feat(places): registry of towns and authorities

Two namespaces because 67 town names collide with an authority name and
neither set contains the other — postal towns cross authority boundaries, so
Bedford the town holds 104 schools against the authority's 86.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015mWQnpye9F299NVRCCSRvj

backend/places.py

@@ -0,0 +1,92 @@
+"""The place registry: what places the site publishes, and what is in each.
+
+One module owns this question. The pages, the sitemap and the internal-link
+modules all read from here, so the threshold and the collision rules exist in
+exactly one place and are testable without a browser or a database.
+
+Two namespaces, never one. 67 viable town names collide with a local
+authority name, and the authority is the larger set in only 43 of them —
+postal towns cross authority boundaries, so neither can absorb the other.
+Keys are "<kind>:<slug>" so the collision cannot reappear in the dict.
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+
+# Five schools with publishable data. Below this a place has nothing to say
+# that a list of schools does not, and publishing it is index bloat.
+MIN_SCHOOLS = 5
+
+
+@dataclass(frozen=True)
+class Place:
+    kind: str                       # "town" | "locality" | "authority" | "outcode"
+    slug: str
+    name: str
+    urns: tuple[int, ...]
+    parent_authority: str | None    # authority NAME, for the 301 target
+
+    @property
+    def key(self) -> str:
+        return f"{self.kind}:{self.slug}"
+
+
+def _publishable_urns(df) -> set[int]:
+    """URNs with something a page could state, deduplicated across years."""
+    from backend.app import _PUBLISHABLE_FIELDS
+
+    cols = [c for c in _PUBLISHABLE_FIELDS if c in df.columns]
+    if not cols:
+        return set()
+    return set(df.loc[df[cols].notna().any(axis=1), "urn"].astype(int))
+
+
+def _parent_authority(group) -> str | None:
+    """The most common authority in a group — the useful 301 target.
+
+    A town spanning several authorities has no single parent, so the mode is
+    the honest answer rather than an arbitrary first row.
+    """
+    if "local_authority" not in group.columns:
+        return None
+    top = group["local_authority"].dropna()
+    return str(top.mode().iloc[0]) if not top.empty else None
+
+
+def _group(df, column: str, kind: str, publishable: set[int]) -> dict[str, Place]:
+    """One Place per distinct value of `column` that clears the threshold."""
+    from backend.app import _slugify
+
+    if column not in df.columns:
+        return {}
+
+    out: dict[str, Place] = {}
+    for name, group in df.groupby(column, dropna=True):
+        name = str(name).strip()
+        if not name:
+            continue
+        urns = tuple(sorted({int(u) for u in group["urn"]} & publishable))
+        if len(urns) < MIN_SCHOOLS:
+            continue
+        slug = _slugify(name)
+        if not slug:
+            continue
+        place = Place(
+            kind=kind, slug=slug, name=name, urns=urns,
+            parent_authority=_parent_authority(group) if kind == "town" else None,
+        )
+        out[place.key] = place
+    return out
+
+
+def build_place_registry(df) -> dict[str, Place]:
+    """Every place the site publishes, keyed by "<kind>:<slug>"."""
+    if df.empty or "urn" not in df.columns:
+        return {}
+
+    publishable = _publishable_urns(df)
+    registry: dict[str, Place] = {}
+    registry.update(_group(df, "local_authority", "authority", publishable))
+    registry.update(_group(df, "town", "town", publishable))
+    return registry