Processing ......
FreeComputerBooks.com
Links to Free Computer, Mathematics, Technical Books all over the World
 
Python for Software Design: How to Think Like a Computer Scientist
🌠 Top Free Unix/Linux Books - 100% Free or Open Source!
  • Title Python for Software Design: How to Think Like a Computer Scientist
  • Author(s) Allen B. Downey
  • Publisher: Cambridge University Press; 1 edition (March 16, 2009)
  • Paperback 270 pages
  • Language: English
  • ISBN-10: 0521725968
  • ISBN-13: 978-0521725965

Book Description

Python for Software Design is a concise introduction to software design using the Python programming language. Intended for people with no programming experience, this book starts with the most basic concepts and gradually adds new material. Some of the ideas students find most challenging, like recursion and object-oriented programming, are divided into a sequence of smaller steps and introduced over the course of several chapters. The focus is on the programming process, with special emphasis on debugging.

The book includes a wide range of exercises, from short examples to substantial projects, so that students have ample opportunity to practice each new concept. Exercise solutions and code examples are available from thinkpython.com, along with Swampy, a suite of Python programs that is used in some of the exercises.

About the Authors
  • Allen B. Downey, Ph.D., is an associate professor of computer science at the Olin College of Engineering in Needham, Massachusetts. He has taught at Wellesly College, Colby College, and UC Berkeley. He has a doctorate in computer science from UC Berkeley and a Master's degree from MIT. Dr Downey is the author of a previous version of this book, titled How to Think Like a Computer Scientist: Learning with Python, which he self-published in 2001.

Reviews and Rating: Related Book Categories: Read and Download Links: Similar Books:
  • O'Reilly® Think Python, 2nd Edition (Allen B. Downey)

    This hands-on guide takes you through the Python programming language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. 2nd edition updated for Python 3.

  • Python for Data Analysis: Pandas, NumPy, and Jupyter

    The focus is specifically on Python programming, libraries, and tools as opposed to data analysis methodology. This is the Python programming you need for data analysis. You'll learn the latest versions of pandas, NumPy, and Jupyter in the process.

  • Introduction to Computer Programming with Python (Harris Wang)

    This introduction to computer programming with Python begins with some of the basics of computing and programming before diving into the fundamental elements and building blocks of computer programs in Python language.

  • Automate the Boring Stuff with Python (Albert Sweigart)

    Learn how to use Python to write programs that do in minutes what would take you hours to do by hand - no prior programming experience required. You'll create Python programs that effortlessly perform useful and impressive feats of automation.

  • Python for Everybody: Exploring Data in Python 3

    This book is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.

  • Deep Learning with Python, 2nd Edition (Francois Chollet)

    This book introduces the field of deep learning using Python and the powerful Keras library. It offers insights for both novice and experienced machine learning practitioners, and builds your understanding through intuitive explanations and practical examples.

  • Beyond the Basic Stuff with Python: Writing Clean Code

    More than a mere collection of advanced syntax and masterful tips for writing clean code, advance your Python programming skills by using the command line and other professional tools like code formatters, type checkers, linters, and version control.

  • Python Packages (Tomas Beuzen, et al.)

    An open source book that describes modern and efficient workflows for creating Python packages. Covering the entire Python packaging life cycle, this essential guide takes readers from package creation all the way to effective maintenance and updating.

  • Inside The Python Virtual Machine (Obi Ike-Nwosu)

    This book describes how Python code is compiled and run, how the language itself can be modified and will demystify the mysterious bytecodes that run on the Python virtual machine.

  • Architecture Patterns with Python (Harry Percival, et al.)

    Enabling Test-Driven Development, Domain-Driven Design, and Event-Driven Microservices, it introduces proven architectural design patterns to help Python developers manage application complexity, and get the most value out of their test suites.

  • Clean Architectures in Python: Better Software Design

    The clean architecture is the opposite of spaghetti code, where everything is interlaced and there are no single elements that can be easily detached from the rest and replaced without the whole system collapsing.

  • Clean Code in Python: Refactor Your Legacy Code Base

    The book describes the basic elements of writing clean code and how it plays an important role in Python programming. You will learn about writing efficient and readable code using the Python standard library and best practices for software design.

  • Problem Solving with Algorithms/Data Structures using Python

    This is a textbook about computer science. It is also about Python. However, there is much more. The tools and techniques that you learn here will be applied over and over as you continue your study of computer science.

  • Fundamentals of Python Programming (Richard L. Halterman)

    It focuses on introducing programming techniques and developing good habits. To that end, our approach avoids some of the more esoteric features of Python and concentrates on the programming basics that transfer directly to other imperative programming.

  • The Little Book of Algorithms in Python (William Lau)

    This workbook is designed to help those learning and teaching Computer Science at secondary school level. The aim of the book is to help students build fluency in their Python programming.

  • Data Structures and Algorithms with OPP Design Patterns in Python

    It promotes object-oriented design using Python and illustrates the use of the latest object-oriented design patterns. Virtually all the data structures are discussed in the context of a single class hierarchy.

  • Learn Python the Right Way: How to Think like a Computer Scientist

    The goal of this book is to teach you to think like a computer scientist. This way of thinking combines some of the best features of mathematics, engineering, and natural science.

Book Categories
:
Other Categories
Resources and Links