Kubeflow Pipelines is a platform for building and deploying portable, scalable machine learning workflows based on Docker containers within the Kubeflow project.
Use Kubeflow Pipelines to compose a multi-step workflow (pipeline) as a graph of containerized tasks using Python code and/or YAML. Then, run your pipeline with specified pipeline arguments, rerun your pipeline with new arguments or data, schedule your pipeline to run on a recurring basis, organize your runs into experiments, save machine learning artifacts to compliant artifact registries, and visualize it all through the Kubeflow Dashboard.
Installation
To install kfp, run:
pip install kfp
Getting started
The following is an example of a simple pipeline that uses the kfp v2 syntax:
from kfp import dsl
import kfp
@dsl.component
def add(a: float, b: float) -> float:
'''Calculates sum of two arguments'''
return a + b
@dsl.pipeline(
name='Addition pipeline',
description='An example pipeline that performs addition calculations.')
def add_pipeline(
a: float = 1.0,
b: float = 7.0,
):
first_add_task = add(a=a, b=4.0)
second_add_task = add(a=first_add_task.output, b=b)
client = kfp.Client(host='<my-host-url>')
client.create_run_from_pipeline_func(
add_pipeline, arguments={
'a': 7.0,
'b': 8.0
})
6 maintainers
Release files for kfp 2.17.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| kfp-2.17.0.tar.gz | 362.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| kfp-2.17.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 840.3 kB
Release files / kfp-2.17.0.tar.gz
| Download URL | kfp-2.17.0.tar.gz |
|---|---|
| Size | 362.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
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Transparency logRelease files / kfp-2.17.0-py3-none-any.whl
| Download URL | kfp-2.17.0-py3-none-any.whl |
|---|---|
| Size | 477.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
dff321b76b2be8a09748a1be805a88699b4919e13bb6a1bf67ebf3074ea8ce3f
|
|
BLAKE2b-256 checksum How to use checksums |
e9c6eab3e5ed59497c09e0aca3f1cf0fc7c9c7ceaa05be0db620787355ffb351
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
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.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jul 9, 2026.
Transparency log
