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Mastering Python 2E

Mastering Python 2E - Second Edition

By : Rick Hattem
4.6 (65)
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Mastering Python 2E

Mastering Python 2E

4.6 (65)
By: Rick Hattem

Overview of this book

Even if you find writing Python code easy, writing code that is efficient, maintainable, and reusable is not so straightforward. Many of Python’s capabilities are underutilized even by more experienced programmers. Mastering Python, Second Edition, is an authoritative guide to understanding advanced Python programming so you can write the highest quality code. This new edition has been extensively revised and updated with exercises, four new chapters and updates up to Python 3.10. Revisit important basics, including Pythonic style and syntax and functional programming. Avoid common mistakes made by programmers of all experience levels. Make smart decisions about the best testing and debugging tools to use, optimize your code’s performance across multiple machines and Python versions, and deploy often-forgotten Python features to your advantage. Get fully up to speed with asyncio and stretch the language even further by accessing C functions with simple Python calls. Finally, turn your new-and-improved code into packages and share them with the wider Python community. If you are a Python programmer wanting to improve your code quality and readability, this Python book will make you confident in writing high-quality scripts and taking on bigger challenges
Table of Contents (21 chapters)
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19
Other Books You May Enjoy
20
Index

itertools

The itertools library contains iterable functions inspired by those available in functional languages. All of these are iterable and have been constructed in such a way that only a minimal amount of memory is required to process even the largest of datasets. While you can easily write most of these functions yourself, I would still recommend using the ones available in the itertools library. These are all fast, memory efficient, and—perhaps more importantly—tested. We’re going to explore a few now: accumulate, chain, compress, dropwhile/takewhile, count, and groupby.

accumulate – reduce with intermediate results

The accumulate function is very similar to the reduce function, which is why some languages actually have accumulate instead of reduce as the folding operator.

The major difference between the two is that the accumulate function returns the immediate results. This can be useful when summing the results of a company’s...

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Mastering Python 2E
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