Metadata-Version: 2.4
Name: databricks-project-accelerators
Version: 0.1.2
Summary: CLI to scaffold Databricks solutions for industry use cases
Project-URL: Homepage, https://github.com/pegodk/databricks-project-accelerators
Project-URL: Repository, https://github.com/pegodk/databricks-project-accelerators
Project-URL: Documentation, https://pegodk.github.io/databricks-project-accelerators/
Project-URL: Bug Tracker, https://github.com/pegodk/databricks-project-accelerators/issues
Author-email: Peter Gormsen <peter.gormsen@twoday.com>
License: MIT
License-File: LICENSE
Keywords: accelerator,databricks,delta-live-tables,medallion
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Software Development :: Code Generators
Classifier: Topic :: Utilities
Requires-Python: >=3.10
Requires-Dist: jinja2>=3.1
Requires-Dist: pyyaml>=6
Requires-Dist: rich>=13
Requires-Dist: shellingham>=1.5
Requires-Dist: typer>=0.12
Provides-Extra: dev
Requires-Dist: faker>=25; extra == 'dev'
Requires-Dist: pytest>=8; extra == 'dev'
Requires-Dist: ruff>=0.9; extra == 'dev'
Provides-Extra: docs
Requires-Dist: mkdocs-material>=9; extra == 'docs'
Requires-Dist: mkdocstrings[python]>=0.29; extra == 'docs'
Provides-Extra: spark
Requires-Dist: faker>=25; extra == 'spark'
Requires-Dist: pyspark>=3.5; extra == 'spark'
Description-Content-Type: text/markdown

# Databricks Project Accelerators

![](docs/assets/hero.png)

CLI tool that scaffolds production-ready Databricks solutions via Jinja2 templates and Databricks Asset Bundles.

**[Documentation](https://pegodk.github.io/databricks-project-accelerators/)**

## Installation

```bash
pip install databricks-project-accelerators
```

## Quickstart

Open an empty folder in VS Code, then run in the terminal:

```bash
# See what's available
dpa list

# Scaffold a project
dpa init medallion-sdp

# Open the generated project
code medallion-sdp
cd medallion-sdp

# Authenticate the Databricks CLI if you haven't already
databricks configure

# Deploy to your workspace
databricks bundle deploy

# Run the job
databricks bundle run medallion_sdp_job
```

That's it — your Databricks solution is live.

## Accelerators

| Name | Description |
|------|-------------|
| `medallion-sdp` | Streaming Delta Pipeline (DLT) with bronze/silver/gold layers and a DAB job |
| `medallion-dbt` | Medallion architecture (bronze/silver/gold) using dbt models over TPCH |
| `mlflow-project` | MLflow training, model registration, and batch scoring over TPCH |
| `lakebase-streamlit-app` | Databricks App (Streamlit) connected to TPCH analytics + Lakebase master data |
| `custom-python-wheel` | Custom Python wheel package with a build-and-upload job and an import verification notebook |
| `ai-bi` | Lakeview dashboard + Genie Space with metric views over the TPCH sample dataset |

## CLI reference

```bash
dpa init <accelerator>          # scaffold a project
dpa init <accelerator> --dry-run  # preview files without writing
dpa init <accelerator> --force    # overwrite existing files
dpa list                          # list all accelerators
dpa deploy --env prod             # deploy via Databricks Asset Bundle
```

## Requirements

- Python 3.10+
- [Databricks CLI v1.3.0+](https://docs.databricks.com/dev-tools/cli/install.html) configured against a Unity Catalog workspace
