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semantic_model_writer

sqllocks_spindle.fabric.semantic_model_writer

Export Spindle schemas to Power BI / Fabric semantic model .bim files.

Generates TOM (Tabular Object Model) JSON at compatibilityLevel 1604, including auto-generated DAX measures for fact tables and M expressions for Lakehouse, Warehouse, or SQL Database sources.

No external dependencies — uses only stdlib json/pathlib.

Usage::

from sqllocks_spindle.fabric.semantic_model_writer import SemanticModelExporter

exporter = SemanticModelExporter()
path = exporter.export_bim(
    schema=schema,
    source_type="lakehouse",
    source_name="MyLakehouse",
    output_path="retail_model.bim",
    include_measures=True,
)

Classes

SemanticModelExporter

Export a SpindleSchema to a Power BI .bim (TOM JSON) file.

Generates
  • Table definitions with typed columns
  • Relationships from SpindleSchema FK definitions
  • Auto-generated DAX measures (SUM, COUNTROWS, AVERAGE)
  • M (Power Query) partition expressions per source type
Methods:
export_bim(schema, source_type='lakehouse', source_name='', output_path='model.bim', include_measures=True, schema_name='dbo')

Export schema to a .bim file (TOM JSON format).

Parameters:

Name Type Description Default
schema SpindleSchema

A SpindleSchema describing tables and relationships.

 required
source_type str

Data source — "lakehouse", "warehouse", or "sql_database".

 'lakehouse'
source_name str

Name of the Lakehouse/Warehouse/Server item.

 ''
output_path str | Path

Destination file path for the .bim output.

 'model.bim'
include_measures bool

Generate DAX measures for numeric columns.

 True
schema_name str

SQL schema for warehouse/sql_database sources.

 'dbo'

Returns:

Type Description
Path

Path to the written .bim file.
to_dict(schema, source_type='lakehouse', source_name='', include_measures=True, schema_name='dbo')

Return the TOM model as a dict (without writing to disk).