DataHub Prefect Plugin
Automatic lineage and run metadata from Prefect into DataHub — captures flow structure, task inputs/outputs, and run history with minimal setup.
What you can do
- Emit flow and task metadata to DataHub as pipeline runs
- Capture dataset lineage — declare inputs and outputs per task and see them in DataHub
- Configure via Prefect blocks — store your DataHub connection settings as a reusable block
- Works with any DataHub deployment — self-hosted or DataHub Cloud
Installation
pip install prefect-datahub
Quickstart
1. Save your DataHub connection as a Prefect block
from prefect_datahub.datahub_emitter import DatahubEmitter
DatahubEmitter(
datahub_rest_url="http://localhost:8080",
env="PROD",
).save("my-datahub")
2. Use it in your flows
from prefect import flow, task
from prefect_datahub.datahub_emitter import DatahubEmitter
from prefect_datahub.entities import Dataset
emitter = DatahubEmitter.load("my-datahub")
@task
def transform(data, emitter):
emitter.add_task(
inputs=[Dataset("snowflake", "mydb.schema.source_table")],
outputs=[Dataset("snowflake", "mydb.schema.output_table")],
)
return data
@flow
def my_pipeline():
data = extract()
transform(data, emitter)
emitter.emit_flow() # required — emits all metadata at the end
Configuration options
| Option | Default | Description |
|---|---|---|
datahub_rest_url |
http://localhost:8080 |
DataHub GMS URL |
env |
PROD |
Environment tag for assets |
platform_instance |
None |
Platform instance for assets |
token |
None |
Auth token (if GMS auth is enabled) |
Links
1 maintainer
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
prefect_datahub-1.7.0.3.tar.gz
(13.7 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file prefect_datahub-1.7.0.3.tar.gz.
File metadata
- Download URL: prefect_datahub-1.7.0.3.tar.gz
- Upload date:
- Size: 13.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/7.0.0 CPython/3.10.20
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
a8b9ead81d70f962838ed5f48af85d4a7f5665b6dca70fbaa3da436713589431
|
|
| MD5 |
4beead7f8c808a5b79e6fe46bf3fe960
|
|
| BLAKE2b-256 |
0bb31a51a0d66a5912159cb46aed5f320e704d8711527ab50ab92e5068ca25ca
|
File details
Details for the file prefect_datahub-1.7.0.3-py3-none-any.whl.
File metadata
- Download URL: prefect_datahub-1.7.0.3-py3-none-any.whl
- Upload date:
- Size: 11.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via:
twine/7.0.0 CPython/3.10.20
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
fe48ad96c5561462463c7f5f42fdf6e39f31cb8013dbf90506a07ec1466b8abc
|
|
| MD5 |
2f3d060af9eabc48d3d76fc336732c99
|
|
| BLAKE2b-256 |
1eb9cb132c035c4de8e50302e4825258c1a5763353d63b80ccd7922029aa31f6
|
