Fix pylint errors

Author: fcollonval

opentelemetry-sdk/src/opentelemetry/sdk/metrics/_internal/aggregation.py

@@ -105,7 +105,6 @@ def aggregate(
             measurement: Measurement to aggregate
             should_sample_exemplar: Whether the measurement should be sampled by the exemplars reservoir or not.
         """
-        pass
 
     @abstractmethod
     def collect(

opentelemetry-sdk/src/opentelemetry/sdk/metrics/_internal/exemplar/exemplar_reservoir.py

@@ -107,7 +107,7 @@ def offer(
 
         self.__offered = True
 
-    def collect(self, point_attributes: Attributes) -> Exemplar | None:
+    def collect(self, point_attributes: Attributes) -> Optional[Exemplar]:
         """May return an Exemplar and resets the bucket for the next sampling period."""
         if not self.__offered:
             return None
@@ -232,11 +232,9 @@ def _find_bucket_index(
         Raises:
             BucketIndexError: If no bucket index can be found.
         """
-        pass
 
     def _reset(self) -> None:
         """Reset the reservoir by resetting any stateful logic after a collection cycle."""
-        pass
 
 
 class SimpleFixedSizeExemplarReservoir(FixedSizeExemplarReservoirABC):
@@ -309,9 +307,9 @@ def _find_bucket_index(
         attributes: Attributes,
         context: Context,
     ) -> int:
-        for i, boundary in enumerate(self._boundaries):
+        for index, boundary in enumerate(self._boundaries):
             if value <= boundary:
-                return i
+                return index
         return len(self._boundaries)
 
 

opentelemetry-sdk/src/opentelemetry/sdk/metrics/_internal/view.py

@@ -35,12 +35,12 @@
 
 
 def _default_reservoir_factory(
-    aggregationType: Type[_Aggregation],
+    aggregation_type: Type[_Aggregation],
 ) -> ExemplarReservoirBuilder:
     """Default reservoir factory per aggregation."""
-    if issubclass(aggregationType, _ExplicitBucketHistogramAggregation):
+    if issubclass(aggregation_type, _ExplicitBucketHistogramAggregation):
         return AlignedHistogramBucketExemplarReservoir
-    elif issubclass(aggregationType, _ExponentialBucketHistogramAggregation):
+    if issubclass(aggregation_type, _ExponentialBucketHistogramAggregation):
         return SimpleFixedSizeExemplarReservoir
     return SimpleFixedSizeExemplarReservoir
 

opentelemetry-sdk/tests/metrics/test_aggregation.py

@@ -704,15 +704,12 @@ def test_collection_simple_fixed_size_reservoir_with_default_reservoir(
 
     def test_collection_aligned_histogram_bucket_reservoir(self):
         boundaries = [5.0, 10.0, 20.0]
-        exemplar_reservoir_factory = (
-            lambda: AlignedHistogramBucketExemplarReservoir(boundaries)
-        )
         synchronous_sum_aggregation = _SumAggregation(
             Mock(),
             True,
             AggregationTemporality.DELTA,
             0,
-            exemplar_reservoir_factory,
+            lambda: AlignedHistogramBucketExemplarReservoir(boundaries),
         )
 
         synchronous_sum_aggregation.aggregate(measurement(2.0))

opentelemetry-sdk/tests/metrics/test_view_instrument_match.py

@@ -52,18 +52,18 @@ def generalized_reservoir_factory(
     size: int = 1, boundaries: Sequence[float] = None
 ) -> Callable[[Type[_Aggregation]], ExemplarReservoirBuilder]:
     def factory(
-        aggregationType: Type[_Aggregation],
+        aggregation_type: Type[_Aggregation],
     ) -> ExemplarReservoirBuilder:
-        if issubclass(aggregationType, _ExplicitBucketHistogramAggregation):
+        if issubclass(aggregation_type, _ExplicitBucketHistogramAggregation):
             return lambda **kwargs: AlignedHistogramBucketExemplarReservoir(
                 boundaries=boundaries or [],
                 **{k: v for k, v in kwargs.items() if k != "boundaries"},
             )
-        else:
-            return lambda **kwargs: SimpleFixedSizeExemplarReservoir(
-                size=size,
-                **{k: v for k, v in kwargs.items() if k != "size"},
-            )
+
+        return lambda **kwargs: SimpleFixedSizeExemplarReservoir(
+            size=size,
+            **{k: v for k, v in kwargs.items() if k != "size"},
+        )
 
     return factory
 
@@ -288,7 +288,11 @@ def test_collect_resets_start_time_unix_nano(self, mock_time_ns):
         # +1 call to _create_aggregation
         view_instrument_match.consume_measurement(
             Measurement(
-                value=0, instrument=instrument, attributes={"foo": "bar0"}
+                value=0,
+                time_unix_nano=time_ns(),
+                instrument=instrument,
+                attributes={"foo": "bar0"},
+                context=Context(),
             )
         )
         view_instrument_match._view._aggregation._create_aggregation.assert_called_with(
@@ -304,7 +308,11 @@ def test_collect_resets_start_time_unix_nano(self, mock_time_ns):
         # +1 call to _create_aggregation
         view_instrument_match.consume_measurement(
             Measurement(
-                value=0, instrument=instrument, attributes={"foo": "bar1"}
+                value=0,
+                time_unix_nano=time_ns(),
+                instrument=instrument,
+                attributes={"foo": "bar1"},
+                context=Context(),
             )
         )
         view_instrument_match._view._aggregation._create_aggregation.assert_called_with(
@@ -322,7 +330,11 @@ def test_collect_resets_start_time_unix_nano(self, mock_time_ns):
         # +1 call to create_aggregation
         view_instrument_match.consume_measurement(
             Measurement(
-                value=0, instrument=instrument, attributes={"foo": "bar"}
+                value=0,
+                time_unix_nano=time_ns(),
+                instrument=instrument,
+                attributes={"foo": "bar"},
+                context=Context(),
             )
         )
         view_instrument_match._view._aggregation._create_aggregation.assert_called_with(
@@ -331,12 +343,20 @@ def test_collect_resets_start_time_unix_nano(self, mock_time_ns):
         # No new calls to _create_aggregation because attributes remain the same
         view_instrument_match.consume_measurement(
             Measurement(
-                value=0, instrument=instrument, attributes={"foo": "bar"}
+                value=0,
+                time_unix_nano=time_ns(),
+                instrument=instrument,
+                attributes={"foo": "bar"},
+                context=Context(),
             )
         )
         view_instrument_match.consume_measurement(
             Measurement(
-                value=0, instrument=instrument, attributes={"foo": "bar"}
+                value=0,
+                time_unix_nano=time_ns(),
+                instrument=instrument,
+                attributes={"foo": "bar"},
+                context=Context(),
             )
         )
         # In total we have 5 calls for _create_aggregation
@@ -520,8 +540,8 @@ def test_consume_measurement_with_custom_reservoir_factory(self):
             )
         )
 
-        data_points = view_instrument_match.collect(
-            AggregationTemporality.CUMULATIVE, 0
+        data_points = list(
+            view_instrument_match.collect(AggregationTemporality.CUMULATIVE, 0)
         )
 
         # Ensure only one data point is collected
@@ -577,8 +597,8 @@ def test_consume_measurement_with_exemplars(self):
         )
 
         # Collect the data points
-        data_points = view_instrument_match.collect(
-            AggregationTemporality.CUMULATIVE, 0
+        data_points = list(
+            view_instrument_match.collect(AggregationTemporality.CUMULATIVE, 0)
         )
 
         # Ensure only one data point is collected
@@ -660,19 +680,9 @@ def test_consume_measurement_with_custom_reservoir_factory(self):
             )
         )
 
-        # view_instrument_match.consume_measurement(
-        #     Measurement(
-        #         value=30.0,  # Should go into the outliners bucket
-        #         time_unix_nano=time_ns(),
-        #         instrument=instrument1,
-        #         context=Context(),
-        #         attributes={"attribute3": "value3"},
-        #     )
-        # )
-
         # Collect the data points
-        data_points = view_instrument_match.collect(
-            AggregationTemporality.CUMULATIVE, 0
+        data_points = list(
+            view_instrument_match.collect(AggregationTemporality.CUMULATIVE, 0)
         )
 
         # Ensure three data points are collected, one for each bucket
@@ -692,4 +702,3 @@ def test_consume_measurement_with_custom_reservoir_factory(self):
         self.assertEqual(
             data_points[2].exemplars[0].value, 15.0
         )  # Third bucket
-        # self.assertEqual(data_points[2].exemplars[0].value, 30.0)  # Outliner bucket