Merge "fix pep8 problem in env.py"
[yardstick.git] / yardstick / benchmark / runners / dynamictp.py
index afff27d..63bfc82 100755 (executable)
 """A runner that searches for the max throughput with binary search
 """
 
-import os
-import multiprocessing
 import logging
-import traceback
+import multiprocessing
 import time
+import traceback
+
+import os
 
 from yardstick.benchmark.runners import base
 
@@ -65,8 +66,7 @@ def _worker_process(queue, cls, method_name, scenario_cfg,
             max_throuput_found = False
             sequence = 0
 
-            last_min_data = {}
-            last_min_data['packets_per_second'] = 0
+            last_min_data = {'packets_per_second': 0}
 
             while True:
                 sequence += 1
@@ -125,7 +125,7 @@ def _worker_process(queue, cls, method_name, scenario_cfg,
                     queue.put(record)
                     max_throuput_found = True
 
-                if (errors) or aborted.is_set() or max_throuput_found:
+                if errors or aborted.is_set() or max_throuput_found:
                     LOG.info("worker END")
                     break
 
@@ -141,11 +141,21 @@ def _worker_process(queue, cls, method_name, scenario_cfg,
             LOG.debug("iterator: %s iterations: %s", iterator, iterations)
 
     if "teardown" in run_step:
-        benchmark.teardown()
+        try:
+            benchmark.teardown()
+        except Exception:
+            # catch any exception in teardown and convert to simple exception
+            # never pass exceptions back to multiprocessing, because some exceptions can
+            # be unpicklable
+            # https://bugs.python.org/issue9400
+            LOG.exception("")
+            raise SystemExit(1)
+
+    LOG.debug("queue.qsize() = %s", queue.qsize())
 
 
 class IterationRunner(base.Runner):
-    '''Run a scenario to find the max throughput
+    """Run a scenario to find the max throughput
 
 If the scenario ends before the time has elapsed, it will be started again.
 
@@ -158,11 +168,13 @@ If the scenario ends before the time has elapsed, it will be started again.
         type:   int
         unit:   pps
         default: 1000 pps
-    '''
+    """
     __execution_type__ = 'Dynamictp'
 
     def _run_benchmark(self, cls, method, scenario_cfg, context_cfg):
+        name = "{}-{}-{}".format(self.__execution_type__, scenario_cfg.get("type"), os.getpid())
         self.process = multiprocessing.Process(
+            name=name,
             target=_worker_process,
             args=(self.result_queue, cls, method, scenario_cfg,
                   context_cfg, self.aborted))