JupyterCon 2023

David Rouquet

I have a Phd in computer science and my research interests are around Natural Language Processing and Semantic Web.
Since 2015 we started Tétras Libre (https://tetras-libre.fr), an IT consulting, research and development firm, based in Grenoble (France), and structured by the Open Source principles. There I conduct data science, software and research projects.


Sessions

05-10
12:00
30min
Tétras Lab : an open source platform propulsing notebooks as Web applications
David Rouquet, David Beniamine

Tétras Lab is an open source platform built around Jupyter Lab. Its goal is to provide an easy to deploy infrastructure that allows fruitful interactions between stakeholders, data scientists and developers while working on decision support systems.

The platform is composed of a Docker stack with the following containers :

  • a Django application to manage users and permissions,
  • a Jupyter Lab instance to provide an integrated IDE,
  • a Voilà container to allow live kernels when accessing dashboards,
  • worker containers for housekeeping tasks, data management, etc.
  • as many database containers, of as many flavors as needed.

The results of notebooks can be rendered in a polished environement for the stakeholders with the following modalities :

  • precomputed notebooks with nbconvert,
  • live notebooks with Voilà that can use Dash or Panel technologies,
  • and we plan to add the support for pure Dash application deployment for use cases that need a better scalability.

The platform is used in production for several clients and in different contexts such as :

  • monthly updated dashboards for marketing evaluation based on open data and sales forecast,
  • hourly updated Web application using statistical models to triggers warnings about landslide and rockfall risks around mountain roads.

Although it was first developped for our internal needs, we believe that the platform can be of interest for organisations that need an easy to deploy environment, that can deliver production ready solutions, for data science and business intelligence projects.

The code and resources are publicly available under the GNU AGPLv3 licence : https://gitlab.com/tetras-lab

A public demo illustrating the capabilities of the Tétras Lab platorm will be deployed for demo and testing during the conference. Meanwhile, a demo of the application for landslide alertness is available : https://sigale.pinea.sage-ingenierie.com/dashboard/public/yrnhmikkticoepshxnmaibnrsslifkxljgbpzltdudlsneeazeanmwnbrtlcjizq.

Enterprise Jupyter Infrastructure
Louis Armand 1