fix: fix format issues

Author: Dewen Qi

src/sagemaker/workflow/fail_step.py

@@ -36,13 +36,17 @@ def __init__(
         """Constructs a `FailStep`.
 
         Args:
-            name (str): The name of the `FailStep`. A name is required and must be unique within a pipeline.
-            error_message (str or PipelineNonPrimitiveInputTypes): An error message defined by the user.
+            name (str): The name of the `FailStep`. A name is required and must be
+                unique within a pipeline.
+            error_message (str or PipelineNonPrimitiveInputTypes):
+                An error message defined by the user.
                 Once the `FailStep` is reached, the execution fails and the
                 error message is set as the failure reason (default: None).
-            display_name (str): The display name of the `FailStep`. The display name provides better UI readability. (default: None).
+            display_name (str): The display name of the `FailStep`.
+                The display name provides better UI readability. (default: None).
             description (str): The description of the `FailStep` (default: None).
-            depends_on (List[str] or List[Step]): A list of `Step` names or `Step` instances that this `FailStep` depends on. 
+            depends_on (List[str] or List[Step]): A list of `Step` names or `Step` instances
+                that this `FailStep` depends on.
                 If a listed `Step` name does not exist, an error is returned (default: None).
         """
         super(FailStep, self).__init__(
@@ -57,9 +61,11 @@ def arguments(self) -> RequestType:
 
     @property
     def properties(self):
-        """A `Properties` object is not available for the `FailStep`. Executing a `FailStep` will terminate the pipeline. 
-            `FailStep` properties should not be referenced and no other `Step` should depend on the `FailStep`."""
+        """A `Properties` object is not available for the `FailStep`.
+
+        Executing a `FailStep` will terminate the pipeline.
+        `FailStep` properties should not be referenced.
+        """
         raise RuntimeError(
-            "The Properties object is not available for the FailStep "
-            + "as it cannot be referenced by other steps."
+            "FailStep is a terminal step and the Properties object is not available for it."
         )

src/sagemaker/workflow/steps.py

@@ -147,8 +147,9 @@ class CacheConfig:
     If caching is enabled, the pipeline attempts to find a previous execution of a `Step`
     that was called with the same arguments. `Step` caching only considers successful execution.
     If a successful previous execution is found, the pipeline propagates the values
-    from the previous execution rather than recomputing the `Step`. When multiple successful executions
-    exist within the timeout period, it uses the result for the most recent successful execution.
+    from the previous execution rather than recomputing the `Step`.
+    When multiple successful executions exist within the timeout period,
+    it uses the result for the most recent successful execution.
 
 
     Attributes:
@@ -237,8 +238,8 @@ def __init__(
     ):
         """Construct a `TrainingStep`, given an `EstimatorBase` instance.
 
-        In addition to the `EstimatorBase` instance, the other arguments are those that are supplied to
-        the `fit` method of the `sagemaker.estimator.Estimator`.
+        In addition to the `EstimatorBase` instance, the other arguments are those
+        that are supplied to the `fit` method of the `sagemaker.estimator.Estimator`.
 
         Args:
             name (str): The name of the `TrainingStep`.
@@ -408,8 +409,8 @@ def __init__(
     ):
         """Constructs a `TransformStep`, given a `Transformer` instance.
 
-        In addition to the `Transformer` instance, the other arguments are those that are supplied to
-        the `transform` method of the `sagemaker.transformer.Transformer`.
+        In addition to the `Transformer` instance, the other arguments are those
+        that are supplied to the `transform` method of the `sagemaker.transformer.Transformer`.
 
         Args:
             name (str): The name of the `TransformStep`.
@@ -614,8 +615,8 @@ def __init__(
     ):
         """Construct a `TuningStep`, given a `HyperparameterTuner` instance.
 
-        In addition to the `HyperparameterTuner` instance, the other arguments are those that are supplied to
-        the `fit` method of the `sagemaker.tuner.HyperparameterTuner`.
+        In addition to the `HyperparameterTuner` instance, the other arguments are those
+        that are supplied to the `fit` method of the `sagemaker.tuner.HyperparameterTuner`.
 
         Args:
             name (str): The name of the `TuningStep`.
@@ -652,7 +653,7 @@ def __init__(
             job_arguments (List[str]): A list of strings to be passed into the processing job.
                 Defaults to `None`.
             cache_config (CacheConfig):  A `sagemaker.workflow.steps.CacheConfig` instance.
-            depends_on (List[str] or List[Step]): A list of `Step` names or `Step` instances that 
+            depends_on (List[str] or List[Step]): A list of `Step` names or `Step` instances that
                 this `sagemaker.workflow.steps.ProcessingStep` depends on.
             retry_policies (List[RetryPolicy]):  A list of retry policies.
         """
@@ -694,8 +695,9 @@ def arguments(self) -> RequestType:
 
     @property
     def properties(self):
-        """A `Properties` object representing
-        `DescribeHyperParameterTuningJobResponse` and
+        """A `Properties` object
+
+        A `Properties` object representing `DescribeHyperParameterTuningJobResponse` and
         `ListTrainingJobsForHyperParameterTuningJobResponse` data model.
         """
         return self._properties
@@ -713,7 +715,7 @@ def get_top_model_s3_uri(self, top_k: int, s3_bucket: str, prefix: str = "") ->
 
         Args:
             top_k (int): The index of the top performing training job
-                tuning step stores up to 50 top performing training jobs. 
+                tuning step stores up to 50 top performing training jobs.
                 A valid top_k value is from 0 to 49. The best training job
                 model is at index 0.
             s3_bucket (str): The S3 bucket to store the training job output artifact.

tests/unit/sagemaker/workflow/test_fail_step.py

@@ -116,6 +116,6 @@ def test_fail_step_with_properties_ref():
         fail_step.properties()
 
     assert (
-        str(error.value) == "The Properties object is not available for the Fail step "
-        "as it cannot be referenced by other steps."
+        str(error.value)
+        == "FailStep is a terminal step and the Properties object is not available for it."
     )