SEO: add 250 English-market city pages; auto-warm archives on deploy (#97)

The population-ranked global top-500 skewed to Asian megacities and missed
high-English-search-demand cities. gen_cities.py now tops up with the top ~250
cities from English-speaking countries (US/GB/CA/AU/NZ/IE/ZA) not already in the
global set, so US coverage goes 13->146, GB 2->42, CA 3->29, etc. (Seattle, Boston,
Manchester, Melbourne, Auckland, Dublin, ...). cities.json regenerated to 750.

Both deploy scripts now launch warm_cities.py automatically after the health check,
detached (dev: a systemd --user transient unit; prod: setsid/nohup), so the city
pages serve from cache without a manual step; idempotent, so only the first deploy
does the full warm. DEPLOY.md updated.

gen_cities.py

@@ -31,7 +31,37 @@ def slugify(*parts: str) -> str:
     return re.sub(r"-{2,}", "-", text)
 
 
-def build(n: int = 500) -> list[dict]:
+# Countries where English is the primary/official language of web search. Used to
+# top up the population-ranked global list (which skews to Asia) with the
+# high-search-demand English-market cities that would otherwise be missed.
+ENGLISH_CC = {"US", "GB", "CA", "AU", "NZ", "IE", "ZA"}
+
+
+def _to_city(e, seen_slugs: set[str]) -> dict | None:
+    name, admin1, country, cc = e[_NAME], e[_ADMIN1], e[_COUNTRY], e[_CC]
+    # Drop admin1 from the slug when it just repeats the city name
+    # (e.g. Tokyo/Tokyo, Singapore/Singapore) to avoid "tokyo-tokyo-jp".
+    admin_part = admin1 if admin1 and slugify(admin1) != slugify(name) else ""
+    base = slugify(name, admin_part, cc or "")
+    if not base:
+        return None
+    slug = base
+    i = 2
+    while slug in seen_slugs:      # disambiguate the rare collision
+        slug = f"{base}-{i}"
+        i += 1
+    seen_slugs.add(slug)
+    return {
+        "slug": slug, "name": name, "admin1": admin1,
+        "country": country, "country_code": cc,
+        "lat": round(e[_LAT], 5), "lon": round(e[_LON], 5),
+        "population": e[_POP],
+    }
+
+
+def build(n_global: int = 500, n_english: int = 250) -> list[dict]:
+    """Top n_global cities worldwide by population, then up to n_english more from
+    English-speaking countries that weren't already in that global set."""
     places._load()  # synchronous parse; fills places._data (entries are pop-desc)
     if not places._data:
         raise SystemExit("GeoNames index failed to load (see logs); cannot generate cities.")
@@ -40,41 +70,37 @@ def build(n: int = 500) -> list[dict]:
     out: list[dict] = []
     seen_slugs: set[str] = set()
     for e in entries:
-        if len(out) >= n:
+        if len(out) >= n_global:
             break
-        name, admin1, country, cc = e[_NAME], e[_ADMIN1], e[_COUNTRY], e[_CC]
+        c = _to_city(e, seen_slugs)
-        # Drop admin1 from the slug when it just repeats the city name
+        if c:
-        # (e.g. Tokyo/Tokyo, Singapore/Singapore) to avoid "tokyo-tokyo-jp".
+            out.append(c)
-        admin_part = admin1 if admin1 and slugify(admin1) != slugify(name) else ""
+
-        base = slugify(name, admin_part, cc or "")
+    # Identity of the cities already chosen, so the English top-up skips them.
-        if not base:
+    chosen = {(c["name"], c["admin1"], c["country_code"]) for c in out}
+    added = 0
+    for e in entries:
+        if added >= n_english:
+            break
+        if e[_CC] not in ENGLISH_CC:
             continue
-        slug = base
+        if (e[_NAME], e[_ADMIN1], e[_CC]) in chosen:
-        i = 2
+            continue
-        while slug in seen_slugs:      # disambiguate the rare collision
+        c = _to_city(e, seen_slugs)
-            slug = f"{base}-{i}"
+        if c:
-            i += 1
+            out.append(c)
-        seen_slugs.add(slug)
+            added += 1
-        out.append({
-            "slug": slug,
-            "name": name,
-            "admin1": admin1,
-            "country": country,
-            "country_code": cc,
-            "lat": round(e[_LAT], 5),
-            "lon": round(e[_LON], 5),
-            "population": e[_POP],
-        })
     return out
 
 
 def main() -> None:
-    n = int(sys.argv[1]) if len(sys.argv) > 1 else 500
+    n_global = int(sys.argv[1]) if len(sys.argv) > 1 else 500
-    cities = build(n)
+    n_english = int(sys.argv[2]) if len(sys.argv) > 2 else 250
+    cities = build(n_global, n_english)
     with open(OUT_PATH, "w", encoding="utf-8") as f:
         json.dump(cities, f, ensure_ascii=False, indent=0, separators=(",", ":"))
         f.write("\n")
-    print(f"wrote {len(cities)} cities -> {OUT_PATH}")
+    print(f"wrote {len(cities)} cities ({n_global} global + up to {n_english} English-market) -> {OUT_PATH}")
     print("sample:", ", ".join(c["slug"] for c in cities[:8]))