Importing Genesys Cloud Outbound Contact Lists via Python SDK

What You Will Build

• A production-ready Python module that parses CSV files, normalizes phone numbers to E.164, validates telephony constraints, and ingests contacts into Genesys Cloud Outbound campaigns using atomic HTTP POST operations.
• The implementation uses the official Genesys Cloud Python SDK alongside httpx for transparent HTTP cycle debugging, webhook configuration for CRM synchronization, and structured audit logging for governance.
• The tutorial covers Python 3.9+ with genesyscloud, httpx, phonenumbers, and standard library utilities.

Prerequisites

• Genesys Cloud Service Account with OAuth client credentials
• Required scopes: outbound:contactlist:write, outbound:contactlist:ingest, platform:webhook:write, platform:webhook:read
• Genesys Cloud Python SDK version 2.10.0+ (pip install genesyscloud)
• Python runtime dependencies: httpx>=0.25.0, phonenumbers>=8.13.0, pydantic>=2.0.0
• Target contact list must exist in Genesys Cloud Outbound with matching column definitions

Authentication Setup

Genesys Cloud uses OAuth 2.0 client credentials flow for server-to-server API access. The SDK handles token caching internally, but explicit token management is required for raw HTTP debugging and webhook payload signing.

import httpx
import json
import time
from typing import Optional

class GenesysOAuthManager:
    def __init__(self, client_id: str, client_secret: str, base_url: str = "https://api.mypurecloud.com"):
        self.client_id = client_id
        self.client_secret = client_secret
        self.base_url = base_url.rstrip("/")
        self.access_token: Optional[str] = None
        self.token_expiry: float = 0.0

    def get_access_token(self) -> str:
        """Retrieve OAuth token with automatic refresh logic."""
        if self.access_token and time.time() < self.token_expiry - 30:
            return self.access_token

        url = f"{self.base_url}/api/v2/oauth/token"
        headers = {"Content-Type": "application/json"}
        payload = {
            "grant_type": "client_credentials",
            "client_id": self.client_id,
            "client_secret": self.client_secret,
            "scope": "outbound:contactlist:write outbound:contactlist:ingest platform:webhook:write"
        }

        with httpx.Client(timeout=15.0) as client:
            response = client.post(url, headers=headers, json=payload)
            response.raise_for_status()

            token_data = response.json()
            self.access_token = token_data["access_token"]
            self.token_expiry = time.time() + token_data["expires_in"]
            return self.access_token

The token request targets /api/v2/oauth/token. The response returns an access_token and expires_in duration. The manager caches the token and refreshes it thirty seconds before expiration to prevent mid-batch 401 Unauthorized errors during long-running ingest jobs.

Implementation

Step 1: CSV Parsing, Phone Normalization, and Schema Validation

Genesys Cloud outbound contacts require E.164 formatted phone numbers and strict column alignment. The ingestion pipeline must validate records before transmission to avoid carrier rejections and partial list corruption.

import csv
import phonenumbers
from phonenumbers import NumberParseException
from typing import Dict, List, Any
from dataclasses import dataclass

@dataclass
class ContactRecord:
    contact_id: str
    phone_number: str
    columns: Dict[str, str]

def parse_and_validate_csv(file_path: str, country_code: str = "US") -> List[ContactRecord]:
    """Parse CSV, normalize phones, and validate against telephony constraints."""
    records: List[ContactRecord] = []
    duplicate_ids: set = set()

    with open(file_path, mode="r", encoding="utf-8") as f:
        reader = csv.DictReader(f)
        for row_num, row in enumerate(reader, start=2):
            ext_id = row.get("EXTERNAL_ID", "").strip()
            raw_phone = row.get("PHONE_NUMBER", "").strip()

            if not ext_id or not raw_phone:
                continue

            if ext_id in duplicate_ids:
                raise ValueError(f"Duplicate EXTERNAL_ID at row {row_num}: {ext_id}")
            duplicate_ids.add(ext_id)

            try:
                parsed = phonenumbers.parse(raw_phone, country_code)
                if not phonenumbers.is_valid_number(parsed):
                    raise ValueError(f"Invalid phone at row {row_num}: {raw_phone}")
                e164_phone = phonenumbers.format_number(parsed, phonenumbers.PhoneNumberFormat.E164)
            except NumberParseException as e:
                raise ValueError(f"Phone normalization failed at row {row_num}: {e}")

            column_matrix = {k: v.strip() for k, v in row.items() if k not in ("EXTERNAL_ID", "PHONE_NUMBER")}
            records.append(ContactRecord(contact_id=ext_id, phone_number=e164_phone, columns=column_matrix))

    return records

The phonenumbers library handles region-specific parsing and enforces E.164 compliance. Duplicate EXTERNAL_ID values are rejected immediately to prevent Genesys Cloud from overwriting existing records unintentionally. The column_matrix extracts all non-identifier fields for the payload.

Step 2: Ingest Payload Construction and Batch Chunking

Genesys Cloud enforces a maximum of 10,000 contacts per ingest request. The pipeline chunks validated records and constructs the list-ref (contactListId), column-matrix, and ingest directive payload structure.

import math
from typing import Generator

def chunk_records(records: List[ContactRecord], max_batch_size: int = 10000) -> Generator[List[ContactRecord], None, None]:
    """Split records into API-compliant batch sizes."""
    total_batches = math.ceil(len(records) / max_batch_size)
    for i in range(total_batches):
        yield records[i * max_batch_size : (i + 1) * max_batch_size]

def build_ingest_payload(contact_list_id: str, batch: List[ContactRecord], ingest_type: str = "ADD") -> Dict[str, Any]:
    """Construct the atomic HTTP POST payload with list-ref, column-matrix, and ingest directive."""
    return {
        "contactListId": contact_list_id,
        "ingestType": ingest_type,
        "contacts": [
            {
                "contactId": rec.contact_id,
                "phoneNumber": rec.phone_number,
                "columns": rec.columns
            }
            for rec in batch
        ]
    }

The contactListId serves as the list-ref anchor. The ingestType directive controls whether records are added, updated, or replaced. The contacts array maps directly to the column-matrix schema defined in the outbound list configuration.

Step 3: Atomic HTTP POST Operations with Retry Logic and Latency Tracking

The ingest operation must handle 429 rate limits gracefully and track latency for governance reporting. This step demonstrates the raw HTTP cycle alongside SDK integration.

import time
import logging
from typing import Optional

logger = logging.getLogger(__name__)

def ingest_batch(
    oauth_manager: GenesysOAuthManager,
    contact_list_id: str,
    payload: Dict[str, Any],
    max_retries: int = 4
) -> Dict[str, Any]:
    """Execute atomic POST with exponential backoff for 429 responses."""
    base_url = oauth_manager.base_url
    url = f"{base_url}/api/v2/outbound/lists/{contact_list_id}/ingest"
    token = oauth_manager.get_access_token()
    headers = {
        "Authorization": f"Bearer {token}",
        "Content-Type": "application/json",
        "Accept": "application/json"
    }

    start_time = time.perf_counter()
    last_exception: Optional[Exception] = None

    for attempt in range(1, max_retries + 1):
        try:
            with httpx.Client(timeout=60.0) as client:
                response = client.post(url, headers=headers, json=payload)

                if response.status_code == 429:
                    retry_after = float(response.headers.get("Retry-After", 2 ** attempt))
                    logger.warning("Rate limited (429). Waiting %.2f seconds on attempt %d", retry_after, attempt)
                    time.sleep(retry_after)
                    continue

                response.raise_for_status()
                latency_ms = (time.perf_counter() - start_time) * 1000
                return {
                    "status": response.status_code,
                    "body": response.json(),
                    "latency_ms": latency_ms,
                    "attempt": attempt
                }

        except httpx.HTTPStatusError as e:
            last_exception = e
            if e.response.status_code in (401, 403):
                raise RuntimeError(f"Authentication/Authorization failed: {e.response.text}")
            logger.error("HTTP %d on attempt %d: %s", e.response.status_code, attempt, e.response.text)
            time.sleep(2 ** attempt)
        except httpx.RequestError as e:
            last_exception = e
            logger.error("Network error on attempt %d: %s", attempt, str(e))
            time.sleep(2 ** attempt)

    raise RuntimeError(f"Ingest failed after {max_retries} attempts: {last_exception}")

The HTTP POST targets /api/v2/outbound/lists/{contactListId}/ingest. The request requires Authorization: Bearer <token> and Content-Type: application/json. A successful 200 response returns a job tracking object with id, status, and processing metrics. The retry loop implements exponential backoff for 429 responses, which commonly occur during high-volume outbound scaling.

Step 4: Webhook Configuration for CRM Synchronization

External CRM platforms require event-driven synchronization. Genesys Cloud supports outbound list events via platform webhooks. This step registers a webhook that triggers on outbound.list.ingest.completed.

def configure_crm_webhook(
    oauth_manager: GenesysOAuthManager,
    webhook_url: str,
    contact_list_id: str
) -> Dict[str, Any]:
    """Register webhook for list imported events to sync with external CRM."""
    base_url = oauth_manager.base_url
    url = f"{base_url}/api/v2/platform/webhooks"
    token = oauth_manager.get_access_token()
    headers = {
        "Authorization": f"Bearer {token}",
        "Content-Type": "application/json"
    }

    webhook_config = {
        "name": f"CRM Sync - List {contact_list_id}",
        "description": "Triggers on outbound list ingest completion for CRM alignment",
        "request": {
            "url": webhook_url,
            "method": "POST",
            "headers": {
                "Content-Type": "application/json",
                "X-Genesys-Event": "outbound.list.ingest"
            }
        },
        "events": ["outbound.list.ingest.completed"],
        "eventFilters": {
            "contactListId": contact_list_id
        },
        "retryPolicy": {
            "maxRetries": 3,
            "retryIntervalSeconds": 10
        }
    }

    with httpx.Client(timeout=15.0) as client:
        response = client.post(url, headers=headers, json=webhook_config)
        response.raise_for_status()
        return response.json()

The webhook payload targets /api/v2/platform/webhooks. The events array specifies outbound.list.ingest.completed. The eventFilters object scopes the trigger to the specific contactListId. CRM endpoints receive a JSON payload containing the list ID, ingest timestamp, and record counts.

Step 5: Audit Logging and Success Rate Calculation

Governance requires immutable audit trails. This step calculates ingest success rates and writes structured logs for compliance review.

import json
from datetime import datetime, timezone

def generate_audit_log(
    contact_list_id: str,
    total_records: int,
    batch_results: List[Dict[str, Any]]
) -> str:
    """Generate structured audit log for outbound governance."""
    successful = sum(1 for r in batch_results if r["status"] == 200)
    failed = len(batch_results) - successful
    avg_latency = sum(r["latency_ms"] for r in batch_results) / len(batch_results) if batch_results else 0.0

    audit_entry = {
        "timestamp": datetime.now(timezone.utc).isoformat(),
        "event": "outbound.contact_list_ingest",
        "contactListId": contact_list_id,
        "total_records": total_records,
        "successful_batches": successful,
        "failed_batches": failed,
        "ingest_success_rate": f"{(successful / len(batch_results)) * 100:.2f}%",
        "average_latency_ms": round(avg_latency, 2),
        "governance_status": "COMPLIANT" if failed == 0 else "REQUIRES_REVIEW"
    }

    return json.dumps(audit_entry, indent=2)

The audit log captures ingestion metrics, success rates, and latency averages. The governance_status flag enables automated compliance dashboards to flag batches requiring manual review.

Complete Working Example

The following module integrates all components into a single importable class. Replace placeholder credentials and file paths before execution.

import logging
import time
from typing import List, Dict, Any, Optional

# Import classes defined in previous steps
# from .auth import GenesysOAuthManager
# from .parsing import parse_and_validate_csv, ContactRecord
# from .ingest import chunk_records, build_ingest_payload, ingest_batch, configure_crm_webhook, generate_audit_log

class GenesysContactImporter:
    def __init__(self, client_id: str, client_secret: str, base_url: str = "https://api.mypurecloud.com"):
        self.oauth = GenesysOAuthManager(client_id, client_secret, base_url)
        self.batch_results: List[Dict[str, Any]] = []
        logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")

    def run_ingest_pipeline(
        self,
        csv_path: str,
        contact_list_id: str,
        country_code: str = "US",
        webhook_url: Optional[str] = None
    ) -> Dict[str, Any]:
        """Execute end-to-end contact import with validation, ingestion, and audit logging."""
        logger = logging.getLogger(__name__)
        logger.info("Starting ingest pipeline for list: %s", contact_list_id)

        # Step 1: Parse and validate
        records = parse_and_validate_csv(csv_path, country_code)
        if not records:
            raise ValueError("No valid records found in CSV")

        # Step 2: Configure webhook if provided
        if webhook_url:
            logger.info("Configuring CRM webhook: %s", webhook_url)
            configure_crm_webhook(self.oauth, webhook_url, contact_list_id)

        # Step 3: Chunk and ingest
        total_records = len(records)
        for batch_idx, batch in enumerate(chunk_records(records), start=1):
            payload = build_ingest_payload(contact_list_id, batch, ingest_type="ADD")
            logger.info("Ingesting batch %d/%.0f (%d records)", batch_idx, math.ceil(total_records/10000), len(batch))
            
            result = ingest_batch(self.oauth, contact_list_id, payload)
            self.batch_results.append(result)
            logger.info("Batch %d completed. Status: %d. Latency: %.2fms", batch_idx, result["status"], result["latency_ms"])

        # Step 4: Generate audit log
        audit_log = generate_audit_log(contact_list_id, total_records, self.batch_results)
        logger.info("Audit log generated:\n%s", audit_log)

        return {
            "contactListId": contact_list_id,
            "totalRecords": total_records,
            "auditLog": audit_log,
            "batchResults": self.batch_results
        }

if __name__ == "__main__":
    import os
    importer = GenesysContactImporter(
        client_id=os.getenv("GENESYS_CLIENT_ID"),
        client_secret=os.getenv("GENESYS_CLIENT_SECRET")
    )
    importer.run_ingest_pipeline(
        csv_path="contacts_batch_001.csv",
        contact_list_id="a1b2c3d4-e5f6-7890-abcd-ef1234567890",
        webhook_url="https://crm.example.com/api/v1/genesys/webhook"
    )

The module handles CSV parsing, E.164 normalization, batch chunking, HTTP ingestion with retry logic, webhook registration, and audit logging. Execution requires environment variables for OAuth credentials and a valid contact list UUID.

Common Errors & Debugging

Error: 400 Bad Request - Invalid Phone Number Format

• Cause: Phone numbers do not match E.164 specification or contain invalid country codes.
• Fix: Verify the country_code parameter in parse_and_validate_csv. Ensure the phonenumbers library correctly parses the region. Check CSV columns for leading zeros, spaces, or extension characters.
• Code Fix: The validation step raises ValueError with row numbers. Inspect the exception message and correct the source CSV before re-running.

Error: 429 Too Many Requests

• Cause: Genesys Cloud rate limits outbound ingest endpoints during high concurrency.
• Fix: The ingest_batch function implements exponential backoff. Increase max_retries or reduce parallel ingest jobs. Monitor Retry-After headers returned by the API.
• Code Fix: Adjust the sleep duration in the retry loop or implement a token bucket rate limiter if ingesting multiple lists simultaneously.

Error: 403 Forbidden - Missing OAuth Scopes

• Cause: The service account lacks outbound:contactlist:write or outbound:contactlist:ingest.
• Fix: Navigate to the Genesys Cloud Admin console, locate the OAuth client, and append the required scopes. Regenerate the access token.
• Code Fix: Update the scope string in GenesysOAuthManager.get_access_token(). Verify token permissions via GET /api/v2/oauth/tokeninfo.

Error: Column Mismatch Validation Failure

• Cause: The CSV contains columns not defined in the Genesys Cloud outbound list schema.
• Fix: Align CSV headers with the list definition in Genesys Cloud. The column_matrix extraction passes all non-identifier columns. Genesys Cloud rejects payloads with undefined column keys.
• Code Fix: Pre-validate column names against the list schema using GET /api/v2/outbound/lists/{contactListId} before ingestion.

Official References

• Genesys Cloud Outbound List Ingest API
• Genesys Cloud Python SDK Documentation
• Genesys Cloud Platform Webhooks API
• E.164 Phone Number Standard
• Genesys Cloud OAuth 2.0 Authentication