"Fix" a flaky test and cleanup an unused import.

[python_utils.git] / unittest_utils.py

diff --git a/unittest_utils.py b/unittest_utils.py
index 8a0556bb52bd8a0e6a135c3923bc0749bdb167d8..8c9a1202f99d46708b8abfd083fc3f57256fcacc 100644 (file)
--- a/unittest_utils.py
+++ b/unittest_utils.py
@@ -56,13 +56,14 @@ _db = '/home/scott/.python_unittest_performance_db'
 
 
 def check_method_for_perf_regressions(func: Callable) -> Callable:
-    """This is meant to be used on a method in a class that subclasses
+    """
+    This is meant to be used on a method in a class that subclasses
     unittest.TestCase.  When thus decorated it will time the execution
     of the code in the method, compare it with a database of
     historical perfmance, and fail the test with a perf-related
     message if it has become too slow.
-    """
 
+    """
     def load_known_test_performance_characteristics():
         with open(_db, 'rb') as f:
             return pickle.load(f)
@@ -77,7 +78,8 @@ def check_method_for_perf_regressions(func: Callable) -> Callable:
             perfdb = load_known_test_performance_characteristics()
         except Exception as e:
             logger.exception(e)
-            logger.warning(f'Unable to load perfdb from {_db}')
+            msg = f'Unable to load perfdb from {_db}'
+            logger.warning(msg)
             perfdb = {}
 
         # This is a unique identifier for a test: filepath!function
@@ -107,7 +109,7 @@ def check_method_for_perf_regressions(func: Callable) -> Callable:
             )
         else:
             stdev = statistics.stdev(hist)
-            limit = hist[-1] + stdev * 3
+            limit = hist[-1] + stdev * 5
             logger.debug(
                 f'Max acceptable performace for {func.__name__} is {limit:f}s'
             )
@@ -117,12 +119,14 @@ def check_method_for_perf_regressions(func: Callable) -> Callable:
             ):
                 msg = f'''{func_id} performance has regressed unacceptably.
 {hist[-1]:f}s is the slowest record in {len(hist)} db perf samples.
-It just ran in {run_time:f}s which is >3 stdevs slower than the slowest sample.
+It just ran in {run_time:f}s which is >5 stdevs slower than the slowest sample.
 Here is the current, full db perf timing distribution:
 
-{hist}'''
-                slf = args[0]
+'''
+                for x in hist:
+                    msg += f'{x:f}\n'
                 logger.error(msg)
+                slf = args[0]
                 slf.fail(msg)
             else:
                 hist.append(run_time)