python - performance generating combinations of objects with combinations of attr -

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i looking advice on how can better approach couple of functions.

i have set of 5 objects 6 attributes on each, number of objects can change amount of attributes.

i need iterate on each possible combination of attribute, on each possible combination of object. no object in set can feature same value within set. , each objects attributes there n possible values ( n set size ). values applicable attributes cannot applicable attribute. ie. attributea's value, never value attributeb.

at moment have objects represented list of lists. eg. [[obj1attr_a, obj1attrb], [obj2attr_a, obj2attr_b]] etc

the problem itertools.combinations returns many redundent combinations not valid ( ie. values appear more once ). if use generator return valid combinations slow never yields correct combination. there way filter results in itertools.combinations efficiently?

#keywords list of possible values each attribute solver.get_unique_combinations(        itertools.combinations(itertools.product(*keywords), 5))  def get_unique_combinations(combinations):     combination in combinations:         flat = [item sublist in combination item in sublist]         if len(set(flat)) < len(flat):             continue         yield combination

ive tried using ifilter same problem (below), way can see going able use other itertools.combinations return sets of objects unique values in each , somehow skip need filter altogether.

 return itertools.ifilter(lambda x: solver.get_unique_combinations(x),     itertools.combinations(itertools.product(*keywords), 5))  @staticmethod def get_unique_combinations(x):     if len(             set(str(x).replace('[', '')                         .replace('[', '')                         .replace(',', '')                         .replace('(', '')                         .replace(')', '')                         .split())) == len(x) * len(x[0]):         return true     return false

**edit: requested - short compilable version:

import itertools   def has_unique_values(iterable, attr_count):     seen = set()     seen_add = seen.add     counter = 0     element in itertools.ifilterfalse(seen.__contains__,              itertools.chain(iterable)):         seen_add(element)         counter += 1     return counter == attr_count  keywords = [     ["australia", "sweden", "germany", "france", "italy"],     ["lion", "tiger", "otter", "bird", "fish"],     ["table", "chair", "cloth", "couch", "tv"],     ["apple", "orange", "pear", "grape", "tomato"],     ["onion", "carrot", "mushroom", "kale", "spinach"]]  keyword_combinations = itertools.product(*keywords) population = len(keywords[0]) attr_count = len(keywords)  unique_count = population * attr_count  c in itertools.ifilter(lambda x: has_unique_values(x, unique_count),           itertools.combinations(keyword_combinations, population)):     print c #doesnt here


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