text: #!/usr/bin/env python3
  # -*- coding: utf-8 -*-
  # Licensed to the Apache Software Foundation (ASF) under one or more
  # contributor license agreements.  See the NOTICE file distributed with
  # this work for additional information regarding copyright ownership.
  # The ASF licenses this file to You under the Apache License, Version 2.0
  # (the "License"); you may not use this file except in compliance with
  # the License.  You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  ########################################################################
  # OPENAPI-URI: /api/ci/queue
  ########################################################################
  # get:
  #   responses:
  #     '200':
  #       content:
  #         application/json:
  #           schema:
  #             $ref: '#/components/schemas/Timeseries'
  #       description: 200 Response
  #     default:
  #       content:
  #         application/json:
  #           schema:
  #             $ref: '#/components/schemas/Error'
  #       description: unexpected error
  #   security:
  #   - cookieAuth: []
  #   summary: Shows email sent over time
  # post:
  #   requestBody:
  #     content:
  #       application/json:
  #         schema:
  #           $ref: '#/components/schemas/defaultWidgetArgs'
  #   responses:
  #     '200':
  #       content:
  #         application/json:
  #           schema:
  #             $ref: '#/components/schemas/Timeseries'
  #       description: 200 Response
  #     default:
  #       content:
  #         application/json:
  #           schema:
  #             $ref: '#/components/schemas/Error'
  #       description: unexpected error
  #   security:
  #   - cookieAuth: []
  #   summary: Shows CI queue over time
  # 
  ########################################################################
  
  
  
  """
  This is the CI queue timeseries renderer for Kibble
  """
  
  import json
  import time
  import hashlib
  
  def run(API, environ, indata, session):
      
      # We need to be logged in for this!
      if not session.user:
          raise API.exception(403, "You must be logged in to use this API endpoint! %s")
      
      now = time.time()
      
      # First, fetch the view if we have such a thing enabled
      viewList = []
      if indata.get('view'):
          viewList = session.getView(indata.get('view'))
      if indata.get('subfilter'):
          viewList = session.subFilter(indata.get('subfilter'), view = viewList) 
      
      # We only want build sources, so we can sum up later.
      viewList = session.subType(['jenkins', 'travis', 'buildbot'], viewList)
      
      dateTo = indata.get('to', int(time.time()))
      dateFrom = indata.get('from', dateTo - (86400*30*6)) # Default to a 6 month span
      
      interval = indata.get('interval', 'month')
      
      
      ####################################################################
      ####################################################################
      dOrg = session.user['defaultOrganisation'] or "apache"
      query = {
                  'query': {
                      'bool': {
                          'must': [
                              {'range':
                                  {
                                      'time': {
                                          'from': dateFrom,
                                          'to': dateTo
                                      }
                                  }
                              },
                              {
                                  'term': {
                                      'organisation': dOrg
                                  }
                              }
                          ]
                      }
                  }
              }
      # Source-specific or view-specific??
      if indata.get('source'):
          viewList = [indata.get('source')]
      
      query['query']['bool']['must'].append({'term': {'sourceID': 'x'}})
      
      timeseries = []
      for source in viewList:
          query['query']['bool']['must'][2] = {'term': {'sourceID': source}}
          
          # Get queue stats
          query['aggs'] = {
                  'timeseries': {
                      'date_histogram': {
                          'field': 'date',
                          'interval': interval
                      },
                      'aggs': {
                          'size': {
                              'avg': {
                                  'field': 'size'
                              }
                          },
                          'blocked': {
                              'avg': {
                                  'field': 'blocked'
                              }
                          },
                          'building': {
                              'avg': {
                                  'field': 'building'
                              }
                          },
                          'stuck': {
                              'avg': {
                                  'field': 'stuck'
                              }
                          },
                          'wait': {
                              'avg': {
                                  'field': 'avgwait'
                              }
                          }
                      }
                  }
              }
          res = session.DB.ES.search(
                  index=session.DB.dbname,
                  doc_type="ci_queue",
                  size = 0,
                  body = query
              )
  
          for bucket in res['aggregations']['timeseries']['buckets']:
              ts = int(bucket['key'] / 1000)
              bucket['wait']['value'] = bucket['wait'].get('value', 0) or 0
              if bucket['doc_count'] == 0:
                  continue
              
              found = False
              for t in timeseries:
                  if t['date'] == ts:
                      found = True
                      t['queue size'] += bucket['size']['value']
                      t['builds running'] += bucket['building']['value']
                      t['average wait (hours)'] += bucket['wait']['value']
                      t['builders'] += 1
              if not found:
                  timeseries.append({
                      'date': ts,
                      'queue size': bucket['size']['value'],
                      'builds running': bucket['building']['value'],
                      'average wait (hours)': bucket['wait']['value'],
                      'builders': 1,
                  })
      
      for t in timeseries:
          t['average wait (hours)'] = int(t['average wait (hours)']/360)/10.0
          del t['builders']
          
      JSON_OUT = {
          'widgetType': {
              'chartType': 'line',  # Recommendation for the UI
              'nofill': True
          },
          'timeseries': timeseries,
          'interval': interval,
          'okay': True,
          'responseTime': time.time() - now
      }
      yield json.dumps(JSON_OUT)
  