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A tool for Python programmers to incorporate the Java class libraries in their programs, so they don't have to create their own each time. It contains fast track sections at the end of each chapter, review questions and activities to provide extra practice for newcomers.
Jython is an implementation of the Python programming language written in 100% pure Java, so it runs under any compliant Java Virtual Machine. The secret to Jython's popularity lies in the combination of Java's librariesand tools with Python's rapid development capabilities. With Jython, you can write Python programs that integrate seamlessly with any Java code. And like Python, Jython can be used interactively, so you can get immediate results as you are programming.Jython Essentials provides a solid introduction to the Python language, offering a brief but thorough tour of the Python concepts you'll need to understand to use Jython effectively. The book makes frequent comparisonsbetween Python and Java, with special emphasis on the different object-oriented semantics of the two languages, so Java programmers can quickly get up to speed with Jython.Jython Essentials also covers the various ways in which Jython and Java can interact. For example, Jython code can create instances of pre-existing Java classes and call methods in those instances. You can write Jython classes that are direct subclasses of existing Java classesand use introspection to discern the capabilities of JavaBeans components. This book provides examples of using Jython with existing Java libraries, including the Swing GUI toolkit, the JDBC database API, the Servlet API, and various XML tools. And finally, the book shows howJython can be used as a scripting language within a Java program.With Jython Essentials, you have everything you need to start creating applications that mix the best of Python's interactivity and Java's robust libraries.
Jython is an open source implementation of the high-level, dynamic, object-oriented scripting language Python seamlessly integrated with the Java platform. The predecessor to Jython, JPython, is certified as 100% Pure Java. Jython is freely available for both commercial and noncommercial use and is distributed with source code. Jython is complementary to Java. The Definitive Guide to Jython, written by the official Jython team leads, covers Jython 2.5 (or 2.5.x)—from the basics to more advanced features. This book begins with a brief introduction to the language and then journeys through Jython’s different features and uses. The Definitive Guide to Jython is organized for beginners as well as advanced users of the language. The book provides a general overview of the Jython language itself, but it also includes intermediate and advanced topics regarding database, web, and graphical user interface (GUI) applications; Web services/SOA; and integration, concurrency, and parallelism, to name a few.
Today, anyone in a scientific or technical discipline needs programming skills. Python is an ideal first programming language, and Introduction to Programming in Python is the best guide to learning it. Princeton University’s Robert Sedgewick, Kevin Wayne, and Robert Dondero have crafted an accessible, interdisciplinary introduction to programming in Python that emphasizes important and engaging applications, not toy problems. The authors supply the tools needed for students to learn that programming is a natural, satisfying, and creative experience. This example-driven guide focuses on Python’s most useful features and brings programming to life for every student in the sciences, engineering, and computer science. Coverage includes Basic elements of programming: variables, assignment statements, built-in data types, conditionals, loops, arrays, and I/O, including graphics and sound Functions, modules, and libraries: organizing programs into components that can be independently debugged, maintained, and reused Object-oriented programming and data abstraction: objects, modularity, encapsulation, and more Algorithms and data structures: sort/search algorithms, stacks, queues, and symbol tables Examples from applied math, physics, chemistry, biology, and computer science—all compatible with Python 2 and 3 Drawing on their extensive classroom experience, the authors provide Q&As, exercises, and opportunities for creative practice throughout. An extensive amount of supplementary information is available at introcs.cs.princeton.edu/python. With source code, I/O libraries, solutions to selected exercises, and much more, this companion website empowers people to use their own computers to teach and learn the material.
This highly accessible textbook teaches programming from first principles. In common with many programming courses, it uses Python as the introductory programming language before going on to use Java as the vehicle for more advanced programming concepts. The first part, which teaches Python, covers fundamental programming concepts, such as data types and control structures and functions. It introduces more complex data types such as lists and dictionaries and also deals with file handling. It introduces object-oriented concepts and ends with a case study bringing together all the topics of the first semester. The second part uses Java to teach advanced concepts and centres around object-oriented programming, teaching key object-oriented concepts such as inheritance and polymorphism. The semester again ends with an advanced case study bringing together all the topics of the second semester. Topics and features: Assumes no prior knowledge, and makes the transition from Python to Java a smooth process Features numerous exercises and also an illustrative case study for each language Examines procedural and object-oriented methodologies, as well as design principles Covers such advanced topics as interfaces and lambda expressions, exceptions and Collections Includes a chapter on graphics programming in Python using Tkinter Introduces the latest Java technology for graphical interfaces, JavaFX Explains design concepts using UML notation Offering a gentle introduction to the field and assuming no prerequisite background, Programming in Two Semesters is the ideal companion to undergraduate modules in software development or programming. In addition, it will serve as a strong primer for professionals looking to strengthen their knowledge of programming with these languages.
The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics.
Are you a seasoned Java developer who wishes to learn Python? Perhaps you’ve just joined a project where a chunk of system integration code is written in Python. Or maybe you need to implement a report generation module in the next sprint and your colleague mentioned that Python would be the perfect tool for the job. In any case, if you are in a situation where you have to pick up the Python programming language overnight, this book is just for you! Hit the ground running and gain a fast-paced overview of what the Python language is all about, the syntax that it uses and the ecosystem of libraries and tools that surround the language. This concise book doesn’t spend time on details from an introductory programming course or document every single Python feature. Instead, Python for the Busy Java Developer is designed for experienced Java developers to obtain sufficient familiarity with the language and dive into coding, quickly. What You'll Learn Discover the fundamentals of the core Python language and how they compare to Java Understand Python syntax and the differences between Python 2.x and 3.x Explore the Python ecosystem, its standard libraries, and how to implement them Who This Book Is For Working programmers who are comfortable with Java or another object-oriented programming language such as C#
A comprehensive guide to exploring modern Python through data structures, design patterns, and effective object-oriented techniques Key Features Build an intuitive understanding of object-oriented design, from introductory to mature programs Learn the ins and outs of Python syntax, libraries, and best practices Examine a machine-learning case study at the end of each chapter Book Description Object-oriented programming (OOP) is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. Python Object-Oriented Programming, Fourth Edition dives deep into the various aspects of OOP, Python as an OOP language, common and advanced design patterns, and hands-on data manipulation and testing of more complex OOP systems. These concepts are consolidated by open-ended exercises, as well as a real-world case study at the end of every chapter, newly written for this edition. All example code is now compatible with Python 3.9+ syntax and has been updated with type hints for ease of learning. Steven and Dusty provide a comprehensive, illustrative tour of important OOP concepts, such as inheritance, composition, and polymorphism, and explain how they work together with Python's classes and data structures to facilitate good design. In addition, the book also features an in-depth look at Python's exception handling and how functional programming intersects with OOP. Two very powerful automated testing systems, unittest and pytest, are introduced. The final chapter provides a detailed discussion of Python's concurrent programming ecosystem. By the end of the book, you will have a thorough understanding of how to think about and apply object-oriented principles using Python syntax and be able to confidently create robust and reliable programs. What you will learn Implement objects in Python by creating classes and defining methods Extend class functionality using inheritance Use exceptions to handle unusual situations cleanly Understand when to use object-oriented features, and more importantly, when not to use them Discover several widely used design patterns and how they are implemented in Python Uncover the simplicity of unit and integration testing and understand why they are so important Learn to statically type check your dynamic code Understand concurrency with asyncio and how it speeds up programs Who this book is for If you are new to object-oriented programming techniques, or if you have basic Python skills and wish to learn how and when to correctly apply OOP principles in Python, this is the book for you. Moreover, if you are an object-oriented programmer coming from other languages or seeking a leg up in the new world of Python, you will find this book a useful introduction to Python. Minimal previous experience with Python is necessary.
Are you ready to learn the most powerful and popular programming language in the world? Code is the language of the future. And the time to learn the ins and outs of coding is now, unless of course you want to be left behind from the biggest revolution that mankind will witness. If for whatever reason, you have been looking to improve your programming skills, Python programming language could be the best option you can get right now. It makes everything so easy! From the rich and well-designed standard library and built-ins to the availability of modules and numerous third-party open source libraries, very few programming languages can beat it. Deemed as a high-level programming language, it is not surprising that many people find Phyton quite intimidating. Thus, they shy away from learning about it. Starting programming may seem to be a struggle but thank to this book you will be able to go from a complete beginner in the world of Python and turn yourself into an expert. You will Learn: - Basics of programming with Python - Python as an Object-Oriented Program - General Methods and Objects - What are Descriptors - Functions Inside of Python - Iterators and Generators - And much more! By learning this essential programming language, you will open tons of doors for both your personal and professional life. With Python, opportunities and possibilities are simply endless… Scroll up and click "BUY NOW with 1-Click" to Start Programming Today!
Are you looking for a complete guide on python? Then keep reading... Python is a programming language that has several features that makes it very attractive to programmers and developers. First of all, Python is a free programming language which means it is available for anybody. Python is also an open-source language which means you can contribute to the source code if you wish. In fact, Python is a language that is supported by a community that gathers its effort through the internet to improve this language. Python is a language that belongs to the category of high-level languages. This implies that Python does not require compiling like other languages such as C or C++, Fortran, and so on. It implies also that the syntax of Python is very easy to use and learn. These features make Python programs to be easily developed, interpreted, and maintained at low cost. Therefore, it allows sharing and collaborating to develop applications based on Python very efficient. Being an easy syntax and high-level programming language does not mean that Python is a very slow programming language. In fact, Python is considered a very competitive and productive language. When compared to other programming languages that are low-level and known to be fast, a Python script can be 3rd or 5th size of a similar script developed with C++ or Java. In addition to requiring less typing and debugging, Python does not require compiling. Once a Python script is developed, it can be run directly without additional steps of compiling or linking to other tools or libraries. In this book You will be able to learn about: Getting Started with Phyton Machine Learning with Phyton Types of Learning Machine Data Analysis with Machine Learning Data Science and How It Fits in Machine Learning Data science Algorithms and Models Data Analysis with Phyton How machine learning works for data science Use Phyton in Machine Learning Functions in Python Tips and Tricks for an Expert Phyton Programming Performed Python programming exercises on functions, strings, lists and mathematical calculations and much more! Python comes with a default library called the standard library which includes a set of modules like the math module for mathematical and numerical programming. Moreover, Python supports using other libraries developed by third parties. There is a wide range of third parties' packages that are available online and allows using advanced tools for a specific domain (e.g. Numpy library for Numerical programming with Python, Pandas, Matplotlib for developing figures and so on). Hence, when coding with Python language, you have access to a wide set of tools and pre-coded and built-in objects that can be easily used. You never start from scratch because there is a high chance that the function you want to use was already coded and made available for use by anybody. Python can be considered as a hybrid language in the context that it allows integrating and to be integrated with other programming languages. For instance, you can use pre-coded or compiled libraries that are written in C or C++ within Python. You can also call Python codes from scripts that are written in C or C++. Are you curious about Phyton Programming? Start learning now by clicking the "Buy Now" button.