diff --git a/src/opnsense/scripts/netflow/export_details.py b/src/opnsense/scripts/netflow/export_details.py
index 25c235ee3..b9d9d6831 100755
--- a/src/opnsense/scripts/netflow/export_details.py
+++ b/src/opnsense/scripts/netflow/export_details.py
@@ -69,7 +69,7 @@ if valid_params:
                 column_names = dict()
                 for record in obj.get_data(start_time, end_time):
                     if rownum == 0:
-                        column_names = record.keys()
+                        column_names = list(record.keys())
                         # dump heading
                         print (','.join(column_names))
                     line = list()
diff --git a/src/opnsense/scripts/netflow/flowd_aggregate.py b/src/opnsense/scripts/netflow/flowd_aggregate.py
index 111211ea7..f40375c4f 100755
--- a/src/opnsense/scripts/netflow/flowd_aggregate.py
+++ b/src/opnsense/scripts/netflow/flowd_aggregate.py
@@ -202,14 +202,14 @@ if __name__ == '__main__':
         if cmd_args.profile:
             # start with profiling
             import cProfile
-            import StringIO
+            import io
             import pstats
 
             pr = cProfile.Profile(builtins=False)
             pr.enable()
             Main()
             pr.disable()
-            s = StringIO.StringIO()
+            s = io.StringIO()
             sortby = 'cumulative'
             ps = pstats.Stats(pr, stream=s).sort_stats(sortby)
             ps.print_stats()
diff --git a/src/opnsense/scripts/netflow/lib/aggregate.py b/src/opnsense/scripts/netflow/lib/aggregate.py
index cbc360f3e..1b584f364 100644
--- a/src/opnsense/scripts/netflow/lib/aggregate.py
+++ b/src/opnsense/scripts/netflow/lib/aggregate.py
@@ -42,9 +42,9 @@ def convert_timestamp(val):
         else:
             datepart = val
             timepart = "0:0:0,0"
-        year, month, day = map(int, datepart.split("-"))
+        year, month, day = list(map(int, datepart.split("-")))
         timepart_full = timepart.split(".")
-        hours, minutes, seconds = map(int, timepart_full[0].split(":"))
+        hours, minutes, seconds = list(map(int, timepart_full[0].split(":")))
         if len(timepart_full) == 2:
             microseconds = int('{:0<6.6}'.format(timepart_full[1].decode()))
         else:
diff --git a/src/opnsense/scripts/netflow/lib/aggregates/__init__.py b/src/opnsense/scripts/netflow/lib/aggregates/__init__.py
index 34d02635d..dca0cadb7 100644
--- a/src/opnsense/scripts/netflow/lib/aggregates/__init__.py
+++ b/src/opnsense/scripts/netflow/lib/aggregates/__init__.py
@@ -78,10 +78,10 @@ class BaseFlowAggregator(object):
         tmp = 'update timeserie set  last_seen = :flow_end, '
         tmp += 'octets = octets + :octets_consumed, packets = packets + :packets_consumed '
         tmp += 'where mtime = :mtime and %s '
-        self._update_stmt = tmp % (' and '.join(map(lambda x: '%s = :%s' % (x, x), self.agg_fields)))
+        self._update_stmt = tmp % (' and '.join(['%s = :%s' % (x, x) for x in self.agg_fields]))
         tmp = 'insert into timeserie (mtime, last_seen, octets, packets, %s) '
         tmp += 'values (:mtime, :flow_end, :octets_consumed, :packets_consumed, %s)'
-        self._insert_stmt = tmp % (','.join(self.agg_fields), ','.join(map(lambda x: ':%s' % x, self.agg_fields)))
+        self._insert_stmt = tmp % (','.join(self.agg_fields), ','.join([':%s' % x for x in self.agg_fields]))
         # open database
         self._open_db()
         self._fetch_known_targets()
@@ -257,7 +257,7 @@ class BaseFlowAggregator(object):
             cur.execute(sql_select, {'start_time': self._parse_timestamp(start_time),
                                      'end_time': self._parse_timestamp(end_time)})
             #
-            field_names = (map(lambda x: x[0], cur.description))
+            field_names = ([x[0] for x in cur.description])
             for record in cur.fetchall():
                 result_record = dict()
                 for field_indx in range(len(field_names)):
@@ -321,7 +321,7 @@ class BaseFlowAggregator(object):
                 cur.execute(sql_select, query_params)
 
                 # fetch all data, to a max of [max_hits] rows.
-                field_names = (map(lambda x: x[0], cur.description))
+                field_names = ([x[0] for x in cur.description])
                 for record in cur.fetchall():
                     result_record = dict()
                     for field_indx in range(len(field_names)):
@@ -360,7 +360,7 @@ class BaseFlowAggregator(object):
             cur.execute(sql_select, query_params)
 
             # fetch all data, to a max of [max_hits] rows.
-            field_names = (map(lambda x: x[0], cur.description))
+            field_names = ([x[0] for x in cur.description])
             while True:
                 record = cur.fetchone()
                 if record is None: