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Point your TRMNL private plugin's\n// `polling` strategy at this val's URL. It returns ONE JSON object; the weather\n// panel (and 7-day strip) read straight from it — SVG paths are precomputed\n// here so the Liquid template just prints them.\n//\n// Later tiers (Todoist / calendar / routine / Apple Health) merge into the SAME\n// object: add their keys alongside `weather` / `forecast_days` and return once.\n//\n// No API key needed — Open-Meteo is free. Amsterdam is hard-coded but can be\n// overridden with ?lat=&lon= query params for testing.\n// ---------------------------------------------------------------------------\n\nconst LAT = 52.3676;\nconst LON = 4.9041;\nconst TZ = \"Europe/Amsterdam\";\nconst LOCATION = \"Amsterdam\";\nconst GREETING = \"Good morning, Tom\";\n\n// --- placeholder data for tiers not yet wired -------------------------------\n// The TRMNL markup renders all nine root keys; until calendar/todoist/routine/\n// sleep/vitals/habits are wired to real sources, we ship the same static values\n// the plugin used before so the dashboard stays whole. Replace each block with\n// live data as that tier is built. (Weather + forecast + header are live below.)\nconst PLACEHOLDER = {\n calendar: [\n { time: \"09:00\", title: \"Kok lab meeting\", location: \"Room B1.12\", now: true },\n { time: \"11:30\", title: \"1:1 with Marleen\", location: \"Office\", now: false },\n { time: \"14:00\", title: \"Xenium imaging\", location: \"Microscopy core\", now: false },\n ],\n todoist: [\n { content: \"Send BELLINI figures → Marleen\", priority: 1, due: \"9AM\" },\n { content: \"Review iNKT cover letter\", priority: 1, due: \"\" },\n { content: \"Book Cytek Aurora — WP11765\", priority: 4, due: \"PM\" },\n { content: \"Re-run DESeq2 on clusters\", priority: 4, due: \"\" },\n { content: \"Reply to Andrea — TLS pitch\", priority: 4, due: \"\" },\n ],\n routine: [\"Weigh in\", \"Stretching\", \"Pack lunch\", \"Eye drops\"],\n sleep: {\n total: \"6h 58m\",\n range: \"23:41 → 06:39\",\n score: 72,\n score_offset: 25,\n hypnogram_points:\n \"0,38 16,38 16,58 34,58 34,38 62,38 62,20 82,20 82,38 116,38 116,58 130,58 130,38 172,38 172,20 196,20 196,38 214,38 214,2 224,2 224,38 262,38 262,58 276,58 276,38 300,38 300,20 320,20\",\n },\n vitals: {\n hrv: 68,\n hrv_avg: 61,\n hrv_spark_points: \"0,15 20,11 40,14 60,8 80,12 100,6 120,7\",\n resting_hr: 52,\n resp_rate: 14,\n },\n habits: [\n { label: \"Caffeine\", days: [1, 1, 0, 1, 1, 1, 1, 1] },\n { label: \"Reading\", days: [0, 1, 1, 0, 1, 1, 0, 1] },\n { label: \"Duolingo\", days: [1, 1, 1, 1, 1, 1, 1, 0] },\n { label: \"Vitamin D\", days: [1, 0, 1, 0, 1, 0, 1, 1] },\n ],\n};\n\n// ---- WMO weather-code → icon name + human label -------------------------------\n// icon names are a small fixed vocabulary the Liquid template maps to inline SVG:\n// sun · partly · cloud · fog · rain · snow · storm\nfunction decodeWeather(code: number): { icon: string; label: string } {\n const map: Record = {\n 0: { icon: \"sun\", label: \"Clear\" },\n 1: { icon: \"sun\", label: \"Mainly clear\" },\n 2: { icon: \"partly\", label: \"Partly cloudy\" },\n 3: { icon: \"cloud\", label: \"Overcast\" },\n 45: { icon: \"fog\", label: \"Fog\" },\n 48: { icon: \"fog\", label: \"Rime fog\" },\n 51: { icon: \"rain\", label: \"Light drizzle\" },\n 53: { icon: \"rain\", label: \"Drizzle\" },\n 55: { icon: \"rain\", label: \"Heavy drizzle\" },\n 56: { icon: \"rain\", label: \"Freezing drizzle\" },\n 57: { icon: \"rain\", label: \"Freezing drizzle\" },\n 61: { icon: \"rain\", label: \"Light rain\" },\n 63: { icon: \"rain\", label: \"Rain\" },\n 65: { icon: \"rain\", label: \"Heavy rain\" },\n 66: { icon: \"rain\", label: \"Freezing rain\" },\n 67: { icon: \"rain\", label: \"Freezing rain\" },\n 71: { icon: \"snow\", label: \"Light snow\" },\n 73: { icon: \"snow\", label: \"Snow\" },\n 75: { icon: \"snow\", label: \"Heavy snow\" },\n 77: { icon: \"snow\", label: \"Snow grains\" },\n 80: { icon: \"rain\", label: \"Light showers\" },\n 81: { icon: \"rain\", label: \"Showers\" },\n 82: { icon: \"rain\", label: \"Heavy showers\" },\n 85: { icon: \"snow\", label: \"Snow showers\" },\n 86: { icon: \"snow\", label: \"Snow showers\" },\n 95: { icon: \"storm\", label: \"Thunderstorm\" },\n 96: { icon: \"storm\", label: \"Thunderstorm\" },\n 99: { icon: \"storm\", label: \"Hail storm\" },\n };\n return map[code] ?? { icon: \"cloud\", label: \"—\" };\n}\n\n// ---- axis helpers -------------------------------------------------------------\n// round a rough interval up to a \"nice\" 1 / 2 / 5 × 10ⁿ value\nfunction niceStep(rough: number): number {\n if (rough <= 0) return 1;\n const pow = Math.pow(10, Math.floor(Math.log10(rough)));\n const n = rough / pow;\n const nice = n <= 1 ? 1 : n <= 2 ? 2 : n <= 5 ? 5 : 10;\n return nice * pow;\n}\n\nconst hhmm = (iso: string) => iso.slice(11, 16); // \"2026-08-25T06:45\" → \"06:45\"\n\n// chart geometry — matches the mockup's fc-plot viewBox\nconst W = 524;\nconst H = 114;\nconst SAMPLES = 13; // one point every 2h across 24h (0,2,…,24)\n\ninterface OpenMeteo {\n current: {\n time: string;\n temperature_2m: number;\n apparent_temperature: number;\n relative_humidity_2m: number;\n wind_speed_10m: number;\n uv_index: number;\n weather_code: number;\n };\n hourly: {\n time: string[];\n temperature_2m: number[];\n precipitation_probability: number[];\n };\n daily: {\n time: string[];\n temperature_2m_max: number[];\n temperature_2m_min: number[];\n precipitation_probability_max: number[];\n weather_code: number[];\n uv_index_max: number[];\n sunrise: string[];\n sunset: string[];\n };\n}\n\n// ---- the transform: Open-Meteo → dashboard merge-variable block ---------------\nexport function buildWeather(d: OpenMeteo, now = new Date()) {\n const cur = d.current;\n const wx = decodeWeather(cur.weather_code);\n\n // locate the current hour inside the hourly arrays, then take the next 24h\n let start = d.hourly.time.findIndex((t) => t === cur.time);\n if (start < 0) start = d.hourly.time.findIndex((t) => t >= cur.time);\n if (start < 0) start = 0;\n\n const temps: number[] = [];\n const rains: number[] = [];\n const hours: string[] = [];\n for (let k = 0; k < SAMPLES; k++) {\n const i = Math.min(start + k * 2, d.hourly.time.length - 1);\n temps.push(d.hourly.temperature_2m[i]);\n rains.push(d.hourly.precipitation_probability[i] ?? 0);\n hours.push(d.hourly.time[i]);\n }\n\n // temperature y-scale: nice bounds around the 24h window, 4 gridline labels\n const tMin = Math.min(...temps);\n const tMax = Math.max(...temps);\n const step = niceStep((tMax - tMin) / 3 || 1);\n const bottom = Math.floor(tMin / step) * step;\n const top = bottom + step * 3;\n const tempToY = (t: number) => {\n const y = ((top - t) / (top - bottom)) * H;\n return Math.max(0, Math.min(H, Math.round(y * 10) / 10));\n };\n const rainToY = (p: number) => Math.round((H * (1 - p / 100)) * 10) / 10;\n\n const xAt = (k: number) => Math.round((k / (SAMPLES - 1)) * W);\n\n // temp line (polyline points)\n const temp_line_points = temps.map((t, k) => `${xAt(k)},${tempToY(t)}`).join(\" \");\n\n // rain area (closed path along the bottom)\n const tops = rains.map((p, k) => `${xAt(k)},${rainToY(p)}`).join(\" L \");\n const rain_area_path = `M ${xAt(0)},${H} L ${tops} L ${xAt(SAMPLES - 1)},${H} Z`;\n\n // axis labels\n const y_temp_labels = [top, top - step, top - 2 * step, bottom].map((v) => `${v}°`);\n const x_time_labels = [0, 3, 6, 9, 12].map((k) => hhmm(hours[k])); // every 6h\n\n // 7-day strip\n const dayName = (isoDate: string, k: number) =>\n k === 0\n ? \"Today\"\n : new Date(isoDate + \"T12:00:00\").toLocaleDateString(\"en-US\", {\n weekday: \"short\",\n timeZone: TZ,\n });\n const forecast_days = d.daily.time.map((date, k) => ({\n name: dayName(date, k),\n icon: decodeWeather(d.daily.weather_code[k]).icon,\n high: Math.round(d.daily.temperature_2m_max[k]),\n low: Math.round(d.daily.temperature_2m_min[k]),\n rain: d.daily.precipitation_probability_max[k] ?? 0,\n }));\n\n const parts = new Intl.DateTimeFormat(\"en-GB\", {\n weekday: \"long\", day: \"numeric\", month: \"long\", year: \"numeric\", timeZone: TZ,\n }).formatToParts(now);\n const gp = (t: string) => parts.find((p) => p.type === t)?.value ?? \"\";\n const dateLabel = `${gp(\"weekday\")} · ${gp(\"day\")} ${gp(\"month\")} ${gp(\"year\")}`;\n\n return {\n generated_at: now.toISOString(),\n ...PLACEHOLDER,\n header: {\n greeting: GREETING,\n location: LOCATION,\n date_label: dateLabel,\n sunrise: hhmm(d.daily.sunrise[0]),\n sunset: hhmm(d.daily.sunset[0]),\n },\n weather: {\n now_temp: Math.round(cur.temperature_2m),\n feels: Math.round(cur.apparent_temperature),\n condition: wx.label,\n icon: wx.icon,\n today_high: Math.round(d.daily.temperature_2m_max[0]),\n today_low: Math.round(d.daily.temperature_2m_min[0]),\n humidity: Math.round(cur.relative_humidity_2m),\n wind_kmh: Math.round(cur.wind_speed_10m),\n // peak UV for the day (more useful than the instant value, which is 0 at night)\n uv: Math.round(d.daily.uv_index_max?.[0] ?? cur.uv_index),\n temp_line_points,\n rain_area_path,\n y_temp_labels,\n x_time_labels,\n },\n forecast_days,\n };\n}\n\n// ---- Open-Meteo fetch ---------------------------------------------------------\nasync function fetchOpenMeteo(lat: number, lon: number): Promise {\n const u = new URL(\"https://api.open-meteo.com/v1/forecast\");\n u.searchParams.set(\"latitude\", String(lat));\n u.searchParams.set(\"longitude\", String(lon));\n u.searchParams.set(\"timezone\", TZ);\n u.searchParams.set(\"forecast_days\", \"7\");\n u.searchParams.set(\n \"current\",\n \"temperature_2m,apparent_temperature,relative_humidity_2m,wind_speed_10m,uv_index,weather_code\",\n );\n u.searchParams.set(\"hourly\", \"temperature_2m,precipitation_probability\");\n u.searchParams.set(\n \"daily\",\n \"temperature_2m_max,temperature_2m_min,precipitation_probability_max,weather_code,uv_index_max,sunrise,sunset\",\n );\n const res = await fetch(u.toString());\n if (!res.ok) throw new Error(`Open-Meteo ${res.status}`);\n return (await res.json()) as OpenMeteo;\n}\n\n// ---- Val Town HTTP entrypoint -------------------------------------------------\nexport default async function (req: Request): Promise {\n try {\n const q = new URL(req.url).searchParams;\n const lat = Number(q.get(\"lat\")) || LAT;\n const lon = Number(q.get(\"lon\")) || LON;\n const data = await fetchOpenMeteo(lat, lon);\n const payload = buildWeather(data);\n return new Response(JSON.stringify(payload, null, 2), {\n headers: {\n \"content-type\": \"application/json; charset=utf-8\",\n // cache 10 min at the edge so rapid TRMNL polls don't hammer Open-Meteo\n \"cache-control\": \"public, max-age=600\",\n },\n });\n } catch (err) {\n return new Response(\n JSON.stringify({ error: String(err) }),\n { status: 502, headers: { \"content-type\": \"application/json\" } },\n );\n }\n}","deleted",false,"label",[36],"c670d253-aeeb-4765-ba96-09bd5588c19e","main.ts","3a5373d0-a0b8-11f1-943e-1607ee4eb77e",["D",1787684860088],1,"script","// trmnl-weather.ts — TRMNL X morning-dashboard aggregator (WEATHER slice)\n// ---------------------------------------------------------------------------\n// Deploy as an HTTP val on Val Town. Point your TRMNL private plugin's\n// `polling` strategy at this val's URL. It returns ONE JSON object; the weather\n// panel (and 7-day strip) read straight from it — SVG paths are precomputed\n// here so the Liquid template just prints them.\n//\n// Later tiers (Todoist / calendar / routine / Apple Health) merge into the SAME\n// object: add their keys alongside `weather` / `forecast_days` and return once.\n//\n// No API key needed — Open-Meteo is free. Amsterdam is hard-coded but can be\n// overridden with ?lat=&lon= query params for testing.\n// ---------------------------------------------------------------------------\n\nconst LAT = 52.3676;\nconst LON = 4.9041;\nconst TZ = \"Europe/Amsterdam\";\nconst LOCATION = \"Amsterdam\";\n\n// ---- WMO weather-code → icon name + human label -------------------------------\n// icon names are a small fixed vocabulary the Liquid template maps to inline SVG:\n// sun · partly · cloud · fog · rain · snow · storm\nfunction decodeWeather(code: number): { icon: string; label: string } {\n const map: Record = {\n 0: { icon: \"sun\", label: \"Clear\" },\n 1: { icon: \"sun\", label: \"Mainly clear\" },\n 2: { icon: \"partly\", label: \"Partly cloudy\" },\n 3: { icon: \"cloud\", label: \"Overcast\" },\n 45: { icon: \"fog\", label: \"Fog\" },\n 48: { icon: \"fog\", label: \"Rime fog\" },\n 51: { icon: \"rain\", label: \"Light drizzle\" },\n 53: { icon: \"rain\", label: \"Drizzle\" },\n 55: { icon: \"rain\", label: \"Heavy drizzle\" },\n 56: { icon: \"rain\", label: \"Freezing drizzle\" },\n 57: { icon: \"rain\", label: \"Freezing drizzle\" },\n 61: { icon: \"rain\", label: \"Light rain\" },\n 63: { icon: \"rain\", label: \"Rain\" },\n 65: { icon: \"rain\", label: \"Heavy rain\" },\n 66: { icon: \"rain\", label: \"Freezing rain\" },\n 67: { icon: \"rain\", label: \"Freezing rain\" },\n 71: { icon: \"snow\", label: \"Light snow\" },\n 73: { icon: \"snow\", label: \"Snow\" },\n 75: { icon: \"snow\", label: \"Heavy snow\" },\n 77: { icon: \"snow\", label: \"Snow grains\" },\n 80: { icon: \"rain\", label: \"Light showers\" },\n 81: { icon: \"rain\", label: \"Showers\" },\n 82: { icon: \"rain\", label: \"Heavy showers\" },\n 85: { icon: \"snow\", label: \"Snow showers\" },\n 86: { icon: \"snow\", label: \"Snow showers\" },\n 95: { icon: \"storm\", label: \"Thunderstorm\" },\n 96: { icon: \"storm\", label: \"Thunderstorm\" },\n 99: { icon: \"storm\", label: \"Hail storm\" },\n };\n return map[code] ?? { icon: \"cloud\", label: \"—\" };\n}\n\n// ---- axis helpers -------------------------------------------------------------\n// round a rough interval up to a \"nice\" 1 / 2 / 5 × 10ⁿ value\nfunction niceStep(rough: number): number {\n if (rough <= 0) return 1;\n const pow = Math.pow(10, Math.floor(Math.log10(rough)));\n const n = rough / pow;\n const nice = n <= 1 ? 1 : n <= 2 ? 2 : n <= 5 ? 5 : 10;\n return nice * pow;\n}\n\nconst hhmm = (iso: string) => iso.slice(11, 16); // \"2026-08-25T06:45\" → \"06:45\"\n\n// chart geometry — matches the mockup's fc-plot viewBox\nconst W = 524;\nconst H = 114;\nconst SAMPLES = 13; // one point every 2h across 24h (0,2,…,24)\n\ninterface OpenMeteo {\n current: {\n time: string;\n temperature_2m: number;\n apparent_temperature: number;\n relative_humidity_2m: number;\n wind_speed_10m: number;\n uv_index: number;\n weather_code: number;\n };\n hourly: {\n time: string[];\n temperature_2m: number[];\n precipitation_probability: number[];\n };\n daily: {\n time: string[];\n temperature_2m_max: number[];\n temperature_2m_min: number[];\n precipitation_probability_max: number[];\n weather_code: number[];\n sunrise: string[];\n sunset: string[];\n };\n}\n\n// ---- the transform: Open-Meteo → dashboard merge-variable block ---------------\nexport function buildWeather(d: OpenMeteo, now = new Date()) {\n const cur = d.current;\n const wx = decodeWeather(cur.weather_code);\n\n // locate the current hour inside the hourly arrays, then take the next 24h\n let start = d.hourly.time.findIndex((t) => t === cur.time);\n if (start < 0) start = d.hourly.time.findIndex((t) => t >= cur.time);\n if (start < 0) start = 0;\n\n const temps: number[] = [];\n const rains: number[] = [];\n const hours: string[] = [];\n for (let k = 0; k < SAMPLES; k++) {\n const i = Math.min(start + k * 2, d.hourly.time.length - 1);\n temps.push(d.hourly.temperature_2m[i]);\n rains.push(d.hourly.precipitation_probability[i] ?? 0);\n hours.push(d.hourly.time[i]);\n }\n\n // temperature y-scale: nice bounds around the 24h window, 4 gridline labels\n const tMin = Math.min(...temps);\n const tMax = Math.max(...temps);\n const step = niceStep((tMax - tMin) / 3 || 1);\n const bottom = Math.floor(tMin / step) * step;\n const top = bottom + step * 3;\n const tempToY = (t: number) => {\n const y = ((top - t) / (top - bottom)) * H;\n return Math.max(0, Math.min(H, Math.round(y * 10) / 10));\n };\n const rainToY = (p: number) => Math.round((H * (1 - p / 100)) * 10) / 10;\n\n const xAt = (k: number) => Math.round((k / (SAMPLES - 1)) * W);\n\n // temp line (polyline points)\n const temp_line_points = temps.map((t, k) => `${xAt(k)},${tempToY(t)}`).join(\n \" \",\n );\n\n // rain area (closed path along the bottom)\n const tops = rains.map((p, k) => `${xAt(k)},${rainToY(p)}`).join(\" L \");\n const rain_area_path = `M ${xAt(0)},${H} L ${tops} L ${\n xAt(SAMPLES - 1)\n },${H} Z`;\n\n // axis labels\n const y_temp_labels = [top, top - step, top - 2 * step, bottom].map((v) =>\n `${v}°`\n );\n const x_time_labels = [0, 3, 6, 9, 12].map((k) => hhmm(hours[k])); // every 6h\n\n // 7-day strip\n const dayName = (isoDate: string, k: number) =>\n k === 0\n ? \"Today\"\n : new Date(isoDate + \"T12:00:00\").toLocaleDateString(\"en-US\", {\n weekday: \"short\",\n timeZone: TZ,\n });\n const forecast_days = d.daily.time.map((date, k) => ({\n name: dayName(date, k),\n icon: decodeWeather(d.daily.weather_code[k]).icon,\n high: Math.round(d.daily.temperature_2m_max[k]),\n low: Math.round(d.daily.temperature_2m_min[k]),\n rain: d.daily.precipitation_probability_max[k] ?? 0,\n }));\n\n const dateLabel = now.toLocaleDateString(\"en-GB\", {\n weekday: \"long\",\n day: \"numeric\",\n month: \"long\",\n year: \"numeric\",\n timeZone: TZ,\n });\n\n return {\n generated_at: now.toISOString(),\n header: {\n location: LOCATION,\n date_label: dateLabel,\n sunrise: hhmm(d.daily.sunrise[0]),\n sunset: hhmm(d.daily.sunset[0]),\n },\n weather: {\n now_temp: Math.round(cur.temperature_2m),\n feels: Math.round(cur.apparent_temperature),\n condition: wx.label,\n icon: wx.icon,\n today_high: Math.round(d.daily.temperature_2m_max[0]),\n today_low: Math.round(d.daily.temperature_2m_min[0]),\n humidity: Math.round(cur.relative_humidity_2m),\n wind_kmh: Math.round(cur.wind_speed_10m),\n uv: Math.round(cur.uv_index),\n temp_line_points,\n rain_area_path,\n y_temp_labels,\n x_time_labels,\n },\n forecast_days,\n };\n}\n\n// ---- Open-Meteo fetch ---------------------------------------------------------\nasync function fetchOpenMeteo(lat: number, lon: number): Promise {\n const u = new URL(\"https://api.open-meteo.com/v1/forecast\");\n u.searchParams.set(\"latitude\", String(lat));\n u.searchParams.set(\"longitude\", String(lon));\n u.searchParams.set(\"timezone\", TZ);\n u.searchParams.set(\"forecast_days\", \"7\");\n u.searchParams.set(\n \"current\",\n \"temperature_2m,apparent_temperature,relative_humidity_2m,wind_speed_10m,uv_index,weather_code\",\n );\n u.searchParams.set(\"hourly\", \"temperature_2m,precipitation_probability\");\n u.searchParams.set(\n \"daily\",\n \"temperature_2m_max,temperature_2m_min,precipitation_probability_max,weather_code,sunrise,sunset\",\n );\n const res = await fetch(u.toString());\n if (!res.ok) throw new Error(`Open-Meteo ${res.status}`);\n return (await res.json()) as OpenMeteo;\n}\n\n// ---- Val Town HTTP entrypoint -------------------------------------------------\nexport default async function (req: Request): Promise {\n try {\n const q = new URL(req.url).searchParams;\n const lat = Number(q.get(\"lat\")) || LAT;\n const lon = Number(q.get(\"lon\")) || LON;\n const data = await fetchOpenMeteo(lat, lon);\n const payload = buildWeather(data);\n return new Response(JSON.stringify(payload, null, 2), {\n headers: {\n \"content-type\": \"application/json; 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Code