> ## Documentation Index
> Fetch the complete documentation index at: https://docs.labelbox.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Labeling Workforce

> Python SDK methods for requesting and managing your labeling workforce.

You can request labeling service for your Annotate projects and manage the requested labeling workforce using the Labelbox Python SDK.

<Info>
  ### Experimental feature

  This is an [experimental](/docs/product-release-phases#experimental) feature that requires you to enable experimental features before using its methods.
</Info>

# Methods

## Get and request labeling service

Use `project.labeling_service = project.get_labeling_service()` to get the labeling service associated with the project. Then use `labeling_service.request()` to request a workforce of trained labelers for your data.

<CodeGroup>
  ```python Python theme={null}
  # Enable experimental features
  client.enable_experimental = True

  # Get labeling service
  labeling_service = project.get_labeling_service()

  # Validate all project requirements and request labeling service
  labeling_service.request()
  ```
</CodeGroup>

## Get labeling service status

Use `project.get_labeling_service_status()` to check the status of your requested labeling service.

<CodeGroup>
  ```python Python theme={null}
  # Enable experimental features
  client.enable_experimental = True

  # Get status of requested labeling service
  project.get_labeling_service_status()
  ```
</CodeGroup>

This method returns the following value defined in the `LabelingServiceStatus` enum, corresponding to the statuses of your requested labeling service:

* `SET_UP`: Your request has been submitted, but you need to set up your request by adding data rows, ontologies, and labeling instructions to proceed the request.
* `REQUESTED`: Your request has been validated and is pending approval for connecting to labeling workforce.
* `ACCEPTED`: Your request has satisfied the prerequisite and been accepted.
* `CALIBRATION`: Labelers are labeling a sample of your data rows that you can review and confirm alignment on the expectation.
* `PRODUCTION`: Labelers are labeling all data rows.
* `COMPLETE`: Labelers have finished adding labels to your projects.

## Get labeling service details

Use `project.get_labeling_service_dashboard()` to retrieve the following attributes of the project for which you requested labeling service:

* `id`: The project ID
* `name`: The project name `status`: The [status](#get-labeling-service-status) of the labeling service
* `data_rows_count`: The total number of data rows batched in the project
* `tasks_completed_count`: The number of completed tasks (with the `COMPLETE` status)
* `tasks_remaining_count`: The number of incomplete tasks (queued data rows with statuses other than `COMPLETE`)
* `tags`: [Project tags](/docs/project-tagging) associated with the project
* `media_type`: The [media type](/reference/project#create-a-project) of the project
* client: The Labelbox client

If you are an admin, you can also use `client.get_labeling_service_dashboards()` to retrieve details of all projects with labeling service requested in your workspace.

<CodeGroup>
  ```python Python theme={null}
  # Enable experimental features
  client.enable_experimental = True

  # Get details of a project with labeling service requested
  project.get_labeling_service_dashboard()

  # Get details of all projects with labeling service requested
  client.get_labeling_service_dashboards()
  ```
</CodeGroup>