chore: minor housekeeping before release

aws_lambda_powertools/utilities/batch/__init__.py

@@ -8,11 +8,11 @@
     BasePartialProcessor,
     BatchProcessor,
     EventType,
-    ExceptionInfo,
     FailureResponse,
     SuccessResponse,
     batch_processor,
 )
+from aws_lambda_powertools.utilities.batch.exceptions import ExceptionInfo
 from aws_lambda_powertools.utilities.batch.sqs import PartialSQSProcessor, sqs_batch_processor
 
 __all__ = (

aws_lambda_powertools/utilities/batch/base.py

@@ -8,11 +8,10 @@
 import sys
 from abc import ABC, abstractmethod
 from enum import Enum
-from types import TracebackType
 from typing import Any, Callable, Dict, List, Optional, Tuple, Type, Union, overload
 
 from aws_lambda_powertools.middleware_factory import lambda_handler_decorator
-from aws_lambda_powertools.utilities.batch.exceptions import BatchProcessingError
+from aws_lambda_powertools.utilities.batch.exceptions import BatchProcessingError, ExceptionInfo
 from aws_lambda_powertools.utilities.data_classes.dynamo_db_stream_event import DynamoDBRecord
 from aws_lambda_powertools.utilities.data_classes.kinesis_stream_event import KinesisStreamRecord
 from aws_lambda_powertools.utilities.data_classes.sqs_event import SQSRecord
@@ -30,8 +29,6 @@ class EventType(Enum):
 # type specifics
 #
 has_pydantic = "pydantic" in sys.modules
-ExceptionInfo = Tuple[Type[BaseException], BaseException, TracebackType]
-OptExcInfo = Union[ExceptionInfo, Tuple[None, None, None]]
 
 # For IntelliSense and Mypy to work, we need to account for possible SQS, Kinesis and DynamoDB subclasses
 # We need them as subclasses as we must access their message ID or sequence number metadata via dot notation
@@ -61,7 +58,7 @@ class BasePartialProcessor(ABC):
     def __init__(self):
         self.success_messages: List[BatchEventTypes] = []
         self.fail_messages: List[BatchEventTypes] = []
-        self.exceptions: List = []
+        self.exceptions: List[ExceptionInfo] = []
 
     @abstractmethod
     def _prepare(self):
@@ -132,15 +129,15 @@ def success_handler(self, record, result: Any) -> SuccessResponse:
         self.success_messages.append(record)
         return entry
 
-    def failure_handler(self, record, exception: OptExcInfo) -> FailureResponse:
+    def failure_handler(self, record, exception: ExceptionInfo) -> FailureResponse:
         """
         Keeps track of batch records that failed processing
 
         Parameters
         ----------
         record: Any
             record that failed processing
-        exception: OptExcInfo
+        exception: ExceptionInfo
             Exception information containing type, value, and traceback (sys.exc_info())
 
         Returns
@@ -411,32 +408,28 @@ def _get_messages_to_report(self) -> Dict[str, str]:
     def _collect_sqs_failures(self):
         if self.model:
             return {"itemIdentifier": msg.messageId for msg in self.fail_messages}
-        else:
-            return {"itemIdentifier": msg.message_id for msg in self.fail_messages}
+        return {"itemIdentifier": msg.message_id for msg in self.fail_messages}
 
     def _collect_kinesis_failures(self):
         if self.model:
             # Pydantic model uses int but Lambda poller expects str
             return {"itemIdentifier": msg.kinesis.sequenceNumber for msg in self.fail_messages}
-        else:
-            return {"itemIdentifier": msg.kinesis.sequence_number for msg in self.fail_messages}
+        return {"itemIdentifier": msg.kinesis.sequence_number for msg in self.fail_messages}
 
     def _collect_dynamodb_failures(self):
         if self.model:
             return {"itemIdentifier": msg.dynamodb.SequenceNumber for msg in self.fail_messages}
-        else:
-            return {"itemIdentifier": msg.dynamodb.sequence_number for msg in self.fail_messages}
+        return {"itemIdentifier": msg.dynamodb.sequence_number for msg in self.fail_messages}
 
     @overload
     def _to_batch_type(self, record: dict, event_type: EventType, model: "BatchTypeModels") -> "BatchTypeModels":
-        ...
+        ...  # pragma: no cover
 
     @overload
     def _to_batch_type(self, record: dict, event_type: EventType) -> EventSourceDataClassTypes:
-        ...
+        ...  # pragma: no cover
 
     def _to_batch_type(self, record: dict, event_type: EventType, model: Optional["BatchTypeModels"] = None):
         if model is not None:
             return model.parse_obj(record)
-        else:
-            return self._DATA_CLASS_MAPPING[event_type](record)
+        return self._DATA_CLASS_MAPPING[event_type](record)

aws_lambda_powertools/utilities/batch/exceptions.py

@@ -2,11 +2,14 @@
 Batch processing exceptions
 """
 import traceback
-from typing import Optional, Tuple
+from types import TracebackType
+from typing import List, Optional, Tuple, Type
+
+ExceptionInfo = Tuple[Type[BaseException], BaseException, TracebackType]
 
 
 class BaseBatchProcessingError(Exception):
-    def __init__(self, msg="", child_exceptions=()):
+    def __init__(self, msg="", child_exceptions: Optional[List[ExceptionInfo]] = None):
         super().__init__(msg)
         self.msg = msg
         self.child_exceptions = child_exceptions
@@ -24,7 +27,7 @@ def format_exceptions(self, parent_exception_str):
 class SQSBatchProcessingError(BaseBatchProcessingError):
     """When at least one message within a batch could not be processed"""
 
-    def __init__(self, msg="", child_exceptions: Optional[Tuple[Exception]] = None):
+    def __init__(self, msg="", child_exceptions: Optional[List[ExceptionInfo]] = None):
         super().__init__(msg, child_exceptions)
 
     # Overriding this method so we can output all child exception tracebacks when we raise this exception to prevent
@@ -37,7 +40,7 @@ def __str__(self):
 class BatchProcessingError(BaseBatchProcessingError):
     """When all batch records failed to be processed"""
 
-    def __init__(self, msg="", child_exceptions: Optional[Tuple[Exception]] = None):
+    def __init__(self, msg="", child_exceptions: Optional[List[ExceptionInfo]] = None):
         super().__init__(msg, child_exceptions)
 
     def __str__(self):

aws_lambda_powertools/utilities/parser/parser.py

@@ -86,12 +86,12 @@ def handler(event: Order, context: LambdaContext):
 
 @overload
 def parse(event: Dict[str, Any], model: Type[Model]) -> Model:
-    ...
+    ...  # pragma: no cover
 
 
 @overload
 def parse(event: Dict[str, Any], model: Type[Model], envelope: Type[Envelope]) -> EnvelopeModel:
-    ...
+    ...  # pragma: no cover
 
 
 def parse(event: Dict[str, Any], model: Type[Model], envelope: Optional[Type[Envelope]] = None):

pyproject.toml

@@ -85,6 +85,12 @@ exclude_lines = [
     # Don't complain if non-runnable code isn't run:
     "if 0:",
     "if __name__ == .__main__.:",
+
+	# Ignore type function overload
+	"@overload",
+
+	# Ignore interfaces, future protocols, and @overload impl
+	"...",
 ]
 
 [tool.isort]

tests/functional/idempotency/test_idempotency.py

@@ -1057,3 +1057,15 @@ def two(data):
     assert one(data=mock_event) == "one"
     assert two(data=mock_event) == "two"
     assert len(persistence_store.table.method_calls) == 4
+
+
+def test_invalid_dynamodb_persistence_layer():
+    # Scenario constructing a DynamoDBPersistenceLayer with a key_attr matching sort_key_attr should fail
+    with pytest.raises(ValueError) as ve:
+        DynamoDBPersistenceLayer(
+            table_name="Foo",
+            key_attr="id",
+            sort_key_attr="id",
+        )
+    # and raise a ValueError
+    assert str(ve.value) == "key_attr [id] and sort_key_attr [id] cannot be the same!"

tests/functional/test_utilities_batch.py

@@ -832,5 +832,7 @@ def lambda_handler(event, context):
         return processor.response()
 
     # WHEN/THEN
-    with pytest.raises(BatchProcessingError):
+    with pytest.raises(BatchProcessingError) as e:
         lambda_handler(event, {})
+        ret = str(e)
+        assert ret is not None