New Master candidate

utils/pathfunctions.py

@@ -57,45 +57,21 @@ def filepathInitialGroup(df: pd.DataFrame):
                 break
         return join_parts(prefix)
 
-    # Step 6: Group directories by shared prefix using custom logic
-    """
-    Loop through each directory path
-    directories: list of all directory paths.
-    groups: will hold lists of grouped directories.
-    used: tracks which directories have already been grouped.
-    """
+    # Step 6: Group directories by shared prefix
     directories = df["directory"].tolist()
     groups = []
     used = set()
 
-    #For Each directory, compare it with others
-    """
-    Skip if already grouped.
-    Start a new group with the current path.
-    parts_i is the list of folder names in the path (e.g., ["C:", "Users", "John", "Documents"]).
-    """
-    
     for i, path in enumerate(directories):
         if path in used:
             continue
         group = [path]
         parts_i = get_parts(path)
 
-    #Compare with all other directories: For each other directory, split it into parts and find the common prefix (shared folder structure).
-        """
-        Logic:
-        If the directory is deep (>3 parts) and shares at least 3 parts → group it.
-        If it's exactly 3 parts long and shares at least 2 → group it.
-        Or, if it shares all but one part and is deep → group it.
-        These rules are designed to:
-        Group directories that are closely related in structure.
-        Avoid grouping unrelated paths that just happen to start similarly.
-        """  
-
         for j in range(i + 1, len(directories)):
             parts_j = get_parts(directories[j])
             common = os.path.commonprefix([parts_i, parts_j])
-        #Apply grouping rules
+
             if (len(parts_i) > 3 and len(common) >= 3) or (len(parts_i) == 3 and len(common) >= 2):
                 group.append(directories[j])
                 used.add(directories[j])
@@ -123,7 +99,7 @@ def filepathInitialGroup(df: pd.DataFrame):
     path_eligible = grouped_df[grouped_df["depth"] > 2].drop(columns=["depth"])
     path_ineligible = grouped_df[grouped_df["depth"] <= 2].drop(columns=["depth"])
 
-    # Step 10: Move entries from eligible to ineligible if grouped_directory contains 'C:\Users' or 'c$\Users'
+    # Step 10: Move entries from eligible to ineligible if grouped_directory contains excluded directories
     mask = path_eligible["grouped_directory"].str.contains(r"(?i)(?:\\Users|\\c\$\\Users|inetpub\\wwwroot|windows\\temp)", na=False)
     move_to_ineligible = path_eligible[mask]
     path_eligible = path_eligible[~mask]