one_similiarity.py

import math
import string
import sys


def read_file(filename):
	
	try:
		with open(filename, 'r') as f:
			data = f.read()
		return data
	
	except IOError:
		print("Error opening or reading input file: ", filename)
		sys.exit()


translation_table = str.maketrans(string.punctuation+string.ascii_uppercase," "*len(string.punctuation)+string.ascii_lowercase)
	

def get_words_from_line_list(text):
	
	text = text.translate(translation_table)
	word_list = text.split()
	
	return word_list



def count_frequency(word_list):
	
	D = {}
	
	for new_word in word_list:
		
		if new_word in D:
			D[new_word] = D[new_word] + 1
			
		else:
			D[new_word] = 1
			
	return D


def word_frequencies_for_file(filename):
	
	line_list = read_file(filename)
	word_list = get_words_from_line_list(line_list)
	freq_mapping = count_frequency(word_list)

	print("File", filename, ":", )
	print(len(line_list), "lines, ", )
	print(len(word_list), "words, ", )
	print(len(freq_mapping), "distinct words")

	return freq_mapping



def dotProduct(D1, D2):
	Sum = 0.0
	
	for key in D1:
		
		if key in D2:
			Sum += (D1[key] * D2[key])
			
	return Sum


def vector_angle(D1, D2):
	numerator = dotProduct(D1, D2)
	denominator = math.sqrt(dotProduct(D1, D1)*dotProduct(D2, D2))
	
	return math.acos(numerator / denominator)


def documentSimilarity(filename_1, filename_2):
	

	sorted_word_list_1 = word_frequencies_for_file(filename_1)
	sorted_word_list_2 = word_frequencies_for_file(filename_2)
	distance = vector_angle(sorted_word_list_1, sorted_word_list_2)
	
	print("The distance between the documents is: % 0.6f (radians)"% distance)
	

documentSimilarity('sample1.txt', 'sample2.txt')


#OUTPUT

# File sample1.txt :
# 598 lines,
# 113 words,
# 66 distinct words
# File sample2.txt :
# 779 lines,
# 154 words,
# 89 distinct words
# The distance between the documents is:  0.618456 (radians)