This commit is contained in:
@@ -4,3 +4,4 @@ __pycache__/
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.env
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pbt.env
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instance/
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data/.osm-cache/
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@@ -20,15 +20,18 @@ Beim ersten Start legt die App die Tabellen (`users`, `trips`, `stops`) automati
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## Haltestellen-Lookup
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Die Felder „Von" und „Nach" haben eine Autovervollständigung aus allen
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österreichischen Haltestellen. Die Daten stammen aus OpenStreetMap
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(© OpenStreetMap-Mitwirkende, ODbL) und liegen als Snapshot im Repo
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(`data/stops_at.csv.gz`, ~37 000 Haltestellen).
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Die Felder „Von" und „Nach" haben eine Autovervollständigung aus den
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Haltestellen in Österreich, Deutschland und der Schweiz (DACH) – aktuell
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**306 954 Haltestellen** (DE 243 278, AT 37 454, CH 26 222). Die Daten stammen
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aus OpenStreetMap (© OpenStreetMap-Mitwirkende, ODbL) und liegen als Snapshot
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im Repo (`data/stops_dach.csv.gz`, ~7,5 MB gepackt).
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Zusätzlich ist pro Haltestelle die Menge der Linien hinterlegt (aus den
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OSM-`route`-Relationen, ~87 % der Halte). Das Feld „Linie" schlägt daraus die
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Linien vor, die an den gewählten Halten verkehren, und füllt sich selbst aus,
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wenn nur eine Linie in Frage kommt. Freitext bleibt immer möglich.
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OSM-`route`-Relationen). Das Feld „Linie" schlägt daraus die Linien vor, die
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an den gewählten Halten verkehren, und füllt sich selbst aus, wenn nur eine
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Linie in Frage kommt. Freitext bleibt immer möglich. Da mehrere Länder
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gleichnamige Haltestellen haben können (mehrere „Hauptbahnhof"), zeigt die
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Vorschlagsliste zusätzlich das Land.
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Nach dem Anlegen der Tabellen den Snapshot in die DB laden:
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@@ -40,14 +43,28 @@ Der Import ist idempotent (Upsert) und braucht kein Internet. Im Produktivbetrie
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übernimmt das die Unit `pbt-import-stops.service` (wird bei jedem Deploy
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angestoßen, s. u.).
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Snapshot neu von OpenStreetMap holen (Halte + Linien, ~5 min, braucht Netzugang
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und ~1 GB RAM):
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### Snapshot aktualisieren
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Bei dieser Größenordnung (AT+DE+CH) geht sich das nicht mehr über die
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öffentliche Overpass-API aus – schon eine reine Zählabfrage für Deutschland
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oder auch nur die Schweiz läuft dort in den Timeout. Stattdessen lädt
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`fetch_stops.py` die offiziellen Geofabrik-Extrakte pro Land herunter
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(`data/.osm-cache/`, nicht committed, ~6 GB) und wertet sie lokal mit
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`pyosmium` aus – keine Last auf einer geteilten API.
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```bash
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python scripts/fetch_stops.py # überschreibt data/stops_at.csv.gz
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pip install osmium # einmalig, nur für dieses Script
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python scripts/fetch_stops.py # überschreibt data/stops_dach.csv.gz
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flask import-stops
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```
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Braucht Netzugang zum Download, ein paar GB RAM und in der Praxis eher
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1–1,5 Stunden als die 5 Minuten von früher (der Großteil davon ist
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Deutschland – Österreich allein dauert ca. 11 Minuten). Bereits
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heruntergeladene Extrakte werden für spätere Läufe wiederverwendet, solange
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sie in `data/.osm-cache/` liegen (~6 GB, `rm -rf data/.osm-cache/` gibt den
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Platz wieder frei).
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## Kartenvorschau (optional, standardmäßig aus)
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Trip-Formular und „Meine Fahrten" können eine kleine Leaflet/OSM-Karte mit den
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@@ -142,6 +142,7 @@ def register_routes(app):
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"id": stop.id,
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"name": stop.name,
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"type": stop.stop_type,
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"country": stop.country,
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"municipality": stop.municipality,
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"lat": stop.latitude,
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"lon": stop.longitude,
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Binary file not shown.
Binary file not shown.
@@ -37,7 +37,8 @@ VERKEHRSMITTEL_OPTIONEN = [
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class Stop(db.Model):
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"""A boardable public-transport stop ("Haltestelle") in Austria.
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"""A boardable public-transport stop ("Haltestelle") in Austria, Germany
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or Switzerland (DACH).
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Sourced from OpenStreetMap; see scripts/fetch_stops.py and stops_import.py.
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"""
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@@ -52,6 +53,9 @@ class Stop(db.Model):
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# lowercased, accent-folded copy of name for diacritic-insensitive search
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name_normalized = db.Column(db.String(200), nullable=False, index=True)
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stop_type = db.Column(db.String(20), nullable=False, default="other")
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# ISO 3166-1 alpha-2 of the fetch query that found this stop (AT/DE/CH) -
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# disambiguates same-named stops across borders (several "Hauptbahnhof").
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country = db.Column(db.String(2), nullable=False, default="AT")
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municipality = db.Column(db.String(120))
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latitude = db.Column(db.Float, nullable=False)
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longitude = db.Column(db.Float, nullable=False)
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+162
-121
@@ -1,59 +1,51 @@
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#!/usr/bin/env python3
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"""Fetch all Austrian public-transport stops (and the lines serving them) from
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OpenStreetMap via the Overpass API and write a deduplicated snapshot to
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data/stops_at.csv.gz.
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"""Fetch all public-transport stops (and the lines serving them) in Austria,
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Germany and Switzerland (DACH) from OpenStreetMap and write a deduplicated
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snapshot to data/stops_dach.csv.gz.
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Data © OpenStreetMap contributors, licensed under the ODbL.
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Run this only when you want to refresh the snapshot; the import into the
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database reads the checked-in CSV and needs no network access. The route pass
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downloads a few hundred MB in ~25 tiles and needs roughly 1 GB of RAM.
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At this scale the public Overpass API can't be used directly - even a plain
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count query for one of these countries times out on it. Instead this
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downloads the official Geofabrik .osm.pbf extract per country (cached in
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data/.osm-cache/, never committed) and processes it locally with pyosmium.
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No load is put on any shared API.
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Run this only when you want to refresh the snapshot; the import into the
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database (`flask import-stops`) reads the checked-in CSV and needs no network
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access. Refreshing needs: `pip install osmium`, ~6 GB of disk for the
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extracts, a few GB of RAM, and maybe 15-30 minutes depending on disk speed
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(most of it is Germany).
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pip install osmium
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python scripts/fetch_stops.py
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"""
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from __future__ import annotations
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import csv
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import gzip
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import json
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import math
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import re
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import sys
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import time
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import unicodedata
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import urllib.parse
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import urllib.request
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from pathlib import Path
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OUT_PATH = Path(__file__).resolve().parent.parent / "data" / "stops_at.csv.gz"
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import osmium
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OVERPASS_ENDPOINTS = [
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"https://overpass-api.de/api/interpreter",
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"https://overpass.kumi.systems/api/interpreter",
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"https://overpass.private.coffee/api/interpreter",
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]
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OUT_PATH = Path(__file__).resolve().parent.parent / "data" / "stops_dach.csv.gz"
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CACHE_DIR = Path(__file__).resolve().parent.parent / "data" / ".osm-cache"
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# Named nodes in Austria that represent a boardable stop ("Haltestelle").
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STOPS_QUERY = """
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[out:json][timeout:600];
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area["ISO3166-1"="AT"][admin_level=2]->.at;
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(
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node(area.at)["highway"="bus_stop"]["name"];
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node(area.at)["railway"="tram_stop"]["name"];
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node(area.at)["railway"="station"]["name"];
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node(area.at)["railway"="halt"]["name"];
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node(area.at)["public_transport"="station"]["name"];
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node(area.at)["amenity"="bus_station"]["name"];
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);
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out body;
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"""
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# ISO 3166-1 alpha-2 -> Geofabrik region file basename.
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GEOFABRIK_REGIONS = {
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"AT": "austria",
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"CH": "switzerland",
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"DE": "germany",
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}
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ROUTE_MODES = "bus|trolleybus|tram|light_rail|subway|train|monorail|share_taxi"
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# Austria bbox, tiled so each Overpass response stays small enough to parse.
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BBOX = (46.35, 9.50, 49.05, 17.20) # south, west, north, east
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LAT_STEP = 0.9
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LON_STEP = 1.0
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ROUTE_MODES = {
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"bus", "trolleybus", "tram", "light_rail", "subway", "train",
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"monorail", "share_taxi",
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}
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STOP_ROLES = {
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"stop", "platform",
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@@ -62,7 +54,7 @@ STOP_ROLES = {
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}
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CSV_FIELDS = [
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"osm_type", "osm_id", "name", "stop_type",
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"osm_type", "osm_id", "name", "stop_type", "country",
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"municipality", "latitude", "longitude", "lines",
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]
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@@ -72,6 +64,8 @@ TYPE_RANK = {"subway": 5, "train": 4, "bus_station": 3, "tram": 2, "bus": 1, "ot
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# nodes with the same name closer than this are treated as one stop.
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MERGE_METERS = 250.0
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MIN_STOPS = 100_000 # DACH sanity floor; refuse to overwrite a good snapshot with junk
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def normalize_name(value: str) -> str:
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"""Lowercase, fold accents and ß so search is diacritic-insensitive.
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@@ -112,46 +106,76 @@ def municipality_of(tags: dict) -> str:
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return ""
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def overpass(query: str, *, tries: int = 4) -> dict:
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body = urllib.parse.urlencode({"data": query}).encode()
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last_error: Exception | None = None
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for attempt in range(tries):
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endpoint = OVERPASS_ENDPOINTS[attempt % len(OVERPASS_ENDPOINTS)]
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try:
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req = urllib.request.Request(
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endpoint, data=body, headers={"User-Agent": "pbt-stop-import/1.0"}
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)
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with urllib.request.urlopen(req, timeout=600) as resp:
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return json.load(resp)
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except Exception as exc: # noqa: BLE001 - retry on another mirror
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last_error = exc
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print(f" {endpoint} failed ({exc}); retrying", file=sys.stderr)
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time.sleep(10 * (attempt + 1))
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raise SystemExit(f"Overpass failed after {tries} tries; last error: {last_error}")
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# --------------------------------------------------------------------------- #
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# Geofabrik download
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# --------------------------------------------------------------------------- #
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def download_extract(iso: str) -> Path:
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region = GEOFABRIK_REGIONS[iso]
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CACHE_DIR.mkdir(parents=True, exist_ok=True)
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dest = CACHE_DIR / f"{region}-latest.osm.pbf"
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if dest.exists() and dest.stat().st_size > 0:
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print(f" using cached {dest.name} ({dest.stat().st_size / 1e6:.0f} MB)", file=sys.stderr)
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return dest
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url = f"https://download.geofabrik.de/europe/{region}-latest.osm.pbf"
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tmp = dest.with_suffix(".pbf.part")
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print(f" downloading {url} ...", file=sys.stderr)
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with urllib.request.urlopen(url, timeout=1800) as resp, open(tmp, "wb") as fh:
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while True:
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chunk = resp.read(1 << 20)
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if not chunk:
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break
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fh.write(chunk)
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tmp.rename(dest)
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print(f" downloaded {dest.name} ({dest.stat().st_size / 1e6:.0f} MB)", file=sys.stderr)
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return dest
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# --------------------------------------------------------------------------- #
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# Stops
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#
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# All three passes below use osmium.FileProcessor with a native (C++-side)
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# filter rather than SimpleHandler.apply_file(): filtering there means most
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# objects never cross into Python at all. A plain SimpleHandler callback -
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# even one that returns immediately - has to be invoked for every single
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# node in the file, and that per-call overhead alone made a whole-country
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# extract (tens of millions of nodes) impractically slow in testing.
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# --------------------------------------------------------------------------- #
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def build_stop_rows(payload: dict) -> list[dict]:
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by_name: dict[str, list[dict]] = {}
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for element in payload.get("elements", []):
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if element.get("type") != "node":
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def collect_stop_nodes(pbf_path: Path, iso: str) -> list[dict]:
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nodes: list[dict] = []
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fp = osmium.FileProcessor(str(pbf_path)).with_filter(osmium.filter.EmptyTagFilter())
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for obj in fp:
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if not obj.is_node() or not obj.location.valid():
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continue
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tags = obj.tags
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if not (
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tags.get("highway") == "bus_stop"
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or tags.get("railway") in ("tram_stop", "station", "halt")
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or tags.get("public_transport") == "station"
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or tags.get("amenity") == "bus_station"
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):
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continue
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tags = element.get("tags", {})
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name = (tags.get("name") or "").strip()
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lat, lon = element.get("lat"), element.get("lon")
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if not name or lat is None or lon is None:
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if not name:
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continue
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node = {
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"osm_id": int(element["id"]),
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tags_dict = {t.k: t.v for t in tags}
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nodes.append({
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"osm_id": int(obj.id),
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"name": name,
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"stop_type": classify(tags),
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"municipality": municipality_of(tags),
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"latitude": round(float(lat), 6),
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"longitude": round(float(lon), 6),
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}
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by_name.setdefault(normalize_name(name), []).append(node)
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"stop_type": classify(tags_dict),
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"country": iso,
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"municipality": municipality_of(tags_dict),
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"latitude": round(obj.location.lat, 6),
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"longitude": round(obj.location.lon, 6),
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})
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print(f" {iso}: {len(nodes)} raw stop nodes", file=sys.stderr)
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return nodes
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def build_stop_rows(nodes: list[dict]) -> list[dict]:
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by_name: dict[str, list[dict]] = {}
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for node in nodes:
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by_name.setdefault(normalize_name(node["name"]), []).append(node)
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rows: list[dict] = []
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for group in by_name.values():
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@@ -180,6 +204,7 @@ def build_stop_rows(payload: dict) -> list[dict]:
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"osm_id": min(n["osm_id"] for n in cluster),
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"name": lead["name"],
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"stop_type": lead["stop_type"],
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"country": lead["country"],
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"municipality": lead["municipality"]
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or next((n["municipality"] for n in cluster if n["municipality"]), ""),
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"latitude": round(sum(n["latitude"] for n in cluster) / len(cluster), 6),
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@@ -194,54 +219,52 @@ def build_stop_rows(payload: dict) -> list[dict]:
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# --------------------------------------------------------------------------- #
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# Lines (route relations -> stops)
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# --------------------------------------------------------------------------- #
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def fetch_route_members() -> tuple[list[tuple[str, int]], dict[int, tuple[str, float, float]]]:
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"""Return (ref, node_id) pairs plus node_id -> (name, lat, lon)."""
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seen_rel: set[int] = set()
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ref_members: list[tuple[str, int]] = []
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def collect_route_members(pbf_path: Path) -> tuple[list[tuple[str, int]], dict[int, tuple[str, float, float]]]:
|
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"""Pass 1: which route relations do we care about, and which node ids do
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their stop/platform members point at? Pass 2: resolve name/coordinates
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||||
for exactly those node ids (they're often bare stop_position nodes with
|
||||
no tags at all, so this can't be narrowed with a tag filter like the
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||||
stops pass - it has to look at every node, hence EntityFilter rather
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||||
than EmptyTagFilter to at least skip all ways in the same pass)."""
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||||
relations: list[tuple[list[str], list[int]]] = []
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wanted_node_ids: set[int] = set()
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fp1 = osmium.FileProcessor(str(pbf_path)).with_filter(osmium.filter.EntityFilter(osmium.osm.RELATION))
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for obj in fp1:
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tags = obj.tags
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if tags.get("route") not in ROUTE_MODES:
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continue
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||||
raw_ref = tags.get("ref")
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||||
if not raw_ref:
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||||
continue
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||||
# A few relations pack several numbers into one ref ("407, 413").
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||||
refs = [part.strip() for part in raw_ref.replace(",", ";").split(";") if part.strip()]
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||||
if not refs:
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||||
continue
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||||
member_ids = [m.ref for m in obj.members if m.type == "n" and m.role in STOP_ROLES]
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if not member_ids:
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||||
continue
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relations.append((refs, member_ids))
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wanted_node_ids.update(member_ids)
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print(
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f" {len(relations)} route relations, "
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||||
f"{len(wanted_node_ids)} distinct stop-member nodes to resolve",
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file=sys.stderr,
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||||
)
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||||
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||||
node_pos: dict[int, tuple[str, float, float]] = {}
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fp2 = osmium.FileProcessor(str(pbf_path)).with_filter(osmium.filter.EntityFilter(osmium.osm.NODE))
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for obj in fp2:
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if obj.id not in wanted_node_ids or not obj.location.valid():
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||||
continue
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node_pos[obj.id] = (obj.tags.get("name", ""), obj.location.lat, obj.location.lon)
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||||
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south, west, north, east = BBOX
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||||
lat = south
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tiles: list[tuple[float, float, float, float]] = []
|
||||
while lat < north:
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||||
lon = west
|
||||
while lon < east:
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||||
tiles.append((lat, lon, min(lat + LAT_STEP, north), min(lon + LON_STEP, east)))
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||||
lon += LON_STEP
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||||
lat += LAT_STEP
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||||
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||||
for i, (s, w, n, e) in enumerate(tiles, 1):
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||||
print(f" route tile {i}/{len(tiles)} ({s:.1f},{w:.1f})", file=sys.stderr)
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||||
query = (
|
||||
f"[out:json][timeout:400];"
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||||
f'relation["type"="route"]["route"~"^({ROUTE_MODES})$"]["ref"]'
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||||
f"({s},{w},{n},{e})->.r;"
|
||||
f".r out body;"
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||||
f"node(r.r);out body;"
|
||||
)
|
||||
payload = overpass(query)
|
||||
for el in payload.get("elements", []):
|
||||
if el["type"] == "node":
|
||||
tags = el.get("tags", {})
|
||||
node_pos[el["id"]] = (tags.get("name", ""), el["lat"], el["lon"])
|
||||
elif el["type"] == "relation":
|
||||
if el["id"] in seen_rel:
|
||||
continue
|
||||
seen_rel.add(el["id"])
|
||||
# A few relations pack several numbers into one ref ("407, 413").
|
||||
refs = [r.strip() for r in re.split(r"[;,]", el["tags"]["ref"]) if r.strip()]
|
||||
if not refs:
|
||||
continue
|
||||
members = [
|
||||
m["ref"] for m in el.get("members", [])
|
||||
if m["type"] == "node" and m["role"] in STOP_ROLES
|
||||
]
|
||||
for ref in refs:
|
||||
for node_id in members:
|
||||
ref_members.append((ref, node_id))
|
||||
del payload
|
||||
|
||||
print(f" {len(seen_rel)} routes, {len(ref_members)} stop memberships", file=sys.stderr)
|
||||
ref_members: list[tuple[str, int]] = []
|
||||
for refs, member_ids in relations:
|
||||
for ref in refs:
|
||||
for node_id in member_ids:
|
||||
ref_members.append((ref, node_id))
|
||||
return ref_members, node_pos
|
||||
|
||||
|
||||
@@ -302,16 +325,31 @@ def line_sort_key(ref: str):
|
||||
|
||||
# --------------------------------------------------------------------------- #
|
||||
def main() -> None:
|
||||
print("Fetching stops ...", file=sys.stderr)
|
||||
rows = build_stop_rows(overpass(STOPS_QUERY))
|
||||
if len(rows) < 10_000:
|
||||
all_nodes: list[dict] = []
|
||||
all_ref_members: list[tuple[str, int]] = []
|
||||
all_node_pos: dict[int, tuple[str, float, float]] = {}
|
||||
|
||||
for iso in GEOFABRIK_REGIONS:
|
||||
print(f"=== {iso} ===", file=sys.stderr)
|
||||
pbf_path = download_extract(iso)
|
||||
|
||||
print(" collecting stops ...", file=sys.stderr)
|
||||
all_nodes.extend(collect_stop_nodes(pbf_path, iso))
|
||||
|
||||
print(" collecting routes ...", file=sys.stderr)
|
||||
ref_members, node_pos = collect_route_members(pbf_path)
|
||||
all_ref_members.extend(ref_members)
|
||||
all_node_pos.update(node_pos)
|
||||
|
||||
print("Clustering stops ...", file=sys.stderr)
|
||||
rows = build_stop_rows(all_nodes)
|
||||
if len(rows) < MIN_STOPS:
|
||||
raise SystemExit(
|
||||
f"Only {len(rows)} stops parsed - refusing to overwrite the snapshot."
|
||||
f"Only {len(rows)} stops parsed (< {MIN_STOPS}) - refusing to overwrite the snapshot."
|
||||
)
|
||||
|
||||
print("Fetching routes ...", file=sys.stderr)
|
||||
ref_members, node_pos = fetch_route_members()
|
||||
matched, unmatched = assign_lines(rows, ref_members, node_pos)
|
||||
print("Matching lines to stops ...", file=sys.stderr)
|
||||
matched, unmatched = assign_lines(rows, all_ref_members, all_node_pos)
|
||||
|
||||
OUT_PATH.parent.mkdir(parents=True, exist_ok=True)
|
||||
with gzip.open(OUT_PATH, "wt", newline="", encoding="utf-8") as fh:
|
||||
@@ -322,10 +360,13 @@ def main() -> None:
|
||||
writer.writerow(row)
|
||||
|
||||
by_type: dict[str, int] = {}
|
||||
by_country: dict[str, int] = {}
|
||||
for row in rows:
|
||||
by_type[row["stop_type"]] = by_type.get(row["stop_type"], 0) + 1
|
||||
by_country[row["country"]] = by_country.get(row["country"], 0) + 1
|
||||
with_lines = sum(1 for r in rows if r["lines"])
|
||||
print(f"Wrote {len(rows)} stops to {OUT_PATH}", file=sys.stderr)
|
||||
print(f" by country: {by_country}", file=sys.stderr)
|
||||
print(f" by type: {by_type}", file=sys.stderr)
|
||||
print(
|
||||
f" lines: {with_lines} stops have >=1 line "
|
||||
|
||||
+1
-1
@@ -152,7 +152,7 @@
|
||||
}
|
||||
var kind = document.createElement("span");
|
||||
kind.className = "kind";
|
||||
kind.textContent = TYPE_LABEL[stop.type] || "";
|
||||
kind.textContent = (TYPE_LABEL[stop.type] || "") + " · " + stop.country;
|
||||
el.appendChild(kind);
|
||||
},
|
||||
onChoose: function (stop) { input.value = stop.name; markMatch(stop); },
|
||||
|
||||
+7
-6
@@ -1,8 +1,8 @@
|
||||
"""Load the checked-in Austrian stop snapshot into the ``stops`` table.
|
||||
"""Load the checked-in DACH stop snapshot into the ``stops`` table.
|
||||
|
||||
The snapshot (data/stops_at.csv.gz) is produced by scripts/fetch_stops.py from
|
||||
OpenStreetMap data (© OpenStreetMap contributors, ODbL). Importing needs no
|
||||
network access.
|
||||
The snapshot (data/stops_dach.csv.gz) is produced by scripts/fetch_stops.py
|
||||
from OpenStreetMap data (© OpenStreetMap contributors, ODbL) for Austria,
|
||||
Germany and Switzerland. Importing needs no network access.
|
||||
|
||||
flask import-stops # import the checked-in snapshot
|
||||
flask import-stops --file X # import an alternative CSV(.gz)
|
||||
@@ -21,7 +21,7 @@ from flask.cli import with_appcontext
|
||||
|
||||
from models import Stop, Trip, db
|
||||
|
||||
SNAPSHOT_PATH = Path(__file__).resolve().parent / "data" / "stops_at.csv.gz"
|
||||
SNAPSHOT_PATH = Path(__file__).resolve().parent / "data" / "stops_dach.csv.gz"
|
||||
|
||||
|
||||
def normalize_name(value: str) -> str:
|
||||
@@ -69,6 +69,7 @@ def import_stops(path: Path | str = SNAPSHOT_PATH) -> dict[str, int]:
|
||||
name=name,
|
||||
name_normalized=normalize_name(name),
|
||||
stop_type=row["stop_type"] or "other",
|
||||
country=(row.get("country") or "AT").strip().upper(),
|
||||
municipality=(row.get("municipality") or "").strip() or None,
|
||||
latitude=float(row["latitude"]),
|
||||
longitude=float(row["longitude"]),
|
||||
@@ -120,7 +121,7 @@ def import_stops(path: Path | str = SNAPSHOT_PATH) -> dict[str, int]:
|
||||
)
|
||||
@with_appcontext
|
||||
def import_stops_command(file_path: str | None) -> None:
|
||||
"""Import Austrian public-transport stops into the database."""
|
||||
"""Import DACH public-transport stops into the database."""
|
||||
stats = import_stops(file_path or SNAPSHOT_PATH)
|
||||
click.echo(
|
||||
"Stops imported: "
|
||||
|
||||
Reference in New Issue
Block a user