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Mastering Python for Finance
Take your financial skills to the next level by mastering cutting-edge mathematical and statistical financial applicationsKey FeaturesExplore advanced financial models used by the industry and ways of solving them using PythonBuild state-of-the-art infrastructure for modeling, visualization, trading, and moreEmpower your financial applications by applying machine learning and deep learningBook DescriptionThe second edition of Mastering Python for Finance will guide you through carrying out complex financial calculations practiced in the industry of finance by using next-generation methodologies. You will master the Python ecosystem by leveraging publicly available tools to successfully perform research studies and modeling, and learn to manage risks with the help of advanced examples.You will start by setting up your Jupyter notebook to implement the tasks throughout the book. You will learn to make efficient and powerful data-driven financial decisions using popular libraries such as TensorFlow, Keras, Numpy, SciPy, and sklearn. You will also learn how to build financial applications by mastering concepts such as stocks, options, interest rates and their derivatives, and risk analytics using computational methods. With these foundations, you will learn to apply statistical analysis to time series data, and understand how time series data is useful for implementing an event-driven backtesting system and for working with high-frequency data in building an algorithmic trading platform. Finally, you will explore machine learning and deep learning techniques that are applied in finance.By the end of this book, you will be able to apply Python to different paradigms in the financial industry and perform efficient data analysis.What you will learnSolve linear and nonlinear models representing various financial problemsPerform principal component analysis on the DOW index and its componentsAnalyze, predict, and forecast stationary and non-stationary time series processesCreate an event-driven backtesting tool and measure your strategiesBuild a high-frequency algorithmic trading platform with PythonReplicate the CBOT VIX index with SPX options for studying VIX-based strategiesPerform regression-based and classification-based machine learning tasks for predictionUse TensorFlow and Keras in deep learning neural network architectureWho this book is forIf you are a financial or data analyst or a software developer in the financial industry who is interested in using advanced Python techniques for quantitative methods in finance, this is the book you need! You will also find this book useful if you want to extend the functionalities of your existing financial applications by using smart machine learning techniques. Prior experience in Python is required.
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Python Unlocked
Become more fluent in Python—learn strategies and techniques for smart and high-performance Python programmingAbout This Book• Write smarter, bug-free, high performance code with minimal effort• Uncover the best tools and options available to Python developers today• Deploy decorators, design patters, and various optimization techniques to use Python 3.5 effectivelyWho This Book Is ForIf you are a Python developer and you think that you don't know everything about the language yet, then this is the book for you. We will unlock the mysteries and re-introduce you to the hidden features of Python to write efficient programs, making optimal use of the language.What You Will Learn• Manipulate object creation processes for instances, classes, and functions• Use the best possible language constructs to write data structures with super speed and maintainability• Make efficient use of design patterns to decrease development time and make your code more maintainable• Write better test cases with an improved understanding of the testing framework of Python and unittests, and discover how to develop new functionalities in it• Write fully-optimized code with the Python language by profiling, compiling C modules, and more• Unlock asynchronous programming to build efficient and scalable applicationsIn DetailPython is a versatile programming language that can be used for a wide range of technical tasks—computation, statistics, data analysis, game development, and more. Though Python is easy to learn, it's range of features means there are many aspects of it that even experienced Python developers don't know about. Even if you're confident with the basics, its logic and syntax, by digging deeper you can work much more effectively with Python – and get more from the language.Python Unlocked walks you through the most effective techniques and best practices for high performance Python programming - showing you how to make the most of the Python language. You'll get to know objects and functions inside and out, and will learn how to use them to your advantage in your programming projects. You will also find out how to work with a range of design patterns including abstract factory, singleton, strategy pattern, all of which will help make programming with Python much more efficient. Finally, as the process of writing a program is never complete without testing it, you will learn to test threaded applications and run parallel tests.If you want the edge when it comes to Python, use this book to unlock the secrets of smarter Python programming.Style and approachThis is book had been created to help you to “unlock” the best ways to tackle the challenges and performance bottlenecks that many Python developers face today. The keys are supported with program examples to help you understand the concepts better and see them in action.
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Python GUI Programming Cookbook
Over 90 recipes to help you develop widgets, forms, layouts, charts, and much more using the latest features of Python 3Key FeaturesUse object-oriented programming to develop impressive GUIs in PythonCreate interesting charts to visually represent data using MatplotlibDevelop GUIs with the latest versions of tkinter, PyQt5, and wxPython frameworksBook DescriptionPython is a multi-domain, interpreted programming language that is easy to learn and implement. With its wide support for frameworks to develop GUIs, you can build interactive and beautiful GUI-based applications easily using Python. This third edition of Python GUI Programming Cookbook follows a task-based approach to help you create effective GUIs with the smallest amount of code. Every recipe in this book builds upon the last to create an entire, real-life GUI application. These recipes also help you solve problems that you might encounter while developing GUIs. This book mainly focuses on using Python’s built-in tkinter GUI framework. You'll learn how to create GUIs in Python using simple programming styles and object-oriented programming (OOP). As you add more widgets and expand your GUI, you will learn how to connect to networks, databases, and graphical libraries that greatly enhance the functionality of your GUI. You’ll also learn how to use threading to ensure that your GUI doesn't become unresponsive. Toward the end, you’ll learn about the versatile PyQt GUI framework, which comes along with its own visual editor that allows you to design GUIs using drag and drop features. By the end of the book, you’ll be an expert in designing Python GUIs and be able to develop a variety of GUI applications with ease.What you will learnCreate amazing GUIs with Python's built-in tkinter moduleCustomize GUIs using layout managers to arrange GUI widgetsAdvance from the typical waterfall coding style to an OOP style using PythonDevelop beautiful charts using the free Matplotlib Python moduleUse threading in a networked environment to make GUIs responsiveDiscover ways to connect GUIs to a MySQL databaseUnderstand how unit tests can be created and internationalize GUIDelve into the world of GUI creation using PyQt5Who this book is forIf you’re a programmer or developer looking to enhance your Python skills by writing powerful GUI applications, this book is for you. Familiarity with the Python programming language is necessary to get the most out of the book.
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Test-Driven Development with Python
The third edition of this trusted guide demonstrates the practical advantages of test-driven development (TDD) with Python and describes how to develop a real web application. You'll learn how to write and run tests before building each part of your app and then develop the minimum amount of code required to pass those tests. The result? Clean code that works. In the process, author Harry Percival teaches software and web developers the basics of Django, Selenium, Git, JavaScript, and Mock libraries, along with current web development techniques. This book--updated for Python 3.14 and Django 4--clearly demonstrates how TDD encourages simple designs and inspires confidence. Fully updated, this third edition addresses: The TDD workflow, including the unit test/code cycle and refactoring Unit tests for classes and functions and functional tests for user interactions within the browser Mock objects and the pros and cons of isolated versus integrated tests Testing and automation of deployments with a staging server Tests applied to the third-party plug-ins you integrate into your site Automatic tests using a continuous integration environment Using TDD to build a REST API with a JavaScript frontend interface
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GPU-Accelerated Computing with Python 3 and CUDA
Accelerate your Python code on the GPU using CUDA, Numba, and modern libraries to solve real-world problems faster and more efficiently.Key FeaturesBuild a solid foundation in CUDA with Python, from kernel design to execution and debuggingOptimize GPU performance with efficient memory access, CUDA streams, and multi-GPU scalingUse JAX, CuPy, RAPIDS, and Numba to accelerate numerical computing and machine learningCreate practical GPU applications, from PDE solvers to image processing and transformersBook DescriptionWriting high-performance Python code doesn’t have to mean switching to C++. This book shows you how to accelerate Python applications using NVIDIA’s CUDA platform and a modern ecosystem of Python tools and libraries. Aimed at researchers, engineers, and data scientists, it offers a practical yet deep understanding of GPU programming and how to fully exploit modern GPU hardware.You’ll begin with the fundamentals of CUDA programming in Python using Numba-CUDA, learning how GPUs work and how to write, execute, and debug custom GPU kernels. Building on this foundation, the book explores memory access optimization, asynchronous execution with CUDA streams, and multi-GPU scaling using Dask-CUDA. Performance analysis and tuning are emphasized throughout, using NVIDIA Nsight profilers.You’ll also learn to use high-level GPU libraries such as JAX, CuPy, and RAPIDS to accelerate numerical Python workflows with minimal code changes. These techniques are applied to real-world examples, including PDE solvers, image processing, physical simulations, and transformer models.Written by experienced GPU practitioners, this hands-on guide emphasizes reproducible workflows using Python 3.10+, CUDA 12.3+, and tools like the Pixi package manager. By the end, you’ll have future-ready skills for building scalable GPU applications in Python.What you will learnUnderstand GPU execution, parallelism, and the CUDA programming modelWrite, launch, and debug custom CUDA kernels in Python with CUDAProfile GPU code with NVIDIA Nsight and optimize memory accessUse CUDA streams and async execution to overlap compute and transfersApply JAX, CuPy, and RAPIDS to numerical computing and machine learningScale GPU workloads across devices using Dask and multi-GPU strategiesAccelerate PDE solvers, simulations, and image processing on the GPUBuild, train, and run a transformer model from scratch on the GPUWho this book is forPython developers, (data) scientists, engineers, and researchers looking to accelerate numerical computations without switching to low-level languages. This book is ideal for those with experience in scientific Python (NumPy, Pandas, SciPy) and a basic understanding of computing fundamentals who want deeper control over performance in GPU environments.
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Mastering OpenCV 4 with Python
Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality.Key FeaturesDevelop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4) and PythonApply machine learning and deep learning techniques with TensorFlow and KerasDiscover the modern design patterns you should avoid when developing efficient computer vision applicationsBook DescriptionOpenCV is considered to be one of the best open source computer vision and machine learning software libraries. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language.In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras.By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands.What you will learnHandle files and images, and explore various image processing techniquesExplore image transformations, including translation, resizing, and croppingGain insights into building histogramsBrush up on contour detection, filtering, and drawingWork with Augmented Reality to build marker-based and markerless applicationsWork with the main machine learning algorithms in OpenCVExplore the deep learning Python libraries and OpenCV deep learning capabilitiesCreate computer vision and deep learning web applicationsWho this book is forThis book is designed for computer vision developers, engineers, and researchers who want to develop modern computer vision applications. Basic experience of OpenCV and Python programming is a must.
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Learning Professional Python
Volume 2 of Learning Professional Python is a resource for students who want to learn Python even if they don’t have any programming knowledge and for teachers who want a comprehensive introduction to Python to use with their students. This book helps the students achieve their dream job in the IT Industry and teaches the students in an easy, understandable manner while strengthening coding skills.Learning Professional Python: Volume 2 Objectives Become familiar with the features of Python programming language Introduce the object-oriented programming concepts Discover how to write Python code by following the object-oriented programming concepts Become comfortable with concepts such as classes, objects, inheritance, dynamic dispatch, interfaces, and packages Learn the Python generics and collections Develop exception handling and the multithreaded applications Design graphical user interface (GUI) applications
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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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Hands-On Enterprise Application Development with Python
Architect scalable, reliable, and maintainable applications for enterprises with PythonKey FeaturesExplore various Python design patterns used for enterprise software developmentApply best practices for testing and performance optimization to build stable applicationsLearn about different attacking strategies used on enterprise applications and how to avoid themBook DescriptionDynamically typed languages like Python are continuously improving. With the addition of exciting new features and a wide selection of modern libraries and frameworks, Python has emerged as an ideal language for developing enterprise applications. Hands-On Enterprise Application Development with Python will show you how to build effective applications that are stable, secure, and easily scalable.The book is a detailed guide to building an end-to-end enterprise-grade application in Python. You will learn how to effectively implement Python features and design patterns that will positively impact your application lifecycle. The book also covers advanced concurrency techniques that will help you build a RESTful application with an optimized frontend. Given that security and stability are the foundation for an enterprise application, you’ll be trained on effective testing, performance analysis, and security practices, and understand how to embed them in your codebase during the initial phase. You’ll also be guided in how to move on from a monolithic architecture to one that is service oriented, leveraging microservices and serverless deployment techniques.By the end of the book, you will have become proficient at building efficient enterprise applications in Python.What you will learnUnderstand the purpose of design patterns and their impact on application lifecycleBuild applications that can handle large amounts of data-intensive operationsUncover advanced concurrency techniques and discover how to handle a large number of requests in productionOptimize frontends to improve the client-side experience of your applicationEffective testing and performance profiling techniques to detect issues in applications early in the development cycleBuild applications with a focus on securityImplement large applications as microservices to improve scalabilityWho this book is forIf you’re a developer who wants to build enterprise-grade applications, this book is for you. Basic to intermediate-level of programming experience with Python and database systems is required to understand the concepts covered in this book.
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Design Multi-Agent AI Systems Using MCP and A2A
Build a production-ready multi-agent AI framework from scratch using MCP and A2A to orchestrate powerful agent workflowsFree with your book: DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesBuild Python-based AI agents without relying on third-party orchestration frameworksDesign production-ready multi-agent systems using A2A messagingIntegrate memory and context with MCP to create adaptive and stateful agentic AI frameworksBook DescriptionFrustrated by opaque agent frameworks that hide how things work? This book gives you complete control by guiding you through building a fully functional, extensible agentic AI framework in Python without relying on external orchestration tools.You’ll begin by implementing a simple tool-using agent, and then gradually extend its capabilities with structured tool schemas, user interfaces, and memory via the Model Context Protocol (MCP). From there, you’ll build collaborative multi-agent systems powered by Agent-to-Agent (A2A) messaging and deploy them in realistic environments. Along the way, you’ll explore secure tool invocation, message routing, observability, and human-in-the-loop workflows.With annotated code, deep engineering insights, and practical deployment patterns, this hands-on guide equips you to build AI agents that reason, plan, act, and adapt, whether you’re shipping production systems or experimenting with cutting-edge LLM-based architectures.Written by Gigi Sayfan, who builds AI agent infrastructure at Perplexity and is a bestselling author with decades of experience in AI and distributed systems, this book gives you the tools and knowledge to engineer your own advanced agentic systems.*Email sign-up and proof of purchase requiredWhat you will learnDesign and implement tool-using AI agents from the ground upBuild modular components for extensible agent frameworksCreate secure and observable tools with structured inputsIntegrate agents with chat UIs such as Slack and ChainlitLeverage MCP for context handling and agent memoryOrchestrate collaborative agent workflows using A2ADebug and deploy agents in production-like environmentsExplore future-ready agent capabilities and GenUX designWho this book is forThis book is essential for AI engineers, ML practitioners, and software architects building agentic systems with large language models. It’s also ideal for DevOps engineers and technical leaders seeking deep insights into building and scaling autonomous AI workflows. Python coding skills and basic familiarity with LLMs are recommended.
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Multiparadigm Constraint Programming Languages
Programming languages are often classified according to their paradigms, e.g. imperative, functional, logic, constraint-based, object-oriented, or aspect-oriented. A paradigm characterizes the style, concepts, and methods of the language for describing situations and processes and for solving problems, and each paradigm serves best for programming in particular application areas. Real-world problems, however, are often best implemented by a combination of concepts from different paradigms, because they comprise aspects from several realms, and this combination is more comfortably realized using multiparadigm programming languages. This book deals with the theory and practice of multiparadigm constraint programming languages. The author first elaborates on programming paradigms and languages, constraints, and the merging of programming concepts which yields multiparadigm (constraint) programming languages. In the second part the author inspects two concrete approaches on multiparadigm constraint programming – the concurrent constraint functional language CCFL, which combines the functional and the constraint-based paradigms and allows the description of concurrent processes; and a general framework for multiparadigm constraint programming and its implementation, Meta-S.The book is appropriate for researchers and graduate students in the areas of programming and artificial intelligence.
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Unlocking Python
A fun and practical guide to learning Python with a special focus on data science, web scraping, and web applications In Unlocking Python: A Comprehensive Guide for Beginners, veteran software engineer, educator, and author Ryan Mitchell delivers an intuitive, engaging, and practical roadmap to Python programming. The author walks you through the vocabulary, tools, foundational knowledge, and occasional pop-culture references you'll need to hone your skills with this popular programming language. You'll learn how to install and run Python on your own machine, get up and coding with the language quickly, and best practices for programming both independently and in the workplace. You'll also find: Key concepts in computer and data science explained from the ground upAdvanced Python topics such as logging, unit testing, multiprocessing, and interacting with databases.Introductions to some of Python's most popular third-party libraries: Flask, Django, Scrapy, Scikit-Learn, Numpy, and PandasAmusing anecdotes from the trenches of industry Perfect for tech-savvy professionals at any stage of their careers who are interested in diving into Python programming. Unlocking Python is also a must-read for readers who work in a technical role but are interested in getting more directly involved with programming, as well as non-Python programmers who want to apply their technical skill to a new language.
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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 Programming for Biology
Do you have a biological question that could be readily answered by computational techniques, but little experience in programming? Do you want to learn more about the core techniques used in computational biology and bioinformatics? Written in an accessible style, this guide provides a foundation for both newcomers to computer programming and those interested in learning more about computational biology. The chapters guide the reader through: a complete beginners' course to programming in Python, with an introduction to computing jargon; descriptions of core bioinformatics methods with working Python examples; scientific computing techniques, including image analysis, statistics and machine learning. This book also functions as a language reference written in straightforward English, covering the most common Python language elements and a glossary of computing and biological terms. This title will teach undergraduates, postgraduates and professionals working in the life sciences how to program with Python, a powerful, flexible and easy-to-use language.
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