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Merge branch 'main' into issue_3198
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‎CHANGELOG.md

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@@ -53,6 +53,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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([#3223](https://github.com/open-telemetry/opentelemetry-python/pull/3223))
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- Add speced out environment variables and arguments for BatchLogRecordProcessor
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([#3237](https://github.com/open-telemetry/opentelemetry-python/pull/3237))
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- Add benchmark tests for metrics
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([#3267](https://github.com/open-telemetry/opentelemetry-python/pull/3267))
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## Version 1.17.0/0.38b0 (2023-03-22)

‎opentelemetry-api/pyproject.toml

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@@ -28,7 +28,7 @@ dependencies = [
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"Deprecated >= 1.2.6",
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# FIXME This should be able to be removed after 3.12 is released if there is a reliable API
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# in importlib.metadata.
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"importlib-metadata ~= 6.0",
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"importlib-metadata >= 6.0",
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]
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dynamic = [
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"version",

‎opentelemetry-sdk/tests/performance/benchmarks/metrics/test_benchmark_metrics.py

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# Copyright The OpenTelemetry Authors
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import pytest
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from opentelemetry.sdk.metrics import Counter, MeterProvider
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from opentelemetry.sdk.metrics.export import (
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AggregationTemporality,
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InMemoryMetricReader,
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)
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reader_cumulative = InMemoryMetricReader()
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reader_delta = InMemoryMetricReader(
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preferred_temporality={
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Counter: AggregationTemporality.DELTA,
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},
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)
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provider_reader_cumulative = MeterProvider(
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metric_readers=[reader_cumulative],
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)
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provider_reader_delta = MeterProvider(metric_readers=[reader_delta])
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meter_cumulative = provider_reader_cumulative.get_meter("sdk_meter_provider")
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meter_delta = provider_reader_delta.get_meter("sdk_meter_provider_delta")
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counter_cumulative = meter_cumulative.create_counter("test_counter")
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counter_delta = meter_delta.create_counter("test_counter2")
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udcounter = meter_cumulative.create_up_down_counter("test_udcounter")
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@pytest.mark.parametrize(
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("num_labels", "temporality"),
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[
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(0, "delta"),
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(1, "delta"),
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(3, "delta"),
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(5, "delta"),
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(10, "delta"),
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(0, "cumulative"),
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(1, "cumulative"),
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(3, "cumulative"),
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(5, "cumulative"),
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(10, "cumulative"),
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],
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)
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def test_counter_add(benchmark, num_labels, temporality):
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labels = {}
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for i in range(num_labels):
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labels = {f"Key{i}": f"Value{i}" for i in range(num_labels)}
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def benchmark_counter_add():
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if temporality == "cumulative":
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counter_cumulative.add(1, labels)
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else:
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counter_delta.add(1, labels)
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benchmark(benchmark_counter_add)
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@pytest.mark.parametrize("num_labels", [0, 1, 3, 5, 10])
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def test_up_down_counter_add(benchmark, num_labels):
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labels = {}
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for i in range(num_labels):
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labels = {f"Key{i}": f"Value{i}" for i in range(num_labels)}
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def benchmark_up_down_counter_add():
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udcounter.add(1, labels)
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benchmark(benchmark_up_down_counter_add)

‎opentelemetry-sdk/tests/performance/benchmarks/metrics/test_benchmark_metrics_histogram,.py

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# Copyright The OpenTelemetry Authors
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import random
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import pytest
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from opentelemetry.sdk.metrics import MeterProvider
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from opentelemetry.sdk.metrics.export import InMemoryMetricReader
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from opentelemetry.sdk.metrics.view import (
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ExplicitBucketHistogramAggregation,
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View,
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)
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MAX_BOUND_VALUE = 10000
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def _generate_bounds(bound_count):
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bounds = []
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for i in range(bound_count):
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bounds.append(i * MAX_BOUND_VALUE / bound_count)
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return bounds
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hist_view_10 = View(
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instrument_name="test_histogram_10_bound",
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aggregation=ExplicitBucketHistogramAggregation(_generate_bounds(10)),
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)
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hist_view_49 = View(
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instrument_name="test_histogram_49_bound",
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aggregation=ExplicitBucketHistogramAggregation(_generate_bounds(49)),
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)
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hist_view_50 = View(
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instrument_name="test_histogram_50_bound",
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aggregation=ExplicitBucketHistogramAggregation(_generate_bounds(50)),
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)
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hist_view_1000 = View(
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instrument_name="test_histogram_1000_bound",
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aggregation=ExplicitBucketHistogramAggregation(_generate_bounds(1000)),
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)
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reader = InMemoryMetricReader()
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provider = MeterProvider(
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metric_readers=[reader],
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views=[
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hist_view_10,
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hist_view_49,
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hist_view_50,
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hist_view_1000,
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],
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)
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meter = provider.get_meter("sdk_meter_provider")
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hist = meter.create_histogram("test_histogram_default")
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hist10 = meter.create_histogram("test_histogram_10_bound")
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hist49 = meter.create_histogram("test_histogram_49_bound")
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hist50 = meter.create_histogram("test_histogram_50_bound")
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hist1000 = meter.create_histogram("test_histogram_1000_bound")
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@pytest.mark.parametrize("num_labels", [0, 1, 3, 5, 7])
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def test_histogram_record(benchmark, num_labels):
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labels = {}
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for i in range(num_labels):
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labels["Key{}".format(i)] = "Value{}".format(i)
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def benchmark_histogram_record():
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hist.record(random.random() * MAX_BOUND_VALUE)
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benchmark(benchmark_histogram_record)
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@pytest.mark.parametrize("num_labels", [0, 1, 3, 5, 7])
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def test_histogram_record_10(benchmark, num_labels):
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labels = {}
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for i in range(num_labels):
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labels["Key{}".format(i)] = "Value{}".format(i)
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def benchmark_histogram_record_10():
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hist10.record(random.random() * MAX_BOUND_VALUE)
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benchmark(benchmark_histogram_record_10)
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@pytest.mark.parametrize("num_labels", [0, 1, 3, 5, 7])
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def test_histogram_record_49(benchmark, num_labels):
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labels = {}
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for i in range(num_labels):
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labels["Key{}".format(i)] = "Value{}".format(i)
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def benchmark_histogram_record_49():
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hist49.record(random.random() * MAX_BOUND_VALUE)
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benchmark(benchmark_histogram_record_49)
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@pytest.mark.parametrize("num_labels", [0, 1, 3, 5, 7])
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def test_histogram_record_50(benchmark, num_labels):
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labels = {}
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for i in range(num_labels):
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labels["Key{}".format(i)] = "Value{}".format(i)
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def benchmark_histogram_record_50():
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hist50.record(random.random() * MAX_BOUND_VALUE)
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benchmark(benchmark_histogram_record_50)
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@pytest.mark.parametrize("num_labels", [0, 1, 3, 5, 7])
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def test_histogram_record_1000(benchmark, num_labels):
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labels = {}
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for i in range(num_labels):
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labels["Key{}".format(i)] = "Value{}".format(i)
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def benchmark_histogram_record_1000():
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hist1000.record(random.random() * MAX_BOUND_VALUE)
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benchmark(benchmark_histogram_record_1000)

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