Getting Started

This guide is for client engineers and analysts who want to move from repository access to a working platform configuration without reading the whole framework first.

Prerequisites

• Python 3.11 or newer for local scripts and development tasks.
• Azure CLI authenticated against the target subscription.
• Access to the deployment subscription and the platform resources your environment expects.
• Familiarity with either Databricks or Fabric, depending on the lens you are using.

Local setup

1. Create or activate the project virtual environment.
2. Install the local development dependencies used by the framework and tests.
3. Choose the example implementation that matches your target platform.
4. Review that example folder before editing contracts, infrastructure, notebooks, or jobs.

Where you will work

Most client teams work in one of these areas:

• databricks_example/ Initial example for Databricks configuration, contracts, notebooks, jobs, and deployment inputs.
• Rockdata Data Contracts to understand the source model and contract expectations before making changes.

In most cases, you will not need to modify the shared framework packages under libs/.

Databricks first run

Start with the Databricks example if you need the most complete reference path in this repository.

• Review databricks_example/jobs/jobs.yml for orchestration.
• Review databricks_example/notebooks/ for notebook entry points.
• Review the Databricks-specific notes in Architecture and Operations.

First engineering tasks

1. Inspect the relevant source and model in Rockdata Data Contracts before changing code.
2. Inspect the relevant example implementation for your platform.
3. Identify the contract, notebook, job, and parameter files you will be working with.
4. Run local validation before changing platform-specific notebooks or deployment files.
5. Validate docs and deployment artifacts in the same change set.