how to limit the ouput of get_all_images in amazon boto?

For example

c.get_all_images(filters = {
   'architecture': 'x86_64'
})

The function returns a list so if you really just need to limit the number of results, I'd do this:

images = con.get_all_images()[: 10]

Also of note, the name accepts wildcards, if you want to filter based on the image names:

images = ec2Connection.get_all_images(owners = ['self'], filters = {
   'name': '*image*'
})

My two cents to find images that have a specific string in the name tag , based on storm_m2138's answer:

amis = EC2conn.get_all_images(
   filters = {
      "tag-key": "Name",
      "tag-value": "*some_string"
   }
)

Suggestion : 2

A list of image layer objects corresponding to the image layer references in the request.,A low-level client representing Amazon EC2 Container Registry (ECR),A list of image objects corresponding to the image references in the request.,Retrieves the pre-signed Amazon S3 download URL corresponding to an image layer. You can only get URLs for image layers that are referenced in an image.

import boto3

client = boto3.client('ecr')

response = client.batch_check_layer_availability(
   registryId = 'string',
   repositoryName = 'string',
   layerDigests = [
      'string',
   ]
)

{
   'layers': [{
      'layerDigest': 'string',
      'layerAvailability': 'AVAILABLE' | 'UNAVAILABLE',
      'layerSize': 123,
      'mediaType': 'string'
   }, ],
   'failures': [{
      'layerDigest': 'string',
      'failureCode': 'InvalidLayerDigest' | 'MissingLayerDigest',
      'failureReason': 'string'
   }, ]
}

response = client.batch_delete_image(
   registryId = 'string',
   repositoryName = 'string',
   imageIds = [{
      'imageDigest': 'string',
      'imageTag': 'string'
   }, ]
)

{
   'imageIds': [{
      'imageDigest': 'string',
      'imageTag': 'string'
   }, ],
   'failures': [{
      'imageId': {
         'imageDigest': 'string',
         'imageTag': 'string'
      },
      'failureCode': 'InvalidImageDigest' | 'InvalidImageTag' | 'ImageTagDoesNotMatchDigest' | 'ImageNotFound' | 'MissingDigestAndTag' | 'ImageReferencedByManifestList' | 'KmsError',
      'failureReason': 'string'
   }, ]
}

response = client.batch_delete_image(
   imageIds = [{
      'imageTag': 'precise',
   }, ],
   repositoryName = 'ubuntu',
)

print(response)

Suggestion : 3

With Amazon S3 Select, you can use simple structured query language (SQL) statements to filter the contents of an Amazon S3 object and retrieve just the subset of data that you need. By using Amazon S3 Select to filter this data, you can reduce the amount of data that Amazon S3 transfers, which reduces the cost and latency to retrieve this data.,You can perform SQL queries using AWS SDKs, the SELECT Object Content REST API, the AWS Command Line Interface (AWS CLI), or the Amazon S3 console. The Amazon S3 console limits the amount of data returned to 40 MB. To retrieve more data, use the AWS CLI or the API., Use the Amazon S3 Select ScanRange parameter and Start at (Byte) 1 and End at (Byte) 4. So the scan range would start at "," and scan till the end of record starting at "C" and return the result C, D because that is the end of the record. ,Amazon S3 Select scan range requests are available to use on the Amazon S3 CLI, API and SDK. You can use the ScanRange parameter in the Amazon S3 Select request for this feature. For more information, see the Amazon S3 SELECT Object Content in the Amazon Simple Storage Service API Reference.

With Amazon S3 Select, you can scan a subset of an object by specifying a range of bytes to query. This capability lets you parallelize scanning the whole object by splitting the work into separate Amazon S3 Select requests for a series of non-overlapping scan ranges. Scan ranges don't need to be aligned with record boundaries. An Amazon S3 Select scan range request runs across the byte range that you specify. A record that starts within the scan range specified but extends beyond the scan range will be processed by the query. For example; the following shows an Amazon S3 object containing a series of records in a line-delimited CSV format:

A, B
C, D
D, E
E, F
G, H
I, J

Suggestion : 4

Migrating from Boto to Boto3,Usage Settings Migrating from Boto to Boto3 CloudFront CloudFront Signed Urls IAM Policy Storage Overriding the default Storage class Model ,Migration from the boto-based to boto3-based backend should be straightforward and painless.,Amazon S3 Usage Settings Migrating from Boto to Boto3 CloudFront CloudFront Signed Urls IAM Policy Storage Overriding the default Storage class Model

DEFAULT_FILE_STORAGE = 'storages.backends.s3boto3.S3Boto3Storage'

STATICFILES_STORAGE = 'storages.backends.s3boto3.S3StaticStorage'

STATICFILES_STORAGE = 'storages.backends.s3boto3.S3ManifestStaticStorage'

AWS_S3_CUSTOM_DOMAIN = 'cdn.mydomain.com'

AWS_CLOUDFRONT_KEY = os.environ.get('AWS_CLOUDFRONT_KEY', None).encode('ascii')
AWS_CLOUDFRONT_KEY_ID = os.environ.get('AWS_CLOUDFRONT_KEY_ID', None)

AWS_CLOUDFRONT_KEY = -- -- - BEGIN RSA PRIVATE KEY-- -- -
   ...
   -- -- - END RSA PRIVATE KEY-- -- -
   AWS_CLOUDFRONT_KEY_ID = APK....