Gordon is a small, stock-stack FastAPI + Jinja + Plotly app that renders every chart, table, and download from the shipped data artifacts. The data layer is rebuilt deterministically from the pre-built source CSVs — no network calls, no random seeds.
pip install -r app/requirements.txt
uvicorn app.main:app --port 8080
# then open http://localhost:8080
Every chart artifact under app/data/charts/ is produced by one script from the
official BLS/BEA/Fed inputs:
python app/build_chart_data.py
The builder reads the pre-built source CSVs (CPI/PCE, employment, JOLTS, wage–price, productivity,
and the heterodox block) and the FRED job-openings-rate series, collapses the sparse master
joins to one row per period, and writes each chart as CSV + XLSX + Parquet plus a
chart_meta.json describing sources, units, and limits. The same script closes
three mechanical packaging gaps: it recomputes the CPI component-contribution decomposition
through the latest month, sources the Beveridge job-openings rate, and derives
service-providing employment as total-private minus goods-producing.
Charts are drawn client-side from /api/chart/<key>, a columnar JSON feed,
using the shared ArkPlotly standard (legend below, accent colorway, the top-right
"Download data (CSV)" button). Client-side transforms (e.g. reindex-to-100 on index series)
run in the browser, so the same artifact backs every view.
Download site reproduction bundle (.zip)
app source + data artifacts; runs offline.
This bundle reproduces the website and its data layer from the pre-built source CSVs. The upstream research code that fetches the raw BLS/BEA/Federal-Reserve series and constructs the derived series is being packaged as a separate, standalone reproduction bundle and will publish with a future release.