Search results for "Python"
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Simple Python
It is no longer necessary to know how to program to use a computer. However, being able to program opens up new possibilities. It is also fun! This book will teach you how to write your own programs using an easy to learn yet extremely versatile language called Python. The book assumes no prior knowledge of programming, so it is suitable for complete beginners. It explains how to write simple standalone procedural (or imperative) programs; for those wishing to develop their skills further, a companion volume builds upon the material here to explain how to write object-orientated programs and incorporate graphics. Once you learn Python, there will probably never be any need to learn any other language, but if you do decide to learn another language the principles taught here should make the learning curve much more manageable. Based upon the recognition that the best way to learn how to do something is by doing it, the book is generously supplemented by examples and exercises.
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Beginning Python 3 with Grok 2
This book is a comprehensive guide designed to teach the fundamentals of Python programming while introducing the exciting possibilities of Generative AI. Whether you’re a novice or a developer looking to integrate Grok into your workflow, this book offers a clear, step-by-step path to mastering Python and leveraging AI-driven code generation. It begins by covering Python fundamentals, including data types, string manipulation, loops, conditional logic, and exception handling. It then introduces Python collections, such as lists, dictionaries, and sets, along with their practical applications. Readers will explore essential Python libraries like NumPy and Pandas, learning how to manipulate data and perform advanced operations. The last two chapters cover Generative AI and Grok, distinguishing it from conversational AI and provides hands-on examples of Grok-generated Python code to solve various programming tasks. Readers will find a balanced mix of theory, practical examples, and Grok-generated code to build both foundational programming skills and an understanding of AI-driven development.FEATURES• Covers Python programming basics and popular libraries like NumPy and Pandas, with a focus on practical applications• Introduces Generative AI concepts and Grok, showcasing its use in generating Python code• Includes companion files with code and images -- available from the publisher for downloading (with proof of purchase)
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Matematicas y Programacion En Python (2* Edicion)
El libro contiene 120 programas originales de Python y mas de 110 ilustraciones. Esperamos que sea util tanto a estudiantes de bachillerato, como a estudiantes de ciencias de los primeros cursos universitarios, asi como recurso pedagogico para los profesores. Todos los programas y graficas del libro se han elaborado utilizando software libre, que se puede obtener gratuita y legalmente en internet, por lo que no es necesario adquirir ningun software adicional. El lenguaje Python es especialmente adecuado para el aprendizaje de programacion, y actualmente es el lenguaje mas utilizado como lenguaje de introduccion a la programacion en las universidades de Estados Unidos. Se puede programar en Python tanto si eres usuario de Windows como si prefieres Mac o Linux. Puedes descargar gratuitamente un extracto de mas de 70 paginas del libro en formato pdf desde nuestro sitio web www.pysamples.com. Los compradores del libro tambien pueden descargar gratuitamente el codigo de los programas del libro.
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Metaprogramming with Python
A practical approach to metaprogramming with real-world examples that enables the development of advanced frameworks, libraries, and applications using PythonKey FeaturesLearn applied metaprogramming through a simple step-by-step approachWork with easily understandable examples and explanations that take you deep into the theory of metaprogrammingGet practical experience in writing reusable code with real-world examplesBook DescriptionEffective and reusable code makes your application development process seamless and easily maintainable. With Python, you will have access to advanced metaprogramming features that you can use to build high-performing applications. The book starts by introducing you to the need and applications of metaprogramming, before navigating the fundamentals of object-oriented programming. Next, you will learn about simple decorators, work with metaclasses, and later focus on introspection and reflection. You'll also delve into generics and typing before defining templates for algorithms. As you progress, you will understand your code using abstract syntax trees and explore method resolution order. This Python book also shows you how to create your own dynamic objects before structuring the objects through design patterns. Finally, you will learn simple code-generation techniques along with discovering best practices and eventually building your own applications. By the end of this learning journey, you'll have acquired the skills and confidence you need to design and build reusable high-performing applications that can solve real-world problems.What you will learnUnderstand the programming paradigm of metaprogramming and its needRevisit the fundamentals of object-oriented programmingDefine decorators and work with metaclassesEmploy introspection and reflection on your codeApply generics, typing, and templates to enhance your codeGet to grips with the structure of your code through abstract syntax trees and the behavior through method resolution orderCreate dynamic objects and generate dynamic codeUnderstand various design patterns and best practicesWho this book is forIf you are an intermediate-level Python programmer looking to enhance your coding skills by developing reusable and advanced frameworks, then this book is for you. Basic knowledge of Python programming will help you get the most out of this learning journey.
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Learning Python: A Course in 16 Lessons for GCSE
This is an introductory text book that teaches Python programming. It is intended mainly for GCSE and IGCSE Computer Science students. It is a very practical book and assumes that the student knows little. The book starts by looking at the Python programming environment, then entering commands at the command prompt. Later on short programs,followed by longer programs. By the time the last chapter has been reached longer programs suitable for coursework are discussed. If used as a text book to learn programming, it is suggested that one lesson (chapter) from the book is studied each week. That way a student can learn Python in 4 months.
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Conceptual Programming with Python
Thorsten and Isaac have written this book based on a programming course we teach for Master's Students at the School of Computer Science of the University of Nottingham. The book is intended for students with little or no background in programming coming from different backgrounds educationally as well as culturally. It is not mainly a Python course but we use Python as a vehicle to teach basic programming concepts. Hence, the words conceptual programming in the title. We cover basic concepts about data structures, imperative programming, recursion and backtracking, object-oriented programming, functional programming, game development and some basics of data science.
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Competitive Programming in Python
Want to kill it at your job interview in the tech industry? Want to win that coding competition? Learn all the algorithmic techniques and programming skills you need from two experienced coaches, problem setters, and jurors for coding competitions. The authors highlight the versatility of each algorithm by considering a variety of problems and show how to implement algorithms in simple and efficient code. Readers can expect to master 128 algorithms in Python and discover the right way to tackle a problem and quickly implement a solution of low complexity. Classic problems like Dijkstra's shortest path algorithm and Knuth-Morris-Pratt's string matching algorithm are featured alongside lesser known data structures like Fenwick trees and Knuth's dancing links. The book provides a framework to tackle algorithmic problem solving, including: Definition, Complexity, Applications, Algorithm, Key Information, Implementation, Variants, In Practice, and Problems. Python code included in the book and on the companion website.
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Python for Engineering and Scientific Computing
It's finally here-your guide to Python for engineers and scientists, by an engineer and scientist! Get to know your development environments and the key Python modules you'll need: NumPy, SymPy, SciPy, Matplotlib, and VPython. Understand basic Python program structures and walk through practical exercises that start simple and increase in complexity as you work your way through the book. With information on statistical calculations, Boolean algebra, and interactive programming with Tkinter, this Python guide belongs on every scientist's shelf!Highlights include:1) Program structures2) NumPy3) Matplotlib4) SymPy5) SciPy6) VPython7) Tkinter8) Numerical calculations9) Statistical calculations10) Boolean algebra
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Hacker's Guide to Scaling Python
Python is an excellent programming language that allows to write applications quickly. But how do you make those applications scale for thousands of users and requests? It takes years of practice, research, trial and errors to build experience and knowledge along the way. Simple questions such as ""How do I make my code faster?,"" ""How do I make sure there is no bottleneck?"" or ""How do I run this application on several computers?"" cost hours to find satisfying answers. Without enough background on the topic, you'll never be sure that any solution you'll come up with will be correct. In The Hacker's Guide to Scaling Python, you will learn how to solve these issues. This book provides guidelines, tips and best practice on how to build high performing Python applications. Adding a few interview of experts on the subject, you will learn how you can distribute your Python application so it can process thousands of requests.
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Non-Programmers Tutorial For Python 2 and 3
This book is a tutorial for the Python 2 and 3 programming language designed for someone with no programming experience. All the examples work in Python 2.6 and Python 3.
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Python Architecture Patterns
Make the best of your test suites by using cutting-edge software architecture patterns in PythonKey FeaturesLearn how to create scalable and maintainable applicationsBuild a web system for micro messaging using concepts in the bookUse profiling to find bottlenecks and improve the speed of the systemBook DescriptionDeveloping large-scale systems that continuously grow in scale and complexity requires a thorough understanding of how software projects should be implemented. Software developers, architects, and technical management teams rely on high-level software design patterns such as microservices architecture, event-driven architecture, and the strategic patterns prescribed by domain-driven design (DDD) to make their work easier.This book covers these proven architecture design patterns with a forward-looking approach to help Python developers manage application complexity—and get the most value out of their test suites.Starting with the initial stages of design, you will learn about the main blocks and mental flow to use at the start of a project. The book covers various architectural patterns like microservices, web services, and event-driven structures and how to choose the one best suited to your project. Establishing a foundation of required concepts, you will progress into development, debugging, and testing to produce high-quality code that is ready for deployment. You will learn about ongoing operations on how to continue the task after the system is deployed to end users, as the software development lifecycle is never finished.By the end of this Python book, you will have developed "architectural thinking": a different way of approaching software design, including making changes to ongoing systems.What you will learnThink like an architect, analyzing software architecture patternsExplore API design, data storage, and data representation methodsInvestigate the nuances of common architectural structuresUtilize and interoperate elements of patterns such as microservicesImplement test-driven development to perform quality code testingRecognize chunks of code that can be restructured as packagesMaintain backward compatibility and deploy iterative changesWho this book is forThis book will help software developers and architects understand the structure of large complex systems and adopt architectural patterns that are scalable. Examples in the book are implemented in Python so a fair grasp of basic Python concepts is expected. Proficiency in any programming languages such as Java or JavaScript is sufficient.
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