feat(places): London localities and postcode districts

The GIAS town field puts 1,819 London schools under the single value
'London', so it cannot answer 'schools in Battersea' — a query that appears in
the baseline. No single field can: parliamentary constituency gives Battersea
but not Canary Wharf, admin_ward gives Canary Wharf but not Battersea, and
neither gives Clapham or Shoreditch. So a locality is curated, defined by the
postcode districts it covers, which needs no new ingestion.

A locality may not shadow a published town: the registry raises rather than
silently costing a page that carries real demand. One below the threshold is
logged rather than raising, because a locality can legitimately be too small.

The pipeline seed mirrors the module, with a test guarding the drift — the
same arrangement gias_codes has, and for the same reason: the backend image
does not contain pipeline/.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015mWQnpye9F299NVRCCSRvj
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TudorandClaude Opus 5 committed 2026-08-21 18:11:56 +01:00
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"""Curated London localities, defined by the postcode districts they cover.
The GIAS `town` field puts 1,819 London schools under the single value
"London", so it cannot answer "schools in Battersea" — a query that appears in
the Search Console baseline. No single field can: parliamentary constituency
gives Battersea but not Canary Wharf; postcodes.io's admin_ward gives Canary
Wharf but not Battersea; neither gives Clapham or Shoreditch, which are postal
and colloquial rather than administrative.
So this is curated. Where a locality ends is a judgement, not a fact, and a
reviewable file is the honest place for a judgement. No new ingestion is
needed — the corpus already carries postcodes.
This is the canonical copy. `pipeline/transform/seeds/locality_outcodes.csv`
mirrors it for anyone querying the warehouse directly; the backend image does
not contain `pipeline/`, which is why the module rather than the seed is
canonical. Same arrangement as `backend/gias_codes.py`.
A locality whose outcodes hold fewer than MIN_SCHOOLS schools is not
published, so a typo produces no page rather than an empty one. Places that
fail that check are logged at startup, because a locality you meant to publish
quietly not appearing is the failure worth hearing about.
"""
# slug -> (display name, outcodes)
LOCALITY_OUTCODES: dict[str, tuple[str, tuple[str, ...]]] = {
"battersea": ("Battersea", ("SW11",)),
"canary-wharf": ("Canary Wharf", ("E14",)),
"clapham": ("Clapham", ("SW4",)),
"shoreditch": ("Shoreditch", ("EC2A", "E1")),
"peckham": ("Peckham", ("SE15",)),
"brixton": ("Brixton", ("SW2", "SW9")),
"hackney": ("Hackney", ("E5", "E8", "E9")),
"islington": ("Islington", ("N1", "N5", "N7")),
"camden-town": ("Camden Town", ("NW1",)),
"greenwich": ("Greenwich", ("SE10",)),
"wimbledon": ("Wimbledon", ("SW19",)),
"putney": ("Putney", ("SW15",)),
"fulham": ("Fulham", ("SW6",)),
"chiswick": ("Chiswick", ("W4",)),
"ealing": ("Ealing", ("W5", "W13")),
"richmond": ("Richmond", ("TW9", "TW10")),
"stratford": ("Stratford", ("E15",)),
"walthamstow": ("Walthamstow", ("E17",)),
"tooting": ("Tooting", ("SW17",)),
"dulwich": ("Dulwich", ("SE21", "SE22")),
}
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@@ -12,8 +12,12 @@ Keys are "<kind>:<slug>" so the collision cannot reappear in the dict.
from __future__ import annotations
import logging
import re
from dataclasses import dataclass
logger = logging.getLogger(__name__)
# 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
@@ -80,6 +84,71 @@ def _group(df, column: str, kind: str, publishable: set[int]) -> dict[str, Place
return out
# "SW11 2AA" -> "SW11". Two letters max, one or two digits, optional letter.
_OUTCODE_RE = re.compile(r"^([A-Z]{1,2}\d{1,2}[A-Z]?)\s")
def _outcode(postcode) -> str | None:
if not isinstance(postcode, str):
return None
m = _OUTCODE_RE.match(postcode.upper().strip())
return m.group(1) if m else None
def _outcode_places(df, publishable: set[int]) -> dict[str, Place]:
"""One Place per postcode district clearing the threshold.
These carry no phase variants: nobody searches "primary schools in SW11".
"""
if "postcode" not in df.columns:
return {}
working = df.assign(_oc=df["postcode"].map(_outcode))
working = working[working["_oc"].notna()]
out: dict[str, Place] = {}
for oc, group in working.groupby("_oc"):
urns = tuple(sorted({int(u) for u in group["urn"]} & publishable))
if len(urns) < MIN_SCHOOLS:
continue
place = Place(kind="outcode", slug=str(oc).lower(), name=str(oc),
urns=urns, parent_authority=_parent_authority(group))
out[place.key] = place
return out
def _locality_places(df, publishable: set[int],
town_slugs: set[str]) -> dict[str, Place]:
"""One Place per curated locality clearing the threshold."""
from backend.localities import LOCALITY_OUTCODES
if "postcode" not in df.columns:
return {}
working = df.assign(_oc=df["postcode"].map(_outcode))
out: dict[str, Place] = {}
for slug, (name, outcodes) in LOCALITY_OUTCODES.items():
if slug in town_slugs:
raise ValueError(
f"locality {slug!r} collides with a published town of the same "
"slug; publishing both would shadow the town silently"
)
group = working[working["_oc"].isin(outcodes)]
urns = tuple(sorted({int(u) for u in group["urn"]} & publishable))
if len(urns) < MIN_SCHOOLS:
# Not an error — a locality can legitimately be too small. Logged
# because one you meant to publish quietly vanishing is the
# failure worth hearing about.
logger.warning(
"locality %s (%s) has %d publishable schools, below the "
"threshold of %d - not published",
slug, ", ".join(outcodes), len(urns), MIN_SCHOOLS)
continue
place = Place(kind="locality", slug=slug, name=name, urns=urns,
parent_authority=_parent_authority(group))
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:
@@ -88,5 +157,11 @@ def build_place_registry(df) -> dict[str, Place]:
publishable = _publishable_urns(df)
registry: dict[str, Place] = {}
registry.update(_group(df, "local_authority", "authority", publishable))
registry.update(_group(df, "town", "town", publishable))
towns = _group(df, "town", "town", publishable)
registry.update(towns)
town_slugs = {p.slug for p in towns.values()}
registry.update(_locality_places(df, publishable, town_slugs))
registry.update(_outcode_places(df, publishable))
return registry
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@@ -84,3 +84,93 @@ def test_a_school_is_counted_once_even_with_several_years_of_rows():
rows += [{**r, "year": year} for r in _town(MIN_SCHOOLS, "Beccles", "Suffolk")]
reg = build_place_registry(_df(rows))
assert len(reg["town:beccles"].urns) == MIN_SCHOOLS
def test_locality_groups_schools_by_outcode(monkeypatch):
# The GIAS town field collapses 1,819 London schools into "London", so a
# locality is defined by its postcode districts instead.
from backend import localities
monkeypatch.setattr(localities, "LOCALITY_OUTCODES",
{"battersea": ("Battersea", ("SW11",))})
rows = _town(MIN_SCHOOLS, "London", "Wandsworth")
for r in rows:
r["postcode"] = "SW11 2AA"
reg = build_place_registry(_df(rows))
assert reg["locality:battersea"].name == "Battersea"
assert len(reg["locality:battersea"].urns) == MIN_SCHOOLS
def test_locality_below_the_threshold_is_not_published(monkeypatch):
from backend import localities
monkeypatch.setattr(localities, "LOCALITY_OUTCODES",
{"nowhere": ("Nowhere", ("ZZ99",))})
reg = build_place_registry(_df(_town(MIN_SCHOOLS, "London", "Wandsworth")))
assert "locality:nowhere" not in reg
def test_a_locality_may_not_shadow_a_viable_town(monkeypatch):
# Silently shadowing a town would lose a page carrying real demand.
from backend import localities
monkeypatch.setattr(localities, "LOCALITY_OUTCODES",
{"brentwood": ("Brentwood", ("CM13",))})
rows = _town(MIN_SCHOOLS, "Brentwood", "Essex")
for r in rows:
r["postcode"] = "CM13 1AA"
with pytest.raises(ValueError, match="brentwood"):
build_place_registry(_df(rows))
def test_outcode_places_are_built_from_postcodes():
rows = _town(MIN_SCHOOLS, "Brentwood", "Essex")
for r in rows:
r["postcode"] = "CM13 1AA"
reg = build_place_registry(_df(rows))
assert reg["outcode:cm13"].name == "CM13"
assert len(reg["outcode:cm13"].urns) == MIN_SCHOOLS
def test_malformed_postcodes_do_not_create_places():
rows = _town(MIN_SCHOOLS, "Brentwood", "Essex")
for r in rows:
r["postcode"] = "not a postcode"
reg = build_place_registry(_df(rows))
assert not any(k.startswith("outcode:") for k in reg)
def test_every_curated_locality_is_structurally_valid():
# Guards the hand-maintained file: real slug, real name, real outcodes.
import re
from backend.localities import LOCALITY_OUTCODES
assert LOCALITY_OUTCODES, "the curated locality list must not be empty"
for slug, (name, outcodes) in LOCALITY_OUTCODES.items():
assert re.fullmatch(r"[a-z0-9-]+", slug), slug
assert name.strip() == name and name, slug
assert outcodes, f"{slug} has no outcodes"
for oc in outcodes:
assert re.fullmatch(r"[A-Z]{1,2}\d{1,2}[A-Z]?", oc), (slug, oc)
def test_the_pipeline_seed_mirrors_the_canonical_module():
"""Two copies with no drift guard is worse than one copy.
backend/localities.py is canonical because the backend image does not
contain pipeline/. The seed exists so the warehouse can join on the same
definitions, and this is what stops the two diverging — the same
arrangement assert_gias_code_names_match_seed.sql gives gias_codes.
"""
import csv
from pathlib import Path
from backend.localities import LOCALITY_OUTCODES
seed_path = (Path(__file__).resolve().parents[2]
/ "pipeline/transform/seeds/locality_outcodes.csv")
assert seed_path.exists(), f"missing seed mirror at {seed_path}"
seed = {
row["locality_slug"]: (row["locality_name"],
tuple(row["outcodes"].split("|")))
for row in csv.DictReader(seed_path.open())
}
assert seed == LOCALITY_OUTCODES