Daily Sync with Botocore v1.40.61 on 2025/10/29

sample/sagemaker/2017-07-24/service-2.json

@@ -1542,6 +1542,19 @@
       ],
       "documentation":"<p>Deletes a pipeline if there are no running instances of the pipeline. To delete a pipeline, you must stop all running instances of the pipeline using the <code>StopPipelineExecution</code> API. When you delete a pipeline, all instances of the pipeline are deleted.</p>"
     },
+    "DeleteProcessingJob":{
+      "name":"DeleteProcessingJob",
+      "http":{
+        "method":"POST",
+        "requestUri":"/"
+      },
+      "input":{"shape":"DeleteProcessingJobRequest"},
+      "errors":[
+        {"shape":"ResourceNotFound"},
+        {"shape":"ResourceInUse"}
+      ],
+      "documentation":"<p>Deletes a processing job. After Amazon SageMaker deletes a processing job, all of the metadata for the processing job is lost. You can delete only processing jobs that are in a terminal state (<code>Stopped</code>, <code>Failed</code>, or <code>Completed</code>). You cannot delete a job that is in the <code>InProgress</code> or <code>Stopping</code> state. After deleting the job, you can reuse its name to create another processing job.</p>"
+    },
     "DeleteProject":{
       "name":"DeleteProject",
       "http":{
@@ -1590,6 +1603,19 @@
       "output":{"shape":"DeleteTagsOutput"},
       "documentation":"<p>Deletes the specified tags from an SageMaker resource.</p> <p>To list a resource's tags, use the <code>ListTags</code> API. </p> <note> <p>When you call this API to delete tags from a hyperparameter tuning job, the deleted tags are not removed from training jobs that the hyperparameter tuning job launched before you called this API.</p> </note> <note> <p>When you call this API to delete tags from a SageMaker Domain or User Profile, the deleted tags are not removed from Apps that the SageMaker Domain or User Profile launched before you called this API.</p> </note>"
     },
+    "DeleteTrainingJob":{
+      "name":"DeleteTrainingJob",
+      "http":{
+        "method":"POST",
+        "requestUri":"/"
+      },
+      "input":{"shape":"DeleteTrainingJobRequest"},
+      "errors":[
+        {"shape":"ResourceNotFound"},
+        {"shape":"ResourceInUse"}
+      ],
+      "documentation":"<p>Deletes a training job. After SageMaker deletes a training job, all of the metadata for the training job is lost. You can delete only training jobs that are in a terminal state (<code>Stopped</code>, <code>Failed</code>, or <code>Completed</code>) and don't retain an <code>Available</code> <a href=\"https://docs.aws.amazon.com/sagemaker/latest/dg/train-warm-pools.html\">managed warm pool</a>. You cannot delete a job that is in the <code>InProgress</code> or <code>Stopping</code> state. After deleting the job, you can reuse its name to create another training job.</p>"
+    },
     "DeleteTrial":{
       "name":"DeleteTrial",
       "http":{
@@ -14682,6 +14708,16 @@
         }
       }
     },
+    "DeleteProcessingJobRequest":{
+      "type":"structure",
+      "required":["ProcessingJobName"],
+      "members":{
+        "ProcessingJobName":{
+          "shape":"ProcessingJobName",
+          "documentation":"<p>The name of the processing job to delete.</p>"
+        }
+      }
+    },
     "DeleteProjectInput":{
       "type":"structure",
       "required":["ProjectName"],
@@ -14740,6 +14776,16 @@
       "type":"structure",
       "members":{}
     },
+    "DeleteTrainingJobRequest":{
+      "type":"structure",
+      "required":["TrainingJobName"],
+      "members":{
+        "TrainingJobName":{
+          "shape":"TrainingJobName",
+          "documentation":"<p>The name of the training job to delete.</p>"
+        }
+      }
+    },
     "DeleteTrialComponentRequest":{
       "type":"structure",
       "required":["TrialComponentName"],
@@ -42006,7 +42052,8 @@
         "Completed",
         "Failed",
         "Stopping",
-        "Stopped"
+        "Stopped",
+        "Deleting"
       ]
     },
     "TrainingJobStatusCounter":{

src/sagemaker_core/main/code_injection/shape_dag.py

@@ -4213,6 +4213,10 @@
         "members": [{"name": "PipelineArn", "shape": "PipelineArn", "type": "string"}],
         "type": "structure",
     },
+    "DeleteProcessingJobRequest": {
+        "members": [{"name": "ProcessingJobName", "shape": "ProcessingJobName", "type": "string"}],
+        "type": "structure",
+    },
     "DeleteProjectInput": {
         "members": [{"name": "ProjectName", "shape": "ProjectEntityName", "type": "string"}],
         "type": "structure",
@@ -4252,6 +4256,10 @@
         "type": "structure",
     },
     "DeleteTagsOutput": {"members": [], "type": "structure"},
+    "DeleteTrainingJobRequest": {
+        "members": [{"name": "TrainingJobName", "shape": "TrainingJobName", "type": "string"}],
+        "type": "structure",
+    },
     "DeleteTrialComponentRequest": {
         "members": [
             {"name": "TrialComponentName", "shape": "ExperimentEntityName", "type": "string"}

src/sagemaker_core/main/resources.py

@@ -26308,6 +26308,40 @@ def refresh(
         transform(response, "DescribeProcessingJobResponse", self)
         return self
 
+    @Base.add_validate_call
+    def delete(
+        self,
+    ) -> None:
+        """
+        Delete a ProcessingJob resource
+
+        Raises:
+            botocore.exceptions.ClientError: This exception is raised for AWS service related errors.
+                The error message and error code can be parsed from the exception as follows:
+                ```
+                try:
+                    # AWS service call here
+                except botocore.exceptions.ClientError as e:
+                    error_message = e.response['Error']['Message']
+                    error_code = e.response['Error']['Code']
+                ```
+            ResourceInUse: Resource being accessed is in use.
+            ResourceNotFound: Resource being access is not found.
+        """
+
+        client = Base.get_sagemaker_client()
+
+        operation_input_args = {
+            "ProcessingJobName": self.processing_job_name,
+        }
+        # serialize the input request
+        operation_input_args = serialize(operation_input_args)
+        logger.debug(f"Serialized input request: {operation_input_args}")
+
+        client.delete_processing_job(**operation_input_args)
+
+        logger.info(f"Deleting {self.__class__.__name__} - {self.get_name()}")
+
     @Base.add_validate_call
     def stop(self) -> None:
         """
@@ -28708,6 +28742,40 @@ def update(
 
         return self
 
+    @Base.add_validate_call
+    def delete(
+        self,
+    ) -> None:
+        """
+        Delete a TrainingJob resource
+
+        Raises:
+            botocore.exceptions.ClientError: This exception is raised for AWS service related errors.
+                The error message and error code can be parsed from the exception as follows:
+                ```
+                try:
+                    # AWS service call here
+                except botocore.exceptions.ClientError as e:
+                    error_message = e.response['Error']['Message']
+                    error_code = e.response['Error']['Code']
+                ```
+            ResourceInUse: Resource being accessed is in use.
+            ResourceNotFound: Resource being access is not found.
+        """
+
+        client = Base.get_sagemaker_client()
+
+        operation_input_args = {
+            "TrainingJobName": self.training_job_name,
+        }
+        # serialize the input request
+        operation_input_args = serialize(operation_input_args)
+        logger.debug(f"Serialized input request: {operation_input_args}")
+
+        client.delete_training_job(**operation_input_args)
+
+        logger.info(f"Deleting {self.__class__.__name__} - {self.get_name()}")
+
     @Base.add_validate_call
     def stop(self) -> None:
         """
@@ -28822,6 +28890,69 @@ def wait(
                     raise TimeoutExceededError(resouce_type="TrainingJob", status=current_status)
                 time.sleep(poll)
 
+    @Base.add_validate_call
+    def wait_for_delete(
+        self,
+        poll: int = 5,
+        timeout: Optional[int] = None,
+    ) -> None:
+        """
+        Wait for a TrainingJob resource to be deleted.
+
+        Parameters:
+            poll: The number of seconds to wait between each poll.
+            timeout: The maximum number of seconds to wait before timing out.
+
+        Raises:
+            botocore.exceptions.ClientError: This exception is raised for AWS service related errors.
+                The error message and error code can be parsed from the exception as follows:
+                ```
+                try:
+                    # AWS service call here
+                except botocore.exceptions.ClientError as e:
+                    error_message = e.response['Error']['Message']
+                    error_code = e.response['Error']['Code']
+                ```
+            TimeoutExceededError:  If the resource does not reach a terminal state before the timeout.
+            DeleteFailedStatusError:   If the resource reaches a failed state.
+            WaiterError: Raised when an error occurs while waiting.
+        """
+        start_time = time.time()
+
+        progress = Progress(
+            SpinnerColumn("bouncingBar"),
+            TextColumn("{task.description}"),
+            TimeElapsedColumn(),
+        )
+        progress.add_task("Waiting for TrainingJob to be deleted...")
+        status = Status("Current status:")
+
+        with Live(
+            Panel(
+                Group(progress, status),
+                title="Wait Log Panel",
+                border_style=Style(color=Color.BLUE.value),
+            )
+        ):
+            while True:
+                try:
+                    self.refresh()
+                    current_status = self.training_job_status
+                    status.update(f"Current status: [bold]{current_status}")
+
+                    if timeout is not None and time.time() - start_time >= timeout:
+                        raise TimeoutExceededError(
+                            resouce_type="TrainingJob", status=current_status
+                        )
+                except botocore.exceptions.ClientError as e:
+                    error_code = e.response["Error"]["Code"]
+
+                    if "ResourceNotFound" in error_code or "ValidationException" in error_code:
+                        logger.info("Resource was not found. It may have been deleted.")
+                        return
+                    raise e
+                time.sleep(poll)
+
     @classmethod
     @Base.add_validate_call
     def get_all(

src/sagemaker_core/tools/api_coverage.json

@@ -1 +1 @@
-{"SupportedAPIs": 363, "UnsupportedAPIs": 15}
+{"SupportedAPIs": 365, "UnsupportedAPIs": 15}