Report all flakes reported to issue tracker also to FindIt

appengine/chromium_try_flakes/handlers/flake_issues.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.
 
 """Task queue endpoints for creating and updating issues on issue tracker."""
 
 import datetime
 import json
 import logging
 import urllib2
 import webapp2
 
 from google.appengine.api import app_identity
 from google.appengine.api import taskqueue
 from google.appengine.api import urlfetch
 from google.appengine.api import users
 from google.appengine.ext import ndb
 
 from apiclient.errors import HttpError
+from findit import findit
 import gae_ts_mon
 from issue_tracker import issue_tracker_api, issue
 from model.flake import (
     Flake, FlakeOccurrence, FlakeUpdate, FlakeUpdateSingleton, FlakyRun)
 from model.build_run import BuildRun
 from status import build_result, util
 from test_results.util import normalize_test_type, flatten_tests_trie
 
 
 MAX_UPDATED_ISSUES_PER_DAY = 10
@@ skipping 178 matching lines @@
     # TODO(sergiyb): Find a way to do this asynchronously to avoid block
     # transaction-bound method calling this. Possible solutions are to use
     # put_multi_sync (need to find a way to test this) or to use deferred
     # execution.
     for fr in new_flaky_runs:
       for occ in fr.flakes:
         if occ.failure == name:
           occ.issue_id = issue_id
     ndb.put_multi(new_flaky_runs)
 
+  @staticmethod
+  @ndb.non_transactional
+  def _report_flakes_to_findit(flake, flaky_runs):
+    findit.FindItAPI().flake(flake, flaky_runs)
+
   @ndb.transactional
   def _update_issue(self, api, flake, new_flakes, now):
     """Updates an issue on the issue tracker."""
     flake_issue = api.getIssue(flake.issue_id)
 
     # Handle cases when an issue has been closed. We need to do this in a loop
     # because we might move onto another issue.
     seen_issues = set()
     while not flake_issue.open:
       if flake_issue.status == 'Duplicate':
@@ skipping 36 matching lines @@
         'suffix': ' %s' % suffix if suffix else ''}
     api.update(flake_issue, comment=new_flaky_runs_msg)
     self.issue_updates.increment_by(1, {'operation': 'update'})
     logging.info('Updated issue %d for flake %s with %d flake runs',
                  flake.issue_id, flake.name, len(new_flakes))
     self._update_new_occurrences_with_issue_id(
         flake.name, new_flakes, flake_issue.id)
     flake.num_reported_flaky_runs = len(flake.occurrences)
     flake.issue_last_updated = now
 
+    self._report_flakes_to_findit(flake, new_flakes)
+
   @ndb.transactional
   def _create_issue(self, api, flake, new_flakes, now):
     _, qlabel = get_queue_details(flake.name)
     labels = ['Type-Bug', 'Pri-1', 'Via-TryFlakes', qlabel]
     if is_trooper_flake(flake.name):
       other_queue_msg = TROOPER_QUEUE_MSG
     else:
       other_queue_msg = SHERIFF_QUEUE_MSG
 
     summary = SUMMARY_TEMPLATE % {'name': flake.name}
@@ skipping 15 matching lines @@
     flake_issue = api.create(new_issue)
     flake.issue_id = flake_issue.id
     self._update_new_occurrences_with_issue_id(
         flake.name, new_flakes, flake_issue.id)
     flake.num_reported_flaky_runs = len(flake.occurrences)
     flake.issue_last_updated = now
     self.issue_updates.increment_by(1, {'operation': 'create'})
     logging.info('Created a new issue %d for flake %s', flake.issue_id,
                  flake.name)
 
+    self._report_flakes_to_findit(flake, new_flakes)
+
     # Find all flakes in the current flakiness period to compute metrics. The
     # flakiness period is a series of flakes with a gap no larger than
     # MAX_GAP_FOR_FLAKINESS_PERIOD seconds.
     period_flakes = self._find_flakiness_period_occurrences(flake)
 
     # Compute the delay since the first flake in the current flakiness period.
     time_since_first_flake = (
         now - period_flakes[0].failure_run_time_finished).total_seconds()
     self.time_since_first_flake.set(time_since_first_flake)
     logging.info('Reported time_since_first_flake %d for flake %s',
@@ skipping 393 matching lines @@
         return
 
     key = self.request.get('key')
     flake = ndb.Key(urlsafe=key).get()
     flake.issue_id = issue_id
     flake.put()
 
     logging.info('%s updated issue_id for flake %s to %d.', user_email,
                  flake.name, issue_id)
     self.redirect('/all_flake_occurrences?key=%s' % key)