argo-workflows-fvdnabee 3.6.1

Description:

argoworkflowsfvdnabee 3.6.1

Argo Workflows Client
Python client for Argo Workflows
Installation
pip install argo-workflows

Usage
If you're familiar with Kubernetes client, the Argo client follows the same behaviour.
from argo.workflows.client import V1alpha1Api
from argo.workflows.config import load_kube_config

load_kube_config() # loads local configuration from ~/.kube/config

And to list Workflows from a namespace (say argo):
v1alpha1 = V1alpha1Api()

wfs = v1alpha1.list_namespaced_workflows(namespace="argo")

To submit a Workflow, one would simply load it from a YAML* and submit it as such:
import requests
import yaml

namespace = "argo"

# hello-world example
resp = requests.get("https://raw.githubusercontent.com/argoproj/argo/master/examples/hello-world.yaml")
resp.raise_for_status()

manifest: dict = yaml.safe_load(resp.text)

# Submit the Workflow to the `argo` namespace
v1alpha1.create_namespaced_workflow(namespace, manifest)

* When working on a higher level of abstraction, check out the Argo Python DSL
Versioning
The client is generated from the Argo and Kubernetes OpenAPI specification.
We follow semantic versioning, the client starts at version 1.0 which matches Argo release 2.3.0 and continues onwards.
Compatibility matrix




Argo 2.3
Argo 2.4
Argo 2.5




client-python 1.0
✓
-
-


client-python 2.0
+
✓
-


client-python 3.0
+
+
✓



Key:

✓ Exactly the same features / API objects in both client-python and the Kubernetes
version.
+ client-python has features or api objects that may not be present in the
Kubernetes cluster, but everything they have in common will work.
- The Kubernetes cluster has features the client-python library can't use
(additional API objects, etc).

We try to be consistent with Argo as much as possible and hence we created special branches for user convenience --- for example argo/v2.4.0 is identical with Argo release v2.4.0.
These can be then installed directly from github:
pip install -e "git+git://github.com/CermakM/argo-client-python@argo/v2.4.0#egg=argo-workflows"


:warning: The compatibility for such cases is not guaranteed

Code generation
If you wish to generate code yourself, you can do so by running make generate with the ARGO_VERSION environment variable being set to the you want to generate the client for.
Before
in the Makefile:

make sure to select a compatible KUBERNETES_BRANCH according to Argo's Gopkg.toml
make sure to select a compatible version of kubernetes-client
update requirements.txt and Pipfile

For additional configuration check out the Makefile.