finish the metrics logger implementation

Author: jaredcnance

aws_embedded_metrics/logger/metrics_context.py

@@ -21,6 +21,7 @@ def __init__(
         self.dimensions: List[Dict[str, str]] = dimensions or []
         self.default_dimensions: Dict[str, str] = default_dimensions or {}
         self.metrics: Dict[str, Metric] = {}
+        self.should_use_default_dimensions = True
 
     def put_metric(self, key: str, value: float, unit: str = None) -> None:
         """
@@ -38,24 +39,18 @@ def put_metric(self, key: str, value: float, unit: str = None) -> None:
         else:
             self.metrics[key] = Metric(value, unit)
 
-    def put_dimension(self, dimensions: Dict[str, str]) -> None:
+    def put_dimensions(self, dimensions: Dict[str, str]) -> None:
         """
         Adds dimensions to the context.
         ```
-        context.put_dimension({ "k1": "v1", "k2": "v2" })
+        context.put_dimensions({ "k1": "v1", "k2": "v2" })
         ```
         """
         if dimensions is None:
             # TODO add ability to define failure strategy
             return
 
-        if self.__has_default_dimensions():
-            merged_dimensions: Dict = {}
-            merged_dimensions.update(self.default_dimensions)
-            merged_dimensions.update(dimensions)
-            self.dimensions.append(merged_dimensions)
-        else:
-            self.dimensions.append(dimensions)
+        self.dimensions.append(dimensions)
 
     def set_dimensions(self, dimensionSets: List[Dict[str, str]]) -> None:
         """
@@ -66,6 +61,7 @@ def set_dimensions(self, dimensionSets: List[Dict[str, str]]) -> None:
             { "k1": "v1", "k2": "v2" }])
         ```
         """
+        self.should_use_default_dimensions = False
         self.dimensions = dimensionSets
 
     def set_default_dimensions(self, default_dimensions: Dict) -> None:
@@ -86,13 +82,23 @@ def get_dimensions(self) -> List[Dict]:
         """
         Returns the current dimensions on the context
         """
+        # user has directly called set_dimensions
+        if not self.should_use_default_dimensions:
+            return self.dimensions
+
         if not self.__has_default_dimensions():
             return self.dimensions
 
         if len(self.dimensions) == 0:
             return [self.default_dimensions]
 
-        return self.dimensions
+        # we have to merge dimensions on the read path
+        # because defaults won't actually get set until the flush
+        # method is called. This allows us to not block the user
+        # code while we're detecting the environment
+        return list(
+            map(lambda custom: {**self.default_dimensions, **custom}, self.dimensions)
+        )
 
     def __has_default_dimensions(self) -> bool:
         return self.default_dimensions is not None and len(self.default_dimensions) > 0

aws_embedded_metrics/logger/metrics_logger.py

@@ -2,6 +2,7 @@
 from aws_embedded_metrics.environment.environment_provider import EnvironmentProvider
 from aws_embedded_metrics.logger.metrics_context import MetricsContext
 from aws_embedded_metrics.config import get_config
+from typing import Any, Dict
 
 Config = get_config()
 
@@ -31,9 +32,28 @@ def __configureContextForEnvironment(self, env: Environment) -> None:
         default_dimensions = {
             # LogGroup name will entirely depend on the environment since there
             # are some cases where the LogGroup cannot be configured (e.g. Lambda)
-            "log_group": env.get_log_group_name(),
-            "service_name": Config.service_name or env.get_name(),
-            "service_type": Config.service_type or env.get_type(),
+            "LogGroup": env.get_log_group_name(),
+            "ServiceName": Config.service_name or env.get_name(),
+            "ServiceType": Config.service_type or env.get_type(),
         }
         self.context.set_default_dimensions(default_dimensions)
         env.configure_context(self.context)
+
+    def set_property(self, key: str, value: Any) -> "MetricsLogger":
+        self.context.set_property(key, value)
+        return self
+
+    def put_dimensions(self, dimensions: Dict[str, str]) -> "MetricsLogger":
+        self.context.put_dimensions(dimensions)
+        return self
+
+    def set_dimensions(self, *dimensions: Dict[str, str]) -> "MetricsLogger":
+        self.context.set_dimensions(list(dimensions))
+        return self
+
+    def put_metric(self, key: str, value: float, unit: str = "None") -> "MetricsLogger":
+        self.context.put_metric(key, value, unit)
+        return self
+
+    def new(self) -> "MetricsLogger":
+        return MetricsLogger(self.env_provider, self.context.create_copy_with_context())

tests/config/test_config.py

@@ -2,22 +2,11 @@
 from faker import Faker
 import os
 from importlib import reload
-import pytest
 
 
 fake = Faker()
 
 
-@pytest.fixture
-def before(self):
-    os.environ["AWS_EMF_ENABLE_DEBUG_LOGGING"] = None
-    os.environ["AWS_EMF_SERVICE_NAME"] = None
-    os.environ["AWS_EMF_SERVICE_TYPE"] = None
-    os.environ["AWS_EMF_LOG_GROUP_NAME"] = None
-    os.environ["AWS_EMF_LOG_STREAM_NAME"] = None
-    os.environ["AWS_EMF_AGENT_ENDPOINT"] = None
-
-
 def get_config():
     # reload the configuration module since it is loaded on
     # startup and cached

tests/logger/test_metrics_context.py

@@ -3,6 +3,7 @@
 from _pytest.monkeypatch import MonkeyPatch
 import pytest
 from faker import Faker
+
 fake = Faker()
 
 
@@ -37,8 +38,7 @@ def test_can_set_property(mock_time):
     context.properties[property_key] = property_value
 
     # assert
-    assert context.properties == {
-        "Timestamp": mock_time, property_key: property_value}
+    assert context.properties == {"Timestamp": mock_time, property_key: property_value}
 
 
 def test_put_dimension_adds_to_dimensions(mock_time):
@@ -49,7 +49,7 @@ def test_put_dimension_adds_to_dimensions(mock_time):
     dimension_value = fake.word()
 
     # act
-    context.put_dimension({dimension_key:  dimension_value})
+    context.put_dimensions({dimension_key: dimension_value})
 
     # assert
     assert context.dimensions == [{dimension_key: dimension_value}]
@@ -60,10 +60,10 @@ def test_get_dimensions_returns_only_custom_dimensions_if_no_default_dimensions_
     context = MetricsContext()
     dimension_key = fake.word()
     dimension_value = fake.word()
-    expected_dimensions = {dimension_key:  dimension_value}
+    expected_dimensions = {dimension_key: dimension_value}
 
     context.set_default_dimensions(None)
-    context.put_dimension(expected_dimensions)
+    context.put_dimensions(expected_dimensions)
 
     # act
     actual_dimensions = context.get_dimensions()
@@ -77,10 +77,10 @@ def test_get_dimensions_returns_only_custom_dimensions_if_default_dimensions_are
     context = MetricsContext()
     dimension_key = fake.word()
     dimension_value = fake.word()
-    expected_dimensions = {dimension_key:  dimension_value}
+    expected_dimensions = {dimension_key: dimension_value}
 
     context.set_default_dimensions({})
-    context.put_dimension(expected_dimensions)
+    context.put_dimensions(expected_dimensions)
 
     # act
     actual_dimensions = context.get_dimensions()
@@ -94,7 +94,7 @@ def test_get_dimensions_returns_default_dimensions_if_custom_dimensions_not_set(
     context = MetricsContext()
     dimension_key = fake.word()
     dimension_value = fake.word()
-    expected_dimensions = {dimension_key:  dimension_value}
+    expected_dimensions = {dimension_key: dimension_value}
     context.set_default_dimensions(expected_dimensions)
 
     # act
@@ -113,12 +113,13 @@ def test_get_dimensions_returns_merged_custom_and_default_dimensions():
     default_dimension_key = fake.word()
     default_dimension_value = fake.word()
 
-    expected_dimensions = {default_dimension_key: default_dimension_value,
-                           custom_dimension_key:  custom_dimension_value}
+    expected_dimensions = {
+        default_dimension_key: default_dimension_value,
+        custom_dimension_key: custom_dimension_value,
+    }
 
-    context.set_default_dimensions(
-        {default_dimension_key: default_dimension_value})
-    context.put_dimension({custom_dimension_key: custom_dimension_value})
+    context.set_default_dimensions({default_dimension_key: default_dimension_value})
+    context.put_dimensions({custom_dimension_key: custom_dimension_value})
 
     # act
     actual_dimensions = context.get_dimensions()
@@ -154,7 +155,7 @@ def test_put_metric_uses_None_unit_if_not_provided():
 
     # assert
     metric = context.metrics[metric_key]
-    assert metric.unit == 'None'
+    assert metric.unit == "None"
 
 
 def test_create_copy_with_context_creates_new_instance():
@@ -200,7 +201,7 @@ def test_create_copy_with_context_copies_dimensions():
     context = MetricsContext()
     dimension_key = fake.word()
     dimension_value = fake.word()
-    context.put_dimension({dimension_key: dimension_value})
+    context.put_dimensions({dimension_key: dimension_value})
 
     # act
     new_context = context.create_copy_with_context()
@@ -227,7 +228,7 @@ def test_set_dimensions_overwrites_all_dimensions():
     # arrange
     context = MetricsContext()
     context.set_default_dimensions({fake.word(): fake.word})
-    context.put_dimension({fake.word(): fake.word})
+    context.put_dimensions({fake.word(): fake.word})
 
     expected_dimensions = {fake.word(): fake.word}