Boring Semantic Layer (BSL)
The Boring Semantic Layer (BSL) is a lightweight semantic layer based on Ibis.
Key Features:
- Lightweight:
pip install boring-semantic-layer - Ibis-powered: Built on top of Ibis, supporting any database engine that Ibis integrates with (DuckDB, Snowflake, BigQuery, PostgreSQL, and more)
- MCP-friendly: Perfect for connecting LLMs to structured data sources
Quick Start
pip install 'boring-semantic-layer[examples]'
1. Define your ibis input table
import ibis
# Create a simple in-memory table
flights_tbl = ibis.memtable({
"origin": ["JFK", "LAX", "JFK", "ORD", "LAX"],
"carrier": ["AA", "UA", "AA", "UA", "AA"]
})
2. Define a semantic table
from boring_semantic_layer import to_semantic_table
flights = (
to_semantic_table(flights_tbl, name="flights")
.with_dimensions(origin=lambda t: t.origin)
.with_measures(flight_count=lambda t: t.count())
)
3. Query it
result_df = flights.group_by("origin").aggregate("flight_count").execute()
📚 Documentation
This project is a joint effort by xorq-labs and boringdata.
We welcome feedback and contributions!
Freely inspired by the awesome Malloy project. We loved the vision, just took the Python route.
1 maintainer
Metadata
1 maintainer
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