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Python Programming on WIN32
Python is growing in popularity; based on download statistics, there are now over 450,000 people using Python, and more than 150,000 people using Python on Windows. Use of the language has been growing at about 40% per year since 1995, and there is every reason to believe that growth will continue. Despite Python's increasing popularity on Windows, Python Programming on Win32 is the first book to demonstrate how to use it as a serious Windows development and administration tool. Unlike scripting on Unix, Windows scripting involves integrating a number of components, such as COM or the various mail and database APIs, with the Win32 programming interface. While experienced Windows C++ programmers can find their way through the various objects, most people need some guidance, and this book is it. It addresses all the basic technologies for common integration tasks on Windows, explaining both the Windows issues and the Python code you need to glue things together.Topics include: * The Python language and the PythonWin extensions * Building a GUI with COM * Adding a Macro language * Distributing the application * Client-side COM for output and data access * Integration with mail and other internet protocols * Managing users and drives This is a vital and unique book. Python Programming on Win32 is an excellent presentation of Windows application development and a solid illustration of how to use Python in the Windows environment.
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Python Programming for Data Analysis
This textbook grew out of notes for the ECE143 Programming for Data Analysis class that the author has been teaching at University of California, San Diego, which is a requirement for both graduate and undergraduate degrees in Machine Learning and Data Science. This book is ideal for readers with some Python programming experience. The book covers key language concepts that must be understood to program effectively, especially for data analysis applications. Certain low-level language features are discussed in detail, especially Python memory management and data structures. Using Python effectively means taking advantage of its vast ecosystem. The book discusses Python package management and how to use third-party modules as well as how to structure your own Python modules. The section on object-oriented programming explains features of the language that facilitate common programming patterns.After developing the key Python language features, the book moves on to third-party modules that are foundational for effective data analysis, starting with Numpy. The book develops key Numpy concepts and discusses internal Numpy array data structures and memory usage. Then, the author moves onto Pandas and details its many features for data processing and alignment. Because strong visualizations are important for communicating data analysis, key modules such as Matplotlib are developed in detail, along with web-based options such as Bokeh, Holoviews, Altair, and Plotly.The text is sprinkled with many tricks-of-the-trade that help avoid common pitfalls. The author explains the internal logic embodied in the Python language so that readers can get into the Python mindset and make better design choices in their codes, which is especially helpful for newcomers to both Python and data analysis. To get the most out of this book, open a Python interpreter and type along with the many code samples.
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UNIX: The Complete Reference, Second Edition
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.The Definitive UNIX Resource--Fully UpdatedGet cutting-edge coverage of the newest releases of UNIX--including Solaris 10, all Linux distributions, HP-UX, AIX, and FreeBSD--from this thoroughly revised, one-stop resource for users at all experience levels. Written by UNIX experts with many years of experience starting with Bell Laboratories, UNIX: The Complete Reference, Second Edition provides step-by-step instructions on how to use UNIX and take advantage of its powerful tools and utilities. Get up-and-running on UNIX quickly, use the command shell and desktop, and access the Internet and e-mail. You'll also learn to administer systems and networks, develop applications, and secure your UNIX environment. Up-to-date chapters on UNIX desktops, Samba, Python, Java Apache, and UNIX Web development are included. Install, configure, and maintain UNIX on your PC or workstationWork with files, directories, commands, and the UNIX shellCreate and modify text files using powerful text editorsUse UNIX desktops, including GNOME, CDE, and KDE, as an end user or system administrator Use and manage e-mail, TCP/IP networking, and Internet servicesProtect and maintain the security of your UNIX system and networkShare devices, printers, and files between Windows and UNIX systemsUse powerful UNIX tools, including awk, sed, and grepDevelop your own shell, Python, and Perl scripts, and Java, C, and C++ programs under UNIXSet up Apache Web servers and develop browser-independent Web sites and applications
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Advanced Python Scripting for ArcGIS Pro
Tackle complex spatial data tasks effortlessly with this easy-to-follow guide to writing specialized Python scripts and developing tools for spatial data in ArcGIS® Pro.Advanced Python Scripting for ArcGIS Pro follows up on the topics explained in Python Scripting for ArcGIS Pro (Esri Press, 2024) and is now updated for ArcGIS Pro 3.2.Intended for users who have a good foundation in Python, this book explores how to develop scripts into tools and notebooks to share with others, use third-party packages, and learn other more specialized tasks. By the end of this book, you’ll be confident in writing more advanced scripts, developing them into tools and notebooks, and sharing them with others.The key topics you will learn include:Creating custom functions and classesWriting specialized scripts using ArcPy™Creating Python script tools and Python toolboxesSharing scripts and toolsManaging Python packages and environmentsMigrating scripts from Python 2 to 3NumPy, Pandas, and MatplotlibCreating and using notebooksArcGIS API for Python and Jupyter NotebookHelpful points to remember, key terms, and review questions are included at the end of each chapter to reinforce your understanding of Python. Companion data and tutorials are available online.Packed with advanced techniques and practical examples, Advanced Python Scripting for ArcGIS Pro is perfect for more experienced ArcGIS Pro users who are looking to upgrade their Python skills and enhance their workflows.
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Programming Pig 2e
For many organizations, Hadoop is the first step for dealing with massive amounts of data. The next step? Processing and analyzing datasets with the Apache Pig scripting platform. With Pig, you can batch-process data without having to create a full-fledged application, making it easy to experiment with new datasets. Updated with use cases and programming examples, this second edition is the ideal learning tool for new and experienced users alike. You'll find comprehensive coverage on key features such as the Pig Latin scripting language and the Grunt shell. When you need to analyze terabytes of data, this book shows you how to do it efficiently with Pig.Delve into Pig's data model, including scalar and complex data types Write Pig Latin scripts to sort, group, join, project, and filter your data Use Grunt to work with the Hadoop Distributed File System (HDFS) Build complex data processing pipelines with Pig's macros and modularity features Embed Pig Latin in Python for iterative processing and other advanced tasks Use Pig with Apache Tez to build high-performance batch and interactive data processing applications Create your own load and store functions to handle data formats and storage mechanisms
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Raspberry Pi Image Processing Programming
Understand the concepts of image processing with Python 3 and create applications using Raspberry Pi 4. This book covers image processing with the latest release of Python 3, using Raspberry Pi OS and Raspberry Pi 4B with the 8 GB RAM model as the preferred computing platform.This second edition begins with the installation of Raspberry Pi OS on the latest model of Raspberry Pi and then introduces Python programming language, IDEs for Python, and digital image processing. It also illustrates the theoretical foundations of Image processing followed by advanced operations in image processing. You'll then review image processing with NumPy, and Matplotlib followed by transformations, interpolation, and measurements of images. Different types of filters such as Kernels convolution filters, low pass filters, high pass filters, and Fourier filters are discussed in a clear, methodical manner. Additionally, the book examines various image processing techniques such as Morphology, Thresholding, and Segmentation, followed by a chapter on live webcam input with OpenCV, an image processing library with Python. The book concludes with an appendix covering a new library for image processing with Python, pgmagik, followed by a few important tips and tricks relevant to RPi.What You'll LearnGet started with Raspberry Pi and PythonUnderstand Image Processing with PillowSee how image processing is processed using Numpy and MatplotlibUse Pi camera and webcamWho This Book Is ForRaspberry Pi and IoT enthusiasts, and Python and Open Source professionals
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Vibe Coding Playbook
A detailed and up-to-date walkthrough for entrepreneurs with limited (or non-existent) coding skills who want to build profitable software companies using new gen-AI tools In The Vibe Coding Playbook: Building Your Tech Business With AI, renowned AI and data science educator Siraj Raval walks you through exactly what you need to do to build a technology business with generative AI-powered code assistants. Raval offers step-by-step guidance for non-technical professionals and entrepreneurs interested in creating scalable, profitable enterprises without spending years learning how to code. This book conceives of new artificial intelligence tools, like Cursor, as “co-founders,” lighting your way to constructing valuable software products and services. You’ll learn to build minimally viable products (MVPs), iterate on your software products as you develop and after launch, and grow your company while maintaining a lean, efficient, solopreneur-focused structure. Inside the book: Detailed guidance for entrepreneurs interested in creating powerful tech solutions for niche problems and markets without hiring expensive software developersStrategies for using generative AI tools to substitute for traditional technical co-foundersIllustrative case studies from real-world founders who built successful technology businesses without learning to codeUseful tools for non-technical entrepreneurs, including prompt libraries, decision trees, QR codes linking to video tutorials demonstrating key techniques, and access to an exclusive online community of like-minded founders Perfect for ambitious professionals and entrepreneurs who want to build a successful technology company now – using commercially available AI tools – The Vibe Coding Playbook is your personal roadmap to creating useful and profitable software for customers without learning how to code.
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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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Errors and Intelligence in Computer-Assisted Language Learning
This book provides the first comprehensive overview of theoretical issues, historical developments and current trends in ICALL (Intelligent Computer-Assisted Language Learning). It assumes a basic familiarity with Second Language Acquisition (SLA) theory and teaching, CALL and linguistics. It is of interest to upper undergraduate and/or graduate students who study CALL, SLA, language pedagogy, applied linguistics, computational linguistics or artificial intelligence as well as researchers with a background in any of these fields.
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Learn Python by Building Data Science Applications
Understand the constructs of the Python programming language and use them to build data science projectsKey FeaturesLearn the basics of developing applications with Python and deploy your first data applicationTake your first steps in Python programming by understanding and using data structures, variables, and loopsDelve into Jupyter, NumPy, Pandas, SciPy, and sklearn to explore the data science ecosystem in PythonBook DescriptionPython is the most widely used programming language for building data science applications. Complete with step-by-step instructions, this book contains easy-to-follow tutorials to help you learn Python and develop real-world data science projects. The “secret sauce” of the book is its curated list of topics and solutions, put together using a range of real-world projects, covering initial data collection, data analysis, and production.This Python book starts by taking you through the basics of programming, right from variables and data types to classes and functions. You’ll learn how to write idiomatic code and test and debug it, and discover how you can create packages or use the range of built-in ones. You’ll also be introduced to the extensive ecosystem of Python data science packages, including NumPy, Pandas, scikit-learn, Altair, and Datashader. Furthermore, you’ll be able to perform data analysis, train models, and interpret and communicate the results. Finally, you’ll get to grips with structuring and scheduling scripts using Luigi and sharing your machine learning models with the world as a microservice.By the end of the book, you’ll have learned not only how to implement Python in data science projects, but also how to maintain and design them to meet high programming standards.What you will learnCode in Python using Jupyter and VS CodeExplore the basics of coding – loops, variables, functions, and classesDeploy continuous integration with Git, Bash, and DVCGet to grips with Pandas, NumPy, and scikit-learnPerform data visualization with Matplotlib, Altair, and DatashaderCreate a package out of your code using poetry and test it with PyTestMake your machine learning model accessible to anyone with the web APIWho this book is forIf you want to learn Python or data science in a fun and engaging way, this book is for you. You’ll also find this book useful if you’re a high school student, researcher, analyst, or anyone with little or no coding experience with an interest in the subject and courage to learn, fail, and learn from failing. A basic understanding of how computers work will be useful.
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Python 3 Using DeepSeek
This book is your definitive guide to mastering DeepSeek, a leading open-source Large Language Model (LLM), and leveraging its power through practical Python programming. It is structured to build your expertise from foundational Python data structures and object-oriented programming to advanced model deployment.The initial chapters establish a strong technical base in Python's core features, including comprehensions, iterators, and the OOP paradigm. The focus then shifts entirely to DeepSeek, detailing its innovative Mixture-of-Experts (MoE) architecture, its superior performance on code-centric benchmarks like HumanEval, and its efficiency advantages. You will gain crucial insight into model management, specifically through the concept of quantization and local deployment with tools like Ollama, which is essential for maximizing performance while minimizing resource usage. The final chapter provides numerous, practical Python mini-projects, allowing you to immediately apply DeepSeek's capabilities to a range of real-world tasks from basic web scraping and data visualization to advanced object-oriented programming and linear regression.Python 3 Using DeepSeek is essential reading for Python developers (intermediate to advanced), machine learning practitioners, and data scientists. It is your guide to integrating high-performing, open-source LLMs into your workflows, particularly for code generation, algorithmic reasoning, and highly efficient local model deployment.
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Programming in Two Semesters
This highly accessible textbook teaches programming from first principles. In common with many programming courses, it uses Python as the introductory programming language before going on to use Java as the vehicle for more advanced programming concepts.The first part, which teaches Python, covers fundamental programming concepts, such as data types and control structures and functions. It introduces more complex data types such as lists and dictionaries and also deals with file handling. It introduces object-oriented concepts and ends with a case study bringing together all the topics of the first semester. The second part uses Java to teach advanced concepts and centres around object-oriented programming, teaching key object-oriented concepts such as inheritance and polymorphism. The semester again ends with an advanced case study bringing together all the topics of the second semester.Topics and features:Assumes no prior knowledge, and makes the transition from Python to Java a smooth processFeatures numerous exercises and also an illustrative case study for each language Examines procedural and object-oriented methodologies, as well as design principles Covers such advanced topics as interfaces and lambda expressions, exceptions and Collections Includes a chapter on graphics programming in Python using Tkinter Introduces the latest Java technology for graphical interfaces, JavaFXExplains design concepts using UML notation Offering a gentle introduction to the field and assuming no prerequisite background, Programming in Two Semesters is the ideal companion to undergraduate modules in software development or programming. In addition, it will serve as a strong primer for professionals looking to strengthen their knowledge of programming with these languages.
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Learning C# Programming with Unity 3D, second edition
Learning C# Programming with Unity 3D, Second Edition is for the novice game programmer without any prior programming experience. Readers will learn how C# is used to make a game in Unity 3D. Many example projects provide working code to learn from and experiment with. As C# evolves, Unity 3D evolves along with it. Many new features and aspects of C# are included and explained. Common programming tasks are taught by way of making working game mechanics. The reader will understand how to read and apply C# in Unity 3D and apply that knowledge to other development environments that use C#. New to this edition: includes latest C# language features and useful tools included with the .NET library like LINQ, Local Functions Tuples, and more!Key Features Provides a starting point for the first-time programmer C# Code examples are simple short and clear Learn the very basics on up to interesting tricks which C# offers
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Handbook of Computer Programming with Python
This handbook provides a hands-on experience based on the underlying topics, and assists students and faculty members in developing their algorithmic thought process and programs for given computational problems. It can also be used by professionals who possess the necessary theoretical and computational thinking background but are presently making their transition to Python.Key Features:Discusses concepts such as basic programming principles, OOP principles, database programming, GUI programming, application development, data analytics and visualization, statistical analysis, virtual reality, data structures and algorithms, machine learning, and deep learning Provides the code and the output for all the concepts discussedIncludes a case study at the end of each chapterThis handbook will benefit students of computer science, information systems, and information technology, or anyone who is involved in computer programming (entry-to-intermediate level), data analytics, HCI-GUI, and related disciplines.
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