Sono disponibili altri esempi AWS SDK nel repository [AWS Doc SDK](https://github.com/awsdocs/aws-doc-sdk-examples) Examples. GitHub
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# Esempi per Amazon S3 con SDK per Python (Boto3)
I seguenti esempi di codice mostrano come eseguire azioni e implementare scenari comuni utilizzando Amazon S3. AWS SDK per Python (Boto3)
*Nozioni di base*: esempi di codice che mostrano come eseguire le operazioni essenziali all’interno di un servizio.
Le *azioni* sono estratti di codice da programmi più grandi e devono essere eseguite nel contesto. Sebbene le azioni mostrino come richiamare le singole funzioni del servizio, è possibile visualizzarle contestualizzate negli scenari correlati.
*Scenari*: esempi di codice che mostrano come eseguire un’attività specifica chiamando più funzioni all’interno dello stesso servizio o combinate con altri Servizi AWS.
Ogni esempio include un link al codice sorgente completo, in cui vengono fornite le istruzioni su come configurare ed eseguire il codice nel contesto.
**Topics**
+ [Nozioni di base](#get_started)
+ [Nozioni di base](#basics)
+ [Azioni](#actions)
+ [Scenari](#scenarios)
+ [Esempi serverless](#serverless_examples)
## Nozioni di base
### Hello Amazon S3
Il seguente esempio di codice mostra come iniziare a usare Amazon S3.
**SDK per Python (Boto3)**
C'è altro su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3#code-examples).
```
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()
```
+ Per i dettagli sull'API, consulta [ListBuckets AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/ListBuckets)*SDK for Python (Boto3) API Reference*.
## Nozioni di base
### Informazioni di base
L’esempio di codice seguente mostra come:
+ Crea un bucket e carica un file in tale bucket.
+ Scaricare un oggetto da un bucket.
+ Copiare un oggetto in una sottocartella in un bucket.
+ Elencare gli oggetti in un bucket.
+ Elimina il bucket e tutti gli oggetti in esso contenuti.
**SDK per Python (Boto3)**
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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"))
```
+ Per informazioni dettagliate sull’API, consulta i seguenti argomenti nella *documentazione di riferimento dell’API AWS SDK per Python (Boto3)*.
+ [CopyObject](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/CopyObject)
+ [CreateBucket](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/CreateBucket)
+ [DeleteBucket](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/DeleteBucket)
+ [DeleteObjects](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/DeleteObjects)
+ [GetObject](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/GetObject)
+ [ListObjectsV2](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/ListObjectsV2)
+ [PutObject](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/PutObject)
## Azioni
### `CopyObject`
Il seguente esempio di codice mostra come usare`CopyObject`.
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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 oggetto utilizzando una richiesta condizionale.
```
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
```
+ Per i dettagli sull'API, consulta [CopyObject AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/CopyObject)*SDK for Python (Boto3) API Reference*.
### `CreateBucket`
Il seguente esempio di codice mostra come utilizzare. `CreateBucket`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
Crea un bucket con le impostazioni di default.
```
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
```
Crea un bucket con versione con una configurazione del ciclo di vita.
```
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
```
+ Per i dettagli sull'API, consulta [CreateBucket AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/CreateBucket)*SDK for Python (Boto3) API Reference*.
### `DeleteBucket`
Il seguente esempio di codice mostra come utilizzare. `DeleteBucket`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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
```
+ Per i dettagli sull'API, consulta [DeleteBucket AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/DeleteBucket)*SDK for Python (Boto3) API Reference*.
### `DeleteBucketCors`
Il seguente esempio di codice mostra come utilizzare. `DeleteBucketCors`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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
```
+ Per i dettagli sull'API, consulta [DeleteBucketCors AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/DeleteBucketCors)*SDK for Python (Boto3) API Reference*.
### `DeleteBucketLifecycle`
Il seguente esempio di codice mostra come utilizzare. `DeleteBucketLifecycle`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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
```
+ Per i dettagli sull'API, consulta [DeleteBucketLifecycle AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/DeleteBucketLifecycle)*SDK for Python (Boto3) API Reference*.
### `DeleteBucketPolicy`
Il seguente esempio di codice mostra come utilizzare. `DeleteBucketPolicy`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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
```
+ Per i dettagli sull'API, consulta [DeleteBucketPolicy AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/DeleteBucketPolicy)*SDK for Python (Boto3) API Reference*.
### `DeleteObject`
Il seguente esempio di codice mostra come utilizzare. `DeleteObject`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
Elimina un oggetto.
```
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
```
Ripristina la versione precedente di un oggetto eliminando quelle successive.
```
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}."
)
```
Riattiva un oggetto eliminato rimuovendo il contrassegno di eliminazione attivo dell’oggetto.
```
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)
```
Crea un gestore Lambda che rimuove un contrassegno di eliminazione da un oggetto S3. Questo gestore può essere utilizzato per ripulire in modo efficiente i contrassegni di eliminazione estranei di un bucket con versione.
```
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_plus(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,
}
```
+ Per i dettagli sull'API, consulta [DeleteObject AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/DeleteObject)*SDK for Python (Boto3) API Reference*.
### `DeleteObjects`
Il seguente esempio di codice mostra come utilizzare. `DeleteObjects`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
Elimina un set di oggetti utilizzando un elenco di chiavi oggetto.
```
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
```
Elimina tutti gli oggetti in 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
```
Elimina in modo permanente un oggetto con versione eliminando tutte le relative versioni.
```
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
```
+ Per i dettagli sull'API, consulta [DeleteObjects AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/DeleteObjects)*SDK for Python (Boto3) API Reference*.
### `GetBucketAcl`
Il seguente esempio di codice mostra come utilizzare. `GetBucketAcl`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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
```
+ Per i dettagli sull'API, consulta [GetBucketAcl AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/GetBucketAcl)*SDK for Python (Boto3) API Reference*.
### `GetBucketCors`
Il seguente esempio di codice mostra come utilizzare. `GetBucketCors`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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
```
+ Per i dettagli sull'API, consulta [GetBucketCors AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/GetBucketCors)*SDK for Python (Boto3) API Reference*.
### `GetBucketLifecycleConfiguration`
Il seguente esempio di codice mostra come utilizzare. `GetBucketLifecycleConfiguration`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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
```
+ Per i dettagli sull'API, consulta [GetBucketLifecycleConfiguration AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/GetBucketLifecycleConfiguration)*SDK for Python (Boto3) API Reference*.
### `GetBucketPolicy`
Il seguente esempio di codice mostra come utilizzare. `GetBucketPolicy`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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)
```
+ Per i dettagli sull'API, consulta [GetBucketPolicy AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/GetBucketPolicy)*SDK for Python (Boto3) API Reference*.
### `GetObject`
Il seguente esempio di codice mostra come utilizzare. `GetObject`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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
```
Ottiene un oggetto utilizzando una richiesta condizionale.
```
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
```
+ Per i dettagli sull'API, consulta [GetObject AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/GetObject)*SDK for Python (Boto3) API Reference*.
### `GetObjectAcl`
Il seguente esempio di codice mostra come utilizzare. `GetObjectAcl`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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
```
+ Per i dettagli sull'API, consulta [GetObjectAcl AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/GetObjectAcl)*SDK for Python (Boto3) API Reference*.
### `GetObjectLegalHold`
Il seguente esempio di codice mostra come utilizzare. `GetObjectLegalHold`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/scenarios/object-locking#code-examples).
Applica a un oggetto lo stato relativo alla conservazione a fini legali.
```
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,
)
```
+ Per i dettagli sull'API, consulta [GetObjectLegalHold AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/GetObjectLegalHold)*SDK for Python (Boto3) API Reference*.
### `GetObjectLockConfiguration`
Il seguente esempio di codice mostra come utilizzare. `GetObjectLockConfiguration`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/scenarios/object-locking#code-examples).
Ottiene la configurazione Object Lock.
```
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
```
+ Per i dettagli sull'API, consulta [GetObjectLockConfiguration AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/GetObjectLockConfiguration)*SDK for Python (Boto3) API Reference*.
### `HeadBucket`
Il seguente esempio di codice mostra come utilizzare. `HeadBucket`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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
```
+ Per i dettagli sull'API, consulta [HeadBucket AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/HeadBucket)*SDK for Python (Boto3) API Reference*.
### `ListBuckets`
Il seguente esempio di codice mostra come utilizzare. `ListBuckets`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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
```
+ Per i dettagli sull'API, consulta [ListBuckets AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/ListBuckets)*SDK for Python (Boto3) API Reference*.
### `ListObjectsV2`
Il seguente esempio di codice mostra come utilizzare. `ListObjectsV2`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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
```
+ Per i dettagli sull'API, consulta [ListObjectsV2 nella Guida](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/ListObjectsV2) di riferimento all'API *AWS SDK for Python (Boto3)*.
### `PutBucketAcl`
Il seguente esempio di codice mostra come utilizzare. `PutBucketAcl`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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
```
+ Per i dettagli sull'API, consulta [PutBucketAcl AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/PutBucketAcl)*SDK for Python (Boto3) API Reference*.
### `PutBucketCors`
Il seguente esempio di codice mostra come utilizzare. `PutBucketCors`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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
```
+ Per i dettagli sull'API, consulta [PutBucketCors AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/PutBucketCors)*SDK for Python (Boto3) API Reference*.
### `PutBucketLifecycleConfiguration`
Il seguente esempio di codice mostra come utilizzare. `PutBucketLifecycleConfiguration`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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
```
+ Per i dettagli sull'API, consulta [PutBucketLifecycleConfiguration AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/PutBucketLifecycleConfiguration)*SDK for Python (Boto3) API Reference*.
### `PutBucketPolicy`
Il seguente esempio di codice mostra come utilizzare. `PutBucketPolicy`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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
```
+ Per i dettagli sull'API, consulta [PutBucketPolicy AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/PutBucketPolicy)*SDK for Python (Boto3) API Reference*.
### `PutObject`
Il seguente esempio di codice mostra come utilizzare. `PutObject`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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()
```
Carica un oggetto utilizzando una richiesta condizionale.
```
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
```
+ Per i dettagli sull'API, consulta [PutObject AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/PutObject)*SDK for Python (Boto3) API Reference*.
### `PutObjectAcl`
Il seguente esempio di codice mostra come utilizzare. `PutObjectAcl`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
```
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
```
+ Per i dettagli sull'API, consulta [PutObjectAcl AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/PutObjectAcl)*SDK for Python (Boto3) API Reference*.
### `PutObjectLegalHold`
Il seguente esempio di codice mostra come utilizzare. `PutObjectLegalHold`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/scenarios/object-locking#code-examples).
Applica a un oggetto lo stato relativo alla conservazione a fini legali.
```
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
)
```
+ Per i dettagli sull'API, consulta [PutObjectLegalHold AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/PutObjectLegalHold)*SDK for Python (Boto3) API Reference*.
### `PutObjectLockConfiguration`
Il seguente esempio di codice mostra come utilizzare. `PutObjectLockConfiguration`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/scenarios/object-locking#code-examples).
Abilita la configurazione Object Lock.
```
s3_client.put_object_lock_configuration(
Bucket=bucket,
ObjectLockConfiguration={"ObjectLockEnabled": "Disabled", "Rule": {}},
)
```
+ Per i dettagli sull'API, consulta [PutObjectLockConfiguration AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/PutObjectLockConfiguration)*SDK for Python (Boto3) API Reference*.
### `PutObjectRetention`
Il seguente esempio di codice mostra come utilizzare. `PutObjectRetention`
**SDK per Python (Boto3)**
C'è altro da fare GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/scenarios/object-locking#code-examples).
Abilita la conservazione degli oggetti.
```
s3_client.put_object_retention(
Bucket=bucket,
Key=key,
VersionId=version_id,
Retention={"Mode": "GOVERNANCE", "RetainUntilDate": far_future_date},
BypassGovernanceRetention=True,
)
```
+ Per i dettagli sull'API, consulta [PutObjectRetention AWS](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/PutObjectRetention)*SDK for Python (Boto3) API Reference*.
## Scenari
### Creazione di un URL prefirmato
L’esempio di codice seguente mostra come creare un URL prefirmato per Amazon S3 e caricare un oggetto.
**SDK per Python (Boto3)**
C'è di più su. GitHub Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_basics#code-examples).
Genera un URL prefirmato in grado di eseguire un’operazione S3 per un periodo di tempo limitato. Utilizza il pacchetto Requests per effettuare una richiesta con l’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()
```
Genera una richiesta POST prefirmata per caricare un file.
```
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
```
### Creazione di un’applicazione Amazon Textract explorer
L’esempio di codice seguente mostra come esplorare l’output di Amazon Textract tramite un’applicazione interattiva.
**SDK per Python (Boto3)**
Mostra come utilizzarlo AWS SDK per Python (Boto3) con Amazon Textract per rilevare elementi di testo, moduli e tabelle nell'immagine di un documento. L’immagine di input e l’output di Amazon Textract sono mostrati in un’applicazione Tkinter che consente di esplorare gli elementi rilevati.
+ Invia un’immagine del documento ad Amazon Textract ed esplora l’output degli elementi rilevati.
+ Invia immagini direttamente ad Amazon Textract o tramite un bucket Amazon Simple Storage Service (Amazon S3).
+ Utilizza asynchronous APIs per avviare un processo che pubblica una notifica su un argomento di Amazon Simple Notification Service (Amazon SNS) al termine del processo.
+ Esegue il polling di una coda Amazon Simple Queue Service (Amazon SQS) per un messaggio di completamento del processo e visualizza i risultati.
Per il codice sorgente completo e le istruzioni su come configurarlo ed eseguirlo, consulta l'esempio completo su. [GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/cross_service/textract_explorer)
**Servizi utilizzati in questo esempio**
+ Amazon Cognito Identity
+ Simple Storage Service (Amazon S3)
+ Amazon SNS
+ Amazon SQS
+ Amazon Textract
### Rilevamento di entità nel testo estratto da un’immagine
L’esempio di codice seguente mostra come utilizzare Amazon Comprehend per rilevare le entità nel testo estratto da Amazon Textract da un’immagine archiviata in Amazon S3.
**SDK per Python (Boto3)**
Mostra come utilizzarlo AWS SDK per Python (Boto3) in un notebook Jupyter per rilevare entità nel testo estratto da un'immagine. In questo esempio viene utilizzato Amazon Textract per estrarre il testo da un’immagine archiviata in Amazon Simple Storage Service (Amazon S3) e Amazon Comprehend per rilevare le entità nel testo estratto.
Questo esempio è un notebook Jupyter e deve essere eseguito in un ambiente in grado di ospitare notebook. Per istruzioni su come eseguire l'esempio utilizzando Amazon SageMaker AI, consulta le istruzioni in [TextractAndComprehendNotebook.ipynb](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/cross_service/textract_comprehend_notebook/TextractAndComprehendNotebook.ipynb).
Per il codice sorgente completo e le istruzioni su come configurarlo ed eseguirlo, guarda l'esempio completo su. [GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/cross_service/textract_comprehend_notebook#readme)
**Servizi utilizzati in questo esempio**
+ Amazon Comprehend
+ Simple Storage Service (Amazon S3)
+ Amazon Textract
### Rilevamento di oggetti nelle immagini
L’esempio di codice seguente mostra come creare un’applicazione che utilizza Amazon Rekognition per rilevare oggetti in base a una categoria nelle immagini.
**SDK per Python (Boto3)**
Illustra come utilizzare il AWS SDK per Python (Boto3) per creare un'applicazione Web che consenta di eseguire le seguenti operazioni:
+ Caricamento di foto in un bucket Amazon Simple Storage Service (Amazon S3).
+ Utilizzo di Amazon Rekognition per analizzare ed etichettare le foto.
+ Utilizzo di Amazon Simple Email Service (Amazon SES) per inviare report dell’analisi delle immagini tramite e-mail.
Questo esempio contiene due componenti principali: una pagina web scritta in JavaScript che è costruita con React e un servizio REST scritto in Python creato con Flask-. RESTful
È possibile utilizzare la pagina web React per:
+ Visualizzare un elenco di immagini archiviate nel bucket S3.
+ Caricare le immagini dal computer nel bucket S3.
+ Visualizzare immagini ed etichette che identificano gli elementi rilevati nell’immagine.
+ Ottenere un report relativo a tutte le immagini nel bucket S3 e inviarlo tramite email.
La pagina web richiama il servizio REST. Il servizio invia richieste a AWS per eseguire le seguenti operazioni:
+ Ottenere e filtrare l’elenco delle immagini nel bucket S3.
+ Caricare le foto nel bucket S3.
+ Utilizzare Amazon Rekognition per analizzare le singole foto e ottenere un elenco di etichette che identificano gli articoli rilevati al loro interno.
+ Analizzare tutte le foto presenti nel bucket S3 e usare Amazon SES per inviare un report tramite e-mail.
Per il codice sorgente completo e le istruzioni su come configurarlo ed eseguirlo, guarda l'esempio completo su. [GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/cross_service/photo_analyzer)
**Servizi utilizzati in questo esempio**
+ Amazon Rekognition
+ Simple Storage Service (Amazon S3)
+ Amazon SES
### Rilevamento di persone e oggetti in un video
L’esempio di codice seguente mostra come rilevare persone e oggetti in un video con Amazon Rekognition.
**SDK per Python (Boto3)**
Usa Amazon Rekognition per rilevare volti, oggetti e persone nei video avviando processi di rilevamento asincrono. Questo esempio, inoltre, configura Amazon Rekognition per notificare un argomento Amazon Simple Notification Service (Amazon SNS) al completamento dei processi e sottoscrive una coda Amazon Simple Queue Service (Amazon SQS) all’argomento. Quando la coda riceve un messaggio su un processo, questo viene recuperato e vengono restituiti i risultati.
Questo esempio è visualizzato al meglio su GitHub. Per il codice sorgente completo e le istruzioni su come configurarlo ed eseguirlo, vedi l'esempio completo su [GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/rekognition).
**Servizi utilizzati in questo esempio**
+ Amazon Rekognition
+ Simple Storage Service (Amazon S3)
+ Amazon SES
+ Amazon SNS
+ Amazon SQS
### Eseguire richieste condizionali
L’esempio di codice seguente mostra come aggiungere precondizioni alle richieste Amazon S3.
**SDK per Python (Boto3)**
C'è altro su GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/scenarios/conditional_requests#code-examples).
Esegue uno scenario interattivo che dimostra le richieste condizionali di 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 classe wrapper che definisce le operazioni delle richieste condizionali.
```
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
```
+ Per informazioni dettagliate sull’API, consulta i seguenti argomenti nella *documentazione di riferimento dell’API AWS SDK per Python (Boto3)*.
+ [CopyObject](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/CopyObject)
+ [GetObject](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/GetObject)
+ [PutObject](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/PutObject)
### Gestione di oggetti con versione in batch con una funzione Lambda
L’esempio di codice seguente mostra come gestire gli oggetti con versione S3 in batch con una funzione Lambda.
**SDK per Python (Boto3)**
Mostra come manipolare oggetti con versione di Amazon Simple Storage Service (Amazon S3) in batch creando processi che richiamano funzioni per eseguire l'elaborazione. AWS Lambda Questo esempio mostra come creare un bucket abilitato per le versioni, caricare le strofe dalla poesia *You Are Old, Father William* di Lewis Carroll e utilizzare i processi batch Amazon S3 per eseguire varie operazioni sulla poesia.
**Scopri come:**
+ Creare funzioni Lambda che operano su oggetti con versione.
+ Creare un manifesto di oggetti da aggiornare.
+ Creare processi batch che invocano le funzioni Lambda per aggiornare gli oggetti.
+ Eliminare funzioni Lambda.
+ Svuotare ed eliminare un bucket con versione.
Questo esempio è visualizzato al meglio su. GitHub Per il codice sorgente completo e le istruzioni su come configurarlo ed eseguirlo, vedi l'esempio completo su [GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_versioning#batch-operation-demo).
**Servizi utilizzati in questo esempio**
+ Simple Storage Service (Amazon S3)
### Caricamento o download di file di grandi dimensioni
L’esempio di codice seguente mostra come caricare o scaricare file di grandi dimensioni in e da Amazon S3.
Per ulteriori informazioni, consulta [Caricamento di un oggetto utilizzando il caricamento in più parti](https://docs.aws.amazon.com/AmazonS3/latest/userguide/mpu-upload-object.html).
**SDK per Python (Boto3)**
C'è altro su GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/file_transfer#code-examples).
Crea funzioni che trasferiscono i file utilizzando diverse impostazioni disponibili del gestore di trasferimento. Utilizza una classe di callback per scrivere l’avanzamento del callback durante il trasferimento file.
```
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
```
Esegui le funzioni del gestore di trasferimento e ottieni i risultati.
```
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."
)
```
### Utilizzo degli oggetti con versione
L’esempio di codice seguente mostra come:
+ Creazione un bucket S3 con versione.
+ Ottenimento di tutte le versioni di un oggetto.
+ Ripristino di un oggetto a una versione precedente.
+ Eliminazione e ripristino di un oggetto con versione.
+ Eliminazione permanente di tutte le versioni di un oggetto.
**SDK per Python (Boto3)**
C'è dell'altro GitHub. Trova l'esempio completo e scopri di più sulla configurazione e l'esecuzione nel [Repository di esempi di codice AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/s3/s3_versioning#code-examples).
Creazione di funzioni che eseguono il wrap delle operazioni 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
```
Caricamento la strofa di una poesia in un oggetto con versione ed esecuzione di una serie di operazioni su di esso.
```
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!")
```
+ Per informazioni dettagliate sull’API, consulta i seguenti argomenti nella *documentazione di riferimento dell’API AWS SDK per Python (Boto3)*.
+ [CreateBucket](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/CreateBucket)
+ [DeleteObject](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/DeleteObject)
+ [ListObjectVersions](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/ListObjectVersions)
+ [PutBucketLifecycleConfiguration](https://docs.aws.amazon.com/goto/boto3/s3-2006-03-01/PutBucketLifecycleConfiguration)
## Esempi serverless
### Invocazione di una funzione Lambda da un trigger Amazon S3
L’esempio di codice seguente mostra come implementare una funzione Lambda che riceve un evento attivato dal caricamento di un oggetto in un bucket S3. La funzione recupera il nome del bucket S3 e la chiave dell’oggetto dal parametro evento e chiama l’API Amazon S3 per recuperare e registrare il tipo di contenuto dell’oggetto.
**SDK per Python (Boto3)**
C'è dell'altro GitHub. Trova l'esempio completo e scopri come eseguire la configurazione e l'esecuzione nel repository di [Esempi serverless](https://github.com/aws-samples/serverless-snippets/tree/main/integration-s3-to-lambda).
Utilizzo di un evento S3 con Lambda tramite 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
```