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 Programming introduces one of the most rapidly evolving and preferred programming language using the concept of modularity. One of the highlights of the text is its in-depth treatment of basic concepts.
Joint Modular Languages Conference, JMLC 2000 Zurich, Switzerland, September 6-8, 2000 Proceedings
Author: Jürg Gutknecht
Thecircleisclosed.The European Modula-2 Conference was originally launched with the goal of increasing the popularity of Modula-2, a programming language created by Niklaus Wirth and his team at ETH Zuric ̈ h as a successor of Pascal. For more than a decade, the conference has wandered through Europe, passing Bled,Slovenia,in1987,Loughborough,UK,in1990,Ulm,Germany,in1994,and Linz, Austria, in 1997. Now, at the beginning of the new millennium, it is back at its roots in Zuric ̈ h, Switzerland. While traveling through space and time, the conference has mutated. It has widened its scope and changed its name to Joint Modular Languages Conference (JMLC). With an invariant focus, though, on modularsoftwareconstructioninteaching,research,and“outthere”inindustry. This topic has never been more important than today, ironically not because of insu?cient language support but, quite on the contrary, due to a truly c- fusing variety of modular concepts o?ered by modern languages: modules, pa- ages, classes, and components, the newest and still controversial trend. “The recent notion of component is still very vaguely de?ned, so vaguely, in fact, that it almost seems advisable to ignore it.” (Wirth in his article “Records, Modules, Objects, Classes, Components” in honor of Hoare’s retirement in 1999). Clar- cation is needed.
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.
Joint Modular Languages Conference, JMLC 2003, Klagenfurt, Austria, August 25-27, 2003, Proceedings
Author: László Böszörményi
Publisher: Springer Science & Business Media
This book constitutes the refereed proceedings of the international Joint Modular Languages Conference, JMLC 2003, held in Klagenfurt, Austria in August 2003. The 17 revised full papers and 10 revised short papers presented together with 5 invited contributions were carefully reviewed and selected from 47 submissions. The papers are organized in topical sections on architectural concepts and education, component architectures, language concepts, frameworks and design principles, compilers and tools, and formal aspects and reflective programming.
The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. ... Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010 Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” John D. Cook, The Mathematical Association of America, September 2011 This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science. Alex Small, IEEE, CiSE Vol. 14 (2), March /April 2012
Techniques for Maintainable, Modular, and Testable Python Code
Author: Chris Armstrong
"In this Functional Programming with Python training course, expert author Chris Armstrong will teach you functional programming techniques for making maintainable, modular, and testable code. This course is designed for users that already have experience with Python. You will start by learning about functional programming, including first class functions, recursion, and modifying data structures. From there, Chris will teach you about many functional programming libraries available in the Python ecosystem. This video tutorial will then teach you how to implement a text adventure game using these techniques and libraries. You will also learn how to write unit tests for functional code, use imperative libraries in a functional way, and use first-class effects. Finally, you will create a web UI for the game, and learn how to isolate an imperative web framework so that all of the application logic remains purely functional. Once you have completed this computer based training course, you will have learned how to apply these functional programming techniques to create maintainable, modular, and testable Python code."--Resource description page.
Take Control of Your Data and Use Python with Confidence Requiring no prior programming experience, Managing Your Biological Data with Python empowers biologists and other life scientists to work with biological data on their own using the Python language. The book teaches them not only how to program but also how to manage their data. It shows how to read data from files in different formats, analyze and manipulate the data, and write the results to a file or computer screen. The first part of the text introduces the Python language and teaches readers how to write their first programs. The second part presents the basic elements of the language, enabling readers to write small programs independently. The third part explains how to create bigger programs using techniques to write well-organized, efficient, and error-free code. The fourth part on data visualization shows how to plot data and draw a figure for an article or slide presentation. The fifth part covers the Biopython programming library for reading and writing several biological file formats, querying the NCBI online databases, and retrieving biological records from the web. The last part provides a cookbook of 20 specific programming "recipes," ranging from secondary structure prediction and multiple sequence alignment analyses to superimposing protein three-dimensional structures. Tailoring the programming topics to the everyday needs of biologists, the book helps them easily analyze data and ultimately make better discoveries. Every piece of code in the text is aimed at solving real biological problems.
Suitable for newcomers to computer science, A Concise Introduction to Programming in Python provides a succinct, yet complete, first course in computer science using the Python programming language. The book features: Short, modular chapters with brief and precise explanations, intended for one class period Early introduction of basic procedural constructs such as functions, selection, and repetition, allowing them to be used throughout the course Objects are introduced in the middle of the course, and class design comes toward the end Examples, exercises, and projects from a wide range of application domains, including biology, physics, images, sound, mathematics, games, and textual analysis No external libraries are required, simplifying the book’s use in common lab spaces Each chapter introduces a main idea through a concrete example and a series of exercises. Designed to teach programming in a concise, yet comprehensive way, this book provides a timely introduction for students and anyone interested in learning Python.
A Tutorial for Hobbyists, Self-starters, and All who Want to Learn the Art of Computer Programming
Author: Alan Gauld
Publisher: Addison-Wesley Professional
Are you a... Systems administrator frustrated by the deficiencies of your existing tools? Web site creator wanting to produce more dynamic content? Computer user with a desire to know what's going on inside the box? Then "Learn to Program Using Python" is the book for you. You will find this book to be an ideal starting point for learning the essentials of computer programming. Assuming no prior knowledge (other than basic computer operation), this unintimidating and clearly written guide introduces you to programming terminology, fundamental concepts, and techniques for writing actual code. Python is ideal for novice programmers: it is available for free; it has simple syntax but powerful features; it supports lots of programming styles; it runs on many platforms; it has a friendly and helpful user community. This book uses the Python language to teach you the fundamentals of computer programming. Once you master the basic techniques and concepts you learn in this book, you can apply them to any language you choose to work with. "Learn to Program Using Python" is based on a popular on-line tutorial that has been expanded and enhanced for this book. It takes you step-by-step through all the essential programming topics. You will learn about: Sequences, branching, and looping Data types and variables Input and output Modular programming Handling files and text Errors Recursion Namespaces Object-oriented programming Event-driven programming Regular expressions Debugging In addition, the book introduces elements of programming style and offers a look at the thinking and steps involved in designing a software solution. Several sample applications illustrate techniques and ideas in action.
Techniques for Integrating Python, Linux, Apache, and MySQL
Author: George Kuriakose Thiruvathukal
Publisher: Prentice Hall
This book is aimed at the practicing programmer seeking to use Python and Linux to rapidly develop web and enterprise services. Will be especially important to those involved in e-commerce programming.
The real-world guide to enterprise-class Python development.-- The right way to write Python: using modularization, toolkits, frameworks, abstract data types, and object-oriented techniques.-- Includes more than 20 proven object-oriented patterns for large-scale Python development.-- Detailed coverage of persistence, concurrent programming, metaprogramming, functional programming, and more.Python isn't just a tool for creating short Web scripts and simple prototypes: its advantages are equally compelling in large-scale development. In this book, Thomas Christopher shows developers the best ways to write large programs with Python, introducing powerful design patterns that deliver unprecedented levels of robustness, scalability, and reuse. Python Programming Patterns teaches both the Python programming language and how to "program in the large" in Python, using object-oriented techniques. Thomas Christopher demonstrates how to write Python code that leverages "programming-in-the-large" software structuring techniques, including modularization, toolkits, frameworks, abstract data types, and especially object-orientation. He presents more than 20 powerful object-oriented design patterns for Python, including creational, structural, and behavior patterns. The book includes detailed coverage of key topics such as persistence, concurrent programming, and metaprogramming (Python's term for reflection or introspection). Christopher also presents useful fun
Explains Algorithms with Beautiful Pictures Learn it Easy Better and Well
Author: Yang Hu
This book is rich in examples, with beautiful pictures and texts, and explains the data structure and algorithms in a way that is easy to understand. It is designed to help programmers better use the energy of algorithms in daily projects.1. Classic reference book in the field of algorithms: reflects the core knowledge system of algorithms2. Comprehensive content: Comprehensive discussion of sorting, linked list, search, hash, graph and tree algorithms and data structures, covering the algorithms commonly used by every programmer3. The new python implementation code, using a modular programming style, gives the actual code of the algorithm.The complexity of life, because they do not understand to simplify the complex, simple is the beginning of wisdom. From the essence of practice, this book to briefly explain the concept and vividly cultivate programming interest, you will learn it easy, fast and well
An innovative reference reveals the many capabilites of the Python Standard Library, which is a compilation of commonly used procedures that can be pasted into a Python script, by providing over 300 real-world example scripts. Original. (Intermediate/Advanced)
Computer BasicsEvolution of computers, Generations of computers, Classification of computers, Applications of computers, Computer components of a computer system, Hardware, Software booting.Software, Programming and InternetProblem solving techniques, Program control structures, Programming paradigms, Programming languages, Generations of programming languages, Language translators, Features of programming language, Internet, Evolution, Basic Internet terms, Getting connected to Internet-Applications.C FundamentalsIntroduction to C, Constants, Variables, Data types, Operators and expressions, Managing input and output operations, Decision making and branching, Looping.Arrays and FunctionsArrays, Character arrays and strings, User defined functions, Storage classes.Structures and FilesStructures, Definition, Initialization, Array of structures, Structures within structures, Structures and functions, Unions, File management in C.
"Raspberry Pi Programming Guide" is a text that gives the reader a bit of insight into this form of technology. It is European based and is just making a debut in North America so many are curious about it and what exactly this technology can do. The aim that the author has with this text is to highlight the main functions of Raspberry Pi and how it can be beneficial to the consumer in the long run. The text is extremely informative and to the point and it is simple to read. The great thing about the book is that anyone, even someone who does not know much about this form of technology can understand the process. It is a great text to have in any household that has a keen interest in technology.
“Each item in Slatkin’s Effective Python teaches a self-contained lesson with its own source code. This makes the book random-access: Items are easy to browse and study in whatever order the reader needs. I will be recommending Effective Python to students as an admirably compact source of mainstream advice on a very broad range of topics for the intermediate Python programmer.” —Brandon Rhodes, software engineer at Dropbox and chair of PyCon 2016-2017 It’s easy to start coding with Python, which is why the language is so popular. However, Python’s unique strengths, charms, and expressiveness can be hard to grasp, and there are hidden pitfalls that can easily trip you up. Effective Python will help you master a truly “Pythonic” approach to programming, harnessing Python’s full power to write exceptionally robust and well-performing code. Using the concise, scenario-driven style pioneered in Scott Meyers’ best-selling Effective C++, Brett Slatkin brings together 59 Python best practices, tips, and shortcuts, and explains them with realistic code examples. Drawing on years of experience building Python infrastructure at Google, Slatkin uncovers little-known quirks and idioms that powerfully impact code behavior and performance. You’ll learn the best way to accomplish key tasks, so you can write code that’s easier to understand, maintain, and improve. Key features include Actionable guidelines for all major areas of Python 3.x and 2.x development, with detailed explanations and examples Best practices for writing functions that clarify intention, promote reuse, and avoid bugs Coverage of how to accurately express behaviors with classes and objects Guidance on how to avoid pitfalls with metaclasses and dynamic attributes More efficient approaches to concurrency and parallelism Better techniques and idioms for using Python’s built-in modules Tools and best practices for collaborative development Solutions for debugging, testing, and optimization in order to improve quality and performance