Search results for "introduction to python programming"
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Python Automation For Dummies
Streamline Your Workflow and Boost Productivity with Python Automation In today's workplaces, there's a high demand for know-how on the Python programming language, especially for writing time-saving scripts that can simplify routine work tasks. Python Automation For Dummies delivers, with simple explanations of how you can use Python to automatically wrangle data files, manage media files, create shortcuts, find and organize web data, and even analyze social media for trends. With this easy-to-follow Dummies guide, you can upskill, expand your productivity, and speed up the process of generating data-driven insights. You'll even learn to enhance your Python automations with AI, for workflows that are faster and smarter. Review the basics of Python coding and follow steps for automating all sorts of tasksManage large file sets, organize and analyze data, and speed up research processesAutomate scheduling and other time-consuming tasks—and optimize work with AIFree up time and resources by automating routine work, so you can foucs on more important issues This is a great Dummies resource for Python developers interested in applying the popular coding language to make workflows more efficient.
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Introduction to Parallel Programming
An introduction to parallel programming with openmpi using C. It is written so that someone with even a basic understanding of programming can begin to write mpi based parallel programs.
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Expert Python Programming -
Become an ace Python programmer by learning best coding practices and advance-level concepts with Python 3.5About This Book• Based on the latest stable version of Python (version 3.5)• Creating well manageable code that will run in various environments with different sets of dependencies• Packed with advanced concepts and best practices to write efficient Python codeWho This Book Is ForThe book would appeal to web developers and Python programmers who want to start using version 3.5 and write code efficiently. Basic knowledge of Python programming is expected.What You Will Learn• Conventions and best practices that are widely adopted in the python community• Package python code effectively for community and production use• Easy and lightweight ways to automate code deployment on remote systems• Improve your code's quality, reliability, and performance• Write concurrent code in python• Extend python with code written in different languagesIn DetailPython is a dynamic programming language, used in a wide range of domains by programmers who find it simple, yet powerful. Even if you find writing Python code easy, writing code that is efficient and easy to maintain and reuse is a challenge.The focus of the book is to familiarize you with common conventions, best practices, useful tools and standards used by python professionals on a daily basis when working with code.You will begin with knowing new features in Python 3.5 and quick tricks for improving productivity. Next, you will learn advanced and useful python syntax elements brought to this new version. Using advanced object-oriented concepts and mechanisms available in python, you will learn different approaches to implement metaprogramming. You will learn to choose good names, write packages, and create standalone executables easily.You will also be using some powerful tools such as buildout and vitualenv to release and deploy the code on remote servers for production use. Moving on, you will learn to effectively create Python extensions with C, C++, cython, and pyrex. The important factors while writing code such as code management tools, writing clear documentation, and test-driven development are also covered.You will now dive deeper to make your code efficient with general rules of optimization, strategies for finding bottlenecks, and selected tools for application optimization.By the end of the book, you will be an expert in writing efficient and maintainable code.Style and approach An easy-to-follow guide that covers industry followed best practices in Python programming
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Computer Science From Scratch
Computer science can feel unapproachable for those without a formal CS education. Fun Computer Science Projects in Python pulls back that curtain, illuminating several foundational CS concepts through creative, hands-on projects. Each of the 7 projects is presented in a code-centric tutorial that gently introduces topics like interpreters, emulators, and machine learning without getting bogged down by complex theory. The projects showcase advanced Python language features and clean code principles while exploring interesting algorithms. Chapters conclude with discussions of real-world applications of the topic and proposed exercises to extend the reader's skills. Covers Python 3.x
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Theoretical Introduction to Programming
Including easily digested information about fundamental techniques and concepts in software construction, this book is distinct in unifying pure theory with pragmatic details. Driven by generic problems and concepts, with brief and complete illustrations from languages including C, Prolog, Java, Scheme, Haskell and HTML.This book is intended to be both a how-to handbook and easy reference guide. Discussions of principle, worked examples and exercises are presented. All concepts outside introductory programming are explained with clear demarcation and dependencies so the experienced programmer can quickly locate material. Readable in a linear manner, with short mono-thematic to encourage dipping and reference. Also included are sections on open problems in software theory and practice.While little other than a novice programmer's knowledge is explicitly assumed, a certain conceptual maturity, either through commercial programming or academic training is required – each language is introduced and explained briefly as needed.
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Bioinformatics Programming Using Python
Through many examples and exercises, this book helps simplify bioinformatics programming using Python. It's an ideal guide for biologists who want to learn either basic scripting or substantial programming for various computational tasks, and for programmers who want to learn bioinformatics programming. "Bioinformatics Programming Using Python" can be used as a reference, for self-instruction, or as a companion book to help you through undergraduate courses in computer science, biology, and other life sciences. With the level of detail this book provides, it's also perfect for Professional Master's graduate courses in Bioinformatics.
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Python for Engineers and Scientists
This book equips technical professionals with a complete, structured path to mastering Python for real-world engineering and scientific applications. As Python becomes central to research labs, automation, simulation, and data-driven engineering, the learning curve remains steep. This book bridges that gap with a practical roadmap from fundamentals to professional-grade scientific computing.The book begins by building a strong programming foundation—covering Python’s architecture, essential syntax, data structures, modules, functions, control flow, and object-oriented design. Readers learn not only how to write Python, but why the language behaves the way it does, ensuring deep understanding and strong problem-solving skills. From there, the focus shifts to practical engineering tools. Dedicated chapters train readers in file handling, math modules, and key scientific libraries including NumPy, SciPy, Pandas, and Matplotlib, enabling efficient computation, signal processing, data analysis, and high-quality visualization. Advanced chapters then showcase Python’s versatility through GUI development with Kivy, database work with SQLAlchemy, and hands-on control system modeling and analysis. Each topic is rooted in industry and academic scenarios, making the content directly applicable to automation, simulation, data workflows, and engineering computation.Whether you're a student building foundational skills or a professional modernizing engineering workflows, this guide provides the programming depth, scientific tools, and applied knowledge needed to use Python confidently for prototyping, simulation, analysis, and automation. It is the one-stop resource for mastering Python in technical disciplines.What you will learn:Learn core Python programming concepts, including variables, loops, functions, and object-oriented principles in a scientific and engineering context.Build strong skills in key scientific Python libraries such as NumPy, Pandas, Matplotlib, and SciPy for computation, analysis, and visualization.Apply Python to real-world engineering scenarios, including dynamic control systems and automation workflows.Develop interactive engineering applications by creating graphical user interfaces (GUIs) with Kivy. Who this book is for:This book is intended for practicing engineers and scientists across various disciplines of engineering who need to use Python for complex problem-solving, simulation, and data analysis in their work.
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Python Programming for Mathematics
Python Programming for Mathematics focuses on the practical use of the Python language in a range of different areas of mathematics. Through fifty-five exercises of increasing difficulty, the book provides an expansive overview of the power of using programming to solve complex mathematical problems.This book is intended for undergraduate and graduate students who already have learned the basics of Python programming and would like to learn how to apply that programming skill in mathematics.FeaturesInnovative style that teaches programming skills via mathematical exercises.Ideal as a main textbook for Python for Mathematics courses, or as a supplementary resource for Numerical Analysis and Scientific Computing courses.
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Introduction to Programming with ActionScript 3.0
This new full-color, multimedia-focused text provides a CS1 level introduction to computer programming by employing an example-based methodology involving animation, sound, graphics, and interactivity. As the multimedia language associated with Adobe� Flash�, ActionScript 3.0 offers a more compelling introduction to the world of programming than other standard programming languages, yet is powerful and comprehensive enough to provide a complete introduction to all the foundational concepts. By using the Flash environment, this book presents programming concepts that are relevant to multimedia-focused games and applications and is the ideal resource for those interested in building visually rich and interactive applications.An Introduction to Programming with ActionScript 3.0 satisfies ACM guidelines for a first course in a computer science curriculum and covers all of the key topics required for any introductory level programming course: program analysis and design, data types, selective and iterative control structures, functions, arrays, and classes. In addition, it covers ActionScript’s powerful ability to construct complex and interactive animations using graphics and sounds. Through programming, this text exposes readers to the problem solving and critical thinking skills required for effective participation in the digital world.An Introduction to Programming with ActionScript 3.0 is ideal for students interested in learning crucial programming concepts for which technology, arts, and media converge. It is also highly recommended for multimedia programmers, interactive artists, game designers, and innovative web application developers.Download the latest version of Flash here: https://get.adobe.com/flashplayer/Preview Content Now! Look to the Samples tab below to preview chapter 5
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Competitive Programming in Python
Want to kill it at your job interview in the tech industry? Want to win that coding competition? Learn all the algorithmic techniques and programming skills you need from two experienced coaches, problem setters, and jurors for coding competitions. The authors highlight the versatility of each algorithm by considering a variety of problems and show how to implement algorithms in simple and efficient code. Readers can expect to master 128 algorithms in Python and discover the right way to tackle a problem and quickly implement a solution of low complexity. Classic problems like Dijkstra's shortest path algorithm and Knuth-Morris-Pratt's string matching algorithm are featured alongside lesser known data structures like Fenwick trees and Knuth's dancing links. The book provides a framework to tackle algorithmic problem solving, including: Definition, Complexity, Applications, Algorithm, Key Information, Implementation, Variants, In Practice, and Problems. Python code included in the book and on the companion website.
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Introduction to Programming Using Visual Basic
For courses in Visual Basic Programming From the Beginning: A Comprehensive Introduction to Visual Basic Programming Schneider’s Introduction to Programming Using Visual Basic, Tenth Edition brings continued refinement to a textbook praised in the industry since 1991. A favorite for both instructors and students, Visual Basic 2015 is designed for readers with no prior computer programming experience. Schneider introduces a problem-solving strategy early in the book and revisits it throughout allowing you to fully develop logic and reasoning. A broad range of real-world examples, section-ending exercises, case studies and programming projects gives you a more hands-on experience than any other Visual Basic book on the market. The Tenth Edition keeps the pace with modern programming methodology while incorporating current content and practices. Each chapter is rich yet concise due to to the author’s focus on developing chapters around crucial subjects rather than covering too many topics superficially. The amount and the range of projects provided in the text offer flexibility to adapt the course according to the interests and abilities of the readers. Some programming projects in later chapters can be assigned as end-of-the-semester projects. Also available with MyProgrammingLabTM. MyProgrammingLab is an online learning system designed to engage students and improve results. MyProgrammingLab consists of a set of programming exercises correlated to specific Pearson CS1/Intro to Programming textbooks. Through practice exercises and immediate, personalized feedback, MyProgrammingLab improves the programming competence of beginning students who often struggle with the basic concepts of programming languages. Interactive Practice providesfirst-hand programming experience in an interactive online environment.Error Messages for Incorrect Answers give studentsimmediate personalized feedback. The error messages include both the feedback from the compiler and plain English interpretations of likely causes for the incorrect answer.Step-by-step VideoNote Tutorials enhance the programming concepts presented in your Pearson textbook by allowing students to view the entire problem-solving process outside of the classroom–when they need help the most.Pearson eText gives students access to their textbook anytime, anywhere. In addition to note taking, highlighting, and bookmarking, the Pearson eText offers interactive and sharing features. Rich media options let students watch lecture and example videos as they read or do their homework. Instructors can share their comments or highlights, and students can add their own, creating a tight community of learners in your class.The Pearson eText companion app allows existing subscribers to access their titles on an iPad or Android tablet for either online or offline viewing.Dynamic grading and assessment provide auto-grading of student assignments, saving you time and offering students immediate learning opportunities:
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Introduction to Modern Scientific Programming and Numerical Methods
The ability to use computers to solve mathematical relationships is a fundamental skill for anyone planning a career in science or engineering. For this reason, numerical analysis is part of the core curriculum for just about every undergraduate physics and engineering department. But for most physics and engineering students, practical programming is a self-taught process.This book introduces the reader not only to the mathematical foundation but also to the programming paradigms encountered in modern hybrid software-hardware scientific computing. After completing the text, the reader will be well-versed in the use of different numerical techniques, programming languages, and hardware architectures, and will be able to select the appropriate software and hardware tool for their analysis.It can serve as a textbook for undergraduate courses on numerical analysis and scientific computing courses within engineering and physical sciences departments. It will also be a valuable guidebook for researchers with experimental backgrounds interested in working with numerical simulations, or for any new personnel working in scientific computing or data analysis.Key Features:• Includes examples of solving numerical problems in multiple programming languages, including MATLAB, Python, Fortran, C++, Arduino, Javascript, and Verilog.• Provides an introduction to modern high-performance computing technologies including multithreading, distributed computing, GPUs, microcontrollers, FPGAs, and web "cloud computing".• Contains an overview of numerical techniques not found in other introductory texts including particle methods, finite volume and finite element methods, Vlasov solvers, and molecular dynamics.Companions websites for this book can be accessed at https://plasmasimulationsbyexample.com/ and https://www.scientificprogrammingbook.com/.Lubos Brieda holds a Ph.D. in Aerospace and Mechanical Aerospace Engineering from the George Washington University in Washington, D.C., USA and an M.Sc. in Aerospace and Ocean Engineering from Virginia Tech in Blacksburg, VA, USA. He is the president of Particle in Cell Consulting, LLC, Westlake Village, CA, USA, while also serving as a part-time lecturer in the Department of Astronautical Engineering at University of Southern California, Los Angeles, CA. Dr. Brieda is the author of numerous simulation codes utilized by the aerospace and plasma modeling communities. Additionally, he maintains an online blog found at particleincell.com/blog focusing on scientific computing and since 2014 he has been teaching online courses on plasma simulations through his website.Joseph Wang is a Professor of Astronautics and Aerospace and Mechanical Engineering at the University of Southern California. Prof. Wang received his Ph.D in Aeronautics and Astronautics from Massachusetts Institute of Technology in 1991. Prof. Wang conducts research in computational physics, space technology, and space and planetary science. He and his students have
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Asynchronous Programming in Python
Take a practical journey through the core principles, concepts, and applications of asynchronous programming in Python across real-world environments and technologies.Key FeaturesUnderstand core principles and theory behind async programming in PythonMeasure the impact of async techniques in practical, real-world use casesApply async patterns in software design and data-oriented architecturesBook DescriptionAsynchronous programming is one of the most effective but often misunderstood techniques for building fast, scalable, and responsive systems in Python. While it can significantly improve performance, efficiency, and sustainability, using async without a clear understanding of its trade-offs can lead to fragile designs and hard-to-debug issues.This book offers a structured approach to applying asynchronous programming in Python. It begins with a conceptual framework to help you distinguish between synchronous and asynchronous execution models, and shows how async relates to other concurrency strategies such as multithreading and multiprocessing. From there, you will explore the core tools available for building async applications in Python.You will also learn how to measure the impact of async programming in practical scenarios, profile and debug asynchronous code, and evaluate performance improvements using real-world metrics. The final chapters focus on applying async techniques to common cloud-based systems, such as web frameworks, database interactions, and data-pipelines tools.Designed for developers looking to apply async programming with confidence, this book blends real-world examples with core concepts to help you write efficient, maintainable Python code.What you will learnUse generators, coroutines and async/await to build scalable Python functionsExplore event loops to manage concurrency and orchestrate async flowCompare concurrency models to choose the right async strategyOptimize I/O-intensive programs to improve system throughput and efficiencyBuild async services using real-world APIs and popular Python librariesApply structured concurrency and design patterns for cleaner async designTest and debug async Python code to ensure reliability and stabilityWho this book is forThis book will help Python developers who want to understand and apply the asynchronous programming model in application development, data analysis, and orchestration scenarios. Junior developers, data engineers,, and tech leads will also benefit from the application design examples.
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Advanced Python Programming
Write fast, robust, and highly reusable applications using Python's internal optimization, state-of-the-art performance-benchmarking tools, and cutting-edge librariesKey FeaturesBenchmark, profile, and accelerate Python programs using optimization toolsScale applications to multiple processors with concurrent programmingMake applications robust and reusable using effective design patternsBook DescriptionPython's powerful capabilities for implementing robust and efficient programs make it one of the most sought-after programming languages.In this book, you'll explore the tools that allow you to improve performance and take your Python programs to the next level.This book starts by examining the built-in as well as external libraries that streamline tasks in the development cycle, such as benchmarking, profiling, and optimizing. You'll then get to grips with using specialized tools such as dedicated libraries and compilers to increase your performance at number-crunching tasks, including training machine learning models.The book covers concurrency, a major solution to making programs more efficient and scalable, and various concurrent programming techniques such as multithreading, multiprocessing, and asynchronous programming.You'll also understand the common problems that cause undesirable behavior in concurrent programs.Finally, you'll work with a wide range of design patterns, including creational, structural, and behavioral patterns that enable you to tackle complex design and architecture challenges, making your programs more robust and maintainable.By the end of the book, you'll be exposed to a wide range of advanced functionalities in Python and be equipped with the practical knowledge needed to apply them to your use cases.What you will learnWrite efficient numerical code with NumPy, pandas, and XarrayUse Cython and Numba to achieve native performanceFind bottlenecks in your Python code using profilersOptimize your machine learning models with JAXImplement multithreaded, multiprocessing, and asynchronous programsSolve common problems in concurrent programming, such as deadlocksTackle architecture challenges with design patternsWho this book is forThis book is for intermediate to experienced Python programmers who are looking to scale up their applications in a systematic and robust manner. Programmers from a range of backgrounds will find this book useful, including software engineers, scientific programmers, and software architects.
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Introduction to IoT with Machine Learning and Image Processing using Raspberry Pi
Machine Learning a branch of Artificial Intelligence is influencing the society, industry and academia at large. The adaptability of Python programming language to Machine Learning has increased its popularity further. Another technology on the horizon is Internet of Things (IoT). The present book tries to address IoT, Python and Machine Learning along with a small introduction to Image Processing. If you are a novice programmer or have just started exploring IoT or Machine Learning with Python, then this book is for you.Features: Raspberry Pi as IoT is described along with the procedure for installation and configuration.A simple introduction to Python Programming Language along with its popular library packages like NumPy, Pandas, SciPy and Matplotlib are dealt in an exhaustive manner along with relevant examples.Machine Learning along with Python Scikit-Learn library is explained to audience with an emphasis on supervised learning and classification.Image processing on IoT is introduced to the audience who love to apply Machine Learning algorithms to ImagesThe book follows hands-on approach and provide a huge collection of Python programs.
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Introduction to the Art of Programming Using Scala
With its flexibility for programming both small and large projects, Scala is an ideal language for teaching beginning programming. Yet there are no textbooks on Scala currently available for the CS1/CS2 levels. Introduction to the Art of Programming Using Scala presents many concepts from CS1 and CS2 using a modern, JVM-based language that works well for both programming in the small and programming in the large. The book progresses from true programming in the small to more significant projects later, leveraging the full benefits of object orientation. It first focuses on fundamental problem solving and programming in the small using the REPL and scripting environments. It covers basic logic and problem decomposition and explains how to use GUIs and graphics in programs. The text then illustrates the benefits of object-oriented design and presents a large collection of basic data structures showing different implementations of key ADTs along with more atypical data structures. It also introduces multithreading and networking to provide further motivating examples. By using Scala as the language for both CS1 and CS2 topics, this textbook gives students an easy entry into programming small projects as well as a firm foundation for taking on larger-scale projects. Many student and instructor resources are available at www.programmingusingscala.net
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Introduction to Programming Using Processing, Second Edition
Written in an informal, conversational, and humorous style, the second edition of Introduction to Programming Using Processing makes learning programming a fun experience. The freely-available Processing language is ideal for a first course in programming. The simple-to-access graphics and multimedia capabilities of the language let students develop eye-catching, animated programs, instead of traditional programs that print text to the console. The text takes a "classes-later" approach, focusing on basics, using objects, selection, iteration, topdown design, and arrays, before writing classes. Every example is presented in the context of the RADIS (Requirements / Analyze / Design / Implement / Support) framework, with considerable attention paid to design. Other positive habits, like good commenting practice and coding style, are emphasized as well.
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Python Programming for Mathematics
Python Programming for Mathematics focuses on the practical use of the Python language in a range of different areas of mathematics. Through fifty-five exercises of increasing difficulty, the book provides an expansive overview of the power of using programming to solve complex mathematical problems.This book is intended for undergraduate and graduate students who already have learned the basics of Python programming and would like to learn how to apply that programming skill in mathematics.FeaturesInnovative style that teaches programming skills via mathematical exercises.Ideal as a main textbook for Python for Mathematics courses, or as a supplementary resource for Numerical Analysis and Scientific Computing courses.
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Introduction to Programming Using Processing, Third Edition
Written in an informal, conversational, and humorous style, the second edition of Introduction to Programming Using Processing makes learning programming a fun experience. It is almost certainly the only programming textbook in the world with references to Jurassic Park, NCIS, Chuck Norris, and Gamera! The freely-available Processing language is ideal for a first course in programming. The simple-to-access graphics and multimedia capabilities of the language let students develop eye-catching, animated programs, instead of traditional programs that print text to the console. User interaction features let students connect with their programs in a manner that they're used to. Processing runs on all the major computing platforms, and can create "clickable" applications, in addition to Web-ready applets. Plus, the language's Java heritage carries over into later programming courses with little fuss. Resources related to the text are available at http://programminginprocessing.com
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Advanced Python Programming
Create distributed applications with clever design patterns to solve complex problemsKey FeaturesSet up and run distributed algorithms on a cluster using Dask and PySparkMaster skills to accurately implement concurrency in your codeGain practical experience of Python design patterns with real-world examplesBook DescriptionThis Learning Path shows you how to leverage the power of both native and third-party Python libraries for building robust and responsive applications. You will learn about profilers and reactive programming, concurrency and parallelism, as well as tools for making your apps quick and efficient. You will discover how to write code for parallel architectures using TensorFlow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. With the knowledge of how Python design patterns work, you will be able to clone objects, secure interfaces, dynamically choose algorithms, and accomplish much more in high performance computing.By the end of this Learning Path, you will have the skills and confidence to build engaging models that quickly offer efficient solutions to your problems.This Learning Path includes content from the following Packt products:Python High Performance - Second Edition by Gabriele LanaroMastering Concurrency in Python by Quan NguyenMastering Python Design Patterns by Sakis KasampalisWhat you will learnUse NumPy and pandas to import and manipulate datasetsAchieve native performance with Cython and NumbaWrite asynchronous code using asyncio and RxPyDesign highly scalable programs with application scaffoldingExplore abstract methods to maintain data consistencyClone objects using the prototype patternUse the adapter pattern to make incompatible interfaces compatibleEmploy the strategy pattern to dynamically choose an algorithmWho this book is forThis Learning Path is specially designed for Python developers who want to build high-performance applications and learn about single core and multi-core programming, distributed concurrency, and Python design patterns. Some experience with Python programming language will help you get the most out of this Learning Path.
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Foundations of Python Network Programming
Foundations of Python Network Programming, Third Edition, covers all of the classic topics found in the second edition of this book, including network protocols, network data and errors, email, server architecture, and HTTP and web applications, plus updates for Python 3.Some of the new topics in this edition include:• Extensive coverage of the updated SSL support in Python 3• How to write your own asynchronous I/O loop.• An overview of the "asyncio" framework that comes with Python 3.4.• How the Flask web framework connects URLs to your Python code.• How cross-site scripting and cross-site request forgery can be used to attack your web site, and how to protect against them.• How a full-stack web framework like Django can automate the round trip from your database to the screen and back.If you're a Python programmer who needs a deep understanding of how to use Python for network-related tasks and applications, this is the book for you. From web application developers, to systems integrators, to system administrators—this book has everything that you need to know.
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Introduction to Programming with C++ for Engineers
A complete textbook and reference for engineers to learn the fundamentals of computer programming with modern C++ Introduction to Programming with C++ for Engineers is an original presentation teaching the fundamentals of computer programming and modern C++ to engineers and engineering students. Professor Cyganek, a highly regarded expert in his field, walks users through basics of data structures and algorithms with the help of a core subset of C++ and the Standard Library, progressing to the object-oriented domain and advanced C++ features, computer arithmetic, memory management and essentials of parallel programming, showing with real world examples how to complete tasks. He also guides users through the software development process, good programming practices, not shunning from explaining low-level features and the programming tools. Being a textbook, with the summarizing tables and diagrams the book becomes a highly useful reference for C++ programmers at all levels. Introduction to Programming with C++ for Engineers teaches how to program by: Guiding users from simple techniques with modern C++ and the Standard Library, to more advanced object-oriented design methods and language featuresProviding meaningful examples that facilitate understanding of the programming techniques and the C++ language constructionsFostering good programming practices which create better professional programmersMinimizing text descriptions, opting instead for comprehensive figures, tables, diagrams, and other explanatory materialGranting access to a complementary website that contains example code and useful links to resources that further improve the reader’s coding abilityIncluding test and exam question for the reader’s review at the end of each chapter Engineering students, students of other sciences who rely on computer programming, and professionals in various fields will find this book invaluable when learning to program with C++.
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Introduction to the Tools of Scientific Computing
The book provides an introduction to common programming tools and methods in numerical mathematics and scientific computing. Unlike standard approaches, it does not focus on any specific language, but aims to explain the underlying ideas.Typically, new concepts are first introduced in the particularly user-friendly Python language and then transferred and extended in various programming environments from C/C++, Julia and MATLAB to Maple and Mathematica. This includes various approaches to distributed computing. By examining and comparing different languages, the book is also helpful for mathematicians and practitioners in deciding which programming language to use for which purposes.At a more advanced level, special tools for the automated solution of partial differential equations using the finite element method are discussed. On a more experimental level, the basic methods of scientific machine learning in artificial neural networks are explained and illustrated.
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Introduction to Scientific Programming
"Introduction to Computational Science" was developed over a period of two years at the University of Utah Department of Computer Science in conjunction with the U.S. Department of Energy-funded Undergraduate Computation in Engineering Science (UCES) program. Each chapter begins by introducing a problem and then guiding the student through its solution. The computational techniques needed to solve the problem are developed as necassary, making the motivation for learning the computing alwasy apparent. Each chapter will introduce a single problem that will be used to motivate a single computing concept. The notes currently consist of 15 chapters. The first seven chapters deal with Maple and the last eight with C. The textbook will contain 20 to 30 chapters covering a similar mix of concepts at a finer level of detail.
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