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blog > 2007 > 12 > 15 >

Avoiding Recursion

Occasionally I implement an algorithm recursively then hit the recursion limit in Python.

For example, I just wrote this:

def clique(self, node, done=None):
    if done is None:
        done = set()
    done.add(node)
    for other_node in self.edges_by_node[node]:
        if other_node not in done:
            self.clique(other_node, done)
    return done

which hits a limit if the graph is too big.

So I rewrote it like this:

def clique(self, start_node):
    done = set()
    to_do = [start_node]
    while to_do:
        node = to_do.pop()
        done.add(node)
        for other_node in self.edges_by_node[node]:
            if other_node not in done:
                to_do.append(other_node)
    return done

There's a simple relationship between the two, quite independent of the specific task at hand. Which got me thinking about abstracting the specific task out of the recursive versus non-recursive pattern.

I guess I was having an SICP moment :-)

Comments (1)

Scott Lamb on Dec. 15, 2007:

It looks like there are others who have thought about tail recursion optimization in Python. For example, http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/474088 has a decorator for it, though it appears horribly inefficient.

By the way, your backlinks from advogato are broken. I'd guess your RSS file is using jtauber.com-relative links, and advogato's syndication feature expects absolute ones. I haven't read the RSS spec in sufficient detail to know which is at fault.