Getting Started


You will need the following

  • Python 2.7 or 3.4+
  • DataRobot account
  • pip

Installing for Cloud DataRobot

If you are using the cloud version of DataRobot, the easiest way to get the latest version of the package is:

pip install datarobot


If you are not running in a Python virtualenv, you probably want to use pip install --user datarobot.

Installing for an On-Site Deploy

If you are using an on-site deploy of DataRobot, the latest version of the package is not the most appropriate for you. Contact your CFDS for guidance on the appropriate version range.

pip install "datarobot>=$(MIN_VERSION),<$(EXCLUDE_VERSION)"

For some particular installation of DataRobot, the correct value of $(MIN_VERSION) could be 2.0 with an $(EXCLUDE_VERSION) of 2.3. This ensures that all the features the client expects to be present on the backend will always be correct.


If you are not running in a Python virtualenv, you probably want to use pip install --user "datarobot>=$(MIN_VERSION),<$(MAX_VERSION).


Each authentication method will specify credentials for DataRobot, as well as the location of the DataRobot deployment. We currently support configuration using a configuration file, by setting environment variables, or within the code itself.


You will have to specify an API token and an endpoint in order to use the client. You can manage your API tokens in the DataRobot webapp, in your profile. This section describes how to use these options. Their order of precedence is as follows, noting that the first available option will be used:

  1. Setting endpoint and token in code using datarobot.Client
  2. Configuring from a config file as specified directly using datarobot.Client
  3. Configuring from a config file as specified by the environment variable DATAROBOT_CONFIG_FILE
  4. Configuring from the environment variables DATAROBOT_ENDPOINT and DATAROBOT_API_TOKEN
  5. Searching for a config file in the home directory of the current user, at ~/.config/datarobot/drconfig.yaml


If you access the DataRobot webapp at, then the correct endpoint to specify would be If you have a local installation, update the endpoint accordingly to point at the installation of DataRobot available on your local network.

Set Credentials Explicitly in Code

Explicitly set credentials in code:

import datarobot as dr
dr.Client(token='your_token', endpoint='')

You can also point to a YAML config file to use:

import datarobot as dr

Use a Configuration File

You can use a configuration file to specify the client setup.

The following is an example configuration file that should be saved as ~/.config/datarobot/drconfig.yaml:

token: yourtoken

You can specify a different location for the DataRobot configuration file by setting the DATAROBOT_CONFIG_FILE environment variable. Note that if you specify a filepath, you should use an absolute path so that the API client will work when run from any location.

Set Credentials Using Environment Variables

Set up an endpoint by setting environment variables in the UNIX shell:

export DATAROBOT_API_TOKEN=your_token

Common Issues

This section has examples of cases that can cause issues with using the DataRobot client, as well as known fixes.


On versions of Python earlier than 2.7.9 you might have InsecurePlatformWarning in your output. To prevent this without updating your Python version you should install pyOpenSSL package:

pip install pyopenssl ndg-httpsclient pyasn1

AttributeError: ‘EntryPoint’ object has no attribute ‘resolve’

Some earlier versions of setuptools will cause an error on importing DataRobot. The recommended fix is upgrading setuptools. If you are unable to upgrade setuptools, pinning trafaret to version <=7.4 will correct this issue.

>>> import datarobot as dr
File "/home/clark/.local/lib/python2.7/site-packages/trafaret/", line 1550, in load_contrib
  trafaret_class = entrypoint.resolve()
AttributeError: 'EntryPoint' object has no attribute 'resolve'

To prevent this upgrade your setuptools:

pip install --upgrade setuptools

Connection Errors

<configuration.rst> describes how to configure the DataRobot client with the max_retries parameter to fine tune behaviors like the number of times it attempts to retry failed connections.


If you have a slow connection to your DataRobot installation, you may see a traceback like

ConnectTimeout: HTTPSConnectionPool(host='', port=443): Max
retries exceeded with url: /api/v2/projects/
(Caused by ConnectTimeoutError(<requests.packages.urllib3.connection.VerifiedHTTPSConnection object at 0x7f130fc76150>,
'Connection to timed out. (connect timeout=6.05)'))

You can configure a larger connect timeout (the amount of time to wait on each request attempting to connect to the DataRobot server before giving up) using a connect_timeout value in either a configuration file or via a direct call to datarobot.Client.


Calling the project.open_leaderboard_browser may block if ran with a text-mode browser or running on a server that doesn’t have an ability to open a browser.