Overview

Cube is configured via environment variables and configuration options in a configuration file. Usually, both would be used to configure a Cube deployment in production.

Environment variables

Environment variables are mostly used for configuration that is defined statically and is not supposed to change while a Cube deployment is running.

Cube Core

You can set environment variables in any way supported by Docker (opens in a new tab), e.g., a .env file or the environment option in the docker-compose.yml file.

Cube Cloud

You can set environment variables in Settings → Configuration:

Configuration options

Configuration options are mostly used for configuration that is defined programmatically and applied dynamically while a Cube deployment is running.

Configuration options take precedence over environment variables.

cube.py and cube.js files

Configuration options can be defined either using Python, in a cube.py file, or using JavaScript, in a cube.js file in the root folder of a Cube project.

from cube import config
 
# Base path for the REST API
config.base_path = '/cube-api'
 
# Inspect, modify, or restrict every query
@config('query_rewrite')
def query_rewrite(query: dict, ctx: dict) -> dict:
  if 'order_id' in ctx['securityContext']:
    query['filters'].append({
      'member': 'orders_view.id',
      'operator': 'equals',
      'values': [ctx['securityContext']['order_id']]
    })
  return query
 

Both ways are equivalent; when in doubt, use Python.

Here is a minimal correct cube.py file. Note that the config object must be imported:

from cube import config
 
# Configuration goes here...

Here is a minimal correct cube.js file. Note that the module.exports object must be defined:

module.exports = {
  // Configuration goes here...
}

You can read more about Python and JavaScript support in the dynamic data modeling section of the documentation.

Cube Core

When using Docker, ensure that the configuration file and your data model folder are mounted to /cube/conf within the Docker container.

Cube Cloud

You can edit the configuration file by going into Development Mode and navigating to Data Model or Visual Model pages.

Runtimes and dependencies

Cube uses Python and Node.js as runtime environments for the code of configuration and dynamic data models. You can look current versions up on GitHub: Python (opens in a new tab), Node.js (opens in a new tab).

It's recommended to use requirements.txt and package.json files to specify dependencies for your Python and JavaScript code, respectively.

Cube Core

If you have specified Python packages in the requirements.txt file, make sure to install them by running pip install -r requirements.txt inside the Docker container.

If you have specified npm packages in the package.json file, make sure to install them by running npm install inside the Docker container. Alternatively, you can run npm install on your local machine and mount the node_modules folder under /cube/conf in the Docker container; however, if your dependencies contain native extensions, they might not work when provided this way.

To automate the installation of dependencies, build and use a custom Docker image.

Cube Cloud

Cube Cloud automatically installs dependencies from requirements.txt and package.json files.

Development mode

Cube can be run in an insecure, development mode by setting the CUBEJS_DEV_MODE environment variable to true. Putting Cube in development mode does the following:

• Disables authentication checks.
• Disables member-level access control.
• Enables Cube Store in single instance mode.
• Enables background refresh for in-memory cache and scheduled pre-aggregations.
• Allows another log level to be set (trace).
• Enables Playground on http://localhost:4000.
• Uses memory instead of cubestore as the default cache/queue engine.
• Logs incorrect/invalid configuration for externalRefresh /waitForRenew instead of throwing errors.