feat: emf multiple metric values (#167)

* feat: Update metrics to allow multiple values for a single metric

* chore: update test comments

* chore: fix type hint

* chore: type hint update

* chore: update CHANGELOG

Author: Tom McCarthy

Diff for: CHANGELOG.md

@@ -7,6 +7,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ## [Unreleased]
 
 ### Added
+- **Metrics**: Support adding multiple metric values to a metric name
 - **Utilities**: Add new `Validator` utility to validate inbound events and responses using JSON Schema
 
 ## [1.5.0] - 2020-09-04

Diff for: aws_lambda_powertools/metrics/base.py

@@ -4,6 +4,7 @@
 import numbers
 import os
 import pathlib
+from collections import defaultdict
 from enum import Enum
 from typing import Any, Dict, List, Union
 
@@ -93,7 +94,7 @@ def __init__(
         self._metric_unit_options = list(MetricUnit.__members__)
         self.metadata_set = self.metadata_set if metadata_set is not None else {}
 
-    def add_metric(self, name: str, unit: MetricUnit, value: Union[float, int]):
+    def add_metric(self, name: str, unit: Union[MetricUnit, str], value: float):
         """Adds given metric
 
         Example
@@ -110,9 +111,9 @@ def add_metric(self, name: str, unit: MetricUnit, value: Union[float, int]):
         ----------
         name : str
             Metric name
-        unit : MetricUnit
+        unit : Union[MetricUnit, str]
             `aws_lambda_powertools.helper.models.MetricUnit`
-        value : Union[float, int]
+        value : float
             Metric value
 
         Raises
@@ -124,7 +125,9 @@ def add_metric(self, name: str, unit: MetricUnit, value: Union[float, int]):
             raise MetricValueError(f"{value} is not a valid number")
 
         unit = self.__extract_metric_unit_value(unit=unit)
-        metric = {"Unit": unit, "Value": float(value)}
+        metric = self.metric_set.get(name, defaultdict(list))
+        metric["Unit"] = unit
+        metric["Value"].append(float(value))
         logger.debug(f"Adding metric: {name} with {metric}")
         self.metric_set[name] = metric
 

Diff for: tests/functional/test_metrics.py

@@ -32,6 +32,14 @@ def metrics() -> List[Dict[str, str]]:
     ]
 
 
+@pytest.fixture
+def metrics_same_name() -> List[Dict[str, str]]:
+    return [
+        {"name": "metric_one", "unit": MetricUnit.Count, "value": 1},
+        {"name": "metric_one", "unit": MetricUnit.Count, "value": 5},
+    ]
+
+
 @pytest.fixture
 def dimension() -> Dict[str, str]:
     return {"name": "test_dimension", "value": "test"}
@@ -485,7 +493,7 @@ def lambda_handler(evt, context):
     output = capture_metrics_output(capsys)
 
     # THEN ColdStart metric and function_name dimension should be logged
-    assert output["ColdStart"] == 1
+    assert output["ColdStart"] == [1.0]
     assert output["function_name"] == "example_fn"
 
 
@@ -607,7 +615,7 @@ def lambda_handler(evt, ctx):
 
 def test_serialize_metric_set_metric_definition(metric, dimension, namespace, service, metadata):
     expected_metric_definition = {
-        "single_metric": 1.0,
+        "single_metric": [1.0],
         "_aws": {
             "Timestamp": 1592237875494,
             "CloudWatchMetrics": [
@@ -655,7 +663,7 @@ def lambda_handler(evt, context):
 
     # THEN ColdStart metric and function_name dimension should be logged
     # in a separate EMF blob than the application metrics
-    assert cold_start_blob["ColdStart"] == 1
+    assert cold_start_blob["ColdStart"] == [1.0]
     assert cold_start_blob["function_name"] == "example_fn"
     assert cold_start_blob["service"] == service
 
@@ -669,5 +677,65 @@ def lambda_handler(evt, context):
 
     # and that application metrics are recorded as normal
     assert custom_metrics_blob["service"] == service
-    assert custom_metrics_blob["single_metric"] == metric["value"]
+    assert custom_metrics_blob["single_metric"] == [float(metric["value"])]
     assert custom_metrics_blob["test_dimension"] == dimension["value"]
+
+
+def test_log_multiple_metrics(capsys, metrics_same_name, dimensions, namespace):
+    # GIVEN Metrics is initialized
+    my_metrics = Metrics(namespace=namespace)
+
+    for dimension in dimensions:
+        my_metrics.add_dimension(**dimension)
+
+    # WHEN we utilize log_metrics to serialize
+    # and flush multiple metrics with the same name at the end of a function execution
+    @my_metrics.log_metrics
+    def lambda_handler(evt, ctx):
+        for metric in metrics_same_name:
+            my_metrics.add_metric(**metric)
+
+    lambda_handler({}, {})
+    output = capture_metrics_output(capsys)
+    expected = serialize_metrics(metrics=metrics_same_name, dimensions=dimensions, namespace=namespace)
+
+    # THEN we should have no exceptions
+    # and a valid EMF object should be flushed correctly
+    remove_timestamp(metrics=[output, expected])
+    assert expected == output
+
+
+def test_serialize_metric_set_metric_definition_multiple_values(
+    metrics_same_name, dimension, namespace, service, metadata
+):
+    expected_metric_definition = {
+        "metric_one": [1.0, 5.0],
+        "_aws": {
+            "Timestamp": 1592237875494,
+            "CloudWatchMetrics": [
+                {
+                    "Namespace": "test_namespace",
+                    "Dimensions": [["test_dimension", "service"]],
+                    "Metrics": [{"Name": "metric_one", "Unit": "Count"}],
+                }
+            ],
+        },
+        "service": "test_service",
+        "username": "test",
+        "test_dimension": "test",
+    }
+
+    # GIVEN Metrics is initialized and multiple metrics are added with the same name
+    my_metrics = Metrics(service=service, namespace=namespace)
+    for metric in metrics_same_name:
+        my_metrics.add_metric(**metric)
+    my_metrics.add_dimension(**dimension)
+    my_metrics.add_metadata(**metadata)
+
+    # WHEN metrics are serialized manually
+    metric_definition_output = my_metrics.serialize_metric_set()
+
+    # THEN we should emit a valid embedded metric definition object
+    assert "Timestamp" in metric_definition_output["_aws"]
+    remove_timestamp(metrics=[metric_definition_output, expected_metric_definition])
+    assert metric_definition_output == expected_metric_definition