Guidance/documentation which parameters lead to long runtime

Firstly, thanks for the great tool! I came across this corner-case: the program below runs for longer than I expect. It took ~2.5mins to complete:

import fuzzysearch
from devtools import debug

pattern = "old pond\nfrog leaps in"
s = "frog leaps in\nold pond\nwater's sound"

debug(
    fuzzysearch.find_near_matches(
        pattern,
        s,
        max_substitutions=int(0.2 * len(pattern)),  # = 4
        max_deletions=int(0.5 * len(pattern)),  # = 11
        max_insertions=int(0.5 * len(pattern)),  # = 11
    )
)

The result is:

% time python old_pond.py
old_pond.py:7 <module>
    fuzzysearch.find_near_matches( pattern, s, ...): [
        Match(start=0, end=13, dist=9, matched='frog leaps in'),
    ] (list) len=1
python old_pond.py  137.45s user 2.34s system 99% cpu 2:20.39 total

Environment: System: MacOS 11.4 Python 3.9.5 fuzzysearch 0.7.3 (compiled)

Hi @yasinzaehringer-paradime,

When the number of allowed changes is large enough compared to the length of the pattern, it's no longer useful to first search for short sub-sequences which must appear somewhere. Therefore, fuzzysearch uses an entirely different (and also highly optimized) algorithm. However, the complexity of the computation increases exponentially with the number of allowed changes, leading to very long run times in examples such as the one you show here.

I'll think about how to explain this clearly in the documentation without making things overly complicated.