Dashboards#
A directory of QuantEcon’s live status dashboards — what each one tracks, where it lives, and how it stays fresh.
QuantEcon programs report status through small, self-updating dashboards: a collector computes facts from live GitHub state on a schedule, commits or regenerates a JSON data store, and a static site on GitHub Pages renders it. No credentials beyond GITHUB_TOKEN; every number is reproducible from public state.
Live dashboards#
Dashboard |
Tracks |
Refresh |
Source repo |
|---|---|---|---|
Coverage, per-lecture freshness, automation wiring, and review state for every language edition, grouped by English source series. Three pages: overview, rollout lifecycle, per-lecture sync detail. |
Nightly collector (03:17 UTC) |
||
Dataset hosting patterns across the Python-family lecture repos, and the migration of static data into the canonical data repository — per-dataset lifecycle with the PRs that moved it. |
On push, weekly, and manual dispatch; strict build fails on inconsistency |
The Execution Statistics page on this site complements these: it reports live build/execution health for each published lecture website.
Repos without a live site yet#
status-lectures — build/environment-configuration reporting for the lecture series (in-repo JSON store; Pages site not yet deployed).
QuantEcon/dashboard(private) — curated presentation hub for projects and programs; links out to the dashboards above rather than hosting them.
Conventions#
status-*pattern: data lives with its collection pipeline; each dashboard repo is self-contained (site + versioned data contract) so it can relocate cheaply if the org’s reporting strategy changes (meta#332, meta#321).Freshness badges: pages state when their data was collected — green within 7 days, orange past a week, red past two — so a stale dashboard announces itself instead of quietly misleading.
History: collectors append dated snapshots (
data/history/), so trend views come free once history accumulates.
When you add a dashboard, list it here.