Semolina

Semolina: the ORM for your Semantic Layer.

Typed models in Python, supporting IDE autocomplete, and a Django-like fluent query interface for the semantic layer of your data warehouse backend.

Get started in 5 minutes

Install Semolina and write your first query.

Installation

Define models

Map Metric and Dimension fields to your warehouse semantic views.

How to define models

Build queries

Chain .metrics(), .dimensions(), .where(), .order_by(), .limit().

How to build queries

API reference

Auto-generated reference for every public class, function, and field.

semolina

Quick example

from semolina import (
    SemanticView,
    Metric,
    Dimension,
    register,
    pool_from_config,
)


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


pool, dialect = pool_from_config()  # reads .semolina.toml
register("default", pool, dialect=dialect)

cursor = (
    Sales.query()
    .metrics(Sales.revenue)
    .dimensions(Sales.country)
    .limit(10)
    .execute()
)

for row in cursor.fetchall_rows():
    print(row.country, row.revenue)

Write the query once. Change the type in your .semolina.toml and the same code runs on Databricks.