Hitting 429 Too Many Requests repeatedly when trying to update 500 users via the Genesys Cloud Python SDK. The standard retry logic in our script isn’t catching the rate limit headers correctly, so it just crashes or hangs.
We’re using genesyscloud_python version 143.0.0. The goal is to batch update user attributes (specifically division_id and skills) for a large cohort. I’ve implemented a basic exponential backoff with jitter based on the Retry-After header, but the SDK’s internal client seems to be throwing a generic ApiException before I can parse the response headers properly.
Here’s the loop structure:
from genesyscloud.rest import Configuration
from genesyscloud.users.api import UsersApi
import time
import random
def update_users_bulk(user_ids, config):
users_api = UsersApi(config)
batch_size = 50
for i in range(0, len(user_ids), batch_size):
batch = user_ids[i:i+batch_size]
for uid in batch:
try:
# Simplified update payload
body = {"division_id": "new_div_123"}
users_api.update_user(user_id=uid, body=body)
except Exception as e:
if e.status == 429:
# Trying to extract Retry-After
retry_after = e.headers.get('Retry-After', 5)
wait_time = int(retry_after) + random.uniform(0, 1)
print(f"Rate limited. Waiting {wait_time}s")
time.sleep(wait_time)
# Retry logic here? Or does the SDK handle this?
else:
raise e
The issue is that e.headers is often None or empty when the 429 hits, even though Postman shows the Retry-After header clearly.
Is there a specific method in the Python SDK to configure global retry policies for 429s? Or do I need to drop down to the urllib3 layer to hook into the response handling? We’re currently falling back to a hardcoded time.sleep() which is inefficient.
Also, is there a way to get the current rate limit window from the API directly, rather than guessing?