HTML_Similarity

ExampleNotebooks/HTML_Similarity.ipynb

+%% Cell type:code id: tags:
 
+``` 
+# -*- coding: utf-8 -*-
+
+import pandas as pd
+from html_similarity import style_similarity, structural_similarity, similarity
+from bs4 import BeautifulSoup, Doctype
+import imgkit
 ```
 
+%% Cell type:code id: tags:
 
+``` 
+file = pd.read_parquet('data.parquet', engine='pyarrow')
+numRows = len(file.index)
+
+validPayloads = []
+timestamps = []
+for i in range(numRows):
+    payload = file.iloc[i].payload
+    mime = file.iloc[i].mime
+    timestamp = file.iloc[i].timestamp
+
+    soup = (BeautifulSoup(payload, "html.parser"))
+
+    # check for only vt.edu
+
+    if (mime == 'text/html' and len(payload) > 1):
+        validPayloads.append(payload)
+        timestamps.append(timestamp)
+
 ```
 
+%% Cell type:code id: tags:
 
+``` 
+for i in range(len(validPayloads)):
+    outFileName = 'captures/' + str(timestamps[i]) + '.jpg'
+
+    #imgkit.from_string(validPayloads[i], outFileName)
+
+scores = [[-1 for i in range(len(validPayloads))] for j in range(len(validPayloads))]
+for i in range(len(validPayloads)):
+    payload1 = validPayloads[i]
+
+    for j in range(len(validPayloads)):
+
+        payload2 = validPayloads[j]
+
+        try:
+            # print(i,j)
+            score = str(similarity(payload1, payload2))
+            scores[i][j] = score
+            # print(score)
+
+        except:
+            print(i, j)
 ```