Remove finder

This commit is contained in:
Andras Schmelczer 2026-04-04 22:59:28 +01:00
parent 55238f59aa
commit cd778dd088
26 changed files with 0 additions and 57826 deletions

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FROM python:3.12-slim
COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv
WORKDIR /app
COPY finder/pyproject.toml ./
RUN uv pip install --system -r pyproject.toml
RUN playwright install-deps chromium firefox
RUN playwright install chromium
RUN camoufox fetch \
&& python -c "from camoufox.pkgman import camoufox_path; p = camoufox_path(download_if_missing=False); print('Camoufox verified at', p)"
COPY finder/*.py ./
COPY property-data/arcgis_data.parquet /data/arcgis_data.parquet
CMD ["python3", "main.py"]

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FROM python:3.12-slim
COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv
WORKDIR /app
COPY pyproject.toml ./
RUN uv pip install --system -r pyproject.toml
RUN playwright install-deps firefox
RUN camoufox fetch \
&& python -c "from camoufox.pkgman import camoufox_path; p = camoufox_path(download_if_missing=False); print('Camoufox verified at', p)"
COPY *.py ./
COPY property-data/arcgis_data.parquet /data/arcgis_data.parquet
HEALTHCHECK --interval=30s --timeout=5s --retries=3 \
CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:1234/health')"
CMD ["python3", "main.py"]

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import os
from pathlib import Path
ARCGIS_PATH = os.environ.get("ARCGIS_PATH", "/data/arcgis_data.parquet")
DATA_DIR = Path("/app/data")
PAGE_SIZE = 24
DELAY_BETWEEN_PAGES = 0.3
DELAY_BETWEEN_OUTCODES = 0.5
MAX_RETRIES = 3
RETRY_BASE_DELAY = 2.0
GRID_CELL_SIZE = 0.01 # degrees for postcode spatial index
MAX_BEDROOMS = 20 # sanity cap — values above this are almost certainly parsing errors
# Rent sanity bounds (monthly). Rents outside this range are nulled out — they are
# almost always total-stay pricing (e.g. "Golf Open 2026" short lets), annual rents
# mislabelled as monthly, or data errors.
MIN_RENT_MONTHLY = 50 # below £50/month is implausible for any UK property
MAX_RENT_MONTHLY = 25_000 # above £25k/month covers ultra-prime London; higher is suspect
SEED = 42
CHECKPOINT_INTERVAL = int(os.environ.get("CHECKPOINT_INTERVAL", "900")) # seconds
# Schedule: hour of day (UTC) to auto-run scrape. Set to -1 to disable.
SCHEDULE_HOUR = int(os.environ.get("SCHEDULE_HOUR", "3"))
# Whether to run a scrape immediately on startup
RUN_ON_STARTUP = os.environ.get("RUN_ON_STARTUP", "").lower() in ("1", "true", "yes")
# Enable/disable individual sources
SCRAPE_RIGHTMOVE = os.environ.get("SCRAPE_RIGHTMOVE", "true").lower() in (
"1",
"true",
"yes",
)
SCRAPE_HOMECOUK = os.environ.get("SCRAPE_HOMECOUK", "true").lower() in (
"1",
"true",
"yes",
)
SCRAPE_OPENRENT = os.environ.get("SCRAPE_OPENRENT", "true").lower() in (
"1",
"true",
"yes",
)
SCRAPE_ZOOPLA = os.environ.get("SCRAPE_ZOOPLA", "true").lower() in (
"1",
"true",
"yes",
)
# URL to trigger server data reload after scrape (e.g. http://server:8001/api/reload)
RELOAD_URL = os.environ.get("RELOAD_URL", "")
TYPEAHEAD_URL = "https://los.rightmove.co.uk/typeahead"
SEARCH_URL = "https://www.rightmove.co.uk/api/property-search/listing/search"
RIGHTMOVE_BASE = "https://www.rightmove.co.uk"
# home.co.uk
HOMECOUK_BASE = "https://home.co.uk"
HOMECOUK_API_BASE = f"{HOMECOUK_BASE}/api"
HOMECOUK_PER_PAGE = 30 # max supported by the API
HOMECOUK_CONCURRENCY = int(os.environ.get("HOMECOUK_CONCURRENCY", "4"))
# OpenRent
OPENRENT_BASE = "https://www.openrent.co.uk"
# Zoopla
ZOOPLA_BASE = "https://www.zoopla.co.uk"
PROPERTY_TYPE_MAP = {
"Detached": "Detached",
"Semi-Detached": "Semi-Detached",
"Terraced": "Terraced",
"End of Terrace": "Terraced",
"Mid Terrace": "Terraced",
"Flat": "Flats/Maisonettes",
"Maisonette": "Flats/Maisonettes",
"Studio": "Flats/Maisonettes",
"Apartment": "Flats/Maisonettes",
"Penthouse": "Flats/Maisonettes",
"Ground Flat": "Flats/Maisonettes",
"Duplex": "Flats/Maisonettes",
"Detached Bungalow": "Detached",
"Semi-Detached Bungalow": "Semi-Detached",
"Town House": "Terraced",
"Link Detached": "Detached",
"Link Detached House": "Detached",
"Bungalow": "Other",
"Cottage": "Other",
"Park Home": "Other",
"Mobile Home": "Other",
"Caravan": "Other",
"Lodge": "Other",
"Land": "Other",
"Farm / Barn": "Other",
"Farm House": "Other",
"House": "Detached",
"House of Multiple Occupation": "Flats/Maisonettes",
"House Share": "Other",
"Not Specified": "Other",
"Chalet": "Other",
"Barn Conversion": "Other",
"Coach House": "Other",
"Character Property": "Other",
"Cluster House": "Other",
"Retirement Property": "Flats/Maisonettes",
"Parking": "Other",
"Plot": "Other",
"Garages": "Other",
"Mews": "Terraced",
"Property": "Other",
"Flat Share": "Other",
"Block of Apartments": "Flats/Maisonettes",
"Private Halls": "Flats/Maisonettes",
"Terraced Bungalow": "Terraced",
"Equestrian Facility": "Other",
"Ground Maisonette": "Flats/Maisonettes",
"Country House": "Detached",
"Village House": "Detached",
"Farm Land": "Other",
"House Boat": "Other",
"Barn": "Other",
"Serviced Apartments": "Flats/Maisonettes",
# Space-separated variants (from home.co.uk underscore/hyphen normalization)
"Semi Detached": "Semi-Detached",
"Semi Detached Bungalow": "Semi-Detached",
"End Of Terrace": "Terraced",
"End Terrace": "Terraced",
"Block Of Apartments": "Flats/Maisonettes",
"Farm / Barn": "Other",
# Lowercase variants (from home.co.uk / Rightmove APIs)
"house": "Detached",
"bungalow": "Other",
"townhouse": "Terraced",
"land": "Other",
"other": "Other",
"not-specified": "Other",
"retirement-property": "Flats/Maisonettes",
"equestrian-facility": "Other",
"flat": "Flats/Maisonettes",
"detached": "Detached",
"semi-detached": "Semi-Detached",
"terraced": "Terraced",
"maisonette": "Flats/Maisonettes",
"apartment": "Flats/Maisonettes",
"studio": "Flats/Maisonettes",
"penthouse": "Flats/Maisonettes",
"cottage": "Other",
"chalet": "Other",
"farm_house": "Detached",
"country house": "Detached",
"village house": "Detached",
}
CHANNELS = [
{"channel": "BUY", "transactionType": "BUY", "sortType": "2"},
{"channel": "RENT", "transactionType": "LETTING", "sortType": "6"},
]

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import json
import logging
import os
import random
import re
import time
from urllib.parse import unquote
import httpx
from curl_cffi.requests import Session
from curl_cffi.requests.errors import RequestsError
from constants import (
DELAY_BETWEEN_PAGES,
HOMECOUK_API_BASE,
HOMECOUK_BASE,
HOMECOUK_PER_PAGE,
MAX_BEDROOMS,
PROPERTY_TYPE_MAP,
RETRY_BASE_DELAY,
)
from metrics import (
flaresolverr_attempts_total,
homecouk_errors_total,
homecouk_properties_scraped,
homecouk_requests_total,
)
from spatial import PostcodeSpatialIndex
from transform import normalize_postcode, normalize_sub_type, validate_floor_area
log = logging.getLogger("homecouk")
class CookiesExpiredError(Exception):
"""Raised when home.co.uk returns 403, indicating cookies need refresh."""
# Channel mapping: internal name → URL path segment
HOMECOUK_CHANNELS = {
"BUY": "for-sale",
"RENT": "to-rent",
}
FLARESOLVERR_URL = os.environ.get("FLARESOLVERR_URL", "http://flaresolverr:8191")
def solve_cloudflare() -> tuple[dict[str, str], str] | None:
"""Use FlareSolverr to solve the Cloudflare challenge.
Returns (cookies_dict, user_agent) or None on failure."""
log.info("Solving Cloudflare challenge via FlareSolverr at %s", FLARESOLVERR_URL)
try:
with httpx.Client(timeout=120) as client:
resp = client.post(
f"{FLARESOLVERR_URL}/v1",
json={
"cmd": "request.get",
"url": f"{HOMECOUK_BASE}/for-sale/e1/",
"maxTimeout": 60000,
},
)
if resp.status_code != 200:
log.error("FlareSolverr returned HTTP %d", resp.status_code)
return None
data = resp.json()
if data.get("status") != "ok":
log.error("FlareSolverr error: %s", data.get("message", "unknown"))
return None
solution = data["solution"]
raw_cookies = solution.get("cookies", [])
user_agent = solution.get("userAgent", "")
# Pass through ALL cookies from FlareSolverr — different Cloudflare
# configurations set different cookies (cf_clearance only appears when
# a challenge is triggered; it's not needed if no challenge was detected)
cookies = {}
for c in raw_cookies:
name = c.get("name", "")
if name:
cookies[name] = c["value"]
if not cookies:
log.error("FlareSolverr solved but returned no cookies at all")
flaresolverr_attempts_total.labels(result="no_cookies").inc()
return None
log.info(
"Cloudflare solved — got %d cookies, UA: %s",
len(cookies),
user_agent[:60],
)
flaresolverr_attempts_total.labels(result="success").inc()
return cookies, user_agent
except (httpx.ConnectError, httpx.ReadTimeout) as e:
log.warning("FlareSolverr not available: %s", e)
flaresolverr_attempts_total.labels(result="unavailable").inc()
return None
except Exception as e:
log.error("FlareSolverr error: %s", e)
flaresolverr_attempts_total.labels(result="error").inc()
return None
def load_cookies() -> tuple[dict[str, str], str] | None:
"""Get home.co.uk cookies + user-agent.
Tries FlareSolverr first, then falls back to environment variables.
Returns (cookies_dict, user_agent) or None if not configured."""
# Try FlareSolverr first
result = solve_cloudflare()
if result:
return result
# Fall back to env vars
cf_clearance = os.environ.get("HOMECOUK_CF_CLEARANCE", "")
session = os.environ.get("HOMECOUK_SESSION", "")
if not cf_clearance or not session:
return None
user_agent = os.environ.get(
"HOMECOUK_USER_AGENT",
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) "
"AppleWebKit/537.36 (KHTML, like Gecko) "
"Chrome/145.0.0.0 Safari/537.36",
)
return {"cf_clearance": cf_clearance, "homecouk_session": session}, user_agent
def make_client(cookies: dict[str, str], user_agent: str) -> Session:
"""Create a curl_cffi Session configured for home.co.uk API calls.
Uses Chrome TLS impersonation so cf_clearance cookies (which are bound
to Chrome's JA3 fingerprint from FlareSolverr) remain valid."""
session = Session(impersonate="chrome")
session.headers.update(
{
"User-Agent": user_agent,
"Accept": "application/json, text/plain, */*",
"x-requested-with": "XMLHttpRequest",
}
)
# Laravel CSRF: the XSRF-TOKEN cookie value must also be sent as the
# X-XSRF-TOKEN request header (URL-decoded). Without this header, the
# server rejects every request with 419/403.
xsrf = cookies.get("XSRF-TOKEN")
if xsrf:
session.headers["X-XSRF-TOKEN"] = unquote(xsrf)
for name, value in cookies.items():
session.cookies.set(name, value, domain="home.co.uk")
return session
def _status_label(code: int) -> str:
if code >= 500:
return "5xx"
return str(code)
def fetch_page(
client: Session, url: str, params: dict, max_retries: int = 3
) -> dict | None:
"""GET JSON with retries on 429/5xx. Returns None on permanent failure.
403 means cookies expired raises CookiesExpiredError immediately."""
for attempt in range(max_retries):
try:
resp = client.get(url, params=params, timeout=30)
homecouk_requests_total.labels(status=_status_label(resp.status_code)).inc()
if resp.status_code == 200:
try:
return resp.json()
except json.JSONDecodeError:
homecouk_errors_total.labels(type="json_decode").inc()
log.error(
"Non-JSON response from %s (got %s)",
url,
resp.headers.get("content-type", "?"),
)
return None
if resp.status_code == 403:
raise CookiesExpiredError("HTTP 403 — cookies likely expired")
if resp.status_code in (429, 500, 502, 503, 504):
delay = RETRY_BASE_DELAY * (2**attempt) + random.uniform(0, 1)
log.warning(
"HTTP %d from %s, retry %d/%d in %.1fs",
resp.status_code,
url,
attempt + 1,
max_retries,
delay,
)
time.sleep(delay)
continue
log.error("HTTP %d from %s (non-retryable)", resp.status_code, url)
return None
except CookiesExpiredError:
raise
except RequestsError as e:
homecouk_errors_total.labels(type=type(e).__name__).inc()
delay = RETRY_BASE_DELAY * (2**attempt) + random.uniform(0, 1)
log.warning(
"%s from %s, retry %d/%d in %.1fs",
type(e).__name__,
url,
attempt + 1,
max_retries,
delay,
)
time.sleep(delay)
homecouk_errors_total.labels(type="retry_exhausted").inc()
log.error("All %d retries exhausted for %s", max_retries, url)
return None
def parse_floor_area(description: str | None) -> float | None:
"""Try to extract floor area from description text like '789 sq.ft.' or '73 sq.m.'."""
if not description:
return None
m = re.search(r"([\d,]+(?:\.\d+)?)\s*sq\.?\s*ft", description, re.IGNORECASE)
if m:
sqft = float(m.group(1).replace(",", ""))
return validate_floor_area(round(sqft * 0.092903, 1))
m = re.search(r"([\d,]+(?:\.\d+)?)\s*sq\.?\s*m", description, re.IGNORECASE)
if m:
return validate_floor_area(round(float(m.group(1).replace(",", "")), 1))
return None
def parse_tenure(prop: dict) -> str | None:
"""Extract tenure from home.co.uk property data.
Checks multiple sources in priority order:
1. Dedicated 'tenure' or 'tenure_type' field in the API response
2. Free-text search in the description for 'freehold' / 'leasehold'
3. Free-text search in features lists
home.co.uk aggregates listings from estate agents, so tenure is often
embedded in the description text rather than a structured field.
"""
# 1. Check dedicated tenure fields (in case the API adds them)
for key in ("tenure", "tenure_type", "tenureType"):
val = prop.get(key)
if val and isinstance(val, str):
lower = val.lower().strip()
if "leasehold" in lower:
return "Leasehold"
if "freehold" in lower:
return "Freehold"
# 2. Check description text — estate agents often include tenure here
description = prop.get("description") or ""
if description:
lower_desc = description.lower()
if re.search(r"\bleasehold\b", lower_desc):
return "Leasehold"
if re.search(r"\bfreehold\b", lower_desc):
# Matches "Freehold" and "Share of Freehold" (both = freehold ownership)
return "Freehold"
# 3. Check features / key_features lists if present
for key in ("features", "key_features", "keyFeatures"):
features = prop.get(key)
if features and isinstance(features, list):
for feat in features:
if not isinstance(feat, str):
continue
lower_feat = feat.lower()
if "leasehold" in lower_feat:
return "Leasehold"
if "freehold" in lower_feat:
return "Freehold"
return None
def map_property_type(raw_type: str | None) -> str:
"""Map home.co.uk property type to canonical type."""
if not raw_type:
return "Other"
canonical = PROPERTY_TYPE_MAP.get(raw_type)
if canonical:
return canonical
# Home.co.uk uses types like "House", "Flat", "Apartment", "Detached", etc.
# Try common patterns
lower = raw_type.lower()
if (
"flat" in lower
or "apartment" in lower
or "maisonette" in lower
or "studio" in lower
):
return "Flats/Maisonettes"
if "detached" in lower and "semi" not in lower:
return "Detached"
if "semi" in lower:
return "Semi-Detached"
if "terrace" in lower or "mews" in lower:
return "Terraced"
log.debug("Unknown property type: %r — mapping to Other", raw_type)
return "Other"
def transform_property(
prop: dict,
channel: str,
pc_index: PostcodeSpatialIndex,
) -> dict | None:
"""Transform a raw home.co.uk property dict into our output schema."""
lat = prop.get("latitude")
lng = prop.get("longitude")
if lat is None or lng is None:
return None
# Validate coordinates are in England
if not (49 <= lat <= 56 and -7 <= lng <= 2):
log.debug("Coords outside England: lat=%.4f lng=%.4f — skipping", lat, lng)
return None
price = prop.get("price") or prop.get("latest_price")
if not price or int(price) <= 0:
return None
# Home.co.uk provides postcodes directly, but fall back to spatial index
postcode = prop.get("postcode")
if not postcode:
postcode = pc_index.nearest(lat, lng)
if not postcode:
log.debug("No postcode for property at %.4f, %.4f — skipping", lat, lng)
return None
raw_beds = prop.get("bedrooms", 0) or 0
raw_baths = prop.get("bathrooms", 0) or 0
bedrooms = raw_beds if raw_beds <= MAX_BEDROOMS else 0
bathrooms = raw_baths if raw_baths <= MAX_BEDROOMS else 0
if raw_beds > MAX_BEDROOMS or raw_baths > MAX_BEDROOMS:
log.warning(
"home.co.uk %s: implausible beds=%d baths=%d (capped to 0)",
prop.get("listing_id") or prop.get("property_id") or "?",
raw_beds, raw_baths,
)
listing_type = prop.get("listing_property_type") or prop.get("property_type") or ""
address = prop.get("display_address") or prop.get("address") or ""
# Derive price qualifier from reduction info
price_qualifier = ""
if prop.get("is_reduced"):
pct = prop.get("reduction_percent", 0)
if pct:
price_qualifier = f"Reduced by {pct}%"
else:
price_qualifier = "Reduced"
listing_id = prop.get("listing_id") or prop.get("property_id") or ""
return {
"id": f"hk_{listing_id}", # prefix to avoid collision with Rightmove IDs
"Bedrooms": bedrooms,
"Bathrooms": bathrooms,
"Number of bedrooms & living rooms": bedrooms + bathrooms,
"lon": lng,
"lat": lat,
"Postcode": normalize_postcode(postcode),
"Address per Property Register": address,
"Leasehold/Freehold": parse_tenure(prop),
"Property type": map_property_type(listing_type),
"Property sub-type": normalize_sub_type(listing_type),
"price": int(price),
"price_frequency": "" if channel == "BUY" else "monthly",
"Price qualifier": price_qualifier,
"Total floor area (sqm)": parse_floor_area(prop.get("description")),
"Listing URL": f"{HOMECOUK_BASE}/property/{listing_id}",
"Listing features": [], # not available from home.co.uk
"first_visible_date": prop.get("added_date") or "",
}
def search_outcode(
client: Session,
outcode: str,
channel: str,
pc_index: PostcodeSpatialIndex,
) -> list[dict]:
"""Paginate through search results for one outcode+channel.
channel: "BUY" or "RENT".
Returns transformed properties."""
url_segment = HOMECOUK_CHANNELS[channel]
url = f"{HOMECOUK_API_BASE}/{url_segment}/{outcode.lower()}/"
properties = []
page = 1
while True:
params = {
"page": str(page),
"sort": "date_desc",
"per_page": str(HOMECOUK_PER_PAGE),
}
# Set referer to match the page URL pattern
client.headers["referer"] = (
f"https://home.co.uk/{url_segment}/{outcode.lower()}/"
f"?page={page}&sort=date_desc&per_page={HOMECOUK_PER_PAGE}"
)
data = fetch_page(client, url, params)
if not data:
break
raw_props = data.get("properties", [])
if not raw_props:
break
for prop in raw_props:
transformed = transform_property(prop, channel, pc_index)
if transformed:
properties.append(transformed)
homecouk_properties_scraped.labels(
channel="buy" if channel == "BUY" else "rent",
).inc()
# Check pagination
pagination = data.get("pagination", {})
last_page = pagination.get("last_page", 1)
if page >= last_page:
break
page += 1
time.sleep(DELAY_BETWEEN_PAGES)
return properties

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import logging
import random
import threading
import time
import httpx
from fake_useragent import UserAgent
from constants import MAX_RETRIES, RETRY_BASE_DELAY
from metrics import http_errors_total, http_requests_total, ip_rotations_total
log = logging.getLogger("rightmove")
_ua = UserAgent(
browsers=["Chrome", "Edge"], os=["Windows", "Mac OS X"], min_version=120.0
)
def _endpoint_label(url: str) -> str:
if "typeahead" in url:
return "typeahead"
if "search" in url:
return "search"
return "other"
def _status_label(code: int) -> str:
if code >= 500:
return "5xx"
return str(code)
# Gluetun control API — runs on port 8000 inside the gluetun container.
# Since finder uses network_mode: service:gluetun, localhost IS gluetun.
GLUETUN_API = "http://127.0.0.1:8000"
_ip_rotate_lock = threading.Lock()
def rotate_ip() -> bool:
"""Ask gluetun to reconnect to a different VPN server, getting a new IP.
Returns True if the IP changed successfully."""
with _ip_rotate_lock:
log.info("Rotating VPN IP via gluetun...")
try:
# Get current IP
with httpx.Client(timeout=10) as ctl:
old_ip_resp = ctl.get(f"{GLUETUN_API}/v1/publicip/ip")
old_ip = (
old_ip_resp.json().get("public_ip", "unknown")
if old_ip_resp.status_code == 200
else "unknown"
)
log.info("Current IP: %s", old_ip)
# Trigger server change — PUT with empty JSON body picks a random server
resp = ctl.put(
f"{GLUETUN_API}/v1/vpn/status", json={"status": "stopped"}
)
if resp.status_code != 200:
log.error("Failed to stop VPN: %d %s", resp.status_code, resp.text)
return False
time.sleep(2)
resp = ctl.put(
f"{GLUETUN_API}/v1/vpn/status", json={"status": "running"}
)
if resp.status_code != 200:
log.error("Failed to start VPN: %d %s", resp.status_code, resp.text)
return False
# Wait for reconnection
for _ in range(30):
time.sleep(2)
try:
with httpx.Client(timeout=10) as ctl:
new_ip_resp = ctl.get(f"{GLUETUN_API}/v1/publicip/ip")
if new_ip_resp.status_code == 200:
new_ip = new_ip_resp.json().get("public_ip", "")
if new_ip and new_ip != old_ip:
log.info("IP rotated: %s%s", old_ip, new_ip)
ip_rotations_total.labels(result="success").inc()
return True
except Exception:
pass # VPN still reconnecting
log.warning("IP rotation timed out (may still be same IP)")
ip_rotations_total.labels(result="failure").inc()
return False
except Exception as e:
log.error("IP rotation failed: %s", e)
ip_rotations_total.labels(result="failure").inc()
return False
def make_client() -> httpx.Client:
return httpx.Client(
timeout=30,
headers={"User-Agent": _ua.random, "Accept": "application/json"},
follow_redirects=True,
)
def fetch_with_retry(
client: httpx.Client, url: str, params: dict | None = None, on_403: bool = True
) -> dict | None:
"""GET JSON with retries on 429/5xx/connection errors. Returns None on permanent failure.
On 403, triggers IP rotation and retries once."""
endpoint = _endpoint_label(url)
for attempt in range(MAX_RETRIES):
try:
resp = client.get(url, params=params)
http_requests_total.labels(
status=_status_label(resp.status_code), endpoint=endpoint
).inc()
if resp.status_code == 200:
return resp.json()
if resp.status_code == 403 and on_403:
log.warning("HTTP 403 — IP likely blocked, rotating...")
if rotate_ip():
# Retry once with new IP (but don't recurse on 403 again)
return fetch_with_retry(client, url, params, on_403=False)
log.error("IP rotation failed, giving up on %s", url)
return None
if resp.status_code in (429, 500, 502, 503, 504):
delay = RETRY_BASE_DELAY * (2**attempt) + random.uniform(0, 1)
log.warning(
"HTTP %d from %s, retry %d/%d in %.1fs",
resp.status_code,
url,
attempt + 1,
MAX_RETRIES,
delay,
)
time.sleep(delay)
continue
log.error("HTTP %d from %s (non-retryable)", resp.status_code, url)
return None
except (
httpx.ConnectError,
httpx.ReadTimeout,
httpx.WriteTimeout,
httpx.PoolTimeout,
) as e:
http_errors_total.labels(type=type(e).__name__).inc()
delay = RETRY_BASE_DELAY * (2**attempt) + random.uniform(0, 1)
log.warning(
"%s from %s, retry %d/%d in %.1fs",
type(e).__name__,
url,
attempt + 1,
MAX_RETRIES,
delay,
)
time.sleep(delay)
http_errors_total.labels(type="retry_exhausted").inc()
log.error("All %d retries exhausted for %s", MAX_RETRIES, url)
return None

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@ -1,211 +0,0 @@
import logging
import threading
import time
from datetime import datetime, timedelta, timezone
from pathlib import Path
from flask import Flask, Response, jsonify, send_from_directory
from prometheus_client import generate_latest, CONTENT_TYPE_LATEST
from constants import (
DATA_DIR,
RUN_ON_STARTUP,
SCHEDULE_HOUR,
SCRAPE_HOMECOUK,
SCRAPE_OPENRENT,
SCRAPE_RIGHTMOVE,
SCRAPE_ZOOPLA,
)
from homecouk import load_cookies as load_homecouk_cookies
from openrent import load_cookies as load_openrent_cookies
from rightmove import outcode_cache
from scraper import (
_sync_gauges,
build_postcode_coords,
build_postcode_index,
load_outcodes,
run_scrape,
status,
status_lock,
)
# ---------------------------------------------------------------------------
# Logging
# ---------------------------------------------------------------------------
LOG_DIR = Path("/app/data")
LOG_DIR.mkdir(parents=True, exist_ok=True)
logging.basicConfig(
level=logging.DEBUG,
format="%(asctime)s [%(levelname)s] %(message)s",
handlers=[
logging.StreamHandler(),
logging.FileHandler(LOG_DIR / "rightmove.log"),
],
)
log = logging.getLogger("rightmove")
log.setLevel(logging.DEBUG)
logging.getLogger("httpx").setLevel(logging.WARNING)
logging.getLogger("httpcore").setLevel(logging.WARNING)
# Suppress noisy /metrics and /health request logs from werkzeug
class _NoiseFilter(logging.Filter):
def filter(self, record):
msg = record.getMessage()
return "GET /metrics" not in msg and "GET /health" not in msg
logging.getLogger("werkzeug").addFilter(_NoiseFilter())
# ---------------------------------------------------------------------------
# Startup: load data
# ---------------------------------------------------------------------------
log.info("Loading arcgis data...")
OUTCODES = load_outcodes()
PC_INDEX = build_postcode_index()
PC_COORDS = build_postcode_coords() if (SCRAPE_OPENRENT or SCRAPE_ZOOPLA) else None
log.info(
"Ready — %d outcodes, postcode index built (rightmove=%s, homecouk=%s, openrent=%s, zoopla=%s)",
len(OUTCODES),
SCRAPE_RIGHTMOVE,
SCRAPE_HOMECOUK,
SCRAPE_OPENRENT,
SCRAPE_ZOOPLA,
)
# ---------------------------------------------------------------------------
# Scheduler
# ---------------------------------------------------------------------------
def _start_scrape() -> bool:
"""Try to start a scrape. Returns True if started, False if already running."""
with status_lock:
if status.state == "running":
return False
status.state = "running"
thread = threading.Thread(
target=run_scrape, args=(OUTCODES, PC_INDEX, PC_COORDS), daemon=True
)
thread.start()
return True
def _seconds_until(hour: int) -> float:
"""Seconds from now until the next occurrence of `hour`:00 UTC."""
now = datetime.now(timezone.utc)
target = now.replace(hour=hour, minute=0, second=0, microsecond=0)
if target <= now:
target += timedelta(days=1)
return (target - now).total_seconds()
def _scheduler_loop() -> None:
"""Background thread that triggers a daily scrape at SCHEDULE_HOUR UTC."""
log.info("Scheduler active — will run daily at %02d:00 UTC", SCHEDULE_HOUR)
while True:
wait = _seconds_until(SCHEDULE_HOUR)
log.info(
"Next scheduled scrape in %.0f seconds (%.1f hours)", wait, wait / 3600
)
time.sleep(wait)
log.info("Scheduled scrape triggered")
if not _start_scrape():
log.warning("Scheduled scrape skipped — already running")
if RUN_ON_STARTUP:
log.info("RUN_ON_STARTUP=true — starting initial scrape")
_start_scrape()
if SCHEDULE_HOUR >= 0:
scheduler = threading.Thread(target=_scheduler_loop, daemon=True)
scheduler.start()
# ---------------------------------------------------------------------------
# Flask app
# ---------------------------------------------------------------------------
app = Flask(__name__)
@app.route("/health")
def health():
return "ok", 200
@app.route("/run", methods=["POST"])
def trigger_run():
if _start_scrape():
return jsonify({"message": "Scrape started"}), 200
return jsonify({"error": "Scrape already running"}), 409
@app.route("/status")
def get_status():
with status_lock:
elapsed = 0.0
if status.started_at:
end = status.finished_at if status.finished_at else time.time()
elapsed = end - status.started_at
resp = {
"state": status.state,
"channel": status.channel,
"outcode": status.outcode,
"outcodes_done": status.outcodes_done,
"outcodes_total": status.outcodes_total,
"properties_buy": status.properties_buy,
"properties_rent": status.properties_rent,
"properties_by_source": {
"rightmove": status.rm_properties,
"homecouk": status.hk_properties,
"openrent": status.or_properties,
"zoopla": status.zp_properties,
},
"errors": status.errors[-20:], # last 20 errors
"elapsed_seconds": round(elapsed, 1),
}
if SCHEDULE_HOUR >= 0:
resp["next_scrape_in_seconds"] = round(_seconds_until(SCHEDULE_HOUR))
return jsonify(resp)
@app.route("/debug")
def get_debug():
hk_cookies = load_homecouk_cookies() if SCRAPE_HOMECOUK else None
or_cookies = load_openrent_cookies() if SCRAPE_OPENRENT else None
return jsonify(
{
"outcode_cache_size": len(outcode_cache),
"outcode_cache_sample": dict(list(outcode_cache.items())[:20]),
"scrape_rightmove": SCRAPE_RIGHTMOVE,
"scrape_homecouk": SCRAPE_HOMECOUK,
"scrape_openrent": SCRAPE_OPENRENT,
"scrape_zoopla": SCRAPE_ZOOPLA,
"homecouk_cookies_available": hk_cookies is not None,
"openrent_cookies_available": or_cookies is not None,
"zoopla_note": "browser-based (Camoufox), no cookies needed",
}
)
@app.route("/metrics")
def metrics():
with status_lock:
_sync_gauges()
return Response(generate_latest(), mimetype=CONTENT_TYPE_LATEST)
@app.route("/data/<filename>")
def serve_data(filename):
if not filename.endswith(".parquet"):
return jsonify({"error": "Only parquet files served"}), 400
return send_from_directory(DATA_DIR, filename)
if __name__ == "__main__":
app.run(host="0.0.0.0", port=1234, debug=False)

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@ -1,167 +0,0 @@
from prometheus_client import Counter, Gauge
# ---------------------------------------------------------------------------
# Gauges — current scrape state, updated after each outcode
# ---------------------------------------------------------------------------
scrape_state = Gauge(
"scrape_state",
"Current scrape state as a labeled gauge (1 = active)",
["state"],
)
scrape_outcodes_done = Gauge(
"scrape_outcodes_done",
"Outcodes processed in current channel",
)
scrape_outcodes_total = Gauge(
"scrape_outcodes_total",
"Total outcodes in current channel",
)
scrape_properties_total = Gauge(
"scrape_properties_total",
"Properties found so far",
["channel", "source"],
)
scrape_elapsed_seconds = Gauge(
"scrape_elapsed_seconds",
"Seconds since scrape started",
)
# ---------------------------------------------------------------------------
# Counters — Rightmove (monotonically increasing)
# ---------------------------------------------------------------------------
http_requests_total = Counter(
"http_requests_total",
"HTTP requests made to Rightmove",
["status", "endpoint"],
)
http_errors_total = Counter(
"http_errors_total",
"Rightmove HTTP connection/timeout errors",
["type"],
)
ip_rotations_total = Counter(
"ip_rotations_total",
"VPN IP rotation attempts",
["result"],
)
scrape_errors_total = Counter(
"scrape_errors_total",
"Per-outcode scrape errors",
["source"],
)
# ---------------------------------------------------------------------------
# Counters — home.co.uk
# ---------------------------------------------------------------------------
homecouk_requests_total = Counter(
"homecouk_requests_total",
"HTTP requests made to home.co.uk API",
["status"],
)
homecouk_errors_total = Counter(
"homecouk_errors_total",
"home.co.uk HTTP connection/timeout errors",
["type"],
)
homecouk_properties_scraped = Counter(
"homecouk_properties_scraped",
"Properties scraped from home.co.uk (before dedup)",
["channel"],
)
cross_source_dedup_total = Counter(
"cross_source_dedup_total",
"Properties skipped because same property already found on another source",
["channel"],
)
# ---------------------------------------------------------------------------
# Counters — OpenRent
# ---------------------------------------------------------------------------
openrent_requests_total = Counter(
"openrent_requests_total",
"HTTP requests made to OpenRent",
["status"],
)
openrent_errors_total = Counter(
"openrent_errors_total",
"OpenRent HTTP connection/timeout errors",
["type"],
)
openrent_properties_scraped = Counter(
"openrent_properties_scraped",
"Properties scraped from OpenRent (before dedup)",
["channel"],
)
# ---------------------------------------------------------------------------
# Counters — Zoopla
# ---------------------------------------------------------------------------
zoopla_pages_scraped = Counter(
"zoopla_pages_scraped",
"Search result pages scraped from Zoopla",
["channel"],
)
zoopla_errors_total = Counter(
"zoopla_errors_total",
"Zoopla scraping errors",
["type"],
)
zoopla_properties_scraped = Counter(
"zoopla_properties_scraped",
"Properties scraped from Zoopla (before dedup)",
["channel"],
)
# ---------------------------------------------------------------------------
# Counters — FlareSolverr / cookie management
# ---------------------------------------------------------------------------
flaresolverr_attempts_total = Counter(
"flaresolverr_attempts_total",
"FlareSolverr Cloudflare challenge-solving attempts",
["result"],
)
cookie_refreshes_total = Counter(
"cookie_refreshes_total",
"home.co.uk cookie refresh attempts (triggered by 403)",
["result"],
)
# ---------------------------------------------------------------------------
# Gauges — home.co.uk state
# ---------------------------------------------------------------------------
homecouk_enabled = Gauge(
"homecouk_enabled",
"Whether home.co.uk scraping is currently active (1=yes, 0=no)",
)
openrent_enabled = Gauge(
"openrent_enabled",
"Whether OpenRent scraping is currently active (1=yes, 0=no)",
)
zoopla_enabled = Gauge(
"zoopla_enabled",
"Whether Zoopla scraping is currently active (1=yes, 0=no)",
)

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@ -1,6 +0,0 @@
Hit the following url with the outcode as the location-id and the page. So for E13, page 2 it's:
https://www.onthemarket.com/async/search/properties-v2/?search-type=for-sale&location-id=e13&page=2&view=map-list
and the response is in [[response.json]]

File diff suppressed because it is too large Load diff

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@ -1,869 +0,0 @@
"""OpenRent (openrent.co.uk) scraper — rental properties only.
OpenRent is behind AWS WAF, so we use Playwright (headless Chromium) to solve
the challenge and get valid cookies. Then we use curl_cffi with Chrome TLS
impersonation to make requests with those cookies.
OpenRent is a rental-only platform, so this scraper only handles RENT channel.
HTML structure (as of 2026-03):
Search results page renders property cards as <a class="pli search-property-card">.
Each card contains:
- Monthly price in <div class="pim"> with <span class="text-primary">£X,XXX</span>
- Weekly price in <div class="piw"> (hidden by Alpine.js)
- Title in <div class="fw-medium text-primary fs-3">N Bed Type, Location, OUTCODE</div>
- Features in <ul> with <li> items like "1 Bed", "1 Bath", "Furnished"
- Listing ID in data-listing-id on the .or-swiper div
- Description snippet in <div class="line-clamp-2">
Detail page has:
- <h1> with property title including outcode
- <div id="map" data-lat="..." data-lng="..."> for coordinates
- Tables with deposit, rent, furnishing, tenant preferences
"""
import logging
import os
import re
import time
from bs4 import BeautifulSoup
from curl_cffi.requests import Session
from curl_cffi.requests.errors import RequestsError
from playwright.sync_api import sync_playwright
from constants import (
DELAY_BETWEEN_PAGES,
MAX_BEDROOMS,
OPENRENT_BASE,
PROPERTY_TYPE_MAP,
RETRY_BASE_DELAY,
)
from metrics import (
flaresolverr_attempts_total,
openrent_errors_total,
openrent_properties_scraped,
openrent_requests_total,
)
from spatial import PostcodeSpatialIndex
from transform import normalize_postcode, normalize_sub_type, validate_floor_area
log = logging.getLogger("openrent")
class WafChallengeError(Exception):
"""Raised when OpenRent returns a WAF challenge, indicating cookies need refresh."""
# ---------------------------------------------------------------------------
# Cookie / session management via Playwright
# ---------------------------------------------------------------------------
def solve_waf() -> tuple[dict[str, str], str] | None:
"""Use Playwright (headless Chromium) to solve the AWS WAF challenge.
Returns (cookies_dict, user_agent) or None on failure."""
log.info("Solving AWS WAF challenge via Playwright")
try:
with sync_playwright() as p:
browser = p.chromium.launch(
headless=True,
args=["--no-sandbox", "--disable-blink-features=AutomationControlled"],
)
context = browser.new_context()
page = context.new_page()
url = f"{OPENRENT_BASE}/properties-to-rent/?term=london&isLive=true"
log.info("Navigating to %s", url)
page.goto(url, wait_until="domcontentloaded", timeout=60000)
content = page.content()
if "AwsWafIntegration" in content:
log.info("Got WAF challenge page, waiting for resolution...")
page.wait_for_selector(
"a.pli, .pli, .search-property-card",
timeout=30000,
)
raw_cookies = context.cookies()
user_agent = page.evaluate("navigator.userAgent")
browser.close()
cookies = {c["name"]: c["value"] for c in raw_cookies}
if "aws-waf-token" not in cookies:
log.error("Playwright solved page but no aws-waf-token cookie found")
flaresolverr_attempts_total.labels(result="no_cookies").inc()
return None
log.info(
"AWS WAF solved — got %d cookies, UA: %s",
len(cookies),
user_agent[:60],
)
flaresolverr_attempts_total.labels(result="success").inc()
return cookies, user_agent
except Exception as e:
log.error("Playwright WAF solve failed: %s", e)
flaresolverr_attempts_total.labels(result="error").inc()
return None
def load_cookies() -> tuple[dict[str, str], str] | None:
"""Get OpenRent cookies + user-agent.
Tries Playwright first, then falls back to environment variables."""
result = solve_waf()
if result:
return result
# Fall back to env vars
waf_token = os.environ.get("OPENRENT_WAF_TOKEN", "")
if not waf_token:
return None
user_agent = os.environ.get(
"OPENRENT_USER_AGENT",
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) "
"AppleWebKit/537.36 (KHTML, like Gecko) "
"Chrome/145.0.0.0 Safari/537.36",
)
return {"aws-waf-token": waf_token}, user_agent
def make_client(cookies: dict[str, str], user_agent: str) -> Session:
"""Create a curl_cffi Session configured for OpenRent.
Uses Chrome TLS impersonation so AWS WAF cookies remain valid."""
session = Session(impersonate="chrome")
session.headers.update(
{
"User-Agent": user_agent,
"Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8",
"Accept-Language": "en-GB,en;q=0.9",
}
)
for name, value in cookies.items():
session.cookies.set(name, value, domain="openrent.co.uk")
return session
# ---------------------------------------------------------------------------
# HTTP fetch with retry
# ---------------------------------------------------------------------------
def _status_label(code: int) -> str:
if code >= 500:
return "5xx"
return str(code)
def fetch_page(
client: Session,
url: str,
max_retries: int = 3,
) -> str | None:
"""GET HTML with retries on 429/5xx. Returns None on permanent failure.
WAF challenge (202 or 403 with challenge JS) raises WafChallengeError."""
for attempt in range(max_retries):
try:
resp = client.get(url, timeout=30)
openrent_requests_total.labels(status=_status_label(resp.status_code)).inc()
if resp.status_code == 200:
html = resp.text
# Detect WAF challenge page masquerading as 200
if "AwsWafIntegration" in html and "challenge.js" in html:
raise WafChallengeError(
"Got AWS WAF challenge page — cookies expired"
)
return html
if resp.status_code in (202, 403):
raise WafChallengeError(
f"HTTP {resp.status_code} — cookies likely expired"
)
if resp.status_code in (429, 500, 502, 503, 504):
delay = RETRY_BASE_DELAY * (2**attempt)
log.warning(
"HTTP %d from %s, retry %d/%d in %.1fs",
resp.status_code,
url,
attempt + 1,
max_retries,
delay,
)
time.sleep(delay)
continue
log.error("HTTP %d from %s (non-retryable)", resp.status_code, url)
return None
except WafChallengeError:
raise
except RequestsError as e:
openrent_errors_total.labels(type=type(e).__name__).inc()
delay = RETRY_BASE_DELAY * (2**attempt)
log.warning(
"%s from %s, retry %d/%d in %.1fs",
type(e).__name__,
url,
attempt + 1,
max_retries,
delay,
)
time.sleep(delay)
openrent_errors_total.labels(type="retry_exhausted").inc()
log.error("All %d retries exhausted for %s", max_retries, url)
return None
# ---------------------------------------------------------------------------
# HTML parsing
# ---------------------------------------------------------------------------
def _extract_price_from_element(el) -> tuple[int, str] | None:
"""Extract price integer from a price element's text like '£2,100'."""
if not el:
return None
text = el.get_text(strip=True)
match = re.search(r"£([\d,]+)", text)
if not match:
return None
return int(match.group(1).replace(",", ""))
def _extract_price(text: str) -> tuple[int, str] | None:
"""Extract price and frequency from text like '£1,500 pcm' or '£350 pw'.
Returns (price_int, frequency) or None.
OpenRent card text shows both monthly and weekly prices (e.g.
'£2,800 per month £646 per week'), so check monthly *before* weekly
to match the first (monthly) price that the regex captures."""
match = re.search(r"£([\d,]+)", text)
if not match:
return None
price = int(match.group(1).replace(",", ""))
lower = text.lower()
if "pcm" in lower or "per month" in lower or "/m" in lower:
return price, "monthly"
if "pw" in lower or "per week" in lower or "/w" in lower:
return price, "weekly"
if "pa" in lower or "per annum" in lower or "/y" in lower:
return price, "yearly"
# OpenRent defaults to pcm (per calendar month)
return price, "monthly"
def _extract_bedrooms_from_title(title: str) -> int | None:
"""Extract bedroom count from title like '2 Bed Flat, Pimlico'."""
match = re.search(r"(\d+)\s*bed", title, re.IGNORECASE)
if match:
return int(match.group(1))
if re.search(r"\bstudio\b", title, re.IGNORECASE):
return 0
return None
def _extract_beds_baths_from_features(
feature_items: list,
) -> tuple[int | None, int | None]:
"""Extract bedrooms and bathrooms from feature list items.
OpenRent search cards have <ul> with items like:
<li>1 Bed</li> <li>1 Bath</li> <li>Furnished</li>
"""
bedrooms = None
bathrooms = None
for li in feature_items:
text = li.get_text(strip=True).lower()
bed_match = re.search(r"(\d+)\s*bed", text)
if bed_match:
bedrooms = int(bed_match.group(1))
bath_match = re.search(r"(\d+)\s*bath", text)
if bath_match:
bathrooms = int(bath_match.group(1))
return bedrooms, bathrooms
def _extract_postcode(text: str) -> str | None:
"""Extract full UK postcode from text like '2 Bed Flat, Pimlico, SW1V 2AA'.
Normalizes to include a space before the 3-char incode."""
match = re.search(r"([A-Z]{1,2}\d[A-Z0-9]?\s*\d[A-Z]{2})", text, re.IGNORECASE)
if match:
raw = match.group(1).upper().strip()
# Ensure space before incode (last 3 chars): "IP265AT" → "IP26 5AT"
if " " not in raw and len(raw) >= 5:
return raw[:-3] + " " + raw[-3:]
return raw
return None
def _extract_outcode(text: str) -> str | None:
"""Extract UK outcode from text like '1 Bed Flat, Bank Chambers, SW1Y'.
Looks for an outcode pattern (e.g., SW1Y, E1, EC2A) at the end of the text
or after the last comma."""
# Try after last comma first (most reliable position in OpenRent titles)
parts = text.split(",")
if len(parts) > 1:
last_part = parts[-1].strip()
match = re.match(r"^([A-Z]{1,2}\d[A-Z0-9]?)$", last_part, re.IGNORECASE)
if match:
return match.group(1).upper()
# Fall back to searching anywhere in text
match = re.search(r"\b([A-Z]{1,2}\d[A-Z0-9]?)\b", text, re.IGNORECASE)
if match:
candidate = match.group(1).upper()
# Avoid matching things like "1 Bed" → "1B"
if len(candidate) >= 2 and not candidate[0].isdigit():
return candidate
return None
def _infer_property_type(title: str) -> str:
"""Infer property type from title text.
Order matters: "Room in a Shared Flat" should be "Room" not "Flat",
so check "room" before "flat"."""
lower = title.lower()
if "room in" in lower or "room " in lower:
return "Room"
if "studio" in lower:
return "Studio"
if "flat" in lower or "apartment" in lower:
return "Flat"
if "maisonette" in lower:
return "Maisonette"
if "house" in lower:
return "House"
if "bungalow" in lower:
return "Bungalow"
return ""
def parse_search_results(html: str) -> list[dict]:
"""Parse property data from OpenRent search results HTML.
Returns list of raw property dicts extracted from property cards.
Current OpenRent card structure (2026-03):
<a class="pli search-property-card" href="/property-to-rent/.../ID">
<div class="or-swiper" data-listing-id="ID">
<div class="pim"><span class="text-primary">£2,100</span> per month</div>
<div class="piw"><span class="text-primary">£485</span> per week</div>
<div class="fw-medium text-primary fs-3">1 Bed Flat, Location, SW1Y</div>
<ul>...<li>1 Bed</li><li>1 Bath</li><li>Furnished</li>...</ul>
"""
soup = BeautifulSoup(html, "lxml")
properties = []
# Property cards: <a class="pli search-property-card">
cards = soup.select("a.pli")
if not cards:
cards = soup.find_all("a", href=re.compile(r"/property-to-rent/"))
if not cards:
log.warning(
"No property cards found in search HTML (%d bytes). "
"CSS selectors may need updating.",
len(html),
)
return []
for card in cards:
prop: dict = {}
# Extract property URL and ID from href
href = card.get("href", "")
if not href:
continue
prop["url"] = href if href.startswith("http") else OPENRENT_BASE + href
id_match = re.search(r"/(\d+)(?:\?|$|#)", href)
if id_match:
prop["id"] = id_match.group(1)
else:
# Try data-listing-id on the swiper element
swiper = card.select_one("[data-listing-id]")
if swiper:
prop["id"] = swiper["data-listing-id"]
else:
continue # can't use a property without an ID
# --- Price ---
# Prefer structured price elements over free-text parsing.
# Monthly price is in <div class="pim"><span class="text-primary">£X</span>
pim = card.select_one(".pim .text-primary, .pim span")
piw = card.select_one(".piw .text-primary, .piw span")
monthly_price = _extract_price_from_element(pim)
weekly_price = _extract_price_from_element(piw)
if monthly_price:
prop["price"] = monthly_price
prop["frequency"] = "monthly"
elif weekly_price:
prop["price"] = weekly_price
prop["frequency"] = "weekly"
else:
# Fall back to parsing card text
card_text = card.get_text(" ", strip=True)
price_result = _extract_price(card_text)
if price_result:
prop["price"], prop["frequency"] = price_result
# --- Title / Address ---
# The property title is in a div with classes "fw-medium text-primary fs-3"
# e.g., "1 Bed Flat, Bank Chambers, SW1Y"
title_el = card.select_one("div.fw-medium.fs-3")
if not title_el:
# Fallback: try image alt text which also has the title
img = card.select_one("img.propertyPic")
if img and img.get("alt"):
prop["title"] = img["alt"]
else:
# Last resort: extract from card text, excluding price/nav noise
prop["title"] = ""
else:
prop["title"] = title_el.get_text(strip=True)
# --- Bedrooms / Bathrooms from feature list ---
feature_list = card.select("ul li")
beds_from_features, baths_from_features = _extract_beds_baths_from_features(
feature_list,
)
# Bedrooms: prefer feature list, fall back to title parsing
if beds_from_features is not None:
prop["bedrooms"] = beds_from_features
else:
beds = _extract_bedrooms_from_title(prop.get("title", ""))
if beds is not None:
prop["bedrooms"] = beds
if baths_from_features is not None:
prop["bathrooms"] = baths_from_features
# --- Property type from title ---
title = prop.get("title", "")
prop["property_type"] = _infer_property_type(title)
# --- Postcode / outcode from title ---
postcode = _extract_postcode(title)
if postcode:
prop["postcode"] = postcode
else:
outcode = _extract_outcode(title)
if outcode:
prop["outcode"] = outcode
# --- Description snippet ---
desc_el = card.select_one(".line-clamp-2")
if desc_el:
prop["description"] = desc_el.get_text(strip=True)
# --- Coordinates from data attributes (may not be present on cards) ---
for el in [card] + card.select("[data-lat], [data-latitude]"):
lat = el.get("data-lat") or el.get("data-latitude")
lng = el.get("data-lng") or el.get("data-longitude") or el.get("data-lon")
if lat and lng:
try:
prop["lat"] = float(lat)
prop["lng"] = float(lng)
except ValueError:
pass
break
properties.append(prop)
log.debug("Parsed %d property cards from search HTML", len(properties))
return properties
def parse_property_detail(html: str) -> dict:
"""Parse a single property detail page for additional data.
Current detail page structure (2026-03):
- <h1> has the full title (e.g., "Room in a Shared House, Lime Tree Court, AL2")
- <div id="map" data-lat="..." data-lng="..."> has coordinates
- Tables have "Rent PCM", "Deposit", "Bills Included", etc. (NOT bedrooms)
- Description in elements with class containing "description"
"""
soup = BeautifulSoup(html, "lxml")
details: dict = {}
# --- Title from h1 ---
h1 = soup.select_one("h1")
if h1:
title_text = h1.get_text(strip=True)
# Validate it's not a nav/modal element (e.g. "Log in")
if len(title_text) > 10 and "log in" not in title_text.lower():
details["title"] = title_text
postcode = _extract_postcode(title_text)
if postcode:
details["postcode"] = postcode
# --- Coordinates from map element ---
# The map div has id="map" with data-lat and data-lng
map_el = soup.select_one("#map[data-lat]")
if not map_el:
# Fallback: any element with data-lat (but prefer #map)
map_el = soup.select_one("[data-lat]")
if map_el:
lat = map_el.get("data-lat")
lng = map_el.get("data-lng") or map_el.get("data-lon")
if lat and lng:
try:
details["lat"] = float(lat)
details["lng"] = float(lng)
except ValueError:
pass
# --- Parse tables for rent and property details ---
for table in soup.select("table"):
for row in table.select("tr"):
cells = row.select("td")
if len(cells) < 2:
continue
label = cells[0].get_text(strip=True).lower()
value = cells[1].get_text(strip=True)
if "rent" in label and "pcm" in label:
match = re.search(r"£([\d,]+)", value)
if match:
details["price"] = int(match.group(1).replace(",", ""))
elif "bedroom" in label:
match = re.search(r"(\d+)", value)
if match:
details["bedrooms"] = int(match.group(1))
elif "bathroom" in label:
match = re.search(r"(\d+)", value)
if match:
details["bathrooms"] = int(match.group(1))
elif "type" in label and "property" in label:
details["property_type"] = value
elif "available" in label or "move" in label:
details["available_date"] = value
elif "furnish" in label:
details["furnished"] = value
# --- Coordinates from inline JavaScript (last resort) ---
if "lat" not in details:
for script in soup.select("script"):
text = script.string or ""
lat_match = re.search(r'"latitude"\s*:\s*([\d.-]+)', text)
lng_match = re.search(r'"longitude"\s*:\s*([\d.-]+)', text)
if lat_match and lng_match:
try:
details["lat"] = float(lat_match.group(1))
details["lng"] = float(lng_match.group(1))
except ValueError:
pass
break
# --- Description for floor area ---
desc_el = soup.select_one(".description, [class*='description'], #description")
if desc_el:
details["description"] = desc_el.get_text(strip=True)
return details
# ---------------------------------------------------------------------------
# Property type mapping & floor area
# ---------------------------------------------------------------------------
def map_property_type(raw_type: str | None) -> str:
"""Map OpenRent property type to canonical type."""
if not raw_type:
return "Other"
canonical = PROPERTY_TYPE_MAP.get(raw_type)
if canonical:
return canonical
lower = raw_type.lower()
if "room" in lower or "shared" in lower:
return "Other"
if (
"flat" in lower
or "apartment" in lower
or "maisonette" in lower
or "studio" in lower
):
return "Flats/Maisonettes"
if "detached" in lower and "semi" not in lower:
return "Detached"
if "semi" in lower:
return "Semi-Detached"
if "terrace" in lower or "mews" in lower:
return "Terraced"
if "house" in lower:
return "Detached"
log.debug("Unknown property type: %r — mapping to Other", raw_type)
return "Other"
def parse_floor_area(description: str | None) -> float | None:
"""Try to extract floor area from description text."""
if not description:
return None
m = re.search(r"([\d,]+(?:\.\d+)?)\s*sq\.?\s*ft", description, re.IGNORECASE)
if m:
sqft = float(m.group(1).replace(",", ""))
return validate_floor_area(round(sqft * 0.092903, 1))
m = re.search(r"([\d,]+(?:\.\d+)?)\s*sq\.?\s*m", description, re.IGNORECASE)
if m:
return validate_floor_area(round(float(m.group(1).replace(",", "")), 1))
return None
# ---------------------------------------------------------------------------
# Transform & search
# ---------------------------------------------------------------------------
def _resolve_outcode_postcodes(
outcode: str,
pc_coords: dict[str, tuple[float, float]],
) -> list[str]:
"""Get all postcodes for an outcode from the postcode coordinates lookup."""
# ONSPD 7-char format: 4-char outcodes have no space before incode
# (e.g., "BH191AB"), while shorter outcodes do (e.g., "E14 5AB").
prefix = outcode + " "
results = [pcd for pcd in pc_coords if pcd.startswith(prefix)]
if not results and len(outcode) >= 4:
results = [pcd for pcd in pc_coords if pcd.startswith(outcode) and len(pcd) > len(outcode)]
return results
def _parse_or_date(date_str: str) -> str:
"""Parse OpenRent date strings to ISO format (YYYY-MM-DD).
Handles 'Today', 'Tomorrow', and 'DD Month, YYYY' formats."""
if not date_str:
return ""
stripped = date_str.strip()
lower = stripped.lower()
if lower == "today":
from datetime import datetime
return datetime.now().strftime("%Y-%m-%d")
if lower == "tomorrow":
from datetime import datetime, timedelta
return (datetime.now() + timedelta(days=1)).strftime("%Y-%m-%d")
# Try "DD Month, YYYY" format (e.g., "01 April, 2026")
from datetime import datetime
for fmt in ("%d %B, %Y", "%d %B %Y"):
try:
return datetime.strptime(stripped, fmt).strftime("%Y-%m-%d")
except ValueError:
continue
return date_str # Return as-is if unparseable
def transform_property(
search_data: dict,
detail_data: dict | None,
pc_index: PostcodeSpatialIndex,
pc_coords: dict[str, tuple[float, float]],
) -> dict | None:
"""Transform OpenRent property data into our output schema.
Merges data from the search results page and (optionally) the detail page.
Uses pc_coords (postcode -> lat/lng) as a fallback when coordinates are
missing but a postcode is available.
"""
detail = detail_data or {}
# Merge: detail page data takes precedence
lat = detail.get("lat") or search_data.get("lat")
lng = detail.get("lng") or search_data.get("lng")
price = detail.get("price") or search_data.get("price")
if not price or int(price) <= 0:
return None
frequency = search_data.get("frequency", "monthly")
# Get postcode: detail page > search card
postcode = detail.get("postcode") or search_data.get("postcode")
if lat is not None and lng is not None:
# Validate coordinates are in England
if not (49 <= lat <= 56 and -7 <= lng <= 2):
log.debug("Coords outside England: lat=%.4f lng=%.4f — skipping", lat, lng)
return None
if not postcode:
if pc_index:
postcode = pc_index.nearest(lat, lng)
elif search_data.get("outcode"):
# No spatial index — try outcode lookup as fallback
outcode_pcs = _resolve_outcode_postcodes(
search_data["outcode"],
pc_coords,
)
if outcode_pcs:
postcode = outcode_pcs[0]
elif postcode:
# Have postcode but no coordinates — look up centroid from arcgis data
coords = pc_coords.get(postcode)
if coords:
lat, lng = coords
else:
log.debug("Postcode %s not in arcgis data — skipping", postcode)
return None
elif search_data.get("outcode"):
# Have only outcode — find postcodes in that outcode and use centroid
outcode = search_data["outcode"]
outcode_postcodes = _resolve_outcode_postcodes(outcode, pc_coords)
if outcode_postcodes:
# Use the first postcode as a rough approximation
postcode = outcode_postcodes[0]
lat, lng = pc_coords[postcode]
else:
log.debug("No postcodes found for outcode %s — skipping", outcode)
return None
else:
return None
if not postcode:
log.debug("No postcode for property — skipping")
return None
raw_beds = detail.get("bedrooms") or search_data.get("bedrooms", 0) or 0
raw_baths = detail.get("bathrooms") or search_data.get("bathrooms", 0) or 0
bedrooms = raw_beds if raw_beds <= MAX_BEDROOMS else 0
bathrooms = raw_baths if raw_baths <= MAX_BEDROOMS else 0
if raw_beds > MAX_BEDROOMS or raw_baths > MAX_BEDROOMS:
log.warning(
"OpenRent %s: implausible beds=%d baths=%d (capped to 0)",
search_data.get("id", "?"), raw_beds, raw_baths,
)
# Title: prefer detail page (has h1 with full title)
title = detail.get("title") or search_data.get("title", "")
# Address: take the middle part of the title (skip the "N Bed Type" prefix
# and the outcode suffix). E.g., "1 Bed Flat, Bank Chambers, SW1Y" -> "Bank Chambers"
address = ""
if title:
parts = [p.strip() for p in title.split(",")]
if len(parts) >= 3:
# Skip first (type) and last (outcode), join the middle
address = ", ".join(parts[1:-1])
elif len(parts) == 2:
# Could be "Location, OUTCODE" or "Type, Location"
# If last part looks like an outcode, use the first part
if re.match(r"^[A-Z]{1,2}\d", parts[-1].strip()):
address = parts[0]
else:
address = parts[1]
else:
address = title
# Property type: prefer detail, then search card, then infer from title
property_type = detail.get("property_type") or search_data.get("property_type", "")
if not property_type and title:
property_type = _infer_property_type(title)
prop_id = search_data.get("id", "")
listing_url = search_data.get(
"url",
f"{OPENRENT_BASE}/{prop_id}" if prop_id else "",
)
description = detail.get("description") or search_data.get("description", "")
return {
"id": f"or_{prop_id}",
"Bedrooms": bedrooms,
"Bathrooms": bathrooms,
"Number of bedrooms & living rooms": bedrooms,
"lon": lng,
"lat": lat,
"Postcode": normalize_postcode(postcode),
"Address per Property Register": address,
# OpenRent is a rental-only platform — tenure (Freehold/Leasehold) is a
# property ownership concept that doesn't apply to rental listings. The
# landlord's tenure is not shown on OpenRent listing pages.
"Leasehold/Freehold": None,
"Property type": map_property_type(property_type),
"Property sub-type": normalize_sub_type(property_type),
"price": int(price),
"price_frequency": frequency,
"Price qualifier": "",
"Total floor area (sqm)": parse_floor_area(description),
"Listing URL": listing_url,
"Listing features": [],
"first_visible_date": _parse_or_date(detail.get("available_date", "")),
}
def search_outcode(
client: Session,
outcode: str,
pc_index: PostcodeSpatialIndex,
pc_coords: dict[str, tuple[float, float]],
fetch_details: bool = True,
) -> list[dict]:
"""Search OpenRent for rental properties in one outcode.
1. Fetches the search results page for the outcode
2. Parses property cards from the HTML (title, price, beds, baths)
3. Fetches each property's detail page for coordinates
4. Transforms to common output schema
The search card provides most data (price, bedrooms, bathrooms, title,
property type). Detail pages are needed primarily for precise coordinates
and full postcodes. When detail pages fail, we fall back to outcode-level
coordinates from the postcode lookup.
"""
search_url = f"{OPENRENT_BASE}/properties-to-rent/?term={outcode}&isLive=true"
html = fetch_page(client, search_url)
if not html:
return []
search_results = parse_search_results(html)
if not search_results:
return []
properties = []
for search_data in search_results:
detail_data = None
# Skip detail page if we already have coordinates or a resolvable postcode
has_coords = (
search_data.get("lat") is not None
and search_data.get("lng") is not None
)
has_resolvable_pc = (
search_data.get("postcode")
and pc_coords
and search_data["postcode"] in pc_coords
)
needs_detail = (
fetch_details
and search_data.get("url")
and not has_coords
and not has_resolvable_pc
)
if needs_detail:
detail_html = fetch_page(client, search_data["url"])
if detail_html:
detail_data = parse_property_detail(detail_html)
# Shorter delay for detail pages (within same outcode)
time.sleep(0.15)
transformed = transform_property(
search_data,
detail_data,
pc_index,
pc_coords,
)
if transformed:
properties.append(transformed)
openrent_properties_scraped.labels(channel="rent").inc()
return properties

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@ -1,17 +0,0 @@
[project]
name = "finder"
version = "0.1.0"
requires-python = ">=3.12"
dependencies = [
"flask",
"httpx",
"curl_cffi",
"polars",
"fake-useragent>=2.2.0",
"prometheus-client",
"beautifulsoup4",
"lxml",
"playwright>=1.58.0",
"playwright-stealth>=2.0.2",
"camoufox>=0.4.11",
]

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@ -1,156 +0,0 @@
import logging
import time
import httpx
from constants import (
PAGE_SIZE,
DELAY_BETWEEN_PAGES,
SEARCH_URL,
TYPEAHEAD_URL,
)
from http_client import fetch_with_retry
from spatial import PostcodeSpatialIndex
from transform import transform_property
log = logging.getLogger("rightmove")
# Outcode ID cache (Rightmove typeahead → internal ID)
outcode_cache: dict[str, str] = {}
# Rightmove hard-caps pagination at index 1008 (42 pages × 24 results).
# Requesting index >= 1008 returns HTTP 400.
_MAX_INDEX = 1008
# Property type filters for splitting overcapped searches. Each sub-query
# gets its own 1008 cap, so we can recover listings beyond the unfiltered limit.
_PROPERTY_TYPES = [
"detached", "semi-detached", "terraced", "flat",
"bungalow", "park-home", "land",
]
def resolve_outcode_id(client: httpx.Client, outcode: str) -> str | None:
"""Look up Rightmove's internal ID for an outcode via typeahead API."""
if outcode in outcode_cache:
return outcode_cache[outcode]
data = fetch_with_retry(
client, TYPEAHEAD_URL, {"query": outcode, "limit": "10", "exclude": "STREET"}
)
if not data:
return None
for match in data.get("matches", []):
if match.get("type") == "OUTCODE" and match.get("displayName") == outcode:
rid = str(match["id"])
outcode_cache[outcode] = rid
return rid
log.debug("Outcode %s not found in typeahead results", outcode)
return None
def _paginate(
client: httpx.Client,
outcode_id: str,
outcode: str,
channel_cfg: dict,
pc_index: PostcodeSpatialIndex,
extra_params: dict | None = None,
) -> tuple[list[dict], int]:
"""Paginate through search results. Returns (properties, result_count)."""
properties = []
index = 0
result_count = 0
while True:
params = {
"useLocationIdentifier": "true",
"locationIdentifier": f"OUTCODE^{outcode_id}",
"index": str(index),
"sortType": channel_cfg["sortType"],
"channel": channel_cfg["channel"],
"transactionType": channel_cfg["transactionType"],
}
if extra_params:
params.update(extra_params)
data = fetch_with_retry(client, SEARCH_URL, params)
if not data:
log.warning(
"Failed to fetch index %d for %s/%s",
index,
outcode,
channel_cfg["channel"],
)
break
raw_props = data.get("properties", [])
if not raw_props:
break
for prop in raw_props:
transformed = transform_property(prop, outcode, pc_index)
if transformed:
properties.append(transformed)
# Check if there are more pages
result_count_str = data.get("resultCount", "0")
result_count = int(result_count_str.replace(",", ""))
index += PAGE_SIZE
if index >= result_count:
break
time.sleep(DELAY_BETWEEN_PAGES)
return properties, result_count
def search_outcode(
client: httpx.Client,
outcode_id: str,
outcode: str,
channel_cfg: dict,
pc_index: PostcodeSpatialIndex,
) -> list[dict]:
"""Paginate through search results for one outcode+channel. Returns transformed properties.
When the unfiltered result count exceeds 1008 (Rightmove's hard pagination cap),
re-queries per property type to recover listings beyond the cap.
"""
properties, result_count = _paginate(
client, outcode_id, outcode, channel_cfg, pc_index
)
if result_count <= _MAX_INDEX:
return properties
# Hit the 1008 cap — re-search per property type to get full coverage
ch = channel_cfg["channel"]
log.info(
"%s/%s: %d results exceed %d cap, splitting by property type",
outcode, ch, result_count, _MAX_INDEX,
)
all_by_id: dict[str, dict] = {p["id"]: p for p in properties}
for pt in _PROPERTY_TYPES:
pt_props, _ = _paginate(
client, outcode_id, outcode, channel_cfg, pc_index,
extra_params={"propertyTypes": pt},
)
new = 0
for p in pt_props:
if p["id"] not in all_by_id:
all_by_id[p["id"]] = p
new += 1
if new:
log.debug("%s/%s type=%s: +%d new properties", outcode, ch, pt, new)
log.info(
"%s/%s: type split recovered %d%d properties",
outcode, ch, len(properties), len(all_by_id),
)
return list(all_by_id.values())

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@ -1,52 +0,0 @@
The API works as follows, you must search for outcodes, such as E11, then hit https://los.rightmove.co.uk/typeahead?query=E11&limit=10&exclude=STREET which will return something like:
{
"matches": [
{
"id": "746",
"type": "OUTCODE",
"displayName": "E11",
"highlighting": "<span class='highlightLetter'>E11</span>",
"highlights": [
{
"text": "E11",
"highlighted": true
}
]
},
{
"id": "749",
"type": "OUTCODE",
"displayName": "E14",
"highlighting": "displayName",
"highlights": []
},
{
"id": "752",
"type": "OUTCODE",
"displayName": "E17",
"highlighting": "displayName",
"highlights": []
},
...
]
}
We need to find the id of the object which has "type": "OUTCODE", and displayName matching the outcode we searched for, in this case E11, which is 746. Then we can hit the search endpoint with that id, and it will return the properties for that outcode:
https://www.rightmove.co.uk/api/property-search/listing/search?useLocationIdentifier=true&locationIdentifier=OUTCODE%5E746&buy=For+sale&_includeSSTC=on&index=0&sortType=2&channel=BUY&transactionType=BUY&displayLocationIdentifier=E12.html
You can see the example response to this at [[buy.json]]
You must set locationIdentifier=OUTCODE%5E{id} where id is 746 in this case, so it's 746 locationIdentifier=OUTCODE%5E746. Paging works by increasing index by the number of results per page, which is 24. So the next page would be index=24, then index=48, etc.
The rental endpoint works similarly:
https://www.rightmove.co.uk/api/property-search/listing/search?locationIdentifier=OUTCODE%5E745&index=0&sortType=6&channel=RENT&transactionType=LETTING&displayLocationIdentifier=E16.html
https://www.rightmove.co.uk/api/property-search/listing/search?locationIdentifier=OUTCODE%5E752&index=48&sortType=6&channel=RENT&transactionType=LETTING&displayLocationIdentifier=E17.html
See a response example for the rental endpoint at [[rent.json]]

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import json
import logging
import random
import threading
import time
from concurrent.futures import ThreadPoolExecutor
from dataclasses import dataclass, field
import polars as pl
import httpx
from constants import (
ARCGIS_PATH,
CHANNELS,
CHECKPOINT_INTERVAL,
DATA_DIR,
DELAY_BETWEEN_OUTCODES,
HOMECOUK_CONCURRENCY,
RELOAD_URL,
SCRAPE_HOMECOUK,
SCRAPE_OPENRENT,
SCRAPE_RIGHTMOVE,
SCRAPE_ZOOPLA,
SEED,
)
from homecouk import CookiesExpiredError
from homecouk import load_cookies as load_homecouk_cookies
from homecouk import make_client as make_homecouk_client
from homecouk import search_outcode as homecouk_search_outcode
from http_client import make_client
from metrics import (
cookie_refreshes_total,
cross_source_dedup_total,
homecouk_enabled,
openrent_enabled,
scrape_elapsed_seconds,
scrape_errors_total,
scrape_outcodes_done,
scrape_outcodes_total,
scrape_properties_total,
scrape_state,
zoopla_enabled,
)
from openrent import WafChallengeError
from openrent import load_cookies as load_openrent_cookies
from openrent import make_client as make_openrent_client
from openrent import search_outcode as openrent_search_outcode
from rightmove import resolve_outcode_id, search_outcode
from zoopla import TurnstileError
from zoopla import launch_browser as launch_zoopla_browser
from zoopla import search_outcode as zoopla_search_outcode
from spatial import PostcodeSpatialIndex
from storage import write_parquet
log = logging.getLogger("rightmove")
@dataclass
class ScrapeStatus:
state: str = "idle" # idle | running | done | error
channel: str = ""
outcode: str = ""
outcodes_done: int = 0
outcodes_total: int = 0
properties_buy: int = 0
properties_rent: int = 0
# Per-source counts (combined across channels)
rm_properties: int = 0
hk_properties: int = 0
or_properties: int = 0
zp_properties: int = 0
errors: list[str] = field(default_factory=list)
started_at: float = 0.0
finished_at: float = 0.0
status = ScrapeStatus()
status_lock = threading.Lock()
def _sync_gauges() -> None:
"""Push current ScrapeStatus values into Prometheus gauges. Must hold status_lock."""
for state in ("idle", "running", "done", "error"):
scrape_state.labels(state=state).set(1 if status.state == state else 0)
scrape_outcodes_done.set(status.outcodes_done)
scrape_outcodes_total.set(status.outcodes_total)
scrape_properties_total.labels(channel="buy", source="total").set(
status.properties_buy
)
scrape_properties_total.labels(channel="rent", source="total").set(
status.properties_rent
)
# Per-source totals (across both channels)
for ch in ("buy", "rent"):
scrape_properties_total.labels(channel=ch, source="rightmove").set(
status.rm_properties
)
scrape_properties_total.labels(channel=ch, source="homecouk").set(
status.hk_properties
)
scrape_properties_total.labels(channel=ch, source="openrent").set(
status.or_properties
)
scrape_properties_total.labels(channel=ch, source="zoopla").set(
status.zp_properties
)
if status.started_at:
end = status.finished_at if status.finished_at else time.time()
scrape_elapsed_seconds.set(end - status.started_at)
else:
scrape_elapsed_seconds.set(0)
def load_outcodes() -> list[str]:
"""Load England-only outcodes from arcgis parquet."""
log.info("Loading outcodes from %s", ARCGIS_PATH)
df = pl.read_parquet(ARCGIS_PATH, columns=["pcd", "ctry", "lat", "long"])
england = df.filter(pl.col("ctry") == "E92000001")
log.info("England postcodes: %d", len(england))
outcodes = (
england.select(
pl.col("pcd").str.extract(r"^([A-Z]{1,2}\d[A-Z0-9]?)", 1).alias("outcode")
)
.drop_nulls()
.get_column("outcode")
.unique()
.sort()
.to_list()
)
log.info("Unique England outcodes: %d", len(outcodes))
return outcodes
def build_postcode_index() -> PostcodeSpatialIndex:
"""Build spatial index from arcgis England postcodes."""
log.info("Building postcode spatial index from %s", ARCGIS_PATH)
df = pl.read_parquet(ARCGIS_PATH, columns=["pcd", "ctry", "lat", "long"])
england = df.filter(pl.col("ctry") == "E92000001").drop_nulls(
subset=["lat", "long"]
)
return PostcodeSpatialIndex(
england.get_column("lat").to_list(),
england.get_column("long").to_list(),
england.get_column("pcd").to_list(),
)
def build_postcode_coords() -> dict[str, tuple[float, float]]:
"""Build postcode → (lat, lng) lookup from arcgis England postcodes.
Used by OpenRent scraper to resolve coordinates from postcodes."""
log.info("Building postcode coords lookup from %s", ARCGIS_PATH)
df = pl.read_parquet(ARCGIS_PATH, columns=["pcd", "ctry", "lat", "long"])
england = df.filter(pl.col("ctry") == "E92000001").drop_nulls(
subset=["lat", "long"]
)
coords: dict[str, tuple[float, float]] = {}
for pcd, lat, lng in zip(
england.get_column("pcd").to_list(),
england.get_column("lat").to_list(),
england.get_column("long").to_list(),
):
coords[pcd] = (lat, lng)
log.info("Postcode coords lookup: %d postcodes", len(coords))
return coords
def _fmt_elapsed(seconds: float) -> str:
"""Format seconds as e.g. '2h13m' or '5m32s'."""
h, rem = divmod(int(seconds), 3600)
m, s = divmod(rem, 60)
if h:
return f"{h}h{m:02d}m"
return f"{m}m{s:02d}s"
def _dedup_key(p: dict) -> tuple:
"""Composite key for cross-source deduplication: (postcode, bedrooms, price).
Two listings on different portals for the same physical property will share
these attributes even though their IDs differ."""
return (p.get("Postcode", ""), p.get("Bedrooms", 0), p.get("price", 0))
class _Progress:
"""Thread-safe progress tracker for parallel source workers."""
def __init__(self):
self._counts: dict[str, int] = {}
self._lock = threading.Lock()
def update(self, source: str, done: int) -> None:
with self._lock:
self._counts[source] = done
def snapshot(self) -> dict[str, int]:
with self._lock:
return dict(self._counts)
def _merge_channel(
rm_props: list[dict],
hk_props: list[dict],
or_props: list[dict],
zp_props: list[dict],
) -> tuple[dict[str, dict], dict[str, int], int]:
"""Merge properties from all sources for one channel with cross-source dedup.
Rightmove has priority; other sources are checked for duplicates.
Returns (all_properties_by_id, per_source_counts, total_dedup_count).
"""
all_properties: dict[str, dict] = {}
seen_keys: set[tuple] = set()
counts = {"rm": 0, "hk": 0, "or": 0, "zp": 0}
total_dedup = 0
# Rightmove first (priority source)
for p in rm_props:
pid = p["id"]
if pid not in all_properties:
all_properties[pid] = p
seen_keys.add(_dedup_key(p))
counts["rm"] += 1
# Other sources (check for cross-source duplicates)
for source, props in [("hk", hk_props), ("or", or_props), ("zp", zp_props)]:
for p in props:
pid = p["id"]
key = _dedup_key(p)
if pid in all_properties or key in seen_keys:
total_dedup += 1
continue
all_properties[pid] = p
seen_keys.add(key)
counts[source] += 1
return all_properties, counts, total_dedup
# ---------------------------------------------------------------------------
# Checkpointing — save/resume partial results across crashes
# ---------------------------------------------------------------------------
def _checkpoint_meta_path():
return DATA_DIR / "checkpoint.json"
def _checkpoint_results_path(source: str, channel: str):
return DATA_DIR / f"checkpoint_{source}_{channel}.json"
def _save_checkpoint(
shuffled: list[str],
progress: _Progress,
source_results: dict[str, dict[str, list]],
active_sources: list[str],
) -> None:
"""Save per-source progress indices and partial results to disk.
Writes atomically (temp + rename) so a crash mid-write leaves the previous
checkpoint intact.
"""
snap = progress.snapshot()
meta = {
"seed": SEED,
"num_outcodes": len(shuffled),
"sources": {s: snap.get(s, 0) for s in active_sources},
"timestamp": time.time(),
}
# Write result files per source per channel
for source in active_sources:
results = source_results.get(source, {})
for ch_key in ("BUY", "RENT"):
props = results.get(ch_key, [])
path = _checkpoint_results_path(source, ch_key.lower())
tmp = path.with_suffix(".tmp")
try:
with open(tmp, "w") as f:
json.dump(props, f, default=str)
tmp.rename(path)
except Exception as e:
log.warning("Failed to write checkpoint %s: %s", path.name, e)
# Write metadata atomically
tmp = _checkpoint_meta_path().with_suffix(".tmp")
try:
with open(tmp, "w") as f:
json.dump(meta, f)
tmp.rename(_checkpoint_meta_path())
except Exception as e:
log.warning("Failed to write checkpoint metadata: %s", e)
return
total = sum(len(source_results.get(s, {}).get(ch, []))
for s in active_sources for ch in ("BUY", "RENT"))
log.info(
"Checkpoint saved: %s (%d properties)",
{s: snap.get(s, 0) for s in active_sources},
total,
)
def _load_checkpoint(
shuffled: list[str],
) -> tuple[dict[str, int], dict[str, dict[str, list]]] | None:
"""Load checkpoint if it exists and matches the current outcode list.
Returns (start_indices, loaded_results) or None if no valid checkpoint.
"""
path = _checkpoint_meta_path()
if not path.exists():
return None
try:
with open(path) as f:
meta = json.load(f)
except Exception:
log.warning("Checkpoint file corrupt, starting fresh")
_clear_checkpoint()
return None
if meta.get("seed") != SEED or meta.get("num_outcodes") != len(shuffled):
log.info("Checkpoint from different run configuration, discarding")
_clear_checkpoint()
return None
start_indices: dict[str, int] = {}
loaded_results: dict[str, dict[str, list]] = {}
for source, completed in meta.get("sources", {}).items():
start_indices[source] = completed
loaded_results[source] = {"BUY": [], "RENT": []}
for channel in ("buy", "rent"):
rpath = _checkpoint_results_path(source, channel)
if rpath.exists():
try:
with open(rpath) as f:
raw = json.load(f)
# Deduplicate by ID — concurrent workers (e.g. hk_worker's
# ThreadPoolExecutor) can cause in-flight outcodes to have
# results saved before their progress index is recorded.
# On resume those outcodes get re-scraped, duplicating results.
seen_ids: set[str] = set()
deduped: list[dict] = []
for p in raw:
pid = p.get("id")
if pid not in seen_ids:
seen_ids.add(pid)
deduped.append(p)
if len(deduped) < len(raw):
log.info(
"Checkpoint %s/%s: deduped %d%d (removed %d dupes)",
source, channel, len(raw), len(deduped),
len(raw) - len(deduped),
)
loaded_results[source][channel.upper()] = deduped
except Exception:
log.warning(
"Checkpoint results for %s/%s corrupt, restarting %s",
source, channel, source,
)
start_indices[source] = 0
loaded_results[source] = {"BUY": [], "RENT": []}
break
elapsed_since = time.time() - meta.get("timestamp", 0)
log.info(
"Resuming from checkpoint (saved %.0fm ago): %s",
elapsed_since / 60,
start_indices,
)
return start_indices, loaded_results
def _clear_checkpoint() -> None:
"""Remove all checkpoint files after successful completion."""
for path in DATA_DIR.glob("checkpoint*"):
try:
path.unlink()
except Exception:
pass
def run_scrape(
outcodes: list[str],
pc_index: PostcodeSpatialIndex,
pc_coords: dict[str, tuple[float, float]] | None = None,
) -> None:
"""Main scrape orchestrator — runs all sources in parallel threads.
Each source (Rightmove, home.co.uk, OpenRent, Zoopla) gets its own thread
that iterates all outcodes for both BUY and RENT channels. Results are
merged with cross-source deduplication after all workers complete.
"""
global status
with status_lock:
status.state = "running"
status.started_at = time.time()
status.finished_at = 0.0
status.errors = []
status.properties_buy = 0
status.properties_rent = 0
status.channel = ""
status.outcode = ""
_sync_gauges()
shuffled = list(outcodes)
random.seed(SEED)
random.shuffle(shuffled)
if not any([SCRAPE_RIGHTMOVE, SCRAPE_HOMECOUK, SCRAPE_OPENRENT, SCRAPE_ZOOPLA]):
log.warning("All scrapers disabled — nothing to do")
with status_lock:
status.state = "done"
status.finished_at = time.time()
_sync_gauges()
return
if not SCRAPE_RIGHTMOVE:
log.info("Rightmove scraping DISABLED (SCRAPE_RIGHTMOVE=false)")
if not SCRAPE_HOMECOUK:
log.info("home.co.uk scraping DISABLED (SCRAPE_HOMECOUK=false)")
homecouk_enabled.set(0)
if not SCRAPE_OPENRENT:
log.info("OpenRent scraping DISABLED (SCRAPE_OPENRENT=false)")
openrent_enabled.set(0)
if not SCRAPE_ZOOPLA:
log.info("Zoopla scraping DISABLED (SCRAPE_ZOOPLA=false)")
zoopla_enabled.set(0)
# Build postcode coords if needed for OpenRent/Zoopla
if (SCRAPE_OPENRENT or SCRAPE_ZOOPLA) and pc_coords is None:
pc_coords = build_postcode_coords()
# Per-source result containers: {channel_name: [properties]}
# Each list is only written by its owning source thread.
rm_results: dict[str, list] = {"BUY": [], "RENT": []}
hk_results: dict[str, list] = {"BUY": [], "RENT": []}
or_results: dict[str, list] = {"BUY": [], "RENT": []}
zp_results: dict[str, list] = {"BUY": [], "RENT": []}
progress = _Progress()
# --- Resume from checkpoint if available ---
start_indices: dict[str, int] = {}
checkpoint = _load_checkpoint(shuffled)
if checkpoint:
start_indices, loaded = checkpoint
source_to_results = {"rm": rm_results, "hk": hk_results, "or": or_results, "zp": zp_results}
for src, data in loaded.items():
if src in source_to_results:
for ch in ("BUY", "RENT"):
source_to_results[src][ch] = data.get(ch, [])
# Reassign in case references changed
rm_results = source_to_results["rm"]
hk_results = source_to_results["hk"]
or_results = source_to_results["or"]
zp_results = source_to_results["zp"]
# Pre-set progress for resumed sources
for src, idx in start_indices.items():
if idx > 0:
progress.update(src, idx)
# --- Source worker closures ---
# Each worker owns its client lifecycle and iterates all outcodes for both
# channels. On auth failure, it refreshes cookies and continues. On fatal
# failure, it marks itself as done and returns partial results.
def rm_worker():
rm_start = start_indices.get("rm", 0)
if rm_start > 0:
log.info("Rightmove resuming from outcode %d/%d", rm_start, len(shuffled))
client = make_client()
try:
for i, outcode in enumerate(shuffled):
if i < rm_start:
continue
try:
outcode_id = resolve_outcode_id(client, outcode)
except Exception as e:
log.error("Rightmove %s ID lookup: %s", outcode, e)
scrape_errors_total.labels(source="rightmove").inc()
progress.update("rm", i + 1)
time.sleep(DELAY_BETWEEN_OUTCODES)
continue
if not outcode_id:
log.debug("No Rightmove ID for %s, skipping", outcode)
progress.update("rm", i + 1)
time.sleep(DELAY_BETWEEN_OUTCODES)
continue
for ch_cfg in CHANNELS:
ch = ch_cfg["channel"]
try:
props = search_outcode(
client, outcode_id, outcode, ch_cfg, pc_index
)
rm_results[ch].extend(props)
except Exception as e:
log.error("Rightmove %s/%s: %s", outcode, ch, e)
scrape_errors_total.labels(source="rightmove").inc()
progress.update("rm", i + 1)
time.sleep(DELAY_BETWEEN_OUTCODES)
except Exception as e:
log.exception("Fatal Rightmove error: %s", e)
with status_lock:
status.errors.append(f"Fatal Rightmove: {e}")
finally:
client.close()
def hk_worker():
hk_result = load_homecouk_cookies()
if not hk_result:
log.info("home.co.uk DISABLED (no cookies available)")
homecouk_enabled.set(0)
progress.update("hk", len(shuffled))
return
hk_start = start_indices.get("hk", 0)
if hk_start > 0:
log.info("home.co.uk resuming from outcode %d/%d", hk_start, len(shuffled))
log.info(
"home.co.uk scraping ENABLED (concurrency=%d)", HOMECOUK_CONCURRENCY
)
homecouk_enabled.set(1)
# Shared state across pool threads
cookie_state = {
"cookies": hk_result[0],
"user_agent": hk_result[1],
"generation": 0,
}
cookie_lock = threading.Lock()
results_lock = threading.Lock()
completed_count = [hk_start]
disabled = [False]
_local = threading.local()
def _get_client():
"""Get or create a thread-local curl_cffi session."""
with cookie_lock:
gen = cookie_state["generation"]
cookies = cookie_state["cookies"]
ua = cookie_state["user_agent"]
if not hasattr(_local, "client") or _local.gen != gen:
if hasattr(_local, "client"):
try:
_local.client.close()
except Exception:
pass
_local.client = make_homecouk_client(cookies, ua)
_local.gen = gen
return _local.client
def _refresh_cookies():
"""Refresh cookies via FlareSolverr. Thread-safe with generation check."""
with cookie_lock:
pre_gen = cookie_state["generation"]
new = load_homecouk_cookies()
if not new:
return False
with cookie_lock:
if cookie_state["generation"] == pre_gen:
cookie_state["cookies"] = new[0]
cookie_state["user_agent"] = new[1]
cookie_state["generation"] += 1
cookie_refreshes_total.labels(result="success").inc()
log.info("home.co.uk cookies refreshed")
return True
def _scrape_outcode(outcode):
if disabled[0]:
return
client = _get_client()
for ch_cfg in CHANNELS:
ch = ch_cfg["channel"]
if disabled[0]:
return
try:
props = homecouk_search_outcode(
client, outcode, ch, pc_index
)
if props:
with results_lock:
hk_results[ch].extend(props)
log.info(
"home.co.uk %s: +%d properties", outcode, len(props)
)
except CookiesExpiredError:
log.warning(
"home.co.uk cookies expired — attempting refresh"
)
if _refresh_cookies():
client = _get_client()
try:
props = homecouk_search_outcode(
client, outcode, ch, pc_index
)
if props:
with results_lock:
hk_results[ch].extend(props)
log.info(
"home.co.uk %s: +%d properties",
outcode,
len(props),
)
except Exception as e:
log.error(
"home.co.uk %s/%s (after refresh): %s",
outcode,
ch,
e,
)
scrape_errors_total.labels(source="homecouk").inc()
else:
log.warning(
"Cookie refresh failed, disabling home.co.uk"
)
disabled[0] = True
homecouk_enabled.set(0)
cookie_refreshes_total.labels(result="failure").inc()
with status_lock:
status.errors.append(
"home.co.uk cookies expired and refresh failed"
)
return
except Exception as e:
log.error("home.co.uk %s/%s: %s", outcode, ch, e)
scrape_errors_total.labels(source="homecouk").inc()
with results_lock:
completed_count[0] += 1
progress.update("hk", completed_count[0])
time.sleep(DELAY_BETWEEN_OUTCODES)
try:
work = [oc for i, oc in enumerate(shuffled) if i >= hk_start]
with ThreadPoolExecutor(
max_workers=HOMECOUK_CONCURRENCY
) as pool:
list(pool.map(_scrape_outcode, work))
except Exception as e:
log.exception("Fatal home.co.uk error: %s", e)
with status_lock:
status.errors.append(f"Fatal home.co.uk: {e}")
if disabled[0]:
progress.update("hk", len(shuffled))
def or_worker():
or_result = load_openrent_cookies()
if not or_result:
log.info("OpenRent DISABLED (no cookies available)")
openrent_enabled.set(0)
progress.update("or", len(shuffled))
return
or_start = start_indices.get("or", 0)
if or_start > 0:
log.info("OpenRent resuming from outcode %d/%d", or_start, len(shuffled))
client = make_openrent_client(*or_result)
log.info("OpenRent scraping ENABLED")
openrent_enabled.set(1)
try:
for i, outcode in enumerate(shuffled):
if i < or_start:
continue
# OpenRent is RENT-only
try:
props = openrent_search_outcode(
client, outcode, pc_index, pc_coords
)
or_results["RENT"].extend(props)
if props:
log.info("OpenRent %s: +%d properties", outcode, len(props))
except WafChallengeError:
log.warning(
"OpenRent WAF cookies expired — attempting refresh"
)
client.close()
or_new = load_openrent_cookies()
if or_new:
client = make_openrent_client(*or_new)
log.info("OpenRent cookies refreshed, continuing")
cookie_refreshes_total.labels(result="success").inc()
else:
log.warning(
"Cookie refresh failed, disabling OpenRent"
)
openrent_enabled.set(0)
cookie_refreshes_total.labels(result="failure").inc()
with status_lock:
status.errors.append(
"OpenRent WAF cookies expired and refresh failed"
)
progress.update("or", len(shuffled))
return
except Exception as e:
log.error("OpenRent %s: %s", outcode, e)
scrape_errors_total.labels(source="openrent").inc()
progress.update("or", i + 1)
time.sleep(DELAY_BETWEEN_OUTCODES)
except Exception as e:
log.exception("Fatal OpenRent error: %s", e)
with status_lock:
status.errors.append(f"Fatal OpenRent: {e}")
finally:
try:
client.close()
except Exception:
pass
def zp_worker():
try:
browser, page = launch_zoopla_browser()
log.info("Zoopla scraping ENABLED (Camoufox browser launched)")
zoopla_enabled.set(1)
except TurnstileError:
log.warning("Zoopla Cloudflare Turnstile failed — disabling Zoopla")
zoopla_enabled.set(0)
progress.update("zp", len(shuffled))
return
except Exception as e:
log.warning("Zoopla browser launch failed: %s — disabling Zoopla", e)
zoopla_enabled.set(0)
progress.update("zp", len(shuffled))
return
zp_start = start_indices.get("zp", 0)
if zp_start > 0:
log.info("Zoopla resuming from outcode %d/%d", zp_start, len(shuffled))
try:
for i, outcode in enumerate(shuffled):
if i < zp_start:
continue
search_url = None
for ch_cfg in CHANNELS:
ch = ch_cfg["channel"]
# Build direct URL for second channel by swapping path
direct_url = None
if search_url:
if ch == "BUY":
direct_url = search_url.replace("/to-rent/", "/for-sale/")
else:
direct_url = search_url.replace("/for-sale/", "/to-rent/")
try:
props, result_url = zoopla_search_outcode(
page, outcode, ch, pc_index, pc_coords,
base_search_url=direct_url,
)
if result_url:
search_url = result_url
zp_results[ch].extend(props)
if props:
log.info("Zoopla %s: +%d properties", outcode, len(props))
except TurnstileError:
log.warning(
"Zoopla Turnstile challenge — relaunching browser"
)
try:
browser.close()
except Exception:
pass
try:
browser, page = launch_zoopla_browser()
log.info("Zoopla browser relaunched, continuing")
except Exception:
log.warning(
"Browser relaunch failed, disabling Zoopla"
)
zoopla_enabled.set(0)
with status_lock:
status.errors.append(
"Zoopla Cloudflare challenge failed and relaunch failed"
)
progress.update("zp", len(shuffled))
return
except Exception as e:
log.error("Zoopla %s/%s: %s", outcode, ch, e)
scrape_errors_total.labels(source="zoopla").inc()
progress.update("zp", i + 1)
time.sleep(DELAY_BETWEEN_OUTCODES)
except Exception as e:
log.exception("Fatal Zoopla error: %s", e)
with status_lock:
status.errors.append(f"Fatal Zoopla: {e}")
finally:
try:
browser.close()
except Exception:
pass
# --- Launch worker threads ---
active_sources: list[str] = []
threads: list[threading.Thread] = []
if SCRAPE_RIGHTMOVE:
threads.append(threading.Thread(target=rm_worker, name="scrape-rm", daemon=True))
active_sources.append("rm")
if SCRAPE_HOMECOUK:
threads.append(threading.Thread(target=hk_worker, name="scrape-hk", daemon=True))
active_sources.append("hk")
if SCRAPE_OPENRENT:
threads.append(threading.Thread(target=or_worker, name="scrape-or", daemon=True))
active_sources.append("or")
if SCRAPE_ZOOPLA:
threads.append(threading.Thread(target=zp_worker, name="scrape-zp", daemon=True))
active_sources.append("zp")
log.info(
"=== Starting scrape: %d outcodes, sources: %s ===",
len(shuffled),
", ".join(active_sources),
)
for t in threads:
t.start()
# --- Monitor progress while workers run ---
# Map source names to result dicts for checkpointing
source_results_map = {
"rm": rm_results, "hk": hk_results,
"or": or_results, "zp": zp_results,
}
scrape_start = time.time()
last_log = 0.0
last_checkpoint = time.time()
try:
while any(t.is_alive() for t in threads):
snap = progress.snapshot()
min_done = min(
(snap.get(s, 0) for s in active_sources), default=0
)
# Count properties across sources (safe: only one thread writes each list)
total_buy = sum(
len(r["BUY"]) for r in [rm_results, hk_results, or_results, zp_results]
)
total_rent = sum(
len(r["RENT"]) for r in [rm_results, hk_results, or_results, zp_results]
)
with status_lock:
status.outcodes_done = min_done
status.outcodes_total = len(shuffled)
status.properties_buy = total_buy
status.properties_rent = total_rent
status.rm_properties = len(rm_results["BUY"]) + len(rm_results["RENT"])
status.hk_properties = len(hk_results["BUY"]) + len(hk_results["RENT"])
status.or_properties = len(or_results["RENT"])
status.zp_properties = len(zp_results["BUY"]) + len(zp_results["RENT"])
_sync_gauges()
now = time.time()
# Log progress every 30 seconds
if now - last_log >= 30:
elapsed = now - scrape_start
per_source = ", ".join(
f"{s}:{snap.get(s, 0)}" for s in active_sources
)
log.info(
"Progress: %d/%d outcodes (%s), %d buy + %d rent props, %s elapsed",
min_done,
len(shuffled),
per_source,
total_buy,
total_rent,
_fmt_elapsed(elapsed),
)
last_log = now
# Save checkpoint periodically
if now - last_checkpoint >= CHECKPOINT_INTERVAL:
try:
_save_checkpoint(
shuffled, progress, source_results_map, active_sources,
)
except Exception as e:
log.warning("Checkpoint save failed: %s", e)
last_checkpoint = now
time.sleep(5)
except Exception as e:
log.exception("Monitor loop error: %s", e)
# Save final checkpoint before joining (in case merge/write fails)
try:
_save_checkpoint(shuffled, progress, source_results_map, active_sources)
except Exception:
pass
for t in threads:
t.join()
log.info("All source workers completed")
# --- Merge results per channel and write parquet ---
try:
for ch_cfg in CHANNELS:
ch = ch_cfg["channel"]
file_suffix = "buy" if ch == "BUY" else "rent"
merged, counts, total_dedup = _merge_channel(
rm_results[ch],
hk_results[ch],
or_results[ch],
zp_results[ch],
)
# Update cross-source dedup counter
ch_label = "buy" if ch == "BUY" else "rent"
if total_dedup:
cross_source_dedup_total.labels(channel=ch_label).inc(total_dedup)
deduped = list(merged.values())
output_path = DATA_DIR / f"online_listings_{file_suffix}.parquet"
write_parquet(deduped, output_path, channel=file_suffix)
with status_lock:
if ch == "BUY":
status.properties_buy = len(deduped)
else:
status.properties_rent = len(deduped)
_sync_gauges()
log.info(
"=== %s complete: %d unique (rm:%d hk:%d or:%d zp:%d, cross-dedup:%d) ===",
ch,
len(deduped),
counts["rm"],
counts["hk"],
counts["or"],
counts["zp"],
total_dedup,
)
# Scrape completed successfully — clear checkpoint
_clear_checkpoint()
with status_lock:
status.state = "done"
status.finished_at = time.time()
status.outcodes_done = len(shuffled)
_sync_gauges()
elapsed = status.finished_at - status.started_at
log.info(
"Scrape complete in %s — buy: %d, rent: %d",
_fmt_elapsed(elapsed),
status.properties_buy,
status.properties_rent,
)
# Trigger server data reload
if RELOAD_URL:
try:
log.info("Triggering server reload at %s", RELOAD_URL)
resp = httpx.post(RELOAD_URL, timeout=300)
if resp.is_success:
body = resp.json()
log.info(
"Server reload complete: %d rows, %d features, %dms",
body.get("rows", 0),
body.get("features", 0),
body.get("elapsed_ms", 0),
)
else:
log.warning(
"Server reload failed (%d): %s",
resp.status_code,
resp.text[:200],
)
except Exception as e:
log.warning("Server reload request failed: %s", e)
except Exception as e:
log.exception("Fatal scrape error during merge/write")
with status_lock:
status.state = "error"
status.errors.append(f"Fatal: {e}")
status.finished_at = time.time()
_sync_gauges()

View file

@ -1,37 +0,0 @@
import logging
import math
from collections import defaultdict
from constants import GRID_CELL_SIZE
log = logging.getLogger("rightmove")
class PostcodeSpatialIndex:
"""Grid-based spatial index over arcgis postcodes for nearest-lookup."""
def __init__(self, lats: list[float], lngs: list[float], postcodes: list[str]):
self.grid: dict[tuple[int, int], list[tuple[float, float, str]]] = defaultdict(
list
)
for lat, lng, pcd in zip(lats, lngs, postcodes):
gx = int(math.floor(lng / GRID_CELL_SIZE))
gy = int(math.floor(lat / GRID_CELL_SIZE))
self.grid[(gx, gy)].append((lat, lng, pcd))
log.info(
"Postcode spatial index: %d cells, %d postcodes", len(self.grid), len(lats)
)
def nearest(self, lat: float, lng: float) -> str | None:
gx = int(math.floor(lng / GRID_CELL_SIZE))
gy = int(math.floor(lat / GRID_CELL_SIZE))
best_dist = float("inf")
best_pcd = None
for dx in range(-1, 2):
for dy in range(-1, 2):
for plat, plng, pcd in self.grid.get((gx + dx, gy + dy), []):
d = (plat - lat) ** 2 + (plng - lng) ** 2
if d < best_dist:
best_dist = d
best_pcd = pcd
return best_pcd

View file

@ -1,183 +0,0 @@
import logging
from datetime import datetime
from pathlib import Path
import polars as pl
from constants import MAX_BEDROOMS, MAX_RENT_MONTHLY, MIN_RENT_MONTHLY
from transform import map_property_type, normalize_postcode, normalize_price
log = logging.getLogger("rightmove")
def write_parquet(properties: list[dict], path: Path, channel: str) -> None:
"""Write properties list to parquet with server-ready column names.
channel: "buy" or "rent"
"""
if not properties:
log.warning("No properties to write to %s", path)
return
# Sanitize bedroom/bathroom counts — values above MAX_BEDROOMS are
# almost certainly prices or other numeric fields mis-parsed as bedrooms.
bad_count = 0
for p in properties:
for key in ("Bedrooms", "Bathrooms"):
val = p.get(key, 0) or 0
if val > MAX_BEDROOMS:
bad_count += 1
p[key] = None
# Recompute derived field after sanitization
beds = p.get("Bedrooms")
baths = p.get("Bathrooms")
if beds is None or baths is None:
p["Number of bedrooms & living rooms"] = None
else:
p["Number of bedrooms & living rooms"] = beds + baths
if bad_count:
log.warning(
"Sanitized %d properties with bedroom/bathroom counts > %d (set to null)",
bad_count,
MAX_BEDROOMS,
)
# Re-derive Property type from Property sub-type using current PROPERTY_TYPE_MAP.
# This retroactively fixes data scraped with older versions of the type map.
remapped = 0
for p in properties:
sub_type = p.get("Property sub-type", "")
if sub_type and sub_type != "Unknown":
new_type = map_property_type(sub_type)
if new_type != p.get("Property type"):
p["Property type"] = new_type
remapped += 1
if remapped:
log.info("Re-mapped %d property types from sub-types", remapped)
# Parse first_visible_date to datetime
listing_dates = []
for p in properties:
fvd = p.get("first_visible_date", "")
if fvd:
try:
dt = datetime.fromisoformat(fvd.replace("Z", "+00:00"))
# Convert to UTC naive datetime for consistent storage
if dt.tzinfo is not None:
from datetime import timezone
dt = dt.astimezone(timezone.utc).replace(tzinfo=None)
listing_dates.append(dt)
except (ValueError, TypeError):
# Try additional date formats (OpenRent: "DD Month, YYYY", "Today")
parsed = None
stripped = fvd.strip()
lower = stripped.lower()
if lower == "today":
parsed = datetime.now().replace(
hour=0, minute=0, second=0, microsecond=0
)
elif lower == "tomorrow":
from datetime import timedelta
parsed = (
datetime.now() + timedelta(days=1)
).replace(hour=0, minute=0, second=0, microsecond=0)
else:
for fmt in ("%d %B, %Y", "%d %B %Y"):
try:
parsed = datetime.strptime(stripped, fmt)
break
except ValueError:
continue
listing_dates.append(parsed)
else:
listing_dates.append(None)
# Derive asking price / asking rent based on channel
# Zero prices indicate parsing failures or POA/auction listings — treat as null
if channel == "buy":
asking_prices = [p["price"] if p["price"] > 0 else None for p in properties]
asking_rents = [None] * len(properties)
listing_statuses = ["For sale"] * len(properties)
else:
asking_prices = [None] * len(properties)
# Normalize to monthly, then apply sanity bounds. Rents outside
# [MIN_RENT_MONTHLY, MAX_RENT_MONTHLY] are almost always total-stay
# pricing (short lets), annual rents mislabelled as monthly, or £0
# placeholders — null them out rather than polluting aggregates.
rent_outliers = 0
asking_rents = []
for p in properties:
monthly = normalize_price(p["price"], p["price_frequency"])
if monthly < MIN_RENT_MONTHLY or monthly > MAX_RENT_MONTHLY:
rent_outliers += 1
asking_rents.append(None)
else:
asking_rents.append(monthly)
if rent_outliers:
log.warning(
"Nulled %d rent outliers outside [£%d, £%d]/month",
rent_outliers,
MIN_RENT_MONTHLY,
MAX_RENT_MONTHLY,
)
listing_statuses = ["For rent"] * len(properties)
df = pl.DataFrame(
{
"Bedrooms": [p["Bedrooms"] for p in properties],
"Bathrooms": [p["Bathrooms"] for p in properties],
"Number of bedrooms & living rooms": [
p["Number of bedrooms & living rooms"] for p in properties
],
"lon": [p["lon"] for p in properties],
"lat": [p["lat"] for p in properties],
"Postcode": [normalize_postcode(p["Postcode"]) for p in properties],
"Address per Property Register": [
p["Address per Property Register"] for p in properties
],
"Leasehold/Freehold": [p["Leasehold/Freehold"] for p in properties],
"Property type": [p["Property type"] for p in properties],
"Property sub-type": [p["Property sub-type"] for p in properties],
"Price qualifier": [p["Price qualifier"] for p in properties],
"Total floor area (sqm)": [p["Total floor area (sqm)"] for p in properties],
"Listing URL": [p["Listing URL"] for p in properties],
"Listing features": [p["Listing features"] for p in properties],
"Listing date": listing_dates,
"Listing status": listing_statuses,
"Asking price": asking_prices,
"Asking rent (monthly)": asking_rents,
},
schema={
"Bedrooms": pl.Int32,
"Bathrooms": pl.Int32,
"Number of bedrooms & living rooms": pl.Int32,
"lon": pl.Float64,
"lat": pl.Float64,
"Postcode": pl.Utf8,
"Address per Property Register": pl.Utf8,
"Leasehold/Freehold": pl.Utf8,
"Property type": pl.Utf8,
"Property sub-type": pl.Utf8,
"Price qualifier": pl.Utf8,
"Total floor area (sqm)": pl.Float64,
"Listing URL": pl.Utf8,
"Listing features": pl.List(pl.Utf8),
"Listing date": pl.Datetime("us"),
"Listing status": pl.Utf8,
"Asking price": pl.Int64,
"Asking rent (monthly)": pl.Int64,
},
)
# Derive asking price per sqm for buy listings
if channel == "buy":
df = df.with_columns(
(pl.col("Asking price") / pl.col("Total floor area (sqm)"))
.round(0)
.cast(pl.Int32, strict=False)
.alias("Asking price per sqm"),
)
df.write_parquet(path)
log.info("Wrote %d properties to %s", len(df), path)

View file

@ -1,230 +0,0 @@
import logging
import re
from constants import MAX_BEDROOMS, PROPERTY_TYPE_MAP, RIGHTMOVE_BASE
from spatial import PostcodeSpatialIndex
log = logging.getLogger("rightmove")
# Floor area bounds (sqm). Values outside this range are almost certainly
# data errors: sub-5 sqm catches garbled extractions (e.g., 0.1 sqm for a
# detached house), and >2000 sqm (~21,500 sq ft) exceeds even the largest
# UK mansions.
MIN_FLOOR_AREA_SQM = 5.0
MAX_FLOOR_AREA_SQM = 2000.0
def validate_floor_area(sqm: float | None) -> float | None:
"""Validate a floor area value. Returns None for nonsensical values.
Rejects values below MIN_FLOOR_AREA_SQM and above MAX_FLOOR_AREA_SQM,
which catches parsing errors where prices or other large numbers are
mistakenly extracted as floor area from free-text descriptions or DOM text.
"""
if sqm is None:
return None
if sqm < MIN_FLOOR_AREA_SQM or sqm > MAX_FLOOR_AREA_SQM:
return None
return sqm
def parse_display_size(display_size: str | None) -> float | None:
"""Parse displaySize like '499 sq. ft.' or '4,124 sq. ft.' to sqm."""
if not display_size:
return None
# Try sq. ft. first
m = re.search(r"([\d,]+(?:\.\d+)?)\s*sq\.?\s*ft", display_size, re.IGNORECASE)
if m:
sqft = float(m.group(1).replace(",", ""))
return validate_floor_area(round(sqft * 0.092903, 1))
# Try sq. m.
m = re.search(r"([\d,]+(?:\.\d+)?)\s*sq\.?\s*m", display_size, re.IGNORECASE)
if m:
return validate_floor_area(round(float(m.group(1).replace(",", "")), 1))
return None
def normalize_sub_type(sub_type: str | None) -> str:
"""Normalize property sub-type for consistent storage.
Fixes delimiter inconsistencies (underscores/hyphens spaces) from
home.co.uk and truncates Zoopla description fragments that were
accidentally captured as sub-types.
"""
if not sub_type:
return "Unknown"
cleaned = sub_type.replace("_", " ").strip()
# Description fragments captured as sub-types are much longer than any
# real property type name (longest canonical is ~25 chars)
if len(cleaned) > 40:
return "Unknown"
# Collapse multiple spaces
cleaned = re.sub(r"\s+", " ", cleaned)
return cleaned.title()
def map_property_type(sub_type: str | None) -> str:
"""Map propertySubType to canonical type."""
if not sub_type:
return "Other"
canonical = PROPERTY_TYPE_MAP.get(sub_type)
if canonical:
return canonical
# Try title-case variant (e.g., "country house" → "Country House")
canonical = PROPERTY_TYPE_MAP.get(sub_type.title())
if canonical:
return canonical
# Try lowercase variant (e.g., "Townhouse" → "townhouse")
canonical = PROPERTY_TYPE_MAP.get(sub_type.lower())
if canonical:
return canonical
# Normalize delimiters (underscores/hyphens → spaces) and try again
normalized = re.sub(r"[-_]+", " ", sub_type).strip().title()
canonical = PROPERTY_TYPE_MAP.get(normalized)
if canonical:
return canonical
# Keyword fallback for compound types not in the map
lower = sub_type.lower()
if "flat" in lower or "apartment" in lower or "maisonette" in lower or "studio" in lower:
return "Flats/Maisonettes"
if "semi" in lower and "detach" in lower:
return "Semi-Detached"
if "detach" in lower:
return "Detached"
if "terrace" in lower or "mews" in lower:
return "Terraced"
if "house" in lower or "cottage" in lower:
return "Detached"
log.warning("Unknown propertySubType: %r — mapping to Other", sub_type)
return "Other"
def extract_tenure(tenure_obj: dict | None) -> str | None:
"""Extract tenure string from tenure object."""
if not tenure_obj:
return None
tt = tenure_obj.get("tenureType", "")
if tt == "FREEHOLD":
return "Freehold"
if tt == "LEASEHOLD":
return "Leasehold"
return None
def fix_coords(lat: float, lng: float) -> tuple[float, float]:
"""Swap lat/lng if they look reversed. England: lat ~4956, lng ~-72."""
if 49 <= lat <= 56 and -7 <= lng <= 2:
return lat, lng
if 49 <= lng <= 56 and -7 <= lat <= 2:
log.debug(
"Swapping reversed coords: lat=%.4f lng=%.4f → lat=%.4f lng=%.4f",
lat,
lng,
lng,
lat,
)
return lng, lat
log.warning(
"Coords outside England bounds even after swap attempt: lat=%.4f lng=%.4f",
lat,
lng,
)
return lat, lng
def normalize_postcode(postcode: str) -> str:
"""Ensure UK postcode has exactly one space before the 3-char incode.
E.g., 'SW1A1AA' 'SW1A 1AA', 'N4 2HA' 'N4 2HA', 'E1 4AB' unchanged."""
# Strip all whitespace then re-insert the single canonical space
compact = re.sub(r"\s+", "", postcode).upper()
if len(compact) < 5:
return compact
return compact[:-3] + " " + compact[-3:]
def normalize_price(amount: int, frequency: str) -> int:
"""Normalise price to monthly for rentals (weekly × 52/12, yearly ÷ 12)."""
if frequency == "weekly":
return round(amount * 52 / 12)
if frequency == "yearly":
return round(amount / 12)
return amount
def transform_property(
prop: dict, outcode: str, pc_index: PostcodeSpatialIndex
) -> dict | None:
"""Transform a raw Rightmove property dict into our output schema."""
loc = prop.get("location")
if not loc:
return None
raw_lat = loc.get("latitude")
raw_lng = loc.get("longitude")
if raw_lat is None or raw_lng is None:
return None
lat, lng = fix_coords(raw_lat, raw_lng)
price_obj = prop.get("price", {})
amount = price_obj.get("amount")
if not amount:
return None
frequency = price_obj.get("frequency", "")
# Store raw price — normalization to monthly happens once in storage.py
price = int(amount)
if price <= 0:
return None
display_prices = price_obj.get("displayPrices", [])
price_qualifier = (
display_prices[0].get("displayPriceQualifier", "") if display_prices else ""
)
# POA / Auction listings have unreliable prices — treat as no price
pq_lower = price_qualifier.lower()
if "poa" in pq_lower or "auction" in pq_lower:
return None
sub_type = prop.get("propertySubType", "")
raw_beds = prop.get("bedrooms", 0) or 0
raw_baths = prop.get("bathrooms", 0) or 0
bedrooms = raw_beds if raw_beds <= MAX_BEDROOMS else 0
bathrooms = raw_baths if raw_baths <= MAX_BEDROOMS else 0
if raw_beds > MAX_BEDROOMS or raw_baths > MAX_BEDROOMS:
log.warning(
"Rightmove %s: implausible beds=%d baths=%d (capped to 0)",
prop.get("id", "?"), raw_beds, raw_baths,
)
key_features = [
kf.get("description", "")
for kf in prop.get("keyFeatures", [])
if kf.get("description")
]
postcode = pc_index.nearest(lat, lng)
if not postcode:
log.debug("No England postcode for property at %.4f, %.4f — skipping", lat, lng)
return None
return {
"id": prop.get("id"),
"Bedrooms": bedrooms,
"Bathrooms": bathrooms,
"Number of bedrooms & living rooms": bedrooms + bathrooms,
"lon": lng,
"lat": lat,
"Postcode": postcode,
"Address per Property Register": prop.get("displayAddress", ""),
"Leasehold/Freehold": extract_tenure(prop.get("tenure")),
"Property type": map_property_type(sub_type),
"Property sub-type": normalize_sub_type(sub_type),
"price": price,
"price_frequency": frequency,
"Price qualifier": price_qualifier,
"Total floor area (sqm)": parse_display_size(prop.get("displaySize")),
"Listing URL": RIGHTMOVE_BASE + prop.get("propertyUrl", ""),
"Listing features": key_features,
"first_visible_date": prop.get("firstVisibleDate", ""),
}

998
finder/uv.lock generated
View file

@ -1,998 +0,0 @@
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revision = 3
requires-python = ">=3.12"
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View file

@ -1,893 +0,0 @@
"""Zoopla (zoopla.co.uk) scraper — buy and rental properties.
Zoopla is behind Cloudflare Turnstile (managed interactive challenge), which
blocks all HTTP clients (curl_cffi, httpx) and even Playwright with stealth
patches. Only Camoufox (an anti-fingerprinting Firefox fork) passes reliably.
Zoopla uses Next.js App Router with React Server Components (RSC). Search
result data is server-rendered in an RSC stream, not available via
__NEXT_DATA__ or a JSON API. URL-based location slugs return 0 results
the working flow requires typing into the autocomplete input, selecting a
suggestion, and clicking Search.
Architecture:
Unlike the other scrapers which use HTTP clients per outcode, Zoopla keeps
a single Camoufox browser alive for the entire scrape. For each outcode, it:
1. Clears and types the outcode into the search input
2. Selects the first autocomplete suggestion
3. Clicks Search
4. Extracts listing data from the rendered DOM
5. Handles pagination via ?pn=N parameter
The browser session replaces the cookie/client pattern used by other scrapers.
"""
import logging
import re
import time
from constants import DELAY_BETWEEN_PAGES, MAX_BEDROOMS, PROPERTY_TYPE_MAP, ZOOPLA_BASE
from metrics import zoopla_errors_total, zoopla_pages_scraped, zoopla_properties_scraped
from spatial import PostcodeSpatialIndex
from transform import normalize_sub_type, validate_floor_area
log = logging.getLogger("zoopla")
class TurnstileError(Exception):
"""Raised when Cloudflare Turnstile challenge cannot be passed."""
# Maximum search result pages to scrape per outcode (25 listings/page)
MAX_PAGES_PER_OUTCODE = 40
# JavaScript to extract listings from the rendered DOM.
# Uses data-testid attributes as primary selectors (stable across deployments),
# then falls back to href-based link matching with parent-walking.
_EXTRACT_LISTINGS_JS = r"""() => {
const seen = new Set();
const results = [];
// Strategy 1: Use data-testid selectors (post-2025 redesign)
const listingCards = document.querySelectorAll(
'[data-testid="regular-listings"] > div, [data-testid="search-content"] li'
);
for (const card of listingCards) {
const link = card.querySelector(
'a[href*="/for-sale/details/"], a[href*="/new-homes/details/"], a[href*="/to-rent/details/"]'
);
if (!link) continue;
const href = link.href;
const match = href.match(/\/details\/(\d+)\//);
if (!match) continue;
const id = match[1];
if (seen.has(id)) continue;
seen.add(id);
const text = card.innerText || '';
// Try data-testid price element first, then regex
const priceEl = card.querySelector('[data-testid="listing-price"]');
const priceText = priceEl ? priceEl.innerText : text;
const priceMatch = priceText.match(/\u00a3([\d,]+)/);
// Try address element first, then regex
const addressEl = card.querySelector('address');
let address = addressEl ? addressEl.innerText.trim() : '';
if (!address) {
const lines = text.split('\n').map(l => l.trim()).filter(Boolean);
for (const line of lines) {
if (/[A-Z]{1,2}\d[A-Z\d]?\s*\d[A-Z]{2}/i.test(line) ||
(line.includes(',') && !line.includes('\u00a3') && !/^\d+ beds?/i.test(line))) {
address = line;
break;
}
}
}
const bedsMatch = text.match(/(\d+)\s*beds?/i);
const bathsMatch = text.match(/(\d+)\s*baths?/i);
const recMatch = text.match(/(\d+)\s*reception/i);
const areaMatch = text.match(/([\d,]+)\s*sq\.?\s*ft/i);
let tenure = '';
if (/leasehold/i.test(text)) tenure = 'Leasehold';
else if (/freehold/i.test(text)) tenure = 'Freehold';
// Extract property type (e.g., "2 bed flat for sale" "flat")
let property_type = '';
const ptMatch = text.match(/\d+\s*(?:beds?|bedrooms?)\s+([\w\s-]+?)\s+(?:for\s+sale|to\s+(?:rent|let)|for\s+rent)/i);
if (ptMatch) property_type = ptMatch[1].trim();
else if (/\bstudio\s*(?:flat|apartment)?\s+(?:for\s+sale|to\s+(?:rent|let)|for\s+rent)/i.test(text)) property_type = 'Studio';
// Keyword fallback when regex doesn't match current DOM format
if (!property_type) {
const lower = text.toLowerCase();
if (/\bstudio\b/.test(lower)) property_type = 'Studio';
else if (/\bpenthouse\b/.test(lower)) property_type = 'Penthouse';
else if (/\bmaisonette\b/.test(lower)) property_type = 'Maisonette';
else if (/\bapartment\b/.test(lower)) property_type = 'Apartment';
else if (/\bflat\b/.test(lower)) property_type = 'Flat';
else if (/\bsemi[- ]?detached\b/.test(lower)) property_type = 'Semi-Detached';
else if (/\bdetached\b/.test(lower)) property_type = 'Detached';
else if (/\bterraced?\b/.test(lower)) property_type = 'Terraced';
else if (/\bbungalow\b/.test(lower)) property_type = 'Bungalow';
else if (/\bcottage\b/.test(lower)) property_type = 'Cottage';
else if (/\bhouse\b/.test(lower)) property_type = 'House';
}
results.push({
id, url: href.replace(window.location.origin, ''),
price: priceMatch ? parseInt(priceMatch[1].replace(/,/g, '')) : null,
price_text: priceText.trim(),
beds: bedsMatch && parseInt(bedsMatch[1]) <= 20 ? parseInt(bedsMatch[1]) : null,
baths: bathsMatch && parseInt(bathsMatch[1]) <= 20 ? parseInt(bathsMatch[1]) : null,
receptions: recMatch && parseInt(recMatch[1]) <= 20 ? parseInt(recMatch[1]) : null,
floor_area_sqft: areaMatch ? parseInt(areaMatch[1].replace(/,/g, '')) : null,
address, tenure, property_type,
});
}
// Strategy 2: Fall back to href-based link matching with parent-walking
if (results.length === 0) {
const links = Array.from(document.querySelectorAll(
'a[href*="/for-sale/details/"], a[href*="/new-homes/details/"], a[href*="/to-rent/details/"]'
));
for (const link of links) {
const href = link.href;
const match = href.match(/\/details\/(\d+)\//);
if (!match) continue;
const id = match[1];
if (seen.has(id)) continue;
seen.add(id);
let card = link;
for (let j = 0; j < 15; j++) {
card = card.parentElement;
if (!card) break;
const t = card.innerText || '';
if (t.includes('\u00a3') && (t.includes('bed') || t.includes('Bath') || t.includes('sq ft'))) {
break;
}
}
if (!card) continue;
const text = card.innerText || '';
const lines = text.split('\n').map(l => l.trim()).filter(Boolean);
const priceEl2 = card.querySelector('[data-testid="listing-price"]');
const priceText2 = priceEl2 ? priceEl2.innerText : text;
const priceMatch = priceText2.match(/\u00a3([\d,]+)/);
const bedsMatch = text.match(/(\d+)\s*beds?/i);
const bathsMatch = text.match(/(\d+)\s*baths?/i);
const recMatch = text.match(/(\d+)\s*reception/i);
const areaMatch = text.match(/([\d,]+)\s*sq\.?\s*ft/i);
let address = '';
for (const line of lines) {
if (/[A-Z]{1,2}\d[A-Z\d]?\s*\d[A-Z]{2}/i.test(line) ||
(line.includes(',') && !line.includes('\u00a3') && !/^\d+ beds?/i.test(line))) {
address = line;
break;
}
}
let tenure = '';
if (/leasehold/i.test(text)) tenure = 'Leasehold';
else if (/freehold/i.test(text)) tenure = 'Freehold';
// Extract property type
let property_type = '';
const ptMatch2 = text.match(/\d+\s*(?:beds?|bedrooms?)\s+([\w\s-]+?)\s+(?:for\s+sale|to\s+(?:rent|let)|for\s+rent)/i);
if (ptMatch2) property_type = ptMatch2[1].trim();
else if (/\bstudio\s*(?:flat|apartment)?\s+(?:for\s+sale|to\s+(?:rent|let)|for\s+rent)/i.test(text)) property_type = 'Studio';
// Keyword fallback when regex doesn't match current DOM format
if (!property_type) {
const lower = text.toLowerCase();
if (/\bstudio\b/.test(lower)) property_type = 'Studio';
else if (/\bpenthouse\b/.test(lower)) property_type = 'Penthouse';
else if (/\bmaisonette\b/.test(lower)) property_type = 'Maisonette';
else if (/\bapartment\b/.test(lower)) property_type = 'Apartment';
else if (/\bflat\b/.test(lower)) property_type = 'Flat';
else if (/\bsemi[- ]?detached\b/.test(lower)) property_type = 'Semi-Detached';
else if (/\bdetached\b/.test(lower)) property_type = 'Detached';
else if (/\bterraced?\b/.test(lower)) property_type = 'Terraced';
else if (/\bbungalow\b/.test(lower)) property_type = 'Bungalow';
else if (/\bcottage\b/.test(lower)) property_type = 'Cottage';
else if (/\bhouse\b/.test(lower)) property_type = 'House';
}
results.push({
id, url: href.replace(window.location.origin, ''),
price: priceMatch ? parseInt(priceMatch[1].replace(/,/g, '')) : null,
price_text: priceText2.trim(),
beds: bedsMatch && parseInt(bedsMatch[1]) <= 20 ? parseInt(bedsMatch[1]) : null,
baths: bathsMatch && parseInt(bathsMatch[1]) <= 20 ? parseInt(bathsMatch[1]) : null,
receptions: recMatch && parseInt(recMatch[1]) <= 20 ? parseInt(recMatch[1]) : null,
floor_area_sqft: areaMatch ? parseInt(areaMatch[1].replace(/,/g, '')) : null,
address, tenure, property_type,
});
}
}
return results;
}"""
# JavaScript to dismiss the Usercentrics cookie consent overlay (shadow DOM).
_DISMISS_COOKIES_JS = """() => {
const aside = document.querySelector('#usercentrics-cmp-ui');
if (aside && aside.shadowRoot) {
const btns = aside.shadowRoot.querySelectorAll('button');
for (const btn of btns) {
if (btn.innerText.includes('Accept')) { btn.click(); return true; }
}
}
if (aside) { aside.remove(); return true; }
return false;
}"""
# ---------------------------------------------------------------------------
# Browser lifecycle
# ---------------------------------------------------------------------------
def launch_browser():
"""Launch Camoufox, navigate to Zoopla homepage, pass Cloudflare Turnstile,
and dismiss cookie consent. Returns (browser, page) tuple.
Raises TurnstileError if Cloudflare cannot be passed within 60 seconds.
Caller must close browser when done."""
from camoufox.pkgman import camoufox_path
# Verify camoufox is pre-installed — never download at runtime
camoufox_path(download_if_missing=False)
from camoufox.sync_api import Camoufox
log.info("Launching Camoufox browser for Zoopla...")
browser = Camoufox(headless=True).__enter__()
page = browser.new_page()
log.info("Navigating to Zoopla homepage...")
page.goto(f"{ZOOPLA_BASE}/", wait_until="domcontentloaded", timeout=60000)
# Wait for Cloudflare Turnstile to resolve.
# Try clicking the Turnstile checkbox if present (helps in some cases).
for i in range(20):
if "Just a moment" not in page.title():
break
# Attempt to click the Turnstile checkbox in the challenge iframe
for frame in page.frames:
if "challenges.cloudflare.com" in frame.url:
try:
iframe_el = page.query_selector('iframe[src*="challenges.cloudflare"]')
if iframe_el:
box = iframe_el.bounding_box()
if box:
page.mouse.click(box["x"] + 30, box["y"] + box["height"] / 2)
except Exception:
pass
break
time.sleep(3)
else:
page.close()
browser.close()
raise TurnstileError("Cloudflare Turnstile did not resolve after 60s")
log.info("Cloudflare passed — title: %s", page.title())
time.sleep(2)
# Dismiss cookie consent
page.evaluate(_DISMISS_COOKIES_JS)
time.sleep(1)
return browser, page
def _ensure_not_challenged(page) -> None:
"""Check if current page is a Cloudflare challenge and wait/raise."""
if "Just a moment" not in page.title():
return
log.warning("Cloudflare challenge detected mid-session, waiting...")
for i in range(20):
time.sleep(3)
if "Just a moment" not in page.title():
log.info("Cloudflare challenge resolved")
return
raise TurnstileError("Cloudflare re-challenge did not resolve")
# ---------------------------------------------------------------------------
# Search navigation
# ---------------------------------------------------------------------------
def _navigate_direct(page, url: str) -> bool:
"""Navigate directly to a Zoopla search URL (skipping the homepage flow).
Used to load the second channel (e.g., RENT after BUY) for the same outcode
by swapping the path component. Falls back gracefully returns False if
the page has no listings, so the caller can retry via the full search flow.
"""
try:
page.goto(url, wait_until="domcontentloaded", timeout=30000)
except Exception as e:
log.debug("Direct navigation failed: %s", e)
return False
_ensure_not_challenged(page)
# Wait for listing content to hydrate
try:
page.wait_for_function(
"""() => {
const cards = document.querySelectorAll(
'[data-testid="regular-listings"] > div'
);
if (cards.length === 0) return false;
for (const card of cards) {
const t = card.innerText || '';
if (t.includes('\\u00a3') && t.length > 50) return true;
}
return false;
}""",
timeout=8000,
)
except Exception:
# Check if the page has any listings at all
has_listings = page.query_selector('a[href*="/details/"]')
if not has_listings:
return False
time.sleep(1.5)
return True
def _navigate_search(page, outcode: str, channel: str) -> bool:
"""Navigate to search results for an outcode via the homepage search flow.
Returns True if results were found, False if no results or navigation failed.
Raises TurnstileError if Cloudflare blocks us."""
# Navigate to homepage to reset search state
page.goto(f"{ZOOPLA_BASE}/", wait_until="domcontentloaded", timeout=30000)
time.sleep(0.5)
_ensure_not_challenged(page)
# Dismiss cookie consent (may reappear after navigation)
page.evaluate(_DISMISS_COOKIES_JS)
time.sleep(0.3)
# Select Buy/Rent tab
if channel == "RENT":
rent_tab = page.query_selector(
'button:has-text("Rent"), [role="tab"]:has-text("Rent")'
)
if rent_tab:
rent_tab.click()
time.sleep(0.2)
# Find and fill search input
search_input = page.query_selector(
'input[name="autosuggest-input"]'
) or page.query_selector('input[type="text"]')
if not search_input:
log.warning("Could not find search input on homepage")
return False
search_input.click()
time.sleep(0.1)
search_input.fill("")
search_input.type(outcode, delay=60)
time.sleep(1.2)
# Select first autocomplete suggestion
first_option = page.query_selector('[role="option"]')
if not first_option:
log.debug("No autocomplete suggestions for outcode %s", outcode)
return False
first_option.click()
time.sleep(0.2)
# Click search button
search_btn = page.query_selector('button:has-text("Search")')
if search_btn:
search_btn.click()
else:
search_input.press("Enter")
# Wait for results to load — try waiting for listings container, fall back to fixed wait
try:
page.wait_for_selector(
'[data-testid="regular-listings"], a[href*="/details/"]',
timeout=10000,
)
except Exception:
time.sleep(4)
_ensure_not_challenged(page)
# Wait for client-side hydration to populate listing content (prices, addresses).
# The structural container appears in server-rendered HTML before React hydrates
# the actual card content — extracting too early yields empty price/address fields.
try:
page.wait_for_function(
"""() => {
const cards = document.querySelectorAll(
'[data-testid="regular-listings"] > div'
);
if (cards.length === 0) return false;
for (const card of cards) {
const t = card.innerText || '';
if (t.includes('\\u00a3') && t.length > 50) return true;
}
return false;
}""",
timeout=8000,
)
except Exception:
# Content never appeared — extraction will likely fail but let it try
log.debug("Listing content hydration wait timed out — prices may not have rendered")
time.sleep(2)
return True
def _get_result_count(page) -> int:
"""Extract the total results count from the page.
Tries __ZAD_TARGETING__ JSON first (most reliable), then body text regex
matching both "N results" and "N properties" patterns."""
try:
# Try the ZAD targeting JSON script tag first
count = page.evaluate("""() => {
const s = document.querySelector('#__ZAD_TARGETING__');
if (s) {
try {
const d = JSON.parse(s.textContent);
if (d.search_results_count != null) return d.search_results_count;
} catch(e) {}
}
return null;
}""")
if count is not None and count > 0:
return count
except Exception:
pass
try:
body = page.inner_text("body")
match = re.search(r"([\d,]+)\s+(?:results?|properties)", body)
if match:
return int(match.group(1).replace(",", ""))
except Exception:
pass
return 0
# ---------------------------------------------------------------------------
# Extraction and pagination
# ---------------------------------------------------------------------------
_first_extraction_logged = False
def _extract_listings(page) -> list[dict]:
"""Extract listing data from the current search results page DOM."""
global _first_extraction_logged
try:
listings = page.evaluate(_EXTRACT_LISTINGS_JS)
# Log diagnostic info on the very first extraction attempt
if not _first_extraction_logged:
_first_extraction_logged = True
try:
diag = page.evaluate("""() => {
const details = document.querySelectorAll('a[href*="/details/"]');
const testids = document.querySelectorAll('[data-testid]');
const testidNames = [...new Set([...testids].map(e => e.dataset.testid))];
return {
url: location.href,
title: document.title,
detailLinks: details.length,
testids: testidNames.slice(0, 30),
bodySnippet: document.body?.innerText?.slice(0, 500) || '',
};
}""")
log.info(
"Zoopla first-page diagnostic: url=%s title=%s detailLinks=%d "
"testids=%s bodySnippet=%.200s",
diag.get("url"), diag.get("title"), diag.get("detailLinks", 0),
diag.get("testids", []), diag.get("bodySnippet", ""),
)
except Exception:
pass
log.info("Zoopla first extraction: %d listings found", len(listings))
return listings
except Exception as e:
log.warning("Failed to extract listings from DOM: %s", e)
zoopla_errors_total.labels(type="extract_failed").inc()
return []
def _paginate(page, total_results: int, channel: str) -> list[dict]:
"""Extract listings from all pages of search results.
Page 1 is already loaded. For subsequent pages, clicks the Next button
or navigates via URL parameter ?pn=N."""
all_listings = _extract_listings(page)
channel_label = "buy" if channel == "BUY" else "rent"
zoopla_pages_scraped.labels(channel=channel_label).inc()
if not all_listings or total_results <= len(all_listings):
return all_listings
seen_ids = {listing["id"] for listing in all_listings}
current_url = page.url
page_num = 2
while len(all_listings) < total_results and page_num <= MAX_PAGES_PER_OUTCODE:
time.sleep(DELAY_BETWEEN_PAGES)
# Try navigating via URL parameter
if "?" in current_url:
next_url = re.sub(r"[?&]pn=\d+", "", current_url)
separator = "&" if "?" in next_url else "?"
next_url = f"{next_url}{separator}pn={page_num}"
else:
next_url = f"{current_url}?pn={page_num}"
try:
page.goto(next_url, wait_until="domcontentloaded", timeout=30000)
_ensure_not_challenged(page)
# Wait for listing content instead of fixed sleep
try:
page.wait_for_function(
"""() => {
const cards = document.querySelectorAll(
'[data-testid="regular-listings"] > div'
);
if (cards.length === 0) return false;
for (const card of cards) {
const t = card.innerText || '';
if (t.includes('\\u00a3') && t.length > 50) return true;
}
return false;
}""",
timeout=8000,
)
except Exception:
time.sleep(1.5)
except TurnstileError:
raise
except Exception as e:
log.debug("Pagination navigation failed at page %d: %s", page_num, e)
break
page_listings = _extract_listings(page)
if not page_listings:
break
# Deduplicate within this outcode
new_count = 0
for listing in page_listings:
if listing["id"] not in seen_ids:
seen_ids.add(listing["id"])
all_listings.append(listing)
new_count += 1
zoopla_pages_scraped.labels(channel=channel_label).inc()
if new_count == 0:
break # No new listings on this page
page_num += 1
return all_listings
# ---------------------------------------------------------------------------
# Property transformation
# ---------------------------------------------------------------------------
# Cached outcode → (postcode, lat, lng) lookups to avoid repeated O(n) scans
# over 2.26M postcodes. Populated lazily on first lookup per outcode.
_outcode_coords_cache: dict[str, tuple[str, float, float] | None] = {}
def _resolve_outcode_coords(
outcode: str, pc_coords: dict[str, tuple[float, float]]
) -> tuple[str, float, float] | None:
"""Find first postcode + coords for an outcode. Result is cached."""
if outcode in _outcode_coords_cache:
return _outcode_coords_cache[outcode]
prefix = outcode + " "
for pcd, (lat, lng) in pc_coords.items():
if pcd.startswith(prefix) or (
len(outcode) >= 4
and pcd.startswith(outcode)
and len(pcd) > len(outcode)
):
_outcode_coords_cache[outcode] = (pcd, lat, lng)
return (pcd, lat, lng)
_outcode_coords_cache[outcode] = None
return None
def _extract_postcode(text: str) -> str | None:
"""Extract a full UK postcode from text like 'Dollar Bay Place, Canary Wharf E14 9SS'.
Normalizes to include a space before the 3-char incode."""
match = re.search(r"([A-Z]{1,2}\d[A-Z0-9]?\s*\d[A-Z]{2})", text, re.IGNORECASE)
if match:
raw = match.group(1).upper().strip()
# Ensure space before incode (last 3 chars): "SW1A1AA" → "SW1A 1AA"
if " " not in raw and len(raw) >= 5:
return raw[:-3] + " " + raw[-3:]
return raw
return None
def _extract_outcode(text: str) -> str | None:
"""Extract a UK outcode from address text like 'Whitechapel Road, London E1'."""
# Look for outcode at end of string or after last comma
match = re.search(r"\b([A-Z]{1,2}\d[A-Z0-9]?)\s*$", text.strip(), re.IGNORECASE)
if match:
return match.group(1).upper()
# Try after comma
parts = text.split(",")
if len(parts) > 1:
last = parts[-1].strip()
match = re.match(r"^([A-Z]{1,2}\d[A-Z0-9]?)$", last, re.IGNORECASE)
if match:
return match.group(1).upper()
return None
def _map_property_type(raw_type: str | None) -> str:
"""Map Zoopla property type text to canonical type."""
if not raw_type:
return "Other"
# Exact match (handles Rightmove-style capitalised values)
canonical = PROPERTY_TYPE_MAP.get(raw_type)
if canonical:
return canonical
# Title-case match (handles regex-extracted lowercase like "town house" → "Town House")
canonical = PROPERTY_TYPE_MAP.get(raw_type.title())
if canonical:
return canonical
# Lowercase match (e.g., "Townhouse" → "townhouse")
canonical = PROPERTY_TYPE_MAP.get(raw_type.lower())
if canonical:
return canonical
# Normalize delimiters (underscores/hyphens → spaces) and try again
normalized = re.sub(r"[-_]+", " ", raw_type).strip().title()
canonical = PROPERTY_TYPE_MAP.get(normalized)
if canonical:
return canonical
# Keyword fallback
lower = raw_type.lower()
if "flat" in lower or "apartment" in lower or "maisonette" in lower or "studio" in lower or "penthouse" in lower:
return "Flats/Maisonettes"
if "semi" in lower and "detach" in lower:
return "Semi-Detached"
if "detach" in lower:
return "Detached"
if "terrace" in lower or "mews" in lower:
return "Terraced"
if "house" in lower:
return "Detached"
return "Other"
def _detect_rent_frequency(price_text: str) -> str:
"""Detect rent frequency from Zoopla price text.
Zoopla price elements contain text like '£1,500 pcm', '£350 pw',
'£18,000 pa'. Defaults to 'monthly' if no frequency indicator found.
Checks monthly indicators (pcm) BEFORE weekly (pw) because Zoopla cards
often display both monthly and weekly prices in the same text. When the
JS extraction falls back to full card text, checking pcm first ensures
the captured monthly price gets the correct frequency label.
"""
lower = price_text.lower()
if "pcm" in lower or "per month" in lower or "per calendar month" in lower:
return "monthly"
if "pw" in lower or "per week" in lower or "/w" in lower:
return "weekly"
if "pa" in lower or "per annum" in lower or "/y" in lower or "per year" in lower:
return "yearly"
# No indicator — default monthly (Zoopla standard)
return "monthly"
def transform_property(
raw: dict,
channel: str,
pc_index: PostcodeSpatialIndex,
pc_coords: dict[str, tuple[float, float]],
search_outcode: str | None = None,
) -> dict | None:
"""Transform a raw Zoopla listing dict into the standard output schema.
Zoopla search cards do not include coordinates, so we resolve lat/lng
from postcodes extracted from the address text."""
price = raw.get("price")
if not price or int(price) <= 0:
return None
address = raw.get("address", "")
# Resolve postcode and coordinates from address
postcode = _extract_postcode(address)
lat = lng = None
if postcode:
coords = pc_coords.get(postcode)
if coords:
lat, lng = coords
if lat is None:
# Try outcode-level fallback from address text
addr_outcode = _extract_outcode(address)
if addr_outcode:
result = _resolve_outcode_coords(addr_outcode, pc_coords)
if result:
postcode, lat, lng = result
# Final fallback: use the outcode we know we're searching
if lat is None and search_outcode:
result = _resolve_outcode_coords(search_outcode, pc_coords)
if result:
postcode, lat, lng = result
if lat is None or lng is None or not postcode:
return None
# Validate coordinates are in England
if not (49 <= lat <= 56 and -7 <= lng <= 2):
return None
raw_beds = raw.get("beds") or 0
raw_baths = raw.get("baths") or 0
bedrooms = raw_beds if raw_beds <= MAX_BEDROOMS else 0
bathrooms = raw_baths if raw_baths <= MAX_BEDROOMS else 0
if raw_beds > MAX_BEDROOMS or raw_baths > MAX_BEDROOMS:
log.warning(
"Zoopla %s: implausible beds=%d baths=%d (capped to 0)",
raw.get("id", "?"), raw_beds, raw_baths,
)
receptions = raw.get("receptions") or 0
# Floor area: convert sq ft to sq m
floor_area_sqm = None
sqft = raw.get("floor_area_sqft")
if sqft:
floor_area_sqm = validate_floor_area(round(sqft * 0.092903, 1))
listing_id = raw.get("id", "")
listing_url = raw.get("url", "")
if listing_url and not listing_url.startswith("http"):
listing_url = ZOOPLA_BASE + listing_url
# Detect rent frequency from price text (e.g. "£1,500 pcm" vs "£350 pw")
if channel == "BUY":
frequency = ""
else:
price_text = raw.get("price_text", "")
frequency = _detect_rent_frequency(price_text)
return {
"id": f"zp_{listing_id}",
"Bedrooms": bedrooms,
"Bathrooms": bathrooms,
"Number of bedrooms & living rooms": bedrooms + receptions,
"lon": lng,
"lat": lat,
"Postcode": postcode,
"Address per Property Register": address,
"Leasehold/Freehold": raw.get("tenure") or None,
"Property type": _map_property_type(raw.get("property_type")),
"Property sub-type": normalize_sub_type(raw.get("property_type")),
"price": int(price),
"price_frequency": frequency,
"Price qualifier": "",
"Total floor area (sqm)": floor_area_sqm,
"Listing URL": listing_url,
"Listing features": [],
"first_visible_date": "",
}
# ---------------------------------------------------------------------------
# Top-level search function (called by scraper.py)
# ---------------------------------------------------------------------------
def search_outcode(
page,
outcode: str,
channel: str,
pc_index: PostcodeSpatialIndex,
pc_coords: dict[str, tuple[float, float]],
base_search_url: str | None = None,
) -> tuple[list[dict], str | None]:
"""Search Zoopla for properties in one outcode.
Takes a live Camoufox Page (from launch_browser). Navigates through the
search flow, extracts listings from rendered DOM, and transforms to the
standard output schema.
If base_search_url is provided (from a previous channel search for the same
outcode), tries direct URL navigation first skipping the slow homepage
search flow. Falls back to full navigation if direct fails.
Returns (properties, search_url) where search_url can be passed to the next
channel call for this outcode.
Raises TurnstileError if Cloudflare blocks us mid-session.
"""
navigated = False
if base_search_url:
navigated = _navigate_direct(page, base_search_url)
if navigated:
log.debug("Zoopla %s %s: used direct URL navigation", outcode, channel)
if not navigated:
if not _navigate_search(page, outcode, channel):
return [], None
total_results = _get_result_count(page)
# Always try extraction even if result count is 0 — the count regex may
# not match Zoopla's current text format, but listings may still be in DOM
raw_listings = _paginate(page, max(total_results, 25), channel)
if not raw_listings:
if total_results > 0:
log.debug(
"Zoopla %s %s: page claims %d results but extraction found 0 — "
"DOM selectors may need updating",
outcode, channel, total_results,
)
return [], None
channel_label = "buy" if channel == "BUY" else "rent"
properties = []
dropped = 0
for raw in raw_listings:
transformed = transform_property(raw, channel, pc_index, pc_coords, search_outcode=outcode)
if transformed:
properties.append(transformed)
zoopla_properties_scraped.labels(channel=channel_label).inc()
else:
dropped += 1
if dropped and not properties:
# Log a sample raw listing to diagnose which fields are missing
sample = raw_listings[0] if raw_listings else {}
log.debug(
"Zoopla %s %s: extracted %d raw listings but all %d dropped in transform "
"(no price/postcode/coords). Sample raw: price=%s address=%r",
outcode, channel, len(raw_listings), dropped,
sample.get("price"), sample.get("address", ""),
)
elif dropped > len(raw_listings) // 2:
log.debug(
"Zoopla %s %s: %d/%d listings dropped in transform",
outcode, channel, dropped, len(raw_listings),
)
return properties, page.url

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@ -1,281 +0,0 @@
#!/usr/bin/env -S uv run --project ../finder
"""Zoopla scraping experiment — working prototype using Camoufox.
Key findings:
- Zoopla uses Cloudflare Turnstile (managed interactive challenge)
- Playwright headless Chromium + stealth patches CANNOT beat it
- Camoufox (anti-fingerprinting Firefox fork) PASSES Cloudflare
- Zoopla uses Next.js App Router with React Server Components (RSC)
- Listing data is NOT in __NEXT_DATA__ it's server-rendered in RSC stream
- URL-based location slugs (e.g. /properties/london/) return 0 results
- Must use the search autocomplete (GraphQL: getGeoSuggestion) to resolve
a location, then submit the form to get results
- GraphQL endpoint: api-graphql-lambda.prod.zoopla.co.uk/graphql
- Listings loaded via getTopLeadListingIds + getRareFindLeadListingIds ops
Usage:
uv run --project finder scripts/zoopla_experiment.py [LOCATION]
uv run --project finder scripts/zoopla_experiment.py "Tower Hamlets"
"""
import json
import logging
import re
import sys
import time
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s %(levelname)-8s %(message)s",
datefmt="%H:%M:%S",
)
log = logging.getLogger("zoopla-exp")
def scrape_zoopla(location: str = "London", channel: str = "BUY"):
from camoufox.sync_api import Camoufox
tab_label = "Buy" if channel == "BUY" else "Rent"
log.info("Scraping Zoopla: location=%s channel=%s", location, channel)
with Camoufox(headless=True) as browser:
page = browser.new_page()
# Intercept GraphQL responses
graphql_responses = []
def on_resp(response):
url = response.url
ct = response.headers.get("content-type", "")
if "json" in ct and "graphql" in url:
try:
body = response.json()
req = response.request.post_data or ""
graphql_responses.append({"body": body, "req": req})
except Exception:
pass
page.on("response", on_resp)
# Step 1: Load homepage and pass Cloudflare
log.info("Loading Zoopla homepage...")
page.goto("https://www.zoopla.co.uk/", wait_until="domcontentloaded", timeout=60000)
for i in range(20):
if "Just a moment" not in page.title():
break
time.sleep(3)
else:
log.error("Cloudflare did not resolve after 60s")
return []
log.info("Homepage loaded: %s", page.title())
time.sleep(3)
# Step 2: Dismiss cookie consent (shadow DOM)
page.evaluate("""() => {
const aside = document.querySelector('#usercentrics-cmp-ui');
if (aside && aside.shadowRoot) {
const btns = aside.shadowRoot.querySelectorAll('button');
for (const btn of btns) {
if (btn.innerText.includes('Accept')) { btn.click(); return; }
}
}
aside?.remove();
}""")
time.sleep(2)
# Step 3: Select Buy/Rent tab if needed
if channel == "RENT":
rent_tab = page.query_selector('button:has-text("Rent")') or page.query_selector(f'[role="tab"]:has-text("{tab_label}")')
if rent_tab:
rent_tab.click()
time.sleep(1)
# Step 4: Type location into search and select autocomplete suggestion
log.info("Searching for '%s'...", location)
search_input = (
page.query_selector('input[name="autosuggest-input"]')
or page.query_selector('input[type="text"]')
)
if not search_input:
log.error("Could not find search input")
return []
search_input.click()
time.sleep(0.5)
search_input.fill("") # Clear any existing text
search_input.type(location, delay=80)
time.sleep(3)
# Select first autocomplete suggestion
first_option = page.query_selector('[role="option"]')
if first_option:
suggestion_text = first_option.inner_text()
log.info("Selecting suggestion: %s", suggestion_text)
first_option.click()
time.sleep(1)
else:
log.warning("No autocomplete suggestions appeared")
# Step 5: Submit search
search_btn = page.query_selector('button:has-text("Search")')
if search_btn:
search_btn.click()
else:
search_input.press("Enter")
log.info("Waiting for results...")
time.sleep(10)
final_url = page.url
final_title = page.title()
log.info("URL: %s", final_url)
log.info("Title: %s", final_title)
# Step 6: Extract listings from rendered DOM
listings = page.evaluate(r"""() => {
const links = Array.from(document.querySelectorAll(
'a[href*="/for-sale/details/"], a[href*="/new-homes/details/"], a[href*="/to-rent/details/"]'
));
const seen = new Set();
const results = [];
for (const link of links) {
const href = link.href;
const match = href.match(/\/details\/(\d+)\//);
if (!match) continue;
const id = match[1];
if (seen.has(id)) continue;
seen.add(id);
// Walk up to find the listing card container
let card = link;
for (let j = 0; j < 10; j++) {
card = card.parentElement;
if (!card) break;
const text = card.innerText || '';
// A listing card should have a price and at least beds or area
if (text.includes('£') && (text.includes('bed') || text.includes('sq ft'))) {
break;
}
}
if (!card) continue;
const text = card.innerText || '';
const lines = text.split('\n').map(l => l.trim()).filter(Boolean);
const priceMatch = text.match(/£([\d,]+)/);
const bedsMatch = text.match(/(\d+)\s*beds?/i);
const bathsMatch = text.match(/(\d+)\s*baths?/i);
const recMatch = text.match(/(\d+)\s*reception/i);
const areaMatch = text.match(/([\d,]+)\s*sq\s*ft/i);
// Try to find address usually a line with a postcode or comma-separated location
let address = '';
for (const line of lines) {
if (/[A-Z]{1,2}\d[A-Z\d]?\s*\d[A-Z]{2}/i.test(line) ||
(line.includes(',') && !line.includes('£') && !line.match(/^\d+ beds?/i))) {
address = line;
break;
}
}
// Tenure
let tenure = '';
if (/freehold/i.test(text)) tenure = 'Freehold';
else if (/leasehold/i.test(text)) tenure = 'Leasehold';
results.push({
id: id,
url: href.replace(window.location.origin, ''),
price: priceMatch ? parseInt(priceMatch[1].replace(/,/g, '')) : null,
beds: bedsMatch ? parseInt(bedsMatch[1]) : null,
baths: bathsMatch ? parseInt(bathsMatch[1]) : null,
receptions: recMatch ? parseInt(recMatch[1]) : null,
floor_area_sqft: areaMatch ? parseInt(areaMatch[1].replace(/,/g, '')) : null,
address: address,
tenure: tenure,
text_preview: lines.slice(0, 10).join(' | '),
});
}
return results;
}""")
log.info("Extracted %d unique listings from page 1", len(listings))
# Step 7: Check for results count and pagination
body_text = page.inner_text("body")
count_match = re.search(r"([\d,]+)\s+results?", body_text)
total_results = int(count_match.group(1).replace(",", "")) if count_match else len(listings)
log.info("Total results: %d", total_results)
# Step 8: Log GraphQL operations we saw
log.info("GraphQL operations intercepted:")
for gql in graphql_responses:
try:
req = json.loads(gql["req"])
op = req.get("operationName", "?")
log.info(" - %s", op)
except Exception:
pass
# Step 9: Extract cookies for potential curl_cffi reuse
cookies = page.context.cookies()
session_cookies = {
c["name"]: c["value"]
for c in cookies
if "zoopla" in c.get("domain", "") or "cf" in c.get("name", "").lower()
}
ua = page.evaluate("navigator.userAgent")
return {
"url": final_url,
"title": final_title,
"total_results": total_results,
"listings": listings,
"cookies": session_cookies,
"user_agent": ua,
}
def main():
location = sys.argv[1] if len(sys.argv) > 1 else "London"
result = scrape_zoopla(location, channel="BUY")
if not result:
log.error("Scraping failed")
sys.exit(1)
listings = result["listings"]
print(f"\n{'='*60}")
print(f" Zoopla: {result['title']}")
print(f" URL: {result['url']}")
print(f" Total: {result['total_results']} results, {len(listings)} extracted")
print(f"{'='*60}\n")
for i, listing in enumerate(listings):
print(f"--- Listing {i+1}: {listing['url']} ---")
display = {k: v for k, v in listing.items() if k != "text_preview" and v}
print(json.dumps(display, indent=2, ensure_ascii=False))
print()
# Summary stats
prices = [item["price"] for item in listings if item["price"]]
beds = [item["beds"] for item in listings if item["beds"]]
if prices:
print(f"Price range: £{min(prices):,} - £{max(prices):,}")
print(f"Median: £{sorted(prices)[len(prices)//2]:,}")
if beds:
print(f"Bedrooms: {min(beds)}-{max(beds)}")
# Cookie info for reuse
print(f"\nSession cookies ({len(result['cookies'])} cookies)")
print(f"User-Agent: {result['user_agent']}")
if __name__ == "__main__":
main()

View file

@ -1,182 +0,0 @@
use std::sync::Arc;
use std::time::Instant;
use axum::extract::State;
use axum::http::StatusCode;
use axum::response::{IntoResponse, Json, Response};
use serde_json::json;
use tracing::{info, warn};
use crate::consts::GRID_CELL_SIZE;
use crate::data::{self, PropertyData};
use crate::metrics::record_data_stats;
use crate::routes::{build_features_response, build_system_prompt};
use crate::state::{AppState, SharedState};
use crate::utils::GridIndex;
pub async fn post_reload(State(shared): State<Arc<SharedState>>) -> Response {
if !shared.try_start_reload() {
return (StatusCode::CONFLICT, "Reload already in progress").into_response();
}
info!("Reload triggered — rebuilding property data");
let start = Instant::now();
// shared is cloned so we retain a reference after spawn_blocking
let sh = Arc::clone(&shared);
let result = tokio::task::spawn_blocking(move || rebuild_data(&sh, start)).await;
// Always clear the reload flag
shared.finish_reload();
match result {
Ok(Ok((rows, features, elapsed_ms))) => Json(json!({
"status": "ok",
"rows": rows,
"features": features,
"elapsed_ms": elapsed_ms,
}))
.into_response(),
Ok(Err(err)) => {
warn!("Reload failed: {err:#}");
(
StatusCode::INTERNAL_SERVER_ERROR,
Json(json!({ "error": format!("{err:#}") })),
)
.into_response()
}
Err(err) => {
warn!("Reload task panicked: {err}");
(
StatusCode::INTERNAL_SERVER_ERROR,
Json(json!({ "error": format!("Reload task panicked: {err}") })),
)
.into_response()
}
}
}
fn rebuild_data(shared: &SharedState, start: Instant) -> anyhow::Result<(usize, usize, u128)> {
let old = shared.load_state();
// 1. Load PropertyData from parquet files
let property_data = PropertyData::load(
&shared.properties_path,
&shared.postcode_features_path,
&shared.listings_buy_path,
&shared.listings_rent_path,
)?;
let row_count = property_data.lat.len();
let feature_count = property_data.num_features;
// 2. Build spatial grid index
info!("Reload: building spatial grid index");
let grid = GridIndex::build(&property_data.lat, &property_data.lon, GRID_CELL_SIZE);
// 3. Precompute H3 cells
info!("Reload: precomputing H3 cells");
let h3_cells = data::precompute_h3(&property_data.lat, &property_data.lon)?;
// 4. Build feature lookup tables
let feature_name_to_index = property_data
.feature_names
.iter()
.enumerate()
.map(|(idx, name)| (name.clone(), idx))
.collect();
let min_keys = property_data
.feature_names
.iter()
.map(|n| format!("min_{n}"))
.collect();
let max_keys = property_data
.feature_names
.iter()
.map(|n| format!("max_{n}"))
.collect();
let avg_keys = property_data
.feature_names
.iter()
.map(|n| format!("avg_{n}"))
.collect();
// 5. Build features response and AI prompt
let features_response = build_features_response(&property_data);
let mode_destinations: Vec<(String, usize)> = old
.travel_time_store
.available_modes
.iter()
.map(|mode| {
let count = old
.travel_time_store
.destinations
.get(mode.as_str())
.map(|slugs| slugs.len())
.unwrap_or(0);
(mode.clone(), count)
})
.filter(|(_, count)| *count > 0)
.collect();
let ai_filters_system_prompt = build_system_prompt(&features_response, &mode_destinations);
// 6. Update data metrics
record_data_stats(
row_count,
old.poi_data.lat.len(),
old.postcode_data.postcodes.len(),
);
// 7. Build new AppState, sharing unchanged fields via Arc
let new_state = AppState {
data: property_data,
grid,
h3_cells,
feature_name_to_index,
min_keys,
max_keys,
avg_keys,
features_response,
ai_filters_system_prompt,
// Shared across reloads (Arc clone is cheap)
poi_data: Arc::clone(&old.poi_data),
poi_grid: Arc::clone(&old.poi_grid),
place_data: Arc::clone(&old.place_data),
postcode_data: Arc::clone(&old.postcode_data),
outcode_data: Arc::clone(&old.outcode_data),
poi_category_groups: Arc::clone(&old.poi_category_groups),
travel_time_store: Arc::clone(&old.travel_time_store),
token_cache: Arc::clone(&old.token_cache),
superuser_token_cache: Arc::clone(&old.superuser_token_cache),
// Config (cheap clone)
screenshot_url: old.screenshot_url.clone(),
public_url: old.public_url.clone(),
is_dev: old.is_dev,
index_html: old.index_html.clone(),
http_client: old.http_client.clone(),
pocketbase_url: old.pocketbase_url.clone(),
pocketbase_admin_email: old.pocketbase_admin_email.clone(),
pocketbase_admin_password: old.pocketbase_admin_password.clone(),
gemini_api_key: old.gemini_api_key.clone(),
gemini_model: old.gemini_model.clone(),
google_maps_api_key: old.google_maps_api_key.clone(),
stripe_secret_key: old.stripe_secret_key.clone(),
stripe_webhook_secret: old.stripe_webhook_secret.clone(),
stripe_referral_coupon_id: old.stripe_referral_coupon_id.clone(),
};
// 8. Atomic swap
shared.swap_state(new_state);
let elapsed = start.elapsed();
info!(
rows = row_count,
features = feature_count,
elapsed_ms = elapsed.as_millis(),
"Reload complete"
);
Ok((row_count, feature_count, elapsed.as_millis()))
}