#
# 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
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# distributed under the License is distributed on an "AS IS" BASIS,
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"""Unit tests for the PipelineRunner and DirectRunner classes.

Note that PipelineRunner and DirectRunner functionality is tested in all
the other unit tests. In this file we choose to test only aspects related to
caching and clearing values that are not tested elsewhere.
"""

# pytype: skip-file

from __future__ import absolute_import

import unittest

import apache_beam as beam
from apache_beam.metrics.metric import Metrics
from apache_beam.runners import DirectRunner
from apache_beam.runners import create_runner


class RunnerTest(unittest.TestCase):
  default_properties = [
      '--dataflow_endpoint=ignored',
      '--job_name=test-job',
      '--project=test-project',
      '--staging_location=ignored',
      '--temp_location=/dev/null',
      '--no_auth'
  ]

  def test_create_runner(self):
    self.assertTrue(isinstance(create_runner('DirectRunner'), DirectRunner))
    self.assertRaises(ValueError, create_runner, 'xyz')

  def test_create_runner_shorthand(self):
    self.assertTrue(isinstance(create_runner('DiReCtRuNnEr'), DirectRunner))
    self.assertTrue(isinstance(create_runner('directrunner'), DirectRunner))
    self.assertTrue(isinstance(create_runner('direct'), DirectRunner))
    self.assertTrue(isinstance(create_runner('DiReCt'), DirectRunner))
    self.assertTrue(isinstance(create_runner('Direct'), DirectRunner))

  def test_run_api(self):
    my_metric = Metrics.counter('namespace', 'my_metric')
    runner = DirectRunner()
    result = runner.run(
        beam.Create([1, 10, 100]) | beam.Map(lambda x: my_metric.inc(x)))
    result.wait_until_finish()
    # Use counters to assert the pipeline actually ran.
    my_metric_value = result.metrics().query()['counters'][0].committed
    self.assertEqual(my_metric_value, 111)

  def test_run_api_with_callable(self):
    my_metric = Metrics.counter('namespace', 'my_metric')

    def fn(start):
      return (
          start
          | beam.Create([1, 10, 100])
          | beam.Map(lambda x: my_metric.inc(x)))

    runner = DirectRunner()
    result = runner.run(fn)
    result.wait_until_finish()
    # Use counters to assert the pipeline actually ran.
    my_metric_value = result.metrics().query()['counters'][0].committed
    self.assertEqual(my_metric_value, 111)


if __name__ == '__main__':
  unittest.main()
