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Learn Python Programming
This edition offers updated content covering Python 3.9 to 3.12, new chapters on type hinting and CLI applications, and expanded practical examples, making it the ideal resource for both new and experienced Python programmersKey FeaturesCreate and deploy APIs and CLI applications, leveraging Python’s strengths in scripting and automationStay current with the latest features and improvements in Python, including pattern matching and the latest exception handling syntaxEngage with new real-world examples and projects, including competitive programming problems, to solidify your understanding of PythonBook DescriptionLearn Python Programming, Fourth Edition, provides a comprehensive, up-to-date introduction to Python programming, covering fundamental concepts and practical applications. This edition has been meticulously updated to include the latest features from Python versions 3.9 to 3.12, new chapters on type hinting and CLI applications, and updated examples reflecting modern Python web development practices. This Python book empowers you to take ownership of writing your software and become independent in fetching the resources you need. By the end of this book, you will have a clear idea of where to go and how to build on what you have learned from the book.Through examples, the book explores a wide range of applications and concludes by building real-world Python projects based on the concepts you have learned. This Python book offers a clear and practical guide to mastering Python and applying it effectively in various domains, such as data science, web development, and automation.What you will learnInstall and set up Python on Windows, Mac, and LinuxWrite elegant, reusable, and efficient codeAvoid common pitfalls such as duplication and over-engineeringUse functional and object-oriented programming approaches appropriatelyBuild APIs with FastAPI and program CLI applicationsUnderstand data persistence and cryptography for secure applicationsManipulate data efficiently using Python's built-in data structuresPackage your applications for distribution via the Python Package Index (PyPI)Solve competitive programming problems with PythonWho this book is forThis Python programming book is for everyone who wants to learn Python from scratch, as well as experienced programmers looking for a reference book. Prior knowledge of basic programming concepts will help you follow along, but it’s not a prerequisite
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Modern Python Cookbook
Complete recipes spread across 15 chapters to help you overcome commonly faced issues by Python for everybody across the globe. Each recipe takes a problem-solution approach to resolve for effective Python.Key FeaturesDevelop expressive and effective Python programsBest practices and common idioms through carefully explained recipesDiscover new ways to apply Python for data-focused developmentMake use of Python’s optional type annotationsBook DescriptionPython is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great language that can power your applications and provide great speed, safety, and scalability. It can be used for simple scripting or sophisticated web applications. By exposing Python as a series of simple recipes, this book gives you insight into specific language features in a particular context. Having a tangible context helps make the language or a given standard library feature easier to understand.This book comes with 133 recipes on the latest version of Python 3.8. The recipes will benefit everyone, from beginners just starting out with Python to experts. You'll not only learn Python programming concepts but also how to build complex applications.The recipes will touch upon all necessary Python concepts related to data structures, object oriented programming, functional programming, and statistical programming. You will get acquainted with the nuances of Python syntax and how to effectively take advantage of it.By the end of this Python book, you will be equipped with knowledge of testing, web services, configuration, and application integration tips and tricks. You will be armed with the knowledge of how to create applications with flexible logging, powerful configuration, command-line options, automated unit tests, and good documentation.What you will learnSee the intricate details of the Python syntax and how to use it to your advantageImprove your coding with Python readability through functionsManipulate data effectively using built-in data structuresGet acquainted with advanced programming techniques in PythonEquip yourself with functional and statistical programming featuresWrite proper tests to be sure a program works as advertisedIntegrate application software using PythonWho this book is forThe Python book is for web developers, programmers, enterprise programmers, engineers, and big data scientists. If you are a beginner, this book will get you started. If you are experienced, it will expand your knowledge base. A basic knowledge of programming would help.
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Hands-On GPU Programming with Python and CUDA
Build real-world applications with Python 2.7, CUDA 9, and CUDA 10. We suggest the use of Python 2.7 over Python 3.x, since Python 2.7 has stable support across all the libraries we use in this book.Key FeaturesExpand your background in GPU programming—PyCUDA, scikit-cuda, and NsightEffectively use CUDA libraries such as cuBLAS, cuFFT, and cuSolverApply GPU programming to modern data science applicationsBook DescriptionHands-On GPU Programming with Python and CUDA hits the ground running: you’ll start by learning how to apply Amdahl’s Law, use a code profiler to identify bottlenecks in your Python code, and set up an appropriate GPU programming environment. You’ll then see how to “query” the GPU’s features and copy arrays of data to and from the GPU’s own memory.As you make your way through the book, you’ll launch code directly onto the GPU and write full blown GPU kernels and device functions in CUDA C. You’ll get to grips with profiling GPU code effectively and fully test and debug your code using Nsight IDE. Next, you’ll explore some of the more well-known NVIDIA libraries, such as cuFFT and cuBLAS.With a solid background in place, you will now apply your new-found knowledge to develop your very own GPU-based deep neural network from scratch. You’ll then explore advanced topics, such as warp shuffling, dynamic parallelism, and PTX assembly. In the final chapter, you’ll see some topics and applications related to GPU programming that you may wish to pursue, including AI, graphics, and blockchain.By the end of this book, you will be able to apply GPU programming to problems related to data science and high-performance computing.What you will learnLaunch GPU code directly from PythonWrite effective and efficient GPU kernels and device functionsUse libraries such as cuFFT, cuBLAS, and cuSolverDebug and profile your code with Nsight and Visual ProfilerApply GPU programming to datascience problemsBuild a GPU-based deep neuralnetwork from scratchExplore advanced GPU hardware features, such as warp shufflingWho this book is forHands-On GPU Programming with Python and CUDA is for developers and data scientists who want to learn the basics of effective GPU programming to improve performance using Python code. You should have an understanding of first-year college or university-level engineering mathematics and physics, and have some experience with Python as well as in any C-based programming language such as C, C++, Go, or Java.
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