# Copyright The OpenTelemetry Authors
#
# Licensed 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.

from platform import system
from time import sleep
from unittest import TestCase

from pytest import mark

from opentelemetry.metrics import NoOpMeterProvider
from opentelemetry.sdk.metrics import Histogram, MeterProvider
from opentelemetry.sdk.metrics.export import (
    AggregationTemporality,
    InMemoryMetricReader,
)
from opentelemetry.sdk.metrics.view import ExplicitBucketHistogramAggregation


class TestExplicitBucketHistogramAggregation(TestCase):
    test_values = [1, 6, 11, 26, 51, 76, 101, 251, 501, 751]

    @mark.skipif(
        system() == "Windows",
        reason=(
            "Tests fail because Windows time_ns resolution is too low so "
            "two different time measurements may end up having the exact same"
            "value."
        ),
    )
    def test_synchronous_delta_temporality(self):
        aggregation = ExplicitBucketHistogramAggregation()

        reader = InMemoryMetricReader(
            preferred_aggregation={Histogram: aggregation},
            preferred_temporality={Histogram: AggregationTemporality.DELTA},
        )

        provider = MeterProvider(metric_readers=[reader])
        # Disable SDK metrics
        # pylint: disable=protected-access
        reader._set_meter_provider(NoOpMeterProvider())
        meter = provider.get_meter("name", "version")

        histogram = meter.create_histogram("histogram")

        results = []

        for _ in range(10):
            results.append(reader.get_metrics_data())

        for metrics_data in results:
            self.assertIsNone(metrics_data)

        results = []

        for test_value in self.test_values:
            histogram.record(test_value)
            results.append(reader.get_metrics_data())

        metric_data = (
            results[0]
            .resource_metrics[0]
            .scope_metrics[0]
            .metrics[0]
            .data.data_points[0]
        )

        previous_time_unix_nano = metric_data.time_unix_nano

        self.assertEqual(
            metric_data.bucket_counts,
            (0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0),
        )

        self.assertLess(
            metric_data.start_time_unix_nano,
            previous_time_unix_nano,
        )
        self.assertEqual(metric_data.min, self.test_values[0])
        self.assertEqual(metric_data.max, self.test_values[0])
        self.assertEqual(metric_data.sum, self.test_values[0])

        for index, metrics_data in enumerate(results[1:]):
            metric_data = (
                metrics_data.resource_metrics[0]
                .scope_metrics[0]
                .metrics[0]
                .data.data_points[0]
            )

            self.assertEqual(
                previous_time_unix_nano, metric_data.start_time_unix_nano
            )
            previous_time_unix_nano = metric_data.time_unix_nano
            self.assertEqual(
                metric_data.bucket_counts,
                # pylint: disable=consider-using-generator
                tuple(
                    [
                        1 if internal_index == index + 2 else 0
                        for internal_index in range(16)
                    ]
                ),
            )
            self.assertLess(
                metric_data.start_time_unix_nano, metric_data.time_unix_nano
            )
            self.assertEqual(metric_data.min, self.test_values[index + 1])
            self.assertEqual(metric_data.max, self.test_values[index + 1])
            self.assertEqual(metric_data.sum, self.test_values[index + 1])

        results = []

        for _ in range(10):
            results.append(reader.get_metrics_data())

        for metrics_data in results:
            self.assertIsNone(metrics_data)

        results = []

        histogram.record(1)
        results.append(reader.get_metrics_data())

        sleep(0.1)
        results.append(reader.get_metrics_data())

        histogram.record(2)
        results.append(reader.get_metrics_data())

        metric_data_0 = (
            results[0]
            .resource_metrics[0]
            .scope_metrics[0]
            .metrics[0]
            .data.data_points[0]
        )
        metric_data_2 = (
            results[2]
            .resource_metrics[0]
            .scope_metrics[0]
            .metrics[0]
            .data.data_points[0]
        )

        self.assertIsNone(results[1])

        self.assertGreater(
            metric_data_2.start_time_unix_nano, metric_data_0.time_unix_nano
        )

        provider.shutdown()

    @mark.skipif(
        system() == "Windows",
        reason=(
            "Tests fail because Windows time_ns resolution is too low so "
            "two different time measurements may end up having the exact same"
            "value."
        ),
    )
    def test_synchronous_cumulative_temporality(self):
        aggregation = ExplicitBucketHistogramAggregation()

        reader = InMemoryMetricReader(
            preferred_aggregation={Histogram: aggregation},
            preferred_temporality={
                Histogram: AggregationTemporality.CUMULATIVE
            },
        )

        provider = MeterProvider(metric_readers=[reader])
        # Disable SDK metrics
        # pylint: disable=protected-access
        reader._set_meter_provider(NoOpMeterProvider())
        meter = provider.get_meter("name", "version")

        histogram = meter.create_histogram("histogram")

        results = []

        for _ in range(10):
            results.append(reader.get_metrics_data())

        for metrics_data in results:
            self.assertIsNone(metrics_data)

        results = []

        for test_value in self.test_values:
            histogram.record(test_value)
            results.append(reader.get_metrics_data())

        start_time_unix_nano = (
            results[0]
            .resource_metrics[0]
            .scope_metrics[0]
            .metrics[0]
            .data.data_points[0]
            .start_time_unix_nano
        )

        for index, metrics_data in enumerate(results):
            metric_data = (
                metrics_data.resource_metrics[0]
                .scope_metrics[0]
                .metrics[0]
                .data.data_points[0]
            )

            self.assertEqual(
                start_time_unix_nano, metric_data.start_time_unix_nano
            )
            self.assertEqual(
                metric_data.bucket_counts,
                # pylint: disable=consider-using-generator
                tuple(
                    [
                        (
                            0
                            if internal_index < 1 or internal_index > index + 1
                            else 1
                        )
                        for internal_index in range(16)
                    ]
                ),
            )
            self.assertEqual(metric_data.min, self.test_values[0])
            self.assertEqual(metric_data.max, self.test_values[index])
            self.assertEqual(
                metric_data.sum, sum(self.test_values[: index + 1])
            )

        results = []

        for _ in range(10):
            results.append(reader.get_metrics_data())

        provider.shutdown()

        start_time_unix_nano = (
            results[0]
            .resource_metrics[0]
            .scope_metrics[0]
            .metrics[0]
            .data.data_points[0]
            .start_time_unix_nano
        )

        for metrics_data in results:
            metric_data = (
                metrics_data.resource_metrics[0]
                .scope_metrics[0]
                .metrics[0]
                .data.data_points[0]
            )

            self.assertEqual(
                start_time_unix_nano, metric_data.start_time_unix_nano
            )
            self.assertEqual(
                metric_data.bucket_counts,
                (0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0),
            )
            self.assertEqual(metric_data.min, self.test_values[0])
            self.assertEqual(metric_data.max, self.test_values[-1])
            self.assertEqual(metric_data.sum, sum(self.test_values))
