Create flip_tables.py

Author: mwilco03

flip_tables.py

@@ -0,0 +1,99 @@
+###This code parses tabular data *automatically using the headers for keys
+###TL;DR Tabular data to list of dictionaries ready for json
+
+import itertools
+import collections
+
+
+###TODO: dynamic import
+###TODO: Automatic test for headers
+###TODO: Automatic expansion on lines that "aren't perfect"
+###TODO: dynamic values for str_match or at least user defineable
+###TODO: dynamic values for headers if duplicates
+def find(s, ch):
+     return [i for i, ltr in enumerate(s) if ltr == ch]
+
+with open("desktop\\SSIDSECURITY2.txt","r") as f:
+    list_arrays = f.readlines()
+
+def freq_check(str_match,list_arrays):
+    list_occurances = [find(i,str_match) for i in list_arrays]
+    return list_occurances
+
+def get_max_len(list_arrays):
+    longest = len(max(list_arrays,key=len))
+    return longest
+
+def get_most_common(list_arrays):
+    x = itertools.chain.from_iterable(list_arrays)
+    most_common_char = collections.Counter(itertools.chain.from_iterable(x)).most_common()[0][0]
+    return most_common_char 
+
+str_match = get_most_common(list_arrays)
+list_occurances = freq_check(str_match,list_arrays)
+longest = get_max_len(list_arrays)
+
+###Creates a list of tuples that dictate most common occurances of str_match
+elements = sorted(collections.Counter(itertools.chain.from_iterable(list_occurances)).items(), key=lambda item: (-item[1], item[0]))
+###Be able to tell what the max occurance is
+max_occurance =  elements[0][1]
+
+###Create a list from the common str_match
+slicer = []
+[slicer.append(list(i)) for i in elements if i[1] == max_occurance]
+
+###FANCY *ISH* HERE
+###enumerate over list of space stops
+###Basically so we have a left and right bounding area
+stops = []
+for idx,element in enumerate(slicer):
+    ###get the next element of the list
+    nxt_element = slicer[(idx + 1) % len(slicer)][0]
+    ###appeend the two elements to the list
+    stops.append([element[0],nxt_element])
+stops[len(stops)-1][1] = longest
+stops[0][0] = 0
+
+
+cols = []
+for i in stops:
+    for h in list_arrays:
+       cols.append(h[i[0]:i[1]].strip())
+
+idx_list = []
+for idx,i in enumerate(cols):
+    if i == '':
+        idx_list.append(idx)
+
+###Similar to lines 35 bounding areas
+comp_list = []
+for idx,element in enumerate(idx_list):
+    nxt_element = idx_list[(idx+1)%len(idx_list)]
+    comp_list.append([element,nxt_element])
+
+comp_list.insert(0,[0,idx_list[0]])
+comp_list.pop()
+
+info = []
+for i in comp_list:
+    info.append(cols[i[0]:i[1]])
+
+for idx,i in enumerate(info):
+    if idx > 0:
+        info[idx].pop(0)
+
+###The code below creates a sorted list of all elments in the list
+###We can then group those items from the [0] element creating a list of tuples 
+###What it looks like is (0,'BSSID','BSSID'),...,(1,'BSSID','DE:AD:BE:EF')
+###TODO: This code is slick, I question it's sustainability 
+x_sorted_list = sorted(itertools.chain.from_iterable([[(idx,i[0],h) for idx,h in enumerate(i)] for i in info]))
+x_list = []
+###The code groups list by first element
+###https://stackoverflow.com/questions/58403206/how-to-group-lists-inside-a-list-by-first-element
+###Then appends that to the x_list
+for i in [list(item[1]) for item in itertools.groupby(x_sorted_list, key=lambda x: x[0])]:
+    x_obj = {}
+    for h in i:
+        x_obj[h[1]] = h[2]
+    x_list.append(x_obj)
+x_list.pop(0)