SQLite Connector

SQLite is what lets development and CI exercise the full sampling path, including SQL sampling, with no credentials. There are two ways to use it: sample in place with SQLiteSource, or read a table into memory with read().

Installation

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

Sample in place with SQLiteSource

import adbc_driver_sqlite.dbapi
from sdm_client import PredictiveQuery, Schema
from sdm_connectors import SQLiteSource
connection = adbc_driver_sqlite.dbapi.connect("data.db")
source = SQLiteSource(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 the database; leave it out to describe every table SQLite holds, under its own name. 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("sqlite", database="data.db", table="USERS")
orders = read("sqlite", database="data.db", table="ORDERS")
schema = Schema.from_data({"users": users, "orders": orders})

database and uri are aliases for the same argument; pass exactly one. 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.