Search results for "Python in Depth"
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R 1,374.00
Mastering Concurrency in Python
Immerse yourself in the world of Python concurrency and tackle the most complex concurrent programming problemsKey FeaturesExplore the core syntaxes, language features and modern patterns of concurrency in PythonUnderstand how to use concurrency to keep data consistent and applications responsiveUtilize application scaffolding to design highly-scalable programs Book DescriptionPython is one of the most popular programming languages, with numerous libraries and frameworks that facilitate high-performance computing. Concurrency and parallelism in Python are essential when it comes to multiprocessing and multithreading; they behave differently, but their common aim is to reduce the execution time. This book serves as a comprehensive introduction to various advanced concepts in concurrent engineering and programming.Mastering Concurrency in Python starts by introducing the concepts and principles in concurrency, right from Amdahl's Law to multithreading programming, followed by elucidating multiprocessing programming, web scraping, and asynchronous I/O, together with common problems that engineers and programmers face in concurrent programming. Next, the book covers a number of advanced concepts in Python concurrency and how they interact with the Python ecosystem, including the Global Interpreter Lock (GIL). Finally, you'll learn how to solve real-world concurrency problems through examples.By the end of the book, you will have gained extensive theoretical knowledge of concurrency and the ways in which concurrency is supported by the Python languageWhat you will learnExplore the concepts of concurrency in programmingExplore the core syntax and features that enable concurrency in PythonUnderstand the correct way to implement concurrencyAbstract methods to keep the data consistent in your programAnalyze problems commonly faced in concurrent programmingUse application scaffolding to design highly-scalable programsWho this book is forThis book is for developers who wish to build high-performance applications and learn about signle-core, multicore programming or distributed concurrency. Some experience with Python programming language is assumed.
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Introduction To Python For Quantitative Finance: From Scratch To Productivity
Written by a data scientist with decades of practical experience on some of the most challenging datasets, this book caters to both novices and professionals working in the fields of data science and machine learning. It enables novices to enter these fields with confidence and ease. There are no formal prerequisites. An introduction to Python is included. The book then proceeds to cover some of the language's most advanced features. The mathematical foundations that follow are meticulously explained. The discussion then proceeds to a practical consideration of data science and machine learning. The material is delivered through case studies developed on real datasets. The reader is invited to follow these case studies, and so develop experience in working with real data. Numerous solved exercises make this work suitable for self-study. The contents of this book have been taught by the author to students of different age groups and levels of experience at Imperial College London and at the Thalesians Intensive Summer School in Artificial Intelligence over the years.
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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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Scaling Python with Ray
Serverless computing enables developers to concentrate solely on their applications rather than worry about where they've been deployed. With the Ray general-purpose serverless implementation in Python, programmers and data scientists can hide servers, implement stateful applications, support direct communication between tasks, and access hardware accelerators.In this book, authors Holden Karau and Boris Lublinsky show you how to scale existing Python applications and pipelines, allowing you to stay in the Python ecosystem while avoiding single points of failure and manual scheduling. If your data processing has grown beyond what a single computer can handle, this book is for you.Written by experienced software architecture practitioners, Scaling Python with Ray is ideal for software architects and developers eager to explore successful case studies and learn more about decision and measurement effectiveness. This book covers distributed processing (the pure Python implementation of serverless) and shows you how to:Implement stateful applications with Ray actorsBuild workflow management in RayUse Ray as a unified platform for batch and streamingImplement advanced data processing with RayApply microservices with Ray platformImplement reliable Ray applications
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Mastering Python Networking
Publisher's Note: This edition from 2018 is outdated. A new third edition, updated for 2020 featuring Python 3.8, with coverage extended to include Azure, AWS, and Ansible 2.8, and data analysis using Elastic Stack has just been published.Master the art of using Python for a diverse range of network engineering tasks.Key FeaturesExplore the power of Python libraries to tackle difficult network problems efficiently and effectivelyUse Python for network device automation, DevOps, and software-defined networkingBecome an expert in implementing advanced network-related tasks with PythonBook DescriptionNetworks in your infrastructure set the foundation for how your application can be deployed, maintained, and serviced. Python is the ideal language for network engineers to explore tools that were previously available to systems engineers and application developers. In this second edition of Mastering Python Networking, you’ll embark on a Python-based journey to transition from traditional network engineers to network developers ready for the next-generation of networks. This book begins by reviewing the basics of Python and teaches you how Python can interact with both legacy and API-enabled network devices. As you make your way through the chapters, you will then learn to leverage high-level Python packages and frameworks to perform network engineering tasks for automation, monitoring, management, and enhanced security. In the concluding chapters, you will use Jenkins for continuous network integration as well as testing tools to verify your network. By the end of this book, you will be able to perform all networking tasks with ease using Python.What you will learnUse Python libraries to interact with your networkIntegrate Ansible 2.5 using Python to control Cisco, Juniper, and Arista eAPI network devicesLeverage existing frameworks to construct high-level APIs Learn how to build virtual networks in the AWS Cloud Understand how Jenkins can be used to automatically deploy changes in your networkUse PyTest and Unittest for Test-Driven Network DevelopmentWho this book is forMastering Python Networking is for network engineers and programmers who want to use Python for networking. Basic familiarity with Python programming and networking-related concepts such as Transmission Control Protocol/Internet Protocol (TCP/IP) will be useful.
R 1,889.00
Coding Club Python: Building Big Apps Level 3
A unique series that provides a framework for teaching coding skills. Build more sophisticated apps with level 3 of Coding Club! Following on from Python: Next Steps, this lively book explains how to break down projects into manageable chunks, guiding and supporting you with building larger, more exciting projects. Activities include building a version of Pong and, using the classes created for Pong, building a Breakout game and an Invaders game, developing and learning the necessary skills to build larger apps on the way. The code is suitable for Mac, Windows and Linux users and therefore compatible with the Raspberry Pi.
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Python Scripting for ArcGIS Pro
Unlock the power of Python in ArcGIS® Pro with this definitive, easy-to-follow guide designed for users with limited programming or scripting experience.Get started learning to write Python scripts to automate tasks in ArcGIS Pro with Python Scripting for ArcGIS Pro. This book begins with the fundamentals of Python programming and then dives into how to write useful Python scripts that work with spatial data in ArcGIS Pro. You’ll learn how to use geoprocessing tools; describe, create, and update data; and execute specialized tasks. With step-by-step instructions, practical examples, and insightful guidance, you’ll be able to write scripts that will automate and improve your ArcGIS Pro workflows.This third edition has been revised for ArcGIS Pro 3.2 and Python 3.9.18 and includes updated images; a fully updated chapter 2; and expanded chapters 4, 8, 9, and 10.The key topics you will learn include:Python fundamentalsSetting up a Python editorAutomating geoprocessing tasks using ArcPy™Exploring and manipulating spatial and tabular dataWorking with geometries using cursorsWorking with rasters and map algebraMap scriptingDebugging and error handlingHelpful points to remember, key terms, and review questions are included at the end of each chapter to reinforce your understanding of Python. Corresponding data and tutorials are available online.Whether you’re new to Python or already have some experience, Python Scripting for ArcGIS Pro is the go-to resource for learning the versatility of Python coding to solve problems and enhance productivity and efficiency in ArcGIS Pro.
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Cracking Codes With Python
Cracking Secret Codes with Python is a hands-on introduction to Python that teaches readers how to make and hack cipher programs, which are used to encrypt secret messages. It covers ciphers like the Caesar cipher, transposition cipher, and the RSA cipher, and teaches readers how to test and hack them. For every program, Sweigart provides the full source code and then walks readers through it, explaining how every line works. Along the way, readers will learn Python fundamentals - and by the book's end, they'll have a solid foundation in Python and some fun programs under their belt.
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