Search results for "python in depth"
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Pro Python
Youve learned the basics of Python, but how do you take your skills to the next stage? Even if you know enough to be productive, there are a number of features that can take you to the next level in Python. Pro Python explores concepts and features normally left to experimentation, allowing you to be even more productive and creative. In addition to pure code concerns, Pro Python will develop your programming techniques and approaches, which will help make you a better Python programmer. Not only will this book help your code, it will also help you understand and interact with the many established Python communities, or even start your own. Take your Python knowledge and coding skills to the next level. Write clean, innovative code that will be respected among your peers. Make your code do more with introspection and metaprogramming. Design complete frameworks and libraries (two are included in the book!). For more information, including a link to the source code referenced in the book, please visit http://propython.com/.
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BiteSize Python for Intermediate Learners
This book is an introduction to Python for intermediate learners. It allows readers to take a slow and steady approach to building upon their understanding of Python code. While there are many books, websites, and online courses about the topic, Python programming is broken down here into easily digestible lessons of less than 5 minutes each, following a tried and tested BiteSize approach.Each lesson begins with a clear and concise introduction to the topic, giving the reader a strong base to start from and gets them ready for deeper learning. This is followed by coding demonstrations that further explore the ideas discussed. The book offers practice tasks in different difficulty levels, so readers can test their knowledge and grow their confidence. The reader will also play with case studies to solve real-world problems. Tips on how to incorporate Generative AI into a learning toolkit are provided, for purposes like feedback, practice exercises, code reviews, and exploring advanced topics. Recommended AI prompts can help readers identify areas for improvement, review key concepts, and track progress.This book is designed for intermediate learners with a basic understanding of Python. It is ideal for individuals with busy schedules or limited time for studying.
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Python Experiments in Physics and Astronomy
Python Experiments in Physics and Astronomy acts as a resource for science and engineering students or faculty who would like to see how a diverse selection of topics can be analyzed and simulated using Python programs. The book also provides Python solutions that can be learned from and modified as needed. The book is mainly aimed at undergraduates, but since many science students and faculty have limited exposure to scientific programming, having a collection of examples that address curve-fitting, Fast Fourier Transforms, image photometry and image alignment, and many others could be very helpful not just for learning from, but also to support classroom projects and demonstrations.Key Features:Features tutorials using Python for non-computer science students and faculty involved with scientific programmingContains complete scientific programming examples for teaching and academic projectsPresents detailed Python solutions for Physics and Astronomy topics, not normally covered in depth, because they would be too time-consumingPurchasers of the book can access the accompanying computer code via the Instructor Resources Download Hub.
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Dive Into Python
* Quick start to learning python—very example oriented approach * Book has its own Web site established by the author: http://diveintopython.org/ Author is well known in the Open Source community and the book has a unique quick approach to learning an object oriented language.
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Modern Django Web Development
Django has evolved into a powerful full-stack framework ideal for developing data-driven web applications, continuously expanding with new tools for asynchronous solutions, APIs, and real-time applications. This book explores modern Django development best practices, including Django Channels for WebSockets, Django REST Framework (DRF) for REST APIs, Graphene and Strawberry for GraphQL APIs, and integrating a front-end built with React The content is structured into two main parts, covering both fundamental and advanced concepts in a practical and digestible manner. The first part introduces Django's core concepts, starting with an overview of web development and Python's asyncio module for asynchronous processing. It then walks you through Django installation, project setup, and the admin interface. The Model-View-Template (MVT) architecture is explained in depth, with chapters on models, views, and templates, illustrating real-world examples. Additionally, it covers database interactions, introducing SQLAlchemy ORM and MongoDB integration to extend Django's capabilities beyond its default ORM. The second part delves into advanced Django features and the broader ecosystem. Topics include authentication, security, messaging, and reusable apps such as the Django toolbar. REST API development with Django REST Framework is explored, followed by an introduction to building GraphQL APIs using Graphene and Strawberry. A dedicated chapter covers Django Channels and the WebSocket protocol for real-time applications. Modern Django Web Development concludes with integrating React to develop front-end clients for Django-based REST, GraphQL, and WebSocket APIs, enabling a full-stack development experience. You Will: Explore the full spectrum of modern Django developmentLearn how to use SQLAlchemy MongoDB with DjangoUnderstand Django Channels for asynchronous web appsExplore DRF for building REST API in DjangoLearn how to build GraphQL API with Graphene and StrawberryUnderstand how to develop a Django-React app Who is it for: Software developers, web developers and engineers who are interested in adding Django to their development skillset. Python Developers can also leverage the power of modern Django with the help of this practical guide.
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Python
This book is an introduction to programming concepts that uses Python 3 as the target language. It follows a practical just in time presentation – material is given to the student when it is needed. Many examples will be based on games because Python has become the language of choice for basic game development. Designed as a year 1 textbook for introduction to programming classes or for the hobbyist who wants to learn the fundamentals of programming, the text assumes no programming experience.FEATURES:Introduces programming concepts using Python 3.Covers basic computer concepts such as loops, strings, functions, files, graphics, multimedia, algorithms, classes, writing code, etc. Develops graphics, exercises, and user interface using Pygame.Includes many examples based on video game development.4 color throughout with game demos on the companion files.New chapters on parsing (14) and graphics (15).Instructor ancillaries for use as a textbook.
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Beginning Python
Beginning Python: Using Python 2.6 and Python 3.1 introduces this open source, portable, interpreted, object-oriented programming language that combines remarkable power with clear syntax. This book enables you to quickly create robust, reliable, and reusable Python applications by teaching the basics so you can quickly develop Web and scientific applications, incorporate databases, and master systems tasks on various operating systems, including Linux, MAC OS, and Windows. You'll get a comprehensive tutorial that guides you from writing simple, basic Python scripts all the way through complex concepts, and also features a reference of the standard modules with examples illustrating how to implement features in the various modules. Plus, the book covers using Python in specific program development domains, such as XML, databases, scientific applications, network programming, and Web development.
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Python Data Analytics
Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn. This third edition is fully updated for the latest version of Python and its related libraries, and includes coverage of social media data analysis, image analysis with OpenCV, and deep learning libraries. Each chapter includes multiple examples demonstrating how to work with each library. At its heart lies the coverage of pandas, for high-performance, easy-to-use data structures and tools for data manipulationAuthor Fabio Nelli expertly demonstrates using Python for data processing, management, and information retrieval. Later chapters apply what you've learned to handwriting recognition and extending graphical capabilities with the JavaScript D3 library. Whether you are dealing with sales data, investment data, medical data, web page usage, or other data sets, Python Data Analytics, Third Edition is an invaluable reference with its examples of storing, accessing, and analyzing data.What You'll LearnUnderstand the core concepts of data analysis and the Python ecosystemGo in depth with pandas for reading, writing, and processing dataUse tools and techniques for data visualization and image analysisExamine popular deep learning libraries Keras, Theano,TensorFlow, and PyTorchWho This Book Is ForExperienced Python developers who need to learn about Pythonic tools for data analysis
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Expert Python Programming
Gain a deep understanding of building, maintaining, packaging, and shipping robust Python applicationsKey FeaturesDiscover the new features of Python, such as dictionary merge, the zoneinfo module, and structural pattern matchingCreate manageable code to run in various environments with different sets of dependenciesImplement effective Python data structures and algorithms to write, test, and optimize codeBook DescriptionThis new edition of Expert Python Programming provides you with a thorough understanding of the process of building and maintaining Python apps. Complete with best practices, useful tools, and standards implemented by professional Python developers, this fourth edition has been extensively updated. Throughout this book, you’ll get acquainted with the latest Python improvements, syntax elements, and interesting tools to boost your development efficiency.The initial few chapters will allow experienced programmers coming from different languages to transition to the Python ecosystem. You will explore common software design patterns and various programming methodologies, such as event-driven programming, concurrency, and metaprogramming. You will also go through complex code examples and try to solve meaningful problems by bridging Python with C and C++, writing extensions that benefit from the strengths of multiple languages. Finally, you will understand the complete lifetime of any application after it goes live, including packaging and testing automation.By the end of this book, you will have gained actionable Python programming insights that will help you effectively solve challenging problems.What you will learnExplore modern ways of setting up repeatable and consistent Python development environmentsEffectively package Python code for community and production useLearn modern syntax elements of Python programming, such as f-strings, enums, and lambda functionsDemystify metaprogramming in Python with metaclassesWrite concurrent code in PythonExtend and integrate Python with code written in C and C++Who this book is forThe Python programming book is intended for expert programmers who want to learn Python’s advanced-level concepts and latest features.Anyone who has basic Python skills should be able to follow the content of the book, although it might require some additional effort from less experienced programmers. It should also be a good introduction to Python 3.9 for those who are still a bit behind and continue to use other older versions.
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Introduction to Python Programming for Scientists and Engineers
Python is one of the most popular programming languages, widely used for data analysis and modelling, and is fast becoming the leading choice for scientists and engineers. Unlike other textbooks introducing Python, typically organised by language syntax, this book uses many examples from across Biology, Chemistry, Physics, Earth science, and Engineering to teach and motivate students in science and engineering. The text is organised by the tasks and workflows students undertake day-to-day, helping them see the connections between programming tools and their disciplines. The pace of study is carefully developed for complete beginners, and a spiral pedagogy is used so concepts are introduced across multiple chapters, allowing readers to engage with topics more than once. “Try This!” exercises and online Jupyter notebooks encourage students to test their new knowledge, and further develop their programming skills. Online solutions are available for instructors, alongside discipline-specific homework problems across the sciences and engineering.
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Learning Advanced Python by Studying Open Source Projects
This book is one of its own kind. It is not an encyclopedia or a hands-on tutorial that traps readers in the tutorial-hell. It is a distillation of just one common Python user’s learning experience. The experience is packaged with exceptional teaching techniques, careful dependence unraveling and most importantly, passion.Learning Advanced Python by Studying Open Source Projects helps readers overcome the difficulty in their day-to-day tasks and seek insights from solutions in famous open source projects. Different from a technical manual, this book mixes the technical knowledge, real-world applications and more theoretical content, providing readers with a practical and engaging approach to learning Python.Throughout the book, readers will learn how to write Python code that is efficient, readable, and maintainable, covering key topics such as data structures, algorithms, object-oriented programming, and more. The author's passion for Python shines through in the book, making it an enjoyable and inspiring read for both beginners and experienced programmers.
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Pro Python 3
Refine your programming techniques and approaches to become a more productive and creative Python programmer. This book explores the concepts and features that will improve not only your code but also your understanding of the Python community with insights and details about the Python philosophy.Pro Python 3, Third Edition gives you the tools to write clean, innovative code. It starts with a review of some core Python principles, which are illustrated by various concepts and examples later in the book. The first half of the book explores aspects of functions, classes, protocols, and strings, describing techniques which may not be common knowledge, but which together form a solid foundation. Later chapters cover documentation, testing, and app distribution. Along the way, you’ll develop a complex Python framework that incorporates ideas learned throughout the book.Updates in this edition include the role of iterators in Python 3, web scraping with Scrapy and BeautifulSoup, using Requests to call web pages without strings, new tools for distribution and installation, and much more. By the end of the book you'll be ready to deploy uncommon features that can take your skills to the next level in Python.What You’ll LearnImplement programs with various types of Python functionsWork with classes and object-oriented programmingUse strings from the standard library and third-party librariesHarvest web site data with PythonAutomate unit testing by writing a test suiteReview imaging, random number generation, and NumPy scientific extensionsUnderstand The Zen of Python documentation to help you decide the best way to distribute your codeWho This Book Is ForIntermediate programmers familiar with Python who are looking to move to an advanced level. You should have written at least a simple Python application, and be comfortable with a basic object-oriented approach, using the interactive interpreter, and writing control structures.
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CPython
Deep Dive CPython explores the internal mechanics of CPython, the widely used Python interpreter written in C. Starting with a practical guide on downloading and compiling the CPython source, this book is perfect for developers eager to understand Python's behaviour at a fundamental level. The book takes readers from basic concepts to complex details with a systematic breakdown of core components. It covers everything from CPython's data structures like PyObject and PyTypeObject to object lifecycle management, giving insight into memory allocation and object reference counting. Each chapter illustrates CPython's architecture, such as Python's "everything is an object" philosophy, list handling, string manipulation, and dictionary operations. Readers will explore Python's REPL modifications, string internals, and custom type creation with practical examples, like crafting a "backflipping" PyKittyType. Detailed sections on Python's virtual machine operations, bytecode generation, and exception handling enrich readers' understanding of how Python code is parsed, compiled, and executed. This book is a thorough guide for readers who want to go beyond basic Python use and understand how it works internally. Covering complex concepts like generators, iterators, descriptors, and metaclasses, this book equips readers with a thorough grasp of Python's performance optimization and design complexities. What you will learn: How to download, compile, and modify CPython's source codeGain insight into fundamental structures like PyObject and PyTypeObject, Understand Python's detailed handling of lists, strings, dictionaries, and the REPL environment.What are bytecode generation, custom types, and the inner workings of Python's virtual machine. Who this book is for: Python programmers aiming to gain a deeper understanding of Python's internals and move beyond standard usage, as well as software professionals interested in CPython's C-based implementation and core architecture.
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Python: Advanced Guide to Artificial Intelligence
Demystify the complexity of machine learning techniques and create evolving, clever solutions to solve your problemsKey FeaturesMaster supervised, unsupervised, and semi-supervised ML algorithms and their implementation Build deep learning models for object detection, image classification, similarity learning, and moreBuild, deploy, and scale end-to-end deep neural network models in a production environmentBook DescriptionThis Learning Path is your complete guide to quickly getting to grips with popular machine learning algorithms. You'll be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this Learning Path will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries. You'll bring the use of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Next, you'll learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF clusters, deploy production models with TensorFlow Serving. You'll implement different techniques related to object classification, object detection, image segmentation, and more. By the end of this Learning Path, you'll have obtained in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problemsThis Learning Path includes content from the following Packt products:Mastering Machine Learning Algorithms by Giuseppe BonaccorsoMastering TensorFlow 1.x by Armando FandangoDeep Learning for Computer Vision by Rajalingappaa ShanmugamaniWhat you will learnExplore how an ML model can be trained, optimized, and evaluatedWork with Autoencoders and Generative Adversarial NetworksExplore the most important Reinforcement Learning techniquesBuild end-to-end deep learning (CNN, RNN, and Autoencoders) modelsWho this book is forThis Learning Path is for data scientists, machine learning engineers, artificial intelligence engineers who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. You will encounter the advanced intricacies and complex use cases of deep learning and AI. A basic knowledge of programming in Python and some understanding of machine learning concepts are required to get the best out of this Learning Path.
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