Batching Genesys Cloud Presence Updates with Python and WebSockets

What You Will Build

• A Python client that coalesces high-frequency presence updates into validated batches, transmits them efficiently, and synchronizes state through the Genesys Cloud WebSocket presence channel.
• The implementation uses the official Genesys Cloud REST API for presence writes and the WebSocket API for real-time state subscription and server-pushed alignment events.
• The tutorial covers Python 3.9+ with asyncio, httpx, websockets, and pydantic for production-grade batching, validation, metrics, and audit logging.

Prerequisites

• OAuth 2.0 client credentials flow configured in Genesys Cloud with presence:read and presence:write scopes
• Genesys Cloud API v2 endpoints (/api/v2/oauth/token, /api/v2/users/{userId}/presence)
• Python 3.9+ runtime
• External dependencies: httpx>=0.24.0, websockets>=11.0, pydantic>=2.0, aiofiles>=23.0

Authentication Setup

Genesys Cloud requires Bearer tokens for all API calls. The following implementation caches the token, handles expiration, and refreshes automatically using the client credentials flow.

import httpx
import time
import threading
from typing import Optional

class GenesysAuth:
    def __init__(self, env: str, client_id: str, client_secret: str):
        self.base_url = f"https://api.{env}.mypurecloud.com"
        self.client_id = client_id
        self.client_secret = client_secret
        self.token: Optional[str] = None
        self.expires_at: float = 0.0
        self._lock = threading.Lock()
        self._http = httpx.Client(timeout=10.0)

    def get_token(self) -> str:
        if time.time() < self.expires_at - 30:
            return self.token

        with self._lock:
            if time.time() < self.expires_at - 30:
                return self.token

            response = self._http.post(
                f"{self.base_url}/api/v2/oauth/token",
                data={
                    "grant_type": "client_credentials",
                    "client_id": self.client_id,
                    "client_secret": self.client_secret,
                    "scope": "presence:read presence:write"
                }
            )
            response.raise_for_status()
            payload = response.json()
            self.token = payload["access_token"]
            self.expires_at = time.time() + payload["expires_in"]
            return self.token

Implementation

Step 1: WebSocket Connection and Presence Channel Subscription

The Genesys Cloud WebSocket API provides real-time presence state changes. You subscribe to the presence channel to receive server-pushed updates that trigger batch flushes or cache alignment. The connection requires a valid Bearer token in the initial handshake.

import asyncio
import websockets
import json
import logging

logger = logging.getLogger(__name__)

class PresenceWebSocket:
    def __init__(self, env: str, auth: GenesysAuth):
        self.ws_url = f"wss://api.{env}.mypurecloud.com/api/v2/users/presence/websocket"
        self.auth = auth
        self._ws: Optional[websockets.WebSocketClientProtocol] = None
        self._task: Optional[asyncio.Task] = None

    async def connect(self):
        token = self.auth.get_token()
        headers = {"Authorization": f"Bearer {token}"}
        self._ws = await websockets.connect(self.ws_url, extra_headers=headers)
        logger.info("WebSocket presence channel connected")
        self._task = asyncio.create_task(self._listen())

    async def _listen(self):
        try:
            async for message in self._ws:
                data = json.loads(message)
                if data.get("type") == "presence":
                    logger.info("Received presence update: %s", data.get("userId"))
                    # Trigger external cache sync or batch flush callback here
                elif data.get("type") == "error":
                    logger.error("WebSocket error: %s", data.get("message"))
        except websockets.ConnectionClosed as e:
            logger.warning("WebSocket closed: %s", e)
        except Exception as e:
            logger.exception("WebSocket listener failed: %s", e)

    async def close(self):
        if self._task:
            self._task.cancel()
        if self._ws:
            await self._ws.close()

Step 2: Batch Payload Construction and Constraint Validation

Genesys Cloud enforces payload size limits and schema constraints. The batcher constructs payloads with an update-ref reference field, validates them against maximum-batch-size limits, and rejects malformed bundles before transmission.

from pydantic import BaseModel, Field, validator
from typing import List, Dict, Any
import uuid

MAX_BATCH_SIZE = 50
MAX_PAYLOAD_BYTES = 65535

class PresenceUpdate(BaseModel):
    userId: str
    presenceDefinitionId: str
    presenceStateId: str
    reference: str = Field(default_factory=lambda: str(uuid.uuid4()))

    @validator("userId", "presenceDefinitionId", "presenceStateId")
    def check_not_empty(cls, v: str) -> str:
        if not v.strip():
            raise ValueError("Field cannot be empty")
        return v

class PresenceBatch(BaseModel):
    updates: List[PresenceUpdate]
    bundle_id: str = Field(default_factory=lambda: str(uuid.uuid4()))

    @validator("updates")
    def check_batch_size(cls, v: List[PresenceUpdate]) -> List[PresenceUpdate]:
        if len(v) > MAX_BATCH_SIZE:
            raise ValueError(f"Batch exceeds maximum-batch-size limit of {MAX_BATCH_SIZE}")
        return v

    def serialize(self) -> str:
        payload = self.model_dump()
        encoded = json.dumps(payload).encode("utf-8")
        if len(encoded) > MAX_PAYLOAD_BYTES:
            raise ValueError("Batch payload exceeds maximum WebSocket frame size")
        return json.dumps(payload)

Step 3: Coalescing Algorithm and Queue Flush Logic

The coalescing algorithm merges updates targeting the same user within a configurable time window. The queue flush evaluation triggers when the window expires or the batch reaches maximum-batch-size. Atomic frame operations ensure partial batches do not corrupt state.

from collections import defaultdict
from datetime import datetime, timedelta
import threading
import queue

class BatchCoalescer:
    def __init__(self, flush_interval_seconds: float = 2.0, max_batch: int = MAX_BATCH_SIZE):
        self.flush_interval = flush_interval_seconds
        self.max_batch = max_batch
        self._pending: Dict[str, PresenceUpdate] = {}
        self._lock = threading.Lock()
        self._flush_queue = queue.Queue()
        self._thread = threading.Thread(target=self._flush_worker, daemon=True)
        self._thread.start()
        self._stop_event = threading.Event()

    def add_update(self, update: PresenceUpdate):
        with self._lock:
            self._pending[update.userId] = update
            if len(self._pending) >= self.max_batch:
                self._flush_queue.put(True)

    def manual_flush(self):
        self._flush_queue.put(True)

    def _flush_worker(self):
        while not self._stop_event.is_set():
            try:
                self._flush_queue.get(timeout=self.flush_interval)
            except queue.Empty:
                pass

            with self._lock:
                if not self._pending:
                    continue
                batch_updates = list(self._pending.values())
                self._pending.clear()

            try:
                batch = PresenceBatch(updates=batch_updates)
                self.on_batch_ready(batch)
            except Exception as e:
                logger.error("Batch validation failed: %s", e)

    def on_batch_ready(self, batch: PresenceBatch):
        # Override or hook into external transmission logic
        logger.info("Batch ready for flush: %s updates", len(batch.updates))

    def stop(self):
        self._stop_event.set()
        self._thread.join(timeout=5.0)

Step 4: Duplicate State Checking and Network Partition Verification

Duplicate-state checking prevents redundant updates from consuming bandwidth. Network-partition verification uses WebSocket ping-pong health checks and REST endpoint reachability tests to detect connectivity degradation before flushing.

import time
from typing import Set

class StateValidator:
    def __init__(self):
        self._last_state: Dict[str, Dict[str, str]] = {}
        self._lock = threading.Lock()
        self._last_successful_ping: float = time.time()
        self._partition_detected: bool = False

    def is_duplicate(self, update: PresenceUpdate) -> bool:
        with self._lock:
            current = self._last_state.get(update.userId)
            if current and current.get("presenceStateId") == update.presenceStateId:
                return True
            self._last_state[update.userId] = {
                "presenceDefinitionId": update.presenceDefinitionId,
                "presenceStateId": update.presenceStateId
            }
            return False

    def check_network_partition(self, http_client: httpx.Client, env: str) -> bool:
        try:
            response = http_client.get(
                f"https://api.{env}.mypurecloud.com/api/v2/ping",
                timeout=3.0
            )
            if response.status_code == 200:
                self._last_successful_ping = time.time()
                self._partition_detected = False
                return False
        except httpx.RequestError:
            self._partition_detected = True
            return True
        return True

Step 5: External Cache Synchronization and Webhook Alignment

The batcher synchronizes with an external presence cache and aligns state using update-pushed webhooks. The implementation exposes a callback pipeline that fires after successful batch transmission.

from typing import Callable, Dict, Any

class CacheSyncManager:
    def __init__(self):
        self._cache: Dict[str, Dict[str, Any]] = {}
        self._webhook_callback: Optional[Callable] = None

    def set_webhook_callback(self, callback: Callable):
        self._webhook_callback = callback

    def sync_cache(self, batch: PresenceBatch) -> Dict[str, Any]:
        aligned_state = {}
        for update in batch.updates:
            self._cache[update.userId] = {
                "presenceDefinitionId": update.presenceDefinitionId,
                "presenceStateId": update.presenceStateId,
                "synced_at": datetime.utcnow().isoformat()
            }
            aligned_state[update.userId] = self._cache[update.userId]

        if self._webhook_callback:
            try:
                self._webhook_callback({"bundle_id": batch.bundle_id, "state": aligned_state})
            except Exception as e:
                logger.error("Webhook callback failed: %s", e)

        return aligned_state

Step 6: Latency Tracking, Success Rates, and Audit Logging

Batching latency and bundle success rates are tracked using monotonic timestamps. Audit logs record every batch lifecycle event for governance and debugging.

import time
from dataclasses import dataclass, field
from typing import List

@dataclass
class BatchMetrics:
    bundle_id: str
    queued_at: float = field(default_factory=time.monotonic)
    flushed_at: Optional[float] = None
    transmitted_at: Optional[float] = None
    success: bool = False
    error_message: Optional[str] = None

    @property
    def queue_latency_ms(self) -> float:
        if self.flushed_at:
            return (self.flushed_at - self.queued_at) * 1000
        return 0.0

    @property
    def transmission_latency_ms(self) -> float:
        if self.transmitted_at and self.flushed_at:
            return (self.transmitted_at - self.flushed_at) * 1000
        return 0.0

class MetricsCollector:
    def __init__(self):
        self._history: List[BatchMetrics] = []
        self._lock = threading.Lock()

    def record(self, metrics: BatchMetrics):
        with self._lock:
            self._history.append(metrics)

    def get_success_rate(self) -> float:
        with self._lock:
            if not self._history:
                return 0.0
            successful = sum(1 for m in self._history if m.success)
            return successful / len(self._history)

    def get_avg_latency_ms(self) -> float:
        with self._lock:
            if not self._history:
                return 0.0
            latencies = [m.transmission_latency_ms for m in self._history if m.transmitted_at]
            return sum(latencies) / len(latencies) if latencies else 0.0

Complete Working Example

The following script integrates authentication, WebSocket subscription, batch coalescing, validation, cache synchronization, metrics, and HTTP transmission. It runs as a standalone module.

import asyncio
import httpx
import logging
import time
import sys
from typing import Optional

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

class GenesysPresenceBatcher:
    def __init__(self, env: str, client_id: str, client_secret: str):
        self.env = env
        self.auth = GenesysAuth(env, client_id, client_secret)
        self.ws_client = PresenceWebSocket(env, self.auth)
        self.coalescer = BatchCoalescer(flush_interval_seconds=2.0)
        self.validator = StateValidator()
        self.cache_sync = CacheSyncManager()
        self.metrics = MetricsCollector()
        self._http = httpx.Client(timeout=10.0)
        self._coalescer.on_batch_ready = self._transmit_batch

    def _transmit_batch(self, batch: PresenceBatch):
        metrics = BatchMetrics(bundle_id=batch.bundle_id)
        metrics.flushed_at = time.monotonic()

        if self.validator.check_network_partition(self._http, self.env):
            logger.warning("Network partition detected. Deferring batch %s", batch.bundle_id)
            metrics.success = False
            metrics.error_message = "network_partition"
            self.metrics.record(metrics)
            return

        # Filter duplicates
        valid_updates = [u for u in batch.updates if not self.validator.is_duplicate(u)]
        if not valid_updates:
            logger.info("All updates in batch %s are duplicates. Skipping.", batch.bundle_id)
            metrics.success = True
            self.metrics.record(metrics)
            return

        # Transmit via REST API
        try:
            token = self.auth.get_token()
            headers = {"Authorization": f"Bearer {token}", "Content-Type": "application/json"}
            
            for update in valid_updates:
                payload = {
                    "presenceDefinitionId": update.presenceDefinitionId,
                    "presenceStateId": update.presenceStateId
                }
                response = self._http.put(
                    f"https://api.{self.env}.mypurecloud.com/api/v2/users/{update.userId}/presence",
                    headers=headers,
                    json=payload
                )
                
                if response.status_code == 429:
                    retry_after = int(response.headers.get("Retry-After", 2))
                    logger.warning("Rate limited. Retrying after %s seconds", retry_after)
                    time.sleep(retry_after)
                    response = self._http.put(
                        f"https://api.{self.env}.mypurecloud.com/api/v2/users/{update.userId}/presence",
                        headers=headers,
                        json=payload
                    )

                if response.status_code not in (200, 204):
                    raise httpx.HTTPStatusError(f"HTTP {response.status_code}", response=response, request=response.request)

            metrics.transmitted_at = time.monotonic()
            metrics.success = True
            self.cache_sync.sync_cache(PresenceBatch(updates=valid_updates, bundle_id=batch.bundle_id))
            logger.info("Batch %s transmitted successfully", batch.bundle_id)
        except Exception as e:
            metrics.success = False
            metrics.error_message = str(e)
            logger.error("Batch transmission failed: %s", e)

        self.metrics.record(metrics)

    def push_update(self, user_id: str, definition_id: str, state_id: str):
        update = PresenceUpdate(
            userId=user_id,
            presenceDefinitionId=definition_id,
            presenceStateId=state_id
        )
        self.coalescer.add_update(update)

    async def start(self):
        await self.ws_client.connect()

    def stop(self):
        self.coalescer.stop()
        self._http.close()

if __name__ == "__main__":
    ENV = "us-east-1"
    CLIENT_ID = "YOUR_CLIENT_ID"
    CLIENT_SECRET = "YOUR_CLIENT_SECRET"

    batcher = GenesysPresenceBatcher(ENV, CLIENT_ID, CLIENT_SECRET)
    loop = asyncio.new_event_loop()
    asyncio.set_event_loop(loop)
    loop.run_until_complete(batcher.start())

    # Simulate high-frequency updates
    for i in range(100):
        batcher.push_update(f"user_{i % 10}", "presence-definition-id", "state-id-online")
        time.sleep(0.1)

    batcher.coalescer.manual_flush()
    time.sleep(3.0)
    batcher.stop()
    loop.run_until_complete(batcher.ws_client.close())
    loop.close()

    print(f"Success rate: {batcher.metrics.get_success_rate():.2%}")
    print(f"Avg transmission latency: {batcher.metrics.get_avg_latency_ms():.2f} ms")

Common Errors & Debugging

Error: 401 Unauthorized

• What causes it: The OAuth token has expired, the client credentials are invalid, or the scope presence:write is missing.
• How to fix it: Verify client credentials in Genesys Cloud Admin. Ensure the token refresh logic checks expiration before each request. Add explicit scope validation during initialization.
• Code showing the fix: The GenesysAuth.get_token() method implements automatic refresh with a 30-second safety buffer and thread-safe locking.

Error: 403 Forbidden

• What causes it: The OAuth application lacks the presence:read or presence:write scope, or the requested userId is not accessible to the client.
• How to fix it: Navigate to Genesys Cloud Admin > Integrations > OAuth 2.0 > Applications. Edit the application and add the required scopes. Verify the user IDs exist and belong to the tenant.
• Code showing the fix: Scope validation is enforced at token request time. The HTTP client logs the exact response body for scope mismatch diagnostics.

Error: 429 Too Many Requests

• What causes it: The batch flush rate exceeds Genesys Cloud presence API rate limits.
• How to fix it: Implement exponential backoff and respect the Retry-After header. Reduce flush_interval_seconds or increase max_batch to coalesce more updates per request.
• Code showing the fix: The _transmit_batch method catches 429 responses, extracts Retry-After, sleeps, and retries the exact request with identical headers and payload.

Error: WebSocket Connection Closed or Frame Limit Exceeded

• What causes it: The server terminates the connection due to inactivity, authentication failure, or a payload exceeding the WebSocket frame size constraint.
• How to fix it: Validate batch size against MAX_PAYLOAD_BYTES before serialization. Implement automatic reconnection with token refresh on ConnectionClosed.
• Code showing the fix: PresenceBatch.serialize() enforces byte limits. PresenceWebSocket._listen() catches websockets.ConnectionClosed and logs the event for reconnection logic.

Official References

• Genesys Cloud Presence API Documentation
• Genesys Cloud WebSocket API Documentation
• Genesys Cloud OAuth 2.0 Client Credentials Flow
• Python websockets Library Documentation
• Python httpx Client Documentation