What Is Modular Programming In Python
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Modular Programming with Python
Introducing modular techniques for building sophisticated programs using Python About This Book The book would help you develop succinct, expressive programs using modular deign The book would explain best practices and common idioms through carefully explained and structured examples It will have broad appeal as far as target audience is concerned and there would be take away for all beginners to Python Who This Book Is For This book is intended for beginner to intermediate level Python programmers who wish to learn how to use modules and packages within their programs. While readers must understand the basics of Python programming, no knowledge of modular programming techniques is required. What You Will Learn Learn how to use modules and packages to organize your Python code Understand how to use the import statement to load modules and packages into your program Use common module patterns such as abstraction and encapsulation to write better programs Discover how to create self-testing Python packages Create reusable modules that other programmers can use Learn how to use GitHub and the Python Package Index to share your code with other people Make use of modules and packages that others have written Use modular techniques to build robust systems that can handle complexity and changing requirements over time In Detail Python has evolved over the years and has become the primary choice of developers in various fields. The purpose of this book is to help readers develop readable, reliable, and maintainable programs in Python. Starting with an introduction to the concept of modules and packages, this book shows how you can use these building blocks to organize a complex program into logical parts and make sure those parts are working correctly together. Using clearly written, real-world examples, this book demonstrates how you can use modular techniques to build better programs. A number of common modular programming patterns are covered, including divide-and-conquer, abstraction, encapsulation, wrappers and extensibility. You will also learn how to test your modules and packages, how to prepare your code for sharing with other people, and how to publish your modules and packages on GitHub and the Python Package Index so that other people can use them. Finally, you will learn how to use modular design techniques to be a more effective programmer. Style and approach This book will be simple and straightforward, focusing on imparting learning through a wide array of examples that the readers can put into use as they read through the book. They should not only be able to understand the way modules help in improving development, but they should also be able to improvise on their techniques of writing concise and effective code.
Python Web Programming
A Python community leader teaches professionals how to integrate web applications with Python.
Introduction to Programming in Python
Author: Robert Sedgewick
language: en
Publisher: Addison-Wesley Professional
Release Date: 2015-05-27
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.