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
1 maintainer
Metadata
1 maintainer
Release files for prefect-datahub 1.7.0.15rc4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| prefect_datahub-1.7.0.15rc4.tar.gz | 13.8 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| prefect_datahub-1.7.0.15rc4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 25.7 kB
Release files / prefect_datahub-1.7.0.15rc4.tar.gz
| Download URL | prefect_datahub-1.7.0.15rc4.tar.gz |
|---|---|
| Size | 13.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
5af2d29151685f9aea7cdea67ff8bfb7aabda99ac11e17912544d29b5ab8b6e2
|
|
BLAKE2b-256 checksum How to use checksums |
c65d52ef91c211d5dd5ae7488f4d57101a11816d14a8c6708d91aedf8f1da57a
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.10.22
|
Release files / prefect_datahub-1.7.0.15rc4-py3-none-any.whl
| Download URL | prefect_datahub-1.7.0.15rc4-py3-none-any.whl |
|---|---|
| Size | 11.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
02755b25835b091340b2741380ffe78eb2504aa4d79db479bb237e967ad796a3
|
|
BLAKE2b-256 checksum How to use checksums |
5cf2a46e2385f9eb7539df103499fa7553a4b90dfd7d8214aad240706a0d284e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.10.22
|
Security for prefect-datahub 1.7.0.15rc4
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
