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# 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
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#    http://www.apache.org/licenses/LICENSE-2.0
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# pytype: skip-file

from __future__ import absolute_import

import threading
import unittest
from collections import defaultdict

import hamcrest as hc

import apache_beam as beam
from apache_beam.metrics.cells import DistributionData
from apache_beam.metrics.cells import DistributionResult
from apache_beam.metrics.execution import MetricKey
from apache_beam.metrics.execution import MetricResult
from apache_beam.metrics.metric import Metrics
from apache_beam.metrics.metricbase import MetricName
from apache_beam.pipeline import Pipeline
from apache_beam.runners import DirectRunner
from apache_beam.runners import TestDirectRunner
from apache_beam.runners import create_runner
from apache_beam.runners.direct.evaluation_context import _ExecutionContext
from apache_beam.runners.direct.transform_evaluator import _GroupByKeyOnlyEvaluator
from apache_beam.runners.direct.transform_evaluator import _TransformEvaluator
from apache_beam.testing import test_pipeline
from apache_beam.testing.util import assert_that
from apache_beam.testing.util import equal_to


class DirectPipelineResultTest(unittest.TestCase):
  def test_waiting_on_result_stops_executor_threads(self):
    pre_test_threads = set(t.ident for t in threading.enumerate())

    for runner in ['DirectRunner',
                   'BundleBasedDirectRunner',
                   'SwitchingDirectRunner']:
      pipeline = test_pipeline.TestPipeline(runner=runner)
      _ = (pipeline | beam.Create([{'foo': 'bar'}]))
      result = pipeline.run()
      result.wait_until_finish()

      post_test_threads = set(t.ident for t in threading.enumerate())
      new_threads = post_test_threads - pre_test_threads
      self.assertEqual(len(new_threads), 0)

  def test_direct_runner_metrics(self):
    class MyDoFn(beam.DoFn):
      def start_bundle(self):
        count = Metrics.counter(self.__class__, 'bundles')
        count.inc()

      def finish_bundle(self):
        count = Metrics.counter(self.__class__, 'finished_bundles')
        count.inc()

      def process(self, element):
        gauge = Metrics.gauge(self.__class__, 'latest_element')
        gauge.set(element)
        count = Metrics.counter(self.__class__, 'elements')
        count.inc()
        distro = Metrics.distribution(self.__class__, 'element_dist')
        distro.update(element)
        return [element]

    p = Pipeline(DirectRunner())
    pcoll = (
        p | beam.Create([1, 2, 3, 4, 5], reshuffle=False)
        | 'Do' >> beam.ParDo(MyDoFn()))
    assert_that(pcoll, equal_to([1, 2, 3, 4, 5]))
    result = p.run()
    result.wait_until_finish()
    metrics = result.metrics().query()
    namespace = '{}.{}'.format(MyDoFn.__module__, MyDoFn.__name__)

    hc.assert_that(
        metrics['counters'],
        hc.contains_inanyorder(
            MetricResult(
                MetricKey('Do', MetricName(namespace, 'elements')), 5, 5),
            MetricResult(
                MetricKey('Do', MetricName(namespace, 'bundles')), 1, 1),
            MetricResult(
                MetricKey('Do', MetricName(namespace, 'finished_bundles')),
                1,
                1)))

    hc.assert_that(
        metrics['distributions'],
        hc.contains_inanyorder(
            MetricResult(
                MetricKey('Do', MetricName(namespace, 'element_dist')),
                DistributionResult(DistributionData(15, 5, 1, 5)),
                DistributionResult(DistributionData(15, 5, 1, 5)))))

    gauge_result = metrics['gauges'][0]
    hc.assert_that(
        gauge_result.key,
        hc.equal_to(MetricKey('Do', MetricName(namespace, 'latest_element'))))
    hc.assert_that(gauge_result.committed.value, hc.equal_to(5))
    hc.assert_that(gauge_result.attempted.value, hc.equal_to(5))

  def test_create_runner(self):
    self.assertTrue(isinstance(create_runner('DirectRunner'), DirectRunner))
    self.assertTrue(
        isinstance(create_runner('TestDirectRunner'), TestDirectRunner))


class BundleBasedRunnerTest(unittest.TestCase):
  def test_type_hints(self):
    with test_pipeline.TestPipeline(runner='BundleBasedDirectRunner') as p:
      _ = (
          p
          | beam.Create([[]]).with_output_types(beam.typehints.List[int])
          | beam.combiners.Count.Globally())

  def test_impulse(self):
    with test_pipeline.TestPipeline(runner='BundleBasedDirectRunner') as p:
      assert_that(p | beam.Impulse(), equal_to([b'']))


class DirectRunnerRetryTests(unittest.TestCase):
  def test_retry_fork_graph(self):
    # TODO(BEAM-3642): The FnApiRunner currently does not currently support
    # retries.
    p = beam.Pipeline(runner='BundleBasedDirectRunner')

    # TODO(mariagh): Remove the use of globals from the test.
    global count_b, count_c  # pylint: disable=global-variable-undefined
    count_b, count_c = 0, 0

    def f_b(x):
      global count_b  # pylint: disable=global-variable-undefined
      count_b += 1
      raise Exception('exception in f_b')

    def f_c(x):
      global count_c  # pylint: disable=global-variable-undefined
      count_c += 1
      raise Exception('exception in f_c')

    names = p | 'CreateNodeA' >> beam.Create(['Ann', 'Joe'])

    fork_b = names | 'SendToB' >> beam.Map(f_b)  # pylint: disable=unused-variable
    fork_c = names | 'SendToC' >> beam.Map(f_c)  # pylint: disable=unused-variable

    with self.assertRaises(Exception):
      p.run().wait_until_finish()
    assert count_b == count_c == 4

  def test_no_partial_writeouts(self):
    class TestTransformEvaluator(_TransformEvaluator):
      def __init__(self):
        self._execution_context = _ExecutionContext(None, {})

      def start_bundle(self):
        self.step_context = self._execution_context.get_step_context()

      def process_element(self, element):
        k, v = element
        state = self.step_context.get_keyed_state(k)
        state.add_state(None, _GroupByKeyOnlyEvaluator.ELEMENTS_TAG, v)

    # Create instance and add key/value, key/value2
    evaluator = TestTransformEvaluator()
    evaluator.start_bundle()
    self.assertIsNone(evaluator.step_context.existing_keyed_state.get('key'))
    self.assertIsNone(evaluator.step_context.partial_keyed_state.get('key'))

    evaluator.process_element(['key', 'value'])
    self.assertEqual(
        evaluator.step_context.existing_keyed_state['key'].state,
        defaultdict(lambda: defaultdict(list)))
    self.assertEqual(
        evaluator.step_context.partial_keyed_state['key'].state,
        {None: {
            'elements': ['value']
        }})

    evaluator.process_element(['key', 'value2'])
    self.assertEqual(
        evaluator.step_context.existing_keyed_state['key'].state,
        defaultdict(lambda: defaultdict(list)))
    self.assertEqual(
        evaluator.step_context.partial_keyed_state['key'].state,
        {None: {
            'elements': ['value', 'value2']
        }})

    # Simulate an exception (redo key/value)
    evaluator._execution_context.reset()
    evaluator.start_bundle()
    evaluator.process_element(['key', 'value'])
    self.assertEqual(
        evaluator.step_context.existing_keyed_state['key'].state,
        defaultdict(lambda: defaultdict(list)))
    self.assertEqual(
        evaluator.step_context.partial_keyed_state['key'].state,
        {None: {
            'elements': ['value']
        }})


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