---
id: argo-workflows
version: "6.7.18"
license: unclear
license_treatment: unclear
maintenance: active
---

# argo-workflows — Argo Workflows API

License: unclear · Maintenance: active · Downloads: 345.1K/mo

## What it is and what it does

argo-workflows is a Python client library for the Argo Workflows API, generated from OpenAPI specifications. It allows developers to programmatically interact with Argo Workflows, the container-native workflow orchestration engine for Kubernetes, without writing raw HTTP requests. The package depends only on urllib3 for HTTP communication and python-dateutil for timestamp handling, making it lightweight to integrate into existing Python applications.

This is primarily a generated API binding rather than a high-level abstraction layer. It exposes the full Argo Workflows API surface, so you interact with it by constructing API objects and calling methods that correspond to REST endpoints. It is useful when you need to submit, monitor, or manage workflows programmatically from Python code, or when building tools and dashboards that orchestrate Argo jobs on Kubernetes.

Use it for:

- Submit and monitor Argo Workflows from Python scripts or applications without shell commands.
- Build CI/CD pipelines that programmatically trigger and track container workflows on Kubernetes.
- Create dashboards or management tools that query and manage Argo workflow status and history.
- Integrate workflow orchestration into Python-based data processing or ML training pipelines.
- Automate workflow lifecycle operations (create, delete, retry) from Python applications.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides Python API bindings for Argo Workflows, enabling programmatic submission and management of container-native workflow jobs on Kubernetes clusters.

Yes, if you need to interact with Argo Workflows from Python code and have a Kubernetes cluster with Argo already running. The low install friction and active maintenance are positive signals. However, verify the license terms before use—the metadata shows the license as unclear, which is a blocker for some organizations. The package is API-binding code, so it requires familiarity with the Argo Workflows API itself.

## Install

pip install argo-workflows
uv add argo-workflows
poetry add argo-workflows

## Installing argo-workflows

Before you install: Low install friction with only two runtime dependencies (urllib3, python-dateutil). Actively maintained as of the latest release date.

License in practice: License status is unclear—no SPDX identifier or raw license text is available in the package metadata. Verify the actual license terms before use in proprietary or restricted contexts.

Quickstart:

pip install argo-workflows

import argo_workflows
# Use the client to interact with Argo Workflows API

Requires Kubernetes cluster with Argo Workflows server already deployed and accessible.

Verify before relying:

- Actual license type and terms—metadata shows 'unclear' treatment with no SPDX or raw license field populated.
- Whether this package is auto-generated from OpenAPI spec and how that affects maintenance or API stability.
- Specific Python version support beyond the minimum requirement of >=3.6.

## Package facts

- License: not declared (unclear)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 345.1K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

argo workflows python client, kubernetes workflow orchestration api, container job scheduling python, argo workflows sdk, kubernetes parallel job management, workflow automation kubernetes, argo api bindings, kubernetes, workflow-orchestration, openapi-generated

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