Debugging null wrapUpCode in Genesys Cloud Analytics Detail Queries

What You Will Build

• A Python script that executes a conversation details query, explicitly requests wrap-up codes, processes partitioned results, and distinguishes between query misconfiguration and legitimate null values.
• Direct HTTP communication with the Genesys Cloud /api/v2/analytics/conversations/details/query endpoint using httpx.
• Production-grade error handling, 429 retry logic, and pagination across analytics partitions.

Prerequisites

• OAuth client credentials (client ID and client secret) for a Genesys Cloud organization
• Required OAuth scope: analytics:query
• Python 3.9 or higher
• External dependencies: httpx (version 0.25+), pydantic (optional for validation, not required for this script)
• Install dependencies: pip install httpx

Authentication Setup

Genesys Cloud uses OAuth 2.0 client credentials flow for server-to-server API access. You must obtain a bearer token before executing analytics queries. The token expires after thirty minutes and requires analytics:query scope for this endpoint.

import httpx
import time
from typing import Optional

OAUTH_TOKEN_URL = "https://login.mypurecloud.com/oauth/token"

def get_access_token(client_id: str, client_secret: str) -> str:
    """
    Retrieves a Genesys Cloud OAuth2 bearer token.
    Raises httpx.HTTPStatusError on 4xx/5xx responses.
    """
    payload = {
        "grant_type": "client_credentials",
        "client_id": client_id,
        "client_secret": client_secret,
        "scope": "analytics:query"
    }
    
    with httpx.Client() as client:
        response = client.post(
            OAUTH_TOKEN_URL,
            data=payload,
            headers={"Content-Type": "application/x-www-form-urlencoded"}
        )
        response.raise_for_status()
        token_data = response.json()
        return token_data["access_token"]

Store the token in memory or a secure cache. Rotate it before expiration in long-running processes. The analytics endpoint rejects requests with missing or expired tokens with a 401 Unauthorized response.

Implementation

Step 1: Construct the Detail Query Payload

The wrapUpCode field returns null for three distinct reasons:

1. The groupBy array does not contain "conversations"
2. The select array does not explicitly list "wrapUpCode"
3. The conversation actually completed without an agent selecting a wrap-up code

You must configure both groupBy and select correctly. The analytics engine does not infer fields. If you omit wrapUpCode from select, the response object will either exclude the field or return null.

import json
from datetime import datetime, timedelta, timezone

def build_detail_query_payload(date_from: str, date_to: str, page_size: int = 25) -> dict:
    """
    Constructs a valid analytics detail query payload.
    Requires explicit groupBy and select configuration.
    """
    query = {
        "dateFrom": date_from,
        "dateTo": date_to,
        "groupBy": [
            "conversations"
        ],
        "select": [
            "conversation.id",
            "conversation.type",
            "conversation.mediaType",
            "wrapUpCode",
            "wrapUpCode.name",
            "wrapUpCode.code",
            "agent.id",
            "agent.name",
            "queue.id",
            "queue.name"
        ],
        "filter": [],
        "size": page_size
    }
    return query

The size parameter controls how many entities return per partition. Genesys Cloud returns up to one thousand entities per request. Setting size to twenty-five or fifty reduces memory pressure and prevents timeout errors during parsing.

Step 2: Execute Query with Retry Logic

The analytics endpoint enforces strict rate limits. Heavy detail queries trigger 429 Too Many Requests. Implement exponential backoff with jitter to avoid cascading failures across your integration.

import httpx
import time
import random
from typing import Dict, Any

GENESYS_BASE_URL = "https://api.mypurecloud.com"
DETAIL_QUERY_PATH = "/api/v2/analytics/conversations/details/query"

def execute_analytics_query(
    access_token: str,
    payload: Dict[str, Any],
    max_retries: int = 5,
    base_delay: float = 1.0
) -> Dict[str, Any]:
    """
    Posts the analytics query with 429 retry logic.
    Returns the parsed JSON response.
    """
    headers = {
        "Authorization": f"Bearer {access_token}",
        "Content-Type": "application/json",
        "Accept": "application/json"
    }
    
    url = f"{GENESYS_BASE_URL}{DETAIL_QUERY_PATH}"
    
    with httpx.Client(timeout=30.0) as client:
        attempt = 0
        while attempt <= max_retries:
            try:
                response = client.post(url, headers=headers, json=payload)
                
                if response.status_code == 200:
                    return response.json()
                elif response.status_code == 429:
                    retry_after = float(response.headers.get("Retry-After", base_delay * (2 ** attempt)))
                    jitter = random.uniform(0, retry_after * 0.1)
                    wait_time = retry_after + jitter
                    print(f"Rate limited (429). Retrying in {wait_time:.2f}s...")
                    time.sleep(wait_time)
                    attempt += 1
                else:
                    response.raise_for_status()
            except httpx.HTTPStatusError as exc:
                if attempt < max_retries:
                    attempt += 1
                    continue
                raise exc
            except httpx.RequestError as exc:
                print(f"Network error: {exc}")
                raise exc
                
        raise RuntimeError("Max retries exceeded for analytics query")

The retry loop checks for 429 status codes and respects the Retry-After header when present. The jitter prevents thundering herd problems when multiple workers synchronize retries.

Step 3: Parse Partitions and Handle Null Wrap-Up Codes

The response structure contains a partitions array. Each partition holds an entities list. You must iterate through every partition to capture all conversations. The wrapUpCode field appears as an object with id, name, and code properties, or as null when no wrap-up occurred.

from typing import List, Dict, Any, Optional

def process_detail_results(response: Dict[str, Any]) -> List[Dict[str, Any]]:
    """
    Flattens partitioned analytics results and extracts wrap-up codes.
    Distinguishes between missing data and query misconfiguration.
    """
    extracted_conversations = []
    partitions = response.get("partitions", [])
    
    if not partitions:
        print("Warning: No partitions returned. Verify date range and filters.")
        return extracted_conversations
        
    for partition in partitions:
        entities = partition.get("entities", [])
        for entity in entities:
            conversation_id = entity.get("conversation", {}).get("id")
            wrap_up_raw = entity.get("wrapUpCode")
            
            # Determine wrap-up status
            if wrap_up_raw is None:
                wrap_up_code = None
                wrap_up_name = None
                wrap_up_type = "NOT_ASSIGNED"
            elif isinstance(wrap_up_raw, dict) and wrap_up_raw.get("id"):
                wrap_up_code = wrap_up_raw.get("code")
                wrap_up_name = wrap_up_raw.get("name")
                wrap_up_type = "ASSIGNED"
            else:
                wrap_up_code = None
                wrap_up_name = None
                wrap_up_type = "MALFORMED_RESPONSE"
                
            record = {
                "conversationId": conversation_id,
                "wrapUpCode": wrap_up_code,
                "wrapUpName": wrap_up_name,
                "wrapUpStatus": wrap_up_type,
                "agentId": entity.get("agent", {}).get("id"),
                "queueId": entity.get("queue", {}).get("id")
            }
            extracted_conversations.append(record)
            
    return extracted_conversations

The parsing logic explicitly checks for null versus empty objects. A null value in wrapUpCode indicates the agent completed the interaction without selecting a wrap-up code. This is valid business data, not a query error. If every record returns null, verify that your select array includes "wrapUpCode" and that your groupBy contains "conversations".

Step 4: Pagination Across Partitions

The analytics detail query does not use nextPageToken. It returns all requested data in the initial response, chunked into the partitions array. If your query exceeds the internal limit, Genesys Cloud splits the results across multiple partitions automatically. You process them sequentially.

To request additional pages when your organization has high volume, you must adjust the dateFrom and dateTo window or apply filters to reduce result sets. The API enforces a hard limit of one thousand entities per request. If you require more, split the time range into smaller intervals.

def split_time_range(date_from: str, date_to: str, interval_hours: int = 24) -> List[tuple]:
    """
    Splits a large date range into smaller intervals to respect API limits.
    Returns list of (start, end) ISO strings.
    """
    start = datetime.fromisoformat(date_from.replace("Z", "+00:00"))
    end = datetime.fromisoformat(date_to.replace("Z", "+00:00"))
    intervals = []
    current = start
    
    while current < end:
        next_time = min(current + timedelta(hours=interval_hours), end)
        intervals.append((current.isoformat(), next_time.isoformat()))
        current = next_time
        
    return intervals

Complete Working Example

The following script combines authentication, query construction, retry logic, and partition processing into a single runnable module. Replace the placeholder credentials with your OAuth client values.

import httpx
import time
import random
from typing import Dict, Any, List
from datetime import datetime, timedelta, timezone

OAUTH_TOKEN_URL = "https://login.mypurecloud.com/oauth/token"
GENESYS_BASE_URL = "https://api.mypurecloud.com"
DETAIL_QUERY_PATH = "/api/v2/analytics/conversations/details/query"

def get_access_token(client_id: str, client_secret: str) -> str:
    payload = {
        "grant_type": "client_credentials",
        "client_id": client_id,
        "client_secret": client_secret,
        "scope": "analytics:query"
    }
    with httpx.Client() as client:
        response = client.post(OAUTH_TOKEN_URL, data=payload, headers={"Content-Type": "application/x-www-form-urlencoded"})
        response.raise_for_status()
        return response.json()["access_token"]

def build_detail_query_payload(date_from: str, date_to: str, page_size: int = 50) -> Dict[str, Any]:
    return {
        "dateFrom": date_from,
        "dateTo": date_to,
        "groupBy": ["conversations"],
        "select": [
            "conversation.id", "conversation.type", "conversation.mediaType",
            "wrapUpCode", "wrapUpCode.name", "wrapUpCode.code",
            "agent.id", "agent.name", "queue.id", "queue.name"
        ],
        "filter": [],
        "size": page_size
    }

def execute_analytics_query(access_token: str, payload: Dict[str, Any], max_retries: int = 5) -> Dict[str, Any]:
    headers = {
        "Authorization": f"Bearer {access_token}",
        "Content-Type": "application/json",
        "Accept": "application/json"
    }
    url = f"{GENESYS_BASE_URL}{DETAIL_QUERY_PATH}"
    
    with httpx.Client(timeout=30.0) as client:
        attempt = 0
        while attempt <= max_retries:
            try:
                response = client.post(url, headers=headers, json=payload)
                if response.status_code == 200:
                    return response.json()
                elif response.status_code == 429:
                    retry_after = float(response.headers.get("Retry-After", 1.0 * (2 ** attempt)))
                    time.sleep(retry_after + random.uniform(0, 0.5))
                    attempt += 1
                else:
                    response.raise_for_status()
            except httpx.HTTPStatusError as exc:
                if attempt < max_retries:
                    attempt += 1
                    continue
                raise exc
            except httpx.RequestError as exc:
                raise RuntimeError(f"Network failure: {exc}") from exc
        raise RuntimeError("Max retries exceeded")

def process_detail_results(response: Dict[str, Any]) -> List[Dict[str, Any]]:
    extracted = []
    for partition in response.get("partitions", []):
        for entity in partition.get("entities", []):
            conv_id = entity.get("conversation", {}).get("id")
            wrap_raw = entity.get("wrapUpCode")
            
            if wrap_raw is None:
                code, name, status = None, None, "NOT_ASSIGNED"
            elif isinstance(wrap_raw, dict) and wrap_raw.get("id"):
                code, name, status = wrap_raw.get("code"), wrap_raw.get("name"), "ASSIGNED"
            else:
                code, name, status = None, None, "MALFORMED"
                
            extracted.append({
                "conversationId": conv_id,
                "wrapUpCode": code,
                "wrapUpName": name,
                "status": status,
                "agentId": entity.get("agent", {}).get("id")
            })
    return extracted

if __name__ == "__main__":
    CLIENT_ID = "YOUR_CLIENT_ID"
    CLIENT_SECRET = "YOUR_CLIENT_SECRET"
    
    # Define a narrow window to avoid rate limits during testing
    end_time = datetime.now(timezone.utc)
    start_time = end_time - timedelta(hours=2)
    date_from = start_time.isoformat()
    date_to = end_time.isoformat()
    
    try:
        token = get_access_token(CLIENT_ID, CLIENT_SECRET)
        payload = build_detail_query_payload(date_from, date_to, page_size=25)
        response = execute_analytics_query(token, payload)
        results = process_detail_results(response)
        
        null_count = sum(1 for r in results if r["status"] == "NOT_ASSIGNED")
        assigned_count = sum(1 for r in results if r["status"] == "ASSIGNED")
        
        print(f"Total conversations: {len(results)}")
        print(f"Assigned wrap-up codes: {assigned_count}")
        print(f"Null wrap-up codes: {null_count}")
        
        for record in results[:5]:
            print(record)
            
    except httpx.HTTPStatusError as e:
        print(f"API Error {e.response.status_code}: {e.response.text}")
    except Exception as e:
        print(f"Execution failed: {e}")

Common Errors & Debugging

Error: 401 Unauthorized

• Cause: Missing, expired, or malformed bearer token. The OAuth client lacks the analytics:query scope.
• Fix: Regenerate the token using the client credentials flow. Verify the scope parameter includes analytics:query. Check that the client ID and secret match a valid Genesys Cloud OAuth client.

Error: 403 Forbidden

• Cause: The OAuth client exists but lacks permission to access analytics data. The organization enforces data access policies that restrict the client.
• Fix: Assign the required analytics permissions to the OAuth client in the Genesys Cloud admin console. Ensure the client is enabled and not suspended.

Error: 400 Bad Request

• Cause: Malformed query payload. Common mistakes include omitting groupBy, using incorrect field names in select, or providing invalid ISO 8601 timestamps.
• Fix: Validate the JSON structure. Ensure groupBy contains exactly ["conversations"]. Verify select includes "wrapUpCode". Check that dateFrom precedes dateTo.

Error: 429 Too Many Requests

• Cause: Rate limit exceeded. Analytics detail queries consume significant server resources. Exceeding the per-minute request quota triggers throttling.
• Fix: Implement exponential backoff with jitter. Reduce query frequency. Split large date ranges into smaller intervals. Monitor the Retry-After header.

Error: wrapUpCode consistently returns null

• Cause: Query misconfiguration or legitimate business data. Agents may complete conversations without selecting a wrap-up code.
• Fix: Verify groupBy includes "conversations" and select includes "wrapUpCode". Test with a known conversation that has a wrap-up code assigned. If the known conversation still returns null, the query payload is incorrect. If only specific conversations return null, the agents did not assign wrap-up codes.

Official References

• Genesys Cloud Analytics Conversations Details Query API
• Genesys Cloud OAuth 2.0 Client Credentials Flow
• Genesys Cloud Analytics Rate Limits and Best Practices
• Python httpx Documentation