Is there a clean way to handle rate limiting when updating a large batch of users via the Genesys Cloud Platform API?
I am processing a list of 500+ user updates. I’m using the PureCloudPlatformClientV2 Python SDK. The initial requests succeed, but after about 20-30 calls, I start hitting 429 Too Many Requests. The SDK does not seem to have a built-in retry mechanism that respects the Retry-After header automatically in the way I expected for bulk operations.
Here is my current implementation:
from platform_sdk_python import Configuration, ApiClient, UsersApi
import time
config = Configuration()
config.host = 'api.mypurecloud.com'
# auth setup omitted for brevity
client = ApiClient(config)
users_api = UsersApi(client)
user_ids = ['id1', 'id2', 'id3'] # ... 500 ids
for uid in user_ids:
try:
body = {"email": "[email protected]"}
users_api.post_users_user(user_id=uid, body=body)
except Exception as e:
if e.status == 429:
# I tried a static sleep, but it's inefficient
time.sleep(1)
# Should I retry here or just break?
else:
raise e
I read this in the documentation:
“Clients should respect the Retry-After header if present in a 429 response. If not present, a standard exponential backoff strategy is recommended.”
How do I properly parse the Retry-After header from the SDK exception object? The exception doesn’t seem to expose headers directly in the standard Exception class. Do I need to catch a specific SDK exception type that contains response metadata? Or is there a utility in the SDK for this?
Also, should I be chunking the requests or using a semaphore to limit concurrency? The default SDK client seems to handle one request at a time in this loop, but I’m still getting throttled quickly.