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Retrieving All Projects for a Client

You can retrieve all projects associated with a specific client ID using the following method:

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Example Usage:

Retrieve All Projects
from labellerr.client import LabellerrClient
from labellerr.exceptions import LabellerrError

# Initialize the client with your API credentials
client = LabellerrClient(api_key, api_secret)
client_id = client_id

try:
    result = client.get_all_project_per_client_id(client_id)

    # Check if projects were retrieved successfully
    if result and 'response' in result:
        projects = result['response']
        print(f"Found {len(projects)} projects:")
        for project in projects:
            print(f"- Project ID: {project.get('project_id')}")
            print(f"  Name: {project.get('project_name')}")
            print(f"  Type: {project.get('data_type')}")
except LabellerrError as e:
    print(f"Failed to retrieve projects: {str(e)}")
This method is useful when you need to:
  • List all projects for a client
  • Find specific project IDs
  • Check project statuses
  • Get an overview of client’s work
The response includes detailed information about each project, including its ID, name, data type, and other relevant metadata.

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Retrieving All Datasets

You can retrieve both linked and unlinked datasets associated with a client using the following method:

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Example Usage:

Retrieve All Datasets
from labellerr.client import LabellerrClient
from labellerr.exceptions import LabellerrError

# Initialize the client with your API credentials
client = LabellerrClient(api_key, api_secret)
client_id = client_id
data_type = 'image'

try:
    result = client.get_all_dataset(client_id, data_type, project_id, scope)
    # Process linked datasets
    linked_datasets = result["response"]["datasets"]
    # print(linked_datasets["datasets"][0]["dataset_id"])
    print(f"Found {len(linked_datasets)} linked datasets:")
    for dataset in linked_datasets:
        # print(dataset["datasets"])
        print(f"- Dataset ID: {dataset.get('dataset_id')}")
        print(f"  Name: {dataset.get('name')}")
        print(f"  Description: {dataset.get('description')}")

except LabellerrError as e:
    print(f"Failed to retrieve datasets: {str(e)}")
This method is useful when you need to:
  • Get an overview of all available datasets
  • Find datasets that are linked to projects
  • Identify unlinked datasets that can be associated with new projects
  • Manage dataset organization and project associations
The response includes two lists:
  • linked: Datasets that are already associated with projects
  • unlinked: Datasets that are not yet associated with any project
Each dataset object contains detailed information including its ID, name, description, and other metadata.

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Error Handling

The Labellerr SDK uses a custom exception class, LabellerrError, to indicate issues during API interactions. Always wrap your function calls in try-except blocks to gracefully handle errors.

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Example:

Error Handling Example
from labellerr.exceptions import LabellerrError

try:
    # Example function call
    result = client.initiate_create_project(payload)
except LabellerrError as e:
    print(f"An error occurred: {str(e)}")
The Labellerr SDK is a fast and reliable solution for managing annotation workflows. Want to try it end-to-end? Refer to this Google Colab Cookbook for a ready-to-run tutorial. For more related cookbooks and examples, please visit our repository: Labellerr Hands-On Learning