[WIP] Views API Prototype

docs/examples/basic_meter/basic_metrics.py

@@ -19,6 +19,7 @@
 - How to configure a meter passing a sateful or stateless.
 - How to configure an exporter and how to create a controller.
 - How to create some metrics intruments and how to capture data with them.
+- How to use views to specify aggregation types for each metric instrument.
 """
 import sys
 import time
@@ -56,7 +57,7 @@ def usage(argv):
 # over the process lifetime. If false, metrics are reset at the beginning of
 # each collection interval.
 metrics.set_meter_provider(MeterProvider())
-meter = metrics.get_meter(__name__, batcher_mode == "stateful")
+meter = metrics.get_meter(__name__, stateful)
 
 # Exporter to export metrics to the console
 exporter = ConsoleMetricsExporter()
@@ -72,7 +73,6 @@ def usage(argv):
     unit="1",
     value_type=int,
     metric_type=Counter,
-    label_keys=("environment",),
 )
 
 requests_size = meter.create_metric(
@@ -81,7 +81,6 @@ def usage(argv):
     unit="1",
     value_type=int,
     metric_type=Measure,
-    label_keys=("environment",),
 )
 
 # Labels are used to identify key-values that are associated with a specific
@@ -101,4 +100,5 @@ def usage(argv):
 
 requests_counter.add(35, testing_labels)
 requests_size.record(2, testing_labels)
-time.sleep(5)
+
+input("...\n")

docs/examples/basic_meter/calling_conventions.py

@@ -19,9 +19,11 @@
 import time
 
 from opentelemetry import metrics
-from opentelemetry.sdk.metrics import Counter, Measure, MeterProvider
+from opentelemetry.sdk.metrics import Counter, MeterProvider
+from opentelemetry.sdk.metrics.export.aggregate import CountAggregation
 from opentelemetry.sdk.metrics.export import ConsoleMetricsExporter
 from opentelemetry.sdk.metrics.export.controller import PushController
+from opentelemetry.sdk.metrics.view import View
 
 # Use the meter type provided by the SDK package
 metrics.set_meter_provider(MeterProvider())
@@ -35,16 +37,6 @@
     unit="1",
     value_type=int,
     metric_type=Counter,
-    label_keys=("environment",),
-)
-
-requests_size = meter.create_metric(
-    name="requests_size",
-    description="size of requests",
-    unit="1",
-    value_type=int,
-    metric_type=Measure,
-    label_keys=("environment",),
 )
 
 clicks_counter = meter.create_metric(
@@ -53,11 +45,18 @@
     unit="1",
     value_type=int,
     metric_type=Counter,
-    label_keys=("environment",),
 )
 
 labels = {"environment": "staging"}
 
+# Views are used to define an aggregation type to use for a specific metric
+counter_view = View(requests_counter, CountAggregation())
+clicks_view = View(clicks_counter, CountAggregation())
+
+# Register the views to the view manager to use the views
+meter.register_view(counter_view)
+meter.register_view(clicks_view)
+
 print("Updating using direct calling convention...")
 # You can record metrics directly using the metric instrument. You pass in
 # labels that you would like to record for.
@@ -80,3 +79,5 @@
 # specified labels for each.
 meter.record_batch(labels, ((requests_counter, 50), (clicks_counter, 70)))
 time.sleep(5)
+
+input("...\n")

docs/examples/basic_meter/observer.py

@@ -21,11 +21,8 @@
 from opentelemetry import metrics
 from opentelemetry.sdk.metrics import MeterProvider
 from opentelemetry.sdk.metrics.export import ConsoleMetricsExporter
-from opentelemetry.sdk.metrics.export.batcher import UngroupedBatcher
 from opentelemetry.sdk.metrics.export.controller import PushController
 
-# Configure a stateful batcher
-batcher = UngroupedBatcher(stateful=True)
 metrics.set_meter_provider(MeterProvider())
 meter = metrics.get_meter(__name__)
 exporter = ConsoleMetricsExporter()
@@ -45,7 +42,6 @@ def get_cpu_usage_callback(observer):
     description="per-cpu usage",
     unit="1",
     value_type=float,
-    label_keys=("cpu_number",),
 )
 
 
@@ -61,7 +57,6 @@ def get_ram_usage_callback(observer):
     description="RAM memory usage",
     unit="1",
     value_type=float,
-    label_keys=(),
 )
 
 input("Metrics will be printed soon. Press a key to finish...\n")

opentelemetry-api/src/opentelemetry/metrics/__init__.py

@@ -291,7 +291,6 @@ def create_metric(
         unit: str,
         value_type: Type[ValueT],
         metric_type: Type[MetricT],
-        label_keys: Sequence[str] = (),
         enabled: bool = True,
     ) -> "Metric":
         """Creates a ``metric_kind`` metric with type ``value_type``.
@@ -303,7 +302,6 @@ def create_metric(
                 (https://unitsofmeasure.org/ucum.html).
             value_type: The type of values being recorded by the metric.
             metric_type: The type of metric being created.
-            label_keys: The keys for the labels with dynamic values.
             enabled: Whether to report the metric by default.
         Returns: A new ``metric_type`` metric with values of ``value_type``.
         """