Update infra_libs to 1.1.15 / 0b44aba87c1c6538439df6d24a409870810747ab

client/third_party/infra_libs/ts_mon/common/interface.py

 # Copyright 2015 The Chromium Authors. All rights reserved.
 # Use of this source code is governed by a BSD-style license that can be
 # found in the LICENSE file.
 
 """Classes representing the monitoring interface for tasks or devices.
 
 Usage:
   import argparse
   from infra_libs import ts_mon
 
@@ skipping 22 matching lines @@
 
 import datetime
 import logging
 import random
 import threading
 import time
 import traceback
 
 from infra_libs.ts_mon.common import errors
 from infra_libs.ts_mon.common import metric_store
-from infra_libs.ts_mon.protos.current import metrics_pb2
-from infra_libs.ts_mon.protos.new import metrics_pb2 as new_metrics_pb2
+from infra_libs.ts_mon.protos import metrics_pb2
 
 # The maximum number of MetricsData messages to include in each HTTP request.
 # MetricsCollections larger than this will be split into multiple requests.
 METRICS_DATA_LENGTH_LIMIT = 500
 
 
 class State(object):
   """Package-level state is stored here so that it is easily accessible.
 
   Configuration is kept in this one object at the global level so that all
@@ skipping 19 matching lines @@
     # --ts-mon-flush != 'auto' or --ts-mon-flush-interval-secs == 0.
     self.flush_thread = None
     # All metrics created by this application.
     self.metrics = {}
     # The MetricStore object that holds the actual metric values.
     self.store = store_ctor(self)
     # Cached time of the last flush. Useful mostly in AppEngine apps.
     self.last_flushed = datetime.datetime.utcfromtimestamp(0)
     # Metric name prefix
     self.metric_name_prefix = '/chrome/infra/'
-    # Use the new proto schema
-    self.use_new_proto = False
     # Metrics registered with register_global_metrics.  Keyed by metric name.
     self.global_metrics = {}
     # Callbacks registered with register_global_metrics_callback.  Keyed by the
     # arbitrary string provided by the user.  Called before each flush.
     self.global_metrics_callbacks = {}
     # Whether to call invoke_global_callbacks() on every flush().  Set to False
     # on Appengine because it does its own thing.
     self.invoke_global_callbacks_on_flush = True
 
   def reset_for_unittest(self):
     self.metrics = {}
     self.global_metrics = {}
     self.global_metrics_callbacks = {}
     self.invoke_global_callbacks_on_flush = True
     self.last_flushed = datetime.datetime.utcfromtimestamp(0)
     self.store.reset_for_unittest()
-    self.use_new_proto = False
 
 state = State()
 
 
 def flush():
   """Send all metrics that are registered in the application."""
   if not state.flush_enabled_fn():
     logging.debug('ts_mon: sending metrics is disabled.')
     return
 
   if not state.global_monitor or not state.target:
     raise errors.MonitoringNoConfiguredMonitorError(None)
 
   if state.invoke_global_callbacks_on_flush:
     invoke_global_callbacks()
 
-  if state.use_new_proto:
-    generator = _generate_proto_new
-  else:
-    generator = _generate_proto
-
-  for proto in generator():
-    state.global_monitor.send(proto)
+  rpcs = []
+  for proto in _generate_proto():
+    rpcs.append(state.global_monitor.send(proto))
+  for rpc in rpcs:
+    if rpc is not None:
+      state.global_monitor.wait(rpc)
   state.last_flushed = datetime.datetime.utcnow()
 
 
-def _generate_proto_new():
+def _generate_proto():
   """Generate MetricsPayload for global_monitor.send()."""
-  proto = new_metrics_pb2.MetricsPayload()
+  proto = metrics_pb2.MetricsPayload()
 
   # Key: Target, value: MetricsCollection.
   collections = {}
 
   # Key: (Target, metric name) tuple, value: MetricsDataSet.
   data_sets = {}
 
   count = 0
   for (target, metric, start_time, end_time, fields_values
        ) in state.store.get_all():
     for fields, value in fields_values.iteritems():
       if count >= METRICS_DATA_LENGTH_LIMIT:
         yield proto
-        proto = new_metrics_pb2.MetricsPayload()
+        proto = metrics_pb2.MetricsPayload()
         collections.clear()
         data_sets.clear()
         count = 0
 
       if target not in collections:
         collections[target] = proto.metrics_collection.add()
-        target._populate_target_pb_new(collections[target])
+        target.populate_target_pb(collections[target])
       collection = collections[target]
 
       key = (target, metric.name)
       new_data_set = None
       if key not in data_sets:
-        new_data_set = new_metrics_pb2.MetricsDataSet()
-        metric._populate_data_set(new_data_set)
+        new_data_set = metrics_pb2.MetricsDataSet()
+        metric.populate_data_set(new_data_set)
 
-      data = new_metrics_pb2.MetricsData()
-      metric._populate_data(data, start_time, end_time, fields, value)
+      data = metrics_pb2.MetricsData()
+      metric.populate_data(data, start_time, end_time, fields, value)
 
       # All required data protos have been successfully populated. Now we can
       # insert them in serialized proto and bookeeping data structures.
       if new_data_set is not None:
         collection.metrics_data_set.add().CopyFrom(new_data_set)
         data_sets[key] = collection.metrics_data_set[-1]
       data_sets[key].data.add().CopyFrom(data)
       count += 1
 
   if count > 0:
     yield proto
 
 
-def _generate_proto():
-  """Generate MetricsCollection for global_monitor.send()."""
-  proto = metrics_pb2.MetricsCollection()
-
-  for target, metric, start_time, _, fields_values in state.store.get_all():
-    for fields, value in fields_values.iteritems():
-      if len(proto.data) >= METRICS_DATA_LENGTH_LIMIT:
-        yield proto
-        proto = metrics_pb2.MetricsCollection()
-
-      metrics_pb = metrics_pb2.MetricsData()
-      metric.serialize_to(metrics_pb, start_time, fields, value, target)
-
-      proto.data.add().CopyFrom(metrics_pb)
-
-  if len(proto.data) > 0:
-    yield proto
-
-
 def register(metric):
   """Adds the metric to the list of metrics sent by flush().
 
   This is called automatically by Metric's constructor.
   """
   # If someone is registering the same metric object twice, that's okay, but
   # registering two different metric objects with the same metric name is not.
   for m in state.metrics.values():
     if metric == m:
       state.metrics[metric.name] = metric
@@ skipping 10 matching lines @@
 
 
 def close():
   """Stops any background threads and waits for them to exit."""
   if state.flush_thread is not None:
     state.flush_thread.stop()
 
 
 def reset_for_unittest(disable=False):
   state.reset_for_unittest()
-  if disable:
-    state.flush_enabled_fn = lambda: False
+  state.flush_enabled_fn = lambda: not disable
 
 
 def register_global_metrics(metrics):
   """Declare metrics as global.
 
   Outside Appengine this has no effect.
 
   On Appengine, registering a metric as "global" simply means it will be reset
   every time the metric is sent. This allows any instance to send such a metric
   to a shared stream, e.g. by overriding target fields like task_num (instance
@@ skipping 78 matching lines @@
             'Last monitoring flush took %f seconds (longer than '
             '--ts-mon-flush-interval-secs = %f seconds)',
             flush_duration, self.interval_secs)
         next_timeout = 0
 
   def stop(self):
     """Stops the background thread and performs a final flush."""
 
     self.stop_event.set()
     self.join()