Asynchronously Bulk-Archiving Genesys Cloud Conversations with aiohttp and Concurrent Throttling

What You Will Build

This script queries historical conversations, paginates through the result set, and submits conversation identifiers to the Genesys Cloud Archiving API in parallel batches. The implementation utilizes the Genesys Cloud Analytics Query API and Archives API. The code runs in Python 3.10+ using the aiohttp library for asynchronous HTTP operations.

Prerequisites

• OAuth 2.0 Client Credentials flow configured in Genesys Cloud
• Required scopes: analytics:conversation:query, archive:conversation:write
• Python 3.10 or newer
• External dependencies: aiohttp>=3.9.0, tenacity>=8.2.0, pydantic>=2.0.0 (for response validation)

Authentication Setup

Genesys Cloud uses bearer tokens issued via the OAuth 2.0 client credentials grant. Tokens expire after 3600 seconds. The following function fetches a token and caches it with an expiration timestamp. The script will refresh the token automatically when a 401 response occurs.

import os
import time
import aiohttp
from typing import Optional, Tuple

GENESYS_BASE_URL = os.getenv("GENESYS_BASE_URL", "https://api.mypurecloud.com")
CLIENT_ID = os.getenv("GENESYS_CLIENT_ID")
CLIENT_SECRET = os.getenv("GENESYS_CLIENT_SECRET")

_token_cache: Tuple[str, float] | None = None

async def get_access_token(session: aiohttp.ClientSession) -> str:
    global _token_cache
    current_time = time.time()
    
    if _token_cache and current_time < _token_cache[1] - 60:
        return _token_cache[0]
        
    auth_data = aiohttp.FormData()
    auth_data.add_field("grant_type", "client_credentials")
    auth_data.add_field("client_id", CLIENT_ID)
    auth_data.add_field("client_secret", CLIENT_SECRET)
    
    async with session.post(
        f"{GENESYS_BASE_URL}/oauth/token",
        data=auth_data,
        headers={"Accept": "application/json"}
    ) as response:
        response.raise_for_status()
        payload = await response.json()
        token = payload["access_token"]
        expires_in = payload.get("expires_in", 3600)
        _token_cache = (token, current_time + expires_in)
        return token

The function checks the cache first. If the token remains valid for at least sixty seconds, it returns the cached value. Otherwise, it posts to /oauth/token with the client credentials. The function stores the token alongside a Unix timestamp representing expiration. The minus sixty second buffer prevents edge-case expiration during concurrent request bursts.

Implementation

Step 1: Querying Conversations with Pagination

The Analytics Query API returns conversation identifiers in paginated blocks. You must send a POST request to /api/v2/analytics/conversations/details/query with a JSON body containing a date filter and page size. The response includes a nextPageId field. When nextPageId is absent, pagination completes.

import asyncio
from datetime import datetime, timedelta
from typing import AsyncGenerator, List

async def fetch_conversation_ids(
    session: aiohttp.ClientSession,
    token: str,
    start_date: datetime,
    end_date: datetime,
    page_size: int = 1000
) -> AsyncGenerator[List[str], None]:
    query_body = {
        "query": {
            "filter": {
                "type": "conversation",
                "value": {
                    "type": "date",
                    "value": {
                        "from": start_date.isoformat() + "Z",
                        "to": end_date.isoformat() + "Z"
                    }
                }
            }
        },
        "pageSize": page_size
    }
    
    while True:
        async with session.post(
            f"{GENESYS_BASE_URL}/api/v2/analytics/conversations/details/query",
            json=query_body,
            headers={"Authorization": f"Bearer {token}", "Accept": "application/json"}
        ) as response:
            if response.status == 401:
                token = await get_access_token(session)
                continue
            response.raise_for_status()
            data = await response.json()
            
        entities = data.get("entities", [])
        ids = [entity["id"] for entity in entities]
        if ids:
            yield ids
            
        next_page = data.get("nextPageId")
        if not next_page:
            break
        query_body["nextPageId"] = next_page

The function yields batches of conversation IDs as they arrive. This generator pattern prevents memory exhaustion when processing millions of records. The nextPageId field updates the request body for subsequent iterations. The loop terminates when the API omits nextPageId.

Step 2: Chunking and Concurrent Throttling

The Archiving API accepts a maximum of 1000 conversation identifiers per request. Sending unthrottled concurrent requests triggers HTTP 429 Too Many Requests responses. You must split the identifier stream into chunks and limit parallel execution using an asyncio semaphore.

from itertools import islice

def chunk_list(lst: List[str], chunk_size: int) -> List[List[str]]:
    it = iter(lst)
    return list(iter(lambda: list(islice(it, chunk_size)), []))

async def throttled_archiver(
    session: aiohttp.ClientSession,
    semaphore: asyncio.Semaphore,
    token: str,
    batch_ids: List[str]
) -> dict:
    async with semaphore:
        return await archive_batch(session, token, batch_ids)

The chunk_list helper divides the flat list of IDs into sublists. The throttled_archiver coroutine acquires the semaphore before proceeding. This guarantees that no more than the specified number of archive requests execute simultaneously. The semaphore releases automatically when the coroutine exits the context manager.

Step 3: Archiving Batches with Retry Logic

The archiving endpoint requires a POST request to /api/v2/archives/conversations. The body contains an ids array. Genesys Cloud returns 429 when rate limits are exceeded. The tenacity library handles exponential backoff and retry logic. The function also catches 401 responses and refreshes the token before retrying.

from tenacity import retry, stop_after_attempt, wait_exponential, retry_if_exception_type
import aiohttp

class RetryableError(Exception):
    pass

@retry(
    stop=stop_after_attempt(3),
    wait=wait_exponential(multiplier=1, min=2, max=10),
    retry=retry_if_exception_type(RetryableError)
)
async def archive_batch(
    session: aiohttp.ClientSession,
    token: str,
    batch_ids: List[str]
) -> dict:
    payload = {"ids": batch_ids}
    
    async with session.post(
        f"{GENESYS_BASE_URL}/api/v2/archives/conversations",
        json=payload,
        headers={
            "Authorization": f"Bearer {token}",
            "Accept": "application/json",
            "Content-Type": "application/json"
        }
    ) as response:
        if response.status == 401:
            global _token_cache
            _token_cache = None
            token = await get_access_token(session)
            return await archive_batch(session, token, batch_ids)
            
        if response.status == 429:
            retry_after = int(response.headers.get("Retry-After", 5))
            await asyncio.sleep(retry_after)
            raise RetryableError(f"Rate limited. Retry after {retry_after}s")
            
        response.raise_for_status()
        return await response.json()

The decorator applies exponential backoff across three attempts. The function checks for 401 and clears the token cache before requesting a fresh token. When the API returns 429, the function reads the Retry-After header, sleeps for the specified duration, and raises RetryableError to trigger the retry decorator. Successful requests return a JSON payload containing archive operation status.

Complete Working Example

The following script combines authentication, pagination, chunking, throttling, and retry logic into a single executable module. Set the environment variables before running.

import os
import asyncio
import aiohttp
from datetime import datetime, timedelta
from typing import List, AsyncGenerator
from itertools import islice
from tenacity import retry, stop_after_attempt, wait_exponential, retry_if_exception_type

GENESYS_BASE_URL = os.getenv("GENESYS_BASE_URL", "https://api.mypurecloud.com")
CLIENT_ID = os.getenv("GENESYS_CLIENT_ID")
CLIENT_SECRET = os.getenv("GENESYS_CLIENT_SECRET")

_token_cache: tuple[str, float] | None = None

async def get_access_token(session: aiohttp.ClientSession) -> str:
    global _token_cache
    import time
    current_time = time.time()
    if _token_cache and current_time < _token_cache[1] - 60:
        return _token_cache[0]
        
    auth_data = aiohttp.FormData()
    auth_data.add_field("grant_type", "client_credentials")
    auth_data.add_field("client_id", CLIENT_ID)
    auth_data.add_field("client_secret", CLIENT_SECRET)
    
    async with session.post(
        f"{GENESYS_BASE_URL}/oauth/token",
        data=auth_data,
        headers={"Accept": "application/json"}
    ) as response:
        response.raise_for_status()
        payload = await response.json()
        token = payload["access_token"]
        expires_in = payload.get("expires_in", 3600)
        _token_cache = (token, current_time + expires_in)
        return token

async def fetch_conversation_ids(
    session: aiohttp.ClientSession,
    token: str,
    start_date: datetime,
    end_date: datetime,
    page_size: int = 1000
) -> AsyncGenerator[List[str], None]:
    query_body = {
        "query": {
            "filter": {
                "type": "conversation",
                "value": {
                    "type": "date",
                    "value": {
                        "from": start_date.isoformat() + "Z",
                        "to": end_date.isoformat() + "Z"
                    }
                }
            }
        },
        "pageSize": page_size
    }
    
    while True:
        async with session.post(
            f"{GENESYS_BASE_URL}/api/v2/analytics/conversations/details/query",
            json=query_body,
            headers={"Authorization": f"Bearer {token}", "Accept": "application/json"}
        ) as response:
            if response.status == 401:
                token = await get_access_token(session)
                continue
            response.raise_for_status()
            data = await response.json()
            
        entities = data.get("entities", [])
        ids = [entity["id"] for entity in entities]
        if ids:
            yield ids
            
        next_page = data.get("nextPageId")
        if not next_page:
            break
        query_body["nextPageId"] = next_page

def chunk_list(lst: List[str], chunk_size: int) -> List[List[str]]:
    it = iter(lst)
    return list(iter(lambda: list(islice(it, chunk_size)), []))

class RetryableError(Exception):
    pass

@retry(
    stop=stop_after_attempt(3),
    wait=wait_exponential(multiplier=1, min=2, max=10),
    retry=retry_if_exception_type(RetryableError)
)
async def archive_batch(
    session: aiohttp.ClientSession,
    token: str,
    batch_ids: List[str]
) -> dict:
    payload = {"ids": batch_ids}
    async with session.post(
        f"{GENESYS_BASE_URL}/api/v2/archives/conversations",
        json=payload,
        headers={
            "Authorization": f"Bearer {token}",
            "Accept": "application/json",
            "Content-Type": "application/json"
        }
    ) as response:
        if response.status == 401:
            global _token_cache
            _token_cache = None
            token = await get_access_token(session)
            return await archive_batch(session, token, batch_ids)
            
        if response.status == 429:
            retry_after = int(response.headers.get("Retry-After", 5))
            await asyncio.sleep(retry_after)
            raise RetryableError(f"Rate limited. Retry after {retry_after}s")
            
        response.raise_for_status()
        return await response.json()

async def main():
    start_date = datetime(2023, 1, 1)
    end_date = datetime(2023, 12, 31, 23, 59, 59)
    max_concurrent = 5
    archive_chunk_size = 500
    
    async with aiohttp.ClientSession() as session:
        token = await get_access_token(session)
        semaphore = asyncio.Semaphore(max_concurrent)
        
        all_ids: List[str] = []
        async for batch in fetch_conversation_ids(session, token, start_date, end_date):
            all_ids.extend(batch)
            
        chunks = chunk_list(all_ids, archive_chunk_size)
        print(f"Collected {len(all_ids)} conversations. Processing {len(chunks)} chunks.")
        
        tasks = [
            archive_batch(session, token, chunk)
            for chunk in chunks
        ]
        
        throttled_tasks = [
            asyncio.create_task(
                throttled_archiver_wrapper(session, semaphore, token, chunk)
            )
            for chunk in chunks
        ]
        
        await asyncio.gather(*throttled_tasks)
        print("Archiving complete.")

async def throttled_archiver_wrapper(
    session: aiohttp.ClientSession,
    semaphore: asyncio.Semaphore,
    token: str,
    batch_ids: List[str]
) -> dict:
    async with semaphore:
        return await archive_batch(session, token, batch_ids)

if __name__ == "__main__":
    asyncio.run(main())

The script collects all conversation IDs into memory before processing chunks. This approach simplifies chunking logic. For datasets exceeding available RAM, replace the list accumulation with an async queue that feeds chunks directly to worker coroutines.

Common Errors & Debugging

Error: 401 Unauthorized

• Cause: The access token expired during a long-running pagination or archiving loop. Client credentials grants issue tokens with a one-hour lifetime.
• Fix: Clear the cached token and request a new one. The provided code handles this by setting _token_cache = None and calling get_access_token recursively. Ensure your OAuth application has the analytics:conversation:query and archive:conversation:write scopes enabled.

Error: 403 Forbidden

• Cause: The OAuth client lacks the required scopes, or the user account associated with the client does not have administrative permissions to archive conversations.
• Fix: Verify the application scopes in the Genesys Cloud administration console. Assign the Architect:Archives:Write or equivalent role to the service account. Confirm the base URL matches your organization region.

Error: 429 Too Many Requests

• Cause: The concurrent request volume exceeds Genesys Cloud rate limits. The Archives API enforces strict throttling to protect backend storage systems.
• Fix: Reduce the semaphore value in main(). The code reads the Retry-After header and sleeps before retrying. If 429 responses persist, lower max_concurrent to 2 or 3. Avoid sending batches larger than 500 identifiers during peak hours.

Error: 500 Internal Server Error

• Cause: The archiving backend encounters a transient storage failure or the conversation IDs reference deleted records.
• Fix: Validate that conversation IDs exist before submission. Implement idempotency by tracking successfully archived IDs in a local set. Skip duplicate submissions. Log the full response body for support tickets.

Error: Pagination Stalls

• Cause: The nextPageId field returns null prematurely due to date filter boundaries or empty result sets.
• Fix: Verify the from and to timestamps use ISO 8601 format with Z suffix. Ensure the date range contains conversations matching the query filter. The code checks if not next_page: break to prevent infinite loops.

Official References

• Analytics Conversations Query API
• Archives Conversations API
• OAuth 2.0 Client Credentials Flow
• Rate Limiting Guidelines