Move exponential histogram tests from integration to unit

Author: rbtz-openai

opentelemetry-sdk/tests/metrics/integration_test/test_console_exporter.py

@@ -16,16 +16,12 @@
 from json import loads
 from unittest import TestCase
 
-from opentelemetry.metrics import Histogram, get_meter, set_meter_provider
+from opentelemetry.metrics import get_meter, set_meter_provider
 from opentelemetry.sdk.metrics import MeterProvider
 from opentelemetry.sdk.metrics.export import (
     ConsoleMetricExporter,
     PeriodicExportingMetricReader,
 )
-from opentelemetry.sdk.metrics.view import (
-    ExponentialBucketHistogramAggregation,
-    View,
-)
 from opentelemetry.test.globals_test import reset_metrics_globals
 
 
@@ -77,56 +73,6 @@ def test_console_exporter(self):
         self.assertEqual(metrics["attributes"], {"a": "b"})
         self.assertEqual(metrics["value"], 1)
 
-    def test_exp_histogram_exporter(self):
-        output = StringIO()
-        exporter = ConsoleMetricExporter(out=output)
-        reader = PeriodicExportingMetricReader(
-            exporter, export_interval_millis=100
-        )
-        provider = MeterProvider(
-            metric_readers=[reader],
-            views=[
-                View(
-                    instrument_type=Histogram,
-                    aggregation=ExponentialBucketHistogramAggregation(),
-                ),
-            ],
-        )
-        set_meter_provider(provider)
-        meter = get_meter(__name__)
-        hist = meter.create_histogram(
-            "name", description="description", unit="unit"
-        )
-        hist.record(1, attributes={"a": "b"})
-        provider.shutdown()
-
-        output.seek(0)
-        result_0 = loads("".join(output.readlines()))
-
-        self.assertGreater(len(result_0), 0)
-
-        metrics = result_0["resource_metrics"][0]["scope_metrics"][0]
-
-        self.assertEqual(metrics["scope"]["name"], "test_console_exporter")
-
-        metrics = metrics["metrics"][0]
-
-        self.assertEqual(metrics["name"], "name")
-        self.assertEqual(metrics["description"], "description")
-        self.assertEqual(metrics["unit"], "unit")
-
-        metrics = metrics["data"]
-
-        self.assertEqual(metrics["aggregation_temporality"], 2)
-        self.assertEqual(len(metrics["data_points"]), 1)
-
-        metrics = metrics["data_points"][0]
-
-        self.assertEqual(metrics["attributes"], {"a": "b"})
-        self.assertEqual(metrics["count"], 1)
-        self.assertEqual(metrics["sum"], 1)
-        self.assertEqual(metrics["zero_count"], 0)
-
     def test_console_exporter_no_export(self):
 
         output = StringIO()

opentelemetry-sdk/tests/metrics/test_point.py

@@ -16,6 +16,9 @@
 
 from opentelemetry.sdk.metrics.export import (
     AggregationTemporality,
+    Buckets,
+    ExponentialHistogram,
+    ExponentialHistogramDataPoint,
     Gauge,
     Histogram,
     HistogramDataPoint,
@@ -100,6 +103,23 @@ def setUpClass(cls):
         )
         cls.histogram_data_point_1_str = f'{{"attributes": {cls.attributes_1_str}, "start_time_unix_nano": 2, "time_unix_nano": 3, "count": 4, "sum": 4.4, "bucket_counts": [2, 1, 1], "explicit_bounds": [1.2, 2.3, 3.4, 4.5], "min": 0.3, "max": 4.4}}'
 
+        cls.exp_histogram_data_point_0 = ExponentialHistogramDataPoint(
+            attributes=cls.attributes_0,
+            start_time_unix_nano=1,
+            time_unix_nano=2,
+            count=1,
+            sum=10,
+            scale=1,
+            zero_count=0,
+            positive=Buckets(offset=0, bucket_counts=[1]),
+            negative=Buckets(offset=0, bucket_counts=[0]),
+            flags=0,
+            min=10,
+            max=10,
+        )
+        cls.exp_histogram_data_point_0_str = f'{{"attributes": {cls.attributes_0_str}, "start_time_unix_nano": 1, "time_unix_nano": 2, "count": 1, "sum": 10, "scale": 1, "zero_count": 0, "positive": {{"offset": 0, "bucket_counts": [1]}}, "negative": {{"offset": 0, "bucket_counts": [0]}}, "flags": 0, "min": 10, "max": 10}}'
+
+
         cls.sum_0 = Sum(
             data_points=[cls.number_data_point_0, cls.number_data_point_1],
             aggregation_temporality=AggregationTemporality.DELTA,
@@ -121,6 +141,15 @@ def setUpClass(cls):
         )
         cls.histogram_0_str = f'{{"data_points": [{cls.histogram_data_point_0_str}, {cls.histogram_data_point_1_str}], "aggregation_temporality": 1}}'
 
+        cls.exp_histogram_0 = ExponentialHistogram(
+            data_points=[
+                cls.exp_histogram_data_point_0,
+            ],
+            aggregation_temporality=AggregationTemporality.CUMULATIVE,
+        )
+        cls.exp_histogram_0_str = f'{{"data_points": [{cls.exp_histogram_data_point_0_str}], "aggregation_temporality": 2}}'
+
+
         cls.metric_0 = Metric(
             name="metric_0",
             description="description_0",
@@ -209,6 +238,15 @@ def test_histogram_data_point(self):
             self.histogram_data_point_1_str,
         )
 
+    def test_exp_histogram_data_point(self):
+
+        self.maxDiff = None
+
+        self.assertEqual(
+            self.exp_histogram_data_point_0.to_json(indent=None),
+            self.exp_histogram_data_point_0_str,
+        )
+
     def test_sum(self):
 
         self.assertEqual(self.sum_0.to_json(indent=None), self.sum_0_str)
@@ -225,6 +263,14 @@ def test_histogram(self):
             self.histogram_0.to_json(indent=None), self.histogram_0_str
         )
 
+    def test_exp_histogram(self):
+
+        self.maxDiff = None
+
+        self.assertEqual(
+            self.exp_histogram_0.to_json(indent=None), self.exp_histogram_0_str
+        )
+
     def test_metric(self):
 
         self.assertEqual(self.metric_0.to_json(indent=None), self.metric_0_str)