Analytics API paging object pageSize vs pageNumber behavior

NICE CXone API & Integrations
1

Trying to understand the exact interaction between pageSize and pageNumber in the Analytics API when retrieving large datasets for Terraform data sources.

GET /api/v2/analytics/conversations/details/query
{
 "pageSize": 1000,
 "pageNumber": 1
}

When pageSize hits the max allowed, does pageCount reflect the total logical pages or just the current batch? Need to know if I should loop on pageNumber or use the nextPage link for idempotent state pulls.

2

Make sure you stop paging on pageNumber because the Analytics API uses cursor-based pagination for detail queries, not offset-based. Use the nextPageToken from the response to fetch the next batch.

// Request
{
 "pageSize": 500
}

// Response
{
 "nextPageToken": "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9...",
 "pageCount": 10
}
3

The problem here is mixing offset pagination with cursor-based endpoints. As the docs state, “detail queries utilize token-based pagination,” so pageNumber is ignored. Use nextPageToken instead. Here is the correct Java SDK loop:

while (resp.getNextPageToken() != null) {
 query.setNextPageToken(resp.getNextPageToken());
 resp = api.getAnalyticsConversationsDetailsQuery(query);
}
4

The docs actually state that mixing offset parameters with cursor-based endpoints leads to undefined behavior because the server ignores pageNumber when nextPageToken is present. The suggestion above regarding the Java SDK loop is correct, but it lacks robust error handling for production CI/CD pipelines. In Python, you must explicitly handle rate limits and transient errors to prevent script failure during large data extractions for Terraform state imports.

import purecloudplatformclientv2
from purecloudplatformclientv2.rest import ApiException

api_instance = purecloudplatformclientv2.AnalyticsApi()
query = purecloudplatformclientv2.ConversationsQuery()
query.page_size = 500

while True:
 try:
 resp = api_instance.post_analytics_conversations_details_query(body=query)
 # process resp.entities
 if not resp.next_page_token:
 break
 query.next_page_token = resp.next_page_token
 except ApiException as e:
 if e.status == 429:
 time.sleep(2)
 else:
 raise

See https://support.mypurecloud.com/articles/12345 for implementation details.

5

I normally fix this by initializing the query with a fixed pageSize and then iterating strictly on the nextPageToken. The pageNumber parameter is effectively dead weight for detail queries and will be ignored by the server, leading to redundant requests or silent failures if you rely on it for loop termination.

Here is the Python SDK pattern I use. It avoids the offset trap As noted above.

from genesyscloud.analytics import AnalyticsApi
from genesyscloud.platform_client import PlatformClient

def get_conversation_details(api: AnalyticsApi, query_body: dict):
 all_results = []
 query_body["pageSize"] = 500 # Max efficient size
 
 response = api.post_analytics_conversations_details_query(body=query_body)
 all_results.extend(response.entity)
 
 while response.next_page_token:
 query_body["nextPageToken"] = response.next_page_token
 response = api.post_analytics_conversations_details_query(body=query_body)
 all_results.extend(response.entity)
 
 return all_results

The suggestion above regarding Java loops is correct, but in Python, ensure you reset the nextPageToken in the body or let the SDK handle the mutation if using a mutable object.

  • nextPageToken lifecycle
  • pageSize limits for detail vs summary queries
  • Token expiration handling