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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

Refactoring a .csv DictReader as a dataclass reader

When we read data from a CSV format file, the csv module offers two general choices for the kind of reader to create:

  • When we use csv.reader(), each row becomes a list of column values.
  • When we use csv.DictReader, each row becomes a dictionary. By default, the contents of the first row become the keys for the row dictionary. An alternative is to provide a list of values that will be used as the keys.

In both cases, referring to data within the row is awkward because it involves rather complex-looking syntax. When we use the csv.reader() function, we must use syntax like row[2] to refer to a cell; the semantics of index 2 are completely obscure.

When we use csv.DictReader, we can use row['date'], which is less obscure, but this is still a lot of extra syntax. While this has a number of advantages, it requires a CSV with a single-row header of unique column names, which is something...

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