Labelbox is the enterprise-grade training data solution with fast AI enabled labeling tools, labeling automation, human workforce, data management, a powerful API for integration & SDK for extensibility. Visit Labelbox for more information.

The Labelbox Python API offers a simple, user-friendly way to interact with the Labelbox back-end.

• Requirements
• Installation
• Documentation
• Authentication
• Contribution
• Testing

• Use Python 3.6, 3.7 or 3.8
• Create an account
• Generate an API key

Prerequisite: Install pip

pip is a package manager for Python. On macOS, you can set it up to use the default python3 install via -

curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py python3 get-pip.py 

If the installation completes with a warning re: pip not being in your path, you'll need to add it by modifying your shell config (.zshrc, .bashrc or similar). You might have to modify the command below depending on the version of python3 on your machine.

export PATH=/Users/<your-macOS-username>/Library/Python/3.8/bin:$PATH 

Install using Python's Pip manager.

pip install labelbox 

• Visit our docs to learn how the SDK works
• Checkout our notebook examples to follow along with interactive tutorials
• view our API reference.

Labelbox uses API keys to validate requests. You can create and manage API keys on Labelbox. Pass your API key as an environment variable. Then, import and initialize the API Client.

user@machine:~$ export LABELBOX_API_KEY="<your api key here>" user@machine:~$ python3 from labelbox import Client client = Client() 

Please consult CONTRIB.md

1. Update the Makefile with your staging or prod API key. Ensure that docker has been installed on your system. Make sure the key is not from a free tier account.
2. To test on staging:

make test-staging 

3. To test on prod:

make test-prod 

4. If you make any changes and need to rebuild the image used for testing, force a rebuild with the -B flag

make -B{build|test-staging|test_prod}