#!/usr/bin/env python3 """Build repo/coverage.html + repo/COVERAGE.md — "which US states actually publish WARN notices, and how deep does each archive go" (c341). WHY THIS PAGE EXISTS (read before changing it) ---------------------------------------------- Every competitor in this market advertises a state count. layoffdata.com says "50 states, 82,000+ notices"; we hold 59,806 across 48 jurisdictions. A buyer comparing the two reads our 48 as "incomplete" and stops there. c341 went to find the missing three and discovered they are not missing — THEY DO NOT EXIST: * Arkansas — no public WARN list published by the state agency. * New Hampshire — no posted list; notices are reported to be released only in response to a public-records request. * Wyoming — no public WARN list published by the state agency. (Searched 2026-09-13. Secondary sources report AR and WY treat these filings as confidential under state law. We did NOT independently read those statutes and this page must not claim we did — see HONESTY RAILS.) So the honest, checkable claim is not "48 states" but "every US jurisdiction that publishes a public WARN list — 48 of 48 — plus a named, sourced account of the three that publish none". That converts our weakest-looking number into the thing a data buyer actually wants: someone who has already done the survey. The second half of the page is the one no competitor publishes at all: WHERE OUR ARCHIVE IS SHALLOW. Our California rows start in 2014 and our Texas rows in 2019 because that is how far back those portals go, not because the layoffs did not happen. A buyer who finds that out after paying churns; a buyer who reads it first and buys anyway is a buyer who trusts the rest of the file. HONESTY RAILS - Every number is computed at build time from repo/data/coverage.json and repo/data/warn_notices.json. Nothing is typed by hand. - "Archive starts" is the earliest NOTICE DATE WE HOLD for that state. It is a fact about the source portal's depth and our scraping of it, never a claim about when the state began requiring notices. The page says so in words. - Undated rows are counted and shown, never silently dropped (c340 rule: a derived page that filters rows states its denominator AND the archive total). - No statutory citation appears on the page. We report what we could and could not find, dated, and ask readers who know better to open an issue. - No comparison claim about a competitor's coverage. We say what we hold. Ordering: runs AFTER gen_site.py in publish.sh (gen_site rewrites index.html and the sitemap; this appends to the sitemap and links itself from api.html). Usage (cwd = product/): python3 gen_coverage_page.py --selftest # offline, asserts the invariants python3 gen_coverage_page.py # write repo/coverage.html + COVERAGE.md """ import collections import html import json import os import re import sys HERE = os.path.dirname(os.path.abspath(__file__)) sys.path.insert(0, HERE) import dataviz # noqa: E402 import page_write # noqa: E402 import sources # noqa: E402 import tiers # noqa: E402 from gen_multistate import EXTRA_CSS, STATE_NAMES # noqa: E402 from gen_site import PAGES_URL, REPO_URL # noqa: E402 from gen_weekly import CSS # noqa: E402 OUT_ROOT = os.path.join(HERE, "repo") REPO = OUT_ROOT URL = PAGES_URL + "coverage.html" ISSUES = REPO_URL.rstrip("/") + "/issues" README_ANCHOR = "" HF_COVERAGE_DS = "https://huggingface.co/datasets/APProjects/which-us-states-publish-warn-act-layoff-notices-coverage" # Jurisdictions with no public WARN list we could find. Each entry carries the # date we looked and exactly what we found — never a legal conclusion. EXTRA_NAMES = {"AR": "Arkansas", "NH": "New Hampshire", "WY": "Wyoming"} def sname(st): """STATE_NAMES only covers the 48 jurisdictions we hold data for.""" return STATE_NAMES.get(st) or EXTRA_NAMES.get(st, st) NO_PUBLIC_LIST = [ ("AR", "Arkansas Division of Workforce Services", "https://dws.arkansas.gov/", "No public WARN notice list on the agency site. Secondary sources report " "that Arkansas treats WARN filings as confidential under its employment-" "security law; we have not read the statute ourselves."), ("NH", "New Hampshire Employment Security", "https://www.nhes.nh.gov/", "No posted list. Secondary sources report that New Hampshire releases WARN " "notices only in response to a public-records request, which is not a " "source a daily pipeline can read."), ("WY", "Wyoming Department of Workforce Services", "https://dws.wyo.gov/", "No public WARN notice list on the agency site. Secondary sources report " "that Wyoming treats WARN filings as confidential under state law; we have " "not read the statute ourselves."), ] SEARCHED_ON = "2026-09-13" # Territories: federal WARN reaches them, but none runs a public notice portal. TERRITORIES = "Puerto Rico, Guam and the US Virgin Islands" # ----------------------------------------------------------------- facts def facts(): """Everything the page says, computed from the published files.""" cov = json.load(open(os.path.join(REPO, "data", "coverage.json"))) rows = json.load(open(os.path.join(REPO, "data", "warn_notices.json"))) years = collections.defaultdict(list) undated = collections.Counter() for r in rows: st = r.get("state") or "" d = (r.get("notice_date") or "")[:10] if len(d) >= 4 and d[:4].isdigit(): years[st].append(d) else: undated[st] += 1 src = sources.load().get("states", {}) out = [] for st, meta in cov.get("states", {}).items(): ds = sorted(years.get(st, [])) out.append({ "st": st, "name": sname(st), "rows": int(meta.get("rows") or 0), "dated": len(ds), "undated": undated.get(st, 0), "first": ds[0][:4] if ds else "", "latest": meta.get("latest_notice_date") or "", "scraped": (meta.get("last_scraped") or "")[:10], "status": meta.get("status") or "", "agency": (src.get(st) or {}).get("agency", ""), "url": (src.get(st) or {}).get("url", ""), }) out.sort(key=lambda d: -d["rows"]) total = int(cov.get("total_rows") or 0) dated_total = sum(d["dated"] for d in out) first_year = min((d["first"] for d in out if d["first"]), default="") return { "cov": cov, "states": out, "total": total, "dated": dated_total, "undated": total - dated_total, "first_year": first_year, "generated_at": cov.get("generated_at", ""), "n_pub": len(out), "n_none": len(NO_PUBLIC_LIST), } def shallow(sts, cutoff=2015): """States whose archive starts late — the honest depth disclosure.""" out = [d for d in sts if d["first"] and int(d["first"]) >= cutoff] out.sort(key=lambda d: (-d["rows"])) return out # ----------------------------------------------------------------- html def build(): f = facts() sts = f["states"] title = ("WARN notice coverage by state — which US states publish layoff " "notices, and which do not") desc = (f"All {f['n_pub']} US jurisdictions that publish a public WARN Act " f"layoff-notice list, with {f['total']:,} notices, how far back each " f"archive goes, and the {f['n_none']} states that publish none.") kpis = dataviz.kpi_row([ (f"{f['n_pub']}", "jurisdictions published", "every US agency we can find that posts a public WARN list"), (f"{f['total']:,}", "notices held", f"{f['dated']:,} carry a usable notice date"), (f["first_year"] or "—", "earliest notice on record", "depth is set by each portal, not by us"), (f"{f['n_none']}", "states publish nothing", "Arkansas, New Hampshire, Wyoming"), ]) kpi_fig = dataviz.figure( kpis, "US WARN-notice coverage held by WARN Feed", source="state workforce-agency portals", asof=f["generated_at"][:10]) top = [d for d in sts if d["rows"] >= 800][:14] bars = dataviz.figure( dataviz.bar_chart([(d["name"], d["rows"]) for d in top], unit=" notices"), "Largest state archives we hold", source="WARN Feed archive", asof=f["generated_at"][:10]) trs = [] for d in sts: agency = (f'{html.escape(d["agency"])}' if d["url"] and d["agency"] else html.escape(d["agency"] or "—")) und = f'
{d["undated"]:,} undated' if d["undated"] else "" trs.append( f'{html.escape(d["name"])} {d["st"]}' f'{d["rows"]:,}{und}' f'{d["first"] or "—"}' f'{html.escape(d["latest"] or "—")}' f'{agency}') table = ("" "" "" + "".join(trs) + "
JurisdictionNoticesArchive startsLatest noticeSource
") none_rows = "".join( f'{html.escape(sname(st))} ' f'{st}' f'{html.escape(agency)}' f'{note}' for st, agency, url, note in NO_PUBLIC_LIST) sh = shallow(sts) sh_rows = "".join( f'{html.escape(d["name"])}' f'{d["first"]}{d["rows"]:,}' for d in sh) cta = tiers.cta_html( "Need these notices matched against your own list of employers, every " "morning, instead of downloading the file yourself?") ld = json.dumps({ "@context": "https://schema.org", "@type": "Dataset", "name": "US WARN Act layoff notices — coverage by state", "description": desc, "url": URL, "license": "https://creativecommons.org/licenses/by/4.0/", "isAccessibleForFree": True, "creator": {"@type": "Organization", "name": "WARN Feed"}, "spatialCoverage": {"@type": "Country", "name": "United States"}, "temporalCoverage": f"{f['first_year']}/..", "distribution": [{ "@type": "DataDownload", "encodingFormat": "text/csv", "contentUrl": PAGES_URL + "data/latest.csv", }, { "@type": "DataDownload", "encodingFormat": "application/json", "contentUrl": PAGES_URL + "data/warn_notices.json", }], }) page = f""" {html.escape(title)}

WARN Feed · coverage

Which US states publish WARN layoff notices — and which publish none

The federal WARN Act makes large employers notify the state before a mass layoff or plant closing. It does not make the state publish what it receives. So the honest coverage question is not “how many of the 50 states do you have?” — it is how many publish at all, and how far back each one goes.

We hold {f['total']:,} notices from all {f['n_pub']} US jurisdictions that publish a public WARN list, rebuilt every morning. {f['n_none']} states publish none, and they are named below with what we found when we looked. The whole file is free under CC BY 4.0.

{kpi_fig}

Download the latest notices (CSV)

Every jurisdiction we publish

“Archive starts” is the earliest notice date we hold for that state. It reflects how far back that agency's portal goes and how deeply we read it — it is not a claim about when the state started requiring notices. Rows with no usable date are counted separately and never dropped: {f['dated']:,} of {f['total']:,} notices carry a usable notice date, {f['undated']:,} do not. Generated {html.escape(f['generated_at'][:10])}.

{table} {bars}

The {f['n_none']} states you cannot get, and why

We searched for a public notice list from each of these agencies on {SEARCHED_ON} and found none. We are reporting what we could and could not find — not a legal conclusion. If you know of a public source for any of them, open an issue and it will be in the file the next morning.

{none_rows}
StateAgencyWhat we found

{TERRITORIES} are covered by federal WARN but run no public notice portal we could find, so they appear in no dataset, ours or anyone else's.

Where our archive is shallow — read this before you buy anything

Several large states publish only a recent window. Our California rows start in {next((d['first'] for d in sts if d['st'] == 'CA'), '—')} and our Texas rows in {next((d['first'] for d in sts if d['st'] == 'TX'), '—')} because that is how far back those portals reach, not because nothing happened before. Any dataset built from these portals has the same floor, whether or not it tells you. Ours tells you:

{sh_rows}
StateArchive starts Notices

Where a state's portal drops its own history, we keep what we already scraped: {f['cov'].get('archive_only_rows', 0):,} notices in our file no longer appear on the agency site at all. That is the part of this job that only gets done if somebody is reading every portal every day.

How to check any of this

Every number above is computed from the published files at build time, and you can recompute it yourself: coverage.json holds the per-state row counts, scrape times and freshness; this table is one CSV row per jurisdiction at warn_coverage_by_state.csv (also on Hugging Face); the free HTTP API serves the whole archive as JSON, NDJSON and per-state CSV with no key and no login. If a number here disagrees with the file, the file is right and it is a bug — tell us.

{cta}

WARN Feed · API · privacy & terms · contact · data CC BY 4.0

""" return page, f # ----------------------------------------------------------------- markdown twin def markdown(): f = facts() sts = f["states"] base = _served_base() lines = [ "# WARN notice coverage by state", "", "Which US jurisdictions publish a public WARN Act layoff-notice list, " "which publish none, and how far back each archive goes.", "", f"**{f['total']:,} notices · {f['n_pub']} publishing jurisdictions · " f"earliest {f['first_year']} · rebuilt daily · CC BY 4.0**", "", f"Full page with charts: <{base}/coverage.html> · " f"free API: <{base}/api.html>", "", f"This table as one CSV row per jurisdiction (51 rows, incl. the three " f"non-publishers): [warn_coverage_by_state.csv]({base}/data/warn_coverage_by_state.csv) · " f"[Hugging Face dataset]({HF_COVERAGE_DS})", "", "## States that publish no WARN list", "", f"Searched {SEARCHED_ON}; no public notice list found from these " "agencies. This reports what we found, not a legal conclusion. Know a " f"public source? [Open an issue]({ISSUES}).", "", "| State | Agency | What we found |", "| --- | --- | --- |", ] for st, agency, url, note in NO_PUBLIC_LIST: lines.append(f"| {sname(st)} | [{agency}]({url}) | " + re.sub(r"\s+", " ", note) + " |") lines += [ "", f"{TERRITORIES} are covered by federal WARN but run no public notice " "portal we could find.", "", "## Every jurisdiction we publish", "", "`Archive starts` is the earliest notice date **we hold** — a fact " "about the portal's depth and our reading of it, not about when the " f"state began requiring notices. {f['dated']:,} of {f['total']:,} " f"notices carry a usable notice date; {f['undated']:,} do not.", "", "| Jurisdiction | Notices | Archive starts | Latest notice | Source |", "| --- | ---: | ---: | ---: | --- |", ] for d in sts: src = f"[{d['agency']}]({d['url']})" if d["url"] and d["agency"] else (d["agency"] or "—") lines.append(f"| {d['name']} ({d['st']}) | {d['rows']:,} | " f"{d['first'] or '—'} | {d['latest'] or '—'} | {src} |") lines += [ "", "## Where the archive is shallow", "", "Large states that publish only a recent window. Any dataset built from " "these portals has the same floor, whether or not it says so.", "", "| State | Archive starts | Notices |", "| --- | ---: | ---: |", ] for d in shallow(sts): lines.append(f"| {d['name']} | {d['first']} | {d['rows']:,} |") lines += [ "", f"Where a portal drops its own history we keep what we already scraped: " f"{f['cov'].get('archive_only_rows', 0):,} notices in our file no longer " "appear on the agency site at all.", "", f"Generated {f['generated_at'][:10]} from the published files. " f"Recompute from [coverage.json]({base}/data/coverage.json).", "", ] return "\n".join(lines) def _served_base(): import repo_host_fix return repo_host_fix.NEW.rstrip("/") def inject_readme(path): line = (f"- [Coverage by state]({_served_base()}/coverage.html) — which " f"states publish a WARN list, which publish none, and how far back " f"each archive goes. {README_ANCHOR}") try: txt = open(path, encoding="utf-8").read() except FileNotFoundError: return False out = [ln for ln in txt.split("\n") if README_ANCHOR not in ln] for i, ln in enumerate(out): if "" in ln: out.insert(i + 1, line) break else: out.append(line) new = "\n".join(out) if new != txt: open(path, "w", encoding="utf-8").write(new) return True def link_from_api_page(): """api.html is the developer front door and has no byte budget problem (index.html does — see gen_api_page.write). Idempotent.""" p = os.path.join(OUT_ROOT, "api.html") if not os.path.exists(p): return False txt = open(p, encoding="utf-8").read() if 'href="coverage.html"' in txt: return False needle = '' link = 'coverage by state · ' if needle in txt: txt = txt.replace(needle, link + needle, 1) open(p, "w", encoding="utf-8").write(txt) print("coverage: linked from api.html") return True print("WARN coverage: no anchor found in api.html — page unlinked there") return False def write(): page, f = build() os.makedirs(OUT_ROOT, exist_ok=True) path = os.path.join(OUT_ROOT, "coverage.html") changed = page_write.write_page(path, page, site=OUT_ROOT) sm = os.path.join(OUT_ROOT, "sitemap.xml") keep = [] if os.path.exists(sm): keep = [u for u in re.findall(r"(.*?)", open(sm).read()) if u != URL] urls = keep + [URL] open(sm, "w").write( '\n' '\n' + "\n".join(f"{u}" for u in urls) + "\n\n") md = markdown() md_p = os.path.join(OUT_ROOT, "COVERAGE.md") if not os.path.exists(md_p) or open(md_p, encoding="utf-8").read() != md: open(md_p, "w", encoding="utf-8").write(md) print(f"coverage: wrote COVERAGE.md ({len(md):,} B)") inject_readme(os.path.join(OUT_ROOT, "README.md")) link_from_api_page() print(f"coverage: wrote coverage.html ({len(page):,} B, changed={changed}) — " f"{f['n_pub']} publishing jurisdictions, {f['n_none']} without a list, " f"{f['total']:,} notices; sitemap now {len(urls):,} urls") def selftest(): page, f = build() assert f["n_pub"] >= 45, f["n_pub"] assert f["total"] > 50000, f["total"] # the count-honesty rule (c340): denominator AND archive total together assert f"{f['dated']:,} of {f['total']:,} notices" in page # every publishing jurisdiction appears exactly once in the big table for d in f["states"]: assert f'>{html.escape(d["name"])}' in page, d["st"] # the three non-publishers are named, and none of them is in the data codes = {d["st"] for d in f["states"]} for st, agency, url, note in NO_PUBLIC_LIST: assert st not in codes, f"{st} has rows but is listed as non-publishing" assert sname(st) in page assert url in page # no statutory citation may appear (HONESTY RAILS) assert not re.search(r"§|Ark\. Code|Wyo\. Stat", page), "statute cited" # ship floor assert "@media" in page, "no responsive breakpoint" assert 'class="btn"' in page or "