Exemples d'Amazon S3 Control utilisant le SDK pour Python (Boto3)

Les exemples de code suivants vous montrent comment effectuer des actions et implémenter des scénarios courants à l' AWS SDK pour Python (Boto3) aide d'Amazon S3 Control.

Les principes de base sont des exemples de code qui vous montrent comment effectuer les opérations essentielles au sein d’un service.

Les actions sont des extraits de code de programmes plus larges et doivent être exécutées dans leur contexte. Alors que les actions vous indiquent comment appeler des fonctions de service individuelles, vous pouvez les voir en contexte dans leurs scénarios associés.

Chaque exemple inclut un lien vers le code source complet, où vous trouverez des instructions sur la configuration et l’exécution du code en contexte.

Mise en route

L’exemple de code suivant montre comment faire ses premiers pas avec Amazon S3 Control.

Kit SDK for Python (Boto3)

Note

Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le référentiel d’exemples de code AWS.


    def list_jobs(self, account_id: str) -> None:
        """
        List all batch jobs for the account.

        Args:
            account_id (str): AWS account ID
        """
        try:
            response = self.s3control_client.list_jobs(
                AccountId=account_id,
                JobStatuses=['Active', 'Complete', 'Cancelled', 'Failed', 'New', 'Paused', 'Pausing', 'Preparing', 'Ready', 'Suspended']
            )
            jobs = response.get('Jobs', [])
            for job in jobs:
                print(f"The job id is {job['JobId']}")
                print(f"The job priority is {job['Priority']}")
        except ClientError as e:
            print(f"Error listing jobs: {e}")
            raise

Pour plus de détails sur l'API, consultez ListJobsle AWS manuel de référence de l'API SDK for Python (Boto3).

Principes de base

L’exemple de code suivant montre comment apprendre les opérations de base pour Amazon S3 Control.

Kit SDK for Python (Boto3)

Note

Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le référentiel d’exemples de code AWS.

Découvrez le scénario de base de S3 Batch.


class S3BatchWrapper:
    """Wrapper class for managing S3 Batch Operations."""

    def __init__(self, s3_client: Any, s3control_client: Any, sts_client: Any) -> None:
        """
        Initializes the S3BatchWrapper with AWS service clients.
        
        :param s3_client: A Boto3 Amazon S3 client. This client provides low-level
                         access to AWS S3 services.
        :param s3control_client: A Boto3 Amazon S3 Control client. This client provides
                               low-level access to AWS S3 Control services.
        :param sts_client: A Boto3 AWS STS client. This client provides low-level
                          access to AWS STS services.
        """
        self.s3_client = s3_client
        self.s3control_client = s3control_client
        self.sts_client = sts_client
        # Get region from the client for bucket creation logic
        self.region_name = self.s3_client.meta.region_name

    def get_account_id(self) -> str:
        """
        Get AWS account ID.

        Returns:
            str: AWS account ID
        """
        return self.sts_client.get_caller_identity()["Account"]

    def create_bucket(self, bucket_name: str) -> None:
        """
        Create an S3 bucket.

        Args:
            bucket_name (str): Name of the bucket to create

        Raises:
            ClientError: If bucket creation fails
        """
        try:
            if self.region_name and self.region_name != 'us-east-1':
                self.s3_client.create_bucket(
                    Bucket=bucket_name,
                    CreateBucketConfiguration={
                        'LocationConstraint': self.region_name
                    }
                )
            else:
                self.s3_client.create_bucket(Bucket=bucket_name)
            print(f"Created bucket: {bucket_name}")
        except ClientError as e:
            print(f"Error creating bucket: {e}")
            raise

    def upload_files_to_bucket(self, bucket_name: str, file_names: List[str]) -> str:
        """
        Upload files to S3 bucket including manifest file.

        Args:
            bucket_name (str): Target bucket name
            file_names (list): List of file names to upload

        Returns:
            str: ETag of the manifest file

        Raises:
            ClientError: If file upload fails
        """
        try:
            for file_name in file_names:
                if file_name != "job-manifest.csv":
                    content = f"Content for {file_name}"
                    self.s3_client.put_object(
                        Bucket=bucket_name,
                        Key=file_name,
                        Body=content.encode('utf-8')
                    )
                    print(f"Uploaded {file_name} to {bucket_name}")

            manifest_content = ""
            for file_name in file_names:
                if file_name != "job-manifest.csv":
                    manifest_content += f"{bucket_name},{file_name}\n"

            manifest_response = self.s3_client.put_object(
                Bucket=bucket_name,
                Key="job-manifest.csv",
                Body=manifest_content.encode('utf-8')
            )
            print(f"Uploaded manifest file to {bucket_name}")
            print(f"Manifest content:\n{manifest_content}")
            return manifest_response['ETag'].strip('"')

        except ClientError as e:
            print(f"Error uploading files: {e}")
            raise

    def create_s3_batch_job(self, account_id: str, role_arn: str, manifest_location: str,
                           report_bucket_name: str) -> str:
        """
        Create an S3 batch operation job.

        Args:
            account_id (str): AWS account ID
            role_arn (str): IAM role ARN for batch operations
            manifest_location (str): Location of the manifest file
            report_bucket_name (str): Bucket for job reports

        Returns:
            str: Job ID

        Raises:
            ClientError: If job creation fails
        """
        try:
            bucket_name = manifest_location.split(':::')[1].split('/')[0]
            manifest_key = 'job-manifest.csv'
            manifest_obj = self.s3_client.head_object(
                Bucket=bucket_name,
                Key=manifest_key
            )
            etag = manifest_obj['ETag'].strip('"')
            
            response = self.s3control_client.create_job(
                AccountId=account_id,
                Operation={
                    'S3PutObjectTagging': {
                        'TagSet': [
                            {
                                'Key': 'BatchTag',
                                'Value': 'BatchValue'
                            },
                        ]
                    }
                },
                Report={
                    'Bucket': report_bucket_name,
                    'Format': 'Report_CSV_20180820',
                    'Enabled': True,
                    'Prefix': 'batch-op-reports',
                    'ReportScope': 'AllTasks'
                },
                Manifest={
                    'Spec': {
                        'Format': 'S3BatchOperations_CSV_20180820',
                        'Fields': ['Bucket', 'Key']
                    },
                    'Location': {
                        'ObjectArn': manifest_location,
                        'ETag': etag
                    }
                },
                Priority=10,
                RoleArn=role_arn,
                Description='Batch job for tagging objects',
                ConfirmationRequired=True
            )
            job_id = response['JobId']
            print(f"The Job id is {job_id}")
            return job_id
        except ClientError as e:
            print(f"Error creating batch job: {e}")
            if 'Message' in str(e):
                print(f"Detailed error message: {e.response['Message']}")
            raise

    def check_job_failure_reasons(self, job_id: str, account_id: str) -> List[Dict[str, Any]]:
        """
        Check for any failure reasons of a batch job.

        Args:
            job_id (str): ID of the batch job
            account_id (str): AWS account ID

        Returns:
            list: List of failure reasons

        Raises:
            ClientError: If checking job failure reasons fails
        """
        try:
            response = self.s3control_client.describe_job(
                AccountId=account_id,
                JobId=job_id
            )
            if 'FailureReasons' in response['Job']:
                for reason in response['Job']['FailureReasons']:
                    print(f"- {reason}")
            return response['Job'].get('FailureReasons', [])
        except ClientError as e:
            print(f"Error checking job failure reasons: {e}")
            raise

    def wait_for_job_ready(self, job_id: str, account_id: str, desired_status: str = 'Ready') -> bool:
        """
        Wait for a job to reach the desired status.

        Args:
            job_id (str): ID of the batch job
            account_id (str): AWS account ID
            desired_status (str): Target status to wait for

        Returns:
            bool: True if desired status is reached, False otherwise

        Raises:
            ClientError: If checking job status fails
        """
        print(f"Waiting for job to become {desired_status}...")
        max_attempts = 60
        attempt = 0
        while attempt < max_attempts:
            try:
                response = self.s3control_client.describe_job(
                    AccountId=account_id,
                    JobId=job_id
                )
                current_status = response['Job']['Status']
                print(f"Current job status: {current_status}")
                if current_status == desired_status:
                    return True
                if current_status == 'Suspended':
                    print("Job is in Suspended state, can proceed with activation")
                    return True
                if current_status in ['Active', 'Failed', 'Cancelled', 'Complete']:
                    print(f"Job is in {current_status} state, cannot reach {desired_status} status")
                    if 'FailureReasons' in response['Job']:
                        print("Failure reasons:")
                        for reason in response['Job']['FailureReasons']:
                            print(f"- {reason}")
                    return False

                time.sleep(20)
                attempt += 1
            except ClientError as e:
                print(f"Error checking job status: {e}")
                raise
        print(f"Timeout waiting for job to become {desired_status}")
        return False

    def update_job_priority(self, job_id: str, account_id: str) -> None:
        """
        Update the priority of a batch job and start it.

        Args:
            job_id (str): ID of the batch job
            account_id (str): AWS account ID
        """
        try:
            response = self.s3control_client.describe_job(
                AccountId=account_id,
                JobId=job_id
            )
            current_status = response['Job']['Status']
            print(f"Current job status: {current_status}")
            
            if current_status in ['Ready', 'Suspended']:
                self.s3control_client.update_job_priority(
                    AccountId=account_id,
                    JobId=job_id,
                    Priority=60
                )
                print("The job priority was updated")
                
                try:
                    self.s3control_client.update_job_status(
                        AccountId=account_id,
                        JobId=job_id,
                        RequestedJobStatus='Ready'
                    )
                    print("Job activated successfully")
                except ClientError as activation_error:
                    print(f"Note: Could not activate job automatically: {activation_error}")
                    print("Job priority was updated successfully. Job may need manual activation in the console.")
            elif current_status in ['Active', 'Completing', 'Complete']:
                print(f"Job is in '{current_status}' state - priority cannot be updated")
                if current_status == 'Completing':
                    print("Job is finishing up and will complete soon.")
                elif current_status == 'Complete':
                    print("Job has already completed successfully.")
                else:
                    print("Job is currently running.")
            else:
                print(f"Job is in '{current_status}' state - priority update not allowed")
                
        except ClientError as e:
            print(f"Error updating job priority: {e}")
            print("Continuing with the scenario...")
            return

    def cancel_job(self, job_id: str, account_id: str) -> None:
        """
        Cancel an S3 batch job.

        Args:
            job_id (str): ID of the batch job
            account_id (str): AWS account ID
        """
        try:
            response = self.s3control_client.describe_job(
                AccountId=account_id,
                JobId=job_id
            )
            current_status = response['Job']['Status']
            print(f"Current job status: {current_status}")

            if current_status in ['Ready', 'Suspended', 'Active']:
                self.s3control_client.update_job_status(
                    AccountId=account_id,
                    JobId=job_id,
                    RequestedJobStatus='Cancelled'
                )
                print(f"Job {job_id} was successfully canceled.")
            elif current_status in ['Completing', 'Complete']:
                print(f"Job is in '{current_status}' state - cannot be cancelled")
                if current_status == 'Completing':
                    print("Job is finishing up and will complete soon.")
                elif current_status == 'Complete':
                    print("Job has already completed successfully.")
            else:
                print(f"Job is in '{current_status}' state - cancel not allowed")
        except ClientError as e:
            print(f"Error canceling job: {e}")
            raise

    def describe_job_details(self, job_id: str, account_id: str) -> None:
        """
        Describe detailed information about a batch job.

        Args:
            job_id (str): ID of the batch job
            account_id (str): AWS account ID
        """
        try:
            response = self.s3control_client.describe_job(
                AccountId=account_id,
                JobId=job_id
            )
            job = response['Job']
            print(f"Job ID: {job['JobId']}")
            print(f"Description: {job.get('Description', 'N/A')}")
            print(f"Status: {job['Status']}")
            print(f"Role ARN: {job['RoleArn']}")
            print(f"Priority: {job['Priority']}")
            if 'ProgressSummary' in job:
                progress = job['ProgressSummary']
                print(f"Progress Summary: Total={progress.get('TotalNumberOfTasks', 0)}, "
                      f"Succeeded={progress.get('NumberOfTasksSucceeded', 0)}, "
                      f"Failed={progress.get('NumberOfTasksFailed', 0)}")
        except ClientError as e:
            print(f"Error describing job: {e}")
            raise
    
    def get_job_tags(self, job_id: str, account_id: str) -> None:
        """
        Get tags associated with a batch job.

        Args:
            job_id (str): ID of the batch job
            account_id (str): AWS account ID
        """
        try:
            response = self.s3control_client.get_job_tagging(
                AccountId=account_id,
                JobId=job_id
            )
            tags = response.get('Tags', [])
            if tags:
                print(f"Tags for job {job_id}:")
                for tag in tags:
                    print(f"  {tag['Key']}: {tag['Value']}")
            else:
                print(f"No tags found for job ID: {job_id}")
        except ClientError as e:
            print(f"Error getting job tags: {e}")
            raise
    
    def put_job_tags(self, job_id: str, account_id: str) -> None:
        """
        Add tags to a batch job.

        Args:
            job_id (str): ID of the batch job
            account_id (str): AWS account ID
        """
        try:
            self.s3control_client.put_job_tagging(
                AccountId=account_id,
                JobId=job_id,
                Tags=[
                    {'Key': 'Environment', 'Value': 'Development'},
                    {'Key': 'Team', 'Value': 'DataProcessing'}
                ]
            )
            print(f"Additional tags were added to job {job_id}")
        except ClientError as e:
            print(f"Error adding job tags: {e}")
            raise
    
    def list_jobs(self, account_id: str) -> None:
        """
        List all batch jobs for the account.

        Args:
            account_id (str): AWS account ID
        """
        try:
            response = self.s3control_client.list_jobs(
                AccountId=account_id,
                JobStatuses=['Active', 'Complete', 'Cancelled', 'Failed', 'New', 'Paused', 'Pausing', 'Preparing', 'Ready', 'Suspended']
            )
            jobs = response.get('Jobs', [])
            for job in jobs:
                print(f"The job id is {job['JobId']}")
                print(f"The job priority is {job['Priority']}")
        except ClientError as e:
            print(f"Error listing jobs: {e}")
            raise
    
    def delete_job_tags(self, job_id: str, account_id: str) -> None:
        """
        Delete all tags from a batch job.

        Args:
            job_id (str): ID of the batch job
            account_id (str): AWS account ID
        """
        try:
            self.s3control_client.delete_job_tagging(
                AccountId=account_id,
                JobId=job_id
            )
            print(f"You have successfully deleted {job_id} tagging.")
        except ClientError as e:
            print(f"Error deleting job tags: {e}")
            raise

    def cleanup_resources(self, bucket_name: str, file_names: List[str]) -> None:
        """
        Clean up all resources created during the scenario.

        Args:
            bucket_name (str): Name of the bucket to clean up
            file_names (list): List of files to delete

        Raises:
            ClientError: If cleanup fails
        """
        try:
            for file_name in file_names:
                self.s3_client.delete_object(Bucket=bucket_name, Key=file_name)
                print(f"Deleted {file_name}")

            response = self.s3_client.list_objects_v2(
                Bucket=bucket_name,
                Prefix='batch-op-reports/'
            )
            if 'Contents' in response:
                for obj in response['Contents']:
                    self.s3_client.delete_object(
                        Bucket=bucket_name,
                        Key=obj['Key']
                    )
                    print(f"Deleted {obj['Key']}")

            self.s3_client.delete_bucket(Bucket=bucket_name)
            print(f"Deleted bucket {bucket_name}")
        except ClientError as e:
            print(f"Error in cleanup: {e}")
            raise

Pour plus de détails sur l’API, consultez les rubriques suivantes dans la Référence des API du kit AWS SDK for Python (Boto3).

Actions

L'exemple de code suivant montre comment utiliserCreateJob.

Kit SDK for Python (Boto3)

Note

Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le référentiel d’exemples de code AWS.


    def create_s3_batch_job(self, account_id: str, role_arn: str, manifest_location: str,
                           report_bucket_name: str) -> str:
        """
        Create an S3 batch operation job.

        Args:
            account_id (str): AWS account ID
            role_arn (str): IAM role ARN for batch operations
            manifest_location (str): Location of the manifest file
            report_bucket_name (str): Bucket for job reports

        Returns:
            str: Job ID

        Raises:
            ClientError: If job creation fails
        """
        try:
            bucket_name = manifest_location.split(':::')[1].split('/')[0]
            manifest_key = 'job-manifest.csv'
            manifest_obj = self.s3_client.head_object(
                Bucket=bucket_name,
                Key=manifest_key
            )
            etag = manifest_obj['ETag'].strip('"')
            
            response = self.s3control_client.create_job(
                AccountId=account_id,
                Operation={
                    'S3PutObjectTagging': {
                        'TagSet': [
                            {
                                'Key': 'BatchTag',
                                'Value': 'BatchValue'
                            },
                        ]
                    }
                },
                Report={
                    'Bucket': report_bucket_name,
                    'Format': 'Report_CSV_20180820',
                    'Enabled': True,
                    'Prefix': 'batch-op-reports',
                    'ReportScope': 'AllTasks'
                },
                Manifest={
                    'Spec': {
                        'Format': 'S3BatchOperations_CSV_20180820',
                        'Fields': ['Bucket', 'Key']
                    },
                    'Location': {
                        'ObjectArn': manifest_location,
                        'ETag': etag
                    }
                },
                Priority=10,
                RoleArn=role_arn,
                Description='Batch job for tagging objects',
                ConfirmationRequired=True
            )
            job_id = response['JobId']
            print(f"The Job id is {job_id}")
            return job_id
        except ClientError as e:
            print(f"Error creating batch job: {e}")
            if 'Message' in str(e):
                print(f"Detailed error message: {e.response['Message']}")
            raise

Pour plus de détails sur l'API, consultez CreateJoble AWS manuel de référence de l'API SDK for Python (Boto3).

L'exemple de code suivant montre comment utiliserDeleteJobTagging.

Kit SDK for Python (Boto3)

Note

Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le référentiel d’exemples de code AWS.


    def delete_job_tags(self, job_id: str, account_id: str) -> None:
        """
        Delete all tags from a batch job.

        Args:
            job_id (str): ID of the batch job
            account_id (str): AWS account ID
        """
        try:
            self.s3control_client.delete_job_tagging(
                AccountId=account_id,
                JobId=job_id
            )
            print(f"You have successfully deleted {job_id} tagging.")
        except ClientError as e:
            print(f"Error deleting job tags: {e}")
            raise

Pour plus de détails sur l'API, consultez DeleteJobTaggingle AWS manuel de référence de l'API SDK for Python (Boto3).

L'exemple de code suivant montre comment utiliserDescribeJob.

Kit SDK for Python (Boto3)

Note

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    def describe_job_details(self, job_id: str, account_id: str) -> None:
        """
        Describe detailed information about a batch job.

        Args:
            job_id (str): ID of the batch job
            account_id (str): AWS account ID
        """
        try:
            response = self.s3control_client.describe_job(
                AccountId=account_id,
                JobId=job_id
            )
            job = response['Job']
            print(f"Job ID: {job['JobId']}")
            print(f"Description: {job.get('Description', 'N/A')}")
            print(f"Status: {job['Status']}")
            print(f"Role ARN: {job['RoleArn']}")
            print(f"Priority: {job['Priority']}")
            if 'ProgressSummary' in job:
                progress = job['ProgressSummary']
                print(f"Progress Summary: Total={progress.get('TotalNumberOfTasks', 0)}, "
                      f"Succeeded={progress.get('NumberOfTasksSucceeded', 0)}, "
                      f"Failed={progress.get('NumberOfTasksFailed', 0)}")
        except ClientError as e:
            print(f"Error describing job: {e}")
            raise

Pour plus de détails sur l'API, consultez DescribeJoble AWS manuel de référence de l'API SDK for Python (Boto3).

L'exemple de code suivant montre comment utiliserGetJobTagging.

Kit SDK for Python (Boto3)

Note

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    def get_job_tags(self, job_id: str, account_id: str) -> None:
        """
        Get tags associated with a batch job.

        Args:
            job_id (str): ID of the batch job
            account_id (str): AWS account ID
        """
        try:
            response = self.s3control_client.get_job_tagging(
                AccountId=account_id,
                JobId=job_id
            )
            tags = response.get('Tags', [])
            if tags:
                print(f"Tags for job {job_id}:")
                for tag in tags:
                    print(f"  {tag['Key']}: {tag['Value']}")
            else:
                print(f"No tags found for job ID: {job_id}")
        except ClientError as e:
            print(f"Error getting job tags: {e}")
            raise

Pour plus de détails sur l'API, consultez GetJobTaggingle AWS manuel de référence de l'API SDK for Python (Boto3).

L'exemple de code suivant montre comment utiliserPutJobTagging.

Kit SDK for Python (Boto3)

Note

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    def put_job_tags(self, job_id: str, account_id: str) -> None:
        """
        Add tags to a batch job.

        Args:
            job_id (str): ID of the batch job
            account_id (str): AWS account ID
        """
        try:
            self.s3control_client.put_job_tagging(
                AccountId=account_id,
                JobId=job_id,
                Tags=[
                    {'Key': 'Environment', 'Value': 'Development'},
                    {'Key': 'Team', 'Value': 'DataProcessing'}
                ]
            )
            print(f"Additional tags were added to job {job_id}")
        except ClientError as e:
            print(f"Error adding job tags: {e}")
            raise

Pour plus de détails sur l'API, consultez PutJobTaggingle AWS manuel de référence de l'API SDK for Python (Boto3).

L'exemple de code suivant montre comment utiliserUpdateJobPriority.

Kit SDK for Python (Boto3)

Note

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    def update_job_priority(self, job_id: str, account_id: str) -> None:
        """
        Update the priority of a batch job and start it.

        Args:
            job_id (str): ID of the batch job
            account_id (str): AWS account ID
        """
        try:
            response = self.s3control_client.describe_job(
                AccountId=account_id,
                JobId=job_id
            )
            current_status = response['Job']['Status']
            print(f"Current job status: {current_status}")
            
            if current_status in ['Ready', 'Suspended']:
                self.s3control_client.update_job_priority(
                    AccountId=account_id,
                    JobId=job_id,
                    Priority=60
                )
                print("The job priority was updated")
                
                try:
                    self.s3control_client.update_job_status(
                        AccountId=account_id,
                        JobId=job_id,
                        RequestedJobStatus='Ready'
                    )
                    print("Job activated successfully")
                except ClientError as activation_error:
                    print(f"Note: Could not activate job automatically: {activation_error}")
                    print("Job priority was updated successfully. Job may need manual activation in the console.")
            elif current_status in ['Active', 'Completing', 'Complete']:
                print(f"Job is in '{current_status}' state - priority cannot be updated")
                if current_status == 'Completing':
                    print("Job is finishing up and will complete soon.")
                elif current_status == 'Complete':
                    print("Job has already completed successfully.")
                else:
                    print("Job is currently running.")
            else:
                print(f"Job is in '{current_status}' state - priority update not allowed")
                
        except ClientError as e:
            print(f"Error updating job priority: {e}")
            print("Continuing with the scenario...")
            return

Pour plus de détails sur l'API, consultez UpdateJobPriorityle AWS manuel de référence de l'API SDK for Python (Boto3).

L'exemple de code suivant montre comment utiliserUpdateJobStatus.

Kit SDK for Python (Boto3)

Note

Il y en a plus à ce sujet GitHub. Trouvez l’exemple complet et découvrez comment le configurer et l’exécuter dans le référentiel d’exemples de code AWS.


    def cancel_job(self, job_id: str, account_id: str) -> None:
        """
        Cancel an S3 batch job.

        Args:
            job_id (str): ID of the batch job
            account_id (str): AWS account ID
        """
        try:
            response = self.s3control_client.describe_job(
                AccountId=account_id,
                JobId=job_id
            )
            current_status = response['Job']['Status']
            print(f"Current job status: {current_status}")

            if current_status in ['Ready', 'Suspended', 'Active']:
                self.s3control_client.update_job_status(
                    AccountId=account_id,
                    JobId=job_id,
                    RequestedJobStatus='Cancelled'
                )
                print(f"Job {job_id} was successfully canceled.")
            elif current_status in ['Completing', 'Complete']:
                print(f"Job is in '{current_status}' state - cannot be cancelled")
                if current_status == 'Completing':
                    print("Job is finishing up and will complete soon.")
                elif current_status == 'Complete':
                    print("Job has already completed successfully.")
            else:
                print(f"Job is in '{current_status}' state - cancel not allowed")
        except ClientError as e:
            print(f"Error canceling job: {e}")
            raise

Pour plus de détails sur l'API, consultez UpdateJobStatusle AWS manuel de référence de l'API SDK for Python (Boto3).

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Compartiments de répertoires S3