DataHub Dagster Plugin
Automatic lineage and run metadata from Dagster into DataHub — captures asset definitions, job runs, and dataset-level lineage with no manual instrumentation.
What you can do
- Capture asset lineage — automatically extract upstream/downstream relationships between Dagster assets and external datasets
- Track run history — record job execution status and task-level outcomes in DataHub
- Map Dagster assets to DataHub entities — assets appear as datasets in your DataHub catalog
- Works with any DataHub deployment — self-hosted or DataHub Cloud
Installation
pip install acryl-datahub-dagster-plugin
Quickstart
Add the DataHub sensor to your Dagster project:
from datahub.ingestion.graph.config import DatahubClientConfig
from datahub_dagster_plugin.sensors.datahub_sensors import (
DatahubDagsterSourceConfig,
make_datahub_sensor,
)
config = DatahubDagsterSourceConfig(
datahub_client_config=DatahubClientConfig(server="http://localhost:8080"),
dagster_url="http://localhost:3000",
)
datahub_sensor = make_datahub_sensor(config=config)
Register it alongside your jobs and assets in your Definitions:
from dagster import Definitions
defs = Definitions(
assets=[...],
jobs=[...],
sensors=[datahub_sensor],
)
Once the sensor is running, every job run will emit lineage and status metadata to DataHub automatically.
Links
1 maintainer
Metadata
1 maintainer
Release files for acryl-datahub-dagster-plugin 1.7.0.17
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| File | Size | Uploaded | Provenance | |
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|---|---|---|---|---|
| acryl_datahub_dagster_plugin-1.7.0.17-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 42.9 kB
Release files / acryl_datahub_dagster_plugin-1.7.0.17.tar.gz
| Download URL | acryl_datahub_dagster_plugin-1.7.0.17.tar.gz |
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| Size | 21.2 kB |
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|---|---|
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| Tags | Python 3 |
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