Search algo

Final algorithm!

algo/adreco.py

@@ -101,7 +101,6 @@ def index_from_id(df,id):
     '''
     return the index of a movie from its id
     '''
-    print(df[df['original_title']=='Uncharted'].index.values[0])
     return df[df['_id']==id].index.values[0]
 
 
@@ -167,30 +166,39 @@ def userDbToDf():
     return df
 
 def user_profile( user_index, moviesdf, usersdf, vectMatrix ):
-    
+    """
+    This function creates a user profile based on the likef movies of the user 
+    and ponderating the vectMatrix of all film liked
+    """
+
+    #fetch movies ID and index from the liked_movies
     moviesID=usersdf['liked_movies'].iloc[user_index]
-    print(moviesID)
-    print('Hello')
     moviesindex=[index_from_id(moviesdf,ID) for ID in moviesID]
+
     n=len(moviesID)#number of film liked
+
+
     if moviesindex != []:
+        #creates the vector of the user
         vectuser=vectMatrix[moviesindex[0]]
         moviesindex.pop(0)
         for i in moviesindex:
             vectuser = vectuser + vectMatrix[i]
         vectuser=vectuser/n
+
+        #calculates the user similarity
         calculated_sim = cosine_similarity(vectuser, vectMatrix)
 
         similarity_scores = list(enumerate(calculated_sim[0]))
-
         similarity_scores_sorted = sorted(similarity_scores, key=lambda x: x[1], reverse=True)
 
+        #lists recommendations index of the movies, ordered by weights
         recommendations_indices = [t[0] for t in similarity_scores_sorted[1:(100+1)]]
 
         return recommendations_indices
     
     else:
-        return
+        return [i for i in range(100)]
     
 def loadRecDB():
 
@@ -223,10 +231,8 @@ def updateDB():
         rec_indices=user_profile( i, moviesdf, usersdf, vect_matrix)
         
         if rec_indices != None:
-            print('pass')
             recdf = moviesdf['id'].iloc[rec_indices]
-
-            print(recdf)
+            titledf = moviesdf['original_title'].iloc[rec_indices]
 
             for j in recdf.index:
                 recommended_movies.append(int(recdf[j]))