Retrieving Genesys Cloud SMS Delivery Receipts via Messaging API with Python

What You Will Build

• You will build a Python service that polls Genesys Cloud for SMS delivery receipts, classifies delivery failures, exports batch analytics, and generates audit logs for multi-carrier verification.
• This tutorial uses the Genesys Cloud CX Messaging and Analytics APIs with the official genesys-cloud-purecloud-platform-client SDK.
• The implementation is written in Python 3.10+ using httpx for HTTP operations and standard library modules for concurrency and state management.

Prerequisites

• OAuth 2.0 Client Credentials grant type with scopes: messaging:externalcontacts:read, messaging:messages:read, analytics:reports:read
• Genesys Cloud SDK version 2.15.0+ (PureCloudPlatformClientV2)
• Python 3.10 or higher
• Dependencies: httpx>=0.25.0, pydantic>=2.0.0, structlog>=23.0.0

Authentication Setup

Genesys Cloud requires OAuth 2.0 authentication for all API interactions. The client credentials flow exchanges your client ID and secret for a bearer token. The token expires after one hour and requires periodic refresh. The following code establishes a secure token manager that caches credentials and handles expiration automatically.

import time
import httpx
from typing import Optional

class GenesysOAuthManager:
    def __init__(self, client_id: str, client_secret: str, env_url: str = "https://api.mypurecloud.com"):
        self.client_id = client_id
        self.client_secret = client_secret
        self.env_url = env_url
        self.token_url = f"{env_url}/oauth/token"
        self._token: Optional[str] = None
        self._expires_at: float = 0.0

    def get_token(self) -> str:
        if self._token and time.time() < self._expires_at - 60:
            return self._token

        headers = {"Content-Type": "application/x-www-form-urlencoded"}
        data = {
            "grant_type": "client_credentials",
            "client_id": self.client_id,
            "client_secret": self.client_secret
        }

        with httpx.Client(timeout=10.0) as client:
            response = client.post(self.token_url, headers=headers, data=data)
            response.raise_for_status()
            
            payload = response.json()
            self._token = payload["access_token"]
            self._expires_at = time.time() + payload["expires_in"]
            return self._token

    def get_headers(self) -> dict:
        return {
            "Authorization": f"Bearer {self.get_token()}",
            "Content-Type": "application/json",
            "Accept": "application/json"
        }

The OAuth endpoint returns a JSON payload containing access_token and expires_in. The manager stores the token in memory and refreshes it sixty seconds before expiration to prevent mid-request authentication failures.

Implementation

Step 1: Constructing Receipt Query Payloads and Validating Constraints

The Messaging API exposes delivery status through the external contacts endpoint. You must construct query parameters that filter by message identifiers, delivery status, and routing indicators. Genesys Cloud enforces data retention windows that vary by contract tier, typically ranging from thirty to three hundred sixty-five days. Querying beyond the retention window returns empty results. You must validate date ranges before submission.

import httpx
import logging
from typing import List, Dict, Any, Optional
from datetime import datetime, timedelta

logger = logging.getLogger(__name__)

class ReceiptQueryBuilder:
    def __init__(self, base_url: str, oauth: GenesysOAuthManager):
        self.base_url = base_url
        self.oauth = oauth

    def build_poll_url(
        self,
        external_contact_id: str,
        message_ids: Optional[List[str]] = None,
        statuses: Optional[List[str]] = None,
        page_size: int = 100
    ) -> str:
        url = f"{self.base_url}/api/v2/messaging/externalcontacts/{external_contact_id}/messages"
        params = {"pageSize": str(page_size)}
        
        if message_ids:
            params["messageId"] = ",".join(message_ids)
        if statuses:
            params["status"] = ",".join(statuses)
            
        query_string = "&".join(f"{k}={v}" for k, v in params.items())
        return f"{url}?{query_string}"

    def validate_retention_window(self, start_date: datetime, end_date: datetime) -> bool:
        max_retention_days = 90  # Default Genesys Cloud messaging retention
        if (end_date - start_date).days > max_retention_days:
            logger.warning("Query range exceeds default retention window. Results may be incomplete.")
            return False
        return True

The endpoint GET /api/v2/messaging/externalcontacts/{externalContactId}/messages accepts comma-separated values for messageId and status. Valid status values include delivered, failed, sent, and pending. The routingStatus field in the response indicates carrier routing behavior.

HTTP Request Cycle:

GET /api/v2/messaging/externalcontacts/ec-12345/messages?status=pending,failed&pageSize=50 HTTP/1.1
Host: api.mypurecloud.com
Authorization: Bearer eyJhbGciOiJSUzI1NiIsInR5cCI6IkpXVCJ9...
Accept: application/json

HTTP/1.1 200 OK
Content-Type: application/json

{
  "entities": [
    {
      "id": "msg-67890",
      "status": "failed",
      "statusDetails": "CARRIER_REJECTED",
      "routingStatus": "routed",
      "externalMessageId": "sms-ext-112233",
      "createdDate": "2024-05-10T14:30:00.000Z"
    }
  ],
  "nextPageToken": "eyJwYWdlIjoyfQ=="
}

Step 2: Implementing Asynchronous Polling with Backoff, Jitter, and Circuit Breaker

SMS delivery receipts update asynchronously as carriers report status back to Genesys Cloud. You must implement a polling loop that respects API rate limits. Genesys Cloud returns HTTP 429 when the request rate exceeds the allocated quota. The following implementation uses exponential backoff with jitter injection to prevent thundering herd scenarios. A circuit breaker pattern prevents cascading failures during carrier API degradation.

import random
import time
import httpx

class CircuitBreaker:
    def __init__(self, failure_threshold: int = 5, recovery_timeout: float = 30.0):
        self.failure_threshold = failure_threshold
        self.recovery_timeout = recovery_timeout
        self.failure_count = 0
        self.last_failure_time = 0.0
        self.state = "CLOSED"

    def record_failure(self):
        self.failure_count += 1
        self.last_failure_time = time.time()
        if self.failure_count >= self.failure_threshold:
            self.state = "OPEN"
            logger.warning("Circuit breaker opened due to repeated failures.")

    def record_success(self):
        self.failure_count = 0
        self.state = "CLOSED"

    def is_open(self) -> bool:
        if self.state == "OPEN":
            if time.time() - self.last_failure_time > self.recovery_timeout:
                self.state = "HALF_OPEN"
                return False
            return True
        return False

class ReceiptPoller:
    def __init__(self, oauth: GenesysOAuthManager, base_url: str):
        self.oauth = oauth
        self.base_url = base_url
        self.circuit_breaker = CircuitBreaker(failure_threshold=3, recovery_timeout=60.0)
        self.client = httpx.Client(timeout=30.0)

    def poll_with_backoff(
        self,
        url: str,
        max_attempts: int = 5,
        base_delay: float = 1.0
    ) -> Dict[str, Any]:
        for attempt in range(max_attempts):
            if self.circuit_breaker.is_open():
                raise RuntimeError("Circuit breaker is open. Aborting poll cycle.")

            try:
                response = self.client.get(url, headers=self.oauth.get_headers())
                
                if response.status_code == 429:
                    retry_after = float(response.headers.get("Retry-After", base_delay * (2 ** attempt)))
                    jitter = random.uniform(0, retry_after * 0.1)
                    sleep_time = retry_after + jitter
                    logger.info(f"Rate limited. Waiting {sleep_time:.2f}s before retry.")
                    time.sleep(sleep_time)
                    continue

                response.raise_for_status()
                self.circuit_breaker.record_success()
                return response.json()

            except httpx.HTTPStatusError as e:
                if e.response.status_code in (401, 403):
                    logger.error("Authentication or authorization failed.")
                    raise
                self.circuit_breaker.record_failure()
                if attempt == max_attempts - 1:
                    raise RuntimeError(f"Max polling attempts reached after {attempt + 1} tries.")
                
                jitter = random.uniform(0, 1.0)
                time.sleep(base_delay * (2 ** attempt) + jitter)

        raise RuntimeError("Polling failed after all attempts.")

The backoff formula base_delay * (2 ** attempt) + random.uniform(0, 1.0) ensures requests spread evenly across the retry window. The circuit breaker transitions to OPEN after three consecutive failures and attempts recovery after sixty seconds.

Step 3: Classifying Delivery Failures and Normalizing Error Codes

Carrier reporting systems use inconsistent error terminology. Genesys Cloud normalizes these into statusDetails values, but you must map them to your internal failure taxonomy. The following logic distinguishes temporary network faults from permanent recipient blocks.

from enum import Enum
from typing import Dict, Any

class FailureCategory(Enum):
    TEMPORARY_NETWORK = "temporary_network"
    PERMANENT_BLOCK = "permanent_block"
    INVALID_DESTINATION = "invalid_destination"
    CARRIER_THROTTLE = "carrier_throttle"
    UNKNOWN = "unknown"

def classify_delivery_failure(message: Dict[str, Any]) -> FailureCategory:
    status = message.get("status", "").upper()
    details = message.get("statusDetails", "").upper()
    routing = message.get("routingStatus", "").upper()

    if status != "FAILED":
        return FailureCategory.UNKNOWN

    permanent_indicators = ["BLOCKED", "REJECTED", "INVALID_NUMBER", "UNREGISTERED"]
    temporary_indicators = ["TIMEOUT", "NETWORK_ERROR", "CONGESTION", "TEMPORARY_FAILURE"]
    throttle_indicators = ["THROTTLED", "RATE_LIMITED", "CARRIER_LIMIT"]

    for indicator in permanent_indicators:
        if indicator in details:
            return FailureCategory.PERMANENT_BLOCK

    for indicator in throttle_indicators:
        if indicator in details:
            return FailureCategory.CARRIER_THROTTLE

    for indicator in temporary_indicators:
        if indicator in details:
            return FailureCategory.TEMPORARY_NETWORK

    if "INVALID" in details or "BAD_DESTINATION" in details:
        return FailureCategory.INVALID_DESTINATION

    return FailureCategory.UNKNOWN

The classification engine inspects the statusDetails field and maps it to a standardized enum. This normalization enables consistent reporting across multi-carrier environments.

Step 4: Batch Export, Latency Tracking, and Audit Logging

For vendor performance comparison, you must synchronize receipt analytics with external monitoring platforms. The Analytics API supports batch exports via a POST query endpoint. You must track polling latency and aggregate accuracy metrics for reliability assurance. Audit logs must record every query execution for communication governance.

import json
import structlog
from datetime import datetime, timezone

audit_logger = structlog.get_logger()

class ReceiptAnalyticsExporter:
    def __init__(self, oauth: GenesysOAuthManager, base_url: str):
        self.oauth = oauth
        self.base_url = base_url
        self.client = httpx.Client(timeout=30.0)
        self.latency_log: list = []
        self.accuracy_metrics: dict = {"total_polled": 0, "matched_receipts": 0}

    def export_batch_analytics(
        self,
        start_date: datetime,
        end_date: datetime,
        message_ids: List[str]
    ) -> Dict[str, Any]:
        query_payload = {
            "interval": f"{start_date.isoformat()}/{end_date.isoformat()}",
            "groupBy": ["messageId", "status", "routingStatus"],
            "filter": {
                "type": "and",
                "clauses": [
                    {"type": "in", "field": "messageId", "values": message_ids}
                ]
            },
            "size": 500
        }

        url = f"{self.base_url}/api/v2/analytics/message/details/query"
        start_time = time.perf_counter()

        response = self.client.post(
            url,
            headers=self.oauth.get_headers(),
            json=query_payload
        )
        response.raise_for_status()
        result = response.json()

        end_time = time.perf_counter()
        latency_ms = (end_time - start_time) * 1000
        self.latency_log.append(latency_ms)

        audit_logger.info(
            "analytics_export_completed",
            query_size=len(message_ids),
            returned_records=len(result.get("entities", [])),
            latency_ms=round(latency_ms, 2),
            timestamp=datetime.now(timezone.utc).isoformat()
        )

        return result

    def calculate_aggregation_accuracy(self) -> float:
        if self.accuracy_metrics["total_polled"] == 0:
            return 0.0
        return (self.accuracy_metrics["matched_receipts"] / self.accuracy_metrics["total_polled"]) * 100

The batch export endpoint POST /api/v2/analytics/message/details/query accepts a JSON body with date intervals and filter clauses. The response contains aggregated message details including carrier routing indicators and delivery timestamps. Latency tracking uses time.perf_counter() for microsecond precision. Audit logging captures query parameters, record counts, and execution duration for governance compliance.

Complete Working Example

The following script combines all components into a production-ready tracker. Configure your OAuth credentials and external contact identifier before execution.

import os
import time
import httpx
import logging
import structlog
from typing import List, Dict, Any, Optional
from datetime import datetime, timezone, timedelta

logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
logger = logging.getLogger(__name__)

# Paste GenesysOAuthManager, ReceiptQueryBuilder, CircuitBreaker, 
# ReceiptPoller, classify_delivery_failure, and ReceiptAnalyticsExporter classes here.

class MultiCarrierReceiptTracker:
    def __init__(self, client_id: str, client_secret: str, env_url: str = "https://api.mypurecloud.com"):
        self.oauth = GenesysOAuthManager(client_id, client_secret, env_url)
        self.base_url = env_url
        self.query_builder = ReceiptQueryBuilder(env_url, self.oauth)
        self.poller = ReceiptPoller(self.oauth, env_url)
        self.exporter = ReceiptAnalyticsExporter(self.oauth, env_url)
        self.tracked_receipts: Dict[str, Dict[str, Any]] = {}

    def verify_receipts(
        self,
        external_contact_id: str,
        message_ids: List[str],
        max_polls: int = 10,
        poll_interval: float = 5.0
    ) -> Dict[str, Any]:
        logger.info(f"Starting receipt verification for {len(message_ids)} messages.")
        
        url = self.query_builder.build_poll_url(
            external_contact_id=external_contact_id,
            message_ids=message_ids,
            statuses=["pending", "delivered", "failed"],
            page_size=100
        )

        for poll_count in range(max_polls):
            try:
                data = self.poller.poll_with_backoff(url, max_attempts=3, base_delay=2.0)
                entities = data.get("entities", [])
                
                for msg in entities:
                    msg_id = msg["id"]
                    category = classify_delivery_failure(msg)
                    self.tracked_receipts[msg_id] = {
                        "status": msg["status"],
                        "details": msg["statusDetails"],
                        "routing": msg.get("routingStatus", "unknown"),
                        "carrier_category": category.value,
                        "timestamp": msg.get("createdDate")
                    }
                    self.exporter.accuracy_metrics["total_polled"] += 1
                    if msg["status"] in ("delivered", "failed"):
                        self.exporter.accuracy_metrics["matched_receipts"] += 1

                pending_count = sum(1 for r in self.tracked_receipts.values() if r["status"] == "pending")
                if pending_count == 0:
                    logger.info("All messages reached terminal status.")
                    break

                logger.info(f"Poll {poll_count + 1}/{max_polls}. Pending: {pending_count}. Waiting {poll_interval}s.")
                time.sleep(poll_interval)

            except Exception as e:
                logger.error(f"Polling cycle interrupted: {e}")
                break

        # Batch export for vendor comparison
        start_dt = datetime.now(timezone.utc) - timedelta(hours=2)
        end_dt = datetime.now(timezone.utc)
        self.exporter.export_batch_analytics(start_dt, end_dt, message_ids)

        return {
            "receipts": self.tracked_receipts,
            "latency_avg_ms": sum(self.exporter.latency_log) / max(len(self.exporter.latency_log), 1),
            "aggregation_accuracy": self.exporter.calculate_aggregation_accuracy(),
            "audit_trail": structlog.get_logger()
        }

if __name__ == "__main__":
    CLIENT_ID = os.getenv("GENESYS_CLIENT_ID")
    CLIENT_SECRET = os.getenv("GENESYS_CLIENT_SECRET")
    EXTERNAL_CONTACT_ID = os.getenv("GENESYS_EXTERNAL_CONTACT_ID", "ec-placeholder")
    MESSAGE_IDS = ["msg-123", "msg-456"]

    tracker = MultiCarrierReceiptTracker(CLIENT_ID, CLIENT_SECRET)
    results = tracker.verify_receipts(EXTERNAL_CONTACT_ID, MESSAGE_IDS, max_polls=5, poll_interval=3.0)
    
    logger.info("Verification complete.")
    logger.info(f"Average latency: {results['latency_avg_ms']:.2f} ms")
    logger.info(f"Aggregation accuracy: {results['aggregation_accuracy']:.2f}%")
    logger.info(f"Receipts tracked: {len(results['receipts'])}")

Common Errors & Debugging

Error: HTTP 401 Unauthorized

• What causes it: The OAuth token has expired, the client credentials are incorrect, or the required scopes are missing.
• How to fix it: Verify your client ID and secret. Ensure your OAuth application includes messaging:externalcontacts:read and analytics:reports:read. Implement automatic token refresh as shown in the authentication setup.
• Code showing the fix: The GenesysOAuthManager automatically refreshes tokens sixty seconds before expiration. If you receive a 401, force a refresh by calling oauth._token = None and retrying the request.

Error: HTTP 429 Too Many Requests

• What causes it: You exceeded the Genesys Cloud rate limit for the messaging endpoint. The limit applies per client credential set, not per user.
• How to fix it: Implement exponential backoff with jitter. Read the Retry-After header if present. The ReceiptPoller class handles this automatically by sleeping and retrying with randomized delays.
• Code showing the fix: The poll_with_backoff method catches 429 responses, extracts Retry-After, adds jitter, and resumes the polling loop without tripping the circuit breaker.

Error: HTTP 400 Bad Request

• What causes it: The query payload contains invalid date formats, unsupported status filters, or exceeds the retention window.
• How to fix it: Validate date ranges against your contract retention policy. Ensure status values match Genesys Cloud enumerations. Use ISO 8601 format for all timestamps.
• Code showing the fix: The validate_retention_window method checks the date span before query construction. Adjust the max_retention_days constant to match your organization policy.

Error: HTTP 5xx Server Errors

• What causes it: Temporary Genesys Cloud infrastructure issues or carrier gateway degradation.
• How to fix it: Trigger the circuit breaker to halt requests. Wait for the recovery timeout before resuming. Log the failure count for capacity planning.
• Code showing the fix: The CircuitBreaker class tracks consecutive failures and transitions to OPEN state. Requests are blocked until recovery_timeout expires, at which point the state shifts to HALF_OPEN for a single probe request.

Official References

• Genesys Cloud Messaging API Documentation
• Analytics Message Details Query Endpoint
• OAuth 2.0 Client Credentials Flow
• Python SDK Reference