---
id: google-cloud-jupyter-config
version: "0.0.13"
license: Apache License 2.0
license_treatment: permissive
maintenance: active
---

# google-cloud-jupyter-config — Jupyter configuration utilities using gcloud

License: permissive · Maintenance: active · Downloads: 743.2K/mo

## What it is and what it does

This package bridges Jupyter and the Google Cloud SDK by reading gcloud configuration (project, region, and other settings) and injecting them into your Jupyter environment at startup. It provides Python classes and utility methods that you add to your Jupyter config file to automatically populate connection details and kernel gateway URLs managed by Google.

The package is designed for developers working with Google Cloud who want their Jupyter notebooks to inherit gcloud authentication and project settings without manual configuration. It depends on cachetools, jupyter_server, and traitlets—all standard components of modern Jupyter deployments. Setup requires gcloud to be installed and authenticated separately, and the kernel gateway feature requires jupyter_server version 2.4.0 or later.

Use it for:

- Automatically populate Google Cloud project and region in Jupyter notebooks without hardcoding them.
- Connect Jupyter notebooks to kernel gateways managed by Google Cloud without manual URL configuration.
- Share Jupyter environments across a team where gcloud authentication is already configured.
- Reduce setup friction when deploying Jupyter on Google Cloud by inheriting gcloud credentials.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Configures Jupyter notebooks and lab environments using settings from the Google Cloud SDK's gcloud tool, allowing you to automatically populate project, region, and kernel gateway connection details.

Yes, if you use Jupyter with Google Cloud and want to reduce configuration boilerplate. The package is actively maintained, has no known vulnerabilities, and integrates cleanly with standard Jupyter workflows. Install only if you have gcloud already installed and authenticated; it adds no value in environments that don't use Google Cloud.

## Install

pip install google-cloud-jupyter-config
uv add google-cloud-jupyter-config
poetry add google-cloud-jupyter-config

## Installing google-cloud-jupyter-config

Before you install: Low friction install with three lightweight runtime dependencies. Package is actively maintained with a recent release and no known vulnerabilities.

License in practice: Apache License 2.0 is permissive, allowing use in commercial and proprietary projects with minimal restrictions.

Quickstart:

pip install google-cloud-jupyter-config

# In ~/.jupyter/jupyter_lab_config.py:
import google.cloud.jupyter_config
google.cloud.jupyter_config.configure_gateway_client(c)

Requires gcloud CLI installed and authenticated (gcloud auth login), plus jupyter_server >= 2.4.0 for kernel gateway features.

Verify before relying:

- Whether the package works with Jupyter versions that do not use jupyter_server.
- Scope and limitations of configuration options accessible through gcloud integration.

## Package facts

- License: Apache License 2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 743.2K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

jupyter gcloud configuration, google cloud jupyter setup, gcloud jupyter config, jupyter kernel gateway google cloud, jupyter lab google cloud integration, gcloud config jupyter, jupyter server google cloud, google-cloud, jupyter-integration

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