Functionally Competent

Here’s a piece of somewhat–ugly, single–purpose Python code, what it does is not particularly interesting:

def span(data):
   r = []
   for row in data:
       if r and row[1] == r[-1][2]:
           r[-1][1] = row[0]
           r.append([row[0], row[0], row[1]])
   return r

After a couple of days of wondering how this might be done in Clojure, I stumbled upon the idea of a partition, and went looking in the docs. Here’s the Clojure version:

(defn span [data]
  (map (fn [spn] [(first (first spn))
                  (first (last spn))
                  (second (first spn))])
    (partition-by (fn [row] (second row)) data)))

To my eye, the Clojure version is a lot nicer (although it could be novelty, or the square brackets containing “magic numbers” in the Python version).

The beauty of the Clojure version comes from the partition-by function, replicated below:

(defn partition-by
  [f coll]
   (when-let [s (seq coll)]
     (let [fst (first s)
           fv (f fst)
           run (cons fst (take-while #(= fv (f %)) (next s)))]
       (cons run (partition-by f (seq (drop (count run) s))))))))

After a few minutes of working out what it does, it “popped”, and at the same time I had a break–through in my understanding of functional programming.

For completeness, here’s a version of partition-by in Python:

import itertools

def partition_by(f, coll):
    if not coll:
        return []
    head, tail = coll[0], coll[1:]
    run = [head] + list(itertools.takewhile(lambda t: f(t) == f(head), tail))
    return [run] + func_partition_by(f, coll[len(run):])

Which can be used to refactor the original span function to:

def span(data):
    return map(
        lambda r: [r[0][0], r[-1][0], r[0][1]],
        partition_by(lambda row: row[1], data))

The nice thing about the original Clojure version, and the final Python version is that the format of the “rows”, and the logic for partitioning data are separate: something I wouldn’t have done if it weren’t for my recent interest in Clojure.