Paginators - Boto3 1.34.2 documentation

Some AWS operations return results that are incomplete and require subsequent requests in order to attain the entire result set. The process of sending subsequent requests to continue where a previous request left off is called pagination. For example, the list_objects operation of Amazon S3 returns up to 1000 objects at a time, and you

Some AWS operations return results that are incomplete and require subsequent requests in order to attain the entire result set. The process of sending subsequent requests to continue where a previous request left off is called pagination. For example, the list_objects operation of Amazon S3 returns up to 1000 objects at a time, and you must send subsequent requests with the appropriate Marker in order to retrieve the next page of results.

Paginators are a feature of boto3 that act as an abstraction over the process of iterating over an entire result set of a truncated API operation.

Creating paginators#

Paginators are created via the get_paginator() method of a boto3 client. The get_paginator() method accepts an operation name and returns a reusable Paginator object. You then call the paginate method of the Paginator, passing in any relevant operation parameters to apply to the underlying API operation. The paginate method then returns an iterable PageIterator:

import boto3 # Create a client client = boto3.client('s3', region_name='us-west-2') # Create a reusable Paginator paginator = client.get_paginator('list_objects_v2') # Create a PageIterator from the Paginator page_iterator = paginator.paginate(Bucket='my-bucket') for page in page_iterator: print(page['Contents']) 

Customizing page iterators#

You must call the paginate method of a Paginator in order to iterate over the pages of API operation results. The paginate method accepts a PaginationConfig named argument that can be used to customize the pagination:

paginator = client.get_paginator('list_objects_v2') page_iterator = paginator.paginate(Bucket='my-bucket', PaginationConfig={'MaxItems': 10}) 
MaxItems

Limits the maximum number of total returned items returned while paginating.

StartingToken

Can be used to modify the starting marker or token of a paginator. This argument if useful for resuming pagination from a previous token or starting pagination at a known position.

PageSize

Controls the number of items returned per page of each result.

Note

Services may choose to return more or fewer items than specified in the PageSize argument depending on the service, the operation, or the resource you are paginating.

Filtering results#

Many Paginators can be filtered server-side with options that are passed through to each underlying API call. For example, S3.Paginator.list_objects.paginate() accepts a Prefix parameter used to filter the paginated results by prefix server-side before sending them to the client:

import boto3 client = boto3.client('s3', region_name='us-west-2') paginator = client.get_paginator('list_objects_v2') operation_parameters = {'Bucket': 'my-bucket', 'Prefix': 'foo/baz'} page_iterator = paginator.paginate(**operation_parameters) for page in page_iterator: print(page['Contents']) 

Filtering results with JMESPath#

JMESPath is a query language for JSON that can be used directly on paginated results. You can filter results client-side using JMESPath expressions that are applied to each page of results through the search method of a PageIterator.

import boto3 client = boto3.client('s3', region_name='us-west-2') paginator = client.get_paginator('list_objects_v2') page_iterator = paginator.paginate(Bucket='my-bucket') filtered_iterator = page_iterator.search("Contents[?Size > `100`][]") for key_data in filtered_iterator: print(key_data) 

When filtering with JMESPath expressions, each page of results that is yielded by the paginator is mapped through the JMESPath expression. If a JMESPath expression returns a single value that is not an array, that value is yielded directly. If the result of applying the JMESPath expression to a page of results is a list, then each value of the list is yielded individually (essentially implementing a flat map). For example, in the above expression, each key that has a Size greater than 100 is yielded by the filtered_iterator.

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