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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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Python Programming
Maintaining a practical perspective, Python Programming: A Practical Approach acquaints you with the wonderful world of programming. The book is a starting point for those who want to learn Python programming. The backbone of any programming, which is the data structure and components such as strings, lists, etc., have been illustrated with many examples and enough practice problems to instill a level of self-confidence in the reader.Drawing on knowledge gained directly from teaching Computer Science as a subject and working on a wide range of projects related to ML, AI, deep learning, and blockchain, the authors have tried their best to present the necessary skills for a Python programmer. Once the foundation of Python programming is built and the readers are aware of the exact structure, dimensions, processing, building blocks, and representation of data, they can readily take up their specific problems from the area of interest and solve them with the help of Python. These include, but are not limited to, operators, control flow, strings, functions, module processing, object-oriented programming, exception and file handling, multithreading, synchronization, regular expressions, and Python database programming.This book on Python programming is specially designed to keep readers busy with learning fundamentals and generates a sense of confidence by attempting the assignment problems. We firmly believe that explaining any particular technology deviates from learning the fundamentals of a programming language. This book is focused on helping readers attempt implementation in their areas of interest through the skills imparted through this book. We have attempted to present the real essence of Python programming, which you can confidently apply in real life by using Python as a tool.Salient Features Based on real-world requirements and solution. Simple presentation without avoiding necessary details of the topic. Executable programs on almost every topic. Plenty of exercise questions, designed to test readers’ skills and understanding.Purposefully designed to be instantly applicable, Python Programming: A Practical Approach provides implementation examples so that the described subject matter can be immediately implemented due to the well-known versatility of Python in handling different data types with ease.
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Learn Python Programming
This edition offers updated content covering Python 3.9 to 3.12, new chapters on type hinting and CLI applications, and expanded practical examples, making it the ideal resource for both new and experienced Python programmersKey FeaturesCreate and deploy APIs and CLI applications, leveraging Python’s strengths in scripting and automationStay current with the latest features and improvements in Python, including pattern matching and the latest exception handling syntaxEngage with new real-world examples and projects, including competitive programming problems, to solidify your understanding of PythonBook DescriptionLearn Python Programming, Fourth Edition, provides a comprehensive, up-to-date introduction to Python programming, covering fundamental concepts and practical applications. This edition has been meticulously updated to include the latest features from Python versions 3.9 to 3.12, new chapters on type hinting and CLI applications, and updated examples reflecting modern Python web development practices. This Python book empowers you to take ownership of writing your software and become independent in fetching the resources you need. By the end of this book, you will have a clear idea of where to go and how to build on what you have learned from the book.Through examples, the book explores a wide range of applications and concludes by building real-world Python projects based on the concepts you have learned. This Python book offers a clear and practical guide to mastering Python and applying it effectively in various domains, such as data science, web development, and automation.What you will learnInstall and set up Python on Windows, Mac, and LinuxWrite elegant, reusable, and efficient codeAvoid common pitfalls such as duplication and over-engineeringUse functional and object-oriented programming approaches appropriatelyBuild APIs with FastAPI and program CLI applicationsUnderstand data persistence and cryptography for secure applicationsManipulate data efficiently using Python's built-in data structuresPackage your applications for distribution via the Python Package Index (PyPI)Solve competitive programming problems with PythonWho this book is forThis Python programming book is for everyone who wants to learn Python from scratch, as well as experienced programmers looking for a reference book. Prior knowledge of basic programming concepts will help you follow along, but it’s not a prerequisite
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Powerful Python
Learn the 5% of Python programming knowledge which exponentially accelerates your learning curve for the remaining 95%.Alleviate the overwhelm of "too much to learn, not enough time". This book cuts through the noise to focus on the "accelerators" that rapidly move the needle.Discover Python's key abstractions which enable and power the most important Python libraries, including Pandas; Django; Flask; SQLAlchemy; Twisted; Pytest; and more.Top Python programming performance is closer than you think. The difference between the best and the rest lies in the distinctions they make, the mental models they leverage, and their ability to perceive what others cannot. Powerful Python cuts through the noise to focus on these performance accelerators which rapidly improve your coding level and yield the most benefit on real-world production engineering and data teams.After a brief tour of the most necessary programming fundamentals; coding techniques and libraries including Pandas, Django, Flask, SQLAlchemy, Twisted, and Pytest are explored to unlock huge capabilities for the reader. Complex patterns are explained with only the minimum detail needed for use, and frequent code examples are used to show all methods in practice. For those ready to move beyond junior programmer stage, this book provides the 5% of knowledge that makes the remaining 95% of the journey a walk in the park.
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Learn Enough Python to Be Dangerous
All You Need to Know, and Nothing You Don't, to Solve Real Problems with Python Python is the dominant programming language for data science and an ideal first programming language for web development and many other uses. You should learn Python, but you don't need to learn "everything" to get started, just how to use it efficiently to solve real problems. In Learn Enough Python to Be Dangerous, renowned instructor Michael Hartl teaches the specific concepts, skills, and approaches you need to be professionally productive. Even if you've never programmed before, Hartl helps you quickly build technical sophistication and master the lore you need to succeed. Hartl introduces Python both as a general-purpose language and as a specialist tool for web development and data science, presenting focused examples and exercises that help you internalize what matters, without wasting time on details pros don't care about. Soon, it'll be like you were born knowing this stuff--and you'll be suddenly, seriously dangerous. Learn enough about . . . Applying core Python concepts with the interactive interpreter and command lineWriting object-oriented code with Python's native objectsDeveloping and publishing self-contained Python packagesUsing elegant, powerful functional programming techniquesBuilding new objects, and extending them via Test-Driven Development (TDD)Leveraging Python's exceptional shell scripting capabilitiesCreating and deploying a full web app, using routes, layouts, embedded Python, and formsGetting started with data science tools for calculation, visualization, analysis, and machine learningMastering concrete and informal skills every developer needs Like this book? Don't miss Michael Hartl's companion video tutorial, Learn Enough Python to Be Dangerous LiveLessons. Michael Hartl's Learn Enough Series includes books and video courses that focus on the most important parts of each subject, so you don't have to learn everything to get started--you just have to learn enough to be dangerous and solve technical problems yourself.
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Mathematical Logic through Python
Using a unique pedagogical approach, this text introduces mathematical logic by guiding students in implementing the underlying logical concepts and mathematical proofs via Python programming. This approach, tailored to the unique intuitions and strengths of the ever-growing population of programming-savvy students, brings mathematical logic into the comfort zone of these students and provides clarity that can only be achieved by a deep hands-on understanding and the satisfaction of having created working code. While the approach is unique, the text follows the same set of topics typically covered in a one-semester undergraduate course, including propositional logic and first-order predicate logic, culminating in a proof of Gödel's completeness theorem. A sneak peek to Gödel's incompleteness theorem is also provided. The textbook is accompanied by an extensive collection of programming tasks, code skeletons, and unit tests. Familiarity with proofs and basic proficiency in Python is assumed.
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Mathematical Logic through Python
Using a unique pedagogical approach, this text introduces mathematical logic by guiding students in implementing the underlying logical concepts and mathematical proofs via Python programming. This approach, tailored to the unique intuitions and strengths of the ever-growing population of programming-savvy students, brings mathematical logic into the comfort zone of these students and provides clarity that can only be achieved by a deep hands-on understanding and the satisfaction of having created working code. While the approach is unique, the text follows the same set of topics typically covered in a one-semester undergraduate course, including propositional logic and first-order predicate logic, culminating in a proof of Gödel's completeness theorem. A sneak peek to Gödel's incompleteness theorem is also provided. The textbook is accompanied by an extensive collection of programming tasks, code skeletons, and unit tests. Familiarity with proofs and basic proficiency in Python is assumed.
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Introduction to Python Programming and Data Structures, Global Edition
For introductory courses in Python Programming and Data Structures. A fundamentals first approach to programming helps students create efficient, elegant code. Introduction to Python Programming and Data Structures introduces students to basic programming concepts using a fundamentals-first approach that prepares students to learn object-oriented programming and advanced Python programming. This approach presents programming concepts and techniques that include control statements, loops, functions, and arrays before designing custom classes. Students learn basic logic and programming concepts prior to moving into object-oriented and GUI programming. The content incorporates a wide variety of problems with various levels of difficulty and covers many application areas to engage and motivate students.
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AI-Assisted Python for Nonprogrammers
It's hard to exaggerate Python's popularity: It's used for everything from data science to servers to the web. It's also famously "easy" to learn. However, learning to program in Python can still be a frustrating experience. AI-Assisted Python for Nonprogrammers is designed to give you the context you need to build a deep understanding not just of Python's syntax but also of the concepts behind it, even if you don't have any previous programming experience.Through clear explanations and explorations, author Reuven Lerner will have you writing simple Python programs in no time. By collaborating with AI chatbots to complete focused hands-on exercises, you'll reinforce core concepts like variables and values, conditions and loops, functions, and modules (while also getting a taste of coding with GenAI). But most importantly, you'll learn how to think about computers and software like a programmer—setting you up to better participate in technical conversations at your job and understand the influence of technology on our world.Write simple Python programs using core data structures, conditions, and loopsWrite and use Python functionsUse Python modulesGain the confidence to continue your Python journey
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