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π det v0.2.0 β Minimum Viable Product Release
Engine change from Polars to Apache DataFusion, addition of decoupled workspace modules, and release of the v0.2.0 MVP.
β‘ Core Engine & Architectural Directives
- Apache DataFusion & Arrow: Replaced Polars with embedded Apache DataFusion (vectorized Rust query engine) and Apache Arrow columnar memory for SIMD-accelerated, multi-threaded SQL execution across CPU cores.
- Modularity: Fully decoupled workspace architecture covering Catalogs (
catalog/*.yaml), Pipeline DAGs (pipelines/*/*.yaml), Storage Connectors, Execution Runner, Static Documentation Generator, and Web IDE. - Performance: Ingest, join, and transform multi-gigabyte datasets in-memory with sub-second step latency and zero cloud egress fees.
- Extensibility: Standardized
BaseConnectorplugin framework enabling custom data sources (PostgreSQL, ClickHouse, DuckDB, REST APIs) in pure Python.
π¦ Polyglot Formats & Medallion Pipelines
- Unifies Parquet, Delta Lake (ACID), multi-sheet Excel (.xlsx), CSV, JSON, NDJSON, and XML in ANSI SQL joins.
- Declarative multi-step DAG orchestrator supporting intermediate caching, automated column lineage, and schema derivation.
πͺ Bundled NovaMart Global Warehouse
- Instantly unpack 14 connections, 8 file formats, and 10 production SQL pipelines using
det sample-data.
π Interactive Web IDE & Live Documentation Portal
- Visual DAG topology viewer, Monaco SQL runner, catalog schema tree, and telemetry monitor (
det gui). - Standalone HTML/Markdown documentation generation (
det docs) and live showcase hosted on GitHub Pages.
π‘οΈ Governance & Security
- Licensed under MIT License with copyright attribution to Saurabh Rai and det-Labs.
- Added
CONTRIBUTING.md,CODE_OF_CONDUCT.md,SECURITY.md, and automated Dependabot updates.