hera

What it is and what it does

Hera is a Python SDK that bridges Python code and Argo Workflows, a Kubernetes-native workflow orchestration engine. Instead of writing YAML manifests, you define workflows as Python functions and DAGs, then submit them directly to an Argo server running on your cluster. The package handles the translation from Python to Argo's workflow format, letting you keep orchestration logic separate from business logic while retaining full access to Argo's capabilities like conditional execution, loops, and resource management.

The core workflow is simple: decorate Python functions with @script(), compose them into DAGs using Python operators (like >> for sequencing), and call w.create() to submit to your cluster. Hera depends on pydantic for data validation, requests for HTTP communication with the Argo server, and typing-extensions for type hints. It supports modern Python versions (3.10 through 3.14) and is in active development with optional extras for YAML export, a CLI tool, and async client support.

Use it for:

• Build multi-step data pipelines on Kubernetes where each step is a Python function, without writing YAML.
• Orchestrate machine learning training and inference workflows with dependency management and conditional branching.
• Create scheduled or event-driven job workflows that run containerized Python code across a cluster.
• Define complex DAGs with parallel execution paths and dynamic task generation using native Python syntax.
• Enable GitOps practices by generating Argo YAML from Python source code for version control and review.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Hera is a Python SDK that turns Python functions into Argo Workflows templates and submits them to Kubernetes clusters, enabling orchestration of containerized workloads without leaving Python.

Yes. Hera is actively maintained, has no known vulnerabilities, low install friction, and a permissive Apache 2.0 license. Install it if you need to orchestrate containerized workloads on Kubernetes and prefer writing Python over YAML. The main prerequisite is having an Argo Workflows server already deployed to a cluster; without that, the package alone is not useful.

Install

hera on PyPI

pip install hera

uv add hera

poetry add hera

Installing hera

Before you install

Low install friction with three lightweight runtime dependencies (pydantic, requests, typing-extensions). Active maintenance with a release within the last 57 days and an active repository.

License in practice

Apache 2.0 permissive license allows commercial and private use with minimal restrictions; you may use, modify, and distribute Hera freely provided you include the license notice.

Quickstart

pip install hera

from hera.workflows import DAG, Workflow, script

@script()
def echo(message: str):
    print(message)

with Workflow(generate_name="test-", entrypoint="diamond") as w:
    with DAG(name="diamond"):
        A = echo(name="A", arguments={"message": "A"})
        B = echo(name="B", arguments={"message": "B"})
        A >> B

w.create()

Requires an Argo Workflows server deployed to a Kubernetes cluster and network access to it; authentication typically via Bearer token or port forwarding to localhost:2746.

Verify before relying

• Whether optional dependencies (yaml, cli, async-client) are commonly needed for typical workflows.
• Performance characteristics when orchestrating large numbers of tasks or complex DAGs.
• Compatibility guarantees with specific Argo Workflows server versions.

Package facts

Evidence: hera-7.0.0-py3-none-any.whl

Tags

More Scientific/Engineering packages