#jupyter
Live, measured metrics for the hashtag #jupyter from the open social web. Every number carries a named source and the time it was fetched. Nothing is estimated.
Own #jupyter
This #name is available to claim. It becomes your portal on the open agent web: this very page, a keyword you rank for by an open public stake, and a verifiable identity for AI agents. Nobody else sells a page like this for every #name.
Day-by-day usage
measured · mastodon.online (Mastodon public tags API) · fetched 2026-10-19 04:14 UTC3 uses by 3 unique accounts across the window. Real per-day counts, not estimates. Newest bar is today so far.
Related hashtags
measured · mastodon.online (Mastodon public search API) · fetched 2026-10-19 04:14 UTCLive pulse
measured · mastodon.online (Mastodon tag timeline) · fetched 2026-10-19 04:14 UTCEverything below is measured over the latest 40 public posts (spanning ~2320 hours).
Posting hours (UTC) — busiest: 09:00
Languages: English (33) · French (2) · Russian (2) · German (2) · Catalan (1)
Avg boosts / post: 1
Top of the latest posts
Juno 4 in one minute: an entire Python project, a local Flask web server in the built-in browser, Jupyter notebooks, and a live REPL — running natively on an iPad, fully offline. AI assistance is strictly bring-your-own-key; your code never
Treballar amb notebooks de #jupyter és una marranada, però és útil per fer provatures en sistemes una mica complexos. Tenen tendència a camuflar l'estat d'execució, etc. Però tenen una cosa encara pitjor, que és el control de versions o ja
🎬️ Marimo as the successor to Jupyter Notebook – Mateusz Konat In this video, Mateusz talks about @marimo_io – successor to the popular Jupyter Notebook. If you're interested in the latest tools from the Python world, be sure to check out
What “jupyter” means
WikipediaProject Jupyter is a project to develop open-source software, open standards, and services for interactive computing across multiple programming languages.
“Project Jupyter” on Wikipedia (CC BY-SA) →#jupyter across platforms
every network with a public tag surfaceFollow #jupyter straight to each platform’s own tag page. Where a platform publishes open data we measure it above; the rest lock their numbers behind paid APIs, so we link rather than guess.
Every number above is measured from a named public API at the shown fetch time. Nothing is estimated or extrapolated. Platforms that lock their data behind paid APIs are not shown. Agents: the same numbers, as JSON, at /api/hashtags/jupyter