How to connect to Snowflake

Install the Snowflake extra

pip install semolina[snowflake]
# or
uv add "semolina[snowflake]"

The Snowflake extra installs adbc-poolhouse[snowflake], which provides the ADBC Snowflake driver and connection pooling.

Configure with .semolina.toml (recommended)

Create a .semolina.toml file in your project root:

# .semolina.toml
[connections.default]
type = "snowflake"
account = "xy12345.us-east-1"
user = "myuser"
password = "mypassword"
database = "analytics"
warehouse = "compute_wh"
# role = ""
# schema = ""

Field	Type	Required	Description
type	str	Yes	Must be "snowflake"
account	str	Yes	Account identifier with region (e.g. xy12345.us-east-1)
user	str	Yes	Snowflake username
password	str	Yes	Snowflake password
database	str	No	Default database
warehouse	str	No	Compute warehouse name
role	str	No	Role to activate for the session
schema	str	No	Default schema

Then load and register the pool:

from semolina import register, pool_from_config

pool, dialect = (
    pool_from_config()
)  # reads [connections.default]
register("default", pool, dialect=dialect)

Tip

Use pool_from_config(connection="analytics") to load a named connection section other than default.

Configure manually

When credentials come from a vault or secrets manager, construct the pool directly:

from adbc_poolhouse import SnowflakeConfig, create_pool
from semolina import register

config = SnowflakeConfig(
    account="xy12345.us-east-1",
    user="myuser",
    password="mypassword",
    database="analytics",
    warehouse="compute_wh",
)
pool = create_pool(config)
register("default", pool, dialect="snowflake")

Run a query

Once a pool is registered, the query API works the same as any backend:

from semolina import SemanticView, Metric, Dimension


class Sales(SemanticView, view="sales"):
    revenue = Metric()
    country = Dimension()


cursor = (
    Sales.query()
    .metrics(Sales.revenue)
    .dimensions(Sales.country)
    .execute()
)
for row in cursor.fetchall_rows():
    print(row.country, row.revenue)

Generated SQL

Snowflake SQL uses AGG() for metrics and double-quoted identifiers:

SELECT AGG("revenue"), "country"
FROM "sales"
GROUP BY ALL

See also

• How to choose and configure a backend – compare connection patterns

• How to connect to Databricks – connect to Databricks metric views

• How to test application code with MockPool – test queries with MockPool