Hello everyone👋, I am glad to announce the 0.2 release of Kedro Boot 🚀 • You want to run your pipeline from an external/standalone applications (Streamlit, Data & AI Platforms, ...), while injecting data ? Give your external apps these factories:

boot_project

&

boot_package

🏭 • You need to write a sort of a Meta pipeline (can be anything from a script to a web app) that consumes your kedro project resources (pipeline runs, config loader, ...) and live inside it ?

AbstractKedroBootApp

is the way to go 💫. Your implementation can be declared in kedro

settings.py

or directly in CLI :

kedro boot run --app <http://path.to|path.to>.your.KedroBootApp <kedro_run_args>

• You want to develop a production-ready REST API that serve your Kedro pipeline.

Kedro FastAPI Server

could help. It offer a declarative way of building REST APIs using FastAPI and Kedro. Checkout the <https://github.com/takikadiri/kedro-boot?tab=readme-ov-file#consuming-kedro-pipeline-through-rest-api%7CFastAPI <-> Kedro objects mapping>. You can also develop your fastapi app explicitely and use one of the two modes cited aboves to integrate it with your kedro project/package If you are intested, you can : • 📦 Download the package with

pip install kedro-boot

• G Visit Kedro Boot github repo, give feedback and ⭐ if you like it • 🧪 Try & Learn with Kedro Boot Examples and give feedback ! ✨ This enable using Kedro pipelines in a wide range of use cases, including model serving, data apps (streamlit, dash), statistical simulations, paralell processing of unstructured data, streaming, and more. It also streamline the deployment of your Kedro pipeline into various Data & AI Platforms 🎉. Takieddine & Yolan