The classic book The Little Lisper (The Little Schemer) is founded on two big ideas
- You can solve most problems in a recursive way (instead of using loops) (assuming you have Tail Call Optimisation)
- Lisp is great because it is easy to implement in itself.
Now one might think this holds true for all Lispy languages (including Clojure). The trouble is, the book is an artefact of its time (1989), probably before Functional Programming with Higher Order Functions (HOFs) was what we have today.(Or was at least considered palatable for undergraduates).
The benefit of recursion (at least in part) is the ease of traversal of nested data structures like ('a 'b ('c ('d 'e)))
.
For example:
(def leftmost
(fn [l]
(println "(leftmost " l)
(println (non-atom? l))
(cond
(null? l) '()
(non-atom? (first l)) (leftmost (first l))
true (first l))))
Now with Functional Zippers - we have a non-recursive approach to traversing nested data structures, and can traverse them as we would any lazy data structure. For example:
(defn map-zipper [m]
(zip/zipper
(fn [x] (or (map? x) (map? (nth x 1))))
(fn [x] (seq (if (map? x) x (nth x 1))))
(fn [x children]
(if (map? x)
(into {} children)
(assoc x 1 (into {} children))))
m))
(def m {:a 3 :b {:x true :y false} :c 4})
(-> (map-zipper m) zip/down zip/right zip/node)
;;=> [:b {:y false, :x true}]
Now it seems you can solve any nested list traversal problem with either:
- a
zipper
as above, or - a
zipper
that walks the structure and returns a set of keys that will let you modify the structure usingassoc
.
Assumptions:
- I'm assuming of course data structures that fixed-size, and fully known prior to traversal
- I'm excluding the streaming data source scenario.
My question is: Is recursion a smell (in idiomatic Clojure) because of of zippers and HOFs?