Fitness Think Python Ebook


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Think Python First Edition, by Allen B. Downey. This is the first edition of Think Python, which uses Python 2. If you are using Python 3, you might want to use the . erating a device-independent representation of a textbook, which can be converted to The result is this book, now with the less grandiose title Think Python. This is the second edition of Think Python, which uses Python 3. If you are Think Python is an introduction to Python programming for beginners. It starts with.

Think Python Ebook

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June Major revision, changed title to Think Python: How to Think Like a a device-independent representation of a textbook, which can be converted to. An introduction to Python programming for beginners, using Python 3. It starts with basic concepts of programming, and is carefully designed to. Think Python is a concise introduction to software design using the Python This textbook has been used in classes atBard College,Olin College of Engineering.

By the end of the book, the reader will be well versed in programming concepts and specifically with Python as a programming language. Python is a great language for beginners to learn the basics of computer programming.

This book covers most of the primary Python syntax. It would make a good reference book to supplement existing lectures, without being too unwieldy. For a For a beginner textbook, I would need to add more explanation of basics and how to think through programming. Content is accurate, although could use more updates for the new version of Python. It was a little confusing in places where explanations switch between Python 2 and Python 3. I believe this work will remain relevant for as long as the current version of Python is in use.

General concepts will not change, but the book will need to be updated with newer versions of code snippets. The writing is clear and concise with few errors. Some lessons will need further explanation from instructor if using this book.

Programming is a difficult topic to teach to beginners. This book did a fairly good job of breaking it down into manageable chunks without overwhelming the reader.

Having said that, the book was not culturally insensitive or offensive in any way. Python is becoming increasingly important in its use for scientific and engineering applications.

This text is an easy-to-read short volume on the use of Python for coding, that teaches the reader generic skills of good programming. The topics The topics covered are comprehensive and sequentially coherent, especially for a novice in programming.

Perhaps the biggest strength of this book is the fluidity of the topics and the ease of communication in the chapters.

There are very useful examples and exercises present in every chapter that progressively walks the reader through the aspects of coding in Python. There are links with solutions in the book for the reader's benefit as well. This reviewer would have liked an introductory section that describes a step by step installation and use of an editor for Python; however, given the wide choices and the changing environment of editors, this is a minor concern that pales in comparison to the myriad benefits provided by this book.

As far as this reviewer is concerned, the contents of this book are accurate and free of glaring errors. Since the author has taken the approach of educating the reader on how to think and program like a computer scientist rather than provide a crash course or a recipe-type approach to programming in Python, this book may not become obsolete in the near future.


However, as version of Python change their syntax every now and then, the onus might be on the reader to keep abreast of such quirks while reading this book. As mentioned before, the biggest strength of this book is the fluidity of the topics and the ease of communication in the chapters. The topics of this book are so arranged in sequential order that it might benefit the novice reader to go thru the book from first to last. However, this may not be true for the slightly advanced reader that may benefit from the modularity of the topic.

This reviewer was able to go back and forth between these topics arranged in chapters. The arrangement of the sections within the chapters are also well thought and presented with increasing complexity.

The text concisely but thoroughly covers the basics of programming in the Python language, from expressions and functions to file processing and object-oriented programming. Each chapter features a glossary of relevant terms and topics. Chapters are named in such a way that it is easy to glean topics. I was especially pleased to see a chapter on graphic user interfaces and the Tkinter library.

Each chapter also includes several coding or thought exercises for the student, and solutions for all of them are provided as URLs and links.

Throughout, special attention is given to principles and techniques in program debugging, and the general prevention of syntactic and semantic errors.

This is a short book, so it does not go into every final detail of the language. Its purpose is rather to teach fundamental programming concepts using Python, and does so very effectively.

I have not spotted any factual inaccuracies or biases in the text. However, see below for some discussion on the particular versions of Python covered. The book's subject matter is mostly timeless, in that as long as procedural and object-oriented programming are taught, the content is relevant.

A minor concern is that the book concentrates on Python 2, a slightly older version of the language. At the time of this review, Python is at version 3. The author does point out the few places where there is a difference in coding between Python 2 and Python 3, for tasks such as printing and integer division.

On the book's web page is a link to a version of the text that is "converted" to Python 3, written by a third party.

Think Python 2nd Edition by Allen B. Downey (free ebook download)

Those already familiar with Python are probably aware of the protracted transition between Python 2 and 3 in industry and academia.

My own preference is that teaching materials cover Python 3 exclusively, to prevent confusion and potentially outmoded coding styles. The prose is direct and to the point, with surprising clarity. New and potentially difficult concepts are expressed clearly, and when technical terminology is used, it is explicitly defined.

The text is very consistent in its overall style for each chapter, and the book overall feels like a coherent unit. The book is divided into 19 chapters and three appendices. Chapters are about pages long, and appendices are about 5 pages long each. The brevity of the text and the many subheadings for each chapter enables a good degree of modularity.

Once in a while, certain concepts are "sprung early" in one chapter, but explained more thoroughly in subsequent chapters. I did not find this practice disruptive. While chapters generally built on one another, I felt that many chapters could stand alone or be reordered as needed.

The text had good organization of topics. Chapters are short, so relatively specific topics such as "Strings", "Files", and "Inheritance" are at the focus of each. Since the chapters are only pages long, small portions of subject matter can be more easily read and understood. There was also a good flow of topics from simple to complex, where ideas introduced in one chapter are revisited or built upon in subsequent chapters.

Think Python: How to Think Like a Computer Scientist

I mainly focused on the PDF version of the text, which was free of errors. My only complaint is that exercises, which are interspersed in the text, are not always set off by white space from any preceding material. As such, narrative sometimes runs into exercises. This is the first edition of Think Python , which uses Python 2. If you are using Python 3, you might want to use the second edition, which is here. Example programs and solutions to some problems are here links to specific examples are in the book.

The code is also available from this GitHub repository. Think Python is an introduction to Python programming for beginners. It starts with basic concepts of programming, and is carefully designed to define all terms when they are first used and to develop each new concept in a logical progression.

Larger pieces, like recursion and object-oriented programming are divided into a sequence of smaller steps and introduced over the course of several chapters. Some examples and exercises are based on Swampy , a Python package written by the author to demonstrate aspects of software design, and to give readers a chance to experiment with simple graphics and animation.

Think Python is a Free Book. The previous edition of this book was published by Cambridge University press with the title Python for Software Design. This edition is available from Amazon. Learning with Python. This edition is available from from Lulu.Close Report a review At Kobo, we try to ensure that published reviews do not contain rude or profane language, spoilers, or any of our reviewer's personal information.

The topics in the chapter are reinforced through examples and again through the exercises provided at the end of the chapter. Flex 4 Cookbook. The framework is consistent throughout the text. Concepts within the chapter are reinforced through exercises provided at the end of each chapter which encourage the reader to practice with Python. However, I found it to be an unexpectedly readable and usable text, and I plan to try it in a future iteration of my Python course.

The book is well written.

FREDDY from Burlington
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