This release is a pre-release and may not be stable for production use.
The Kumo SDK implements a pythonic interface for users to programmatically interact with the Kumo machine learning platform (documentation).
Installation
The Kumo SDK is available for Python 3.10 to Python 3.14. To install, simply run
pip install kumoai
Optional database connectors can be installed with extras, for example:
pip install kumoai[sqlite]
pip install kumoai[duckdb]
pip install kumoai[snowflake]
Looking up projects
Every SDK session has one active project. You can retrieve another visible project by its display name or immutable Kumo ID without changing that active project:
import kumoai
kumoai.init() # Selects the canonical Default project.
fraud = kumoai.get_project("Fraud Detection")
assert kumoai.current_project().name == "Default"
# Pass the stable ID to project-scoped objects when needed.
events = kumoai.BigQueryConnector(
name="events",
project_id="company-data-prod", # Google Cloud project ID
dataset_id="events",
kumo_project_id=fraud.id, # Kumo project ID
)
Use kumoai.set_project(fraud) when you do want to change the active project.
Multi-categorical string columns
For a scalar string containing several categories, set the proven delimiter on the column. Kumo persists it in the table definition, so metadata validation, snapshots, and training all split the values identically. Comma, pipe, semicolon, and tab are supported.
interests = kumoai.Column(
name="interests",
stype="multicategorical",
dtype="string",
multicategorical_delimiter="|",
)
Do not set a delimiter for native stringlist or intlist columns; their
array structure already separates categories. When metadata inference detects
a delimiter, the SDK retains the inferred value automatically.
Google identities stay credential-free in the SDK
Administrators assign BigQuery and GCS identities to project-owning groups. Users can inspect the safe authentication mode and pass the identity to any number of project connectors, but private keys and workload tokens never enter SDK code. Workload identity is preferred when the deployment enables it.
identity = kumoai.get_identity("Production Google")
print(identity.config.authentication.mode)
# "workload_identity" or "service_account_key"
events = kumoai.BigQueryConnector(
name="events",
project_id="company-data-prod",
dataset_id="events",
identity=identity,
)
Omit identity to ask the server to select the only authorized identity that
can access the exact connector target. Connector constructors never accept
Google keys, source credentials, or access tokens.
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