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Functional Python Programming

You're reading from   Functional Python Programming Create succinct and expressive implementations with functional programming in Python

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Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781784396992
Length 360 pages
Edition 1st 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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Table of Contents (18) Chapters Close

Preface 1. Introducing Functional Programming FREE CHAPTER 2. Introducing Some Functional Features 3. Functions, Iterators, and Generators 4. Working with Collections 5. Higher-order Functions 6. Recursions and Reductions 7. Additional Tuple Techniques 8. The Itertools Module 9. More Itertools Techniques 10. The Functools Module 11. Decorator Design Techniques 12. The Multiprocessing and Threading Modules 13. Conditional Expressions and the Operator Module 14. The PyMonad Library 15. A Functional Approach to Web Services 16. Optimizations and Improvements Index

Reducing a product


In relational database theory, a join between tables can be thought of as a filtered product. A SQL SELECT statement that joins tables without a WHERE clause will produce a Cartesian product of rows in the tables. This can be thought of as the worst-case algorithm: a product without any filtering to pick the proper results.

We can use the join() function to join two tables, as shown in the following commands:

def join(t1, t2, where):):
    return filter(where, product(t1, t2)))))

All combinations of the two iterables, t1 and t2, are computed. The filter() function will apply the given where function to pass or reject items that didn't fit the given condition to match appropriate rows from each iterable. This will work when the where function returns a simple Boolean.

In some cases, we don't have a simple Boolean matching function. Instead, we're forced to search for a minimum or maximum of some distance between items.

Assume that we have a table of Color objects as follows...

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