Index: lnt/server/reporting/runs.py
===================================================================
--- lnt/server/reporting/runs.py
+++ lnt/server/reporting/runs.py
@@ -2,6 +2,7 @@
 Report functionality centered around individual runs.
 """
 
+from collections import namedtuple
 import time
 import lnt.server.reporting.analysis
 import lnt.server.ui.app
@@ -123,7 +124,9 @@
         if not bucket or bucket_name == 'Unchanged Test' or not show_perf:
             return bucket
         else:
-            return sorted(bucket, key=lambda (_, cr, __): -abs(cr.pct_delta))
+            return sorted(
+                bucket,
+                key=lambda bucket_entry: -abs(bucket_entry.cr.pct_delta))
 
     def prioritize_buckets(test_results):
         prioritized = [(priority, field, bucket_name,
@@ -212,6 +215,7 @@
     return data
 
 
+BucketEntry = namedtuple('BucketEntry', ['name', 'cr', 'test_id'])
 def _get_changes_by_type(ts, run_a, run_b, metric_fields, test_names,
                          num_comparison_runs, sri):
     comparison_results = {}
@@ -249,7 +253,7 @@
             else:
                 bucket = unchanged_tests
 
-            bucket.append((name, cr, test_id))
+            bucket.append(BucketEntry(name, cr, test_id))
 
         results_by_type.append(
             (field, (('New Failures', new_failures, False),
Index: lnt/server/ui/views.py
===================================================================
--- lnt/server/ui/views.py
+++ lnt/server/ui/views.py
@@ -799,6 +799,8 @@
     show_highlight = not options['hide_highlight']
 
     # Load the graph parameters.
+    GraphParameter = namedtuple('GraphParameter',
+                                ['machine', 'test', 'field', 'field_index'])
     graph_parameters = []
     for name, value in request.args.items():
         # Plots to graph are passed as::
@@ -827,10 +829,12 @@
             field = ts.sample_fields[field_index]
         except NoResultFound:
             return abort(404)
-        graph_parameters.append((machine, test, field, field_index))
+        graph_parameters.append(GraphParameter(machine, test, field, field_index))
 
     # Order the plots by machine name, test name and then field.
-    graph_parameters.sort(key=lambda (m, t, f, _): (m.name, t.name, f.name, _))
+    graph_parameters.sort(key=lambda graph_parameter:
+                          (graph_parameter.machine.name, graph_parameter.test.name,
+                           graph_parameter.field.name, graph_parameter.field_index))
 
     # Extract requested mean trend.
     mean_parameter = None