Bruin CLI

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Seed Assets ​

Seeds are CSV-files that contain data that is prepared outside of your pipeline that will be loaded into your data platform. Bruin supports seed assets natively, allowing you to simply drop a CSV file in your pipeline and ensuring the data is loaded to the destination platform accurately.

You can define seed assets in a file ending with .asset.yaml:

yaml
name: dashboard.hello
type: duckdb.seed

parameters:
    path: seed.csv

The type key in the configuration defines what platform to run the query against.

You can see the "Data Platforms" on the left sidebar to see supported types.

Parameters ​

The parameters key in the configuration defines the parameters for the seed asset. The path parameter is the path to the CSV file that will be loaded into the data platform. The path can be:

  • A relative file path: relative to the asset definition file (e.g., ./seed.csv)
  • A URL: an HTTP or HTTPS URL pointing to a publicly accessible CSV file (e.g., https://example.com/data.csv)

Column validation skipped for URLs

When using a URL path, column validation is skipped during bruin validate. Column mismatches will be caught at runtime when bruin run fetches the data.

TIP

URL-based seeds work with all supported platforms (DuckDB, BigQuery, Snowflake, PostgreSQL, etc.). The URL must be publicly accessible without authentication.

Examples ​

The examples below show how to load a CSV into a DuckDB & BigQuery database.

Simplest: Load csv into a Duckdb ​

yaml
name: dashboard.hello
type: duckdb.seed

parameters:
    path: hello.csv

Example CSV:

csv
name,networking_through,position,contact_date
Y,LinkedIn,SDE,2024-01-01
B,LinkedIn,SDE 2,2024-01-01

This operation will load the CSV into a table called seed.raw in the DuckDB database.

Adding quality checks ​

You can attach quality checks to seed assets the same way you do for other assets.

yaml
name: dashboard.hello
type: duckdb.seed

parameters:
    path: hello.csv

columns:
  - name: name
    type: string
    checks:
      - name: not_null
      - name: unique

The example above ensures that the name column contains unique and non-null values after the CSV is loaded.

Loading from a URL ​

You can load data directly from a public URL:

yaml
name: taxi_zones.lookup
type: duckdb.seed

parameters:
    path: https://d37ci6vzurychx.cloudfront.net/misc/taxi_zone_lookup.csv

This will download the CSV from the URL and load it into the database at runtime.