follow along with hands-on examples to learn how to tackle common DevOps tasks.Trade Review"DevOps for the Desperate is a short, approachable guided tour of a few core tools in the software operations toolkit. Structured as a set of hands-on tutorials in topics like system administration basics, configuration tools like Ansible and Vagrant, and orchestration tools like Kubernetes, this book covers a lot of ground quickly. The focus is very much on the practical, rather than the philosophy of DevOps. Don't expect to use this as your sole reference on DevOps topics, but this is worthwhile as a gentle starting point for the absolute beginner to software operations." —Laura Nolan, Slack "A very useful book. . . . it would give any competent developer a good grasp of how to use the tools commonly found in DevOps. Recommended."—Kay Ewbank, I-Programmer"Zero-to-hero in one guide."—td, Amazon Reviewer

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Book SynopsisEcosystems and Technology: Idea Generation and Content Model Processing, presents important new innovations in the area of management and computing. Innovation is the generation and application of new ideas and skills to produce new products, processes, and services that improve economic and social prosperity. This includes management and design policy decisions and encompasses innovation research, analysis, and best practice in enterprises, public and private sector service organizations, government, regional societies and economies. The book, the first volume in the Innovation Management and Computing book series, looks at technology that improves efficiency and idea generation, including systems for business, medical/health, education, and more. The book provides detailed examples to provide readers with current issues, including Venture planning for innovations New technologies supporting innovations systems Competitive business modeling Context-driven innovation modeling The generation of ideas faster The measurement of relevant data Virtual interfaces Business intelligence and content processing Predictive modeling Haptic expression and emotion recognition innovations, with applications to neurocognitive medical science This book provides a wealth of information that will be useful for IT and business professionals, educators, and students in many fields.Table of ContentsTechnology Selection for Software Startups. Innovation Ecosystems and Technology. Self-Organizing Coordination and Control Approaches: The Impact of Social Norms on Self-Regulated Innovation Activities in Self-Managing Teams. Digital Opportunities for First-Year University Students’ Motivational Enhancement. Building a Successful Innovation Platform for Affordable Medical Technology in Low Resource Settings. Soft-Factors Enabling Innovation. IoT and M.E.S.: Are You Ready for the Next Industrial Revolution?. A Structured Process to Generate Ideas in Med Tech. Logic-Based Medicine versus Evidence-Based Medicine for Modeling Qualified-Self Health Kits. Virtual Mobile Interfaces, Business Intelligence, and Analytics Content Processing. A Haptic Computing basis for Facial or Visual Emotion Expression Recognition.

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Book SynopsisAndrew Smith has worked as a critic and feature writer for the Sunday Times, the Guardian, the Observer and The Face, and has penned documentaries for the BBC. He is the author of the internationally bestselling book Moondust, about the nine remaining men who walked on the moon between 1969 and 1972, and Totally Wired. He was raised in the UK and currently lives in California.

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Book SynopsisDESCRIPTION Cloud Computing is here to stay. As an economically viable way for businesses of all sizes to distribute computing, this technology shows tremendous promise. But the intense hype surrounding the Cloud is making it next to impossible for responsible IT managers and business decision-makers to get a clear understanding of what the Cloud really means, what it might do for them, when it is practical, and what their future with the Cloud looks like. The Cloud at Your Service helps cut through all this fog to help enterprises make these critical decisions based on facts and the authors’ informed unbiased recommendations and predictions. KEY POINTSF • Highly readable approach.F • Cuts through the hype.F • Helps managers make decisions.F • Practical guidance on working in the Cloud.

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Book SynopsisKapitel 1. Grundlegende Operationen.- Kapitel 2. Datenverarbeitung.- Kapitel 3. Daten visualisieren.- Kapitel 4. Programmierung.- Kapitel 5. Ein besserer Klang.- Kapitel 6. Bilder erstellen und verarbeiten.- Kapitel 7. Datenanalyse.- Kapitel 8. Der Reiz grafischer Benutzeroberflächen.- Kapitel 9. Psychtoolbox: Video.- Kapitel 10. Psychtoolbox: Ton, Tastatur und Maus.- Kapitel 11. Verbindung mit externen Geräten.- Kapitel 12. Praktisches Schreiben von Experimenten.

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Book SynopsisPython ist eine der beliebtesten und vielseitigsten Programmiersprachen überhaupt. Für viele Entwickler führt deshalb kein Weg an Python vorbei. Schöpfen Sie mit diesem Buch aus dem reichen Erfahrungsschatz zweier langjähriger Softwareentwickler. Sie lernen zunächst die Syntax der Sprache und vertiefen dann das Erlernte anhand von konkreten Aufgabenstellungen. Für den Blick über den Tellerrand sorgen Kapitel zu Programmierparadigmen, Code-Qualität, Test-Ansätzen und Dokumentation. Jede Menge Tipps und Tricks und ein breites Spektrum an Beispielen lassen Sie zu einem wahren Python-Profi werden.Table of ContentsÜber die Autoren 11 Einleitung 23 Törichte Annahmen über den Leser 23 Wie Sie dieses Buch nutzen können 23 Was Sie nicht lesen müssen 24 Wie dieses Buch aufgebaut ist 24 Symbole, die in diesem Buch verwendet werden 25 Konventionen in diesem Buch 26 Teil I: Langweilige Einmallektüre 27 Kapitel 1 Orientierung 29 Motivation 29 Was ist Python? 29 Warum sollte ich Python lernen? 29 Was ist an Python so besonders? 30 Seit wann gibt es Python? 30 Warum ist Python weniger verbreitet als andere Sprachen? 31 Welche Sprachfeatures bringt Python mit? 31 Ist Python eine Skript- oder eine Programmiersprache? 32 Ich habe gehört, dass Python langsam ist Stimmt das? 32 Anwendungsgebiete 33 Wer verwendet Python? 33 Kann man mit Python Geld verdienen? 33 Was kann ich mit Python machen? 33 Sollte ich nicht doch lieber eine andere Sprache lernen? 34 Kapitel 2 Im Kriechgang – die Installation 35 Windows 35 Schritt 1 – Herunterladen 36 Schritt 2 – Installieren 37 Schritt 3 – Läuft’s? 39 macOS 40 Schritt 1 – Herunterladen 40 Schritt 2 – Installieren 41 Schritt 3 – Läuft’s? 44 Alternative: Homebrew 44 Linux 45 Einer für alle 46 Kapitel 3 Der Schlange Beine machen – Python ausführen 49 Der REPL 49 Editor oder IDE? 50 Teil II: Python sprechen lernen 53 Kapitel 4 Hic forum est – Schnellkurs 55 Vogelperspektive 56 Das kleinste Python-Programm der Welt 59 Zeichenketten und Bildschirmausgabe 60 Rechnen mit Python 63 Variablen 66 Wahrheitswerte und bedingte Ausführung 69 Boolesche Logik in Python 69 Truthy und Falsy 71 Wenn – Dann – Sonst 72 Listen und Schleifen 74 Funktionen und Module 77 Funktionen definieren und aufrufen 78 Module nutzen 79 Fehlerbehandlung 80 Kapitel 5 Daten strukturieren 85 Listen 86 Listen anlegen 86 Was steckt drin? 86 Listen verändern 88 Listen sortieren 89 Absteigend oder aufsteigend sortieren? 90 Tupel 91 Einpacken 91 Entpacken 92 Tupel verändern 94 Tupel sortieren 95 Wann Sie Listen und wann Tupel verwenden sollten 95 Dictionarys 96 Dictionarys anlegen 97 Was steckt drin? 98 Dictionarys verändern 99 Sets 100 Sets anlegen 101 Was steckt drin? 101 Sets verändern 102 Mengenlehre 104 Kapitel 6 Daten transformieren 109 Iteration 109 Comprehensions 112 Syntax 112 List Comprehensions 114 Dictionary Comprehensions 115 Set Comprehensions 116 Generator Expressions 117 Slicing 120 Ein einziges Element 121 Mehrere Elemente 122 Schrittweise Auswahl 122 Beispiel: IBAN validieren 123 Iteration ohne Index 125 FAQ – Leben ohne Index 127 Nur ein Element 128 Nummerierung 128 Listen zusammenführen 129 Listen zerteilen 129 Dictionarys erzeugen 130 Dictionarys iterieren 131 Verschachtelte Iteration 131 Kapitel 7 Mit der Außenwelt kommunizieren 133 Selbstgespräche führen 134 Text ausgeben 134 Text einlesen 135 Textausgabe steuern 136 Längere Texte zusammenbasteln 137 Texte formatieren 137 Textkodierung 140 Kommandozeilenparameter 140 Textdateien einlesen 142 Im Ganzen lesen 142 Zeilenweise lesen 143 Textdateien schreiben 146 Dateimodi: Behalten oder neu machen? 146 Im Ganzen schreiben 147 Zeilenweise schreiben 148 Vollständiges Beispiel 149 Alles fließt 150 Bin∖xc3∖xa4rdaten lesen 152 Im Ganzen lesen 153 Häppchenweise lesen 154 Binärdaten schreiben 158 Teil III: Mit Python Probleme lösen 161 Kapitel 8 Was Python schon kann 163 Built-ins 163 Built-ins für den REPL 165 Umwandlungsfunktionen 166 Mathematische Funktionen 171 Mengen aggregieren 172 Daten transformieren 173 Module und Pakete 175 Module importieren 176 Direktimporte 176 Aus Paketen importieren 177 Namenskonflikte verhindern 177 Import mit Wildcard – Alle für einen 178 Die Standardbibliothek 179 Im Lieferumfang enthalten sind 180 os – Welches Betriebssystem läuft? 180 random und secrets – Zufall 183 imaplib – E-Mails versenden 184 urllib und json – Web 186 Minisprachen 187 Datum- und Zeitangaben 187 Strings formatieren 192 Kapitel 9 Was Python (noch) nicht kann 197 Pip installieren 197 Pakete installieren 198 Installierte Pakete ansehen 199 Spezifische Versionen installieren 199 Pakete entfernen 200 Kapitel 10 Was Sie Python beibringen können 201 Eigene Module 201 Eigene Module anlegen 202 Eigene Pakete 202 Eigene Skripte 204 Hintergrund: Wie Module geladen werden 206 Wo sucht Python Module? 206 Module Laden 207 Teil IV: Python als Handwerk 209 Kapitel 11 Funktionale Programmierung 211 Anatomie einer Funktion 212 Definition 212 Aufruf 212 Namen und Konzepte 213 Effekte und Nebeneffekte 213 Positionale Argumente 214 Benannte Argumente 215 Regeln für Funktionsaufrufe aufstellen 216 Optionale Argumente 219 Variable Argumente mit *args und **kwargs 222 Argumente entpacken 225 Funktionen haben »Bürgerrechte« 226 Funktionen zusammenstecken 227 Arbeitsteilung 229 Funktionen, die Funktionen erzeugen 232 Dekoratoren 233 Generatoren 235 Kapitel 12 Objektorientierte Programmierung 239 Anatomie eines Objekts 240 Objekte 241 Klassen und Konstruktoren 241 Attribute und Methoden 242 Instanzen 246 Operatoren 248 Beziehungen 252 Vererbung – Objekte als Familie 253 Komposition – Objekte im Team 263 In Objekten denken 270 Was ist eigentlich objektorientierte Programmierung? 271 Wie man gute Objekte designt 273 Kapitel 13 Ausnahmen 279 Ausnahmen behandeln 281 Eigene Ausnahmen auslösen 282 Ausnahmen als Signale nutzen 283 Beispiel: Hotels buchen 285 Kapitel 14 Testen 295 Wenn Ihr Programm nicht tut, was es soll 296 Eigenschaften von Python 296 Fehlerklassen (oder: Was alles schief gehen kann) 298 Wo und wie Tests helfen können 300 Python bei der Arbeit zuschauen 301 Debuggen mit print 301 Bedingungen prüfen mit assert 302 Den Programmfluss kontrollierbar machen 303 Unit-Tests schreiben mit dem unittest-Modul 305 Unit-Tests erstellen und ausführen 306 Bestehende Komponenten testen 309 Teil V: Brötchen (oder Lorbeeren) mit Python verdienen 313 Kapitel 15 Code-Qualität 315 Werkzeuge 316 Programmstil überprüfen mit Pycodestyle 317 Code reformatieren 319 Programmierfehler erkennen mit Pyflakes 321 Dokumentation überprüfen mit Pydocstyle 323 Sicherheitsrisiken finden mit Bandit 326 Integrierte Code-Audits 328 Modulare Audits mit Flake8 329 Das Schweizer Taschenmesser: Pylint 333 Chancen und Grenzen 335 Listen to your tools 335 Was Werkzeuge nicht leisten können 337 Kapitel 16 Webanwendungen entwickeln 339 Python und das Web 339 Die Qual der Wahl 340 Django 340 Was macht Django? 341 Wie Django HTTP-Anfragen verarbeitet 342 Ein Beispielprojekt 343 Schritt 1 – Setup 344 Schritt 2 – Die erste Seite 344 Schritt 3 – Ein Modell 348 Schritt 4 – Die Django-Verwaltung 350 Schritt 5 – Eine eigene View 353 Schritt 6 – HTML rendern 354 Zusammenfassung 355 Kapitel 17 Daten aufbereiten, visualisieren und auswerten 357 Setup 358 Szenario: Minigolf 358 Datensatz 359 Schritt 0 – Fragen 361 Schritt 1 – Daten einlesen 362 Schritt 2 – Data Frames untersuchen 362 Schritt 3 – Series-Objekte betrachten 364 Schritt 4 – Beschreibende Statistiken ausgeben 365 Schritt 5 – Filtern und Bereinigen 367 Schritt 6 – Auswerten 369 Schritt 7 – Visualisieren 371 Schritt 8 – Schließende Statistik 372 Zusammenfassung 373 Teil VI: Der Top-Ten-Teil 375 Kapitel 18 Zehn gute Bibliotheken 377 Die Standardbibliothek 377 Requests 377 BeautifulSoup 378 Scrapy 378 Selenium 379 Cryptography 379 Pypdftk 380 Flask 380 OpenCV 380 NLTK 381 Kapitel 19 Zehn Dinge, die wir ausgelassen haben 383 Python 2.7 383 Interoperabilität mit C 384 Python Bytecode disassemblieren 384 Debugging 385 Logging 385 GUIs 386 Nebenläufige Ausführung 387 Typ-Annotationen 387 Dataclasses 388 Walross-Operator 389 Stichwortverzeichnis 393

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