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)

Metadata

Release files for prefect-datahub 1.7.0.15rc5

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Source distribution (sdist)

Source distribution for prefect-datahub 1.7.0.15rc5
File	Size	Uploaded	Provenance
prefect_datahub-1.7.0.15rc5.tar.gz	13.8 kB	Oct 20, 2026	Without provenance	Details

Built distribution (wheel)

Table of built distributions (wheels) for prefect-datahub 1.7.0.15rc5
File	Interpreter	ABI	Platform	Reset
prefect_datahub-1.7.0.15rc5-py3-none-any.whl 11.9 kB Oct 20, 2026 Without provenance	Python 3	none	any	Details

Total release size: 25.7 kB

Release files / prefect_datahub-1.7.0.15rc5.tar.gz

Download URL	prefect_datahub-1.7.0.15rc5.tar.gz
Size	13.8 kB
Tags	Source
SHA-256 checksum How to use checksums	`939a7793a2f6d4f26d3e3c2b7e00d11a39ae8b972c62a751aa6f9ee441c98fa6`
BLAKE2b-256 checksum How to use checksums	`9633390a40b5d54892dd99fd8f6e5c644c582a6045ae6c5c004f3d35199d3b6c`
Upload date	Oct 20, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.10.22`

Release files / prefect_datahub-1.7.0.15rc5-py3-none-any.whl

Download URL	prefect_datahub-1.7.0.15rc5-py3-none-any.whl
Size	11.9 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`44ee47453b4363a71e63ee85ffe94ff3cd80e43acfa44e7ca0b0bdac5e93e37e`
BLAKE2b-256 checksum How to use checksums	`07790e0a0ea79073c6f6be34ff31d9ee5bf1dfd94268b5f5b9e758a7aebff485`
Upload date	Oct 20, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.10.22`

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