Python Environments (Local or Kubeflow)#

Connecting to the Feature Store from any Python environment requires setting up a Feature Store API key and installing the library. This guide explains step by step how to connect to the Feature Store from any Python environment such as your local environment or KubeFlow.

Install HSFS#

To be able to access the Hopsworks Feature Store, the HSFS Python library needs to be installed in the environment from which you want to connect to the Feature Store. You can install the library through pip. We recommend using a Python environment manager such as virtualenv or conda.

pip install hsfs[python]~=[HOPSWORKS_VERSION]

The major version of HSFS needs to match the major version of Hopsworks.

Generate an API key#

For instructions on how to generate an API key follow this user guide. For the Python client to work correctly make sure you add the following scopes to your API key:

1. featurestore
2. project
3. job
4. kafka

Connect to the Feature Store#

You are now ready to connect to the Hopsworks Feature Store from your Python environment:

import hsfs
conn = hsfs.connection(
    host='my_instance',                 # DNS of your Feature Store instance
    port=443,                           # Port to reach your Hopsworks instance, defaults to 443
    project='my_project',               # Name of your Hopsworks Feature Store project
    api_key_value='apikey',             # The API key to authenticate with Hopsworks
    hostname_verification=True,         # Disable for self-signed certificates
    engine="python"                     # Set to "spark" if you are using Spark/EMR
)
fs = conn.get_feature_store()           # Get the project's default feature store

Next Steps#

For more information about how to connect, see the Connection API reference. Or continue with the Data Source guide to import your own data to the Feature Store.