labelbox

What it is and what it does

Labelbox is the official Python SDK for the Labelbox data labeling platform. It provides a structured client interface to manage labeling projects, retrieve annotations, and work with labeled datasets programmatically. The SDK is built around an ORM layer that maps Labelbox data entities to Python objects, with GraphQL-backed queries for efficient server communication.

The package is organized into functional modules: a data/ package for annotation serialization and deserialization (including NDJson support), an orm/ package providing base classes and generic query patterns, a schema/ package defining entity types, and a Client class serving as the main entry point. It handles pagination, custom exceptions, and utility functions for common workflows. The SDK supports Python versions 3.9 through 3.13 and integrates with standard libraries like pydantic for validation and requests for HTTP communication.

Use it for:

• Retrieve and process labeled datasets from Labelbox projects for training machine learning models.
• Programmatically create, update, and manage labeling projects and export annotations in bulk.
• Serialize and deserialize annotation data between Labelbox and external formats like NDJson.
• Automate quality assurance workflows by querying label metadata and project statistics.
• Integrate Labelbox labeling workflows into custom data pipeline and ETL processes.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Labelbox is a Python SDK for interacting with the Labelbox data labeling platform, providing client-side access to projects, labels, annotations, and related data management through a GraphQL-backed API.

Yes. Labelbox is actively maintained, has low install friction, carries no known vulnerabilities, and is licensed permissively. Install it if you need to programmatically interact with Labelbox projects, export annotations, or integrate labeling workflows into Python applications. Not relevant if you do not use the Labelbox platform.

Install

labelbox on PyPI

pip install labelbox

uv add labelbox

poetry add labelbox

Installing labelbox

Before you install

Low install friction with a pure-wheel distribution. Actively maintained with a recent release and ongoing repository activity. Nine runtime dependencies are all standard, well-established packages.

License in practice

Licensed under Apache Software License (permissive), allowing use in commercial and private projects with minimal restrictions.

Quickstart

pip install labelbox

from labelbox import Client

client = Client(api_key='your_api_key')
project = client.get_project('project_id')
labels = project.labels

Requires a valid Labelbox API key to authenticate; integration with Labelbox servers is necessary for most operations.

Verify before relying

• Whether the SDK supports offline annotation workflows or requires live server connectivity for all operations.
• Performance characteristics when working with large annotation datasets or high-volume label exports.
• Extent of support for custom annotation types beyond the built-in schema definitions.

Package facts

Evidence: labelbox-7.11.0-py3-none-any.whl

Keywords: ai, edu, labelbox, labeling, llm, machinelearning, ml

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