a compact apriori pythonian version

AprioriCompact.py

from collections import defaultdict
from itertools import imap, combinations

def get_frequent_items_sets(transactions,min_support,steps=0):
	frequent_itemsets = []
	items = defaultdict(lambda: 0)
	[inc(items,item,1) for transaction in transactions for item in transaction]
	items = set(item for item, support in items.iteritems()
		if support >= min_support)
	[frequent_itemsets.append(item) for item in items]
	transactions = [set(filter(lambda v: v in items, y)) for y in transactions]
	count = 2
	while bool(len(items)) and count != steps:
		candidates = combinations([i for i in items],count)
		items = defaultdict(lambda: 0)
		[inc(items,candidate,1) for candidate in candidates for transaction in transactions if transaction.issuperset(candidate)]
		[frequent_itemsets.append(item) for item,support in items.iteritems() if support >= min_support]
		items = set(element for tupl in items.iterkeys() for element in tupl)
		count+=1
	return frequent_itemsets

def inc(dic,key,val):
	dic[key]+=val

#[transaction.remove(element) for item,support in items.iteritems() for element in item if support < minimum_support and element in transaction]

Apriori Python Compact Implementation

AUTHOR: Andrea Galloni (Twitter or Web)

E-Mail: andreagalloni92{at}gmail[dot]com

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A compact implementation of the notorious Apriori algorithm, this implementation would like to show the compactness of Python2.7 codestyle when needed.

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The whole code in this repository comes without any kind of warranty or license, use it at your own risk.

If you have some improvements or suggestions, please create a pull request or write to me at: andreagalloni92{at}gmail[dot]com