Effective Python: 59 Specific Ways to Write Better Python
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Effective Python: 59 Specific Ways to Write Better Python by Brett Slatkin (Paperback, 2015)
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- ISBN 10: 0134034287.
Instructors, you may still place orders with your bookstore. About the Author s. Relevant Courses. Python Programming Computer Science. Sign In We're sorry! Username Password Forgot your username or password? Sign Up Already have an access code? Instructor resource file download The work is protected by local and international copyright laws and is provided solely for the use of instructors in teaching their courses and assessing student learning.
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Signed out You have successfully signed out and will be required to sign back in should you need to download more resources. Digital Access Code. Anyone looking to take their Python skills to the next level would benefit from putting the book's advice into practice. No customer reviews. Share your thoughts with other customers. Write a customer review. Most helpful customer reviews on Amazon. June 25, - Published on Amazon.
Verified Purchase. I'm really enjoying this book as an intermediate python programmer looking to learn more "pythonic" ways of doing things and taking advantage of the full standard library and more performant practices.
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This book is very practical and you can skip around in no particular order and there are concise code examples to demonstrate the ideas contained in each tip. This book is more about the philosophy of good code design and scalability than it is a workbook to accomplish specific tasks, so don't expect to read it and code along and make really interesting projects.
Instead, think of this book as a set of best practices to make your code more easily debugged, easier to read, easier for other people to use, and hopefully have better performance as well. April 7, - Published on Amazon.
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Very good book. Starts with basics, but it quickly goes into 'magic' territory, so whether you're a veteran or just wanting to see what's special about Python, you will find some new approaches.
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The examples are clear. They are not some 'dry' Class X, method Y sort of examples, they tend to use examples that better illustrate the scenario; so if you at first don't get the author's explanation, you might see what's going on because of the connotations that come with sensible examples. The formatting and layout are fairly good, especially with syntax highlighting code.
But that's just minor nit-picking. My biggest 'complaint' is about what's NOT in the book. There is only a slight mention of itertools, or any functional programming concepts, that are so neatly baked into Python. There is also very slim amount of information on testing, which I would like to read more about, as it's become very commonplace.
I would love to see a second edition of this book with extended sections on the aforementioned topics. March 4, - Published on Amazon. Although I'm only about half way through the book I've already learned a lot of really cool tricks that I've actually applied in my own programs since.
I hate learning tricks that aren't that useful in practical use cases So far, I especially enjoyed the sections about list comprehension and generators. Generators were completely new to me and I was amazed at how useful they are for large data sets! There's lots of cool tricks to learn. Successfully reported this slideshow. We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads.
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