Semantic data layer: SemanticQuery → backend SQL with authorisation, row-level scoping, time-spine fill, and a typed four-role LLM prompt pipeline.
Project description
semql
Pure-Python compiler from a semantic spec to backend SQL. Define cubes (dimensions, measures, time-dimensions, joins) once; emit correct, parameterised SQL for Postgres, ClickHouse, DuckDB and (via the strategy seam) Snowflake / BigQuery.
semql does no I/O: catalogs are Python data; the compiler
returns SQL + bound params; running the SQL is the caller's job.
Prompt-fragment rendering for LLM planners ships in the core
(semql.prompt). Sibling packages add MCP exposure (semql-mcp)
and ER diagrams (semql-erd).
Install
pip install semql
Quick start
from semql import (
Backend,
Catalog,
Cube,
Dimension,
Measure,
SemanticQuery,
)
orders = Cube(
name="orders",
backend=Backend.POSTGRES,
table="orders",
alias="o",
measures=[
Measure(name="revenue", sql="{o}.amount", agg="sum", unit="currency"),
],
dimensions=[
Dimension(name="region", sql="{o}.region", type="string"),
],
)
catalog = Catalog([orders])
compiled = catalog.compile(
SemanticQuery(measures=["orders.revenue"], dimensions=["orders.region"]),
)
# compiled.sql, compiled.params, compiled.columns, compiled.backend
The {o} placeholder in a cube's sql is its alias; the compiler
resolves it (along with {schema}-style context placeholders and
{ctx.X} row-level-security placeholders) at compile time.
What lives in the box
| Surface | Module |
|---|---|
| Cube / Measure / Dimension / TimeDimension / Join | semql.model |
| SemanticQuery / Filter / TimeWindow / CompareWindow | semql.spec |
| Catalog wrapper (validation, prompt, compile entry) | semql.catalog |
| Compiler — sqlglot AST → dialect SQL | semql.compile |
| Collect-all static validator | semql.validate |
| Reflection cubes (catalog_cubes, ...) | semql.introspect |
| Planner / router prompt fragments | semql.prompt |
| Backend strategies + sqlglot dialect adapter | semql.backend, semql.dialect |
| Visualisation decision (chart type, axes, formats) | semql.visualize |
is_safe_select post-hoc SQL guard |
semql.safe |
| Structured error hierarchy | semql.errors |
Features
- Compare windows —
CompareWindow(mode="previous_period")wraps the inner query incurrent/priorCTEs joined viaFULL OUTER JOINand emits{m}_current/{m}_prior/{m}_delta/{m}_pct_changecolumns per measure. - Tenancy — per-cube
SCHEMA(default;{tenant_schema}substitution) orDISCRIMINATOR(compiler wraps the source in a subquery withWHERE tenancy_column = $tenant). - Row-level security —
Cube.security_sqlAND-composes with tenancy inside the isolation subquery;{ctx.X}placeholders bind as parameters, never inline as literals. - MCP-ready —
Catalog.prompt()produces the planner system-prompt fragment;semql-mcpwraps it as a server. - Pluggable backends —
BackendDialectProtocol lets out-of-tree Snowflake / BigQuery adapters slot in without forking the compiler.
Philosophy
See PHILOSOPHY.md at the repo root. Highlights:
- Correct SQL, not optimal. The query planner is the database's job.
- The emitted SQL must read like something a human could have written.
compile()fails at the first problem;validate()collects them all.- The catalog is data; reflection isn't an afterthought.
Status
Pre-v1. The shape is stable, but minor names / fields may move before the v1 contract locks. Tests pin every public behaviour the README documents.
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