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Bulk Operations Guide

Bulk operations allow you to process multiple projects at once, making it efficient to manage large numbers of projects programmatically.

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Overview

Bulk operations include:
  • Bulk Archive - Archive multiple projects
  • Bulk Copy - Copy projects to another workspace
  • Bulk Move - Move projects between workspaces
  • Bulk Delete - Delete multiple projects
  • Bulk Tagging - Add or remove tags from projects
  • Bulk Recipe Execution - Run recipes on multiple projects
  • Bulk Export - Request exports for multiple projects

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Bulk Request Workflow

Bulk operations follow an asynchronous pattern:
  1. Submit bulk request - Send list of project IDs and operation
  2. Monitor request status - Check progress of bulk operation
  3. Handle results - Process completed operations

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Bulk Archive

  • Python
import requests

api_url = "https://voyager.lumafield.com"
headers = {"Authorization": f"Token {token}"}

project_ids = ["uuid1", "uuid2", "uuid3"]

# Archive multiple projects
response = requests.post(
    f"{api_url}/api/v2/bulkProjects/archive",
    headers=headers,
    json={"projectIds": project_ids}
)
response.raise_for_status()

bulk_request = response.json()
print(f"Bulk archive request ID: {bulk_request['id']}")

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Bulk Copy

  • Python
destination_workspace = "destination-workspace-uuid"

response = requests.post(
    f"{api_url}/api/v2/bulkProjects/copy",
    headers=headers,
    json={
        "projectIds": project_ids,
        "destinationWorkspaceId": destination_workspace
    }
)
bulk_request = response.json()

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Bulk Move

  • Python
response = requests.post(
    f"{api_url}/api/v2/bulkProjects/move",
    headers=headers,
    json={
        "projectIds": project_ids,
        "destinationWorkspaceId": destination_workspace
    }
)
bulk_request = response.json()

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Bulk Delete

  • Python
response = requests.post(
    f"{api_url}/api/v2/bulkProjects/delete",
    headers=headers,
    json={"projectIds": project_ids}
)
bulk_request = response.json()

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Bulk Tagging

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Add Tags

  • Python
response = requests.post(
    f"{api_url}/api/v2/bulkProjects/addTags",
    headers=headers,
    json={
        "projectIds": project_ids,
        "tags": ["production", "q1-2024"]
    }
)
bulk_request = response.json()

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Remove Tags

  • Python
response = requests.post(
    f"{api_url}/api/v2/bulkProjects/removeTags",
    headers=headers,
    json={
        "projectIds": project_ids,
        "tags": ["archived"]
    }
)
bulk_request = response.json()

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Bulk Recipe Execution

  • Python
recipe_pk = "recipe-uuid"

response = requests.post(
    f"{api_url}/api/v2/bulkProjects/runRecipe",
    headers=headers,
    json={
        "projectIds": project_ids,
        "recipePk": recipe_pk
    }
)
bulk_request = response.json()

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Monitoring Bulk Requests

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List Bulk Requests

  • Python
# List all bulk requests
response = requests.get(
    f"{api_url}/api/v2/bulkRequests",
    headers=headers
)
requests_list = response.json()

for req in requests_list['results']:
    print(f"Request: {req['id']}")
    print(f"Status: {req['status']}")
    print(f"Type: {req['operationType']}")

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Get Bulk Request Status

  • Python
bulk_request_id = "bulk-request-uuid"

response = requests.get(
    f"{api_url}/api/v2/bulkRequests/{bulk_request_id}",
    headers=headers
)
request_status = response.json()

print(f"Status: {request_status['status']}")
print(f"Progress: {request_status.get('progress', 'N/A')}")
print(f"Completed: {request_status.get('completedCount', 0)}")
print(f"Failed: {request_status.get('failedCount', 0)}")

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Cancel Bulk Request

  • Python
# Cancel a bulk request
response = requests.post(
    f"{api_url}/api/v2/bulkRequests/{bulk_request_id}/cancel",
    headers=headers
)
response.raise_for_status()

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Best Practices

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1. Batch Sizes

Keep batch sizes reasonable: 
# ✅ Good - reasonable batch size
project_ids = project_ids[:100]  # Process 100 at a time

# ❌ Avoid - too many at once
# project_ids = all_project_ids  # Could be thousands

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2. Monitor Progress

Implement proper monitoring: 
def wait_for_bulk_request(bulk_request_id, max_wait=3600):
    start = time.time()
    while time.time() - start < max_wait:
        status = get_bulk_request_status(bulk_request_id)
        
        if status['status'] == 'completed':
            return status
        elif status['status'] == 'failed':
            raise Exception("Bulk operation failed")
        
        print(f"Progress: {status.get('completedCount', 0)}/{status.get('totalCount', 0)}")
        time.sleep(30)
    
    raise TimeoutError("Bulk operation timeout")

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3. Handle Failures

Check for partial failures: 
status = get_bulk_request_status(bulk_request_id)

if status['failedCount'] > 0:
    print(f"Warning: {status['failedCount']} operations failed")
    # Check failed items and retry if needed

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Next Steps