Cover by Mark Lutz

Safari, the world’s most comprehensive technology and business learning platform.

Find the exact information you need to solve a problem on the fly, or go deeper to master the technologies and skills you need to succeed

Start Free Trial

No credit card required

O'Reilly logo

Chapter 20. Iterations and Comprehensions, Part 2

This chapter continues the advanced function topics theme, with a reprisal of the comprehension and iteration concepts introduced in Chapter 14. Because list comprehensions are as much related to the prior chapter’s functional tools (e.g., map and filter) as they are to for loops, we’ll revisit them in this context here. We’ll also take a second look at iterators in order to study generator functions and their generator expression relatives—user-defined ways to produce results on demand.

Iteration in Python also encompasses user-defined classes, but we’ll defer that final part of this story until Part VI, when we study operator overloading. As this is the last pass we’ll make over built-in iteration tools, though, we will summarize the various tools we’ve met thus far, and time the relative performance of some of them. Finally, because this is the last chapter in the part of the book, we’ll close with the usual sets of “gotchas” and exercises to help you start coding the ideas you’ve read about.

List Comprehensions Revisited: Functional Tools

In the prior chapter, we studied functional programming tools like map and filter, which map operations over sequences and collect results. Because this is such a common task in Python coding, Python eventually sprouted a new expression—the list comprehension—that is even more flexible than the tools we just studied. In short, list comprehensions apply an arbitrary expression to items in an iterable, ...

Find the exact information you need to solve a problem on the fly, or go deeper to master the technologies and skills you need to succeed

Start Free Trial

No credit card required