如何在python中找到内置函数的复杂性

Question

I have the special case of the problem, but it would be nice to know whether it is possible for any function.

So I want to find the position of a substring in a string. Ok, in python there is a find method which does exactly what is needed.

string.find(s, sub[, start[, end]])

Return the lowest index in s where the substring sub is found such that sub is wholly contained in s[start:end]. Return -1 on failure. Defaults for start and end and interpretation of negative values is the same as for slices.

Amazing, but the problem is that finding a big substring in a big string can run from O(n*m) to O(n) (which is a huge deal) depending on the algorithm . Documentation gives no information about time complexity, nor information about the underlying algorithm.

I see few approaches how to resolve this:

• benchmark
• go to source code and try to understand it

Both does not sound really easy (I hope that there is an easier way). So how can I find a complexity of a built-in function?

Answer 1

You say, "go to source code and try to understand it," but it might be easier than you think. Once you get to the actual implementation code, in Objects/stringlib/fastsearch.h , you find:

/* fast search/count implementation, based on a mix between boyer-
   moore and horspool, with a few more bells and whistles on the top.
   for some more background, see: http://effbot.org/zone/stringlib.htm */

The URL referenced there has a good discussion of the algorithm and its complexity.