Hacker News Reader

Comment by ggchappell | Hacker News Reader

He does do a "map", although without using the function of that name:

  answers = [f(x) for x in iterable]

Also, the "zip" operation gives loops that seem to me to be unable to be decomposed into map, filter, reduce. E.g., how would you print a file with line numbers using only map, filter, reduce?

Regardless, I agree with your basic point: that thinking of loops in terms of high-level loop primitives, is a Good Thing.

View on HN

    def zip(*seqs):
      return map(lambda *items: items, *seqs)

    assert [(1, 'a'), (2, 'b'), (3, 'c')] == zip([1,2,3],['a','b','c'])


    def count(start=0):
      while True:
        yield start
        start += 1

    from itertools import izip, islice # lazy versions
    with open('/etc/passwd', 'r') as f:
      zipped = izip(count(), f.readlines())
      for numbered in zipped: print numbered

izip and islice are trivial to implement: https://github.com/dustingetz/sandbox/blob/master/etc/lazy.p...

Well, strictly speaking, you have answered my objection. But I guess I was thinking in Haskell. If Python's map takes multiple iterables, then, yes, zip is a special case. But writing zip by mapping a function without side effects, using a "map" that works only on a single iterable (as in Haskell) strikes me as a rather different thing.

So I suppose that the truth of "this loop can be written using map" depends on exactly what one means by "map".

interesting. how about

    def head(seq): return seq[0]
    def rest(seq): return seq[1:]
    def transpose(mtx):
        a = map(head, mtx)
        b = map(rest, mtx)
        return [a] + ([transpose(b)] if b[0] else [])

    def zip(xs, ys):
        return transpose((xs, ys))

    def zip2(*seqs):
        return transpose(seqs)

this works but is sort of icky in python, any ideas? this is also where functional python starts to fall apart - no tail call recursion, and default data structures aren't persistent. based on a haskell solution which is nicer. http://stackoverflow.com/questions/2578930/understanding-thi...

Line numbering a file with reduce is straightforward:

    def line_number_catamorphism(fp):
        def accumulate(a, line):
            line_number, lines = a
            return line_number + 1, lines + [(line_number + 1, line)]
        return reduce(accumulate, fp, (0, []))[1]

It may be worth nothing that zip can be straightforwardly expressed in terms of map as well, i.e.:

    zip = lambda *a: map(None, *a)

I'm sorry, is this a joke? "straightforward"? Why would you use that code when you could implement the same thing more simply like this?

    def line_number_mogrifier(f):
        num = 0
        for line in f:
            yield (num, line)
            num += 1

The functional proponents say that eventually everything will be functional, I guess I'll wait and see how that goes over. People think procedurally. Functional constructs may have some technical advantages, but if adopting them shrinks the pool of effective developers, it won't catch on.

Reply on news.ycombinator.com