Merge branch 'develop'

* develop:
  chore: plat wheels are not needed
  Fix Logger value coercion to main keys (#53)
  fix: cast dimension value to str to avoid issue where EMF silently fails (#52)

Author: heitorlessa

CHANGELOG.md

@@ -6,6 +6,11 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+## [0.9.5] - 2020-06-02
+### Fixed
+- **Metrics**: Coerce non-string dimension values to string
+- **Logger**: Correct `cold_start`, `function_memory_size` values from string to bool and int respectively
+
 ## [0.9.4] - 2020-05-29
 ### Fixed
 - **Metrics**: Fix issue where metrics were not correctly flushed, and cleared on every invocation

Makefile

@@ -70,12 +70,7 @@ release-test:
 	poetry config pypi-token.pypi ${PYPI_TEST_TOKEN}
 	poetry publish --repository testpypi -n
 
-build-linux-wheels:
+release: pr
 	poetry build
-	docker run --env PLAT=manylinux1_x86_64 --rm -it -v ${PWD}:/io -w /io quay.io/pypa/manylinux1_x86_64 /io/build_linux_wheels.sh
-	cp ./wheelhouse/* dist/ && rm -rf wheelhouse
-
-release:
-	$(MAKE) build-linux-wheels
 	$(MAKE) release-test
 	$(MAKE) release-prod

aws_lambda_powertools/helper/models.py

@@ -65,7 +65,7 @@ def build_lambda_context_model(context: object) -> LambdaContextModel:
 
     context = {
         "function_name": context.function_name,
-        "function_memory_size": str(context.memory_limit_in_mb),
+        "function_memory_size": context.memory_limit_in_mb,
         "function_arn": context.invoked_function_arn,
         "function_request_id": context.aws_request_id,
     }

aws_lambda_powertools/logging/logger.py

@@ -62,6 +62,7 @@ def __init__(self, **kwargs):
         datefmt = kwargs.pop("datefmt", None)
 
         super(JsonFormatter, self).__init__(datefmt=datefmt)
+        self.reserved_keys = ["timestamp", "level", "location"]
         self.format_dict = {
             "timestamp": "%(asctime)s",
             "level": "%(levelname)s",
@@ -76,10 +77,12 @@ def format(self, record):  # noqa: A003
 
         log_dict = {}
         for key, value in self.format_dict.items():
-            if value:
+            if value and key in self.reserved_keys:
                 # converts default logging expr to its record value
                 # e.g. '%(asctime)s' to '2020-04-24 09:35:40,698'
                 log_dict[key] = value % record_dict
+            else:
+                log_dict[key] = value
 
         if isinstance(record_dict["msg"], dict):
             log_dict["message"] = record_dict["msg"]
@@ -149,20 +152,19 @@ def handler(evt, ctx):
     raise DeprecationWarning("Use Logger instead - This method will be removed when GA")
 
 
-def _is_cold_start() -> str:
-    """Verifies whether is cold start and return a string used for struct logging
+def _is_cold_start() -> bool:
+    """Verifies whether is cold start
 
     Returns
     -------
-    str
-        lower case bool as a string
-        aws_lambda_logging doesn't support bool; cast cold start value to string
+    bool
+        cold start bool value
     """
-    cold_start = "false"
+    cold_start = False
 
     global is_cold_start
     if is_cold_start:
-        cold_start = str(is_cold_start).lower()
+        cold_start = is_cold_start
         is_cold_start = False
 
     return cold_start

aws_lambda_powertools/metrics/base.py

@@ -203,7 +203,14 @@ def add_dimension(self, name: str, value: str):
             Dimension value
         """
         logger.debug(f"Adding dimension: {name}:{value}")
-        self.dimension_set[name] = value
+
+        # Cast value to str according to EMF spec
+        # Majority of values are expected to be string already, so
+        # checking before casting improves performance in most cases
+        if isinstance(value, str):
+            self.dimension_set[name] = value
+        else:
+            self.dimension_set[name] = str(value)
 
     def __extract_metric_unit_value(self, unit: Union[str, MetricUnit]) -> str:
         """Return metric value from metric unit whether that's str or MetricUnit enum

build_linux_wheels.sh

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "aws_lambda_powertools"
-version = "0.9.4"
+version = "0.9.5"
 description = "Python utilities for AWS Lambda functions including but not limited to tracing, logging and custom metric"
 authors = ["Amazon Web Services"]
 classifiers=[

pyproject.toml

@@ -228,12 +228,12 @@ def handler(event, context):
     first_log, second_log, third_log, fourth_log = logs
 
     # First execution
-    assert "true" == first_log["cold_start"]
-    assert "true" == second_log["cold_start"]
+    assert first_log["cold_start"] is True
+    assert second_log["cold_start"] is True
 
     # Second execution
-    assert "false" == third_log["cold_start"]
-    assert "false" == fourth_log["cold_start"]
+    assert third_log["cold_start"] is False
+    assert fourth_log["cold_start"] is False
 
 
 def test_log_metric(capsys):

tests/functional/test_logger.py

@@ -1,5 +1,5 @@
 import json
-from typing import Dict, List
+from typing import Any, Dict, List
 
 import pytest
 
@@ -48,6 +48,14 @@ def dimensions() -> List[Dict[str, str]]:
     ]
 
 
+@pytest.fixture
+def non_str_dimensions() -> List[Dict[str, Any]]:
+    return [
+        {"name": "test_dimension", "value": True},
+        {"name": "test_dimension_2", "value": 3},
+    ]
+
+
 @pytest.fixture
 def namespace() -> Dict[str, str]:
     return {"name": "test_namespace"}
@@ -380,3 +388,27 @@ def lambda_handler(evt, context):
 
     # THEN metric set should be empty after function has been run
     assert my_metrics.metric_set == {}
+
+
+def test_log_metrics_non_string_dimension_values(capsys, metrics, non_str_dimensions, namespace):
+    # GIVEN Metrics is initialized and dimensions with non-string values are added
+    my_metrics = Metrics()
+    my_metrics.add_namespace(**namespace)
+    for metric in metrics:
+        my_metrics.add_metric(**metric)
+    for dimension in non_str_dimensions:
+        my_metrics.add_dimension(**dimension)
+
+    # WHEN we utilize log_metrics to serialize
+    # and flush all metrics at the end of a function execution
+    @my_metrics.log_metrics
+    def lambda_handler(evt, ctx):
+        return True
+
+    lambda_handler({}, {})
+    output = json.loads(capsys.readouterr().out.strip())
+
+    # THEN we should have no exceptions
+    # and dimension values hould be serialized as strings
+    for dimension in non_str_dimensions:
+        assert isinstance(output[dimension["name"]], str)