Files
republic-os/scripts/build.py
T
Fabio 199d8b37d3 Municipals: nest 1,823 city officeholders under their real counties
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>
2026-07-04 20:23:57 -04:00

722 lines
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#!/usr/bin/env python3
"""Build the OKF entity tree from the raw source exports in data/.
Inputs (committed raw, one JSON object per line):
officeholders-v3.jsonl Atlas — person->seat records (13,329)
bodies.jsonl congress-legislators — institutions (233)
leadership.jsonl current federal leadership roles (28)
committee_memberships.jsonl person->committee edges (3,879)
place_county_crosswalk.jsonl Census place -> county (PostGIS join) (32,041)
Outputs (fully regenerated each run):
data/jurisdictions/** Person files (federal ones enriched with
bioguide, leadership, committee seats)
data/jurisdictions/us/bodies/** Body files (chambers, committees,
subcommittees) with their leadership
Deterministic by construction: sorted iteration, fixed key order, one full
rebuild per run. Two consecutive runs produce a byte-identical tree.
"""
import json
import re
import shutil
import unicodedata
from pathlib import Path
REPO = Path(__file__).resolve().parent.parent
DATA = REPO / "data"
OUT = DATA / "jurisdictions"
BODIES_OUT = OUT / "us" / "bodies"
DATASET_DATE = "2026-07-04" # officeholders v3 export date
CONGRESS_DATE = "2026-07-03" # congress-legislators ingest date
# --------------------------------------------------------------------------- #
# helpers
# --------------------------------------------------------------------------- #
def slugify(text):
text = unicodedata.normalize("NFKD", text).encode("ascii", "ignore").decode()
text = re.sub(r"[^a-z0-9]+", "-", text.lower()).strip("-")
return re.sub(r"-{2,}", "-", text) or "unnamed"
def yval(v):
if isinstance(v, bool):
return "true" if v else "false"
if isinstance(v, (int, float)):
return str(v)
return json.dumps(v, ensure_ascii=False)
def norm_name(n):
"""Normalize a person name for cross-source reconciliation."""
n = re.sub(r'["\'][^"\']*["\']', "", n) # quoted nickname
n = re.sub(r",?\s+(Jr|Sr|II|III|IV)\.?(?=\s|$)", "", n) # suffix (any pos)
return re.sub(r"\s+", " ", n).strip().lower()
def norm_county(name):
return re.sub(r"\bSaint\b", "St", name)
def norm_place(s):
"""Normalize a Census place name for crosswalk lookup (bare, ascii, alnum)."""
s = unicodedata.normalize("NFKD", s or "").encode("ascii", "ignore").decode()
return re.sub(r"[^a-z0-9]+", " ", s.lower()).strip()
def acs_cslug(row):
"""County directory slug derived from an ACS county row (the authority for
county node names — municipals must nest under the same slug)."""
base = re.sub(r",\s*[A-Z]{2}$", "", row.get("county_name") or "")
return slugify(norm_county(re.sub(r"\s+County$", "", base)))
# committee_title (source) -> normalized role on the committee
ROLE_MAP = {
"member": "member", "Chair": "chair", "Chairman": "chair",
"Chairwoman": "chair", "Cochairman": "co-chair", "Vice Chair": "vice-chair",
"Vice Chairman": "vice-chair", "Vice Chairwoman": "vice-chair",
"Ranking Member": "ranking-member", "Ex Officio": "ex-officio",
}
LEADER_ROLES = {"chair", "co-chair", "vice-chair", "ranking-member"}
# --------------------------------------------------------------------------- #
# body paths / ids
# --------------------------------------------------------------------------- #
INSTITUTIONS = {"house", "senate", "executive"}
def committee_codes(bodies):
return sorted((b["code"] for b in bodies if b["type"] == "committee"),
key=len, reverse=True)
def parent_code(sub_code, comm_codes):
for c in comm_codes:
if sub_code.startswith(c) and sub_code != c:
return c
return None
def body_id(code, bodies_by_code, comm_codes):
"""Stable path-based id (relative to data/jurisdictions) for a body."""
b = bodies_by_code[code]
if b["type"] in INSTITUTIONS:
return f"us/bodies/{slugify(b['name'])}"
if b["type"] == "committee":
return f"us/bodies/{b['chamber']}/committees/{slugify(short_name(b))}"
parent = parent_code(code, comm_codes)
pb = bodies_by_code[parent]
return (f"us/bodies/{pb['chamber']}/committees/{slugify(short_name(pb))}"
f"/subcommittees/{slugify(short_name(b))}")
def short_name(b):
"""Committee/subcommittee name minus redundant chamber/parent prefix."""
name = b["name"]
name = re.sub(r"^(House|Senate|Joint)\s+(Committee|Subcommittee)\s+on\s+",
"", name)
if " - " in name: # subcommittee: keep the tail
name = name.split(" - ", 1)[1]
return name
# --------------------------------------------------------------------------- #
# federal enrichment index (name -> bioguide, leadership, committee seats)
# --------------------------------------------------------------------------- #
def build_enrichment(leadership, memberships, bodies_by_code, comm_codes):
idx = {}
def slot(name):
return idx.setdefault(norm_name(name),
{"bioguide": None, "leadership": [], "committees": []})
for l in leadership:
s = slot(l["person_name"])
s["bioguide"] = l["bioguide"]
s["leadership"].append({
"role": l["role_title"], "body": l["body_code"],
"since": l.get("start_date"),
})
for m in memberships:
s = slot(m["person_name"])
s["bioguide"] = m["bioguide"]
s["committees"].append({
"code": m["body_code"], "name": m["committee_name"],
"role": ROLE_MAP.get(m["committee_title"], "member"),
"rank": m.get("rank"),
"id": body_id(m["body_code"], bodies_by_code, comm_codes),
})
for s in idx.values():
s["leadership"].sort(key=lambda r: (r["role"], r["body"]))
s["committees"].sort(key=lambda c: (c["id"]))
return idx
# --------------------------------------------------------------------------- #
# Person files
# --------------------------------------------------------------------------- #
def county_slug(rec, place_to_cslug=None):
label = norm_county(rec.get("jurisdiction_label") or "")
m = re.match(r"(.+?) County, FL$", label)
if m:
return slugify(m.group(1))
if rec["level"] == "municipal":
m = re.search(r"County:\s*([^;]+)", rec.get("description") or "")
if m:
return slugify(norm_county(m.group(1).strip()))
title = rec.get("title") or ""
m = re.search(r"\bof\s+(.+?)\s+County\b", title) or re.match(r"(.+?)\s+County\b", title)
if m:
return slugify(norm_county(m.group(1)))
# Census place -> county via the committed crosswalk (place_county_crosswalk).
# Only unique name matches whose county has an ACS node are resolved here;
# ambiguous names, label-less rows, and CT planning regions fall through.
if place_to_cslug and rec["level"] == "municipal":
jl = rec.get("jurisdiction_label") or ""
pm = re.match(r"(.+?),\s*[A-Z]{2}$", jl) # "Tampa, FL" -> "Tampa"
placename = pm.group(1) if pm else jl # "Elgin" -> "Elgin"
cslug = place_to_cslug.get((norm_place(placename), rec.get("state_abbr")))
if cslug:
return cslug
return "_unresolved"
def city_slug(rec):
jl = rec.get("jurisdiction_label") or ""
m = re.match(r"(.+?),\s*[A-Z]{2}$", jl) # "Elgin, TX" / "Naples, FL"
if m:
return slugify(m.group(1))
if jl: # bare "Elgin"
return slugify(jl)
m = re.match(r"Mayor of (.+)$", rec.get("title") or "")
if m:
return slugify(m.group(1))
return "_unresolved"
def person_dir(rec, place_to_cslug=None):
lvl, st = rec["level"], (rec.get("state_abbr") or "").lower()
if lvl == "federal":
return OUT / "us" / "people"
if lvl == "state":
return OUT / "us" / "states" / st / "people"
if lvl == "county":
return OUT / "us" / "states" / st / "counties" / county_slug(rec, place_to_cslug) / "people"
if lvl == "municipal":
return (OUT / "us" / "states" / st / "counties" / county_slug(rec, place_to_cslug)
/ "municipalities" / city_slug(rec) / "people")
return OUT / "_unresolved" / "people"
def display_name(rec):
return rec.get("full_name") or rec.get("title") or "Unknown"
def person_frontmatter(rec, enr):
lines = ["type: Person", f"title: {yval(display_name(rec))}"]
jl = rec.get("jurisdiction_label")
desc = rec.get("title") or ""
if jl and jl not in desc:
desc = f"{desc}{jl}" if desc else jl
if desc:
lines.append(f"description: {yval(desc)}")
if rec.get("title"):
lines.append(f"role: {yval(rec['title'])}")
if rec.get("party"):
lines.append(f"party: {yval(rec['party'])}")
lines.append(f"level: {yval(rec['level'])}")
if rec.get("branch"):
lines.append(f"branch: {yval(rec['branch'])}")
if rec.get("state_abbr"):
lines.append(f"state: {yval(rec['state_abbr'])}")
if rec.get("jurisdiction_type") == "district" and jl:
lines.append(f"district: {yval(jl)}")
if enr and enr["leadership"]:
lines.append("leadership:")
for r in enr["leadership"]:
lines.append(f" - role: {yval(r['role'])}")
lines.append(f" body: {yval(r['body'])}")
if r.get("since"):
lines.append(f" since: {yval(r['since'])}")
if enr and enr["committees"]:
lines.append("committees:")
for c in enr["committees"]:
lines.append(f" - name: {yval(c['name'])}")
lines.append(f" role: {yval(c['role'])}")
lines.append(f" body: {yval(c['id'])}")
contact = [(k, rec.get(k)) for k in ("email", "phone", "website") if rec.get(k)]
if contact:
lines.append("contact:")
for k, v in contact:
lines.append(f" {k}: {yval(v)}")
tenure = [(k2, rec.get(k1)) for k1, k2 in
(("start_date", "start"), ("end_date", "end"),
("is_current", "current"), ("tenure_notes", "notes"))
if rec.get(k1) is not None]
if tenure:
lines.append("tenure:")
for k, v in tenure:
lines.append(f" {k}: {yval(v)}")
election = [(k2, rec.get(k1)) for k1, k2 in
(("next_election_year", "next"), ("term_length", "term_length"),
("term_limit", "term_limit")) if rec.get(k1) is not None]
if election:
lines.append("election:")
for k, v in election:
lines.append(f" {k}: {yval(v)}")
lines.append("ids:")
for k1, k2 in (("person_id", "person"), ("office_id", "office"),
("tenure_id", "tenure"), ("jurisdiction_id", "jurisdiction")):
if rec.get(k1):
lines.append(f" {k2}: {yval(rec[k1])}")
if enr and enr["bioguide"]:
lines.append(f" bioguide: {yval(enr['bioguide'])}")
srcs = [(f, rec[k]) for f, k in (("office", "office_source"),
("tenure", "tenure_source"), ("jurisdiction", "jurisdiction_source"))
if rec.get(k)]
if enr and (enr["leadership"] or enr["committees"]):
srcs.append(("roles", "congress-legislators (unitedstates project)"))
if srcs:
lines.append("sources:")
for f, s in srcs:
lines.append(f" - field: {f}")
lines.append(f" source: {yval(s)}")
lines.append("confidence: official")
tags = ["officeholder", rec["level"]]
if rec.get("branch"):
tags.append(rec["branch"])
if rec.get("state_abbr"):
tags.append(rec["state_abbr"].lower())
lines.append("tags: [" + ", ".join(tags) + "]")
lines.append(f"timestamp: {yval(DATASET_DATE)}")
return lines
def person_body(rec, enr):
name = display_name(rec)
role = rec.get("title") or "officeholder"
jl = rec.get("jurisdiction_label")
where = f" ({jl})" if jl and jl not in role else ""
cur = "Current" if rec.get("is_current") else "Former"
out = [f"# {name}", "", f"{cur} {role}{where}.", ""]
if enr and enr["leadership"]:
out += ["## Leadership", ""]
for r in enr["leadership"]:
since = f" (since {r['since']})" if r.get("since") else ""
out.append(f"- {r['role']}{since}")
out.append("")
if enr and enr["committees"]:
out += ["## Committees", ""]
for c in enr["committees"]:
tag = "" if c["role"] == "member" else f" — **{c['role']}**"
out.append(f"- [{c['name']}](/{c['id']}.md){tag}")
out.append("")
out += ["## Sources", ""]
any_src = False
for f, k in (("office", "office_source"), ("tenure", "tenure_source"),
("jurisdiction", "jurisdiction_source")):
if rec.get(k):
out.append(f"- {f}: {rec[k]}")
any_src = True
if enr and (enr["leadership"] or enr["committees"]):
out.append("- roles: congress-legislators (unitedstates project)")
any_src = True
if not any_src:
out.append("- (no field-level source recorded)")
out += ["", f"Generated from the Atlas officeholders v3 export ({DATASET_DATE})."]
return out
# --------------------------------------------------------------------------- #
# Body files
# --------------------------------------------------------------------------- #
TYPE_LABEL = {"house": "Chamber", "senate": "Chamber", "executive": "Executive Office",
"committee": "Committee", "subcommittee": "Subcommittee"}
def body_file(b, bid, bodies_by_code, comm_codes, leaders_of, members_count):
lines = ["type: Body", f"title: {yval(b['name'])}",
f"classification: {yval(b['type'])}",
f"chamber: {yval(b['chamber'])}", f"code: {yval(b['code'])}"]
if b["type"] == "subcommittee":
pc = parent_code(b["code"], comm_codes)
lines.append(f"parent: {yval(body_id(pc, bodies_by_code, comm_codes))}")
lead = leaders_of.get(b["code"], [])
if lead:
lines.append("leadership:")
for person_name, role, pid in lead:
lines.append(f" - person: {yval(person_name)}")
lines.append(f" role: {yval(role)}")
lines.append("sources:")
lines.append(" - field: definition")
lines.append(" source: congress-legislators (unitedstates project)")
lines.append("confidence: official")
tags = ["body", b["type"], b["chamber"]]
lines.append("tags: [" + ", ".join(dict.fromkeys(tags)) + "]")
lines.append(f"timestamp: {yval(CONGRESS_DATE)}")
body = [f"# {b['name']}", "",
f"{TYPE_LABEL.get(b['type'], 'Body')} ({b['chamber']}).", ""]
if lead:
body += ["## Leadership", ""]
for person_name, role, pid in lead:
body.append(f"- {role}: {person_name}")
body.append("")
if members_count:
body += [f"{members_count} members "
"(see each member's file for their seat on this body).", ""]
body += ["## Source", "",
"- definition: congress-legislators (unitedstates project)"]
return "---\n" + "\n".join(lines) + "\n---\n\n" + "\n".join(body) + "\n"
# --------------------------------------------------------------------------- #
# Candidate files (FEC)
# --------------------------------------------------------------------------- #
STANCE = {"I": "incumbent", "C": "challenger", "O": "open-seat"}
CAND_STATUS = {"C": "statutory candidate", "N": "not yet a candidate",
"P": "prior candidate", "F": "future candidate"}
PARTY_FULL = {"REP": "Republican", "DEM": "Democratic", "IND": "Independent",
"LIB": "Libertarian", "GRE": "Green",
"DFL": "Democratic-Farmer-Labor"}
def candidate_name(raw):
"""'CARL, JERRY LEE, JR' -> 'Jerry Lee Carl Jr'."""
parts = [p.strip() for p in raw.split(",")]
last = parts[0] if parts else raw
first = parts[1] if len(parts) > 1 else ""
suffix = parts[2] if len(parts) > 2 else ""
return " ".join(x for x in (first, last, suffix) if x).title()
def candidate_office(rec):
return "U.S. Senate" if rec.get("office") == "S" else "U.S. House"
def candidate_seat(rec):
st = rec.get("state") or ""
if rec.get("office") == "H" and rec.get("district"):
return f"{st}-{rec['district']}"
return st
def candidate_frontmatter(rec, disp):
office, seat, yr = candidate_office(rec), candidate_seat(rec), rec.get("election_year")
lines = ["type: Candidate", f"title: {yval(disp)}",
f"description: {yval(f'{office} candidate, {seat} ({yr})')}",
f"office: {yval(office)}"]
if rec.get("state"):
lines.append(f"state: {yval(rec['state'])}")
if rec.get("office") == "H" and rec.get("district"):
lines.append(f"district: {yval(seat)}")
if rec.get("party"):
lines.append(f"party: {yval(rec['party'])}")
if rec.get("incumbent_challenge") in STANCE:
lines.append(f"stance: {yval(STANCE[rec['incumbent_challenge']])}")
if yr:
lines.append(f"election_year: {yr}")
if rec.get("candidate_status") in CAND_STATUS:
lines.append(f"status: {yval(CAND_STATUS[rec['candidate_status']])}")
if rec.get("committee_name"):
lines.append("committee:")
lines.append(f" name: {yval(rec['committee_name'])}")
if rec.get("committee_id"):
lines.append(f" id: {yval(rec['committee_id'])}")
lines.append("ids:")
lines.append(f" fec: {yval(rec['fec_id'])}")
lines.append("sources:")
lines.append(" - field: filing")
lines.append(" source: FEC (Federal Election Commission)")
lines.append("confidence: official")
tags = ["candidate", "federal",
"senate" if rec.get("office") == "S" else "house"]
if rec.get("state"):
tags.append(rec["state"].lower())
lines.append("tags: [" + ", ".join(tags) + "]")
lines.append(f"timestamp: {yval(CONGRESS_DATE)}")
return lines
def candidate_body(rec, disp):
office, seat = candidate_office(rec), candidate_seat(rec)
stance = STANCE.get(rec.get("incumbent_challenge"), "candidate")
party = PARTY_FULL.get(rec.get("party"), rec.get("party") or "")
out = [f"# {disp}", "",
f"{party} {stance} for {office} ({seat}), {rec.get('election_year')}.", ""]
if rec.get("committee_name"):
cid = f" ({rec['committee_id']})" if rec.get("committee_id") else ""
out += ["## Campaign Committee", "", f"- {rec['committee_name']}{cid}", ""]
out += ["## Source", "", "- filing: FEC (Federal Election Commission)", "",
"Federal candidate filing; not yet linked to an officeholder record."]
return out
# --------------------------------------------------------------------------- #
# Jurisdiction demographic nodes (ACS)
# --------------------------------------------------------------------------- #
def numify(v):
if v is None or v == "":
return None
if isinstance(v, (int, float)):
return v
try:
f = float(v)
return int(f) if "." not in str(v) and f == int(f) else round(f, 4)
except (ValueError, TypeError):
return v
def canonical_fips(fips):
return re.sub(r"\D", "", str(fips))[-5:]
DEMOG_LABELS = {
"population": "Population", "population_under_18": "Under 18",
"population_18_64": "1864", "population_65_plus": "65+",
"median_household_income": "Median household income",
"poverty_rate": "Poverty rate", "homeownership_rate": "Homeownership rate",
"unemployment_rate": "Unemployment rate", "median_home_value": "Median home value",
"gini_index": "Gini index", "vacancy_rate": "Vacancy rate",
"race_white": "White", "race_black": "Black", "race_asian": "Asian",
"race_native": "Native", "hispanic": "Hispanic/Latino",
"bachelors_plus": "Bachelor's or higher",
}
def normalize_demog(row):
def pick(*cols):
for c in cols:
if row.get(c) not in (None, ""):
return numify(row.get(c))
return None
d = {
"population": pick("total_population"),
"population_under_18": pick("population_under_18"),
"population_18_64": pick("population_18_64"),
"population_65_plus": pick("population_65_plus"),
"median_household_income": pick("median_household_income"),
"poverty_rate": pick("poverty_rate"),
"homeownership_rate": pick("homeownership_rate"),
"unemployment_rate": pick("unemployment_rate"),
"median_home_value": pick("median_home_value"),
"gini_index": pick("gini_index"),
"vacancy_rate": pick("vacancy_rate"),
"race_white": pick("race_white"), "race_black": pick("race_black"),
"race_asian": pick("race_asian"), "race_native": pick("race_native"),
"hispanic": pick("hispanic_latino", "hispanic"),
}
bp = pick("edu_bachelors_plus")
if bp is None:
bp = (pick("edu_bachelors") or 0) + (pick("edu_graduate") or 0) or None
d["bachelors_plus"] = bp
return {k: v for k, v in d.items() if v is not None}
def demog_yaml(demog):
lines = ["demographics:"]
for k, v in demog.items():
lines.append(f" {k}: {yval(v) if isinstance(v, str) else v}")
return lines
def demog_table(demog):
out = ["## Demographics (ACS 2023)", "", "| Measure | Value |", "| --- | --- |"]
for k, v in demog.items():
out.append(f"| {DEMOG_LABELS.get(k, k)} | {v} |")
return out + [""]
def jurisdiction_file(title, classification, extra_fm, demog, st, body_intro):
lines = ["type: Jurisdiction", f"title: {yval(title)}",
f"classification: {classification}"]
lines += extra_fm
if demog:
lines += demog_yaml(demog)
lines += ["sources:", " - field: demographics",
" source: Census ACS 2023", "confidence: official",
f"tags: [jurisdiction, {classification}, {st}]",
f"timestamp: {yval(CONGRESS_DATE)}"]
body = [f"# {title}", "", body_intro, ""]
if demog:
body += demog_table(demog)
body += ["## Source", "", "- demographics: Census ACS 2023"]
return "---\n" + "\n".join(lines) + "\n---\n\n" + "\n".join(body) + "\n"
# --------------------------------------------------------------------------- #
# main
# --------------------------------------------------------------------------- #
def load(name):
return [json.loads(l) for l in (DATA / name).open()]
def main():
officeholders = load("officeholders-v3.jsonl")
bodies = load("bodies.jsonl")
leadership = load("leadership.jsonl")
memberships = load("committee_memberships.jsonl")
candidates = load("fec_candidates.jsonl")
acs_county = load("acs_county.jsonl")
acs_cd = load("acs_cd.jsonl")
crosswalk = load("place_county_crosswalk.jsonl")
# place -> county resolver: (normalized place name, state) -> county dir slug.
# county_geoid is the stable key; the slug is taken from the ACS county node
# (the same source that names county dirs) so municipals nest correctly.
fips_to_cslug = {canonical_fips(r["county_fips"]): acs_cslug(r) for r in acs_county}
_place_geoids = {}
for x in crosswalk:
_place_geoids.setdefault(
(norm_place(x["place_name"]), x["state_code"]), set()).add(x["county_geoid"])
place_to_cslug = {}
for key, geos in _place_geoids.items():
if len(geos) == 1:
cf = canonical_fips(next(iter(geos)))
if cf in fips_to_cslug:
place_to_cslug[key] = fips_to_cslug[cf]
bodies_by_code = {b["code"]: b for b in bodies}
comm_codes = committee_codes(bodies)
enrichment = build_enrichment(leadership, memberships, bodies_by_code, comm_codes)
# reverse index: body code -> its leaders, and -> member count
leaders_of, members_count = {}, {}
name_to_pid = {norm_name(r.get("full_name") or ""): r.get("person_id")
for r in officeholders if r.get("full_name")}
for m in memberships:
members_count[m["body_code"]] = members_count.get(m["body_code"], 0) + 1
role = ROLE_MAP.get(m["committee_title"], "member")
if role in LEADER_ROLES:
pid = name_to_pid.get(norm_name(m["person_name"]))
leaders_of.setdefault(m["body_code"], []).append(
(m["person_name"], role, pid))
for v in leaders_of.values():
v.sort(key=lambda t: (t[1], t[0]))
matched = sum(1 for r in officeholders if r["level"] == "federal"
and norm_name(r.get("full_name") or "") in enrichment)
# ---- plan person paths (disambiguate deterministically) ----
planned = {}
for rec in sorted(officeholders, key=lambda r: r["person_id"]):
planned.setdefault((person_dir(rec, place_to_cslug), slugify(display_name(rec))), []).append(rec)
person_files = {}
for (d, base), group in planned.items():
by_person = {}
for rec in group:
slug = base if len(group) == 1 else f"{base}-{rec['person_id'][:8]}"
by_person.setdefault(slug, []).append(rec)
for slug, sub in by_person.items():
for rec in sub:
final = slug if len(sub) == 1 else f"{slug}-{rec['office_id'][:8]}"
p = d / f"{final}.md"
assert p not in person_files, f"collision {p}"
person_files[p] = rec
# ---- write ----
if OUT.exists():
shutil.rmtree(OUT)
for path, rec in sorted(person_files.items()):
enr = enrichment.get(norm_name(rec.get("full_name") or "")) \
if rec["level"] == "federal" else None
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text("---\n" + "\n".join(person_frontmatter(rec, enr))
+ "\n---\n\n" + "\n".join(person_body(rec, enr)) + "\n",
encoding="utf-8")
for b in sorted(bodies, key=lambda x: x["code"]):
bid = body_id(b["code"], bodies_by_code, comm_codes)
path = OUT / (bid + ".md")
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(body_file(b, bid, bodies_by_code, comm_codes,
leaders_of, members_count.get(b["code"], 0)),
encoding="utf-8")
# ---- candidates (FEC) ----
cand_plan = {}
for rec in sorted(candidates, key=lambda r: r["fec_id"]):
d = OUT / "us" / "states" / (rec.get("state") or "xx").lower() / "candidates"
cand_plan.setdefault((d, slugify(candidate_name(rec["candidate_name"]))), []).append(rec)
n_cand = 0
for (d, base), group in sorted(cand_plan.items(), key=lambda kv: str(kv[0][0]) + kv[0][1]):
for rec in group:
slug = base if len(group) == 1 else f"{base}-{rec['fec_id'][-4:].lower()}"
disp = candidate_name(rec["candidate_name"])
path = d / f"{slug}.md"
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text("---\n" + "\n".join(candidate_frontmatter(rec, disp))
+ "\n---\n\n" + "\n".join(candidate_body(rec, disp)) + "\n",
encoding="utf-8")
n_cand += 1
# ---- county jurisdictions (ACS, deduped by canonical fips) ----
oh_count = {}
for rec in officeholders:
if rec["level"] in ("county", "municipal"):
key = ((rec.get("state_abbr") or "").lower(), county_slug(rec, place_to_cslug))
oh_count[key] = oh_count.get(key, 0) + 1
seen_fips, n_county = set(), 0
for row in sorted(acs_county, key=lambda r: canonical_fips(r["county_fips"])):
cf = canonical_fips(row["county_fips"])
if cf in seen_fips:
continue
seen_fips.add(cf)
st = row.get("state_abbr")
if not st:
continue
base = re.sub(r",\s*[A-Z]{2}$", "", row.get("county_name") or "")
cslug = acs_cslug(row)
title = f"{base}, {st}"
demog = normalize_demog(row)
ohc = oh_count.get((st.lower(), cslug), 0)
intro = (f"County jurisdiction — {ohc} officeholders mapped."
if ohc else "County jurisdiction.")
extra = [f"fips: {yval(cf)}", f"state: {yval(st)}"]
path = OUT / "us" / "states" / st.lower() / "counties" / cslug / "index.md"
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(jurisdiction_file(title, "county", extra, demog,
st.lower(), intro), encoding="utf-8")
n_county += 1
# ---- congressional-district jurisdictions (ACS) ----
n_cd = 0
for row in sorted(acs_cd, key=lambda r: (r["state_abbr"], r["district"])):
st, dist = row["state_abbr"], row["district"]
title = f"{st}-{dist}"
demog = normalize_demog(row)
extra = [f"state: {yval(st)}", f"district: {yval(title)}"]
path = OUT / "us" / "states" / st.lower() / "districts" / f"{dist}.md"
path.parent.mkdir(parents=True, exist_ok=True)
path.write_text(jurisdiction_file(title, "congressional-district", extra,
demog, st.lower(),
f"Congressional district {title}."),
encoding="utf-8")
n_cd += 1
print(f"candidate files: {n_cand} county jurisdictions: {n_county} "
f"district jurisdictions: {n_cd}")
print(f"person files: {len(person_files)} "
f"(federal enriched: {matched}/{sum(1 for r in officeholders if r['level']=='federal')})")
print(f"body files: {len(bodies)} "
f"(chambers/exec {sum(1 for b in bodies if b['type'] in INSTITUTIONS)}, "
f"committees {sum(1 for b in bodies if b['type']=='committee')}, "
f"subcommittees {sum(1 for b in bodies if b['type']=='subcommittee')})")
if __name__ == "__main__":
main()