docstring + code coverage

aws_lambda_powertools/metrics/provider/base.py

@@ -9,42 +9,141 @@
 
 
 class MetricsProviderBase(ABC):
-    """Class for metric provider template
+    """
+    Class for metric provider template.
 
-    Use this template to create your own metric provider.
+    This class serves as a template for creating your own metric provider. Inherit from this class
+    and implement the required methods to define your specific metric provider.
 
+    Usage:
+        1. Inherit from this class.
+        2. Implement the required methods specific to your metric provider.
+        3. Customize the behavior and functionality of the metric provider in your subclass.
     """
 
-    # General add metric function. Should return combined metrics Dict
     @abstractmethod
     def add_metric(self, *args, **kwargs):
-        pass
+        """
+        Abstract method for adding a metric.
+
+        This method must be implemented in subclasses to add a metric and return a combined metrics dictionary.
+
+        Parameters
+        ----------
+        *args:
+            Positional arguments.
+        *kwargs:
+            Keyword arguments.
+
+        Returns
+        ----------
+        Dict
+            A combined metrics dictionary.
+
+        Raises
+        ----------
+        NotImplementedError
+            This method must be implemented in subclasses.
+        """
+        raise NotImplementedError
 
-    # serialize and return dict for flushing
     @abstractmethod
     def serialize(self, *args, **kwargs):
-        pass
+        """
+        Abstract method for serialize a metric.
+
+        This method must be implemented in subclasses to add a metric and return a combined metrics dictionary.
+
+        Parameters
+        ----------
+        *args:
+            Positional arguments.
+        *kwargs:
+            Keyword arguments.
+
+        Returns
+        ----------
+        Dict
+            Serialized metrics
+
+        Raises
+        ----------
+        NotImplementedError
+            This method must be implemented in subclasses.
+        """
+        raise NotImplementedError
 
     # flush serialized data to output, or send to API directly
     @abstractmethod
     def flush(self, *args, **kwargs):
-        pass
+        """
+        Abstract method for flushing a metric.
+
+        This method must be implemented in subclasses to add a metric and return a combined metrics dictionary.
+
+        Parameters
+        ----------
+        *args:
+            Positional arguments.
+        *kwargs:
+            Keyword arguments.
+
+        Raises
+        ----------
+        NotImplementedError
+            This method must be implemented in subclasses.
+        """
+        raise NotImplementedError
 
 
 class MetricsBase(ABC):
-    """Class for metric template
+    """
+    Class for metric template.
 
-    Use this template to create your own metric class.
+    This class serves as a template for creating your own metric class. Inherit from this class
+    and implement the necessary methods to define your specific metric.
 
+    NOTE: need to improve this docstring
     """
 
     @abstractmethod
     def add_metric(self, *args, **kwargs):
-        pass
+        """
+        Abstract method for adding a metric.
+
+        This method must be implemented in subclasses to add a metric and return a combined metrics dictionary.
+
+        Parameters
+        ----------
+        *args:
+            Positional arguments.
+        *kwargs:
+            Keyword arguments.
+
+        Returns
+        ----------
+        Dict
+            A combined metrics dictionary.
+
+        Raises
+        ----------
+        NotImplementedError
+            This method must be implemented in subclasses.
+        """
+        raise NotImplementedError
 
     @abstractmethod
     def flush_metrics(self, raise_on_empty_metrics: bool = False) -> None:
-        pass
+        """Manually flushes the metrics. This is normally not necessary,
+        unless you're running on other runtimes besides Lambda, where the @log_metrics
+        decorator already handles things for you.
+
+        Parameters
+        ----------
+        raise_on_empty_metrics : bool, optional
+            raise exception if no metrics are emitted, by default False
+        """
+        raise NotImplementedError
 
     def log_metrics(
         self,

aws_lambda_powertools/metrics/provider/opentelemetry_provider_draft.py

@@ -71,8 +71,8 @@ class OTLPMetrics(MetricsBase):
 
     Example
     -------
-    dd_provider = DataDogProvider(namespace="default")
-    metrics = DataDogMetrics(provider=dd_provider)
+    dd_provider = OTLPProvider(namespace="default")
+    metrics = OTLPMetrics(provider=dd_provider)
 
     @metrics.log_metrics(capture_cold_start_metric: bool = True, raise_on_empty_metrics: bool = False)
     def lambda_handler(event, context)

aws_lambda_powertools/shared/user_agent.py

@@ -112,7 +112,7 @@ def register_feature_to_session(session, feature):
 def register_feature_to_botocore_session(botocore_session, feature):
     """
     Register the given feature string to the event system of the provided botocore session
-    
+
     Please notice this function is for patching botocore session and is different from
     previous one which is for patching boto3 session
 
@@ -127,7 +127,7 @@ def register_feature_to_botocore_session(botocore_session, feature):
     ------
     AttributeError
         If the provided session does not have an event system.
-        
+
     Examples
     --------
     **register data-masking user-agent to botocore session**
@@ -139,7 +139,7 @@ def register_feature_to_botocore_session(botocore_session, feature):
         >>> session = botocore.session.Session()
         >>> register_feature_to_botocore_session(botocore_session=session, feature="data-masking")
         >>> key_provider = StrictAwsKmsMasterKeyProvider(key_ids=self.keys, botocore_session=session)
-    
+
     """
     try:
         botocore_session.register(TARGET_SDK_EVENT, _create_feature_function(feature))