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Modern Python Cookbook

You're reading from   Modern Python Cookbook 133 recipes to develop flawless and expressive programs in Python 3.8

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781800207455
Length 822 pages
Edition 2nd Edition
Languages
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Author (1):
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Steven F. Lott Steven F. Lott
Author Profile Icon Steven F. Lott
Steven F. Lott
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Toc

Table of Contents (18) Chapters Close

Preface 1. Numbers, Strings, and Tuples 2. Statements and Syntax FREE CHAPTER 3. Function Definitions 4. Built-In Data Structures Part 1: Lists and Sets 5. Built-In Data Structures Part 2: Dictionaries 6. User Inputs and Outputs 7. Basics of Classes and Objects 8. More Advanced Class Design 9. Functional Programming Features 10. Input/Output, Physical Format, and Logical Layout 11. Testing 12. Web Services 13. Application Integration: Configuration 14. Application Integration: Combination 15. Statistical Programming and Linear Regression 16. Other Books You May Enjoy
17. Index

Using dataclasses to simplify working with CSV files

One commonly used data format is known as CSV. Python's csv module has a very handy DictReader class definition. When a file contains a one-row header, the header row's values become keys that are used for all the subsequent rows. This allows a great deal of flexibility in the logical layout of the data. For example, the column ordering doesn't matter, since each column's data is identified by a name taken from the header row.

This leads to dictionary-based references to a column's data. We're forced to write, for example, row['lat'] or row['date'] to refer to data in specific columns. While this isn't horrible, it would be much nicer to use syntax like row.lat or row.date to refer to column values.

Additionally, we often have derived values that should – perhaps – be properties of a class definition instead of a separate function. This can properly encapsulate...

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