On 01/12/2014 10:04 AM, Keith Winston wrote:
I've got this line:
for k in range(len(tcombo)):
tcombo_ep.append(list(combinations(tcombo, k+1)))
generating every possible length combination of tcombo. I then test
them, and throw most of them away. I need to do this differently, it
gets way too big (crashes my computer).
I'm going to play some more, but I think I need to test the
combinations as they're generated... and then only add them to a list
(probably better: a set) if they meet a requirement (something like
sum(specific.combination(tcombo) == goal)) AND if they are not already
part of that list (the uniqueness issue is why a set might be better)
I'm partially asking in order to clarify the question in my mind, but
any help will be appreciated. I don't really understand lambda
functions yet, but I can sort of imagine they might work here
somehow... or not.
You say yourself that, on the application side, the semantics are that relevant
items (individual combinations) are a subset of the ones otherwise produced,
right? Thus they are conceptually the output of a *filter*. Whether they are
stored (in a list --> list comprehension) or directly processed (from a
generator --> generator expression), you should only ever deal with the relevant
ones.
production filter
data ---> combinations ---> [storage] usage
If the filter's criterion is 'crit':
combs = (comb for comb in combinations(tcombo, k+1)) if crit(comb))
This, in addition to the requirement of uniqueness which as you say is probably
best met using a set (after filter). This may lead to you chosing to store, even
if otherwise not truely necessary. An question is: what kind of data are
combinations, and how do you compare them? If there is a possibly cheap shortcut
by comparing only a little bit of combination data, then you may make a set of
those little bits only and avoid storing the whole of combinations.
Denis
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