|Project Name||Stars||Downloads||Repos Using This||Packages Using This||Most Recent Commit||Total Releases||Latest Release||Open Issues||License||Language|
|Plotly.py||13,500||37||3 days ago||88||August 14, 2022||1,376||mit||Python|
|The interactive graphing library for Python :sparkles: This project now includes Plotly Express!|
|Kubeflow||12,589||2||2 days ago||112||April 13, 2021||449||apache-2.0||TypeScript|
|Machine Learning Toolkit for Kubernetes|
|Nuclio||4,851||3 days ago||65||April 25, 2021||110||apache-2.0||Go|
|High-Performance Serverless event and data processing platform|
|Polyaxon||3,317||4||11||a day ago||334||June 05, 2022||122||apache-2.0|
|MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle|
|Panel||2,796||18||94||a day ago||225||July 05, 2022||647||bsd-3-clause||Python|
|A high-level app and dashboarding solution for Python|
|Football_analytics||1,091||10 days ago||2||Jupyter Notebook|
|📊⚽ A collection of football analytics projects, data, and analysis by Edd Webster (@eddwebster), including a curated list of publicly available resources published by the football analytics community.|
|Dashboards||985||11||1||4 years ago||15||April 05, 2017||32||other||Jupyter Notebook|
|[RETIRED] See Voilà as a supported replacement|
|Datastream.io||761||3 years ago||21||apache-2.0||Python|
|An open-source framework for real-time anomaly detection using Python, ElasticSearch and Kibana|
|Bowtie||703||10||4 years ago||45||October 13, 2018||49||mit||Python|
|:bowtie: Create a dashboard with python!|
|Explainx||322||8 months ago||56||February 04, 2021||12||mit||Jupyter Notebook|
|Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ [email protected]|
A Dashboard publishing solution for Data Science teams to share results with decision makers.
Run a private on-premise or cloud-based JupyterHub with extensions to instantly publish apps and notebooks as user-friendly interactive dashboards to share with non-technical colleagues.
Currently supported frameworks:
This open source package allows data scientists to instantly and reliably publish interactive notebooks or other scripts as secure interactive web apps.
Source files can be pulled from a Git repo or from the user's Jupyter tree.
Any authorised JupyterHub user can view the dashboard, or choose to give permission only to named users.
All of this works through a new Dashboards menu item added to JupyterHub's header.
Data scientist creates a Jupyter Notebook as normal
Data scientist creates a new Dashboard to clone their Jupyter server
Other logged-in JupyterHub users see the dashboard in their list
Uses OAuth to gain access
Other user sees a safe user-friendly Voilà version of the original notebook
Or other app frameworks
Note that JupyterHub 2.x is not supported. You will need to install a version 1.x (e.g. 1.5).
You should be able to use any authenticator for users to login - for example, corporate Google email sign in, or LDAP.
Any JupyterHub distribution should be suitable, depending on configuration. See requirements.
Full Setup and Installation details are in the documentation.
Please see LICENSE for details.
Please do get in touch if you try out the package, or would like to but need some support. I would be very interested to find out how it can be used, and to work (without charge) to help you get it running. The project needs feedback in order to develop further!
Contact [email protected] with any comments or questions at all.
There is a Gitter room for general chat with other community members, e.g. for confguration and use case tips.