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Kumo RelationalUser GuidePrepare DataConnect Data Sources

DuckDB Connector

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There are two ways to use DuckDB data: sample it in place with DuckDBSource, or read a table into memory with read().

Installation

pip install "structured-data-models-client[relational,duckdb]"

Sample in place with DuckDBSource

import duckdb
from sdm_client import PredictiveQuery, Schema
from sdm_connectors import DuckDBSource
connection = duckdb.connect("warehouse.duckdb", read_only=True)
source = DuckDBSource(connection)
schema = Schema.from_source(source, {"users": "USERS", "orders": "ORDERS"})
request = PredictiveQuery(
    "PREDICT COUNT(orders.*, 0, 30, days) FOR EACH users.user_id", schema
).materialize(indices=[7, 12, 3])

tables maps the names your query uses to the names in DuckDB; leave it out to describe every table in the database. The connection is yours — close it when you are done sampling.

Read into memory instead

from sdm_connectors import read
from sdm_client import Schema
users = read("duckdb", database="warehouse.duckdb", table="USERS")
orders = read("duckdb", database="warehouse.duckdb", table="ORDERS")
schema = Schema.from_data({"users": users, "orders": orders})

database and uri are aliases for the same argument; pass exactly one. Omitting it opens an in-memory database. Pass query= instead of table= to read the result of an arbitrary SQL statement.

Review the inferred schema and relationships before predicting — see Build a Schema.