Trying to automate user onboarding by reading a CSV and pushing records via the Genesys Cloud Python SDK. The goal is simple: read names, emails, and queue assignments from a local file, then call the API to create the users. It works fine for the first few dozen, then it crashes with a 429 Too Many Requests error. I’ve added a time.sleep(0.5) between calls, but the rate limit seems to hit hard regardless. The documentation mentions rate limits per client ID, but I’m not seeing how to gracefully handle the retry logic without writing a custom wrapper around the SDK client.
Here’s the core loop I’m using:
import time
import csv
from platform_sdk.client import PureCloudPlatformClientV2
client = PureCloudPlatformClientV2(client_id, client_secret)
auth_api = client.get_authentication_api()
users_api = client.get_users_api()
with open('new_users.csv', 'r') as f:
reader = csv.DictReader(f)
for row in reader:
try:
body = {
'name': row['name'],
'email': row['email'],
'division_id': 'default_division_id'
}
users_api.post_users(body=body)
time.sleep(0.5) # Attempting to throttle
except Exception as e:
print(f"Failed creating {row['name']}: {e}")
break
The error message is standard:
platform_sdk.rest.ApiException: (429) Reason: Too Many Requests
I don’t want to rewrite the SDK’s retry mechanism. Is there a built-in way in the Python SDK to handle rate limiting for batch operations? Or am I stuck writing my own exponential backoff loop? The post_users method doesn’t seem to have a wait or retry parameter. Just looking for a clean way to keep the script running without manual intervention when the rate limit hits.