Merge branch 'develop' into feat/precommit-hooks

* develop:
  improv: include example tests in `make tests` (#63)
  chore: rename Makefile target docs-dev to docs-local (#65)
  improv: better namespace/dimension handling for Metrics (#62)

Makefile

@@ -42,10 +42,10 @@ build-docs-website: dev-docs
 	cd docs && npm run build
 	cp -R docs/public/* dist/
 
-docs-dev:
+docs-local:
 	cd docs && npm run start
 
-docs-api-dev:
+docs-api-local:
 	poetry run pdoc --http : aws_lambda_powertools
 
 security-baseline:

aws_lambda_powertools/metrics/base.py

@@ -35,7 +35,7 @@ class MetricManager:
 
     Environment variables
     ---------------------
-    POWERTOOLS_SERVICE_NAME : str
+    POWERTOOLS_METRICS_NAMESPACE : str
         metric namespace to be set for all metrics
 
     Raises
@@ -53,7 +53,7 @@ class MetricManager:
     def __init__(self, metric_set: Dict[str, str] = None, dimension_set: Dict = None, namespace: str = None):
         self.metric_set = metric_set if metric_set is not None else {}
         self.dimension_set = dimension_set if dimension_set is not None else {}
-        self.namespace = namespace or os.getenv("POWERTOOLS_SERVICE_NAME")
+        self.namespace = namespace or os.getenv("POWERTOOLS_METRICS_NAMESPACE")
         self._metric_units = [unit.value for unit in MetricUnit]
         self._metric_unit_options = list(MetricUnit.__members__)
 

aws_lambda_powertools/metrics/metric.py

@@ -21,7 +21,7 @@ class SingleMetric(MetricManager):
 
     Environment variables
     ---------------------
-    POWERTOOLS_SERVICE_NAME : str
+    POWERTOOLS_METRICS_NAMESPACE : str
         metric namespace
 
     Example
@@ -30,7 +30,7 @@ class SingleMetric(MetricManager):
 
         from aws_lambda_powertools.metrics import SingleMetric, MetricUnit
         import json
-        metric = Single_Metric(service="ServerlessAirline")
+        metric = Single_Metric(namespace="ServerlessAirline")
 
         metric.add_metric(name="ColdStart", unit=MetricUnit.Count, value=1)
         metric.add_dimension(name="function_version", value=47)
@@ -62,7 +62,7 @@ def add_metric(self, name: str, unit: MetricUnit, value: float):
 
 
 @contextmanager
-def single_metric(name: str, unit: MetricUnit, value: float, service: str = None):
+def single_metric(name: str, unit: MetricUnit, value: float, namespace: str = None):
     """Context manager to simplify creation of a single metric
 
     Example
@@ -71,12 +71,12 @@ def single_metric(name: str, unit: MetricUnit, value: float, service: str = None
 
         from aws_lambda_powertools.metrics import single_metric, MetricUnit
 
-        with single_metric(name="ColdStart", unit=MetricUnit.Count, value=1, service="ServerlessAirline") as metric:
+        with single_metric(name="ColdStart", unit=MetricUnit.Count, value=1, namespace="ServerlessAirline") as metric:
                 metric.add_dimension(name="function_version", value=47)
 
     **Same as above but set namespace using environment variable**
 
-        $ export POWERTOOLS_SERVICE_NAME="ServerlessAirline"
+        $ export POWERTOOLS_METRICS_NAMESPACE="ServerlessAirline"
 
         from aws_lambda_powertools.metrics import single_metric, MetricUnit
 
@@ -91,8 +91,8 @@ def single_metric(name: str, unit: MetricUnit, value: float, service: str = None
         `aws_lambda_powertools.helper.models.MetricUnit`
     value : float
         Metric value
-    service: str
-        Service name used as namespace
+    namespace: str
+        Namespace for metrics
 
     Yields
     -------
@@ -106,7 +106,7 @@ def single_metric(name: str, unit: MetricUnit, value: float, service: str = None
     """
     metric_set = None
     try:
-        metric: SingleMetric = SingleMetric(namespace=service)
+        metric: SingleMetric = SingleMetric(namespace=namespace)
         metric.add_metric(name=name, unit=unit, value=value)
         yield metric
         logger.debug("Serializing single metric")

aws_lambda_powertools/metrics/metrics.py

@@ -1,6 +1,7 @@
 import functools
 import json
 import logging
+import os
 from typing import Any, Callable
 
 from aws_lambda_powertools.metrics.base import MetricManager
@@ -29,10 +30,9 @@ class Metrics(MetricManager):
 
         from aws_lambda_powertools.metrics import Metrics
 
-        metrics = Metrics(service="ServerlessAirline")
+        metrics = Metrics(namespace="ServerlessAirline", service="payment")
         metrics.add_metric(name="ColdStart", unit=MetricUnit.Count, value=1)
         metrics.add_metric(name="BookingConfirmation", unit="Count", value=1)
-        metrics.add_dimension(name="service", value="booking")
         metrics.add_dimension(name="function_version", value="$LATEST")
         ...
 
@@ -47,8 +47,10 @@ def do_something():
 
     Environment variables
     ---------------------
-    POWERTOOLS_SERVICE_NAME : str
+    POWERTOOLS_METRICS_NAMESPACE : str
         metric namespace
+    POWERTOOLS_SERVICE_NAME : str
+        service name used for default dimension
 
     Parameters
     ----------
@@ -64,13 +66,14 @@ def do_something():
     _metrics = {}
     _dimensions = {}
 
-    def __init__(
-        self, service: str = None,
-    ):
+    def __init__(self, service: str = None, namespace: str = None):
         self.metric_set = self._metrics
         self.dimension_set = self._dimensions
-        self.service = service
-        super().__init__(metric_set=self.metric_set, dimension_set=self.dimension_set, namespace=self.service)
+        self.service = service or os.environ.get("POWERTOOLS_SERVICE_NAME")
+        self.namespace = namespace
+        if self.service:
+            self.dimension_set["service"] = self.service
+        super().__init__(metric_set=self.metric_set, dimension_set=self.dimension_set, namespace=self.namespace)
 
     def clear_metrics(self):
         logger.debug("Clearing out existing metric set from memory")

docs/content/core/metrics.mdx

@@ -16,7 +16,7 @@ Metrics creates custom metrics asynchronously via logging metrics to standard ou
 
 ## Initialization
 
-Set `POWERTOOLS_SERVICE_NAME` env var as a start - Here is an example using AWS Serverless Application Model (SAM)
+Set `POWERTOOLS_SERVICE_NAME` and `POWERTOOLS_METRICS_NAMESPACE` env vars as a start - Here is an example using AWS Serverless Application Model (SAM)
 
 ```yaml:title=template.yaml
 Resources:
@@ -27,37 +27,39 @@ Resources:
         Runtime: python3.8
         Environment:
             Variables:
-                POWERTOOLS_SERVICE_NAME: ServerlessAirline # highlight-line
+                POWERTOOLS_SERVICE_NAME: payment # highlight-line
+                POWERTOOLS_METRICS_NAMESPACE: ServerlessAirline # highlight-line
 ```
 
 We recommend you use your application or main service as a metric namespace.
-You can explicitly set a namespace name via `service` param or via `POWERTOOLS_SERVICE_NAME` env var. This sets **namespace** key that will be used for all metrics.
+You can explicitly set a namespace name via `namespace` param or via `POWERTOOLS_METRICS_NAMESPACE` env var. This sets **namespace** key that will be used for all metrics.
+You can also pass a service name via `service` param or `POWERTOOLS_SERVICE_NAME` env var. This will create a dimension with the service name.
 
 ```python:title=app.py
 from aws_lambda_powertools.metrics import Metrics, MetricUnit
 
-# POWERTOOLS_SERVICE_NAME defined
-metrics = Metrics() # highlight-line
+# POWERTOOLS_METRICS_NAMESPACE and POWERTOOLS_SERVICE_NAME defined
+metrics = Metrics() # highlight-line 
 
 # Explicit definition
-Metrics(service="ServerlessAirline")  # sets namespace to "ServerlessAirline"
+Metrics(namespace="ServerlessAirline", service="orders")  # creates a default dimension {"service": "orders"} under the namespace "ServerlessAirline"
 
 
 ```
 
-You can initialize Metrics anywhere in your code as many time as you need - It'll keep track of your aggregate metrics in memory.
+You can initialize Metrics anywhere in your code as many times as you need - It'll keep track of your aggregate metrics in memory.
 
 ## Creating metrics
 
-You can create metrics using `add_metric`, and set dimensions for all your aggregate metrics using `add_dimension`.
+You can create metrics using `add_metric`, and manually create dimensions for all your aggregate metrics using `add_dimension`.
 
 ```python:title=app.py
 from aws_lambda_powertools.metrics import Metrics, MetricUnit
 
-metrics = Metrics(service="ExampleService")
+metrics = Metrics(namespace="ExampleApplication", service="booking")
 # highlight-start
-metrics.add_metric(name="ColdStart", unit=MetricUnit.Count, value=1)
-metrics.add_dimension(name="service", value="booking")
+metrics.add_dimension(name="environment", value="prod")
+metrics.add_metric(name="SuccessfulBooking", unit=MetricUnit.Count, value=1)
 # highlight-end
 ```
 
@@ -79,7 +81,7 @@ CloudWatch EMF uses the same dimensions across all your metrics. Use `single_met
 ```python:title=single_metric.py
 from aws_lambda_powertools.metrics import MetricUnit, single_metric
 
-with single_metric(name="ColdStart", unit=MetricUnit.Count, value=1, service="ExampleService") as metric: # highlight-line
+with single_metric(name="ColdStart", unit=MetricUnit.Count, value=1, namespace="ExampleApplication") as metric: # highlight-line
     metric.add_dimension(name="function_context", value="$LATEST")
     ...
 ```
@@ -115,15 +117,14 @@ def lambda_handler(evt, ctx):
 ```python:title=lambda_handler_nested_middlewares.py
 from aws_lambda_powertools.metrics import Metrics, MetricUnit
 
-metrics = Metrics(service="ExampleService")
+metrics = Metrics(namespace="ExampleApplication", service="booking")
 metrics.add_metric(name="ColdStart", unit="Count", value=1)
 
 # highlight-start
 @metrics.log_metrics
 @tracer.capture_lambda_handler
 # highlight-end
 def lambda_handler(evt, ctx):
-    metrics.add_dimension(name="service", value="booking")
     metrics.add_metric(name="BookingConfirmation", unit="Count", value=1)
     ...
 ```
@@ -136,9 +137,8 @@ If you prefer not to use `log_metrics` because you might want to encapsulate add
 import json
 from aws_lambda_powertools.metrics import Metrics, MetricUnit
 
-metrics = Metrics(service="ExampleService")
+metrics = Metrics(namespace="ExampleApplication", service="booking")
 metrics.add_metric(name="ColdStart", unit="Count", value=1)
-metrics.add_dimension(name="service", value="booking")
 
 # highlight-start
 your_metrics_object = metrics.serialize_metric_set()
@@ -149,10 +149,11 @@ print(json.dumps(your_metrics_object))
 
 ## Testing your code
 
-Use `POWERTOOLS_SERVICE_NAME` env var when unit testing your code to ensure a metric namespace object is created, and your code doesn't fail validation.
+Use `POWERTOOLS_METRICS_NAMESPACE` and `POWERTOOLS_SERVICE_NAME` env vars when unit testing your code to ensure metric namespace and dimension objects are created, and your code doesn't fail validation.
 
 ```bash:title=pytest_metric_namespace.sh
-POWERTOOLS_SERVICE_NAME="Example" python -m pytest
+
+POWERTOOLS_SERVICE_NAME="Example" POWERTOOLS_METRICS_NAMESPACE="Application" python -m pytest
 ```
 
-You can ignore this if you are explicitly setting namespace by passing a service name when initializing Metrics: `metrics = Metrics(service=ServiceName)`.
+You can ignore this if you are explicitly setting namespace/default dimension by passing the `namespace` and `service` parameters when initializing Metrics: `metrics = Metrics(namespace=ApplicationName, service=ServiceName)`.

docs/content/index.mdx

@@ -36,7 +36,8 @@ _`*` Core utilities are Tracer, Logger and Metrics. Optional utilities may vary
 
 Environment variable | Description | Utility
 ------------------------------------------------- | --------------------------------------------------------------------------------- | --------------------------------------------------------------------------------- | -------------------------------------------------
-**POWERTOOLS_SERVICE_NAME** | Sets service name used for tracing namespace, metrics namespace and structured logging | all
+**POWERTOOLS_SERVICE_NAME** | Sets service name used for tracing namespace, metrics dimension and structured logging | all
+**POWERTOOLS_METRICS_NAMESPACE** | Sets namespace used for metrics | [Metrics](./core/metrics)
 **POWERTOOLS_TRACE_DISABLED** | Disables tracing | [Tracing](./core/tracer)
 **POWERTOOLS_TRACE_MIDDLEWARES** | Creates sub-segment for each custom middleware | [middleware_factory](./utilities/middleware_factory)
 **POWERTOOLS_LOGGER_LOG_EVENT** | Logs incoming event | [Logging](./core/logger)

example/README.md

@@ -1,6 +1,6 @@
 # Summary
 
-This example uses both [tracing](https://github.com/awslabs/aws-lambda-powertools/tree/develop/python#tracing) and [logging](https://github.com/awslabs/aws-lambda-powertools/tree/develop/python#logging) features, includes all environment variables that can be used, and demonstrates how to explicitly disable tracing while running unit tests - That is not necessary when running within SAM CLI as it detects the local env automatically.
+This example uses [tracer](https://awslabs.github.io/aws-lambda-powertools-python/core/tracer/), [metrics](https://awslabs.github.io/aws-lambda-powertools-python/core/metrics/),and [logger](https://awslabs.github.io/aws-lambda-powertools-python/core/logger/) features, includes all environment variables that can be used, and demonstrates how to explicitly disable tracing while running unit tests - That is not necessary when running within SAM CLI as it detects the local env automatically.
 
 **Quick commands**
 
@@ -9,9 +9,9 @@ This example uses both [tracing](https://github.com/awslabs/aws-lambda-powertool
 * **Deploy**: `sam deploy --guided`
 * **Unit Tests**: We recommend proceeding with the following commands in a virtual environment
   - **Install deps**: `pip install -r hello_world/requirements.txt && pip install -r requirements-dev.txt`
-  - **Run tests with tracing disabled and namespace set**
-    - `POWERTOOLS_SERVICE_NAME="Example" POWERTOOLS_TRACE_DISABLED=1 python -m pytest`
-    - Both are necessary because `app.py` initializes them in the global scope, since both Tracer and Metrics will be initialized and configured during import time. For unit tests, we could always patch and explicitly config but env vars do just fine for this example.
+  - **Run tests with namespace and service set, and tracing disabled**
+    - `POWERTOOLS_METRICS_NAMESPACE="Example" POWERTOOLS_SERVICE_NAME="Example" POWERTOOLS_TRACE_DISABLED=1 python -m pytest`
+    - These are necessary because `app.py` initializes them in the global scope, since both Tracer and Metrics will be initialized and configured during import time. For unit tests, we could always patch and explicitly config but env vars do just fine for this example.
 
 # Example code
 
@@ -118,7 +118,7 @@ Tests are defined in the `tests` folder in this project. Use PIP to install the
 ```bash
 example$ pip install -r hello_world/requirements.txt
 example$ pip install -r requirements-dev.txt
-example$ POWERTOOLS_TRACE_DISABLED=1 python -m pytest tests/ -v
+example$ pytest -v
 ```
 
 ## Cleanup

example/template.yaml

@@ -24,6 +24,7 @@ Resources:
           POWERTOOLS_TRACE_DISABLED: "false"          # Explicitly disables tracing, default
           POWERTOOLS_LOGGER_LOG_EVENT: "false"        # Logs incoming event, default
           POWERTOOLS_LOGGER_SAMPLE_RATE: "0"          # Debug log sampling percentage, default
+          POWERTOOLS_METRICS_NAMESPACE: "Example"     # Metric Namespace
           LOG_LEVEL: INFO                             # Log level for Logger (INFO, DEBUG, etc.), default
       Events:
         HelloWorld:

example/tests/test_handler.py

@@ -1,9 +1,24 @@
 import json
+import os
+import sys
 from dataclasses import dataclass
 
 import pytest
 
-from hello_world import app
+
+@pytest.fixture()
+def env_vars(monkeypatch):
+    monkeypatch.setenv("POWERTOOLS_METRICS_NAMESPACE", "example_namespace")
+    monkeypatch.setenv("POWERTOOLS_SERVICE_NAME", "example_service")
+    monkeypatch.setenv("POWERTOOLS_TRACE_DISABLED", "1")
+
+
+@pytest.fixture()
+def lambda_handler(env_vars):
+    from hello_world import app
+
+    return app.lambda_handler
+
 
 
 @pytest.fixture()
@@ -71,8 +86,9 @@ class Context:
     aws_request_id: str = "5b441b59-a550-11c8-6564-f1c833cf438c"
 
 
-def test_lambda_handler(apigw_event, mocker, capsys):
-    ret = app.lambda_handler(apigw_event, Context())
+@pytest.mark.skipif(sys.version_info < (3, 7), reason="requires python3.7 or higher")
+def test_lambda_handler(lambda_handler, apigw_event, mocker, capsys):
+    ret = lambda_handler(apigw_event, Context())
     data = json.loads(ret["body"])
 
     output = capsys.readouterr()

pyproject.toml

@@ -46,7 +46,7 @@ radon = "^4.1.0"
 xenon = "^0.7.0"
 flake8-bugbear = "^20.1.4"
 flake8-eradicate = "^0.3.0"
-pre-commit = "^2.4.0"
+dataclasses = {version = "*", python = "~3.6"}
 
 [tool.coverage.run]
 source = ["aws_lambda_powertools"]

pytest.ini

@@ -1,3 +1,3 @@
 [pytest]
 addopts = -ra --cov --cov-config=.coveragerc
-testpaths = ./tests
+testpaths = ./tests ./example/tests