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Ejemplos de Amazon S3 usando SDK para Python (Boto3)
En los siguientes ejemplos de código, se muestra cómo realizar acciones e implementar situaciones comunes mediante el uso AWS SDK for Python (Boto3) de Amazon S3.
Los conceptos básicos son ejemplos de código que muestran cómo realizar las operaciones esenciales dentro de un servicio.
Las acciones son extractos de código de programas más grandes y deben ejecutarse en contexto. Mientras las acciones muestran cómo llamar a las distintas funciones de servicio, es posible ver las acciones en contexto en los escenarios relacionados.
Los escenarios son ejemplos de código que muestran cómo llevar a cabo una tarea específica a través de llamadas a varias funciones dentro del servicio o combinado con otros Servicios de AWS.
En cada ejemplo se incluye un enlace al código de origen completo, con instrucciones de configuración y ejecución del código en el contexto.
Introducción
En los siguientes ejemplos de código se muestra cómo empezar a utilizar Amazon S3.
- SDK para Python (Boto3)
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nota
Hay más información al respecto GitHub. Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. import boto3 def hello_s3(): """ Use the AWS SDK for Python (Boto3) to create an Amazon Simple Storage Service (Amazon S3) client and list the buckets in your account. This example uses the default settings specified in your shared credentials and config files. """ # Create an S3 client. s3_client = boto3.client("s3") print("Hello, Amazon S3! Let's list your buckets:") # Create a paginator for the list_buckets operation. paginator = s3_client.get_paginator("list_buckets") # Use the paginator to get a list of all buckets. response_iterator = paginator.paginate( PaginationConfig={ "PageSize": 50, # Adjust PageSize as needed. "StartingToken": None, } ) # Iterate through the pages of the response. buckets_found = False for page in response_iterator: if "Buckets" in page and page["Buckets"]: buckets_found = True for bucket in page["Buckets"]: print(f"\t{bucket['Name']}") if not buckets_found: print("No buckets found!") if __name__ == "__main__": hello_s3()
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Para obtener más información sobre la API, consulta ListBucketsla AWS Referencia de API de SDK for Python (Boto3).
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Conceptos básicos
En el siguiente ejemplo de código, se muestra cómo:
Creación de un bucket y cargar un archivo en el bucket.
Descargar un objeto desde un bucket.
Copiar un objeto en una subcarpeta de un bucket.
Obtención de una lista de los objetos de un bucket.
Eliminación del bucket y todos los objetos que incluye.
- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. import io import os import uuid import boto3 from boto3.s3.transfer import S3UploadFailedError from botocore.exceptions import ClientError def do_scenario(s3_resource): print("-" * 88) print("Welcome to the Amazon S3 getting started demo!") print("-" * 88) bucket_name = f"amzn-s3-demo-bucket-{uuid.uuid4()}" bucket = s3_resource.Bucket(bucket_name) try: bucket.create( CreateBucketConfiguration={ "LocationConstraint": s3_resource.meta.client.meta.region_name } ) print(f"Created demo bucket named {bucket.name}.") except ClientError as err: print(f"Tried and failed to create demo bucket {bucket_name}.") print(f"\t{err.response['Error']['Code']}:{err.response['Error']['Message']}") print(f"\nCan't continue the demo without a bucket!") return file_name = None while file_name is None: file_name = input("\nEnter a file you want to upload to your bucket: ") if not os.path.exists(file_name): print(f"Couldn't find file {file_name}. Are you sure it exists?") file_name = None obj = bucket.Object(os.path.basename(file_name)) try: obj.upload_file(file_name) print( f"Uploaded file {file_name} into bucket {bucket.name} with key {obj.key}." ) except S3UploadFailedError as err: print(f"Couldn't upload file {file_name} to {bucket.name}.") print(f"\t{err}") answer = input(f"\nDo you want to download {obj.key} into memory (y/n)? ") if answer.lower() == "y": data = io.BytesIO() try: obj.download_fileobj(data) data.seek(0) print(f"Got your object. Here are the first 20 bytes:\n") print(f"\t{data.read(20)}") except ClientError as err: print(f"Couldn't download {obj.key}.") print( f"\t{err.response['Error']['Code']}:{err.response['Error']['Message']}" ) answer = input( f"\nDo you want to copy {obj.key} to a subfolder in your bucket (y/n)? " ) if answer.lower() == "y": dest_obj = bucket.Object(f"demo-folder/{obj.key}") try: dest_obj.copy({"Bucket": bucket.name, "Key": obj.key}) print(f"Copied {obj.key} to {dest_obj.key}.") except ClientError as err: print(f"Couldn't copy {obj.key} to {dest_obj.key}.") print( f"\t{err.response['Error']['Code']}:{err.response['Error']['Message']}" ) print("\nYour bucket contains the following objects:") try: for o in bucket.objects.all(): print(f"\t{o.key}") except ClientError as err: print(f"Couldn't list the objects in bucket {bucket.name}.") print(f"\t{err.response['Error']['Code']}:{err.response['Error']['Message']}") answer = input( "\nDo you want to delete all of the objects as well as the bucket (y/n)? " ) if answer.lower() == "y": try: bucket.objects.delete() bucket.delete() print(f"Emptied and deleted bucket {bucket.name}.\n") except ClientError as err: print(f"Couldn't empty and delete bucket {bucket.name}.") print( f"\t{err.response['Error']['Code']}:{err.response['Error']['Message']}" ) print("Thanks for watching!") print("-" * 88) if __name__ == "__main__": do_scenario(boto3.resource("s3"))
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Para obtener información sobre la API, consulte los siguientes temas en la Referencia de la API de AWS SDK para Python (Boto3).
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Acciones
En el siguiente ejemplo de código, se muestra cómo utilizar CopyObject
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- SDK para Python (Boto3)
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nota
Hay más información GitHub. Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class ObjectWrapper: """Encapsulates S3 object actions.""" def __init__(self, s3_object): """ :param s3_object: A Boto3 Object resource. This is a high-level resource in Boto3 that wraps object actions in a class-like structure. """ self.object = s3_object self.key = self.object.key def copy(self, dest_object): """ Copies the object to another bucket. :param dest_object: The destination object initialized with a bucket and key. This is a Boto3 Object resource. """ try: dest_object.copy_from( CopySource={"Bucket": self.object.bucket_name, "Key": self.object.key} ) dest_object.wait_until_exists() logger.info( "Copied object from %s:%s to %s:%s.", self.object.bucket_name, self.object.key, dest_object.bucket_name, dest_object.key, ) except ClientError: logger.exception( "Couldn't copy object from %s/%s to %s/%s.", self.object.bucket_name, self.object.key, dest_object.bucket_name, dest_object.key, ) raise
Copia un objeto mediante una solicitud condicional.
class S3ConditionalRequests: """Encapsulates S3 conditional request operations.""" def __init__(self, s3_client): self.s3 = s3_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ s3_client = boto3.client("s3") return cls(s3_client) def copy_object_conditional( self, source_key: str, dest_key: str, source_bucket: str, dest_bucket: str, condition_type: str, condition_value: str, ): """ Copies an object from one Amazon S3 bucket to another with a conditional request. :param source_key: The key of the source object to copy. :param dest_key: The key of the destination object. :param source_bucket: The source bucket of the object. :param dest_bucket: The destination bucket of the object. :param condition_type: The type of condition to apply, e.g. 'CopySourceIfMatch', 'CopySourceIfNoneMatch', 'CopySourceIfModifiedSince', 'CopySourceIfUnmodifiedSince'. :param condition_value: The value to use for the condition. """ try: self.s3.copy_object( Bucket=dest_bucket, Key=dest_key, CopySource={"Bucket": source_bucket, "Key": source_key}, **{condition_type: condition_value}, ) print( f"\tConditional copy successful for key {dest_key} in bucket {dest_bucket}." ) except ClientError as e: error_code = e.response["Error"]["Code"] if error_code == "PreconditionFailed": print("\tConditional copy failed: Precondition failed") elif error_code == "304": # Not modified error code. print("\tConditional copy failed: Object not modified") else: logger.error(f"Unexpected error: {error_code}") raise
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Para obtener más información sobre la API, consulta CopyObjectla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar CreateBucket
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- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. Cree un bucket con la configuración predeterminada.
class BucketWrapper: """Encapsulates S3 bucket actions.""" def __init__(self, bucket): """ :param bucket: A Boto3 Bucket resource. This is a high-level resource in Boto3 that wraps bucket actions in a class-like structure. """ self.bucket = bucket self.name = bucket.name def create(self, region_override=None): """ Create an Amazon S3 bucket in the default Region for the account or in the specified Region. :param region_override: The Region in which to create the bucket. If this is not specified, the Region configured in your shared credentials is used. """ if region_override is not None: region = region_override else: region = self.bucket.meta.client.meta.region_name try: self.bucket.create(CreateBucketConfiguration={"LocationConstraint": region}) self.bucket.wait_until_exists() logger.info("Created bucket '%s' in region=%s", self.bucket.name, region) except ClientError as error: logger.exception( "Couldn't create bucket named '%s' in region=%s.", self.bucket.name, region, ) raise error
Cree un bucket con control de versiones con una configuración de ciclo de vida.
def create_versioned_bucket(bucket_name, prefix): """ Creates an Amazon S3 bucket, enables it for versioning, and configures a lifecycle that expires noncurrent object versions after 7 days. Adding a lifecycle configuration to a versioned bucket is a best practice. It helps prevent objects in the bucket from accumulating a large number of noncurrent versions, which can slow down request performance. Usage is shown in the usage_demo_single_object function at the end of this module. :param bucket_name: The name of the bucket to create. :param prefix: Identifies which objects are automatically expired under the configured lifecycle rules. :return: The newly created bucket. """ try: bucket = s3.create_bucket( Bucket=bucket_name, CreateBucketConfiguration={ "LocationConstraint": s3.meta.client.meta.region_name }, ) logger.info("Created bucket %s.", bucket.name) except ClientError as error: if error.response["Error"]["Code"] == "BucketAlreadyOwnedByYou": logger.warning("Bucket %s already exists! Using it.", bucket_name) bucket = s3.Bucket(bucket_name) else: logger.exception("Couldn't create bucket %s.", bucket_name) raise try: bucket.Versioning().enable() logger.info("Enabled versioning on bucket %s.", bucket.name) except ClientError: logger.exception("Couldn't enable versioning on bucket %s.", bucket.name) raise try: expiration = 7 bucket.LifecycleConfiguration().put( LifecycleConfiguration={ "Rules": [ { "Status": "Enabled", "Prefix": prefix, "NoncurrentVersionExpiration": {"NoncurrentDays": expiration}, } ] } ) logger.info( "Configured lifecycle to expire noncurrent versions after %s days " "on bucket %s.", expiration, bucket.name, ) except ClientError as error: logger.warning( "Couldn't configure lifecycle on bucket %s because %s. " "Continuing anyway.", bucket.name, error, ) return bucket
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Para obtener más información sobre la API, consulta CreateBucketla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar DeleteBucket
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- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class BucketWrapper: """Encapsulates S3 bucket actions.""" def __init__(self, bucket): """ :param bucket: A Boto3 Bucket resource. This is a high-level resource in Boto3 that wraps bucket actions in a class-like structure. """ self.bucket = bucket self.name = bucket.name def delete(self): """ Delete the bucket. The bucket must be empty or an error is raised. """ try: self.bucket.delete() self.bucket.wait_until_not_exists() logger.info("Bucket %s successfully deleted.", self.bucket.name) except ClientError: logger.exception("Couldn't delete bucket %s.", self.bucket.name) raise
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Para obtener más información sobre la API, consulta DeleteBucketla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar DeleteBucketCors
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- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class BucketWrapper: """Encapsulates S3 bucket actions.""" def __init__(self, bucket): """ :param bucket: A Boto3 Bucket resource. This is a high-level resource in Boto3 that wraps bucket actions in a class-like structure. """ self.bucket = bucket self.name = bucket.name def delete_cors(self): """ Delete the CORS rules from the bucket. :param bucket_name: The name of the bucket to update. """ try: self.bucket.Cors().delete() logger.info("Deleted CORS from bucket '%s'.", self.bucket.name) except ClientError: logger.exception("Couldn't delete CORS from bucket '%s'.", self.bucket.name) raise
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Para obtener más información sobre la API, consulta DeleteBucketCorsla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar DeleteBucketLifecycle
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- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class BucketWrapper: """Encapsulates S3 bucket actions.""" def __init__(self, bucket): """ :param bucket: A Boto3 Bucket resource. This is a high-level resource in Boto3 that wraps bucket actions in a class-like structure. """ self.bucket = bucket self.name = bucket.name def delete_lifecycle_configuration(self): """ Remove the lifecycle configuration from the specified bucket. """ try: self.bucket.LifecycleConfiguration().delete() logger.info( "Deleted lifecycle configuration for bucket '%s'.", self.bucket.name ) except ClientError: logger.exception( "Couldn't delete lifecycle configuration for bucket '%s'.", self.bucket.name, ) raise
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Para obtener más información sobre la API, consulta DeleteBucketLifecyclela AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar DeleteBucketPolicy
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- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class BucketWrapper: """Encapsulates S3 bucket actions.""" def __init__(self, bucket): """ :param bucket: A Boto3 Bucket resource. This is a high-level resource in Boto3 that wraps bucket actions in a class-like structure. """ self.bucket = bucket self.name = bucket.name def delete_policy(self): """ Delete the security policy from the bucket. """ try: self.bucket.Policy().delete() logger.info("Deleted policy for bucket '%s'.", self.bucket.name) except ClientError: logger.exception( "Couldn't delete policy for bucket '%s'.", self.bucket.name ) raise
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Para obtener más información sobre la API, consulta DeleteBucketPolicyla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar DeleteObject
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- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. Elimine un objeto.
class ObjectWrapper: """Encapsulates S3 object actions.""" def __init__(self, s3_object): """ :param s3_object: A Boto3 Object resource. This is a high-level resource in Boto3 that wraps object actions in a class-like structure. """ self.object = s3_object self.key = self.object.key def delete(self): """ Deletes the object. """ try: self.object.delete() self.object.wait_until_not_exists() logger.info( "Deleted object '%s' from bucket '%s'.", self.object.key, self.object.bucket_name, ) except ClientError: logger.exception( "Couldn't delete object '%s' from bucket '%s'.", self.object.key, self.object.bucket_name, ) raise
Revierta un objeto a una versión anterior y elimine versiones posteriores del objeto.
def rollback_object(bucket, object_key, version_id): """ Rolls back an object to an earlier version by deleting all versions that occurred after the specified rollback version. Usage is shown in the usage_demo_single_object function at the end of this module. :param bucket: The bucket that holds the object to roll back. :param object_key: The object to roll back. :param version_id: The version ID to roll back to. """ # Versions must be sorted by last_modified date because delete markers are # at the end of the list even when they are interspersed in time. versions = sorted( bucket.object_versions.filter(Prefix=object_key), key=attrgetter("last_modified"), reverse=True, ) logger.debug( "Got versions:\n%s", "\n".join( [ f"\t{version.version_id}, last modified {version.last_modified}" for version in versions ] ), ) if version_id in [ver.version_id for ver in versions]: print(f"Rolling back to version {version_id}") for version in versions: if version.version_id != version_id: version.delete() print(f"Deleted version {version.version_id}") else: break print(f"Active version is now {bucket.Object(object_key).version_id}") else: raise KeyError( f"{version_id} was not found in the list of versions for " f"{object_key}." )
Reactive un objeto eliminado quitando el marcador de eliminación activo del objeto.
def revive_object(bucket, object_key): """ Revives a versioned object that was deleted by removing the object's active delete marker. A versioned object presents as deleted when its latest version is a delete marker. By removing the delete marker, we make the previous version the latest version and the object then presents as *not* deleted. Usage is shown in the usage_demo_single_object function at the end of this module. :param bucket: The bucket that contains the object. :param object_key: The object to revive. """ # Get the latest version for the object. response = s3.meta.client.list_object_versions( Bucket=bucket.name, Prefix=object_key, MaxKeys=1 ) if "DeleteMarkers" in response: latest_version = response["DeleteMarkers"][0] if latest_version["IsLatest"]: logger.info( "Object %s was indeed deleted on %s. Let's revive it.", object_key, latest_version["LastModified"], ) obj = bucket.Object(object_key) obj.Version(latest_version["VersionId"]).delete() logger.info( "Revived %s, active version is now %s with body '%s'", object_key, obj.version_id, obj.get()["Body"].read(), ) else: logger.warning( "Delete marker is not the latest version for %s!", object_key ) elif "Versions" in response: logger.warning("Got an active version for %s, nothing to do.", object_key) else: logger.error("Couldn't get any version info for %s.", object_key)
Cree un controlador Lambda que elimine un marcador de eliminación de un objeto de S3. Este controlador se puede utilizar para limpiar de forma eficiente marcadores de eliminación extraños en un bucket con control de versiones.
import logging from urllib import parse import boto3 from botocore.exceptions import ClientError logger = logging.getLogger(__name__) logger.setLevel("INFO") s3 = boto3.client("s3") def lambda_handler(event, context): """ Removes a delete marker from the specified versioned object. :param event: The S3 batch event that contains the ID of the delete marker to remove. :param context: Context about the event. :return: A result structure that Amazon S3 uses to interpret the result of the operation. When the result code is TemporaryFailure, S3 retries the operation. """ # Parse job parameters from Amazon S3 batch operations invocation_id = event["invocationId"] invocation_schema_version = event["invocationSchemaVersion"] results = [] result_code = None result_string = None task = event["tasks"][0] task_id = task["taskId"] try: obj_key = parse.unquote(task["s3Key"], encoding="utf-8") obj_version_id = task["s3VersionId"] bucket_name = task["s3BucketArn"].split(":")[-1] logger.info( "Got task: remove delete marker %s from object %s.", obj_version_id, obj_key ) try: # If this call does not raise an error, the object version is not a delete # marker and should not be deleted. response = s3.head_object( Bucket=bucket_name, Key=obj_key, VersionId=obj_version_id ) result_code = "PermanentFailure" result_string = ( f"Object {obj_key}, ID {obj_version_id} is not " f"a delete marker." ) logger.debug(response) logger.warning(result_string) except ClientError as error: delete_marker = error.response["ResponseMetadata"]["HTTPHeaders"].get( "x-amz-delete-marker", "false" ) if delete_marker == "true": logger.info( "Object %s, version %s is a delete marker.", obj_key, obj_version_id ) try: s3.delete_object( Bucket=bucket_name, Key=obj_key, VersionId=obj_version_id ) result_code = "Succeeded" result_string = ( f"Successfully removed delete marker " f"{obj_version_id} from object {obj_key}." ) logger.info(result_string) except ClientError as error: # Mark request timeout as a temporary failure so it will be retried. if error.response["Error"]["Code"] == "RequestTimeout": result_code = "TemporaryFailure" result_string = ( f"Attempt to remove delete marker from " f"object {obj_key} timed out." ) logger.info(result_string) else: raise else: raise ValueError( f"The x-amz-delete-marker header is either not " f"present or is not 'true'." ) except Exception as error: # Mark all other exceptions as permanent failures. result_code = "PermanentFailure" result_string = str(error) logger.exception(error) finally: results.append( { "taskId": task_id, "resultCode": result_code, "resultString": result_string, } ) return { "invocationSchemaVersion": invocation_schema_version, "treatMissingKeysAs": "PermanentFailure", "invocationId": invocation_id, "results": results, }
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Para obtener más información sobre la API, consulta DeleteObjectla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar DeleteObjects
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- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. Elimine un conjunto de objetos mediante una lista de claves de objeto.
class ObjectWrapper: """Encapsulates S3 object actions.""" def __init__(self, s3_object): """ :param s3_object: A Boto3 Object resource. This is a high-level resource in Boto3 that wraps object actions in a class-like structure. """ self.object = s3_object self.key = self.object.key @staticmethod def delete_objects(bucket, object_keys): """ Removes a list of objects from a bucket. This operation is done as a batch in a single request. :param bucket: The bucket that contains the objects. This is a Boto3 Bucket resource. :param object_keys: The list of keys that identify the objects to remove. :return: The response that contains data about which objects were deleted and any that could not be deleted. """ try: response = bucket.delete_objects( Delete={"Objects": [{"Key": key} for key in object_keys]} ) if "Deleted" in response: logger.info( "Deleted objects '%s' from bucket '%s'.", [del_obj["Key"] for del_obj in response["Deleted"]], bucket.name, ) if "Errors" in response: logger.warning( "Could not delete objects '%s' from bucket '%s'.", [ f"{del_obj['Key']}: {del_obj['Code']}" for del_obj in response["Errors"] ], bucket.name, ) except ClientError: logger.exception("Couldn't delete any objects from bucket %s.", bucket.name) raise else: return response
Elimine todos los objetos de un bucket.
class ObjectWrapper: """Encapsulates S3 object actions.""" def __init__(self, s3_object): """ :param s3_object: A Boto3 Object resource. This is a high-level resource in Boto3 that wraps object actions in a class-like structure. """ self.object = s3_object self.key = self.object.key @staticmethod def empty_bucket(bucket): """ Remove all objects from a bucket. :param bucket: The bucket to empty. This is a Boto3 Bucket resource. """ try: bucket.objects.delete() logger.info("Emptied bucket '%s'.", bucket.name) except ClientError: logger.exception("Couldn't empty bucket '%s'.", bucket.name) raise
Elimine de forma permanente un objeto con control de versiones mediante la eliminación de todas sus versiones.
def permanently_delete_object(bucket, object_key): """ Permanently deletes a versioned object by deleting all of its versions. Usage is shown in the usage_demo_single_object function at the end of this module. :param bucket: The bucket that contains the object. :param object_key: The object to delete. """ try: bucket.object_versions.filter(Prefix=object_key).delete() logger.info("Permanently deleted all versions of object %s.", object_key) except ClientError: logger.exception("Couldn't delete all versions of %s.", object_key) raise
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Para obtener más información sobre la API, consulta DeleteObjectsla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar GetBucketAcl
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- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class BucketWrapper: """Encapsulates S3 bucket actions.""" def __init__(self, bucket): """ :param bucket: A Boto3 Bucket resource. This is a high-level resource in Boto3 that wraps bucket actions in a class-like structure. """ self.bucket = bucket self.name = bucket.name def get_acl(self): """ Get the ACL of the bucket. :return: The ACL of the bucket. """ try: acl = self.bucket.Acl() logger.info( "Got ACL for bucket %s. Owner is %s.", self.bucket.name, acl.owner ) except ClientError: logger.exception("Couldn't get ACL for bucket %s.", self.bucket.name) raise else: return acl
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Para obtener más información sobre la API, consulta GetBucketAclla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar GetBucketCors
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- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class BucketWrapper: """Encapsulates S3 bucket actions.""" def __init__(self, bucket): """ :param bucket: A Boto3 Bucket resource. This is a high-level resource in Boto3 that wraps bucket actions in a class-like structure. """ self.bucket = bucket self.name = bucket.name def get_cors(self): """ Get the CORS rules for the bucket. :return The CORS rules for the specified bucket. """ try: cors = self.bucket.Cors() logger.info( "Got CORS rules %s for bucket '%s'.", cors.cors_rules, self.bucket.name ) except ClientError: logger.exception(("Couldn't get CORS for bucket %s.", self.bucket.name)) raise else: return cors
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Para obtener más información sobre la API, consulta GetBucketCorsla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar GetBucketLifecycleConfiguration
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- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class BucketWrapper: """Encapsulates S3 bucket actions.""" def __init__(self, bucket): """ :param bucket: A Boto3 Bucket resource. This is a high-level resource in Boto3 that wraps bucket actions in a class-like structure. """ self.bucket = bucket self.name = bucket.name def get_lifecycle_configuration(self): """ Get the lifecycle configuration of the bucket. :return: The lifecycle rules of the specified bucket. """ try: config = self.bucket.LifecycleConfiguration() logger.info( "Got lifecycle rules %s for bucket '%s'.", config.rules, self.bucket.name, ) except: logger.exception( "Couldn't get lifecycle rules for bucket '%s'.", self.bucket.name ) raise else: return config.rules
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Para obtener más información sobre la API, consulta GetBucketLifecycleConfigurationla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar GetBucketPolicy
.
- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class BucketWrapper: """Encapsulates S3 bucket actions.""" def __init__(self, bucket): """ :param bucket: A Boto3 Bucket resource. This is a high-level resource in Boto3 that wraps bucket actions in a class-like structure. """ self.bucket = bucket self.name = bucket.name def get_policy(self): """ Get the security policy of the bucket. :return: The security policy of the specified bucket, in JSON format. """ try: policy = self.bucket.Policy() logger.info( "Got policy %s for bucket '%s'.", policy.policy, self.bucket.name ) except ClientError: logger.exception("Couldn't get policy for bucket '%s'.", self.bucket.name) raise else: return json.loads(policy.policy)
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Para obtener más información sobre la API, consulta GetBucketPolicyla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar GetObject
.
- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class ObjectWrapper: """Encapsulates S3 object actions.""" def __init__(self, s3_object): """ :param s3_object: A Boto3 Object resource. This is a high-level resource in Boto3 that wraps object actions in a class-like structure. """ self.object = s3_object self.key = self.object.key def get(self): """ Gets the object. :return: The object data in bytes. """ try: body = self.object.get()["Body"].read() logger.info( "Got object '%s' from bucket '%s'.", self.object.key, self.object.bucket_name, ) except ClientError: logger.exception( "Couldn't get object '%s' from bucket '%s'.", self.object.key, self.object.bucket_name, ) raise else: return body
Obtenga un objeto mediante una solicitud condicional.
class S3ConditionalRequests: """Encapsulates S3 conditional request operations.""" def __init__(self, s3_client): self.s3 = s3_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ s3_client = boto3.client("s3") return cls(s3_client) def get_object_conditional( self, object_key: str, source_bucket: str, condition_type: str, condition_value: str, ): """ Retrieves an object from Amazon S3 with a conditional request. :param object_key: The key of the object to retrieve. :param source_bucket: The source bucket of the object. :param condition_type: The type of condition: 'IfMatch', 'IfNoneMatch', 'IfModifiedSince', 'IfUnmodifiedSince'. :param condition_value: The value to use for the condition. """ try: response = self.s3.get_object( Bucket=source_bucket, Key=object_key, **{condition_type: condition_value}, ) sample_bytes = response["Body"].read(20) print( f"\tConditional read successful. Here are the first 20 bytes of the object:\n" ) print(f"\t{sample_bytes}") except ClientError as e: error_code = e.response["Error"]["Code"] if error_code == "PreconditionFailed": print("\tConditional read failed: Precondition failed") elif error_code == "304": # Not modified error code. print("\tConditional read failed: Object not modified") else: logger.error(f"Unexpected error: {error_code}") raise
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Para obtener más información sobre la API, consulta GetObjectla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar GetObjectAcl
.
- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class ObjectWrapper: """Encapsulates S3 object actions.""" def __init__(self, s3_object): """ :param s3_object: A Boto3 Object resource. This is a high-level resource in Boto3 that wraps object actions in a class-like structure. """ self.object = s3_object self.key = self.object.key def get_acl(self): """ Gets the ACL of the object. :return: The ACL of the object. """ try: acl = self.object.Acl() logger.info( "Got ACL for object %s owned by %s.", self.object.key, acl.owner["DisplayName"], ) except ClientError: logger.exception("Couldn't get ACL for object %s.", self.object.key) raise else: return acl
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Para obtener más información sobre la API, consulta GetObjectAclla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar GetObjectLegalHold
.
- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. Ponga una retención legal en un objeto.
def get_legal_hold(s3_client, bucket: str, key: str) -> None: """ Get the legal hold status of a specific file in a bucket. Args: s3_client: Boto3 S3 client. bucket: The name of the bucket containing the file. key: The key of the file to get the legal hold status of. """ print() logger.info("Getting legal hold status of file [%s] in bucket [%s]", key, bucket) try: response = s3_client.get_object_legal_hold(Bucket=bucket, Key=key) legal_hold_status = response["LegalHold"]["Status"] logger.debug( "Legal hold status of file [%s] in bucket [%s] is [%s]", key, bucket, legal_hold_status, ) except Exception as e: logger.error( "Failed to get legal hold status of file [%s] in bucket [%s]: %s", key, bucket, e, )
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Para obtener más información sobre la API, consulta GetObjectLegalHoldla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar GetObjectLockConfiguration
.
- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. Obtenga la configuración de bloqueo de objetos.
def is_object_lock_enabled(s3_client, bucket: str) -> bool: """ Check if object lock is enabled for a bucket. Args: s3_client: Boto3 S3 client. bucket: The name of the bucket to check. Returns: True if object lock is enabled, False otherwise. """ try: response = s3_client.get_object_lock_configuration(Bucket=bucket) return ( "ObjectLockConfiguration" in response and response["ObjectLockConfiguration"]["ObjectLockEnabled"] == "Enabled" ) except s3_client.exceptions.ClientError as e: if e.response["Error"]["Code"] == "ObjectLockConfigurationNotFoundError": return False else: raise
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Para obtener más información sobre la API, consulta GetObjectLockConfigurationla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar HeadBucket
.
- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class BucketWrapper: """Encapsulates S3 bucket actions.""" def __init__(self, bucket): """ :param bucket: A Boto3 Bucket resource. This is a high-level resource in Boto3 that wraps bucket actions in a class-like structure. """ self.bucket = bucket self.name = bucket.name def exists(self): """ Determine whether the bucket exists and you have access to it. :return: True when the bucket exists; otherwise, False. """ try: self.bucket.meta.client.head_bucket(Bucket=self.bucket.name) logger.info("Bucket %s exists.", self.bucket.name) exists = True except ClientError: logger.warning( "Bucket %s doesn't exist or you don't have access to it.", self.bucket.name, ) exists = False return exists
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Para obtener más información sobre la API, consulta HeadBucketla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar ListBuckets
.
- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class BucketWrapper: """Encapsulates S3 bucket actions.""" def __init__(self, bucket): """ :param bucket: A Boto3 Bucket resource. This is a high-level resource in Boto3 that wraps bucket actions in a class-like structure. """ self.bucket = bucket self.name = bucket.name @staticmethod def list(s3_resource): """ Get the buckets in all Regions for the current account. :param s3_resource: A Boto3 S3 resource. This is a high-level resource in Boto3 that contains collections and factory methods to create other high-level S3 sub-resources. :return: The list of buckets. """ try: buckets = list(s3_resource.buckets.all()) logger.info("Got buckets: %s.", buckets) except ClientError: logger.exception("Couldn't get buckets.") raise else: return buckets
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Para obtener más información sobre la API, consulta ListBucketsla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar ListObjectsV2
.
- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class ObjectWrapper: """Encapsulates S3 object actions.""" def __init__(self, s3_object): """ :param s3_object: A Boto3 Object resource. This is a high-level resource in Boto3 that wraps object actions in a class-like structure. """ self.object = s3_object self.key = self.object.key @staticmethod def list(bucket, prefix=None): """ Lists the objects in a bucket, optionally filtered by a prefix. :param bucket: The bucket to query. This is a Boto3 Bucket resource. :param prefix: When specified, only objects that start with this prefix are listed. :return: The list of objects. """ try: if not prefix: objects = list(bucket.objects.all()) else: objects = list(bucket.objects.filter(Prefix=prefix)) logger.info( "Got objects %s from bucket '%s'", [o.key for o in objects], bucket.name ) except ClientError: logger.exception("Couldn't get objects for bucket '%s'.", bucket.name) raise else: return objects
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Para obtener más información sobre la API, consulta ListObjectsla versión 2 en la Referencia de API de AWS SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar PutBucketAcl
.
- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class BucketWrapper: """Encapsulates S3 bucket actions.""" def __init__(self, bucket): """ :param bucket: A Boto3 Bucket resource. This is a high-level resource in Boto3 that wraps bucket actions in a class-like structure. """ self.bucket = bucket self.name = bucket.name def grant_log_delivery_access(self): """ Grant the AWS Log Delivery group write access to the bucket so that Amazon S3 can deliver access logs to the bucket. This is the only recommended use of an S3 bucket ACL. """ try: acl = self.bucket.Acl() # Putting an ACL overwrites the existing ACL. If you want to preserve # existing grants, append new grants to the list of existing grants. grants = acl.grants if acl.grants else [] grants.append( { "Grantee": { "Type": "Group", "URI": "http://acs.amazonaws.com/groups/s3/LogDelivery", }, "Permission": "WRITE", } ) acl.put(AccessControlPolicy={"Grants": grants, "Owner": acl.owner}) logger.info("Granted log delivery access to bucket '%s'", self.bucket.name) except ClientError: logger.exception("Couldn't add ACL to bucket '%s'.", self.bucket.name) raise
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Para obtener más información sobre la API, consulta PutBucketAclla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar PutBucketCors
.
- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class BucketWrapper: """Encapsulates S3 bucket actions.""" def __init__(self, bucket): """ :param bucket: A Boto3 Bucket resource. This is a high-level resource in Boto3 that wraps bucket actions in a class-like structure. """ self.bucket = bucket self.name = bucket.name def put_cors(self, cors_rules): """ Apply CORS rules to the bucket. CORS rules specify the HTTP actions that are allowed from other domains. :param cors_rules: The CORS rules to apply. """ try: self.bucket.Cors().put(CORSConfiguration={"CORSRules": cors_rules}) logger.info( "Put CORS rules %s for bucket '%s'.", cors_rules, self.bucket.name ) except ClientError: logger.exception("Couldn't put CORS rules for bucket %s.", self.bucket.name) raise
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Para obtener más información sobre la API, consulta PutBucketCorsla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar PutBucketLifecycleConfiguration
.
- SDK para Python (Boto3)
-
nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class BucketWrapper: """Encapsulates S3 bucket actions.""" def __init__(self, bucket): """ :param bucket: A Boto3 Bucket resource. This is a high-level resource in Boto3 that wraps bucket actions in a class-like structure. """ self.bucket = bucket self.name = bucket.name def put_lifecycle_configuration(self, lifecycle_rules): """ Apply a lifecycle configuration to the bucket. The lifecycle configuration can be used to archive or delete the objects in the bucket according to specified parameters, such as a number of days. :param lifecycle_rules: The lifecycle rules to apply. """ try: self.bucket.LifecycleConfiguration().put( LifecycleConfiguration={"Rules": lifecycle_rules} ) logger.info( "Put lifecycle rules %s for bucket '%s'.", lifecycle_rules, self.bucket.name, ) except ClientError: logger.exception( "Couldn't put lifecycle rules for bucket '%s'.", self.bucket.name ) raise
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Para obtener más información sobre la API, consulta PutBucketLifecycleConfigurationla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar PutBucketPolicy
.
- SDK para Python (Boto3)
-
nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class BucketWrapper: """Encapsulates S3 bucket actions.""" def __init__(self, bucket): """ :param bucket: A Boto3 Bucket resource. This is a high-level resource in Boto3 that wraps bucket actions in a class-like structure. """ self.bucket = bucket self.name = bucket.name def put_policy(self, policy): """ Apply a security policy to the bucket. Policies control users' ability to perform specific actions, such as listing the objects in the bucket. :param policy: The policy to apply to the bucket. """ try: self.bucket.Policy().put(Policy=json.dumps(policy)) logger.info("Put policy %s for bucket '%s'.", policy, self.bucket.name) except ClientError: logger.exception("Couldn't apply policy to bucket '%s'.", self.bucket.name) raise
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Para obtener más información sobre la API, consulta PutBucketPolicyla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar PutObject
.
- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class ObjectWrapper: """Encapsulates S3 object actions.""" def __init__(self, s3_object): """ :param s3_object: A Boto3 Object resource. This is a high-level resource in Boto3 that wraps object actions in a class-like structure. """ self.object = s3_object self.key = self.object.key def put(self, data): """ Upload data to the object. :param data: The data to upload. This can either be bytes or a string. When this argument is a string, it is interpreted as a file name, which is opened in read bytes mode. """ put_data = data if isinstance(data, str): try: put_data = open(data, "rb") except IOError: logger.exception("Expected file name or binary data, got '%s'.", data) raise try: self.object.put(Body=put_data) self.object.wait_until_exists() logger.info( "Put object '%s' to bucket '%s'.", self.object.key, self.object.bucket_name, ) except ClientError: logger.exception( "Couldn't put object '%s' to bucket '%s'.", self.object.key, self.object.bucket_name, ) raise finally: if getattr(put_data, "close", None): put_data.close()
Carga un objeto mediante una solicitud condicional.
class S3ConditionalRequests: """Encapsulates S3 conditional request operations.""" def __init__(self, s3_client): self.s3 = s3_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ s3_client = boto3.client("s3") return cls(s3_client) def put_object_conditional(self, object_key: str, source_bucket: str, data: bytes): """ Uploads an object to Amazon S3 with a conditional request. Prevents overwrite using an IfNoneMatch condition for the object key. :param object_key: The key of the object to upload. :param source_bucket: The source bucket of the object. :param data: The data to upload. """ try: self.s3.put_object( Bucket=source_bucket, Key=object_key, Body=data, IfNoneMatch="*" ) print( f"\tConditional write successful for key {object_key} in bucket {source_bucket}." ) except ClientError as e: error_code = e.response["Error"]["Code"] if error_code == "PreconditionFailed": print("\tConditional write failed: Precondition failed") else: logger.error(f"Unexpected error: {error_code}") raise
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Para obtener más información sobre la API, consulta PutObjectla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar PutObjectAcl
.
- SDK para Python (Boto3)
-
nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. class ObjectWrapper: """Encapsulates S3 object actions.""" def __init__(self, s3_object): """ :param s3_object: A Boto3 Object resource. This is a high-level resource in Boto3 that wraps object actions in a class-like structure. """ self.object = s3_object self.key = self.object.key def put_acl(self, email): """ Applies an ACL to the object that grants read access to an AWS user identified by email address. :param email: The email address of the user to grant access. """ try: acl = self.object.Acl() # Putting an ACL overwrites the existing ACL, so append new grants # if you want to preserve existing grants. grants = acl.grants if acl.grants else [] grants.append( { "Grantee": {"Type": "AmazonCustomerByEmail", "EmailAddress": email}, "Permission": "READ", } ) acl.put(AccessControlPolicy={"Grants": grants, "Owner": acl.owner}) logger.info("Granted read access to %s.", email) except ClientError: logger.exception("Couldn't add ACL to object '%s'.", self.object.key) raise
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Para obtener más información sobre la API, consulta PutObjectAclla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar PutObjectLegalHold
.
- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. Ponga una retención legal en un objeto.
def set_legal_hold(s3_client, bucket: str, key: str) -> None: """ Set a legal hold on a specific file in a bucket. Args: s3_client: Boto3 S3 client. bucket: The name of the bucket containing the file. key: The key of the file to set the legal hold on. """ print() logger.info("Setting legal hold on file [%s] in bucket [%s]", key, bucket) try: before_status = "OFF" after_status = "ON" s3_client.put_object_legal_hold( Bucket=bucket, Key=key, LegalHold={"Status": after_status} ) logger.debug( "Legal hold set successfully on file [%s] in bucket [%s]", key, bucket ) _print_legal_hold_update(bucket, key, before_status, after_status) except Exception as e: logger.error( "Failed to set legal hold on file [%s] in bucket [%s]: %s", key, bucket, e )
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Para obtener más información sobre la API, consulta PutObjectLegalHoldla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar PutObjectLockConfiguration
.
- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. Configuración de la activación del bloqueo de objetos.
s3_client.put_object_lock_configuration( Bucket=bucket, ObjectLockConfiguration={"ObjectLockEnabled": "Disabled", "Rule": {}}, )
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Para obtener más información sobre la API, consulta PutObjectLockConfigurationla AWS Referencia de API de SDK for Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo utilizar PutObjectRetention
.
- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. Ponga un retención de objeto.
s3_client.put_object_retention( Bucket=bucket, Key=key, VersionId=version_id, Retention={"Mode": "GOVERNANCE", "RetainUntilDate": far_future_date}, BypassGovernanceRetention=True, )
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Para obtener más información sobre la API, consulta PutObjectRetentionla AWS Referencia de API de SDK for Python (Boto3).
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Escenarios
En el siguiente ejemplo de código se muestra cómo crear una URL prefirmada para Amazon S3 y cargar un objeto.
- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. Genere una URL prefirmada que pueda realizar una acción de S3 durante un tiempo limitado. Utilice el paquete Requests para realizar una solicitud con la URL.
import argparse import logging import boto3 from botocore.exceptions import ClientError import requests logger = logging.getLogger(__name__) def generate_presigned_url(s3_client, client_method, method_parameters, expires_in): """ Generate a presigned Amazon S3 URL that can be used to perform an action. :param s3_client: A Boto3 Amazon S3 client. :param client_method: The name of the client method that the URL performs. :param method_parameters: The parameters of the specified client method. :param expires_in: The number of seconds the presigned URL is valid for. :return: The presigned URL. """ try: url = s3_client.generate_presigned_url( ClientMethod=client_method, Params=method_parameters, ExpiresIn=expires_in ) logger.info("Got presigned URL: %s", url) except ClientError: logger.exception( "Couldn't get a presigned URL for client method '%s'.", client_method ) raise return url def usage_demo(): logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s") print("-" * 88) print("Welcome to the Amazon S3 presigned URL demo.") print("-" * 88) parser = argparse.ArgumentParser() parser.add_argument("bucket", help="The name of the bucket.") parser.add_argument( "key", help="For a GET operation, the key of the object in Amazon S3. For a " "PUT operation, the name of a file to upload.", ) parser.add_argument("action", choices=("get", "put"), help="The action to perform.") args = parser.parse_args() s3_client = boto3.client("s3") client_action = "get_object" if args.action == "get" else "put_object" url = generate_presigned_url( s3_client, client_action, {"Bucket": args.bucket, "Key": args.key}, 1000 ) print("Using the Requests package to send a request to the URL.") response = None if args.action == "get": response = requests.get(url) if response.status_code == 200: with open(args.key.split("/")[-1], 'wb') as object_file: object_file.write(response.content) elif args.action == "put": print("Putting data to the URL.") try: with open(args.key, "rb") as object_file: object_text = object_file.read() response = requests.put(url, data=object_text) except FileNotFoundError: print( f"Couldn't find {args.key}. For a PUT operation, the key must be the " f"name of a file that exists on your computer." ) if response is not None: print(f"Status: {response.status_code}\nReason: {response.reason}") print("-" * 88) if __name__ == "__main__": usage_demo()
Genere una solicitud POST prefirmada para cargar un archivo.
class BucketWrapper: """Encapsulates S3 bucket actions.""" def __init__(self, bucket): """ :param bucket: A Boto3 Bucket resource. This is a high-level resource in Boto3 that wraps bucket actions in a class-like structure. """ self.bucket = bucket self.name = bucket.name def generate_presigned_post(self, object_key, expires_in): """ Generate a presigned Amazon S3 POST request to upload a file. A presigned POST can be used for a limited time to let someone without an AWS account upload a file to a bucket. :param object_key: The object key to identify the uploaded object. :param expires_in: The number of seconds the presigned POST is valid. :return: A dictionary that contains the URL and form fields that contain required access data. """ try: response = self.bucket.meta.client.generate_presigned_post( Bucket=self.bucket.name, Key=object_key, ExpiresIn=expires_in ) logger.info("Got presigned POST URL: %s", response["url"]) except ClientError: logger.exception( "Couldn't get a presigned POST URL for bucket '%s' and object '%s'", self.bucket.name, object_key, ) raise return response
El siguiente ejemplo de código muestra cómo explorar los resultados de Amazon Textract a través de una aplicación interactiva.
- SDK para Python (Boto3)
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Muestra cómo utilizar Amazon Textract para detectar elementos de texto, formulario y tabla en una imagen de documento. AWS SDK for Python (Boto3) La imagen de entrada y la salida de Amazon Textract aparecen en una aplicación Tkinter que permite explorar los elementos detectados.
Envía la imagen de un documento a Amazon Textract y explora el resultado de los elementos detectados.
Envía imágenes directamente a Amazon Textract o mediante un bucket de Amazon Simple Storage Service (Amazon S3).
Utilice la función asincrónica APIs para iniciar un trabajo que publique una notificación en un tema del Amazon Simple Notification Service (Amazon SNS) cuando se complete el trabajo.
Consulta una cola de Amazon Simple Queue Service (Amazon SQS) en busca de un mensaje de finalización de trabajo y muestra los resultados.
Para obtener el código fuente completo y las instrucciones sobre cómo configurarlo y ejecutarlo, consulte el ejemplo completo en. GitHub
Servicios utilizados en este ejemplo
Amazon S3
Amazon SNS
Amazon SQS
Amazon Textract
En el siguiente ejemplo de código, se muestra cómo utilizar Amazon Comprehend para detectar entidades en el texto extraído por Amazon Textract Texact de una imagen almacenada en Amazon S3.
- SDK para Python (Boto3)
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Muestra cómo usarlo AWS SDK for Python (Boto3) en un cuaderno de Jupyter para detectar entidades en el texto extraído de una imagen. En este ejemplo, se utiliza Amazon Textract para extraer texto de una imagen almacenada en Amazon Simple Storage Service (Amazon S3) y Amazon Comprehend para detectar entidades en el texto extraído.
Este ejemplo es un bloc de notas Jupyter y debe ejecutarse en un entorno que pueda alojar blocs de notas. Para obtener instrucciones sobre cómo ejecutar el ejemplo con Amazon SageMaker AI, consulta las instrucciones que aparecen en el TextractAndComprehendNotebookarchivo.ipynb
. Para obtener el código fuente completo y las instrucciones sobre cómo configurarlo y ejecutarlo, consulte el ejemplo completo en. GitHub
Servicios utilizados en este ejemplo
Amazon Comprehend
Amazon S3
Amazon Textract
El siguiente ejemplo de código muestra cómo crear una aplicación que utilice Amazon Rekognition para detectar objetos por categoría en las imágenes.
- SDK para Python (Boto3)
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Le muestra cómo usarlo AWS SDK for Python (Boto3) para crear una aplicación web que le permita hacer lo siguiente:
Subir fotos en un bucket de Amazon Simple Storage Service (Amazon S3).
Utilizar Amazon Rekognition para analizar y etiquetar las fotos.
Utilice Amazon Simple Email Service (Amazon SES) para enviar informes de análisis de imágenes por correo electrónico.
Este ejemplo contiene dos componentes principales: una página web escrita en JavaScript React y un servicio REST escrito en Python creado con Flask-RESTful.
Puede utilizar la página web de React para:
Mostrar una lista de imágenes almacenadas en el bucket de S3.
Subir imágenes desde la computadora en el bucket de S3.
Mostrar imágenes y etiquetas que identifican los elementos detectados en la imagen.
Obtener un informe de todas las imágenes del bucket de S3 y enviar un correo electrónico del informe.
La página web llama al servicio REST. El servicio envía solicitudes a AWS para llevar a cabo las siguientes acciones:
Obtener y filtrar la lista de imágenes del bucket de S3.
Subir fotos en el bucket de S3.
Utilizar Amazon Rekognition para analizar fotos individuales y obtener una lista de etiquetas que identifican los elementos detectados en la foto.
Analizar todas las fotos del bucket de S3 y usar Amazon SES para enviar un informe por correo electrónico.
Para ver el código fuente completo y las instrucciones sobre cómo configurarlo y ejecutarlo, consulta el ejemplo completo en GitHub
. Servicios utilizados en este ejemplo
Amazon Rekognition
Amazon S3
Amazon SES
El siguiente ejemplo de código muestra cómo añadir condiciones previas a las solicitudes de Amazon S3.
- SDK para Python (Boto3)
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nota
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. Ejecute un escenario interactivo que demuestre las solicitudes condicionales de Amazon S3.
""" Purpose Shows how to use AWS SDK for Python (Boto3) to get started using conditional requests for Amazon Simple Storage Service (Amazon S3). """ import logging import random import sys import datetime import boto3 from botocore.exceptions import ClientError from s3_conditional_requests import S3ConditionalRequests # Add relative path to include demo_tools in this code example without need for setup. sys.path.append("../../../..") import demo_tools.question as q # noqa # Constants FILE_CONTENT = "This is a test file for S3 conditional requests." RANDOM_SUFFIX = str(random.randint(100, 999)) logger = logging.getLogger(__name__) class ConditionalRequestsScenario: """Runs a scenario that shows how to use S3 Conditional Requests.""" def __init__(self, conditional_requests, s3_client): """ :param conditional_requests: An object that wraps S3 conditional request actions. :param s3_client: A Boto3 S3 client for setup and cleanup operations. """ self.conditional_requests = conditional_requests self.s3_client = s3_client def setup_scenario(self, source_bucket: str, dest_bucket: str, object_key: str): """ Sets up the scenario by creating a source and destination bucket. Prompts the user to provide a bucket name prefix. :param source_bucket: The name of the source bucket. :param dest_bucket: The name of the destination bucket. :param object_key: The name of a test file to add to the source bucket. """ # Create the buckets. try: self.s3_client.create_bucket(Bucket=source_bucket) self.s3_client.create_bucket(Bucket=dest_bucket) print( f"Created source bucket: {source_bucket} and destination bucket: {dest_bucket}" ) except ClientError as e: error_code = e.response["Error"]["Code"] logger.error(f"Error creating buckets: {error_code}") raise # Upload test file into the source bucket. try: print(f"Uploading file {object_key} to bucket {source_bucket}") response = self.s3_client.put_object( Bucket=source_bucket, Key=object_key, Body=FILE_CONTENT ) object_etag = response["ETag"] return object_etag except Exception as e: logger.error( f"Failed to upload file {object_key} to bucket {source_bucket}: {e}" ) def cleanup_scenario(self, source_bucket: str, dest_bucket: str): """ Cleans up the scenario by deleting the source and destination buckets. :param source_bucket: The name of the source bucket. :param dest_bucket: The name of the destination bucket. """ self.cleanup_bucket(source_bucket) self.cleanup_bucket(dest_bucket) def cleanup_bucket(self, bucket_name: str): """ Cleans up the bucket by deleting all objects and then the bucket itself. :param bucket_name: The name of the bucket. """ try: # Get list of all objects in the bucket. list_response = self.s3_client.list_objects_v2(Bucket=bucket_name) objs = list_response.get("Contents", []) for obj in objs: key = obj["Key"] self.s3_client.delete_object(Bucket=bucket_name, Key=key) self.s3_client.delete_bucket(Bucket=bucket_name) print(f"Cleaned up bucket: {bucket_name}.") except ClientError as e: error_code = e.response["Error"]["Code"] if error_code == "NoSuchBucket": logger.info(f"Bucket {bucket_name} does not exist, skipping cleanup.") else: logger.error(f"Error deleting bucket: {error_code}") raise def display_buckets(self, source_bucket: str, dest_bucket: str): """ Display a list of the objects in the test buckets. :param source_bucket: The name of the source bucket. :param dest_bucket: The name of the destination bucket. """ self.list_bucket_contents(source_bucket) self.list_bucket_contents(dest_bucket) def list_bucket_contents(self, bucket_name): """ Display a list of the objects in the bucket. :param bucket_name: The name of the bucket. """ try: # Get list of all objects in the bucket. print(f"\t Items in bucket {bucket_name}") list_response = self.s3_client.list_objects_v2(Bucket=bucket_name) objs = list_response.get("Contents", []) if not objs: print("\t\tNo objects found.") for obj in objs: key = obj["Key"] print(f"\t\t object: {key} ETag {obj['ETag']}") return objs except ClientError as e: error_code = e.response["Error"]["Code"] if error_code == "NoSuchBucket": logger.info(f"Bucket {bucket_name} does not exist.") else: logger.error(f"Error listing bucket and objects: {error_code}") raise def display_menu( self, source_bucket: str, dest_bucket: str, object_key: str, etag: str ): """ Displays the menu of conditional request options for the user. :param source_bucket: The name of the source bucket. :param dest_bucket: The name of the destination bucket. :param object_key: The key of the test object in the source bucket. :param etag: The etag of the test object in the source bucket. """ actions = [ "Print list of bucket items.", "Perform a conditional read.", "Perform a conditional copy.", "Perform a conditional write.", "Clean up and exit.", ] conditions = [ "If-Match: using the object's ETag. This condition should succeed.", "If-None-Match: using the object's ETag. This condition should fail.", "If-Modified-Since: using yesterday's date. This condition should succeed.", "If-Unmodified-Since: using yesterday's date. This condition should fail.", ] condition_types = [ "IfMatch", "IfNoneMatch", "IfModifiedSince", "IfUnmodifiedSince", ] copy_condition_types = [ "CopySourceIfMatch", "CopySourceIfNoneMatch", "CopySourceIfModifiedSince", "CopySourceIfUnmodifiedSince", ] yesterday_date = datetime.datetime.utcnow() - datetime.timedelta(days=1) choice = 0 while choice != 4: print("-" * 88) print("Choose an action to explore some example conditional requests.") choice = q.choose("Which action would you like to take? ", actions) if choice == 0: print("Listing the objects and buckets.") self.display_buckets(source_bucket, dest_bucket) elif choice == 1: print("Perform a conditional read.") condition_type = q.choose("Enter the condition type : ", conditions) if condition_type == 0 or condition_type == 1: self.conditional_requests.get_object_conditional( object_key, source_bucket, condition_types[condition_type], etag ) elif condition_type == 2 or condition_type == 3: self.conditional_requests.get_object_conditional( object_key, source_bucket, condition_types[condition_type], yesterday_date, ) elif choice == 2: print("Perform a conditional copy.") condition_type = q.choose("Enter the condition type : ", conditions) dest_key = q.ask("Enter an object key: ", q.non_empty) if condition_type == 0 or condition_type == 1: self.conditional_requests.copy_object_conditional( object_key, dest_key, source_bucket, dest_bucket, copy_condition_types[condition_type], etag, ) elif condition_type == 2 or condition_type == 3: self.conditional_requests.copy_object_conditional( object_key, dest_key, copy_condition_types[condition_type], yesterday_date, ) elif choice == 3: print( "Perform a conditional write using IfNoneMatch condition on the object key." ) print("If the key is a duplicate, the write will fail.") object_key = q.ask("Enter an object key: ", q.non_empty) self.conditional_requests.put_object_conditional( object_key, source_bucket, b"Conditional write example data." ) elif choice == 4: print("Proceeding to cleanup.") def run_scenario(self): """ Runs the interactive scenario. """ print("-" * 88) print("Welcome to the Amazon S3 conditional requests example.") print("-" * 88) print( f"""\ This example demonstrates the use of conditional requests for S3 operations. You can use conditional requests to add preconditions to S3 read requests to return or copy an object based on its Entity tag (ETag), or last modified date. You can use a conditional write requests to prevent overwrites by ensuring there is no existing object with the same key. This example will allow you to perform conditional reads and writes that will succeed or fail based on your selected options. Sample buckets and a sample object will be created as part of the example. """ ) bucket_prefix = q.ask("Enter a bucket name prefix: ", q.non_empty) source_bucket_name = f"{bucket_prefix}-source-{RANDOM_SUFFIX}" dest_bucket_name = f"{bucket_prefix}-dest-{RANDOM_SUFFIX}" object_key = "test-upload-file.txt" try: etag = self.setup_scenario(source_bucket_name, dest_bucket_name, object_key) self.display_menu(source_bucket_name, dest_bucket_name, object_key, etag) finally: self.cleanup_scenario(source_bucket_name, dest_bucket_name) print("-" * 88) print("Thanks for watching.") print("-" * 88) if __name__ == "__main__": scenario = ConditionalRequestsScenario( S3ConditionalRequests.from_client(), boto3.client("s3") ) scenario.run_scenario()
Una clase contenedora que define las operaciones de solicitud condicional.
import boto3 import logging from botocore.exceptions import ClientError # Configure logging logger = logging.getLogger(__name__) class S3ConditionalRequests: """Encapsulates S3 conditional request operations.""" def __init__(self, s3_client): self.s3 = s3_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ s3_client = boto3.client("s3") return cls(s3_client) def get_object_conditional( self, object_key: str, source_bucket: str, condition_type: str, condition_value: str, ): """ Retrieves an object from Amazon S3 with a conditional request. :param object_key: The key of the object to retrieve. :param source_bucket: The source bucket of the object. :param condition_type: The type of condition: 'IfMatch', 'IfNoneMatch', 'IfModifiedSince', 'IfUnmodifiedSince'. :param condition_value: The value to use for the condition. """ try: response = self.s3.get_object( Bucket=source_bucket, Key=object_key, **{condition_type: condition_value}, ) sample_bytes = response["Body"].read(20) print( f"\tConditional read successful. Here are the first 20 bytes of the object:\n" ) print(f"\t{sample_bytes}") except ClientError as e: error_code = e.response["Error"]["Code"] if error_code == "PreconditionFailed": print("\tConditional read failed: Precondition failed") elif error_code == "304": # Not modified error code. print("\tConditional read failed: Object not modified") else: logger.error(f"Unexpected error: {error_code}") raise def put_object_conditional(self, object_key: str, source_bucket: str, data: bytes): """ Uploads an object to Amazon S3 with a conditional request. Prevents overwrite using an IfNoneMatch condition for the object key. :param object_key: The key of the object to upload. :param source_bucket: The source bucket of the object. :param data: The data to upload. """ try: self.s3.put_object( Bucket=source_bucket, Key=object_key, Body=data, IfNoneMatch="*" ) print( f"\tConditional write successful for key {object_key} in bucket {source_bucket}." ) except ClientError as e: error_code = e.response["Error"]["Code"] if error_code == "PreconditionFailed": print("\tConditional write failed: Precondition failed") else: logger.error(f"Unexpected error: {error_code}") raise def copy_object_conditional( self, source_key: str, dest_key: str, source_bucket: str, dest_bucket: str, condition_type: str, condition_value: str, ): """ Copies an object from one Amazon S3 bucket to another with a conditional request. :param source_key: The key of the source object to copy. :param dest_key: The key of the destination object. :param source_bucket: The source bucket of the object. :param dest_bucket: The destination bucket of the object. :param condition_type: The type of condition to apply, e.g. 'CopySourceIfMatch', 'CopySourceIfNoneMatch', 'CopySourceIfModifiedSince', 'CopySourceIfUnmodifiedSince'. :param condition_value: The value to use for the condition. """ try: self.s3.copy_object( Bucket=dest_bucket, Key=dest_key, CopySource={"Bucket": source_bucket, "Key": source_key}, **{condition_type: condition_value}, ) print( f"\tConditional copy successful for key {dest_key} in bucket {dest_bucket}." ) except ClientError as e: error_code = e.response["Error"]["Code"] if error_code == "PreconditionFailed": print("\tConditional copy failed: Precondition failed") elif error_code == "304": # Not modified error code. print("\tConditional copy failed: Object not modified") else: logger.error(f"Unexpected error: {error_code}") raise
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Para obtener información sobre la API, consulte los siguientes temas en la Referencia de la API de AWS SDK para Python (Boto3).
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En el siguiente ejemplo de código, se muestra cómo administrar objetos de S3 con control de versiones en lotes con una función de Lambda.
- SDK para Python (Boto3)
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Muestra cómo manipular objetos versionados de Amazon Simple Storage Service (Amazon S3) en lotes mediante la creación de trabajos que AWS Lambda llaman a funciones para realizar el procesamiento. En este ejemplo se crea un bucket con control de versiones, se cargan las estrofas del poema You Are Old, Father William de Lewis Carroll y se utilizan trabajos por lotes de Amazon S3 para cambiar el poema de varias formas.
Aprenda cómo:
Crear funciones Lambda que funcionen en objetos con control de versiones.
Crear un manifiesto de objetos para actualizar.
Crear trabajos por lotes que invoquen funciones Lambda para actualizar objetos.
Eliminar funciones Lambda.
Vaciar y eliminar un bucket con control de versiones.
La mejor forma de ver este ejemplo es en. GitHub Para obtener el código fuente completo y las instrucciones sobre cómo configurarlo y ejecutarlo, consulte el ejemplo completo en GitHub
. Servicios utilizados en este ejemplo
Amazon S3
En el siguiente ejemplo de código se muestra cómo cargar o descargar archivos grandes en y desde Amazon S3.
Para obtener información, consulte Carga de un objeto con carga multiparte.
- SDK para Python (Boto3)
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nota
Hay más información al respecto GitHub. Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. Cree funciones que transfieran archivos utilizando varios de los ajustes del administrador de transferencias disponibles. Utilice una clase de devolución de llamada para escribir el progreso de la devolución de llamada durante la transferencia de archivos.
import sys import threading import boto3 from boto3.s3.transfer import TransferConfig MB = 1024 * 1024 s3 = boto3.resource("s3") class TransferCallback: """ Handle callbacks from the transfer manager. The transfer manager periodically calls the __call__ method throughout the upload and download process so that it can take action, such as displaying progress to the user and collecting data about the transfer. """ def __init__(self, target_size): self._target_size = target_size self._total_transferred = 0 self._lock = threading.Lock() self.thread_info = {} def __call__(self, bytes_transferred): """ The callback method that is called by the transfer manager. Display progress during file transfer and collect per-thread transfer data. This method can be called by multiple threads, so shared instance data is protected by a thread lock. """ thread = threading.current_thread() with self._lock: self._total_transferred += bytes_transferred if thread.ident not in self.thread_info.keys(): self.thread_info[thread.ident] = bytes_transferred else: self.thread_info[thread.ident] += bytes_transferred target = self._target_size * MB sys.stdout.write( f"\r{self._total_transferred} of {target} transferred " f"({(self._total_transferred / target) * 100:.2f}%)." ) sys.stdout.flush() def upload_with_default_configuration( local_file_path, bucket_name, object_key, file_size_mb ): """ Upload a file from a local folder to an Amazon S3 bucket, using the default configuration. """ transfer_callback = TransferCallback(file_size_mb) s3.Bucket(bucket_name).upload_file( local_file_path, object_key, Callback=transfer_callback ) return transfer_callback.thread_info def upload_with_chunksize_and_meta( local_file_path, bucket_name, object_key, file_size_mb, metadata=None ): """ Upload a file from a local folder to an Amazon S3 bucket, setting a multipart chunk size and adding metadata to the Amazon S3 object. The multipart chunk size controls the size of the chunks of data that are sent in the request. A smaller chunk size typically results in the transfer manager using more threads for the upload. The metadata is a set of key-value pairs that are stored with the object in Amazon S3. """ transfer_callback = TransferCallback(file_size_mb) config = TransferConfig(multipart_chunksize=1 * MB) extra_args = {"Metadata": metadata} if metadata else None s3.Bucket(bucket_name).upload_file( local_file_path, object_key, Config=config, ExtraArgs=extra_args, Callback=transfer_callback, ) return transfer_callback.thread_info def upload_with_high_threshold(local_file_path, bucket_name, object_key, file_size_mb): """ Upload a file from a local folder to an Amazon S3 bucket, setting a multipart threshold larger than the size of the file. Setting a multipart threshold larger than the size of the file results in the transfer manager sending the file as a standard upload instead of a multipart upload. """ transfer_callback = TransferCallback(file_size_mb) config = TransferConfig(multipart_threshold=file_size_mb * 2 * MB) s3.Bucket(bucket_name).upload_file( local_file_path, object_key, Config=config, Callback=transfer_callback ) return transfer_callback.thread_info def upload_with_sse( local_file_path, bucket_name, object_key, file_size_mb, sse_key=None ): """ Upload a file from a local folder to an Amazon S3 bucket, adding server-side encryption with customer-provided encryption keys to the object. When this kind of encryption is specified, Amazon S3 encrypts the object at rest and allows downloads only when the expected encryption key is provided in the download request. """ transfer_callback = TransferCallback(file_size_mb) if sse_key: extra_args = {"SSECustomerAlgorithm": "AES256", "SSECustomerKey": sse_key} else: extra_args = None s3.Bucket(bucket_name).upload_file( local_file_path, object_key, ExtraArgs=extra_args, Callback=transfer_callback ) return transfer_callback.thread_info def download_with_default_configuration( bucket_name, object_key, download_file_path, file_size_mb ): """ Download a file from an Amazon S3 bucket to a local folder, using the default configuration. """ transfer_callback = TransferCallback(file_size_mb) s3.Bucket(bucket_name).Object(object_key).download_file( download_file_path, Callback=transfer_callback ) return transfer_callback.thread_info def download_with_single_thread( bucket_name, object_key, download_file_path, file_size_mb ): """ Download a file from an Amazon S3 bucket to a local folder, using a single thread. """ transfer_callback = TransferCallback(file_size_mb) config = TransferConfig(use_threads=False) s3.Bucket(bucket_name).Object(object_key).download_file( download_file_path, Config=config, Callback=transfer_callback ) return transfer_callback.thread_info def download_with_high_threshold( bucket_name, object_key, download_file_path, file_size_mb ): """ Download a file from an Amazon S3 bucket to a local folder, setting a multipart threshold larger than the size of the file. Setting a multipart threshold larger than the size of the file results in the transfer manager sending the file as a standard download instead of a multipart download. """ transfer_callback = TransferCallback(file_size_mb) config = TransferConfig(multipart_threshold=file_size_mb * 2 * MB) s3.Bucket(bucket_name).Object(object_key).download_file( download_file_path, Config=config, Callback=transfer_callback ) return transfer_callback.thread_info def download_with_sse( bucket_name, object_key, download_file_path, file_size_mb, sse_key ): """ Download a file from an Amazon S3 bucket to a local folder, adding a customer-provided encryption key to the request. When this kind of encryption is specified, Amazon S3 encrypts the object at rest and allows downloads only when the expected encryption key is provided in the download request. """ transfer_callback = TransferCallback(file_size_mb) if sse_key: extra_args = {"SSECustomerAlgorithm": "AES256", "SSECustomerKey": sse_key} else: extra_args = None s3.Bucket(bucket_name).Object(object_key).download_file( download_file_path, ExtraArgs=extra_args, Callback=transfer_callback ) return transfer_callback.thread_info
Demuestre las funciones del administrador de transferencias e informe de los resultados.
import hashlib import os import platform import shutil import time import boto3 from boto3.s3.transfer import TransferConfig from botocore.exceptions import ClientError from botocore.exceptions import ParamValidationError from botocore.exceptions import NoCredentialsError import file_transfer MB = 1024 * 1024 # These configuration attributes affect both uploads and downloads. CONFIG_ATTRS = ( "multipart_threshold", "multipart_chunksize", "max_concurrency", "use_threads", ) # These configuration attributes affect only downloads. DOWNLOAD_CONFIG_ATTRS = ("max_io_queue", "io_chunksize", "num_download_attempts") class TransferDemoManager: """ Manages the demonstration. Collects user input from a command line, reports transfer results, maintains a list of artifacts created during the demonstration, and cleans them up after the demonstration is completed. """ def __init__(self): self._s3 = boto3.resource("s3") self._chore_list = [] self._create_file_cmd = None self._size_multiplier = 0 self.file_size_mb = 30 self.demo_folder = None self.demo_bucket = None self._setup_platform_specific() self._terminal_width = shutil.get_terminal_size(fallback=(80, 80))[0] def collect_user_info(self): """ Collect local folder and Amazon S3 bucket name from the user. These locations are used to store files during the demonstration. """ while not self.demo_folder: self.demo_folder = input( "Which file folder do you want to use to store " "demonstration files? " ) if not os.path.isdir(self.demo_folder): print(f"{self.demo_folder} isn't a folder!") self.demo_folder = None while not self.demo_bucket: self.demo_bucket = input( "Which Amazon S3 bucket do you want to use to store " "demonstration files? " ) try: self._s3.meta.client.head_bucket(Bucket=self.demo_bucket) except ParamValidationError as err: print(err) self.demo_bucket = None except ClientError as err: print(err) print( f"Either {self.demo_bucket} doesn't exist or you don't " f"have access to it." ) self.demo_bucket = None def demo( self, question, upload_func, download_func, upload_args=None, download_args=None ): """Run a demonstration. Ask the user if they want to run this specific demonstration. If they say yes, create a file on the local path, upload it using the specified upload function, then download it using the specified download function. """ if download_args is None: download_args = {} if upload_args is None: upload_args = {} question = question.format(self.file_size_mb) answer = input(f"{question} (y/n)") if answer.lower() == "y": local_file_path, object_key, download_file_path = self._create_demo_file() file_transfer.TransferConfig = self._config_wrapper( TransferConfig, CONFIG_ATTRS ) self._report_transfer_params( "Uploading", local_file_path, object_key, **upload_args ) start_time = time.perf_counter() thread_info = upload_func( local_file_path, self.demo_bucket, object_key, self.file_size_mb, **upload_args, ) end_time = time.perf_counter() self._report_transfer_result(thread_info, end_time - start_time) file_transfer.TransferConfig = self._config_wrapper( TransferConfig, CONFIG_ATTRS + DOWNLOAD_CONFIG_ATTRS ) self._report_transfer_params( "Downloading", object_key, download_file_path, **download_args ) start_time = time.perf_counter() thread_info = download_func( self.demo_bucket, object_key, download_file_path, self.file_size_mb, **download_args, ) end_time = time.perf_counter() self._report_transfer_result(thread_info, end_time - start_time) def last_name_set(self): """Get the name set used for the last demo.""" return self._chore_list[-1] def cleanup(self): """ Remove files from the demo folder, and uploaded objects from the Amazon S3 bucket. """ print("-" * self._terminal_width) for local_file_path, s3_object_key, downloaded_file_path in self._chore_list: print(f"Removing {local_file_path}") try: os.remove(local_file_path) except FileNotFoundError as err: print(err) print(f"Removing {downloaded_file_path}") try: os.remove(downloaded_file_path) except FileNotFoundError as err: print(err) if self.demo_bucket: print(f"Removing {self.demo_bucket}:{s3_object_key}") try: self._s3.Bucket(self.demo_bucket).Object(s3_object_key).delete() except ClientError as err: print(err) def _setup_platform_specific(self): """Set up platform-specific command used to create a large file.""" if platform.system() == "Windows": self._create_file_cmd = "fsutil file createnew {} {}" self._size_multiplier = MB elif platform.system() == "Linux" or platform.system() == "Darwin": self._create_file_cmd = f"dd if=/dev/urandom of={{}} " f"bs={MB} count={{}}" self._size_multiplier = 1 else: raise EnvironmentError( f"Demo of platform {platform.system()} isn't supported." ) def _create_demo_file(self): """ Create a file in the demo folder specified by the user. Store the local path, object name, and download path for later cleanup. Only the local file is created by this method. The Amazon S3 object and download file are created later during the demonstration. Returns: A tuple that contains the local file path, object name, and download file path. """ file_name_template = "TestFile{}-{}.demo" local_suffix = "local" object_suffix = "s3object" download_suffix = "downloaded" file_tag = len(self._chore_list) + 1 local_file_path = os.path.join( self.demo_folder, file_name_template.format(file_tag, local_suffix) ) s3_object_key = file_name_template.format(file_tag, object_suffix) downloaded_file_path = os.path.join( self.demo_folder, file_name_template.format(file_tag, download_suffix) ) filled_cmd = self._create_file_cmd.format( local_file_path, self.file_size_mb * self._size_multiplier ) print( f"Creating file of size {self.file_size_mb} MB " f"in {self.demo_folder} by running:" ) print(f"{'':4}{filled_cmd}") os.system(filled_cmd) chore = (local_file_path, s3_object_key, downloaded_file_path) self._chore_list.append(chore) return chore def _report_transfer_params(self, verb, source_name, dest_name, **kwargs): """Report configuration and extra arguments used for a file transfer.""" print("-" * self._terminal_width) print(f"{verb} {source_name} ({self.file_size_mb} MB) to {dest_name}") if kwargs: print("With extra args:") for arg, value in kwargs.items(): print(f'{"":4}{arg:<20}: {value}') @staticmethod def ask_user(question): """ Ask the user a yes or no question. Returns: True when the user answers 'y' or 'Y'; otherwise, False. """ answer = input(f"{question} (y/n) ") return answer.lower() == "y" @staticmethod def _config_wrapper(func, config_attrs): def wrapper(*args, **kwargs): config = func(*args, **kwargs) print("With configuration:") for attr in config_attrs: print(f'{"":4}{attr:<20}: {getattr(config, attr)}') return config return wrapper @staticmethod def _report_transfer_result(thread_info, elapsed): """Report the result of a transfer, including per-thread data.""" print(f"\nUsed {len(thread_info)} threads.") for ident, byte_count in thread_info.items(): print(f"{'':4}Thread {ident} copied {byte_count} bytes.") print(f"Your transfer took {elapsed:.2f} seconds.") def main(): """ Run the demonstration script for s3_file_transfer. """ demo_manager = TransferDemoManager() demo_manager.collect_user_info() # Upload and download with default configuration. Because the file is 30 MB # and the default multipart_threshold is 8 MB, both upload and download are # multipart transfers. demo_manager.demo( "Do you want to upload and download a {} MB file " "using the default configuration?", file_transfer.upload_with_default_configuration, file_transfer.download_with_default_configuration, ) # Upload and download with multipart_threshold set higher than the size of # the file. This causes the transfer manager to use standard transfers # instead of multipart transfers. demo_manager.demo( "Do you want to upload and download a {} MB file " "as a standard (not multipart) transfer?", file_transfer.upload_with_high_threshold, file_transfer.download_with_high_threshold, ) # Upload with specific chunk size and additional metadata. # Download with a single thread. demo_manager.demo( "Do you want to upload a {} MB file with a smaller chunk size and " "then download the same file using a single thread?", file_transfer.upload_with_chunksize_and_meta, file_transfer.download_with_single_thread, upload_args={ "metadata": { "upload_type": "chunky", "favorite_color": "aqua", "size": "medium", } }, ) # Upload using server-side encryption with customer-provided # encryption keys. # Generate a 256-bit key from a passphrase. sse_key = hashlib.sha256("demo_passphrase".encode("utf-8")).digest() demo_manager.demo( "Do you want to upload and download a {} MB file using " "server-side encryption?", file_transfer.upload_with_sse, file_transfer.download_with_sse, upload_args={"sse_key": sse_key}, download_args={"sse_key": sse_key}, ) # Download without specifying an encryption key to show that the # encryption key must be included to download an encrypted object. if demo_manager.ask_user( "Do you want to try to download the encrypted " "object without sending the required key?" ): try: _, object_key, download_file_path = demo_manager.last_name_set() file_transfer.download_with_default_configuration( demo_manager.demo_bucket, object_key, download_file_path, demo_manager.file_size_mb, ) except ClientError as err: print( "Got expected error when trying to download an encrypted " "object without specifying encryption info:" ) print(f"{'':4}{err}") # Remove all created and downloaded files, remove all objects from # S3 storage. if demo_manager.ask_user( "Demonstration complete. Do you want to remove local files " "and S3 objects?" ): demo_manager.cleanup() if __name__ == "__main__": try: main() except NoCredentialsError as error: print(error) print( "To run this example, you must have valid credentials in " "a shared credential file or set in environment variables." )
En el siguiente ejemplo de código, se muestra cómo:
Crear un bucket de S3 con control de versiones.
Obtener todas las versiones de un objeto.
Revertir un objeto a una versión anterior.
Eliminar y restaurar un objeto con control de versiones.
Eliminar permanentemente todas las versiones de un objeto.
- SDK para Python (Boto3)
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nota
Hay más información GitHub. Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS
. Crear funciones que encapsulen acciones de S3.
def create_versioned_bucket(bucket_name, prefix): """ Creates an Amazon S3 bucket, enables it for versioning, and configures a lifecycle that expires noncurrent object versions after 7 days. Adding a lifecycle configuration to a versioned bucket is a best practice. It helps prevent objects in the bucket from accumulating a large number of noncurrent versions, which can slow down request performance. Usage is shown in the usage_demo_single_object function at the end of this module. :param bucket_name: The name of the bucket to create. :param prefix: Identifies which objects are automatically expired under the configured lifecycle rules. :return: The newly created bucket. """ try: bucket = s3.create_bucket( Bucket=bucket_name, CreateBucketConfiguration={ "LocationConstraint": s3.meta.client.meta.region_name }, ) logger.info("Created bucket %s.", bucket.name) except ClientError as error: if error.response["Error"]["Code"] == "BucketAlreadyOwnedByYou": logger.warning("Bucket %s already exists! Using it.", bucket_name) bucket = s3.Bucket(bucket_name) else: logger.exception("Couldn't create bucket %s.", bucket_name) raise try: bucket.Versioning().enable() logger.info("Enabled versioning on bucket %s.", bucket.name) except ClientError: logger.exception("Couldn't enable versioning on bucket %s.", bucket.name) raise try: expiration = 7 bucket.LifecycleConfiguration().put( LifecycleConfiguration={ "Rules": [ { "Status": "Enabled", "Prefix": prefix, "NoncurrentVersionExpiration": {"NoncurrentDays": expiration}, } ] } ) logger.info( "Configured lifecycle to expire noncurrent versions after %s days " "on bucket %s.", expiration, bucket.name, ) except ClientError as error: logger.warning( "Couldn't configure lifecycle on bucket %s because %s. " "Continuing anyway.", bucket.name, error, ) return bucket def rollback_object(bucket, object_key, version_id): """ Rolls back an object to an earlier version by deleting all versions that occurred after the specified rollback version. Usage is shown in the usage_demo_single_object function at the end of this module. :param bucket: The bucket that holds the object to roll back. :param object_key: The object to roll back. :param version_id: The version ID to roll back to. """ # Versions must be sorted by last_modified date because delete markers are # at the end of the list even when they are interspersed in time. versions = sorted( bucket.object_versions.filter(Prefix=object_key), key=attrgetter("last_modified"), reverse=True, ) logger.debug( "Got versions:\n%s", "\n".join( [ f"\t{version.version_id}, last modified {version.last_modified}" for version in versions ] ), ) if version_id in [ver.version_id for ver in versions]: print(f"Rolling back to version {version_id}") for version in versions: if version.version_id != version_id: version.delete() print(f"Deleted version {version.version_id}") else: break print(f"Active version is now {bucket.Object(object_key).version_id}") else: raise KeyError( f"{version_id} was not found in the list of versions for " f"{object_key}." ) def revive_object(bucket, object_key): """ Revives a versioned object that was deleted by removing the object's active delete marker. A versioned object presents as deleted when its latest version is a delete marker. By removing the delete marker, we make the previous version the latest version and the object then presents as *not* deleted. Usage is shown in the usage_demo_single_object function at the end of this module. :param bucket: The bucket that contains the object. :param object_key: The object to revive. """ # Get the latest version for the object. response = s3.meta.client.list_object_versions( Bucket=bucket.name, Prefix=object_key, MaxKeys=1 ) if "DeleteMarkers" in response: latest_version = response["DeleteMarkers"][0] if latest_version["IsLatest"]: logger.info( "Object %s was indeed deleted on %s. Let's revive it.", object_key, latest_version["LastModified"], ) obj = bucket.Object(object_key) obj.Version(latest_version["VersionId"]).delete() logger.info( "Revived %s, active version is now %s with body '%s'", object_key, obj.version_id, obj.get()["Body"].read(), ) else: logger.warning( "Delete marker is not the latest version for %s!", object_key ) elif "Versions" in response: logger.warning("Got an active version for %s, nothing to do.", object_key) else: logger.error("Couldn't get any version info for %s.", object_key) def permanently_delete_object(bucket, object_key): """ Permanently deletes a versioned object by deleting all of its versions. Usage is shown in the usage_demo_single_object function at the end of this module. :param bucket: The bucket that contains the object. :param object_key: The object to delete. """ try: bucket.object_versions.filter(Prefix=object_key).delete() logger.info("Permanently deleted all versions of object %s.", object_key) except ClientError: logger.exception("Couldn't delete all versions of %s.", object_key) raise
Cargar la estrofa de un poema en un objeto con control de versiones y realizar una serie de acciones en él.
def usage_demo_single_object(obj_prefix="demo-versioning/"): """ Demonstrates usage of versioned object functions. This demo uploads a stanza of a poem and performs a series of revisions, deletions, and revivals on it. :param obj_prefix: The prefix to assign to objects created by this demo. """ with open("father_william.txt") as file: stanzas = file.read().split("\n\n") width = get_terminal_size((80, 20))[0] print("-" * width) print("Welcome to the usage demonstration of Amazon S3 versioning.") print( "This demonstration uploads a single stanza of a poem to an Amazon " "S3 bucket and then applies various revisions to it." ) print("-" * width) print("Creating a version-enabled bucket for the demo...") bucket = create_versioned_bucket("bucket-" + str(uuid.uuid1()), obj_prefix) print("\nThe initial version of our stanza:") print(stanzas[0]) # Add the first stanza and revise it a few times. print("\nApplying some revisions to the stanza...") obj_stanza_1 = bucket.Object(f"{obj_prefix}stanza-1") obj_stanza_1.put(Body=bytes(stanzas[0], "utf-8")) obj_stanza_1.put(Body=bytes(stanzas[0].upper(), "utf-8")) obj_stanza_1.put(Body=bytes(stanzas[0].lower(), "utf-8")) obj_stanza_1.put(Body=bytes(stanzas[0][::-1], "utf-8")) print( "The latest version of the stanza is now:", obj_stanza_1.get()["Body"].read().decode("utf-8"), sep="\n", ) # Versions are returned in order, most recent first. obj_stanza_1_versions = bucket.object_versions.filter(Prefix=obj_stanza_1.key) print( "The version data of the stanza revisions:", *[ f" {version.version_id}, last modified {version.last_modified}" for version in obj_stanza_1_versions ], sep="\n", ) # Rollback two versions. print("\nRolling back two versions...") rollback_object(bucket, obj_stanza_1.key, list(obj_stanza_1_versions)[2].version_id) print( "The latest version of the stanza:", obj_stanza_1.get()["Body"].read().decode("utf-8"), sep="\n", ) # Delete the stanza print("\nDeleting the stanza...") obj_stanza_1.delete() try: obj_stanza_1.get() except ClientError as error: if error.response["Error"]["Code"] == "NoSuchKey": print("The stanza is now deleted (as expected).") else: raise # Revive the stanza print("\nRestoring the stanza...") revive_object(bucket, obj_stanza_1.key) print( "The stanza is restored! The latest version is again:", obj_stanza_1.get()["Body"].read().decode("utf-8"), sep="\n", ) # Permanently delete all versions of the object. This cannot be undone! print("\nPermanently deleting all versions of the stanza...") permanently_delete_object(bucket, obj_stanza_1.key) obj_stanza_1_versions = bucket.object_versions.filter(Prefix=obj_stanza_1.key) if len(list(obj_stanza_1_versions)) == 0: print("The stanza has been permanently deleted and now has no versions.") else: print("Something went wrong. The stanza still exists!") print(f"\nRemoving {bucket.name}...") bucket.delete() print(f"{bucket.name} deleted.") print("Demo done!")
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Para obtener información sobre la API, consulte los siguientes temas en la Referencia de la API de AWS SDK para Python (Boto3).
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Ejemplos de tecnología sin servidor
En el siguiente ejemplo de código se muestra cómo implementar una función de Lambda que recibe un evento activado al cargar un objeto en un bucket de S3. La función recupera el nombre del bucket de S3 y la clave del objeto del parámetro de evento y llama a la API de Amazon S3 para recuperar y registrar el tipo de contenido del objeto.
- SDK para Python (Boto3)
-
nota
Hay más información GitHub. Busque el ejemplo completo y aprenda a configurar y ejecutar en el repositorio de ejemplos sin servidor
. Uso de un evento de S3 con Lambda mediante Python.
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # SPDX-License-Identifier: Apache-2.0 import json import urllib.parse import boto3 print('Loading function') s3 = boto3.client('s3') def lambda_handler(event, context): #print("Received event: " + json.dumps(event, indent=2)) # Get the object from the event and show its content type bucket = event['Records'][0]['s3']['bucket']['name'] key = urllib.parse.unquote_plus(event['Records'][0]['s3']['object']['key'], encoding='utf-8') try: response = s3.get_object(Bucket=bucket, Key=key) print("CONTENT TYPE: " + response['ContentType']) return response['ContentType'] except Exception as e: print(e) print('Error getting object {} from bucket {}. Make sure they exist and your bucket is in the same region as this function.'.format(key, bucket)) raise e