Kaggle CLI Documentation

June 15, 2026 · View on GitHub

Welcome to the Kaggle CLI documentation. This guide provides detailed information on how to use the Kaggle command-line interface to interact with Kaggle's platform.

Installation

Note: Ensure you have Python 3.11+ and the package manager pip installed.

Install the kaggle package with pip:

pip install kaggle

If you run into a Command kaggle not found error, ensure that your Python executable scripts are in your PATH.ForalocaluserinstallonLinux,thedefaultlocationis‘ /.local/bin‘.OnWindows,thedefaultlocationis‘PATH. For a local user install on Linux, the default location is `~/.local/bin`. On Windows, the default location is `PYTHON_HOME/Scripts`.

Authentication

First, you will need a Kaggle account. You can sign up here.

After login, you can download your Kaggle API credentials at https://www.kaggle.com/settings/api by clicking on the "Generate New Token" button under the "API" section.

Option 1: OAuth

Obtains access credentials for your Kaggle user accounts via a web-based authrorization flow.

kaggle auth login

Option 2: Environment variable

export KAGGLE_API_TOKEN=xxxxxxxxxxxxxx # Copied from the settings UI

Option 3: API token file

Store your Kaggle API token obtained from your Kaggle account API tokens settings page in a file at ~/.kaggle/access_token.

Option 4: Legacy API credentials file

From your Kaggle account API tokens settings page, under "Legacy API Credentials", click on the "Create Legacy API Key" button to generate a kaggle.json file and store it at ~/.kaggle/kaggle.json.

CLI Usage

Run the following command to list the available commands:

kaggle --help

The Kaggle CLI is organized into several command groups:

  • Competitions: Manage and participate in Kaggle competitions.
  • Datasets: Search, download, and manage Kaggle datasets.
  • Forums: Browse and read Kaggle discussion forums.
  • Kernels: Interact with Kaggle Kernels (notebooks and scripts).
  • Models: Manage your Kaggle Models.
  • Model Variations: Manage variations of your Kaggle Models.
  • Model Variation Versions: Manage versions of your Kaggle Model Variations.
  • Benchmarks: Define evaluation tasks, run them against LLM models, and download results.
  • Configuration: Configure the Kaggle CLI.

Many commands produce output, which can be formatted for different purposes:

Tutorials

Explore these tutorials to learn how to perform common tasks: