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The Clojure Workshop

You're reading from   The Clojure Workshop Use functional programming to build data-centric applications with Clojure and ClojureScript

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Product type Paperback
Published in Jan 2020
Publisher Packt
ISBN-13 9781838825485
Length 800 pages
Edition 1st Edition
Languages
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Authors (5):
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Konrad Szydlo Konrad Szydlo
Author Profile Icon Konrad Szydlo
Konrad Szydlo
Yehonathan Sharvit Yehonathan Sharvit
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Yehonathan Sharvit
Scott McCaughie Scott McCaughie
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Scott McCaughie
Thomas Haratyk Thomas Haratyk
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Thomas Haratyk
Joseph Fahey Joseph Fahey
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Joseph Fahey
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Toc

Table of Contents (17) Chapters Close

Preface 1. Hello REPL! 2. Data Types and Immutability FREE CHAPTER 3. Functions in Depth 4. Mapping and Filtering 5. Many to One: Reducing 6. Recursion and Looping 7. Recursion II: Lazy Sequences 8. Namespaces, Libraries and Leiningen 9. Host Platform Interoperability with Java and JavaScript 10. Testing 11. Macros 12. Concurrency 13. Database Interaction and the Application Layer 14. HTTP with Ring 15. The Frontend: A ClojureScript UI Appendix

Lazy Trees

So far, we've seen that the "laziness" of lazy sequences is that they can point to future computations that will only be performed if they become necessary. There is another important advantage that is equally important, and that is what we are going to explore now. Remember from Chapter 6, Recursion and Looping, how recursive functions in Clojure need to use recur to avoid blowing up the stack? And remember how recur only works with a specific kind of recursion, tail recursion, where the next call to the recursive function can totally replace the previous call? The problem, you'll recall, is that only a limited number of stack frames are available. The function call on the root node of the tree needs to wait until all the calls have completed on all the child and grandchild and great-grandchild nodes, and so on. Stack frames are a limited resource but the data we need to operate on is often vast. This mismatch is a problem.

This is where lazy evaluation...

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