> ## Documentation Index
> Fetch the complete documentation index at: https://developers.stellar.org/llms.txt
> Use this file to discover all available pages before exploring further.

# Getting Started

> stellar-dbt-public GitHub repository.

[stellar-dbt-public GitHub repository](https://github.com/stellar/stellar-dbt-public/tree/master)

## Recommended Usage

### Import stellar-dbt-public as a dbt Package

If you need to build your own models on top of stellar-dbt-public, you can import stellar-dbt-public as a dbt package into a separate dbt project.

Example instructions:

* Create a new file `packages.yml` in your dbt project (not the stellar-dbt-public project) with the yml below

```
packages:
  - git: "https://github.com/stellar/stellar-dbt-public.git"
    revision: v0.0.28
```

* (Optional) Update your profiles.yml to include profile configurations for stellar-dbt-public

```
new_project:
  target: test
  outputs:
    test:
      project: <project>
      dataset: <dataset>
      <other configurations>

stellar_dbt_public:
  target: test
  outputs:
    test:
      project: <project>
      dataset: <dataset>
      <other configurations>
```

* (Optional) Update your dbt\_project.yml to include project configurations for stellar-dbt-public

```
name: 'stellar_dbt'
version: '1.0.0'
config-version: 2

profile: 'new_project'

model-paths: ["models"]
analysis-paths: ["analyses"]
test-paths: ["tests"]
seed-paths: ["seeds"]
macro-paths: ["macros"]
snapshot-paths: ["snapshots"]

target-path: "target"
clean-targets:
  - "target"
  - "dbt_packages"

models:
  new_project:
    staging:
      +materialized: view
    intermediate:
      +materialized: ephemeral
    marts:
      +materialized: table

  stellar_dbt_public:
    staging:
      +materialized: ephemeral
    intermediate:
      +materialized: ephemeral
    marts:
      +materialized: table
```

* Models from the stellar-dbt-public package/repo will now be available in your new dbt project

## Building and Running Locally

### Clone the repo

```
git clone https://github.com/stellar/stellar-dbt-public
```

### Install required python packages

```
pip install --upgrade pip && pip install -r requirements.txt

```

### Install required dbt packages

```
dbt deps
```

### Running dbt

* There are many useful commands that come with dbt which can be found in the [dbt documentation](https://docs.getdbt.com/reference/dbt-commands#available-commands)
* stellar-dbt-public is designed to use the `dbt build` command which will `run` the model and `test` the model table output
* (Optional) run with the `--full-refresh` option

```
dbt build --full-refresh
```

* Subsequent runs can be run with incremental mode (only inserts the newest of data instead of rebuilding all of history every time)

```
dbt build
```

* You can also specify just a single model if you don't want to run all stellar-dbt-public models

```
dbt build --select <model name or tag>
```

Please see the [stellar-dbt-public/modles/marts](https://github.com/stellar/stellar-dbt-public/tree/master/models/marts) directory to see a full list of the available models that dbt can run