[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_154":155,"_156":157},"routes/_app.x.$handle.$name",{"_11":12,"_13":14,"_15":16,"_18":19,"_17":-7,"_117":-5,"_20":118,"_22":119,"_120":121,"_122":123,"_25":124,"_24":-5,"_125":-5,"_126":-5,"_127":53,"_128":129,"_130":44,"_131":-5,"_132":-5,"_133":134},"routes/_app.x.$handle.$name.branch.$branch.code.$",{"_11":12,"_13":14,"_15":16,"_17":-7,"_18":19,"_20":21,"_22":23,"_24":-7,"_25":26,"_27":-5,"_28":-5,"_29":-5,"_30":-5,"_31":-5},"handle","niclaskamm","name","health-notion-sync","branchName","main","version","path","","project",{"_33":61,"_13":14,"_45":62,"_63":-5,"_64":53,"_65":66,"_67":66,"_68":69,"_70":-5,"_71":72,"_73":37,"_74":44,"_75":-5,"_76":-5,"_77":78,"_79":80,"_81":-5,"_82":-5,"_83":-5,"_84":-5,"_85":86,"_87":86,"_88":89,"_90":89,"_91":89,"_92":86,"_93":86,"_94":95,"_96":97,"_98":99,"_100":53},"tree",[56],"file","contents",[32],"upstream","pull","ahead","behind","envVars",{"_33":34,"_13":35,"_36":37,"_38":-5,"_39":40,"_41":42,"_43":44,"_45":46,"_17":47,"_48":49,"_50":51,"_52":53,"_54":-5,"_18":55},"id","5d3fbf6e-5a1a-11f1-8b3c-ee650bb23af1","main.ts","fileId","d60571d6-58ef-11f1-9722-ee650bb23af1","parentId","branchId","b61ce656-58ef-11f1-8b8e-ee650bb23af1","branchVersion",15,"latest",true,"createdAt",["D",1779920470518],14,"fileType","http","content","// HAE → Notion Health Inbox endpoint · v7 (2026-05-28)\n// FIX v7: Multi-Day-Aggregation. aggQty/aggCat summierten ALLE Samples (auch aus Vortagen\n// wenn HAE Backfill liefert). Jetzt: alle Sample-Dates sammeln → neuestes als\n// targetDate → nur Samples dieses Datums aggregieren. Behebt 1598-Samples-für-1-Tag.\n\nconst NOTION_PAGE_ID = \"36a858d6-0e6a-814a-adb3-e3ee68cb43eb\";\nconst NOTION_TOKEN = \"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\";\nconst NOTION = \"https://api.notion.com/v1\";\nconst HDR = {\n \"Authorization\": `Bearer ${NOTION_TOKEN}`,\n \"Notion-Version\": \"2022-06-28\",\n \"Content-Type\": \"application/json\",\n};\n\nexport default async function (req: Request): Promise {\n if (req.method !== \"POST\") return new Response(\"POST only\", { status: 405 });\n\n const payload = await req.json();\n const data = payload?.data ?? payload ?? {};\n const metricsIn: any[] = Array.isArray(data.metrics) ? data.metrics : [];\n\n const pickArr = (...c: any[]) =>\n c.find((x) => Array.isArray(x) && x.length > 0) ?? [];\n const workoutsInAll: any[] = pickArr(\n data.workouts,\n payload.workouts,\n data.workout,\n payload.workout,\n data.activities,\n payload.activities,\n );\n\n // PATCH 9 (NEU v7) — Multi-Day Date-Filter\n const allDates: Set = new Set();\n for (const m of metricsIn) {\n for (const s of (m.data ?? [])) {\n const d = s.date ?? s.endDate ?? s.startDate;\n if (d) allDates.add(String(d).slice(0, 10));\n }\n }\n for (const w of workoutsInAll) {\n const d = w.start ?? w.startDate ?? w.startTime ?? w.startISO;\n if (d) allDates.add(String(d).slice(0, 10));\n }\n const sortedDates = Array.from(allDates).sort();\n const targetDate = sortedDates.at(-1) ?? new Intl.DateTimeFormat(\"sv-SE\", {\n timeZone: \"Europe/Berlin\",\n year: \"numeric\",\n month: \"2-digit\",\n day: \"2-digit\",\n }).format(new Date());\n console.log(\n \"payload_dates:\",\n sortedDates.join(\",\") || \"(none)\",\n \"→ targetDate:\",\n targetDate,\n \"total_dates:\",\n sortedDates.length,\n );\n\n const filterToDate = (arr: any[]) =>\n arr.filter((s) => {\n const d = s.date ?? s.endDate ?? s.startDate;\n return !d || String(d).slice(0, 10) === targetDate;\n });\n\n // Workouts auf Ziel-Datum begrenzen\n const workoutsIn = workoutsInAll.filter((w) => {\n const d = w.start ?? w.startDate ?? w.startTime ?? w.startISO;\n return !d || String(d).slice(0, 10) === targetDate;\n });\n\n console.log(\n \"metrics_count:\",\n metricsIn.length,\n \"workouts_count_filtered:\",\n workoutsIn.length,\n \"of_total:\",\n workoutsInAll.length,\n );\n if (workoutsIn.length > 0) {\n console.log(\"workout_first_keys:\", Object.keys(workoutsIn[0]).join(\",\"));\n }\n\n const r = (n: any, d = 1) => {\n if (n == null || isNaN(n)) return 0;\n const f = 10 ** d;\n return Math.round(n * f) / f;\n };\n const minBetween = (a: string, b: string) =>\n (+new Date(b) - +new Date(a)) / 60000;\n const hhmm = (iso: string) =>\n iso\n ? new Date(iso).toLocaleTimeString(\"de-DE\", {\n timeZone: \"Europe/Berlin\",\n hour: \"2-digit\",\n minute: \"2-digit\",\n })\n : \"\";\n\n const SUM = new Set([\n \"count\",\n \"kcal\",\n \"kJ\",\n \"m\",\n \"km\",\n \"mi\",\n \"L\",\n \"mL\",\n \"g\",\n \"mg\",\n \"µg\",\n \"IU\",\n \"step\",\n \"steps\",\n \"flight\",\n \"flights\",\n \"min\",\n \"minutes\",\n \"s\",\n \"seconds\",\n \"cup\",\n \"oz\",\n ]);\n const AVG = new Set([\n \"bpm\",\n \"ms\",\n \"%\",\n \"°C\",\n \"°F\",\n \"L/min\",\n \"mmHg\",\n \"mg/dL\",\n \"mmol/L\",\n \"mL/(kg*min)\",\n \"mL/kg·min\",\n \"count/min\",\n \"dBASPL\",\n \"dBHL\",\n \"UV index\",\n \"µSv\",\n \"m/s\",\n \"kg/m²\",\n \"kcal/hr\",\n \"W\",\n ]);\n const LAST = new Set([\"cm\", \"kg\", \"lb\", \"in\", \"BMI\", \"ft\", \"%body\"]);\n\n const detectAgg = (units: string, arr: any[]) => {\n if (\n arr.length && arr[0].value !== undefined && arr[0].startDate &&\n arr[0].endDate\n ) return \"category\";\n const u = (units ?? \"\").trim();\n if (SUM.has(u)) return \"sum\";\n if (AVG.has(u)) return \"avg\";\n if (LAST.has(u)) return \"last\";\n return \"sum\";\n };\n\n const aggQty = (arr: any[]) => {\n const vals = arr.map((s) => s.qty).filter((v: any) =>\n v != null && !isNaN(v)\n );\n if (!vals.length) {\n return { sum: 0, avg: 0, min: 0, max: 0, last: 0, count: 0 };\n }\n const sum = vals.reduce((a: number, b: number) => a + b, 0);\n const sorted = [...arr].filter((s) => s.qty != null).sort((a, b) =>\n +new Date(a.date) - +new Date(b.date)\n );\n return {\n sum: r(sum, 2),\n avg: r(sum / vals.length, 2),\n min: r(Math.min(...vals), 2),\n max: r(Math.max(...vals), 2),\n last: r(sorted.at(-1)?.qty ?? 0, 2),\n count: vals.length,\n };\n };\n\n const aggCat = (arr: any[]) => {\n const by: Record = {};\n let first: string | null = null, last: string | null = null;\n for (const s of arr) {\n const mins = minBetween(s.startDate, s.endDate);\n by[s.value] = (by[s.value] || 0) + mins;\n if (!first || +new Date(s.startDate) < +new Date(first)) {\n first = s.startDate;\n }\n if (!last || +new Date(s.endDate) > +new Date(last)) last = s.endDate;\n }\n for (const k of Object.keys(by)) by[k] = r(by[k], 0);\n const total = Object.values(by).reduce((a, b) => a + b, 0);\n return {\n by_category_min: by,\n total_min: r(total, 0),\n first_start: first,\n last_end: last,\n };\n };\n\n const metricsOut: Record = {};\n for (const m of metricsIn) {\n const arrRaw = Array.isArray(m.data) ? m.data : [];\n const arr = filterToDate(arrRaw);\n const agg = detectAgg(m.units, arr);\n if (agg === \"category\") {\n metricsOut[m.name] = {\n units: m.units ?? \"\",\n agg,\n value: aggCat(arr),\n samples_n: arr.length,\n };\n } else {\n const stats = aggQty(arr);\n const value = agg === \"avg\"\n ? stats.avg\n : agg === \"last\"\n ? stats.last\n : stats.sum;\n metricsOut[m.name] = {\n units: m.units ?? \"\",\n agg,\n value,\n stats,\n samples_n: arr.length,\n };\n }\n }\n\n const sr = metricsIn.find((m) => m.name === \"sleep_analysis\");\n let sleep = {\n total_min: 0,\n deep_min: 0,\n rem_min: 0,\n core_min: 0,\n awake_min: 0,\n in_bed_min: 0,\n asleep_min: 0,\n in_bed_from: \"\",\n out_of_bed: \"\",\n sleep_score_apple: 0,\n };\n\n if (sr?.data?.length) {\n const srData = filterToDate(sr.data);\n if (srData.length) {\n const first = srData[0];\n const isAggregated = first &&\n (first.asleep !== undefined || first.deep !== undefined ||\n first.core !== undefined || first.rem !== undefined ||\n first.inBed !== undefined);\n if (isAggregated) {\n const sum = srData.reduce((acc: any, d: any) => ({\n deep: acc.deep + (d.deep ?? 0),\n rem: acc.rem + (d.rem ?? 0),\n core: acc.core + (d.core ?? 0),\n asleep: acc.asleep + (d.asleep ?? 0),\n awake: acc.awake + (d.awake ?? 0),\n inBed: acc.inBed + (d.inBed ?? d.in_bed ?? 0),\n }), { deep: 0, rem: 0, core: 0, asleep: 0, awake: 0, inBed: 0 });\n const total = sum.deep + sum.rem + sum.core +\n (sum.asleep && (sum.deep + sum.rem + sum.core === 0)\n ? sum.asleep\n : 0);\n const ib = srData.find((d: any) =>\n d.sleepStart || d.startDate || d.in_bed_start\n )?.sleepStart ??\n srData.find((d: any) => d.startDate)?.startDate ??\n srData.find((d: any) => d.in_bed_start)?.in_bed_start;\n const ob = srData.find((d: any) =>\n d.sleepEnd || d.endDate || d.in_bed_end\n )?.sleepEnd ??\n srData.find((d: any) => d.endDate)?.endDate ??\n srData.find((d: any) => d.in_bed_end)?.in_bed_end;\n sleep = {\n total_min: r(total || sum.asleep, 0),\n deep_min: r(sum.deep, 0),\n rem_min: r(sum.rem, 0),\n core_min: r(sum.core, 0),\n awake_min: r(sum.awake, 0),\n in_bed_min: r(sum.inBed, 0),\n asleep_min: r(sum.asleep, 0),\n in_bed_from: ib ? hhmm(ib) : \"\",\n out_of_bed: ob ? hhmm(ob) : \"\",\n sleep_score_apple: 0,\n };\n } else {\n const mins = (lbl: string) =>\n srData.filter((s: any) =>\n (s.value || \"\").toLowerCase().includes(lbl.toLowerCase())\n ).reduce(\n (sum: number, s: any) => sum + minBetween(s.startDate, s.endDate),\n 0,\n );\n const deep = mins(\"deep\"),\n rem = mins(\"rem\"),\n core = mins(\"core\"),\n asleep = mins(\"asleep\"),\n awake = mins(\"awake\"),\n inBed = mins(\"inbed\");\n const bed = srData.filter((s: any) =>\n /inbed|asleep|core|deep|rem/i.test(s.value || \"\")\n );\n const ib = bed.length\n ? bed.reduce((a: any, b: any) =>\n +new Date(a.startDate) < +new Date(b.startDate) ? a : b\n ).startDate\n : null;\n const ob = bed.length\n ? bed.reduce((a: any, b: any) =>\n +new Date(a.endDate) > +new Date(b.endDate) ? a : b\n ).endDate\n : null;\n sleep = {\n total_min: r(\n core + deep + rem +\n (asleep && (core + deep + rem === 0) ? asleep : 0),\n 0,\n ),\n deep_min: r(deep, 0),\n rem_min: r(rem, 0),\n core_min: r(core, 0),\n awake_min: r(awake, 0),\n in_bed_min: r(inBed, 0),\n asleep_min: r(asleep, 0),\n in_bed_from: hhmm(ib),\n out_of_bed: hhmm(ob),\n sleep_score_apple: 0,\n };\n }\n console.log(\n \"sleep_samples_filtered:\",\n srData.length,\n \"of_total:\",\n sr.data.length,\n );\n }\n }\n\n const workouts = workoutsIn.map((w) => ({\n name: w.name ?? w.workoutActivityType ?? w.activityType ?? w.type ??\n w.activity ?? \"Workout\",\n start: w.start ?? w.startDate ?? w.startTime ?? w.startISO ?? \"\",\n end: w.end ?? w.endDate ?? w.endTime ?? w.endISO ?? \"\",\n duration_min: r(\n (w.duration ?? w.durationInSeconds ?? w.totalDuration ?? w.elapsedTime ??\n 0) / 60,\n 0,\n ),\n kcal: r(\n w.totalEnergyBurned ?? w.activeEnergyBurned ??\n w.totalActiveEnergyBurned ?? w.calories ?? w.activeKilocalories ?? 0,\n 0,\n ),\n distance_m: r(\n w.totalDistance ?? w.distance ?? w.totalDistanceMeters ?? 0,\n 0,\n ),\n elevation_m: r(\n w.elevationGain ?? w.elevationAscended ?? w.elevation_ascended ??\n w.totalElevation ?? 0,\n 0,\n ),\n avg_hr: r(\n w.avgHeartRate ?? w.averageHeartRate ?? w.heartRate?.avg ??\n w.heartRateAverage ?? 0,\n 0,\n ),\n max_hr: r(\n w.maxHeartRate ?? w.maximumHeartRate ?? w.heartRate?.max ??\n w.heartRateMax ?? 0,\n 0,\n ),\n }));\n\n const date = targetDate;\n const pick = (k: string, d = 1) => r(metricsOut[k]?.value ?? 0, d);\n const pickN = (k: string, d = 1) =>\n pick(k, d) || pick(k.replace(/^dietary_/, \"\"), d);\n\n const summary = {\n heart_rate_avg: pick(\"heart_rate\", 0),\n resting_hr: pick(\"resting_heart_rate\", 0),\n walking_hr_avg: pick(\"walking_heart_rate_average\", 0),\n hrv_ms: pick(\"heart_rate_variability\", 1),\n heart_rate_recovery_one_minute: pick(\"heart_rate_recovery_one_minute\", 0),\n respiratory_rate: pick(\"respiratory_rate\", 1),\n spo2_pct: pick(\"blood_oxygen_saturation\", 1),\n vo2max: pick(\"vo2_max\", 1) || pick(\"vo2max\", 1),\n steps: pick(\"step_count\", 0),\n flights_climbed: pick(\"flights_climbed\", 0),\n distance_walking_running_m: pick(\"walking_running_distance\", 0) ||\n pick(\"distance_walking_running\", 0),\n distance_cycling_m: pick(\"cycling_distance\", 0) ||\n pick(\"distance_cycling\", 0),\n distance_swimming_m: pick(\"swimming_distance\", 0) ||\n pick(\"distance_swimming\", 0),\n push_count: pick(\"push_count\", 0),\n apple_exercise_time_min: pick(\"apple_exercise_time\", 0),\n apple_move_time_min: pick(\"apple_move_time\", 0),\n apple_stand_time_min: pick(\"apple_stand_time\", 0),\n active_energy_kcal: pick(\"active_energy\", 0),\n basal_energy_kcal: pick(\"basal_energy_burned\", 0),\n weight_kg: pick(\"weight_body_mass\", 1) || pick(\"body_mass\", 1),\n body_fat_pct: pick(\"body_fat_percentage\", 1),\n lean_body_mass_kg: pick(\"lean_body_mass\", 1),\n bmi: pick(\"body_mass_index\", 1),\n height_cm: pick(\"height\", 0),\n waist_circumference_cm: pick(\"waist_circumference\", 1),\n body_temp_c: pick(\"body_temperature\", 1),\n basal_body_temp_c: pick(\"basal_body_temperature\", 2),\n wrist_temp_dev_c: pick(\"apple_sleeping_wrist_temperature\", 2),\n bp_systolic: pick(\"blood_pressure_systolic\", 0),\n bp_diastolic: pick(\"blood_pressure_diastolic\", 0),\n blood_glucose_mgdl: pick(\"blood_glucose\", 0),\n running_power_w: pick(\"running_power\", 0),\n running_speed_ms: pick(\"running_speed\", 2),\n running_stride_length_m: pick(\"running_stride_length\", 2),\n running_vertical_oscillation_cm: pick(\"running_vertical_oscillation\", 1),\n running_ground_contact_time_ms: pick(\"running_ground_contact_time\", 0),\n walking_speed_ms: pick(\"walking_speed\", 2),\n walking_step_length_cm: pick(\"walking_step_length\", 1),\n walking_double_support_pct: pick(\"walking_double_support_percentage\", 1),\n walking_asymmetry_pct: pick(\"walking_asymmetry_percentage\", 1),\n six_minute_walking_test_m: pick(\"six_minute_walking_test_distance\", 0),\n stair_ascent_speed_ms: pick(\"stair_ascent_speed\", 2),\n stair_descent_speed_ms: pick(\"stair_descent_speed\", 2),\n dietary_energy_kcal: pickN(\"dietary_energy\", 0),\n dietary_water_ml: pickN(\"dietary_water\", 0),\n dietary_protein_g: pickN(\"dietary_protein\", 1),\n dietary_carbohydrates_g: pickN(\"dietary_carbohydrates\", 1),\n dietary_fat_total_g: pickN(\"dietary_fat_total\", 1) || pick(\"total_fat\", 1),\n dietary_fat_saturated_g: pickN(\"dietary_fat_saturated\", 1) ||\n pick(\"saturated_fat\", 1),\n dietary_fiber_g: pickN(\"dietary_fiber\", 1),\n dietary_sugar_g: pickN(\"dietary_sugar\", 1),\n dietary_sodium_mg: pickN(\"dietary_sodium\", 0),\n dietary_potassium_mg: pickN(\"dietary_potassium\", 0),\n dietary_calcium_mg: pickN(\"dietary_calcium\", 0),\n dietary_iron_mg: pickN(\"dietary_iron\", 1),\n dietary_magnesium_mg: pickN(\"dietary_magnesium\", 0),\n dietary_zinc_mg: pickN(\"dietary_zinc\", 1),\n dietary_caffeine_mg: pickN(\"dietary_caffeine\", 0),\n dietary_cholesterol_mg: pickN(\"dietary_cholesterol\", 0),\n dietary_vitamin_c_mg: pickN(\"dietary_vitamin_c\", 1),\n dietary_vitamin_d_iu: pickN(\"dietary_vitamin_d\", 0),\n dietary_vitamin_b12_µg: pickN(\"dietary_vitamin_b12\", 2),\n dietary_vitamin_b6_mg: pickN(\"dietary_vitamin_b6\", 2),\n dietary_vitamin_a_iu: pickN(\"dietary_vitamin_a\", 0),\n dietary_vitamin_e_mg: pickN(\"dietary_vitamin_e\", 2),\n dietary_vitamin_k_µg: pickN(\"dietary_vitamin_k\", 1),\n mindful_min: pick(\"mindful_minutes\", 0) || pick(\"mindful_min\", 0),\n time_in_daylight_min: pick(\"time_in_daylight\", 0),\n headphone_audio_exposure_dB: pick(\"headphone_audio_exposure\", 1),\n environmental_audio_exposure_dB: pick(\"environmental_audio_exposure\", 1),\n uv_exposure: pick(\"uv_exposure\", 1),\n forced_expiratory_volume_1_L: pick(\"forced_expiratory_volume_1\", 2),\n forced_vital_capacity_L: pick(\"forced_vital_capacity\", 2),\n peak_expiratory_flow_L_min: pick(\"peak_expiratory_flow_rate\", 1),\n inhaler_usage: pick(\"inhaler_usage\", 0),\n electrodermal_activity_µS: pick(\"electrodermal_activity\", 2),\n number_of_times_fallen: pick(\"number_of_times_fallen\", 0),\n handwashing_events: pick(\"handwashing_event\", 0) || pick(\"handwashing\", 0),\n workouts_count: workouts.length,\n workout_kcal_total: r(\n workouts.reduce((acc, w) => acc + (w.kcal || 0), 0),\n 0,\n ),\n workout_duration_total_min: r(\n workouts.reduce((acc, w) => acc + (w.duration_min || 0), 0),\n 0,\n ),\n };\n\n const freshSnapshot = {\n date,\n generated_at: new Date().toISOString(),\n sleep,\n workouts,\n metrics: metricsOut,\n summary,\n };\n\n // Notion list + delete + append (mit Merge, wie v6)\n const all: any[] = [];\n let cursor: string | undefined;\n do {\n const u = new URL(`${NOTION}/blocks/${NOTION_PAGE_ID}/children`);\n if (cursor) u.searchParams.set(\"start_cursor\", cursor);\n u.searchParams.set(\"page_size\", \"100\");\n const res = await fetch(u, { headers: HDR });\n if (!res.ok) {\n return new Response(\n JSON.stringify({\n ok: false,\n step: \"list\",\n notion_status: res.status,\n notion_error: await res.text(),\n }),\n { status: 502, headers: { \"Content-Type\": \"application/json\" } },\n );\n }\n const j = await res.json();\n all.push(...(j.results || []));\n cursor = j.has_more ? j.next_cursor : undefined;\n } while (cursor);\n\n let existingSnapshot: any = null;\n const blockIdsToDelete: string[] = [];\n for (let i = 0; i < all.length; i++) {\n const b = all[i];\n if (\n b.type === \"heading_3\" &&\n (b.heading_3.rich_text?.[0]?.plain_text || \"\").trim() === date\n ) {\n blockIdsToDelete.push(b.id);\n for (let j = 1; j < 3 && all[i + j]; j++) {\n const x = all[i + j];\n if (x.type === \"code\") {\n blockIdsToDelete.push(x.id);\n const fullText = (x.code.rich_text || []).map((rt: any) =>\n rt.plain_text ?? rt.text?.content ?? \"\"\n ).join(\"\");\n try {\n existingSnapshot = JSON.parse(fullText);\n } catch (e) {\n console.error(\n \"EXISTING_JSON_PARSE_FAILED:\",\n String(e).slice(0, 200),\n );\n existingSnapshot = null;\n }\n } else if (x.type === \"divider\") blockIdsToDelete.push(x.id);\n else break;\n }\n break;\n }\n }\n\n const mergeNonZero = >(\n ex: T | undefined,\n fr: T,\n ): T => {\n if (!ex) return fr;\n const out: any = { ...ex };\n for (const k of Object.keys(fr)) {\n const fv = (fr as any)[k], ev = (ex as any)[k];\n const fHas = typeof fv === \"number\"\n ? fv !== 0\n : typeof fv === \"string\"\n ? fv.length > 0\n : fv != null;\n const eHas = typeof ev === \"number\"\n ? ev !== 0\n : typeof ev === \"string\"\n ? ev.length > 0\n : ev != null;\n out[k] = fHas ? fv : (eHas ? ev : fv);\n }\n return out as T;\n };\n const mergeWorkouts = (ex: any[] = [], fr: any[] = []) => {\n const m = new Map();\n for (const w of ex) m.set(`${w.name ?? \"\"}|${w.start ?? \"\"}`, w);\n for (const w of fr) {\n const k = `${w.name ?? \"\"}|${w.start ?? \"\"}`;\n m.set(k, m.has(k) ? mergeNonZero(m.get(k), w) : w);\n }\n return Array.from(m.values()).sort((a, b) =>\n String(a.start || \"\").localeCompare(String(b.start || \"\"))\n );\n };\n const mergeMetrics = (\n ex: Record = {},\n fr: Record = {},\n ) => {\n const out: Record = { ...ex };\n for (const k of Object.keys(fr)) {\n const fv = fr[k], ev = ex[k];\n const fHas = fv &&\n ((typeof fv.value === \"number\" && fv.value !== 0) ||\n (typeof fv.value === \"object\" && fv.value !== null) ||\n (fv.samples_n ?? 0) > 0);\n out[k] = fHas ? fv : (ev ?? fv);\n }\n return out;\n };\n\n const mergedSnapshot = existingSnapshot\n ? {\n date,\n generated_at: freshSnapshot.generated_at,\n sleep: mergeNonZero(existingSnapshot.sleep, freshSnapshot.sleep),\n workouts: mergeWorkouts(\n existingSnapshot.workouts ?? [],\n freshSnapshot.workouts ?? [],\n ),\n metrics: mergeMetrics(\n existingSnapshot.metrics ?? {},\n freshSnapshot.metrics ?? {},\n ),\n summary: mergeNonZero(existingSnapshot.summary, freshSnapshot.summary),\n }\n : freshSnapshot;\n\n if (mergedSnapshot.workouts && mergedSnapshot.summary) {\n mergedSnapshot.summary.workouts_count = mergedSnapshot.workouts.length;\n mergedSnapshot.summary.workout_kcal_total = r(\n mergedSnapshot.workouts.reduce(\n (a: number, w: any) => a + (w.kcal || 0),\n 0,\n ),\n 0,\n );\n mergedSnapshot.summary.workout_duration_total_min = r(\n mergedSnapshot.workouts.reduce(\n (a: number, w: any) => a + (w.duration_min || 0),\n 0,\n ),\n 0,\n );\n }\n\n for (const id of blockIdsToDelete) {\n const dr = await fetch(`${NOTION}/blocks/${id}`, {\n method: \"DELETE\",\n headers: HDR,\n });\n if (!dr.ok) console.error(\"NOTION_DELETE_FAILED:\", dr.status, \"id:\", id);\n }\n\n const jsonStr = JSON.stringify(mergedSnapshot, null, 2);\n const CHUNK = 1900;\n const richTextChunks: any[] = [];\n for 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Code