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Getting Started

Setup

Follow these steps to set up your local development environment for the project.

1. Open VS Code

Launch Visual Studio Code and make sure it’s up to date.

2. Install Required Extensions

Windows users:

  1. Install the WSL extension.
  2. Press Ctrl + Shift + P, then run >WSL: Connect to WSL.
WSL: Connect to WSL

Clone Repository

All users:

Install the Dev Containers extension.

3. Clone the Repository

“Clone Repository” to download the project to your Linux filesystem (this provides much better performance inside WSL).

Cloning the Repository

Clone Repository

4. Configure Environment Variables

Copy the example environment file and update your credentials:

cp .env.example .env

Edit .env and fill in your local development secrets (e.g., API keys, database credentials).

Environment Setup

Environment Variables

5. Open the Project in a Dev Container

From VS Code, press Ctrl + Shift + P and run:

> Dev Containers: Open in Container

If prompted, install Docker for WSL (free community edition).
This launches your project in an isolated development container with preconfigured dependencies.

Dev Container Setup

Dev Container

6. Create a Feature Branch

Create a feature branch based off the QA branch.

Feature Branch

Dev Container

7. Sync Dependencies

Once the container is running, open the integrated terminal and run:

uv sync --all-packages

This command installs and synchronizes all project dependencies.

Syncing Dependencies

Sync Dependencies

Note:
Windows users must have Windows Subsystem for Linux (WSL) installed with at least one Linux distribution configured.
You can verify WSL installation with:

wsl --list --verbose

Usage

Once your container environment is up and running, you’re ready to develop.

Dagster

For local development, the dagster dev command can now be used to preview and test the changes you make in the code base.

dagster dev
Dagster Dev

Dagster Dev

Running dbt

  • dbt and its extensions are automatically installed inside the container.
    You can execute dbt models directly from VS Code using the built-in terminal.

Running Snowflake Scripts

The Snowflake extension is also preinstalled.
You can use it to run non-dbt SQL scripts directly from VS Code.

Managing Local Environments

Libraries and packages under libs/ and packages/data_analytics/ do not install automatically.
For best results, run the following inside each subproject directory:

uv sync

This creates and syncs isolated virtual environments for each workspace.

✅ Summary - Use WSL and Dev Containers for a consistent local setup.
- Run uv sync --all-packages after launching your container.
- dbt-Fusion and Snowflake are ready out of the box.
- Run uv sync inside each subproject for smoother development.