Python SDK Analytics Export to S3 Failing with 403 on Specific Date Ranges

We are running into a peculiar issue with our daily analytics export job. The script uses the Genesys Cloud Python SDK to pull queue metrics and then pushes the resulting JSON to an S3 bucket via boto3. The authentication flow seems solid, as we are successfully retrieving the OAuth token and making initial calls to the analytics API without issue. The problem manifests only when the date range exceeds a certain threshold, specifically when querying more than 30 days of historical data in a single request.

The script constructs the API call using genesys_cloud.analytics.api.get_queue_metrics. When the start_time and end_time parameters are set to a range smaller than 30 days, the response code is 200, and the data populates correctly. However, increasing the range to 45 days triggers an immediate 403 Forbidden error from the Genesys Cloud API, not a timeout. This is strange because the documentation does not mention a hard limit on the date range for this specific endpoint, only a limit on the number of records returned.

Here is the relevant snippet from our Python script:

from genesyscloud import analytics_api, configuration

config = configuration.Configuration()
config.oauth_client_id = os.getenv('GC_CLIENT_ID')
config.oauth_client_secret = os.getenv('GC_CLIENT_SECRET')

analytics = analytics_api.AnalyticsApi(configuration=config)

# This works
start = datetime.datetime(2023, 1, 1, 0, 0, 0)
end = datetime.datetime(2023, 1, 30, 23, 59, 59)

# This fails with 403
# start = datetime.datetime(2023, 1, 1, 0, 0, 0)
# end = datetime.datetime(2023, 2, 15, 23, 59, 59)

try:
 response = analytics.get_queue_metrics(
 group_by='interval',
 start_time=start.isoformat(),
 end_time=end.isoformat(),
 view='default'
 )
except Exception as e:
 print(f"API Error: {e}")

The error message returned is simply “Forbidden” with no additional context in the JSON body. We have verified that the OAuth token has the necessary analytics:reports:view scope. We are considering splitting the date range into smaller chunks and merging the results client-side, but that introduces complexity in handling overlapping intervals and increases the load on our S3 write operations. Is there a known limitation on the date range for the get_queue_metrics endpoint that is not documented, or should we be using a different API method for larger datasets? The current approach feels brittle, and we need a reliable way to export 90 days of history without hitting this wall.

The 403 error usually means your OAuth token lacks the specific scope required for historical analytics data. The standard analytics:query scope is often enough for real-time or recent data, but pulling more than 30 days back might hit a different permission layer or rate limit depending on your org’s security settings.

Check the scopes attached to your service account. You likely need analytics:query combined with analytics:export if you are trying to push large datasets. Also, verify that the service account has the Admin:Analytics or Viewer:Analytics role assigned. Without that role, the API will reject the request regardless of the token.

Here is how to verify the token scopes in Python before making the call:

from gen_cloud_python_sdk.client import PlatformClient

pc = PlatformClient()
pc.set_access_token('your_access_token')
pc.set_refresh_token('your_refresh_token')
pc.set_client_id('your_client_id')
pc.set_client_secret('your_client_secret')

# Get current user info to check roles
try:
 user_response = pc.users.get_user_by_id("me")
 print(f"User Roles: {user_response.body.roles}")
except Exception as e:
 print(f"Error fetching user info: {e}")

If the roles look correct, the issue might be the date range format. The analytics API expects ISO 8601 format. Ensure your from_date and to_date parameters are strictly formatted like 2023-10-01T00:00:00.000Z. A malformed date can sometimes trigger a 403 if the validation fails silently.

Try breaking the query into smaller chunks if the range is huge. The API has limits on how much data it will return in a single response. If you are hitting the limit, it might throw a 403 instead of a 400.