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R 458.00
Mastering Python
Use advanced features of Python to write high-quality, readable code and packagesKey FeaturesExtensively updated for Python 3.10 with new chapters on design patterns, scientific programming, machine learning, and interactive PythonShape your scripts using key concepts like concurrency, performance optimization, asyncio, and multiprocessingLearn how advanced Python features fit together to produce maintainable codeBook DescriptionEven if you find writing Python code easy, writing code that is efficient, maintainable, and reusable is not so straightforward. Many of Python's capabilities are underutilized even by more experienced programmers. Mastering Python, Second Edition, is an authoritative guide to understanding advanced Python programming so you can write the highest quality code. This new edition has been extensively revised and updated with exercises, four new chapters and updates up to Python 3.10. Revisit important basics, including Pythonic style and syntax and functional programming. Avoid common mistakes made by programmers of all experience levels. Make smart decisions about the best testing and debugging tools to use, optimize your code's performance across multiple machines and Python versions, and deploy often-forgotten Python features to your advantage. Get fully up to speed with asyncio and stretch the language even further by accessing C functions with simple Python calls. Finally, turn your new-and-improved code into packages and share them with the wider Python community. If you are a Python programmer wanting to improve your code quality and readability, this Python book will make you confident in writing high-quality scripts and taking on bigger challengesWhat you will learnWrite beautiful Pythonic code and avoid common Python coding mistakesApply the power of decorators, generators, coroutines, and metaclassesUse different testing systems like pytest, unittest, and doctestTrack and optimize application performance for both memory and CPU usageDebug your applications with PDB, Werkzeug, and faulthandlerImprove your performance through asyncio, multiprocessing, and distributed computingExplore popular libraries like Dask, NumPy, SciPy, pandas, TensorFlow, and scikit-learnExtend Python's capabilities with C/C++ libraries and system callsWho this book is forThis book will benefit more experienced Python programmers who wish to upskill, serving as a reference for best practices and some of the more intricate Python techniques. Even if you have been using Python for years, chances are that you haven't yet encountered every topic discussed in this book. A good understanding of Python programming is necessary
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Python: Master the Art of Design Patterns
Ensure your code is sleek, efficient and elegant by mastering powerful Python design patternsAbout This Book* Learn all about abstract design patterns and how to implement them in Python 3* Understand the structural, creational, and behavioral Python design patterns* Get to know the context and application of design patterns to solve real-world problems in software architecture, design, and application development* Discover how to simplify Design Pattern implementation using the power of Python 3Who This Book Is ForIf you have basic Python skills and wish to learn in depth how to correctly apply appropriate design patterns, this course is tailor made for you.What You Will Learn* Discover what design patterns are and how to apply them to writing Python* Implement objects in Python by creating classes and defining methods* Separate related objects into a taxonomy of classes and describe the properties and behaviors of those objects via the class interface* Understand when to use object-oriented features, and more importantly when not to use them* Get to know proven solutions to common design issues* Explore the design principles that form the basis of software design, such as loose coupling, the Hollywood principle, and the Open Close principle, among others* Use Structural Design Patterns and find out how objects and classes interact to build larger applications* Improve the productivity and code base of your application using Python design patterns* Secure an interface using the Proxy patternIn DetailPython is an object-oriented scripting language that is used in everything from data science to web development. Known for its simplicity, Python increases productivity and minimizes development time. Through applying essential software engineering design patterns to Python, Python code becomes even more efficient and reusable from project to project.This learning path takes you through every traditional and advanced design pattern best applied to Python code, building your skills in writing exceptional Python. Divided into three distinct modules, you'll go from foundational to advanced concepts by following a series of practical tutorials.Start with the bedrock of Python programming - the object-oriented paradigm. Rethink the way you work with Python as you work through the Python data structures and object-oriented techniques essential to modern Python programming. Build your confidence as you learn Python syntax, and how to use OOP principles with Python tools such as Django and Kivy.In the second module, run through the most common and most useful design patterns from a Python perspective. Progress through Singleton patterns, Factory patterns, Facade patterns and more all with detailed hands-on guidance. Enhance your professional abilities in in software architecture, design, and development.In the final module, run through the more complex and less common design patterns, discovering how to apply them to Python coding with the help
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Pythonic Programming
Make your good Python code even better by following proven and effective pythonic programming tips. Avoid logical errors that usually go undetected by Python linters and code formatters, such as frequent data look-ups in long lists, improper use of local and global variables, and mishandled user input. Discover rare language features, like rational numbers, set comprehensions, counters, and pickling, that may boost your productivity. Discover how to apply general programming patterns, including caching, in your Python code. Become a better-than-average Python programmer, and develop self-documented, maintainable, easy-to-understand programs that are fast to run and hard to break.Python is one of the most popular and rapidly growing modern programming languages. With more than 200 standard libraries and even more third-party libraries, it reaches into the software development areas as diverse as artificial intelligence, bioinformatics, natural language processing, and computer vision. Find out how to improve your understanding of the spirit of the language by using one hundred pythonic tips to make your code safer, faster, and better documented.This programming style manual is a quick reference of helpful hints and a random source of inspiration. Choose the suitable data structures for searching and sorting jobs and become aware of how a wrong choice may cause your application to be completely ineffective. Understand global and local variables, class and instance attributes, and information-hiding techniques. Create functions with flexible interfaces. Manage intermediate computation results by caching them in files and memory to improve performance and reliability. Polish your documentation skills to make your code easy for other programmers to understand. As a bonus, discover Easter eggs cleverly planted in the standard library by its developers.Polish, secure, and speed-up your Python applications, and make them easier to maintain by following pythonic programming tips.What You Need:You will need a Python interpreter (ideally, version 3.4 or above) and the standard Python library that usually comes with the interpreter.
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Mastering Python Design Patterns
Exploit various design patterns to master the art of solving problems using PythonKey FeaturesMaster the application design using the core design patterns and latest features of Python 3.7Learn tricks to solve common design and architectural challengesChoose the right plan to improve your programs and increase their productivityBook DescriptionPython is an object-oriented scripting language that is used in a wide range of categories. In software engineering, a design pattern is an elected solution for solving software design problems. Although they have been around for a while, design patterns remain one of the top topics in software engineering, and are a ready source for software developers to solve the problems they face on a regular basis. This book takes you through a variety of design patterns and explains them with real-world examples. You will get to grips with low-level details and concepts that show you how to write Python code, without focusing on common solutions as enabled in Java and C++. You'll also fnd sections on corrections, best practices, system architecture, and its designing aspects. This book will help you learn the core concepts of design patterns and the way they can be used to resolve software design problems. You'll focus on most of the Gang of Four (GoF) design patterns, which are used to solve everyday problems, and take your skills to the next level with reactive and functional patterns that help you build resilient, scalable, and robust applications. By the end of the book, you'll be able to effciently address commonly faced problems and develop applications, and also be comfortable working on scalable and maintainable projects of any size.What you will learnExplore Factory Method and Abstract Factory for object creationClone objects using the Prototype patternMake incompatible interfaces compatible using the Adapter patternSecure an interface using the Proxy patternChoose an algorithm dynamically using the Strategy patternKeep the logic decoupled from the UI using the MVC patternLeverage the Observer pattern to understand reactive programmingExplore patterns for cloud-native, microservices, and serverless architecturesWho this book is forThis book is for intermediate Python developers. Prior knowledge of design patterns is not required to enjoy this book.
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Deep Dive Python
Take your programming skills to the next level by expanding real-world Python applications in open-source code. This book is an essential guide for experienced developers looking to enhance their Python proficiency. Using code examples from popular open-source projects you'll master Python concepts and see how they are applied in production-level code. By understanding code from established projects, you'll develop a deeper appreciation for Python's capabilities and learn best practices that have been battle-tested in the real world. You'll gain the confidence to tackle complex projects, optimize your code, and implement advanced Python features effectively. You'll also examine typing, generators, iterators, the itertools module, multithreading, multiprocessing, and asyncio. This will equip you to build production-ready Python programs and libraries. Whether you're building large-scale applications, contributing to open-source projects, or solving intricate programming challenges, Deep Dive Python will provide you with the knowledge and practical experience to excel in your Python development journey. What You Will Learn Master Python's core data structures and how to use them effectively. Implement decorators, descriptors, metaclasses, and abstract base classes in your code Enhance your code with functional programming techniques using the functools module Improve iteration with generators, iterators, and the itertools module Select the best Python concurrent programming models to use for optimal performance Apply best practices for code organization, packaging, and creating maintainable Python projects Who This Book Is For Experienced Python developers who want to expand their programming skils
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Python for Engineers and Scientists
This book equips technical professionals with a complete, structured path to mastering Python for real-world engineering and scientific applications. As Python becomes central to research labs, automation, simulation, and data-driven engineering, the learning curve remains steep. This book bridges that gap with a practical roadmap from fundamentals to professional-grade scientific computing.The book begins by building a strong programming foundation—covering Python’s architecture, essential syntax, data structures, modules, functions, control flow, and object-oriented design. Readers learn not only how to write Python, but why the language behaves the way it does, ensuring deep understanding and strong problem-solving skills. From there, the focus shifts to practical engineering tools. Dedicated chapters train readers in file handling, math modules, and key scientific libraries including NumPy, SciPy, Pandas, and Matplotlib, enabling efficient computation, signal processing, data analysis, and high-quality visualization. Advanced chapters then showcase Python’s versatility through GUI development with Kivy, database work with SQLAlchemy, and hands-on control system modeling and analysis. Each topic is rooted in industry and academic scenarios, making the content directly applicable to automation, simulation, data workflows, and engineering computation.Whether you're a student building foundational skills or a professional modernizing engineering workflows, this guide provides the programming depth, scientific tools, and applied knowledge needed to use Python confidently for prototyping, simulation, analysis, and automation. It is the one-stop resource for mastering Python in technical disciplines.What you will learn:Learn core Python programming concepts, including variables, loops, functions, and object-oriented principles in a scientific and engineering context.Build strong skills in key scientific Python libraries such as NumPy, Pandas, Matplotlib, and SciPy for computation, analysis, and visualization.Apply Python to real-world engineering scenarios, including dynamic control systems and automation workflows.Develop interactive engineering applications by creating graphical user interfaces (GUIs) with Kivy. Who this book is for:This book is intended for practicing engineers and scientists across various disciplines of engineering who need to use Python for complex problem-solving, simulation, and data analysis in their work.
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