kfp-server-api
Kubeflow Pipelines API
Decision gist · record as of 2026-08-14
Yes, if you need programmatic access to a Kubeflow Pipelines service and are comfortable with a low-level API client. The high install friction and lack of declared Python version support suggest this is aimed at users already familiar with Kubeflow and Kubernetes. No known vulnerabilities and active maintenance are positive signals. Not recommended if you're looking for a high-level SDK—use the main Kubeflow Pipelines SDK instead.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a running Kubeflow Pipelines service (typically deployed on Kubernetes) to connect to; this package is a client library only.
- High install friction due to being a generated OpenAPI client with multiple HTTP/date-handling dependencies.
- Actively maintained with recent releases, though the package itself is a thin wrapper around the Kubeflow Pipelines service API.
License · maintenance · safety
Apache 2.0 (permissive) — Apache 2.0 is permissive; you can use, modify, and distribute this package freely in commercial and private projects with minimal restrictions.
last release 2026-07-09 (36 days) · last repo commit 2026-08-14 · 4,183 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 3,151,118 downloads/mo, #2,725 on PyPI
Alternatives
Verify before relying
pip install kfp-server-api
from kfp_server_api.rest import ApiClient
from kfp_server_api.models.api_pipeline import ApiPipeline
client = ApiClient()
# Configure client with Kubeflow Pipelines server endpoint- Whether this package is intended for end users or primarily for SDK/tooling developers building on top of Kubeflow Pipelines.
- Specific Python version requirements or compatibility constraints not declared in the package metadata.
- Whether high install friction reflects genuine dependency complexity or transient build issues.
What it is and what it does
kfp-server-api is an auto-generated Python client for the Kubeflow Pipelines REST API. It provides typed Python bindings to interact with a Kubeflow Pipelines service deployed on Kubernetes, allowing you to programmatically create, list, run, and manage ML pipelines and experiments. The package depends on standard HTTP and date-handling libraries (urllib3, certifi, python-dateutil, six) to handle API communication.
This is a low-level client library—it exposes the raw API surface rather than a high-level SDK. It is typically used by tooling, integrations, or advanced users who need direct API access rather than the higher-level Kubeflow Pipelines SDK. The package is actively maintained and generated from the Kubeflow Pipelines API specification.
Use it for
- Build custom tooling or integrations that need to interact with a Kubeflow Pipelines service programmatically.
- Automate pipeline management tasks (create, list, run, monitor) from Python scripts or applications.
- Integrate Kubeflow Pipelines into CI/CD systems or workflow orchestrators that require API-level control.
- Develop monitoring or auditing tools that query pipeline status and execution history from a Kubeflow cluster.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need programmatic access to a Kubeflow Pipelines service and are comfortable with a low-level API client.
The high install friction and lack of declared Python version support suggest this is aimed at users already familiar with Kubeflow and Kubernetes. No known vulnerabilities and active maintenance are positive signals. Not recommended if you're looking for a high-level SDK—use the main Kubeflow Pipelines SDK instead.
Install
kfp-server-api on PyPI
Before you install
High install friction due to being a generated OpenAPI client with multiple HTTP/date-handling dependencies. Actively maintained with recent releases, though the package itself is a thin wrapper around the Kubeflow Pipelines service API.
Requires a running Kubeflow Pipelines service (typically deployed on Kubernetes) to connect to; this package is a client library only.
License in practice
Apache 2.0 is permissive; you can use, modify, and distribute this package freely in commercial and private projects with minimal restrictions.
Quickstart
pip install kfp-server-api
from kfp_server_api.rest import ApiClient
from kfp_server_api.models.api_pipeline import ApiPipeline
client = ApiClient()
# Configure client with Kubeflow Pipelines server endpointVerify before relying
- Whether this package is intended for end users or primarily for SDK/tooling developers building on top of Kubeflow Pipelines.
- Specific Python version requirements or compatibility constraints not declared in the package metadata.
- Whether high install friction reflects genuine dependency complexity or transient build issues.
Package facts
| License | Apache 2.0 permissive |
| Python support | Not specified |
| Install friction | High. Source build required |
| Runtime dependencies | 4 packagesurllib3sixcertifipython-dateutil |
| Maintenance | Actively maintained 36 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 3,151,118 / month, #2,725 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: kfp_server_api-2.17.0.tar.gz
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See also kfp · kfp-pipeline-spec · kubeflow · kfp-kubernetes · argo-workflows · google-cloud-pipeline-components · valohai-papi · hera · hera-workflows · koheesio