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Modern Python Cookbook

Modern Python Cookbook

By : Steven F. Lott
4.8 (15)
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Modern Python Cookbook

Modern Python Cookbook

4.8 (15)
By: Steven F. Lott

Overview of this book

Python is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great language that can power your applications and provide great speed, safety, and scalability. It can be used for simple scripting or sophisticated web applications. By exposing Python as a series of simple recipes, this book gives you insight into specific language features in a particular context. Having a tangible context helps make the language or a given standard library feature easier to understand. This book comes with 133 recipes on the latest version of Python 3.8. The recipes will benefit everyone, from beginners just starting out with Python to experts. You'll not only learn Python programming concepts but also how to build complex applications. The recipes will touch upon all necessary Python concepts related to data structures, object oriented programming, functional programming, and statistical programming. You will get acquainted with the nuances of Python syntax and how to effectively take advantage of it. By the end of this Python book, you will be equipped with knowledge of testing, web services, configuration, and application integration tips and tricks. You will be armed with the knowledge of how to create applications with flexible logging, powerful configuration, command-line options, automated unit tests, and good documentation.
Table of Contents (18 chapters)
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16
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17
Index

Using tuples of items

What's the best way to represent simple (x,y) and (r,g,b) groups of values? How can we keep things that are pairs, such as latitude and longitude, together?

Getting ready

In the String parsing with regular expressions recipe, we skipped over an interesting data structure.

We had data that looked like this:

>>> ingredient = "Kumquat: 2 cups"

We parsed this into meaningful data using a regular expression, like this:

>>> import re
>>> ingredient_pattern = re.compile(r'(?P<ingredient>\w+):\s+(?P<amount>\d+)\s+(?P<unit>\w+)')
>>> match = ingredient_pattern.match(ingredient)
>>> match.groups()
('Kumquat', '2', 'cups')

The result is a tuple object with three pieces of data. There are lots of places where this kind of grouped data can come in handy.

How to do it...

We'll look at two aspects to this: putting things...

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