A composable Python data engineering ecosystem. Expressions, rules, validation, schema conformance and pipelines are built once against a single expression algebra, then run on Polars, pandas, DuckDB and the other backends reachable through Ibis and Narwhals. The backend becomes a deployment decision, not a code decision.
Status: under active development, not production ready. None of the packages are on PyPI yet, and APIs can change without notice.
mainis the release line; work happens ondevelop.
Documentation: docs.mountainash.io
The foundation the other packages build on.
| Package | Intent |
|---|---|
| mountainash | Cross-backend expressions and relational plans. Write col(), lit(), when() in Polars-style syntax and compile to the selected backend. |
| mountainash-data | One connection interface for analytical backends: relational databases through Ibis, and Iceberg catalogs through PyIceberg. |
| mountainash-settings | Typed configuration: layered YAML, TOML, JSON and environment variables, template resolution and Pydantic integration. |
| Package | Intent |
|---|---|
| mountainash-rules | Metadata-driven business rules engine. Rules are rows, not code: decision tables with multiple match strategies, ranked by specificity, evaluated in one vectorised pass, with per-rule explainability. |
| mountainash-structuremap | Declarative, bidirectional transformation between hierarchical payloads (XML, JSON) and relational tables. |
| Package | Intent |
|---|---|
| mountainash-transport | Storage abstraction with one interface across local and cloud object stores. |
Start with mountainash and its manual. It introduces the expression and relation abstractions everything else uses.
Built in Melbourne. Website: mountainash.io
