Databricks CLI

The Databricks command-line interface (CLI) provides an easy-to-use interface to the Databricks platform. The open source project is hosted on GitHub. The CLI is built on top of the Databricks REST API 2.0 and is organized into command groups based on the Workspace API, Clusters API, Instance Pools API, DBFS API, Groups API, Jobs API, Libraries API, and Secrets API: workspace, clusters, instance-pools, fs, groups, jobs, runs, libraries, and secrets.


This CLI is under active development and is released as an Experimental client. This means that interfaces are still subject to change.

Set up the CLI

This section lists CLI requirements and describes how to install and configure your environment to run the CLI.


  • Python 3 - 3.6 and above

  • Python 2 - 2.7.9 and above


    On MacOS, the default Python 2 installation does not implement the TLSv1_2 protocol and running the CLI with this Python installation results in the error: AttributeError: 'module' object has no attribute 'PROTOCOL_TLSv1_2'. Use Homebrew to install a version of Python that has ssl.PROTOCOL_TLSv1_2.

Install the CLI

Run pip install databricks-cli using the appropriate version of pip for your Python installation.

Set up authentication

Before you can run CLI commands, you must set up authentication. To authenticate to the CLI you use a personal access token.

To configure the CLI to use the personal access token, run databricks configure --token. The command issues the prompts:

Databricks Host (should begin with https://):

After you complete the prompts, your access credentials are stored in the file ~/.databrickscfg. The file should contain entries like:

host = https://<databricks-instance>
token =  <personal-access-token>

For CLI 0.8.1 and above, you can change the path of this file by setting the environment variable DATABRICKS_CONFIG_FILE.

You can also use your username and password to authenticate. Run databricks configure and follow the prompts.


Because the CLI is built on top of the REST API, your authentication configuration in your .netrc file takes precedence over your configuration in .databrickscfg.

CLI 0.8.0 and above supports the following environment variables:


An environment variable setting takes precedence over the setting in the configuration file.

Connection profiles

The Databricks CLI configuration supports multiple connection profiles. The same installation of Databricks CLI can be used to make API calls on multiple Databricks workspaces.

To add a connection profile:

databricks configure [--profile <profile>]

To use the connection profile:

databricks workspace ls --profile <profile>

Alias command groups

Sometimes it can be inconvenient to prefix each CLI invocation with the name of a command group, for example databricks workspace ls. To make the CLI easier to use, you can alias command groups to shorter commands. For example to shorten databricks workspace ls to dw ls in the Bourne again shell, you can add alias dw="databricks workspace" to the appropriate bash profile. Typically, this file is located at ~/.bash_profile.


Databricks has already aliased databricks fs to dbfs; databricks fs ls and dbfs ls are equivalent.

Use the CLI

This section shows you how to get CLI help, parse CLI output, and invoke commands in each command group.

Display CLI command group help

You list the subcommands for any command group by running databricks <group> -h. For example, you list the DBFS CLI subcommands by running databricks fs -h.

Use jq to parse CLI output

Some Databricks CLI commands output the JSON response from the API endpoint. Sometimes it can be useful to parse out parts of the JSON to pipe into other commands. For example, to copy a job definition, you must take the settings field of /api/2.0/jobs/get and use that as an argument to the databricks jobs create command.

In these cases, we recommend you to use the utility jq. You can install jq on MacOS using Homebrew with brew install jq.

For more information on jq, see the jq Manual.

JSON string parameters

String parameters are handled differently depending on your operating system:

  • Unix: You must enclose JSON string parameters in single quotes. For example:

    databricks jobs run-now --job-id 9 --jar-params '["20180505", "alantest"]'
  • Windows: You must enclose JSON string parameters in double quotes, and the quote characters inside the string must be preceded by \. For example:

    databricks jobs run-now --job-id 9 --jar-params "[\"20180505\", \"alantest\"]"