



from __future__ import annotations

def       A_   (						__a  :					int			,		__a  :					list[int]			,		__a  :					list[int]			,		__a  :					int		):

				"""simple docstring"""

				# Base Case
				if counter == 0 or capacity == 0:
								return 0

				# If weight of the nth item is more than Knapsack of capacity,
				#   then this item cannot be included in the optimal solution,
				# else return the maximum of two cases:
				#   (1) nth item included
				#   (2) not included
				if weights[counter - 1] > capacity:
								return knapsack(__a			,		__a			,		__a			,		counter - 1		)
				else:
								a__					   =		capacity - weights[counter - 1]
								a__					   =		values[counter - 1] + knapsack(
								    __a			,		__a			,		__a			,		counter - 1		)
								a__					   =		knapsack(__a			,		__a			,		__a			,		counter - 1		)
								return max(__a			,		__a		)


if __name__ == "__main__":
	import doctest

	doctest.testmod()






from collections import defaultdict

def       A_   (						__a  :					str		):

				"""simple docstring"""
				a__					   =		defaultdict(__a		)
				# Creating a dictionary containing count of each word
				for word in sentence.split():
								occurrence[word] += 1
				return occurrence


if __name__ == "__main__":
	for word, count in word_occurrence("""INPUT STRING""").items():
		print(f"""{word}: {count}""")

