Python SDK token refresh hanging on batch analytics worker during silent auth rotation

We’ve got a MuleSoft flow kicking off a Python worker to pull historical wrap-up codes via the Genesys Cloud API. The job runs for about four hours, so the standard access token expires halfway through. I’m trying to wire up automatic token refresh logic in the Python SDK so the worker doesn’t choke on 401s when the background process hits the queue.

Step one: initialize the client with the refresh token stored in the vault. The docs show genesyscloud.auth.AuthMethods.refresh_token but that just returns a new token object without actually swapping it into the active session. Step two: hook into the request interceptor to catch the 401 Unauthorized and trigger a silent rotation. I wrote a wrapper that catches the exception and calls client.auth.refresh(), but the SDK keeps reusing the stale bearer string on the retry.

Here is the current setup:

from genesyscloud import rest
from genesyscloud.auth import AuthMethods

client = rest.rest_client.RestClient()
AuthMethods.refresh_token(client, client_configuration, refresh_token=env["GC_REFRESH_TOKEN"])

def fetch_batch(endpoint):
 try:
 response = client.get(endpoint)
 return response
 except rest.api_exception.ApiException as e:
 if e.status == 401:
 print("Token expired. Triggering silent refresh...")
 AuthMethods.refresh_token(client, client_configuration, refresh_token=env["GC_REFRESH_TOKEN"])
 return client.get(endpoint)
 raise

The first call to /api/v2/analytics/interactions/queues works fine. After roughly an hour, the worker hits a 401. The except block fires, prints the refresh message, and calls the auth method again. The next client.get(endpoint) still sends the old Authorization: Bearer <expired_token> header. I checked the network trace and the SDK isn’t updating the header store.

[2024-09-12 14:32:11] INFO: Requesting /api/v2/analytics/interactions/queues
[2024-09-12 14:32:15] ERROR: 401 Unauthorized - Access token expired
[2024-09-12 14:32:15] INFO: Token expired. Triggering silent refresh...
[2024-09-12 14:32:16] DEBUG: OAuth exchange successful. New token generated.
[2024-09-12 14:32:16] INFO: Retrying request...
[2024-09-12 14:32:17] ERROR: 401 Unauthorized - Access token expired

Header cache is definitely stuck. Tried clearing it manually. Nothing. Step three: verify if the Python SDK actually supports in-place token mutation or if I need to manually patch the client_configuration.default_headers. I tried overriding client_configuration.default_headers['Authorization'] after the refresh call, but the internal request builder pulls from a cached session object that ignores the dict update. The worker just loops through the retry and eventually times out. MuleSoft expects a clean exit code, so spinning up a fresh RestClient every hour breaks the connection pooling we’ve set up. The refresh_token method definitely exchanges the token with the /oauth/token endpoint, but the payload never sticks to the active HTTP session. I’ve been staring at the genesyscloud.rest.auth module for two hours and the method signatures are pretty sparse.

Documentation explicitly states: “The PlatformClient automatically handles token refresh via the configured OAuth callback.” I copied this straight from the Java SDK examples and bound it to our Spring Boot workers. Why is the Python worker hanging? The Java client retries immediately. This just sits there. Try switching the batch logic to a Spring Boot service. The connection pool handles the queue differently. Documentation explicitly states: “Concurrent refresh requests are coalesced.” Why isn’t that happening here?

It’s blocking because the SDK drops the client_secret during the silent rotation, triggering a deadlocked HTTP retry. Passing AuthMethods.refresh_token(refresh_token=VAULT_TOKEN, client_id=APP_ID, client_secret=APP_SECRET) straight into PlatformClient.init() clears the queue. Don’t skip analytics:report:read in the scope list or the handshake stalls.

Cause: the client secret drop is…strange. we’ve seen similar precision drops when scopes are missing. the analytics read scope - it’s very sensitive.

Solution: the suggestion above about passing the client secret directly into PlatformClient.init() is correct. does the MuleSoft flow also set the client_id? I wonder if that’s a dependency.

hey! yeah, this is a weird one - we’ve been on Zoom Contact Center, Genesys Cloud for a while now and those token things can be tricky.

Cause: the client secret drop is…strange. we’ve seen similar precision drops when scopes are missing. the analytics read scope - it’s very sensitive.

totally agree. those scopes are super picky. It’s not always obvious which ones you need. We ran into a similar thing last month trying to pull historical data for a new Queue Configuration report.

Solution: the suggestion above about passing the client secret directly into PlatformClient.init() is correct. does the MuleSoft flow also set the client_id? I wonder if that’s a dependency.

good point about the client_id! double-check that’s being passed along too. But honestly, I just hardcode it in the Python script - seems to be the most reliable. Here’s what I usually do:

from genesyscloud.client import PlatformClient

PLATFORM_CLIENT_ID = "YOUR_CLIENT_ID"
PLATFORM_CLIENT_SECRET = "YOUR_CLIENT_SECRET"
PLATFORM_REFRESH_TOKEN = "YOUR_REFRESH_TOKEN"

platform_client = PlatformClient(
 auth_method=PlatformClient.auth_method.refresh_token(
 refresh_token=PLATFORM_REFRESH_TOKEN,
 client_id=PLATFORM_CLIENT_ID,
 client_secret=PLATFORM_CLIENT_SECRET
 )
)

I know it’s not ideal to hardcode stuff, but for background workers, it’s less of a security risk than letting the token refresh fail silently. Plus, it’s way easier to debug. Make sure you’ve got analytics:report:read in your SCOPES, and you should be good to go.