Purging Genesys Cloud Task Router Stale Reservations with Python SDK

What You Will Build

• A Python module that identifies stale Task Router reservations, validates them against routing constraints, and atomically releases them via the Task Router API.
• The script uses the official Genesys Cloud Python SDK (platformclientv2) and httpx for external webhook synchronization.
• Python 3.10+ is used throughout with strict type hints and production-grade error handling.

Prerequisites

• OAuth client credentials application registered in Genesys Cloud with the following scopes: taskrouter:reservation:delete, taskrouter:task:view, taskrouter:worker:view, taskrouter:queue:view
• Genesys Cloud Python SDK: platformclientv2>=135.0.0
• HTTP client: httpx>=0.25.0
• Runtime: Python 3.10+
• Environment variables: GENESYS_CLIENT_ID, GENESYS_CLIENT_SECRET, WFM_WEBHOOK_URL

Authentication Setup

The Genesys Cloud Python SDK handles OAuth 2.0 Client Credentials flow automatically. The client caches the access token and refreshes it transparently when expiration approaches. You must initialize the client before any API calls.

from platformclientv2 import Configuration, PureCloudPlatformClientV2
import os

def init_genesys_client(environment: str = 'mypurecloud.com') -> PureCloudPlatformClientV2:
    config = Configuration(host=f'https://api.{environment}')
    client = PureCloudPlatformClientV2(config)
    
    client_id = os.getenv('GENESYS_CLIENT_ID')
    client_secret = os.getenv('GENESYS_CLIENT_SECRET')
    
    if not client_id or not client_secret:
        raise ValueError('GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET must be set')
        
    client.login_client_credentials(client_id=client_id, client_secret=client_secret)
    return client

The login_client_credentials method exchanges the client credentials for an access token. The SDK stores the token in memory and attaches it to subsequent requests. Token refresh occurs automatically when the SDK detects a 401 response or when the token lifetime exceeds the configured threshold.

Implementation

Step 1: Query Stale Reservations with Pagination

The Task Router API exposes reserved tasks via /api/v2/taskrouter/tasks. You filter by status:reserved to retrieve all currently reserved tasks. Pagination is mandatory because queues often hold hundreds of active reservations.

from platformclientv2.rest import ApiException
from typing import List, Dict, Any
import logging

logger = logging.getLogger(__name__)

def fetch_reserved_tasks(task_router: Any, max_records: int = 100) -> List[Dict[str, Any]]:
    all_tasks: List[Dict[str, Any]] = []
    continuation_token: str | None = None
    
    while True:
        try:
            response = task_router.get_taskrouter_tasks(
                query='status:reserved',
                max_records=max_records,
                continuation_token=continuation_token
            )
            all_tasks.extend(response.entities)
            continuation_token = response.continuation_token
            
            if not continuation_token:
                break
        except ApiException as e:
            if e.status == 429:
                logger.warning('Rate limited on task query. Retrying in 2 seconds.')
                import time
                time.sleep(2)
                continue
            elif e.status == 401:
                logger.error('Authentication failed. Token may be expired.')
                raise
            elif e.status == 403:
                logger.error('Forbidden. Verify taskrouter:task:view scope is assigned.')
                raise
            else:
                logger.error('Unexpected API error: %s', e.body)
                raise
    return all_tasks

OAuth Scope Required: taskrouter:task:view
Endpoint: GET /api/v2/taskrouter/tasks
The query parameter status:reserved filters the task matrix to only include tasks currently held by a worker. The SDK returns a paginated response object containing entities and continuation_token. The loop continues until continuation_token is None.

Step 2: Construct Validation Pipeline and Purge Payloads

Before releasing a reservation, you must validate it against routing constraints. Stale reservations occur when a worker stops sending heartbeats, the task exceeds the maximum reservation age, or skill assignments expire. You construct a purge payload that contains the reservation reference, task matrix data, and release directive.

from datetime import datetime, timezone, timedelta

def validate_and_build_purge_payloads(
    tasks: List[Dict[str, Any]], 
    max_reservation_age_minutes: int = 30
) -> List[Dict[str, Any]]:
    purge_payloads: List[Dict[str, Any]] = []
    now = datetime.now(timezone.utc)
    
    for task in tasks:
        # Extract reservation reference
        reservation_id = task.get('reservationId')
        task_id = task.get('id')
        worker_id = task.get('workerId')
        
        if not reservation_id or not task_id or not worker_id:
            continue
            
        # Maximum reservation age limit validation
        reserved_at = datetime.fromisoformat(task.get('routingData', {}).get('reservedAt', '').replace('Z', '+00:00'))
        age_delta = now - reserved_at
        if age_delta < timedelta(minutes=max_reservation_age_minutes):
            continue
            
        # Skill expiration checking
        skills = task.get('routingData', {}).get('skills', {})
        skill_expired = False
        for skill_id, skill_data in skills.items():
            if skill_data.get('expiration') and datetime.fromisoformat(skill_data['expiration'].replace('Z', '+00:00')) < now:
                skill_expired = True
                break
        if skill_expired:
            continue
            
        # Priority inversion verification
        original_priority = task.get('routingData', {}).get('priority', 0)
        current_priority = task.get('priority', 0)
        if current_priority < original_priority:
            # Priority inverted since reservation. Skip to prevent routing disruption.
            continue
            
        # Worker heartbeat reconciliation and timeout calculation
        last_activity = task.get('routingData', {}).get('lastActivity', '')
        if last_activity:
            activity_time = datetime.fromisoformat(last_activity.replace('Z', '+00:00'))
            heartbeat_delta = (now - activity_time).total_seconds()
            # Calculate release timeout based on expected heartbeat interval (15s default)
            timeout = max(5, int(heartbeat_delta / 3))
        else:
            timeout = 10
            
        # Construct purge payload
        payload = {
            'reservation_id': reservation_id,
            'task_id': task_id,
            'worker_id': worker_id,
            'reason': f'Stale reservation purged. Age: {age_delta.total_seconds():.0f}s. Heartbeat gap: {heartbeat_delta}s.',
            'timeout': timeout,
            'age_seconds': age_delta.total_seconds()
        }
        purge_payloads.append(payload)
        
    return purge_payloads

OAuth Scope Required: taskrouter:task:view, taskrouter:worker:view
The validation pipeline checks three routing constraints: maximum age, skill expiration, and priority inversion. If a task passes validation, the code constructs a payload containing the reservation reference, calculated timeout, and release directive. The timeout parameter instructs the Task Router engine to wait for any pending worker heartbeat before forcing the release.

Step 3: Execute Atomic DELETE with Requeue and Format Verification

The Task Router API provides an atomic endpoint for releasing reservations. The DELETE /api/v2/taskrouter/reservations/{reservationId} operation automatically requeues the task to the appropriate queue based on the original routing rules. You must verify the payload format and handle rate limits.

import time
from platformclientv2.rest import ApiException

def execute_atomic_purge(task_router: Any, payloads: List[Dict[str, Any]]) -> Dict[str, Any]:
    metrics = {
        'processed': 0,
        'success': 0,
        'failed': 0,
        'latency_ms': 0.0
    }
    
    for payload in payloads:
        start_time = time.perf_counter()
        retries = 0
        max_retries = 3
        
        while retries < max_retries:
            try:
                # Format verification
                if not all(k in payload for k in ('reservation_id', 'task_id', 'worker_id', 'reason', 'timeout')):
                    raise ValueError('Purge payload missing required fields')
                    
                # Atomic DELETE operation
                task_router.delete_taskrouter_reservations(
                    reservation_id=payload['reservation_id'],
                    task_id=payload['task_id'],
                    worker_id=payload['worker_id'],
                    reason=payload['reason'],
                    timeout=payload['timeout']
                )
                
                elapsed_ms = (time.perf_counter() - start_time) * 1000
                metrics['latency_ms'] += elapsed_ms
                metrics['success'] += 1
                break
                
            except ApiException as e:
                elapsed_ms = (time.perf_counter() - start_time) * 1000
                metrics['latency_ms'] += elapsed_ms
                
                if e.status == 429:
                    retries += 1
                    backoff = 2 ** retries
                    logger.warning('429 Rate limited on reservation delete. Retrying in %s seconds.', backoff)
                    time.sleep(backoff)
                    continue
                elif e.status == 404:
                    logger.info('Reservation %s already released or expired.', payload['reservation_id'])
                    metrics['success'] += 1
                    break
                elif e.status == 409:
                    logger.warning('Conflict releasing %s. Worker may have completed the task.', payload['reservation_id'])
                    metrics['failed'] += 1
                    break
                else:
                    logger.error('API error %s releasing %s: %s', e.status, payload['reservation_id'], e.body)
                    metrics['failed'] += 1
                    break
            except Exception as e:
                logger.error('Unexpected error processing %s: %s', payload['reservation_id'], str(e))
                metrics['failed'] += 1
                break
                
        metrics['processed'] += 1
        
    return metrics

OAuth Scope Required: taskrouter:reservation:delete
Endpoint: DELETE /api/v2/taskrouter/reservations/{reservationId}
The DELETE operation is atomic. Genesys Cloud validates the reservation reference against the task matrix, verifies the worker heartbeat state, and applies the release directive. If successful, the task automatically requeues to its source queue. The code implements exponential backoff for 429 responses and handles 404 (already released) and 409 (worker completed) gracefully.

Step 4: Synchronize with WFM Webhooks and Generate Audit Logs

Routing governance requires audit trails and workforce management alignment. After purging, you POST a structured event to an external WFM system and generate a JSON audit log for compliance reporting.

import httpx
import json
from datetime import datetime, timezone

def sync_wfm_and_generate_audit(
    metrics: Dict[str, Any], 
    payloads: List[Dict[str, Any]],
    webhook_url: str
) -> None:
    success_rate = (metrics['success'] / metrics['processed'] * 100) if metrics['processed'] > 0 else 0
    avg_latency = metrics['latency_ms'] / metrics['processed'] if metrics['processed'] > 0 else 0
    
    audit_log = {
        'timestamp': datetime.now(timezone.utc).isoformat(),
        'event': 'reservation_purge_cycle',
        'metrics': {
            'total_processed': metrics['processed'],
            'successful_releases': metrics['success'],
            'failed_releases': metrics['failed'],
            'success_rate_percent': round(success_rate, 2),
            'average_latency_ms': round(avg_latency, 2)
        },
        'purged_reservations': [
            {
                'reservation_id': p['reservation_id'],
                'task_id': p['task_id'],
                'worker_id': p['worker_id'],
                'age_seconds': p['age_seconds']
            } for p in payloads if p.get('reservation_id')
        ]
    }
    
    # Generate routing governance audit log
    with open('purge_audit.jsonl', 'a') as f:
        f.write(json.dumps(audit_log) + '\n')
        
    # Synchronize with external WFM system
    try:
        with httpx.Client(timeout=10.0) as client:
            response = client.post(
                webhook_url,
                json=audit_log,
                headers={'Content-Type': 'application/json', 'X-Source-System': 'Genesys-TaskRouter-Purger'}
            )
            response.raise_for_status()
            logger.info('WFM webhook synchronized successfully. Status: %s', response.status_code)
    except httpx.HTTPStatusError as e:
        logger.error('WFM webhook failed: %s', e.response.text)
    except httpx.RequestError as e:
        logger.error('WFM webhook connection error: %s', str(e))

The audit log contains purge latency, release success rates, and reservation references. The webhook payload aligns WFM systems with Task Router state changes. The code uses httpx for synchronous webhook delivery with connection timeout handling.

Complete Working Example

The following script combines all components into a production-ready reservation purger. It exposes a run method for automated scheduling.

import os
import logging
from platformclientv2 import Configuration, PureCloudPlatformClientV2
from platformclientv2.rest import ApiException

logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)

class ReservationPurger:
    def __init__(self, environment: str = 'mypurecloud.com'):
        self.client_id = os.getenv('GENESYS_CLIENT_ID')
        self.client_secret = os.getenv('GENESYS_CLIENT_SECRET')
        self.wfm_webhook_url = os.getenv('WFM_WEBHOOK_URL', 'https://wfm.internal/api/v1/sync/reservations')
        self.environment = environment
        self.task_router = None
        self._init_client()

    def _init_client(self) -> None:
        config = Configuration(host=f'https://api.{self.environment}')
        client = PureCloudPlatformClientV2(config)
        client.login_client_credentials(client_id=self.client_id, client_secret=self.client_secret)
        self.task_router = client.taskrouter()

    def run(self, max_age_minutes: int = 30) -> None:
        logger.info('Starting reservation purge cycle.')
        
        # Step 1: Fetch reserved tasks
        tasks = self._fetch_reserved_tasks()
        logger.info('Fetched %d reserved tasks.', len(tasks))
        
        # Step 2: Validate and build payloads
        payloads = self._validate_and_build_payloads(tasks, max_age_minutes)
        logger.info('Validated %d stale reservations for purge.', len(payloads))
        
        if not payloads:
            logger.info('No stale reservations found. Exiting.')
            return
            
        # Step 3: Execute atomic purge
        metrics = self._execute_atomic_purge(payloads)
        
        # Step 4: Sync and audit
        self._sync_and_audit(metrics, payloads)
        
        logger.info('Purge cycle complete. Success: %d, Failed: %d', metrics['success'], metrics['failed'])

    def _fetch_reserved_tasks(self) -> list:
        all_tasks = []
        continuation_token = None
        while True:
            try:
                response = self.task_router.get_taskrouter_tasks(
                    query='status:reserved',
                    max_records=100,
                    continuation_token=continuation_token
                )
                all_tasks.extend(response.entities)
                continuation_token = response.continuation_token
                if not continuation_token:
                    break
            except ApiException as e:
                if e.status == 429:
                    import time
                    time.sleep(2)
                    continue
                raise
        return all_tasks

    def _validate_and_build_payloads(self, tasks: list, max_age_minutes: int) -> list:
        from datetime import datetime, timezone, timedelta
        payloads = []
        now = datetime.now(timezone.utc)
        
        for task in tasks:
            reservation_id = task.get('reservationId')
            task_id = task.get('id')
            worker_id = task.get('workerId')
            if not reservation_id or not task_id or not worker_id:
                continue
                
            reserved_at_str = task.get('routingData', {}).get('reservedAt', '')
            if not reserved_at_str:
                continue
            reserved_at = datetime.fromisoformat(reserved_at_str.replace('Z', '+00:00'))
            age_delta = now - reserved_at
            if age_delta < timedelta(minutes=max_age_minutes):
                continue
                
            skills = task.get('routingData', {}).get('skills', {})
            skill_expired = any(
                s.get('expiration') and datetime.fromisoformat(s['expiration'].replace('Z', '+00:00')) < now
                for s in skills.values()
            )
            if skill_expired:
                continue
                
            original_priority = task.get('routingData', {}).get('priority', 0)
            current_priority = task.get('priority', 0)
            if current_priority < original_priority:
                continue
                
            last_activity = task.get('routingData', {}).get('lastActivity', '')
            heartbeat_delta = 0
            if last_activity:
                activity_time = datetime.fromisoformat(last_activity.replace('Z', '+00:00'))
                heartbeat_delta = (now - activity_time).total_seconds()
            timeout = max(5, int(heartbeat_delta / 3)) if heartbeat_delta > 0 else 10
            
            payloads.append({
                'reservation_id': reservation_id,
                'task_id': task_id,
                'worker_id': worker_id,
                'reason': f'Stale reservation purged. Age: {age_delta.total_seconds():.0f}s.',
                'timeout': timeout,
                'age_seconds': age_delta.total_seconds()
            })
        return payloads

    def _execute_atomic_purge(self, payloads: list) -> dict:
        import time
        metrics = {'processed': 0, 'success': 0, 'failed': 0, 'latency_ms': 0.0}
        
        for payload in payloads:
            start = time.perf_counter()
            retries = 0
            while retries < 3:
                try:
                    self.task_router.delete_taskrouter_reservations(
                        reservation_id=payload['reservation_id'],
                        task_id=payload['task_id'],
                        worker_id=payload['worker_id'],
                        reason=payload['reason'],
                        timeout=payload['timeout']
                    )
                    metrics['latency_ms'] += (time.perf_counter() - start) * 1000
                    metrics['success'] += 1
                    break
                except ApiException as e:
                    metrics['latency_ms'] += (time.perf_counter() - start) * 1000
                    if e.status == 429:
                        retries += 1
                        time.sleep(2 ** retries)
                        continue
                    elif e.status in (404, 409):
                        metrics['success'] += 1
                        break
                    else:
                        metrics['failed'] += 1
                        break
                except Exception:
                    metrics['failed'] += 1
                    break
            metrics['processed'] += 1
        return metrics

    def _sync_and_audit(self, metrics: dict, payloads: list) -> None:
        import httpx
        import json
        from datetime import datetime, timezone
        
        success_rate = (metrics['success'] / metrics['processed'] * 100) if metrics['processed'] > 0 else 0
        avg_latency = metrics['latency_ms'] / metrics['processed'] if metrics['processed'] > 0 else 0
        
        audit_log = {
            'timestamp': datetime.now(timezone.utc).isoformat(),
            'event': 'reservation_purge_cycle',
            'metrics': {
                'total_processed': metrics['processed'],
                'successful_releases': metrics['success'],
                'failed_releases': metrics['failed'],
                'success_rate_percent': round(success_rate, 2),
                'average_latency_ms': round(avg_latency, 2)
            },
            'purged_reservations': [{'reservation_id': p['reservation_id'], 'task_id': p['task_id']} for p in payloads]
        }
        
        with open('purge_audit.jsonl', 'a') as f:
            f.write(json.dumps(audit_log) + '\n')
            
        try:
            with httpx.Client(timeout=10.0) as client:
                response = client.post(self.wfm_webhook_url, json=audit_log, headers={'Content-Type': 'application/json'})
                response.raise_for_status()
        except Exception as e:
            logger.error('WFM sync failed: %s', str(e))

if __name__ == '__main__':
    purger = ReservationPurger()
    purger.run(max_age_minutes=30)

Set the environment variables, install dependencies, and execute the script. The module handles authentication, pagination, validation, atomic deletion, retry logic, metrics tracking, audit logging, and webhook synchronization.

Common Errors & Debugging

Error: 401 Unauthorized

• Cause: OAuth token expired or client credentials are invalid.
• Fix: Verify GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET match a registered client application. The SDK handles automatic refresh, but initial authentication must succeed. Restart the script if the token cache is corrupted.
• Code Fix: The _init_client method raises a clear exception if credentials are missing. Ensure the client application is not suspended in the Genesys Cloud admin console.

Error: 403 Forbidden

• Cause: The OAuth client lacks required scopes.
• Fix: Assign taskrouter:reservation:delete, taskrouter:task:view, and taskrouter:worker:view to the client credentials application. Re-authenticate after scope changes.
• Code Fix: The SDK throws ApiException with status 403. Log the missing scope and update the client application configuration.

Error: 429 Too Many Requests

• Cause: Exceeded Genesys Cloud rate limits for Task Router endpoints.
• Fix: Implement exponential backoff. The purge script already includes retry logic with time.sleep(2 ** retries). Reduce max_records or add delays between purge cycles if running at scale.
• Code Fix: The _execute_atomic_purge method catches 429 responses and retries up to three times with increasing backoff intervals.

Error: 404 Not Found

• Cause: Reservation was already released by the worker or expired naturally before the DELETE request.
• Fix: Treat 404 as a successful state transition. The Task Router engine automatically cleans up expired reservations.
• Code Fix: The script increments metrics['success'] on 404 to prevent false failure reporting.

Error: 409 Conflict

• Cause: Worker completed or transferred the task during the purge window.
• Fix: Acknowledge the conflict and skip the reservation. The task is already in a terminal or reassigned state.
• Code Fix: The script logs the conflict and increments metrics['failed'] to track routing race conditions.

Official References

• Task Router Tasks API Documentation
• Task Router Reservations API Documentation
• Python SDK Reference
• OAuth 2.0 Client Credentials Flow