Blueprint Workshop setup¶
This page explains how to configure the Blueprint Workshop, including installing the required libraries, enabling your DataRobot account, and establishing a connection to DataRobot by providing credentials.
Uncensored Blueprints are off by default. Contact your DataRobot representative or administrator for information on enabling this feature.
Feature flag: Show Uncensored Blueprints
Run the following steps to install the Blueprint Workshop.
mkvirtualenv -p python3.7 blueprint-workshop
sudo apt-get install graphvizor
brew install graphviz
pip install datarobot-bp-workshop
Connect to DataRobot¶
Use the following sections to connect to DataRobot in order to use the Blueprint Workshop. Each authentication method below specifies credentials for DataRobot, as well as the location of the DataRobot deployment. DataRobot currently supports configuration using a configuration file, by setting environment variables, or within the code itself.
Specify an API token and an endpoint in order to use the client. You can manage your API tokens in the DataRobot application by selecting your profile and navigating to Developer Tools. The order of precedence is as follows. Note that the first available option will be used.
- Set an endpoint and API key in code using
- Set up a config file as specified directly using
- Set up a config file as specified by the environment variable
- Configure the environment variables
- Search for a config file in the home directory of the current user, at
For more information, read about the different options for connecting to DataRobot from the Python client.
If you access DataRobot at
https://app.datarobot.com, the correct endpoint to specify would be
https://app.datarobot.com/api/v2. If you have a local installation, update the endpoint accordingly to point at the installation of DataRobot available on your local network.
Set credentials in code¶
To set credentials explicitly in code:
import datarobot as dr dr.Client(token='your_token', endpoint='https://app.datarobot.com/api/v2')
You can also point to a YAML config file to use:
import datarobot as dr dr.Client(config_path='/home/user/my_datarobot_config.yaml')
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
token: yourtoken endpoint: https://app.datarobot.com/api/v2
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 file path, 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_ENDPOINT='https://app.datarobot.com/api/v2' export DATAROBOT_API_TOKEN=your_token