Merge branch 'main' into tf_idf

.gitignore

@@ -1,2 +1,3 @@
-/data/DEV
+/data/
 *.shelve
+/__pycache__/

indexer.py

@@ -14,6 +14,7 @@ import json
 import os
 import shelve
 from bs4 import BeautifulSoup
+from time import perf_counter
 
 
 
@@ -26,6 +27,9 @@ import numpy as np
 
 import re
 
+#Logging postings
+from posting import Posting
+
 
 class Indexer():
 	def __init__(self,restart,trimming):
@@ -34,7 +38,6 @@ class Indexer():
 		self.restart = restart
 		self.trimming = trimming
 		self.stemmer = PorterStemmer()
-		self.vectorizer = TfidfVectorizer(lowercase=True,ngram_range = (1,3))
 
 		#Shelves for index
 		#https://www3.nd.edu/~busiforc/handouts/cryptography/letterfrequencies.html
@@ -44,7 +47,7 @@ class Indexer():
 		#Save #2 = EFGHIJK + (2-3)~ 27.1% of words
 		#Save #3 = LMNOPQ + (4-7) ~ 25.4% of words
 		#Save #4 = RSTUVWXYZ + (8-9)~ 29.2% of words
-		#Save #5 = Numbers ???
+		#Save #5 = Special characters
 		if os.path.exists("save_1.shelve") and restart:
 			os.remove("save_1.shelve")
 		if os.path.exists("save_2.shelve") and restart:
@@ -53,34 +56,40 @@ class Indexer():
 			os.remove("save_3.shelve")
 		if os.path.exists("save_4.shelve") and restart:
 			os.remove("save_4.shelve")
+		if os.path.exists("save_5.shelve") and restart:
+			os.remove("save_5.shelve")
 
 
 		self.save_1 = shelve.open("save_1.shelve")
 		self.save_2 = shelve.open("save_2.shelve")
 		self.save_3 = shelve.open("save_3.shelve")
 		self.save_4 = shelve.open("save_4.shelve")
+		self.save_5 = shelve.open("save_5.shelve")
 
 
 	def save_index(self,word,posting):
-		wordhash = hash(word)	##Honestly do not know why hashing is even needed, might cause more problems 
-		cur_save = get_save(word)
+		cur_save = self.get_save_file(word)
 		shelve_list = list()
 
-		if wordhash not in cur_save:
-			shelve_list.append(posting)
-			cur_save[wordhash] = shelve_list
-			cur_save.sync()
-		else:
-			shelve_list = cur_save[wordhash]
+		try:
+			shelve_list = cur_save[word]
 			shelve_list.append(posting)
+			tic = perf_counter()
 			shelve_list.sort(key=lambda x: x.tf_idf, reverse = True)
+			toc = perf_counter()
+			if toc - tic > 1 :
+				print("Took " + str(toc - tic) + "seconds to sort shelve list !")
+			cur_save.sync()
+		except:
+			shelve_list.append(posting)
+			cur_save[word] = shelve_list
 			cur_save.sync()
 
 	def get_save_file(self,word):
 		#return the correct save depending on the starting letter of word
 		word_lower = word.lower()
 
-		if re.match(r"^[a-d1-1].*",word_lower):
+		if re.match(r"^[a-d0-1].*",word_lower):
 			return self.save_1
 		elif re.match(r"^[e-k2-3].*",word_lower):
 			return self.save_2
@@ -89,8 +98,10 @@ class Indexer():
 		elif re.match(r"^[r-z8-9].*",word_lower):
 			return self.save_4
 		else:
+			print(word)
 			print("You have somehow went beyond the magic")
-			return None
+			return self.save_5
+
 	# I have a test file (mytest.py) with pandas but couldn't figure out how to grab just a single cell.
 	# so I came up with this, if anyone knows how to get a single cell and can explain it to
 	# me I would love to know, as I think that method might be quicker, maybe, idk it like
@@ -118,31 +129,66 @@ class Indexer():
 				#JSON["url"] = url of crawled page, ignore fragments
 				#JSON["content"] = actual HTML
 				#JSON["encoding"] = ENCODING
+				ticker = perf_counter()
+				tic = perf_counter()
 				file_load = open(self.path + "/" + directory + "/"+file)
 				data = json.load(file_load)
 				soup = BeautifulSoup(data["content"],from_encoding=data["encoding"])
 				words = word_tokenize(soup.get_text())
+				toc = perf_counter()
+				if toc - tic > 1 :
+					print("Took " + str(toc - tic) + "seconds to tokenize text !")
+
 				tokenized_words = list()
 				stemmed_words = list()
+
+				tic = perf_counter()
 				for word in words:
-					if word != "" and word.isalnum():
+					if word != "" and re.fullmatch('[A-Za-z0-9]+',word):
 						#So all the tokenized words are here,
 						tokenized_words.append(word)
+				toc = perf_counter()
+				if toc - tic > 1 :
+					print("Took " + str(toc - tic) + "seconds to isalnum text !")
 				#YOUR CODE HERE
-				print(tokenized_words)
 
+				tic = perf_counter()
 				for word in tokenized_words:
 					stemmed_words.append(self.stemmer.stem(word))
-
-					print(X)
 					#stemming,
 					#tf_idf
 					#get_tf_idf(stemmed_words,word)
 					#post = Posting()
+				toc = perf_counter()
+				if toc - tic > 1 :
+					print("Took " + str(toc - tic) + "seconds to stemmed text !")
+
+				for word in stemmed_words:
+					#posting = Posting(data["url"],self.get_tf_idf(list(' '.join(stemmed_words)),word))
+					tic = perf_counter()
+					posting = Posting(data["url"],self.tf_idf_raw(stemmed_words,word))
+					toc = perf_counter()
+					if toc - tic > 1 :
+						print("Took " + str(toc - tic) + "seconds to tf_idf text !")
+
+					tic = perf_counter()
+					self.save_index(word,posting)
+					toc = perf_counter()
+					if toc - tic > 1 :
+						print("Took " + str(toc - tic) + "seconds to save text !")
+
+				tocker = perf_counter()
+				print("Finished " + data['url'] + " in \t " + str(tocker-ticker))
+
+	def tf_idf_raw(self,words,word):
+		tf_times = words.count(word)
+
+		tf = tf_times/len(words)
+
+		return tf
+
+		
 
-				print(stemmed_words)
-				#
-				exit(1)
 
 
 				

posting.py

@@ -1,9 +1,10 @@
 #Posting class for indexer, will probably be more complex as we keep adding crap to it
 
 class Posting():
-	def __init(self,url,tf_idf):
+	def __init__(self,url,tf_idf):
 		self.url = url
 		self.tf_idf = tf_idf
 		
 	def comparator(self):
-		#Some custom comparator for sorting postings later
+		#Some custom comparator for sorting postings later
+		pass