Setting the file. One moment.
Subchapter 2.3
references/assets/definition-metadata.mdMarkdown2 KBView on GitHub
Applied once when the asset is defined:
@dg.asset(
description="Detailed description for the UI",
group_name="analytics",
key_prefix=["warehouse", "staging"],
owners=["team:data-engineering", "user@example.com"],
tags={"priority": "high", "pii": "true", "domain": "sales"},
code_version="1.2.0",
)
def my_asset() -> None:
passteam:name) or individuals for accountabilityAssetKey([*prefix, fn_name]), e.g. key_prefix=["warehouse", "raw"] on a function named orders produces AssetKey(["warehouse", "raw", "orders"]). Use the name argument to override the function name portion (useful in factory patterns that produce many assets from one function).For @multi_asset, set the same properties on each AssetSpec:
@dg.multi_asset(
specs=[
dg.AssetSpec(
"users",
group_name="raw_data",
owners=["team:data-engineering"],
tags={"priority": "high"},
description="Raw user records from API",
),
dg.AssetSpec(
"orders",
group_name="raw_data",
deps=["users"],
),
],
)
def load_data(): ...AssetSpec accepts the same metadata parameters as @dg.asset: description, group_name, owners, tags, kinds, deps, code_version, automation_condition, key_prefix, and more.