| Congrats as well! We've been loving it for making internal point-and-click tools + external project starters (ex: tutorials, solution engineering, ..). Today, if you and your users are coding-heavy for data flows (dataset -> pydata wrangling/ml/... -> ui), jupyter notebooks are #1, and if you're in bigco, maybe say databricks notebooks as #2. However, most operational users really want an interactive point-and-click dashboard UI. Tableau and friends don't make as much sense in the pydata world, mostly for simpler SQL-only flows, and the existing python dashboarding tools (voila, panels, plotly, ...) have been too much work, esp. when sharing. I've been liking Streamlit as it's pretty opinionated + prestyled (less work!), simple interaction model (accessible!), etc. It clearly can be better, but is already so much more accessible than our experiences with other tools here. As some examples: * We've been building https://github.com/graphistry/graph-app-kit for people building mini graph apps (one-click self-hosted launch via docker + st dashboard + graphistry viz + optional graph db connectors + optional graph compute tools). * We're releasing 2-3 more integration + tutorial sets this month, where they're both notebook modes + dashboard modes. * We just ran a hackathon for the same w/ the TigerGraph team: https://tigergraph-web-app-hack.devpost.com/ * projectdomino.org uses it internal for anti-misinfo dashboard tools. Our devs/data sci/some advanced osint researchers are fine w/ nb's, but everyone else needs dashboard UIs. I'm excited to see what 2021 + 2022 bring here, and esp. if they can keep increasing accessibility all the way to no-code! |