.. _bring-your-own:

Get started with your dbt project
=================================

If you have a sample project that you want to use to test out Cosmos functionality, or, you want to see how to set up a more custom project, check out the Bring your Own project guides.
These guides provide the general structure for how to set up a dbt project in Cosmos.

- :ref:`Open-source Airflow <open-source>`
- :ref:`Astro <astro>`
- :ref:`AWS MWAA <mwaa>`
- :ref:`Google Cloud Composer <gcc>`

When you're ready to set up and customize your Cosmos project, see the :ref:`guides`.

Example Demo: Jaffle Shop Project
__________________________________

If you don't have your own project that you want to set up as a demo, you can explore a practical example in the **Bring your own project** guides to see how Cosmos can convert the dbt workflow into an Airflow Dag.

The `jaffle_shop project <https://github.com/dbt-labs/jaffle_shop>`_ is a sample dbt project that simulates an e-commerce store's data.
The project includes a series of dbt models that transform raw data into structured tables, such as sales, customers, and products.

The following diagram shows the original dbt workflow in a lineage graph. This graph illustrates the relationships between different models:

.. image:: /_static/jaffle_shop_dbt_graph.png

Cosmos can take this dbt workflow and convert it into an Airflow Dag, allowing you to leverage Airflow's scheduling and
orchestration capabilities.

To convert this dbt workflow into an Airflow Dag, create a new Dag definition file, import ``DbtDag`` from the Cosmos library,
and fill in a few parameters, such as the dbt project directory path and the profile name:

..
   The following renders in Sphinx but not Github:

.. literalinclude:: ./../../dev/dags/basic_cosmos_dag.py
    :language: python
    :start-after: [START local_example]
    :end-before: [END local_example]


This code snippet then generates an Airflow Dag like this:

.. image:: https://raw.githubusercontent.com/astronomer/astronomer-cosmos/main/docs/_static/jaffle_shop_dag.png

``DbtDag`` is a custom Dag generator that converts dbt projects into Airflow Dags. It also accepts Cosmos-specific arguments like
``fail_fast``, to immediately fail a dag if dbt fails to process a resource, or ``cancel_query_on_kill``, to cancel any running
queries if the task is externally killed or manually set to failed in Airflow. ``DbtDag`` also accepts standard Dag arguments such
as ``max_active_tasks``, ``max_active_runs``, and ``default_args``.

With Cosmos, transitioning from a dbt workflow to an Airflow Dag is seamless, giving you the best of both tools
for managing and scaling your data workflows.