process.py

from transaction import Transaction
from collections import Counter
import time

start = time.clock()

retail_file = "retail.dat"
history_triplet_log = []
history_pair_log = []
history_single_log = []

def get_highest_count(array_log):
	# use Counter to count all of the occurences of items in the log and get the highest count.
	highest_counter = Counter(array_log).most_common(1)
	# print counter.most_common(1)
	for combination, occurence in highest_counter:
		return combination, occurence


def get_probability_count(array_log, values):
	# counter = Counter(array_log)
	counter = array_log.count(values)
	# print counter.most_common(1)
	return counter


def get_pair_log(items):
	# we only care about the co-occurences
	for item in range(len(items) - 1):
		history_pair_log.append((items[item], items[item + 1]))
		# print(items[item], items[item + 1])
	return None


def get_single_log(items):
	for item in range(len(items)):
		history_single_log.append((items[item]))
		# print(items[item])
	return None

def get_triplet_log(items):
	# we only care about the triple-occurences
	for item in range(len(items) - 2):
		history_triplet_log.append((items[item], items[item + 1], items[item + 2]))
	return None

def main():
	with open(retail_file, "r") as retail_data:
		count = 0
		for line in retail_data:
			trans = Transaction(count, map(int, line.split()))
			parsed_items = trans.get_items()
			get_pair_log(parsed_items)
			get_triplet_log(parsed_items)
			get_single_log(parsed_items)
			count += 1
	print("**** Using no threading or multi-processing ****\n")
	print("File: %s contains %d lines.\n" % (retail_file, count))
	highest_pairs, pair_count = get_highest_count(history_pair_log)
	highest_triplets, triplet_count = get_highest_count(history_triplet_log)

	# get item a of the highest pair occurence.
	prob_val_from_pair = highest_pairs[0]
	# process the count of item a for pair probability.  use the single log to count item a.
	prob_count_from_pair = get_probability_count(history_single_log, prob_val_from_pair)
	# calculate the probability of the highest pair occurence.
	prob_of_pair = float(pair_count) / float(prob_count_from_pair)

	# get b,c items from the highest triplet occurence.
	prob_val_from_triplets = (highest_triplets[1], highest_triplets[2])
	# process the count of b,c items for triplet probability.  since we already have a log of pairs we can re-use it.
	prob_count_from_triplets = get_probability_count(history_pair_log, prob_val_from_triplets)
	# calculate the probability of the highest triplet occurence.
	prob_of_triplets = float(triplet_count) / float(prob_count_from_triplets)

	print("The highest co-occurence item pairs in the file are: %s with count %d" % (str(highest_pairs), pair_count))
	print("The probability of this occurence of pairs is:   ~%.2f" % (prob_of_pair))

	print("\nThe highest co-occurence item triplets in the file are: %s with count %d" % (str(highest_triplets), triplet_count))
	print("The probability of this occurence of triplets is:   ~%.2f" % (prob_of_triplets))
	
	retail_data.close()
	end = time.clock()
	print("\nFinished in %s seconds." % (end - start))
	print("=======================================================================")

if __name__ == "__main__":
	main()