Retrieve Real-Time Queue Metrics via the Genesys Cloud Statistics API

What You Will Build

• A Python script that authenticates to Genesys Cloud and retrieves real-time queue statistics, including waiting call counts and available agent counts.
• This tutorial uses the Genesys Cloud PureCloudPlatformClientV2 Python SDK.
• The implementation covers OAuth authentication, endpoint construction, and handling pagination for large organizations.

Prerequisites

• OAuth Client: A Genesys Cloud OAuth client with the api_user or api_gateway grant type.
• Required Scopes:
  • queue:realtime:view (Required for viewing real-time queue statistics)
  • analytics:queues:view (Often required depending on specific metric granularity, though queue:realtime:view is primary for live data)
• SDK Version: genesys-cloud-purecloud-platform-client-v2 >= 130.0.0
• Language/Environment: Python 3.8+
• Dependencies:
  • genesys-cloud-purecloud-platform-client-v2
  • python-dotenv (for secure credential management)

Authentication Setup

Genesys Cloud uses OAuth 2.0 for authentication. For server-to-server integrations (like this script), you will use the Client Credentials flow. The Python SDK handles token acquisition and refresh automatically when initialized correctly.

Create a .env file in your project root to store credentials securely.

# .env
GENESYS_CLIENT_ID=your_client_id_here
GENESYS_CLIENT_SECRET=your_client_secret_here
GENESYS_REGION=us-east-1

Initialize the SDK client. The PureCloudPlatformClientV2 class manages the authentication context.

from purecloud_platform_client_v2 import PureCloudPlatformClientV2
from purecloud_platform_client_v2.api import QueueApi
from purecloud_platform_client_v2.model import QueueRealtimeQuery
import os
from dotenv import load_dotenv

# Load environment variables
load_dotenv()

def get_platform_client():
    """
    Initializes and returns the Genesys Cloud Platform Client.
    """
    client_id = os.getenv("GENESYS_CLIENT_ID")
    client_secret = os.getenv("GENESYS_CLIENT_SECRET")
    region = os.getenv("GENESYS_REGION", "us-east-1")
    
    if not client_id or not client_secret:
        raise EnvironmentError("GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET must be set in .env")

    # Initialize the platform client
    platform_client = PureCloudPlatformClientV2(
        client_id=client_id,
        client_secret=client_secret,
        region=region
    )
    
    return platform_client

Implementation

Step 1: Constructing the Real-Time Query

The core endpoint for real-time queue data is POST /api/v2/analytics/queues/details/query. Unlike standard REST GET requests, this endpoint uses a POST body to define the query parameters. This allows for complex filtering and aggregation of real-time metrics.

The key object is QueueRealtimeQuery. You must specify the groupBy and metrics you require. For queue-specific data, grouping by queue is standard.

from purecloud_platform_client_v2.model import GroupBy, QueueRealtimeQuery

def build_queue_query():
    """
    Constructs a QueueRealtimeQuery object to fetch waiting counts and agent availability.
    """
    # Define the metrics you want to retrieve.
    # 'waitingCount' = Number of conversations waiting in the queue.
    # 'availableAgents' = Number of agents currently available to take calls.
    # 'busyAgents' = Number of agents currently on a call or wrap-up.
    metrics = [
        "waitingCount",
        "availableAgents",
        "busyAgents",
        "talkingAgents",
        "wrapupAgents"
    ]

    # Group by queue to get stats per queue.
    # You can also group by 'skill' or 'member' if needed.
    group_by = GroupBy(
        group_by="queue"
    )

    # Create the query object
    query = QueueRealtimeQuery(
        group_by=group_by,
        metrics=metrics
    )

    return query

Note on Metrics: The waitingCount metric represents the total number of interactions currently waiting in the queue. availableAgents represents agents who are logged in, not on a call, and not in wrap-up, and are eligible to receive interactions from this queue.

Step 2: Executing the API Call

Use the QueueApi class from the SDK. You need to pass the queue_api instance and the query object built in Step 1.

def fetch_realtime_queue_stats(platform_client):
    """
    Fetches real-time queue statistics using the QueueApi.
    """
    queue_api = QueueApi(platform_client)
    query = build_queue_query()

    try:
        # Execute the query
        # The API returns a QueueRealtimeResponse
        response = queue_api.post_analytics_queues_details_query(body=query)
        
        return response
    except Exception as e:
        print(f"Error fetching queue stats: {e}")
        raise

Step 3: Processing Results and Handling Pagination

The API returns a QueueRealtimeResponse object. This object contains a list of QueueRealtimeEntity objects in the entities field. Each entity corresponds to a queue (since we grouped by queue).

If you have more queues than the default page size (usually 200), you must handle pagination. The response includes a nextPageUri if more data is available.

def process_queue_response(response):
    """
    Parses the QueueRealtimeResponse and prints key metrics.
    """
    if not response.entities:
        print("No queue data returned.")
        return

    print(f"{'Queue ID':<30} {'Name':<25} {'Waiting':<10} {'Available':<10} {'Busy':<10}")
    print("-" * 85)

    for entity in response.entities:
        queue_id = entity.id
        queue_name = entity.name
        
        # Extract metrics from the entity
        # Metrics are stored in a dictionary-like structure within the entity
        waiting_count = entity.metrics.get("waitingCount", 0)
        available_agents = entity.metrics.get("availableAgents", 0)
        busy_agents = entity.metrics.get("busyAgents", 0)

        print(f"{queue_id:<30} {queue_name:<25} {waiting_count:<10} {available_agents:<10} {busy_agents:<10}")

    # Check for pagination
    if response.next_page_uri:
        print("\n... Pagination detected. Use nextPageUri to fetch remaining queues.")
        print(f"Next Page URI: {response.next_page_uri}")

Complete Working Example

Below is the full, copy-pasteable Python script. Save this as get_queue_stats.py. Ensure you have installed the dependencies: pip install genesys-cloud-purecloud-platform-client-v2 python-dotenv.

import os
import sys
from dotenv import load_dotenv

# Import Genesys Cloud SDK
from purecloud_platform_client_v2 import PureCloudPlatformClientV2
from purecloud_platform_client_v2.api import QueueApi
from purecloud_platform_client_v2.model import QueueRealtimeQuery, GroupBy

def load_credentials():
    """Loads credentials from .env file."""
    load_dotenv()
    client_id = os.getenv("GENESYS_CLIENT_ID")
    client_secret = os.getenv("GENESYS_CLIENT_SECRET")
    region = os.getenv("GENESYS_REGION", "us-east-1")
    
    if not client_id or not client_secret:
        raise EnvironmentError("GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET are required in .env file.")
        
    return client_id, client_secret, region

def init_client(client_id, client_secret, region):
    """Initializes the PureCloudPlatformClientV2."""
    try:
        platform_client = PureCloudPlatformClientV2(
            client_id=client_id,
            client_secret=client_secret,
            region=region
        )
        return platform_client
    except Exception as e:
        print(f"Failed to initialize client: {e}")
        sys.exit(1)

def get_realtime_queue_data(platform_client):
    """
    Retrieves real-time queue statistics.
    
    Returns:
        list: A list of dictionaries containing queue metrics.
    """
    queue_api = QueueApi(platform_client)
    
    # Define metrics to retrieve
    metrics = [
        "waitingCount",
        "availableAgents",
        "busyAgents",
        "talkingAgents",
        "wrapupAgents",
        "offlineAgents"
    ]

    # Define grouping
    group_by = GroupBy(group_by="queue")

    # Build query
    query = QueueRealtimeQuery(
        group_by=group_by,
        metrics=metrics
    )

    try:
        # Execute API call
        response = queue_api.post_analytics_queues_details_query(body=query)
        
        # Process entities
        queue_data = []
        if response.entities:
            for entity in response.entities:
                queue_info = {
                    "id": entity.id,
                    "name": entity.name,
                    "waitingCount": entity.metrics.get("waitingCount", 0),
                    "availableAgents": entity.metrics.get("availableAgents", 0),
                    "busyAgents": entity.metrics.get("busyAgents", 0),
                    "talkingAgents": entity.metrics.get("talkingAgents", 0),
                    "wrapupAgents": entity.metrics.get("wrapupAgents", 0),
                    "offlineAgents": entity.metrics.get("offlineAgents", 0)
                }
                queue_data.append(queue_info)
        
        # Handle Pagination (Optional: Implement loop if nextPageUri exists)
        if response.next_page_uri:
            print("Warning: Results are paginated. Only first page retrieved.")
            
        return queue_data

    except Exception as e:
        print(f"API Error: {e}")
        raise

def main():
    # 1. Load Credentials
    client_id, client_secret, region = load_credentials()
    
    # 2. Initialize Client
    platform_client = init_client(client_id, client_secret, region)
    
    # 3. Fetch Data
    print("Fetching real-time queue statistics...")
    queue_data = get_realtime_queue_data(platform_client)
    
    # 4. Display Data
    if not queue_data:
        print("No queue data found.")
        return

    print(f"\n{'Queue Name':<30} {'Waiting':<10} {'Avail':<10} {'Busy':<10} {'Talking':<10} {'Wrapup':<10}")
    print("-" * 90)
    
    for q in queue_data:
        print(f"{q['name']:<30} {q['waitingCount']:<10} {q['availableAgents']:<10} "
              f"{q['busyAgents']:<10} {q['talkingAgents']:<10} {q['wrapupAgents']:<10}")

if __name__ == "__main__":
    main()

Common Errors & Debugging

Error: 401 Unauthorized

Cause: The OAuth token is invalid, expired, or the client credentials are incorrect.
Fix:

1. Verify GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET in your .env file match the values in the Genesys Cloud Admin Console.
2. Ensure the OAuth client has not been revoked.
3. Check that the region in .env matches your organization’s region (e.g., us-east-1, eu-west-1).

# Debugging tip: Print the error response body
try:
    response = queue_api.post_analytics_queues_details_query(body=query)
except Exception as e:
    if hasattr(e, 'body'):
        print(f"Error Body: {e.body}")
    raise

Error: 403 Forbidden

Cause: The OAuth client lacks the required scope queue:realtime:view.
Fix:

1. Go to Genesys Cloud Admin Console > Security > OAuth Clients.
2. Edit your client.
3. Add queue:realtime:view to the scopes list.
4. Save and restart your script. Note: Scope changes may take a few minutes to propagate.

Error: 429 Too Many Requests

Cause: You have exceeded the rate limit for the Statistics API. Real-time endpoints have stricter rate limits than historical data endpoints.
Fix: Implement exponential backoff. Do not poll this endpoint faster than every 5-10 seconds unless specifically required by your use case.

import time

def fetch_with_retry(queue_api, query, max_retries=3):
    for attempt in range(max_retries):
        try:
            return queue_api.post_analytics_queues_details_query(body=query)
        except Exception as e:
            if hasattr(e, 'status') and e.status == 429:
                wait_time = 2 ** attempt
                print(f"Rate limited. Waiting {wait_time} seconds...")
                time.sleep(wait_time)
            else:
                raise
    raise Exception("Max retries exceeded")

Error: Empty entities List

Cause: No queues match the query criteria, or no agents are logged in to any queues.
Fix:

1. Ensure there are queues created in your Genesys Cloud org.
2. Ensure at least one agent is logged in. Real-time statistics are only populated when there is activity or logged-in members associated with the queue.
3. Verify you are querying the correct region.

Official References

• Genesys Cloud Queue Real-Time API Documentation
• Python SDK Reference for QueueApi
• OAuth Scopes Reference