Measurement site	Body of water	County	Date	Water temperature [°C]
Starnberg	StarnbergerSee	STA	19.07.2026 19:00	22.9
Ammerseeboje	Ammersee	LL	--	--
BadRow

`;\n\n// Mock date converter: returns the input unchanged so assertions are stable.\nconst mockConvert = (s: string) => s;\n\nconst readings = parseWaterTemperatures(html, 0, mockConvert);\n\nassertEqual(readings.length, 1, \"only the valid row is parsed\");\n\nassertEqual(\n readings[0] satisfies WaterTemperatureReading,\n {\n category_id: 0,\n measurement_site: \"Starnberg\",\n body_of_water: \"StarnbergerSee\",\n measured_at: \"19.07.2026 19:00\",\n water_temperature: 22.9,\n },\n \"valid row has correct fields\",\n);\n\n// Verify categoryId flows through for rivers (category_id=1).\nconst riverReadings = parseWaterTemperatures(html, 1, mockConvert);\nassertEqual(riverReadings[0].category_id, 1, \"rivers use category_id=1\");\n\nconsole.log(\"\\nAll tests passed.\");\n",[],[90,165],"41f2d670-1e36-4dee-b8ee-1f0b02714605","german-date.ts","d3cc2e9c-8396-11f1-b1dd-1607ee4eb77e",["D",1784481924665],"/**\n * Parse a German-format date string (\"24.05.2023 20:00\") as Berlin local time\n * and return the corresponding UTC ISO-8601 timestamp.\n *\n * Berlin observes CET (UTC+1) in winter and CEST (UTC+2) in summer. The offset\n * is resolved for the specific date via Intl timezone formatting, so DST\n * boundaries are handled correctly — no fixed UTC offset assumption.\n *\n * Used to convert gkd.bayern.de measurement timestamps (which are Berlin\n * wall-clock) into the UTC `measured_at` column stored in SQLite.\n */\nexport function germanDateToUtcIso(dateStr: string): string {\n const [day, month, year, hour, minute] = dateStr.split(/[.: ]/).map(Number);\n // Treat the components as if they were UTC to get a reference instant.\n const guess = new Date(Date.UTC(year, month - 1, day, hour, minute));\n // Determine Berlin's UTC offset (minutes) at that instant, then shift back.\n const offsetMin = berlinOffsetMinutes(guess);\n return new Date(guess.getTime() - offsetMin * 60000).toISOString();\n}\n\n/**\n * Return Berlin's UTC offset (in minutes) at the given instant. Positive means\n * Berlin is ahead of UTC (CEST = +120, CET = +60).\n *\n * Uses the same Intl trick as api/pools.ts's berlinDayUtcBounds: format the\n * instant as Berlin wall-clock, parse back as if UTC, and diff.\n */\nfunction berlinOffsetMinutes(at: Date): number {\n const s = at.toLocaleString(\"en-US\", {\n timeZone: \"Europe/Berlin\",\n hour12: false,\n year: \"numeric\",\n month: \"2-digit\",\n day: \"2-digit\",\n hour: \"2-digit\",\n minute: \"2-digit\",\n second: \"2-digit\",\n });\n // s like \"07/17/2026, 20:38:04\"\n const [d, t] = s.split(\", \");\n const [mo, da, yr] = d.split(\"/\").map(Number);\n const [h, mi, se] = t.split(\":\").map(Number);\n const asUtc = Date.UTC(yr, mo - 1, da, h, mi, se);\n return Math.round((asUtc - at.getTime()) / 60000);\n}\n",[],[90,172],"eab32498-06b9-4217-b196-00cee9e5ff83","german-date.test.ts","d3cc25d2-8396-11f1-b1dd-1607ee4eb77e",["D",1784481924665],"import { germanDateToUtcIso } from \"./german-date.ts\";\n\nfunction assertEqual(actual: unknown, expected: unknown, label: string): void {\n const a = JSON.stringify(actual);\n const e = JSON.stringify(expected);\n if (a !== e) {\n throw new Error(`FAIL: ${label}\\n expected: ${e}\\n actual: ${a}`);\n }\n console.log(`PASS: ${label} → ${a}`);\n}\n\n// Summer (CEST, UTC+2): 20:00 Berlin → 18:00 UTC\nassertEqual(\n germanDateToUtcIso(\"24.05.2023 20:00\"),\n \"2023-05-24T18:00:00.000Z\",\n \"summer CEST 20:00 Berlin → 18:00 UTC\",\n);\n\n// Winter (CET, UTC+1): 18:00 Berlin → 17:00 UTC\nassertEqual(\n germanDateToUtcIso(\"15.01.2023 18:00\"),\n \"2023-01-15T17:00:00.000Z\",\n \"winter CET 18:00 Berlin → 17:00 UTC\",\n);\n\n// Midnight Berlin → previous day 22:00 UTC (summer)\nassertEqual(\n germanDateToUtcIso(\"19.07.2026 00:00\"),\n \"2026-07-18T22:00:00.000Z\",\n \"midnight CEST → previous day 22:00 UTC\",\n);\n\n// Noon Berlin → 10:00 UTC (summer)\nassertEqual(\n germanDateToUtcIso(\"19.07.2026 12:00\"),\n \"2026-07-19T10:00:00.000Z\",\n \"noon CEST → 10:00 UTC\",\n);\n\n// DST transition spring: 26.03.2023 03:00 (just after spring-forward)\nassertEqual(\n germanDateToUtcIso(\"26.03.2023 03:00\"),\n \"2023-03-26T01:00:00.000Z\",\n \"after spring-forward 03:00 CEST → 01:00 UTC\",\n);\n\nconsole.log(\"\\nAll tests passed.\");\n",[],[90,179],"63212832-fac2-415b-9ff5-cddef63210d0","business-hours.ts","d556390a-820c-11f1-8a02-1607ee4eb77e",["D",1784312705542],"/**\n * Munich / German business-hours guard, ported from v1 cron/german-business-hours.js.\n * Returns true between 07:00 and 23:00 Europe/Berlin time. Used to skip pool\n * occupancy logging overnight when the baths are closed.\n */\nexport function isGermanBusinessHours(now: Date = new Date()): boolean {\n const germanTime = now.toLocaleString(\"en-US\", { timeZone: \"Europe/Berlin\" });\n const hours = new Date(germanTime).getHours();\n return hours >= 7 && hours < 23;\n}\n",[],[90,186],"976a6e28-b4f0-46ab-825c-6a3aaea2870a","db","caca4203-217f-44e5-9a2c-341ad96c7be7",["D",1784311938655],[198],[193],{"_35":199,"_13":200,"_38":201,"_40":194,"_42":43,"_44":159,"_46":47,"_48":202,"_17":203,"_51":112,"_53":204,"_55":56,"_57":-5,"_86":205,"_18":206},"c00dc9e1-a3d0-4af2-a91c-3413043f2d77","schema.ts","0c3d430c-820b-11f1-b505-1607ee4eb77e",["D",1784481924665],4,"import { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\n\n/**\n * Create all tables + indexes. Idempotent: safe to run on every deploy.\n * All timestamps are ISO-8601 UTC strings, e.g. \"2024-06-01T18:00:00Z\".\n */\nexport async function migrate() {\n await sqlite.batch([\n // --- Water temperatures (lakes, rivers, feringasee) ---\n `CREATE TABLE IF NOT EXISTS water_temperatures (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n category_id INTEGER NOT NULL, -- 0 = lakes, 1 = rivers\n measurement_site TEXT NOT NULL,\n body_of_water TEXT NOT NULL,\n measured_at TEXT NOT NULL, -- ISO-8601 UTC\n water_temperature REAL NOT NULL,\n updated_at TEXT NOT NULL -- ISO-8601 UTC\n )`,\n // Upsert key: one reading per site+body+time.\n `CREATE UNIQUE INDEX IF NOT EXISTS idx_water_temperatures_unique\n ON water_temperatures (category_id, measurement_site, body_of_water, measured_at)`,\n // Read path: latest readings per body of water within a category.\n `CREATE INDEX IF NOT EXISTS idx_water_temperatures_read\n ON water_temperatures (category_id, body_of_water, measured_at)`,\n\n // --- Bodies of water catalog (presentation metadata for the UI) ---\n // Auto-populated by the water-temperature scraper (INSERT OR IGNORE by\n // category_id + name). `geopath` is curated by hand afterwards.\n `CREATE TABLE IF NOT EXISTS bodies_of_water (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n category_id INTEGER NOT NULL, -- 0 = lakes, 1 = rivers\n name TEXT NOT NULL, -- matches water_temperatures.body_of_water\n slug TEXT NOT NULL, -- generated from name\n geopath TEXT, -- optional frontend asset, e.g. \"isar.svg\"\n created_at TEXT NOT NULL -- ISO-8601 UTC\n )`,\n `CREATE UNIQUE INDEX IF NOT EXISTS idx_bodies_of_water_unique\n ON bodies_of_water (category_id, name)`,\n `CREATE INDEX IF NOT EXISTS idx_bodies_of_water_slug\n ON bodies_of_water (category_id, slug)`,\n\n // --- Bath areas catalog (SWM pool occupancy) ---\n // Roster comes from the SWM visitorCount feed itself (locations -> areas),\n // so this is auto-populated by the pools cron, not hand-seeded. Each area\n // (Hallenbad / Freibad / Sauna / ...) belongs to a location.\n `CREATE TABLE IF NOT EXISTS bath_areas (\n area_id INTEGER PRIMARY KEY, -- SWM area_id\n area_name TEXT NOT NULL,\n location_id INTEGER NOT NULL, -- SWM location_id\n location_name TEXT NOT NULL,\n active INTEGER NOT NULL DEFAULT 1, -- hide areas without deleting history\n updated_at TEXT NOT NULL -- ISO-8601 UTC\n )`,\n `CREATE INDEX IF NOT EXISTS idx_bath_areas_location\n ON bath_areas (location_id)`,\n\n // --- Pool occupancy history (area-level time series) ---\n `CREATE TABLE IF NOT EXISTS occupancy_log (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n area_id INTEGER NOT NULL, -- -> bath_areas.area_id\n customer_amount INTEGER NOT NULL, -- current occupancy\n customer_amount_max INTEGER NOT NULL, -- capacity\n recorded_at TEXT NOT NULL -- ISO-8601 UTC\n )`,\n `CREATE INDEX IF NOT EXISTS idx_occupancy_log_read\n ON occupancy_log (area_id, recorded_at)`,\n ]);\n}\n\n/**\n * Slugify a body-of-water name. Ported verbatim from v1 src/lib/slugify.js so\n * generated slugs match the frontend's expectations (ä→ae, ö→oe, ü→ue, spaces→-).\n */\nexport function slugify(text: string): string {\n const replacements: Record = { \"ä\": \"ae\", \"ö\": \"oe\", \"ü\": \"ue\" };\n text = text.toLowerCase();\n for (const [umlaut, replacement] of Object.entries(replacements)) {\n text = text.split(umlaut).join(replacement);\n }\n return text.replace(/\\s+/g, \"-\");\n}\n\n/**\n * Register any newly-seen bodies of water in the catalog. Called by the water\n * scraper with the (category_id, name) pairs it just observed. INSERT OR IGNORE\n * keeps existing rows (and their curated `geopath`) untouched.\n */\nexport async function upsertBodiesOfWater(\n bodies: { category_id: number; name: string }[],\n): Promise {\n if (bodies.length === 0) return;\n // De-dupe within this batch so we don't issue redundant inserts.\n const seen = new Set();\n const unique = bodies.filter((b) => {\n const key = `${b.category_id}\\u0000${b.name}`;\n if (seen.has(key)) return false;\n seen.add(key);\n return true;\n });\n const now = new Date().toISOString();\n await sqlite.batch(\n unique.map((b) => ({\n sql: `INSERT OR IGNORE INTO bodies_of_water (category_id, name, slug, created_at)\n VALUES (?, ?, ?, ?)`,\n args: [b.category_id, b.name, slugify(b.name), now],\n })),\n );\n}\n\n/**\n * Upsert water-temperature readings. On conflict (same category+site+body+time),\n * update the temperature and `updated_at` timestamp so re-scraping is idempotent.\n * Mirrors the upsertBathAreas pattern.\n */\nexport async function upsertWaterTemperatures(\n readings: {\n category_id: number;\n measurement_site: string;\n body_of_water: string;\n measured_at: string;\n water_temperature: number;\n }[],\n): Promise {\n if (readings.length === 0) return;\n const now = new Date().toISOString();\n await sqlite.batch(\n readings.map((r) => ({\n sql: `INSERT INTO water_temperatures\n (category_id, measurement_site, body_of_water, measured_at, water_temperature, updated_at)\n VALUES (?, ?, ?, ?, ?, ?)\n ON CONFLICT(category_id, measurement_site, body_of_water, measured_at) DO UPDATE SET\n water_temperature = excluded.water_temperature,\n updated_at = excluded.updated_at`,\n args: [r.category_id, r.measurement_site, r.body_of_water, r.measured_at, r.water_temperature, now],\n })),\n );\n}\n\n/**\n * Keep the bath_areas roster in sync with the SWM feed. Upserts area/location\n * names by area_id (so renames propagate) without touching the `active` flag\n * once a row exists — you can deactivate areas by hand and it will stick.\n */\nexport async function upsertBathAreas(\n areas: { area_id: number; area_name: string; location_id: number; location_name: string }[],\n): Promise {\n if (areas.length === 0) return;\n const now = new Date().toISOString();\n await sqlite.batch(\n areas.map((a) => ({\n sql: `INSERT INTO bath_areas (area_id, area_name, location_id, location_name, active, updated_at)\n VALUES (?, ?, ?, ?, 1, ?)\n ON CONFLICT(area_id) DO UPDATE SET\n area_name = excluded.area_name,\n location_id = excluded.location_id,\n location_name = excluded.location_name,\n updated_at = excluded.updated_at`,\n args: [a.area_id, a.area_name, a.location_id, a.location_name, now],\n })),\n );\n}\n",[],[193,200],"7eb4bc66-14c6-4aa3-a9b9-5469b6fab177","cron","d0f4549d-bbf6-4e80-b297-f7fc8a3e7f9c",16,["D",1784312720344],[214,215,216],[208],{"_35":231,"_13":232,"_38":233,"_40":209,"_42":43,"_44":234,"_46":47,"_48":235,"_17":83,"_51":220,"_53":236,"_55":56,"_57":-5,"_86":237,"_18":238},{"_35":224,"_13":225,"_38":226,"_40":209,"_42":43,"_44":210,"_46":47,"_48":227,"_17":71,"_51":220,"_53":228,"_55":56,"_57":-5,"_86":229,"_18":230},{"_35":217,"_13":37,"_38":218,"_40":209,"_42":43,"_44":159,"_46":47,"_48":219,"_17":71,"_51":220,"_53":221,"_55":56,"_57":-5,"_86":222,"_18":223},"755c2c95-93fd-423d-ada2-9d7f8d33e54b","d3cc1614-8396-11f1-b1dd-1607ee4eb77e",["D",1784481924665],"interval","import { fetch as stdFetch } from \"https://esm.town/v/std/fetch\";\nimport { migrate, upsertBodiesOfWater, upsertWaterTemperatures } from \"../db/schema.ts\";\nimport { parseWaterTemperatures } from \"../lib/parse-water-temperatures.ts\";\nimport { germanDateToUtcIso } from \"../lib/german-date.ts\";\n\nconst SOURCES = [\n { category_id: 0, url: \"https://www.gkd.bayern.de/en/lakes/watertemperature/tables\" },\n { category_id: 1, url: \"https://www.gkd.bayern.de/en/rivers/watertemperature/tables\" },\n] as const;\n\nasync function fetchHtml(url: string): Promise {\n const res = await stdFetch(url, {\n headers: { accept: \"text/html\", \"user-agent\": \"Mozilla/5.0\" },\n });\n if (!res.ok) throw new Error(`HTTP ${res.status} for ${url}`);\n return await res.text();\n}\n\n/**\n * One cron pass: fetch both lakes and rivers tables from gkd.bayern.de, parse\n * them into readings, register any newly-seen bodies of water in the catalog\n * (slug auto-generated), and upsert the readings. Idempotent — re-scraping the\n * same measurement just refreshes `updated_at`.\n */\nexport async function recordWaterTemperatures(): Promise<{\n lakes: number;\n rivers: number;\n}> {\n await migrate();\n const counts: Record = {};\n for (const source of SOURCES) {\n const html = await fetchHtml(source.url);\n const readings = parseWaterTemperatures(html, source.category_id, germanDateToUtcIso);\n const bodies = readings.map((r) => ({ category_id: r.category_id, name: r.body_of_water }));\n await upsertBodiesOfWater(bodies);\n await upsertWaterTemperatures(readings);\n counts[source.category_id] = readings.length;\n }\n return { lakes: counts[0] ?? 0, rivers: counts[1] ?? 0 };\n}\n\nexport default async function (interval: Interval) {\n const result = await recordWaterTemperatures();\n console.log(\n `Scraped ${result.lakes} lake readings and ${result.rivers} river readings.`,\n );\n}\n",[],[208,37],"6d8aef11-7bc2-48fe-bff3-d7c9f3c1dfa3","pools-capacity.ts","de2a3e3c-820c-11f1-aaf3-1607ee4eb77e",["D",1784312720344],"import { fetch as stdFetch } from \"https://esm.town/v/std/fetch\";\nimport { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\nimport { migrate, upsertBathAreas } from \"../db/schema.ts\";\nimport { isGermanBusinessHours } from \"../lib/business-hours.ts\";\n\nconst VISITOR_COUNT_URL = \"https://www.swm.de/.rest/bath/visitorCount\";\n\ninterface SwmArea {\n area_id: number;\n area_name: string;\n customer_amount: number;\n customer_amount_max: number;\n}\ninterface SwmLocation {\n location_id: number;\n location_name: string;\n area_list: SwmArea[];\n}\ninterface SwmResponse {\n return_code: string;\n data: SwmLocation[];\n}\n\n/**\n * Fetch the full SWM bath occupancy feed. A single request (no query params)\n * returns every location with its nested areas and live counts.\n */\nasync function fetchVisitorCounts(): Promise {\n const res = await stdFetch(VISITOR_COUNT_URL, {\n headers: { accept: \"*/*\", \"user-agent\": \"Mozilla/5.0\" },\n });\n if (!res.ok) throw new Error(`SWM visitorCount HTTP ${res.status}`);\n const json = (await res.json()) as SwmResponse;\n if (json.return_code !== \"success\" || !Array.isArray(json.data)) {\n throw new Error(`SWM visitorCount unexpected response: ${JSON.stringify(json).slice(0, 200)}`);\n }\n return json.data;\n}\n\n/**\n * One cron pass: fetch the feed, sync the area roster, and log area-level\n * occupancy. Skips logging outside Munich business hours (baths closed), but\n * still refreshes the roster so new areas are discovered even overnight.\n */\nexport async function recordOccupancy(now: Date = new Date()): Promise<{\n skipped: boolean;\n areas: number;\n rows: number;\n}> {\n await migrate();\n\n const locations = await fetchVisitorCounts();\n\n // Flatten locations -> areas, carrying the parent location metadata.\n const flat = locations.flatMap((loc) =>\n loc.area_list.map((a) => ({\n area_id: a.area_id,\n area_name: a.area_name,\n location_id: loc.location_id,\n location_name: loc.location_name,\n customer_amount: a.customer_amount,\n customer_amount_max: a.customer_amount_max,\n }))\n );\n\n // Keep the roster fresh regardless of the hour.\n await upsertBathAreas(flat);\n\n if (!isGermanBusinessHours(now)) {\n return { skipped: true, areas: flat.length, rows: 0 };\n }\n\n const recorded_at = now.toISOString();\n await sqlite.batch(\n flat.map((a) => ({\n sql: `INSERT INTO occupancy_log (area_id, customer_amount, customer_amount_max, recorded_at)\n VALUES (?, ?, ?, ?)`,\n args: [a.area_id, a.customer_amount, a.customer_amount_max, recorded_at],\n })),\n );\n\n return { skipped: false, areas: flat.length, rows: flat.length };\n}\n\nexport default async function (interval: Interval) {\n const result = await recordOccupancy();\n console.log(\n result.skipped\n ? `Outside business hours — refreshed ${result.areas} areas, logged 0 rows.`\n : `Logged ${result.rows} occupancy rows across ${result.areas} areas.`,\n );\n}\n",[],[208,225],"1c4f882b-7bd1-41a6-a7b8-c77844d91d66","feringasee.ts","bc7812fe-83a2-11f1-a9b7-1607ee4eb77e",32,["D",1784487378812],"import { fetch as stdFetch } from \"https://esm.town/v/std/fetch\";\nimport {\n migrate,\n upsertBodiesOfWater,\n upsertWaterTemperatures,\n} from \"../db/schema.ts\";\nimport { germanDateToUtcIso } from \"../lib/german-date.ts\";\n\nconst URL = \"https://xn--wasserwacht-unterfhring-plc.de/aktuelles-wetter/\";\n\n// \"vom 19.07.2026 20:10: 25.80 Grad Celius im Wasser und 24.40 Grad Celsius an der Luft.\"\n// \"Celius\" (sic) is a typo in the source's water-temperature wording — preserved verbatim.\nconst READING_REGEX =\n /vom (\\d{2}\\.\\d{2}\\.\\d{4}\\s\\d{2}:\\d{2}):\\s([\\d.]+) Grad Celius im Wasser und ([\\d.]+) Grad Celsius an der Luft\\./;\n\nasync function fetchHtml(url: string): Promise {\n const res = await stdFetch(url, {\n headers: { accept: \"text/html\", \"user-agent\": \"Mozilla/5.0\" },\n });\n if (!res.ok) throw new Error(`HTTP ${res.status} for ${url}`);\n return await res.text();\n}\n\n/**\n * One cron pass: fetch the Wasserwacht Unterföhring Feringasee weather page,\n * extract the latest water+air temperature reading, register Feringasee in the\n * bodies-of-water catalog if new, and upsert the reading. Idempotent —\n * re-scraping the same measurement just refreshes `updated_at`.\n *\n * Returns null when no reading is found on the page (sensors down, page\n * restructured, etc.), otherwise the parsed reading.\n */\nexport async function recordFeringasee(): Promise<{\n water_temperature: number;\n air_temperature: number;\n measured_at: string;\n} | null> {\n await migrate();\n const html = await fetchHtml(URL);\n // The page wraps the temperature values in tags (e.g. \"25.80 Grad\n // Celius\"). Strip all tags so the regex sees plain text, matching the\n // original v1 scraper's use of node-html-parser's .textContent.\n const text = html.replace(/<[^>]+>/g, \"\");\n const match = text.match(READING_REGEX);\n if (!match) return null;\n\n const measured_at = germanDateToUtcIso(match[1]);\n const water_temperature = parseFloat(match[2]);\n const air_temperature = parseFloat(match[3]);\n\n await upsertBodiesOfWater([{ category_id: 0, name: \"Feringasee\" }]);\n await upsertWaterTemperatures([\n {\n category_id: 0,\n measurement_site: \"Feringasee\",\n body_of_water: \"Feringasee\",\n measured_at,\n water_temperature,\n },\n ]);\n\n return { water_temperature, air_temperature, measured_at };\n}\n\nexport default async function (interval: Interval) {\n const result = await recordFeringasee();\n if (!result) {\n console.log(\"No Feringasee reading found on the page.\");\n return;\n }\n console.log(\n `Feringasee: ${result.water_temperature}°C water, ${result.air_temperature}°C air at ${result.measured_at}.`,\n );\n}\n",[],[208,232],["D",1784313509669],[242,243],[19],{"_35":60,"_13":61,"_38":62,"_40":41,"_42":43,"_44":63,"_46":47,"_48":247,"_17":65,"_51":52,"_53":66,"_55":56,"_57":67,"_86":248,"_18":249},{"_35":36,"_13":37,"_38":39,"_40":41,"_42":43,"_44":45,"_46":47,"_48":244,"_17":50,"_51":52,"_53":54,"_55":56,"_57":58,"_86":245,"_18":246},["D",1785062610268],[],[19,37],["D",1785058040952],[],[19,61],"d8bfb0f0-1676-42ac-a1a4-4ef765725e9b",["D",1784311508215],"deletedAt","legacyEnvVars","privacy","public","httpPrivacy","description","Munich water temps & pool capacity: backend, DB, 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