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https://github.com/ploomber/soopervisor

☁️ Export Ploomber pipelines to Kubernetes (Argo), Airflow, AWS Batch, SLURM, and Kubeflow.
https://github.com/ploomber/soopervisor

airflow argo argo-workflows aws data-science kubeflow kubeflow-pipelines kubernetes machine-learning slurm workflow

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☁️ Export Ploomber pipelines to Kubernetes (Argo), Airflow, AWS Batch, SLURM, and Kubeflow.

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README

        

Soopervisor
-----------

.. image:: https://github.com/ploomber/soopervisor/workflows/CI/badge.svg
:target: https://github.com/ploomber/soopervisor/workflows/CI/badge.svg
:alt: CI badge

.. image:: https://github.com/ploomber/soopervisor/workflows/CI%20macOS/badge.svg
:target: https://github.com/ploomber/soopervisor/workflows/CI%20macOS/badge.svg
:alt: CI macOS badge

.. image:: https://github.com/ploomber/soopervisor/workflows/CI%20Windows/badge.svg
:target: https://github.com/ploomber/soopervisor/workflows/CI%20Windows/badge.svg
:alt: CI Windows badge

.. image:: https://img.shields.io/badge/code%20style-black-000000.svg
:target: https://github.com/psf/black

*Tip: Deploy AI apps for free on* `Ploomber Cloud! `_

Soopervisor runs `Ploomber `_ pipelines
for batch processing (large-scale training or batch serving) or online
inference.

.. code-block:: sh

pip install soopervisor

Check out the `documentation `_ to learn more.

*Compatible with Python 3.7 and higher.*

Supported platforms
===================

* Batch serving and large-scale training:

* `Airflow `_
* `Argo/Kubernetes `_
* `AWS Batch `_
* `Kubeflow `_
* `SLURM `_

* Online inference:

* `AWS Lambda `_

From notebook to a production pipeline
======================================

We also have `an example `_ that shows how to use our ecosystem of tools to
go **from a monolithic notebook to a pipeline deployed in Kubernetes.**

Usage
=====

Say that you want to train multiple models in a Kubernetes
cluster, you may create a new target environment to execute your pipeline
using Argo Workflows:

.. code-block:: sh

soopervisor add training --backend argo-workflows

After filling in some basic configuration settings, export the pipeline with:

.. code-block:: sh

soopervisor export training

Depending on the selected backend (Argo, Airflow, AWS Batch, or AWS Lambda),
configuration details will change, but the API remains the same:
``soopervisor add``, then ``soopervisor export``.

About Ploomber
==============

Ploomber is a big community of data enthusiasts pushing the boundaries of Data Science and Machine Learning tooling.

Whatever your skillset is, you can contribute to our mission. So whether you're a beginner or an experienced professional, you're welcome to join us on this journey!

`Click here to know how you can contribute to Ploomber. `_