The Board is a self-contained Artifact, so its county data is INLINED
(const D / const CDETAIL) — the standalone county_*.json companions are not
read by it. build_viz.py was only writing those companions, so the rendered
Board kept showing the pre-crosswalk state (67 counties). Now build_viz.py
injects the fresh data straight into board.html's three marked const lines,
and the header stats read from an injected TOTALS object instead of being
hardcoded (so they can't go stale — the original 11,285 drift).
- scripts/build_viz.py — inject_board(): rewrite const D / CDETAIL / TOTALS
in board.html; load candidates + acs_cd for the totals
- viz/board.html — header driven by TOTALS; inlined data refreshed
(county drill-downs 67 → 1049 counties; e.g. Fulton GA now shows all 7
metro mayors)
Deterministic: board.html is byte-identical on rerun. Verified live —
header 13,329/2,494/3,131/363, Fulton/Bastrop drill-downs render nested
municipals.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
build_viz.py was resolving officials to counties without the place→county
crosswalk, so only FL's 67 counties had rosters. Factor the resolver out of
build.py into a shared build.place_resolver() and use it in both, so the
Board and the tree agree by construction.
- scripts/build.py — extract place_resolver(); main() now calls it (tree
output byte-identical, refactor is behavior-preserving)
- scripts/build_viz.py — resolve via the shared resolver
- viz/county_data.json, viz/county_detail.json — regenerated
County drill-downs: 67 → 1049 counties with rosters; officials mapped
5184/5226 (42 county-unresolvable, tree-only). Deterministic.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Pull Atlas's place→county crosswalk (Census TIGER 2024 places × county
geometries, 32,041 places) into the build as a committed raw input, and
use it to resolve municipal officeholders whose county was unknown.
- data/place_county_crosswalk.jsonl — new raw input (place_geoid → county_geoid)
- build.py — place-name+state → county_geoid → ACS county slug as a fallback
in county_slug(); city_slug() generalized to non-FL bare place labels
- data/sources/sources.yaml — provenance entry for the crosswalk
_unresolved municipals: 1919 → 58. The remainder are genuine: CT planning
regions (post-county), county-level rows mislabeled municipal upstream,
consolidated city-counties (null label), Wikidata-QID placeholder names,
and ambiguous same-name places — left unresolved rather than guessed.
Join key is county_geoid (5-digit FIPS); the directory slug is taken from
the ACS county node so municipals nest under the exact existing county dir.
Deterministic (byte-identical rebuild); validate.py passes 19,721 records.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Re-exported directly from Postgres (10.0.0.116), not Atlas's introspection,
which under-reported the roster (its v3 export had 11,473, missing the
restored Florida League of Cities municipal set). Live DB current tenures:
state 7,561 · municipal 4,009 · county 1,217 · federal 542.
- build.py now reads officeholders-v3.jsonl (was v2); dataset vintage 2026-07-04
- fixed one corrupt start_date at source-export (21021-12-03 -> 2021-12-03,
Lorraine Borowski, Mayor of Decorah IA)
- scripts/build_viz.py: committed, deterministic generator for the Board's
county_data.json / county_detail.json (previously built ad-hoc)
- generate_changelog.py: ignore files whose only change is the vintage stamp,
so the diff reflects government change, not re-export bookkeeping
Person files 11,285 -> 13,329. Non-FL municipal officials (1,903) are in the
tree but not yet county-mappable (place->county crosswalk still NULL).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The diff is the product — now literally. generate_changelog.py reads a
git diff of the entity tree between any two refs and says, in plain
language, what changed in the government: entities added / modified /
removed, grouped by type and by jurisdiction, dated from the commit.
CHANGELOG.md is seeded from the real history so far:
- initial load: +11,285 people across 51 states
- institutional gap: +233 bodies, ~532 people enriched
- elections + demographics: +2,494 candidates, +3,494 jurisdictions
(TX +541, FL +396, CA +341 ...)
On an initial load every entity is an addition; on a re-sync of the same
source, only real government changes will surface — which is the whole
point. When nothing changed, it says so.
make changelog [BASE=.. HEAD=..]. No third-party deps.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
The README claimed 'validated by JSON Schema' — now it is true.
/schemas holds a JSON Schema for each entity type (Person, Body,
Candidate, Jurisdiction): a stricter profile over OKF's permissive
base, tolerating unknown keys by design.
scripts/validate.py checks all 17,506 files with no third-party deps
(hand-rolled frontmatter parser + minimal schema engine):
1. OKF conformance — every file has frontmatter with a non-empty type
2. Schema conformance — required fields, property types, enums
3. Link integrity — internal /-rooted links resolve
Non-zero exit on failure, so it is a CI gate. Verified with a negative
test: it catches bad enums and dead links. All 17,506 files pass today.
Makefile ties it together: make build / validate / check.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Two new entity types, built deterministically from the raw exports:
Candidate (2,494) — 2026 federal candidates as files under
us/states/<st>/candidates/, with office,
district, party, incumbent/challenger stance,
campaign committee, FEC id.
Jurisdiction (3,494) — demographic nodes carrying ACS 2023 data:
3,131 counties (deduped from 3,231 mixed-format
fips keys) + 363 congressional districts.
This completes the county skeleton nationwide: every US county is now a
browsable node with population, income, poverty, race, education and
housing — even where no officeholders are mapped yet. In Florida the
county index.md merges into the existing dir and reports its officeholder
count alongside demographics (St. Lucie: 33 officeholders + ACS profile).
build.py now reads seven raw inputs in one deterministic pass
(byte-identical on rerun). The mirror now answers: who holds power, who
runs this institution, who is running, and what each place is made of.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
The seat data answered 'who represents this place?' but not 'who runs
this institution?' — the Speaker of the House existed only as the rep
for LA-4. This adds the missing axis of institutional power.
New Body entities (233): the U.S. House, U.S. Senate, Executive Office,
49 committees, 181 subcommittees — each with its leadership.
Federal people (532/542) enriched with bioguide IDs, leadership roles,
and committee seats, reconciled from congress-legislators by name.
Mike Johnson is now Speaker of the House, not just LA-4.
Sources ingested directly into the repo (repo-canonical): Atlas
supplied bodies/leadership/committee_memberships via congress-legislators,
committed raw in data/. build.py supersedes convert_officeholders.py and
reads all four inputs in one deterministic pass (byte-identical on rerun).
The 10 unenriched federal records are a finding, not a bug: vacancies,
the President, and ~5 seats where Atlas's roster disagrees with the
authoritative current roster — model-vs-reality discrepancies to surface.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
One record, one file. The jurisdiction tree is now real:
us/people/ 542 federal
us/states/<xx>/people/ 7,561 state
us/states/fl/counties/<c>/people/ 1,058 county
.../municipalities/<m>/people/ 2,124 municipal (67 FL counties)
Each file is OKF markdown + YAML frontmatter: fixed key order,
field-level source provenance, Atlas UUIDs for round-tripping,
deterministic paths and slugs. Converter passes the determinism
test: two runs, byte-identical tree.
Generated by scripts/convert_officeholders.py from
data/officeholders-v2.jsonl (unchanged).
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Fabio