#
# 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.
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"""End-to-end test for the leader board example.

Code: beam/sdks/python/apache_beam/examples/complete/game/leader_board.py
Usage:

  python setup.py nosetests --test-pipeline-options=" \
      --runner=TestDataflowRunner \
      --project=... \
      --region=... \
      --staging_location=gs://... \
      --temp_location=gs://... \
      --output=gs://... \
      --sdk_location=... \

"""

# pytype: skip-file

import logging
import time
import unittest
import uuid

from hamcrest.core.core.allof import all_of
from nose.plugins.attrib import attr

from apache_beam.examples.complete.game import leader_board
from apache_beam.io.gcp.tests import utils
from apache_beam.io.gcp.tests.bigquery_matcher import BigqueryMatcher
from apache_beam.runners.runner import PipelineState
from apache_beam.testing import test_utils
from apache_beam.testing.pipeline_verifiers import PipelineStateMatcher
from apache_beam.testing.test_pipeline import TestPipeline


class LeaderBoardIT(unittest.TestCase):

  # Input event containing user, team, score, processing time, window start.
  INPUT_EVENT = 'user1,teamA,10,%d,2015-11-02 09:09:28.224'
  INPUT_TOPIC = 'leader_board_it_input_topic'
  INPUT_SUB = 'leader_board_it_input_subscription'

  # SHA-1 hash generated from sorted rows reading from BigQuery table
  DEFAULT_EXPECTED_CHECKSUM = 'de00231fe6730b972c0ff60a99988438911cda53'
  OUTPUT_DATASET = 'leader_board_it_dataset'
  OUTPUT_TABLE_USERS = 'leader_board_users'
  OUTPUT_TABLE_TEAMS = 'leader_board_teams'
  DEFAULT_INPUT_COUNT = 500

  WAIT_UNTIL_FINISH_DURATION = 10 * 60 * 1000  # in milliseconds

  def setUp(self):
    self.test_pipeline = TestPipeline(is_integration_test=True)
    self.project = self.test_pipeline.get_option('project')
    _unique_id = str(uuid.uuid4())

    # Set up PubSub environment.
    from google.cloud import pubsub

    self.pub_client = pubsub.PublisherClient()
    self.input_topic = self.pub_client.create_topic(
        self.pub_client.topic_path(self.project, self.INPUT_TOPIC + _unique_id))

    self.sub_client = pubsub.SubscriberClient()
    self.input_sub = self.sub_client.create_subscription(
        self.sub_client.subscription_path(
            self.project, self.INPUT_SUB + _unique_id),
        self.input_topic.name)

    # Set up BigQuery environment
    self.dataset_ref = utils.create_bq_dataset(
        self.project, self.OUTPUT_DATASET)

    self._test_timestamp = int(time.time() * 1000)

  def _inject_pubsub_game_events(self, topic, message_count):
    """Inject game events as test data to PubSub."""

    logging.debug(
        'Injecting %d game events to topic %s', message_count, topic.name)

    for _ in range(message_count):
      self.pub_client.publish(
          topic.name, (self.INPUT_EVENT % self._test_timestamp).encode('utf-8'))

  def _cleanup_pubsub(self):
    test_utils.cleanup_subscriptions(self.sub_client, [self.input_sub])
    test_utils.cleanup_topics(self.pub_client, [self.input_topic])

  @attr('IT')
  def test_leader_board_it(self):
    state_verifier = PipelineStateMatcher(PipelineState.RUNNING)

    success_condition = 'total_score=5000 LIMIT 1'
    users_query = (
        'SELECT total_score FROM `%s.%s.%s` '
        'WHERE %s' % (
            self.project,
            self.dataset_ref.dataset_id,
            self.OUTPUT_TABLE_USERS,
            success_condition))
    bq_users_verifier = BigqueryMatcher(
        self.project, users_query, self.DEFAULT_EXPECTED_CHECKSUM)

    teams_query = (
        'SELECT total_score FROM `%s.%s.%s` '
        'WHERE %s' % (
            self.project,
            self.dataset_ref.dataset_id,
            self.OUTPUT_TABLE_TEAMS,
            success_condition))
    bq_teams_verifier = BigqueryMatcher(
        self.project, teams_query, self.DEFAULT_EXPECTED_CHECKSUM)

    extra_opts = {
        'allow_unsafe_triggers': True,
        'subscription': self.input_sub.name,
        'dataset': self.dataset_ref.dataset_id,
        'topic': self.input_topic.name,
        'team_window_duration': 1,
        'wait_until_finish_duration': self.WAIT_UNTIL_FINISH_DURATION,
        'on_success_matcher': all_of(
            state_verifier, bq_users_verifier, bq_teams_verifier)
    }

    # Register cleanup before pipeline execution.
    # Note that actual execution happens in reverse order.
    self.addCleanup(self._cleanup_pubsub)
    self.addCleanup(utils.delete_bq_dataset, self.project, self.dataset_ref)

    # Generate input data and inject to PubSub.
    self._inject_pubsub_game_events(self.input_topic, self.DEFAULT_INPUT_COUNT)

    # Get pipeline options from command argument: --test-pipeline-options,
    # and start pipeline job by calling pipeline main function.
    leader_board.run(
        self.test_pipeline.get_full_options_as_args(**extra_opts),
        save_main_session=False)


if __name__ == '__main__':
  logging.getLogger().setLevel(logging.DEBUG)
  unittest.main()
