Strip empty chars

Author: leandrodamascena

aws_lambda_powertools/metrics/provider/cloudwatch_emf/cloudwatch.py

@@ -273,7 +273,7 @@ def add_dimension(self, name: str, value: str) -> None:
                 f"Maximum number of dimensions exceeded ({MAX_DIMENSIONS}): Unable to add dimension {name}.",
             )
 
-        if not name or not value:
+        if not name.strip() or not value.strip():
             warnings.warn(
                 f"The dimension {name} doesn't meet the requirements and won't be added. "
                 "Ensure the dimension name and value are non empty strings",

docs/core/metrics.md

@@ -25,7 +25,7 @@ If you're new to Amazon CloudWatch, there are five terminologies you must be awa
 * **Resolution**. It's a value representing the storage resolution for the corresponding metric. Metrics can be either Standard or High resolution. Read more [here](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/publishingMetrics.html#high-resolution-metrics){target="_blank"}.
 
 <figure>
-  <img src="../../media/metrics_terminology.png" />
+  <img src="../../media/metrics_terminology.png" alt="Terminology" />
   <figcaption>Metric terminology, visually explained</figcaption>
 </figure>
 
@@ -131,6 +131,8 @@ If you'd like to remove them at some point, you can use `clear_default_dimension
     --8<-- "examples/metrics/src/set_default_dimensions_log_metrics.py"
     ```
 
+**Note:** Dimensions with empty values will not be included.
+
 ### Changing default timestamp
 
 When creating metrics, we use the current timestamp. If you want to change the timestamp of all the metrics you create, utilize the `set_timestamp` function. You can specify a datetime object or an integer representing an epoch timestamp in milliseconds.

tests/functional/metrics/required_dependencies/test_metrics_cloudwatch_emf.py

@@ -1053,7 +1053,7 @@ def test_add_dimensions_with_empty_value(namespace, capsys, metric):
 
     # WHEN we try to add a dimension with empty value
     with pytest.warns(UserWarning, match=f"The dimension {my_dimension} doesn't meet the requirements *"):
-        my_metrics.add_dimension(name="my_empty_dimension", value="")
+        my_metrics.add_dimension(name="my_empty_dimension", value=" ")
 
     my_metrics.add_metric(**metric)
     my_metrics.flush_metrics()