Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

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

Metadata

Release files for prefect-datahub 1.7.0.9rc1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for prefect-datahub 1.7.0.9rc1
File Size Uploaded
prefect_datahub-1.7.0.9rc1.tar.gz 13.7 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for prefect-datahub 1.7.0.9rc1
File Interpreter ABI Platform
prefect_datahub-1.7.0.9rc1-py3-none-any.whl Python 3 none any Details

Total release size: 25.6 kB

Release files / prefect_datahub-1.7.0.9rc1.tar.gz

Download URL prefect_datahub-1.7.0.9rc1.tar.gz
Size 13.7 kB
Tags Source
SHA-256 checksum
How to use checksums
afee96663b4bc2733758de69c9c607b008e62955f5824aabdbbec6e3e61497c1
BLAKE2b-256 checksum
How to use checksums
c8bff1903a431fd0714cc8806a55d879863f712539aa4095a7dc85554b3e4a25
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.10.21

Release files / prefect_datahub-1.7.0.9rc1-py3-none-any.whl

Download URL prefect_datahub-1.7.0.9rc1-py3-none-any.whl
Size 11.9 kB
Tags Python 3
SHA-256 checksum
How to use checksums
2334e027d02648a1bf5781bf448884b20661729cef70f10d5c150b2835279569
BLAKE2b-256 checksum
How to use checksums
ac77dfe39973b2c58248313e587c452e15446ffe1f538cc498a861270e9b385c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.10.21

Release history Release notifications | RSS feed

15.0.4

2 release files

This release

1.7.0.9rc1 This release

2 release files

1.7.0

2 release files

1.6.0

2 release files

1.5.0

2 release files

1.4.0

2 release files

1.3.1

2 release files

1.3.0

2 release files

1.2.0

2 release files

1.1.0

2 release files

1.0.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page