\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n

Blood Sugar Weekly Rollup

${stats.start} to ${stats.end}

\n 🔺 🔷 〰️ 🟢 〰️ 🔶 〰️ 🟡 〰️ 🟣 🔺 🔵 〰️\n

\n \n \n \n \n \n \n

Avg

${stats.avg}

Min

${stats.min}

Max

${stats.max}

\n \n \n \n \n \n \n \n \n \n

\n \n Entries \n ${stats.count}/${stats.expected} \n \n	\n \n Completion \n ${stats.completionRate}% \n \n
\n \n Streak \n ${stats.currentStreak} day${stats.currentStreak === 1 ? \"\" : \"s\"} \n \n	\n \n XP \n ${stats.xp} \n \n

\n Perfect Week Streak: ${stats.perfectWeekStreak ? \"Yes\" : \"No\"}\n

\n Badges:\n

\n ${\n stats.badges.length\n ? stats.badges\n .map(\n (badge) =>\n `${escapeHtml(badge)}`,\n )\n .join(\"\")\n : `No badges yet`\n }\n

\n ${escapeHtml(stats.encouragement)}\n

\n ${escapeHtml(stats.disclaimer)}\n

\n Entries\n

\n \n \n \n \n \n \n \n \n \n ${rows || ``}\n \n

Date	1st	2nd
No entries

\n `;\n}\n\nexport function escapeHtml(value: string): string {\n return value\n .replaceAll(\"&\", \"&\")\n .replaceAll(\"<\", \"<\")\n .replaceAll(\">\", \">\")\n .replaceAll('\"', \""\")\n .replaceAll(\"'\", \"'\");\n}\n",[],[1853,1860],{"_105":1870,"_97":1871,"_161":1872,"_163":1854,"_164":146,"_165":1873,"_167":168,"_107":1874,"_101":1875,"_170":1865,"_172":1876,"_173":22,"_174":-5,"_175":1877,"_100":1878},"8f078c0a-f7ac-11f0-9c14-42dde27851f2","food_report.cron.tsx","f851115a-f233-11f0-a807-42dde27851f2",417,["D",1769098095429],38,"import { getWeeklyRange } from \"../shared/date.ts\";\nimport { OpenAI } from \"https://esm.town/v/std/openai\";\nimport { fetchNotionPages, type NotionPage, updateNotionPage } from \"../shared/notion.ts\";\nimport { fetchFoodMacros, getFatSecretConfig, requestAccessToken, sumIfComplete } from \"../shared/fatsecret.ts\";\nimport {\n buildNutritionProperties,\n buildFoodRollup,\n type Entry,\n type MacroKey,\n parseEntry,\n PROPERTY_NAMES,\n roundNumber,\n safeParseJson,\n shouldEnrich,\n} from \"../shared/food_enrich.ts\";\nimport { initRollupSchema, upsertWeeklyRollup } from \"../storage/rollups.ts\";\n\ntype NotionConfig = {\n token: string;\n databaseId: string;\n};\n\nexport default async function () {\n // Resolve configs and hydrate external clients first to fail fast.\n const notionConfig = getNotionConfig();\n if (!notionConfig) {\n return new Response(\"Missing Notion secrets.\", { status: 500 });\n }\n const openai = new OpenAI();\n const fatSecretConfig = getFatSecretConfig();\n const fatSecretToken = fatSecretConfig ? await requestAccessToken(fatSecretConfig) : null;\n\n const { start, end } = getWeeklyRange();\n const entries = await fetchEntries(start, end, notionConfig);\n console.log(`Food entries ${start} to ${end}:`, entries);\n\n let enriched = 0;\n for (const entry of entries) {\n // Only enrich entries missing core macros to avoid overwriting manual edits.\n if (!shouldEnrich(entry)) continue;\n if (!entry.food || entry.food === \"Unknown\") continue;\n const enrichment = await fetchNutrition(entry.food, openai, fatSecretConfig, fatSecretToken);\n if (!enrichment) continue;\n const properties = buildNutritionProperties(enrichment.macros);\n if (!Object.keys(properties).length) continue;\n console.log(\"Enriching entry\", {\n pageId: entry.pageId,\n food: entry.food,\n loggedAt: entry.loggedAt,\n macros: enrichment.macros,\n });\n console.log(\"Notion update properties\", {\n pageId: entry.pageId,\n properties,\n });\n await updateNotionPage(entry.pageId, notionConfig.token, properties);\n entry.macros = { ...entry.macros, ...enrichment.macros };\n enriched += 1;\n }\n\n await initRollupSchema();\n const rollup = buildFoodRollup(entries, start, end);\n await upsertWeeklyRollup(rollup);\n\n return new Response(`Weekly food entries logged. Enriched ${enriched}.`, { status: 200 });\n}\n\nfunction getNotionConfig(): NotionConfig | null {\n const token = Deno.env.get(\"NOTION_TOKEN\");\n const databaseId = Deno.env.get(\"NOTION_FOOD_DB_ID\");\n if (!token || !databaseId) return null;\n return { token, databaseId };\n}\n\nasync function fetchEntries(start: string, end: string, config: NotionConfig): Promise {\n // Pull just the last-week window to keep the Notion query fast.\n const pages = await fetchNotionPages(config.databaseId, config.token, (cursor) => ({\n filter: {\n and: [\n { property: PROPERTY_NAMES.loggedAt, date: { on_or_after: start } },\n { property: PROPERTY_NAMES.loggedAt, date: { on_or_before: end } },\n ],\n },\n sorts: [{ property: PROPERTY_NAMES.loggedAt, direction: \"ascending\" }],\n ...(cursor ? { start_cursor: cursor } : {}),\n }));\n\n const entries: Entry[] = [];\n for (const page of pages) {\n const entry = parseEntry(page);\n if (entry) entries.push(entry);\n }\n\n return entries;\n}\n\nasync function fetchNutrition(\n foodName: string,\n openai: OpenAI,\n config: ReturnType,\n token: string | null,\n): Promise<{\n macros: Partial>;\n} | null> {\n if (!config || !token) return null;\n const items = await parseFoodItems(foodName, openai);\n const macros = await fetchFatSecretTotals(items, foodName, token, config);\n if (!macros || !Object.keys(macros).length) return null;\n return { macros };\n}\n\ntype FoodItem = {\n name: string;\n servings: number;\n};\n\nasync function parseFoodItems(foodName: string, openai: OpenAI): Promise {\n // Keep the OpenAI request compact to control costs.\n const completion = await openai.chat.completions.create({\n model: \"gpt-5-nano\",\n messages: [\n {\n role: \"system\",\n content:\n \"You normalize food log entries. \" +\n \"Return a single JSON object: {\\\"items\\\":[{\\\"name\\\":\\\"...\\\",\\\"servings\\\":1}]}. \" +\n \"Correct spelling, keep names short, and split sides when phrased as \\\"with\\\" or \\\"and\\\". \" +\n \"Infer servings for a regular meal: default to 1 per item; if explicit quantities are given, \" +\n \"convert to a servings multiplier. Keep brands and key ingredients. No extra text.\",\n },\n {\n role: \"user\",\n content: `Food entry: \"${foodName}\".`,\n },\n ],\n max_tokens: 160,\n });\n\n const text = completion.choices[0]?.message?.content?.trim();\n if (!text) return [{ name: foodName, servings: 1 }];\n const parsed = safeParseJson(text);\n if (!parsed || typeof parsed !== \"object\") return [{ name: foodName, servings: 1 }];\n const items = (parsed as Record).items;\n if (!Array.isArray(items)) return [{ name: foodName, servings: 1 }];\n const cleaned = items\n .map((item) => coerceFoodItem(item))\n .filter((item): item is FoodItem => !!item)\n .map((item) => ({\n name: item.name.trim(),\n servings: sanitizeServings(item.servings),\n }))\n .filter((item) => item.name.length > 0);\n return cleaned.length ? cleaned : [{ name: foodName, servings: 1 }];\n}\n\nasync function fetchFatSecretTotals(\n items: FoodItem[],\n original: string,\n token: string,\n config: ReturnType,\n): Promise> | null> {\n if (!config) return null;\n const components: Array> | null> = [];\n for (const item of items) {\n const macros = await fetchFoodMacros(item.name, token);\n components.push(macros ? scaleMacros(macros, item.servings) : null);\n }\n\n if (components.length === 1 && components[0]) return components[0];\n const totals = sumComponentMacros(components);\n if (totals && hasCoreMacros(totals)) return totals;\n const fallback = await fetchFoodMacros(original, token);\n return fallback ?? null;\n}\n\nconst CORE_MACROS: MacroKey[] = [\"calories\", \"protein\", \"carbs\", \"fat\"];\nconst SUM_MACROS: MacroKey[] = [\"calories\", \"protein\", \"carbs\", \"fat\", \"fiber\", \"sugar\", \"sodium\"];\n\nfunction hasCoreMacros(macros: Partial>): boolean {\n return CORE_MACROS.every((key) => typeof macros[key] === \"number\");\n}\n\nfunction sumComponentMacros(\n components: Array> | null>,\n): Partial> | null {\n if (!components.length) return null;\n if (components.some((component) => !component)) return null;\n const entries = components as Array>>;\n const totals: Partial> = {};\n for (const key of SUM_MACROS) {\n const value = sumIfComplete(entries.map((entry) => entry[key]));\n if (value !== undefined) totals[key] = value;\n }\n return totals;\n}\n\nfunction coerceFoodItem(item: unknown): FoodItem | null {\n if (typeof item === \"string\") {\n return { name: item, servings: 1 };\n }\n if (!item || typeof item !== \"object\") return null;\n const record = item as Record;\n const name = record.name;\n if (typeof name !== \"string\") return null;\n const servings = record.servings;\n if (typeof servings === \"number\" && Number.isFinite(servings)) {\n return { name, servings };\n }\n if (typeof servings === \"string\") {\n const parsed = Number(servings.trim());\n if (Number.isFinite(parsed)) return { name, servings: parsed };\n }\n return { name, servings: 1 };\n}\n\nfunction sanitizeServings(value: number): number {\n if (!Number.isFinite(value) || value <= 0) return 1;\n return roundNumber(value);\n}\n\nfunction scaleMacros(\n macros: Partial>,\n servings: number,\n): Partial> {\n const scaled: Partial> = {};\n for (const [key, value] of Object.entries(macros) as Array<[MacroKey, number]>) {\n if (typeof value !== \"number\") continue;\n scaled[key] = roundNumber(value * servings);\n }\n return scaled;\n}\n",[],[1853,1871],[1853],{"_105":1881,"_97":1882,"_161":1883,"_163":-5,"_164":146,"_165":1884,"_167":168,"_107":1885,"_101":33,"_170":171,"_172":-5,"_173":22,"_174":-5,"_175":1886,"_100":1908},"250d8f1e-f23b-11f0-88fe-42dde27851f2","services","250d8fd2-f23b-11f0-88fe-42dde27851f2",92,["D",1768499628695],[1887,1898],{"_105":1888,"_97":1889,"_161":1890,"_163":1883,"_164":146,"_165":1891,"_167":168,"_107":1892,"_101":1893,"_170":1894,"_172":1895,"_173":22,"_174":-5,"_175":1896,"_100":1897},"65ed11d8-fadf-11f0-b590-42dde27851f2","monthly_report_page.http.tsx","044f06e4-f31d-11f0-b40c-42dde27851f2",428,["D",1769449784146],17,"http","import React from \"https://esm.sh/react@18.2.0\";\nimport { renderToString } from \"https://esm.sh/react-dom@18.2.0/server\";\nimport { sqlite } from \"../storage/sqlite.ts\";\nimport {\n aggregateBloodSugarMonth,\n aggregateFoodMonth,\n resolveMonthRange,\n type Rollup,\n} from \"../shared/monthly_report.ts\";\n\n// HTTP val that renders a monthly dashboard directly from the val-scoped DB.\nexport default async function (req: Request) {\n const url = new URL(req.url);\n const monthParam = url.searchParams.get(\"month\");\n const now = new Date();\n // Keep defaults aligned with the dropdown so the first render has data.\n const startYear = 2026;\n const selectedMonth = resolveSelectedMonth(monthParam, now, startYear);\n const { start, end } = resolveMonthRange(selectedMonth, now);\n const includePartialWeeks = url.searchParams.get(\"partial\") === \"true\";\n const monthOptions = buildMonthOptions(startYear, now);\n\n // Pull all rollups for the requested month window, then split by category.\n const rollups = await fetchRollups(start, end, includePartialWeeks);\n const bloodSugar = aggregateBloodSugarMonth(rollups.filter((r) => r.category === \"blood_sugar\"), start, end, {\n includePartialWeeks,\n });\n const food = aggregateFoodMonth(rollups.filter((r) => r.category === \"food\"), start, end, {\n includePartialWeeks,\n });\n\n // Render a full HTML page as a string (server-side React).\n const html = renderToString(\n ,\n );\n\n return new Response(`${html}`, {\n headers: { \"Content-Type\": \"text/html; charset=utf-8\" },\n });\n}\n\n// Fetch weekly rollups for the month; optionally include overlapping weeks.\n// Query weekly rollups that overlap the selected month.\nasync function fetchRollups(start: string, end: string, includePartialWeeks: boolean): Promise {\n const where = includePartialWeeks\n ? \"period_start <= ? AND period_end >= ?\"\n : \"period_start >= ? AND period_end <= ?\";\n const args = includePartialWeeks ? [end, start] : [start, end];\n const result = await sqlite.execute({\n sql: `\n SELECT\n category,\n period_start,\n period_end,\n streak,\n completion_rate,\n xp,\n badges_json,\n stats_json,\n run_id\n FROM weekly_rollups_1\n WHERE ${where}\n ORDER BY period_start ASC\n `,\n args,\n });\n\n return result.rows.map((row) => rowToRollup(row as Record | unknown[]));\n}\n\n// Convert SQLite array or object rows into typed rollup objects.\n// (The SQLite client can return either shape depending on context.)\nfunction rowToRollup(row: Record | unknown[]): Rollup {\n const values = Array.isArray(row) ? row : [\n row.category,\n row.period_start,\n row.period_end,\n row.streak,\n row.completion_rate,\n row.xp,\n row.badges_json,\n row.stats_json,\n row.run_id,\n ];\n const [\n category,\n periodStart,\n periodEnd,\n streak,\n completionRate,\n xp,\n badgesJson,\n statsJson,\n runId,\n ] = values;\n return {\n category: String(category),\n periodStart: String(periodStart),\n periodEnd: String(periodEnd),\n streak: Number(streak ?? 0),\n completionRate: Number(completionRate ?? 0),\n xp: Number(xp ?? 0),\n badges: safeParseJsonArray(badgesJson),\n stats: safeParseJsonObject(statsJson),\n runId: String(runId),\n };\n}\n\nfunction safeParseJsonArray(value: unknown): string[] {\n const parsed = safeParseJson(value);\n return Array.isArray(parsed) ? parsed.map(String) : [];\n}\n\nfunction safeParseJsonObject(value: unknown): Record {\n const parsed = safeParseJson(value);\n return parsed && typeof parsed === \"object\" ? (parsed as Record) : {};\n}\n\n// Guard against invalid JSON in stored rollup columns.\nfunction safeParseJson(value: unknown) {\n if (typeof value !== \"string\") return null;\n try {\n return JSON.parse(value);\n } catch {\n return null;\n }\n}\n\n// Present the monthly report as a static HTML page.\nfunction ReportPage(props: {\n monthStart: string;\n monthEnd: string;\n includePartialWeeks: boolean;\n selectedMonth: string;\n monthOptions: string[];\n bloodSugar: ReturnType;\n food: ReturnType;\n}) {\n const { monthStart, monthEnd, includePartialWeeks, selectedMonth, monthOptions, bloodSugar, food } = props;\n const title = \"Praise Cage Monthly Rollup\";\n return (\n \n \n \n \n {title}\n \n \n \n {/* Decorative background layers */}\n

\n \n

{title}

\n Range: {monthStart} → {monthEnd} {includePartialWeeks ? \"(partial weeks included)\" : \"(full weeks only)\"}\n

\n {/* Month navigation is query-string driven for shareable URLs. */}\n \n

\n\n {/* Main content: two summary cards */}\n

Blood Sugar

\n \n \n \n \n \n \n \n

\n {(bloodSugar.badges.length ? bloodSugar.badges : [\"No badges yet\"]).map((badge) => (\n \n {badge}\n \n ))}\n

\n\n

Food Log

\n \n \n \n \n \n \n \n

\n Macro averages (per entry)\n {Object.keys(food.macroSummary).length === 0 &&

No macro data yet.

}\n {Object.entries(food.macroSummary).map(([key, value]) => (\n

\n {key}\n {value.avg}\n

\n ))}\n

\n\n

\n Praise Cage mode: keep logging, keep winning. Data from weekly rollups stored in Val Town SQLite.\n

\n \n \n \n );\n}\n\nfunction Stat(props: { label: string; value: string | number }) {\n return (\n

\n {props.label}\n {props.value}\n

\n );\n}\n\n// Build the month dropdown from the first data year through the current month.\nfunction buildMonthOptions(startYear: number, now: Date): string[] {\n const options: string[] = [];\n const start = new Date(Date.UTC(startYear, 0, 1));\n const end = new Date(Date.UTC(now.getUTCFullYear(), now.getUTCMonth(), 1));\n if (end < start) {\n return [formatMonth(start)];\n }\n for (let cursor = start; cursor <= end; cursor = addMonths(cursor, 1)) {\n options.push(formatMonth(cursor));\n }\n return options;\n}\n\n// Use the query string if valid, otherwise default to last month.\nfunction resolveSelectedMonth(monthParam: string | null, now: Date, startYear: number): string {\n const minMonth = `${startYear}-01`;\n if (monthParam && /^\\d{4}-\\d{2}$/.test(monthParam)) {\n return monthParam < minMonth ? minMonth : monthParam;\n }\n const year = now.getUTCFullYear();\n const month = now.getUTCMonth();\n const previous = new Date(Date.UTC(year, month - 1, 1));\n const fallback = formatMonth(previous);\n return fallback < minMonth ? minMonth : fallback;\n}\n\n// Format a Date as YYYY-MM for query params and dropdown values.\nfunction formatMonth(date: Date): string {\n const year = date.getUTCFullYear();\n const month = String(date.getUTCMonth() + 1).padStart(2, \"0\");\n return `${year}-${month}`;\n}\n\n// Date helper for iterating month-by-month.\nfunction addMonths(date: Date, amount: number): Date {\n return new Date(Date.UTC(date.getUTCFullYear(), date.getUTCMonth() + amount, 1));\n}\n",[],[1882,1889],{"_105":1899,"_97":1900,"_161":1901,"_163":1883,"_164":146,"_165":1902,"_167":168,"_107":1903,"_101":1904,"_170":1894,"_172":1905,"_173":22,"_174":-5,"_175":1906,"_100":1907},"2d1a4f62-f23b-11f0-a85a-42dde27851f2","weekly_rollup_persist.http.tsx","f84d1afa-f233-11f0-9eff-42dde27851f2",190,["D",1768499642189],1,"import { initRollupSchema, insertBadgeEvents, upsertWeeklyRollup, type BadgeEvent, type WeeklyRollup } from \"../storage/rollups.ts\";\n\ntype PersistPayload = {\n rollup: WeeklyRollup;\n badgeEvents?: BadgeEvent[];\n};\n\nexport default async function (req: Request) {\n if (req.method !== \"POST\") {\n return new Response(\"Method Not Allowed\", { status: 405 });\n }\n\n const authError = checkAuth(req);\n if (authError) {\n return new Response(authError, { status: 401 });\n }\n\n const data = (await req.json()) as unknown;\n if (!isPersistPayload(data)) {\n return new Response(\"Invalid payload.\", { status: 400 });\n }\n\n await initRollupSchema();\n await upsertWeeklyRollup(data.rollup);\n if (data.badgeEvents?.length) {\n await insertBadgeEvents(data.badgeEvents);\n }\n\n return new Response(\"Persisted.\", { status: 200 });\n}\n\nfunction checkAuth(req: Request): string | null {\n const token = Deno.env.get(\"ROLLUP_PERSIST_TOKEN\");\n if (!token) return null;\n const header = req.headers.get(\"Authorization\") ?? \"\";\n const match = header.match(/^Bearer\\s+(.+)$/i);\n if (!match || match[1] !== token) return \"Unauthorized.\";\n return null;\n}\n\nfunction isPersistPayload(value: unknown): value is PersistPayload {\n if (!value || typeof value !== \"object\") return false;\n const record = value as Record;\n if (!isWeeklyRollup(record.rollup)) return false;\n if (record.badgeEvents === undefined) return true;\n return Array.isArray(record.badgeEvents) && record.badgeEvents.every(isBadgeEvent);\n}\n\nfunction isWeeklyRollup(value: unknown): value is WeeklyRollup {\n if (!value || typeof value !== \"object\") return false;\n const record = value as Record;\n return (\n typeof record.category === \"string\" &&\n typeof record.periodStart === \"string\" &&\n typeof record.periodEnd === \"string\" &&\n typeof record.streak === \"number\" &&\n typeof record.completionRate === \"number\" &&\n typeof record.xp === \"number\" &&\n Array.isArray(record.badges) &&\n typeof record.stats === \"object\" &&\n record.stats !== null &&\n typeof record.runId === \"string\"\n );\n}\n\nfunction isBadgeEvent(value: unknown): value is BadgeEvent {\n if (!value || typeof value !== \"object\") return false;\n const record = value as Record;\n return (\n typeof record.category === \"string\" &&\n typeof record.badge === \"string\" &&\n typeof record.periodStart === \"string\" &&\n typeof record.periodEnd === \"string\" &&\n typeof record.awardedAt === \"string\"\n );\n}\n",[],[1882,1900],[1882],{"_105":1910,"_97":1911,"_161":1912,"_163":-5,"_164":146,"_165":1913,"_167":168,"_107":1914,"_101":33,"_170":171,"_172":-5,"_173":22,"_174":-5,"_175":1915,"_100":1974},"25688aae-f23b-11f0-a33f-42dde27851f2","shared","25688b9e-f23b-11f0-a33f-42dde27851f2",96,["D",1768499629303],[1916,1927,1936,1945,1955,1964],{"_105":1917,"_97":1918,"_161":1919,"_163":1912,"_164":146,"_165":1920,"_167":168,"_107":1921,"_101":1922,"_170":1923,"_172":1924,"_173":22,"_174":-5,"_175":1925,"_100":1926},"8f10723e-f7ac-11f0-98e3-42dde27851f2","blood_sugar_logic.ts","e6a27e5e-f309-11f0-8d21-42dde27851f2",418,["D",1769098095502],12,"script","import { calculateCurrentStreak, countEntriesByDate, listDateRange } from \"./date.ts\";\nimport { type NotionCreatedTimeProperty, type NotionNumberProperty, type NotionTextProperty } from \"./notion.ts\";\n\nconst REPORT_TIMEZONE = \"America/New_York\";\n\n// Scoring constants for XP and bonuses.\nconst XP_PER_ENTRY = 12;\nconst STREAK_BONUS_MULTIPLIER = 1.2;\nconst HEALTHY_AVG_BONUS_MULTIPLIER = 1.2;\nconst HEALTHY_AVG_THRESHOLD = 100;\n\n// Notion page shape and normalized entry types.\nexport type BloodSugarNotionPage = {\n id: string;\n properties: {\n \"Blood Sugar Level\"?: NotionNumberProperty;\n \"Created time\"?: NotionCreatedTimeProperty | NotionTextProperty;\n };\n};\n\nexport type Entry = {\n date: string;\n createdTime: string | null;\n value: number;\n};\n\nexport type BloodSugarRollup = {\n category: string;\n periodStart: string;\n periodEnd: string;\n streak: number;\n completionRate: number;\n xp: number;\n badges: string[];\n stats: {\n totalEntries: number;\n avg: number;\n min: number;\n max: number;\n entriesByDate: Record;\n expected: number;\n missing: number;\n };\n runId: string;\n};\n\nexport type GroupedEntries = {\n date: string;\n am: Entry[];\n pm: Entry[];\n};\n\n// Parse a Notion page into a normalized entry.\nexport function parseEntry(page: BloodSugarNotionPage): Entry | null {\n // Normalize a Notion page into the minimal shape used by the report.\n const props = page.properties ?? {};\n const value = props[\"Blood Sugar Level\"]?.number ?? null;\n const createdProp = props[\"Created time\"];\n const createdTimeRaw = isCreatedTimeProperty(createdProp)\n ? createdProp.created_time\n : isTextProperty(createdProp)\n ? createdProp.rich_text?.[0]?.plain_text ?? null\n : null;\n if (!createdTimeRaw || typeof value !== \"number\") return null;\n const date = extractDate(createdTimeRaw);\n if (!date) return null;\n const createdTime = formatCreatedTime(createdTimeRaw);\n return { date, createdTime, value };\n}\n\nfunction extractDate(value: string): string | null {\n const trimmed = value.trim();\n const textMatch = trimmed.match(\n /^(January|February|March|April|May|June|July|August|September|October|November|December)\\s+(\\d{1,2}),\\s*(\\d{4})\\s+(\\d{1,2}):(\\d{2})\\s*([AP]M)$/i,\n );\n if (textMatch) {\n const monthMap: Record = {\n january: 1,\n february: 2,\n march: 3,\n april: 4,\n may: 5,\n june: 6,\n july: 7,\n august: 8,\n september: 9,\n october: 10,\n november: 11,\n december: 12,\n };\n const month = monthMap[textMatch[1].toLowerCase()];\n const day = Number(textMatch[2]);\n const year = Number(textMatch[3]);\n if (!month || Number.isNaN(day) || Number.isNaN(year)) return null;\n return `${year}-${String(month).padStart(2, \"0\")}-${String(day).padStart(2, \"0\")}`;\n }\n\n const parsed = new Date(trimmed);\n if (Number.isNaN(parsed.getTime())) return null;\n return formatDateInTimeZone(parsed, REPORT_TIMEZONE);\n}\n\n// Normalize various Notion \"created time\" formats into readable time strings.\nexport function formatCreatedTime(value: string | null): string | null {\n if (!value) return null;\n const trimmed = value.trim();\n const timeMatch = trimmed.match(/(\\d{1,2}:\\d{2}\\s*[AP]M)/i);\n if (timeMatch) {\n return timeMatch[1].toUpperCase().replace(/\\s+/, \" \");\n }\n const parsed = new Date(trimmed);\n if (Number.isNaN(parsed.getTime())) return trimmed;\n return parsed.toLocaleTimeString(\"en-US\", {\n hour: \"numeric\",\n minute: \"2-digit\",\n hour12: true,\n timeZone: REPORT_TIMEZONE,\n });\n}\n\nfunction formatDateInTimeZone(date: Date, timeZone: string): string {\n const parts = new Intl.DateTimeFormat(\"en-US\", {\n timeZone,\n year: \"numeric\",\n month: \"2-digit\",\n day: \"2-digit\",\n }).formatToParts(date);\n const lookup = parts.reduce>((acc, part) => {\n acc[part.type] = part.value;\n return acc;\n }, {});\n return `${lookup.year}-${lookup.month}-${lookup.day}`;\n}\n\n// Perfect streak means 2+ readings per day for a full week.\nexport function hasPerfectWeekStreak(dateRange: string[], dateCounts: Record): boolean {\n return dateRange.length >= 7 && dateRange.every((date) => (dateCounts[date] ?? 0) >= 2);\n}\n\n// XP is weighted by streak and healthy average bonuses.\nexport function calculateXp(totalCount: number, avg: number, perfectWeekStreak: boolean): number {\n const baseXp = totalCount * XP_PER_ENTRY;\n if (baseXp === 0) return 0;\n const streakBonus = perfectWeekStreak ? STREAK_BONUS_MULTIPLIER : 1;\n const healthyAvgBonus = avg > 0 && avg < HEALTHY_AVG_THRESHOLD ? HEALTHY_AVG_BONUS_MULTIPLIER : 1;\n return Math.round(baseXp * streakBonus * healthyAvgBonus);\n}\n\n// Build the weekly rollup stored in SQLite.\nexport function buildBloodSugarRollup(entries: Entry[], start: string, end: string): BloodSugarRollup {\n const values = entries.map((entry) => entry.value);\n const count = values.length;\n const avg = count ? Math.round((values.reduce((a, b) => a + b, 0) / count) * 10) / 10 : 0;\n const min = count ? Math.min(...values) : 0;\n const max = count ? Math.max(...values) : 0;\n\n const dateCounts = countEntriesByDate(entries);\n const dateRange = listDateRange(start, end);\n const expected = dateRange.length * 2;\n const missing = Math.max(0, expected - count);\n const completionRate = expected ? Math.round((count / expected) * 100) : 0;\n const currentStreak = calculateCurrentStreak(dateRange, dateCounts);\n const perfectWeekStreak = hasPerfectWeekStreak(dateRange, dateCounts);\n const badges = buildBadges(dateRange, dateCounts, count, avg, perfectWeekStreak);\n const xp = calculateXp(count, avg, perfectWeekStreak);\n\n return {\n category: \"blood_sugar\",\n periodStart: start,\n periodEnd: end,\n streak: currentStreak,\n completionRate,\n xp,\n badges,\n stats: {\n totalEntries: count,\n avg,\n min,\n max,\n entriesByDate: dateCounts,\n expected,\n missing,\n },\n runId: `blood_sugar-${start}-${end}`,\n };\n}\n\n// Decide which badges to award for the week.\nexport function buildBadges(\n _dateRange: string[],\n _dateCounts: Record,\n totalCount: number,\n avg: number,\n perfectWeekStreak: boolean,\n): string[] {\n const badges: string[] = [];\n if (totalCount >= 7) badges.push(\"Mandy-Mode Consistency\");\n if (totalCount >= 14) badges.push(\"Cage Match: Full Week\");\n if (perfectWeekStreak) badges.push(\"Cage Match: Double-Check Champion\");\n if (avg > 0 && avg < HEALTHY_AVG_THRESHOLD) badges.push(\"National Treasure: Healthy Average\");\n return badges;\n}\n\n// Short motivational copy for emails.\nexport function buildEncouragement(completionRate: number, streak: number): string {\n if (completionRate >= 90) return \"Amazing work — you kept a near-perfect log this week.\";\n if (completionRate >= 70) return \"Great consistency — you’re building a strong habit.\";\n if (completionRate >= 40) return \"Nice progress — a few more check-ins will make this even stronger.\";\n if (streak >= 3) return \"You’re on a streak — keep it going!\";\n return \"Every entry helps — you’ve got this.\";\n}\n\n// Group entries into a per-day AM/PM structure for reports.\nexport function groupEntriesByDate(entries: Entry[], dateRange: string[]): GroupedEntries[] {\n // Bucket entries by date and AM/PM for consistent report formatting.\n const buckets: Record = {};\n for (const date of dateRange) {\n buckets[date] = { am: [], pm: [] };\n }\n for (const entry of entries) {\n if (!buckets[entry.date]) {\n buckets[entry.date] = { am: [], pm: [] };\n }\n const meridiem = getMeridiem(entry.createdTime);\n if (meridiem === \"AM\") {\n buckets[entry.date].am.push(entry);\n } else if (meridiem === \"PM\") {\n buckets[entry.date].pm.push(entry);\n } else {\n buckets[entry.date].pm.push(entry);\n }\n }\n return dateRange.map((date) => ({\n date,\n am: buckets[date]?.am ?? [],\n pm: buckets[date]?.pm ?? [],\n }));\n}\n\n// Format a single line of the daily summary table.\nexport function formatGroupedEntryLine(group: GroupedEntries): string {\n const [first, second] = formatFirstSecondText(group);\n return `${group.date} | 1st: ${first} | 2nd: ${second}`;\n}\n\n// Type guard for Notion created_time fields.\nexport function isCreatedTimeProperty(value: unknown): value is NotionCreatedTimeProperty {\n return (\n !!value &&\n typeof value === \"object\" &&\n \"created_time\" in value &&\n typeof (value as { created_time?: unknown }).created_time === \"string\"\n );\n}\n\n// Type guard for Notion rich_text fields.\nexport function isTextProperty(value: unknown): value is NotionTextProperty {\n return (\n !!value &&\n typeof value === \"object\" &&\n \"rich_text\" in value &&\n Array.isArray((value as { rich_text?: unknown }).rich_text)\n );\n}\n\n// Extract AM/PM from a time string if possible.\nfunction getMeridiem(value: string | null): \"AM\" | \"PM\" | null {\n if (!value) return null;\n const match = value.match(/\\b(AM|PM)\\b/i);\n if (!match) return null;\n return match[1].toUpperCase() as \"AM\" | \"PM\";\n}\n\n// Pick the first two readings (with an overflow indicator).\nfunction formatFirstSecondText(group: GroupedEntries): [string, string] {\n const ordered = orderEntries(group);\n if (!ordered.length) return [\"—\", \"—\"];\n const first = String(ordered[0].value);\n if (ordered.length === 1) return [first, \"—\"];\n const secondValue = String(ordered[1].value);\n const overflow = ordered.length > 2 ? ` (+${ordered.length - 2})` : \"\";\n return [first, `${secondValue}${overflow}`];\n}\n\n// Order entries by time when present (unknown times go last).\nfunction orderEntries(group: GroupedEntries): Entry[] {\n const combined = [...group.am, ...group.pm];\n return combined.sort((a, b) => {\n const aMinutes = parseTimeToMinutes(a.createdTime);\n const bMinutes = parseTimeToMinutes(b.createdTime);\n if (aMinutes === null && bMinutes === null) return 0;\n if (aMinutes === null) return 1;\n if (bMinutes === null) return -1;\n return aMinutes - bMinutes;\n });\n}\n\n// Convert \"h:mm AM/PM\" into minutes since midnight.\nfunction parseTimeToMinutes(value: string | null): number | null {\n if (!value) return null;\n const match = value.match(/(\\d{1,2}):(\\d{2})\\s*([AP]M)/i);\n if (!match) return null;\n let hours = Number(match[1]);\n const minutes = Number(match[2]);\n const meridiem = match[3].toUpperCase();\n if (meridiem === \"PM\" && hours < 12) hours += 12;\n if (meridiem === \"AM\" && hours === 12) hours = 0;\n return hours * 60 + minutes;\n}\n",[],[1911,1918],{"_105":1928,"_97":1929,"_161":1930,"_163":1912,"_164":146,"_165":1931,"_167":168,"_107":1932,"_101":1904,"_170":1923,"_172":1933,"_173":22,"_174":-5,"_175":1934,"_100":1935},"e4d88144-f328-11f0-8a43-42dde27851f2","date.ts","2de18fc8-f23b-11f0-8627-42dde27851f2",352,["D",1768601741204],"// Date helpers shared across rollup logic.\nexport function getWeeklyRange(): { start: string; end: string } {\n const today = new Date();\n const end = toDateOnly(today);\n const startDate = new Date(Date.UTC(today.getUTCFullYear(), today.getUTCMonth(), today.getUTCDate()));\n startDate.setUTCDate(startDate.getUTCDate() - 6);\n const start = toDateOnly(startDate);\n return { start, end };\n}\n\n// Convert a Date into YYYY-MM-DD (UTC).\nexport function toDateOnly(date: Date): string {\n return date.toISOString().slice(0, 10);\n}\n\n// Count days between two YYYY-MM-DD values, inclusive.\nexport function daysBetweenInclusive(start: string, end: string): number {\n const startDate = new Date(`${start}T00:00:00Z`);\n const endDate = new Date(`${end}T00:00:00Z`);\n const ms = endDate.getTime() - startDate.getTime();\n return Math.floor(ms / 86400000) + 1;\n}\n\n// List each day (YYYY-MM-DD) between two dates, inclusive.\nexport function listDateRange(start: string, end: string): string[] {\n const startDate = new Date(`${start}T00:00:00Z`);\n const endDate = new Date(`${end}T00:00:00Z`);\n const dates: string[] = [];\n const cursor = new Date(startDate.getTime());\n while (cursor <= endDate) {\n dates.push(toDateOnly(cursor));\n cursor.setUTCDate(cursor.getUTCDate() + 1);\n }\n return dates;\n}\n\n// Tally entries per date for quick rollup math.\nexport function countEntriesByDate(entries: T[]): Record {\n return entries.reduce>((acc, entry) => {\n acc[entry.date] = (acc[entry.date] ?? 0) + 1;\n return acc;\n }, {});\n}\n\n// Count consecutive days from the end of the range with at least one entry.\nexport function calculateCurrentStreak(dateRange: string[], dateCounts: Record): number {\n let streak = 0;\n for (let i = dateRange.length - 1; i >= 0; i -= 1) {\n const date = dateRange[i];\n if ((dateCounts[date] ?? 0) > 0) {\n streak += 1;\n } else {\n break;\n }\n }\n return streak;\n}\n",[],[1911,1929],{"_105":1937,"_97":1938,"_161":1939,"_163":1912,"_164":146,"_165":1940,"_167":168,"_107":1941,"_101":33,"_170":1923,"_172":1942,"_173":22,"_174":-5,"_175":1943,"_100":1944},"8ef3721a-f7ac-11f0-bbc1-42dde27851f2","fatsecret.ts","8ef372ba-f7ac-11f0-bbc1-42dde27851f2",413,["D",1769098095307],"import type { MacroKey } from \"./food_enrich.ts\";\nimport { roundNumber } from \"./food_enrich.ts\";\n\nexport type FatSecretConfig = {\n clientId: string;\n clientSecret: string;\n};\n\nconst TOKEN_URL = \"https://oauth.fatsecret.com/connect/token\";\nconst SEARCH_URL = \"https://platform.fatsecret.com/rest/foods/search/v1\";\nconst FOOD_GET_URL = \"https://platform.fatsecret.com/rest/food/v2\";\n\nexport function getFatSecretConfig(): FatSecretConfig | null {\n const clientId = Deno.env.get(\"FATSECRET_CLIENT_ID\");\n const clientSecret = Deno.env.get(\"FATSECRET_CLIENT_SECRET\");\n if (!clientId || !clientSecret) return null;\n return { clientId, clientSecret };\n}\n\nexport async function requestAccessToken(config: FatSecretConfig): Promise {\n const body = new URLSearchParams({ grant_type: \"client_credentials\" });\n const basic = btoa(`${config.clientId}:${config.clientSecret}`);\n const resp = await fetch(TOKEN_URL, {\n method: \"POST\",\n headers: {\n \"Authorization\": `Basic ${basic}`,\n \"Content-Type\": \"application/x-www-form-urlencoded\",\n },\n body,\n });\n\n if (!resp.ok) {\n throw new Error(`FatSecret token request failed: ${resp.status} ${resp.statusText}`);\n }\n\n const payload = await resp.json() as Record;\n const token = payload.access_token;\n if (typeof token !== \"string\") {\n throw new Error(`FatSecret token response missing access_token.`);\n }\n return token;\n}\n\nexport async function fetchFoodMacros(\n term: string,\n token: string,\n): Promise> | null> {\n const foodId = await fetchFoodId(term, token);\n if (foodId) {\n const detailed = await fetchFoodDetails(foodId, token);\n if (detailed && Object.keys(detailed).length) return detailed;\n }\n\n const params = new URLSearchParams({\n search_expression: term,\n max_results: \"1\",\n format: \"json\",\n });\n const resp = await fetch(`${SEARCH_URL}?${params.toString()}`, {\n method: \"GET\",\n headers: {\n \"Authorization\": `Bearer ${token}`,\n },\n });\n\n const text = await resp.text();\n if (!resp.ok) {\n throw new Error(`FatSecret search failed: ${resp.status} ${resp.statusText} ${text}`);\n }\n const payload = text ? JSON.parse(text) as Record : {};\n const foods = payload.foods as Record | undefined;\n const list = foods?.food;\n const first = Array.isArray(list) ? list[0] : list;\n if (!first || typeof first !== \"object\") return null;\n\n const food = first as Record;\n const nutrition = parseFoodDescription(food.food_description);\n if (!nutrition) return null;\n\n const macros: Partial> = {};\n if (nutrition.calories !== undefined) macros.calories = roundNumber(nutrition.calories);\n if (nutrition.protein !== undefined) macros.protein = roundNumber(nutrition.protein);\n if (nutrition.carbs !== undefined) macros.carbs = roundNumber(nutrition.carbs);\n if (nutrition.fat !== undefined) macros.fat = roundNumber(nutrition.fat);\n if (nutrition.fiber !== undefined) macros.fiber = roundNumber(nutrition.fiber);\n if (nutrition.sugar !== undefined) macros.sugar = roundNumber(nutrition.sugar);\n if (nutrition.sodium !== undefined) macros.sodium = roundNumber(nutrition.sodium);\n return Object.keys(macros).length ? macros : null;\n}\n\nexport function sumIfComplete(values: Array): number | undefined {\n if (!values.length) return undefined;\n if (values.some((value) => typeof value !== \"number\")) return undefined;\n const total = values.reduce((acc, value) => acc + (value ?? 0), 0);\n return roundNumber(total);\n}\n\nasync function fetchFoodId(term: string, token: string): Promise {\n const params = new URLSearchParams({\n search_expression: term,\n max_results: \"1\",\n format: \"json\",\n });\n const resp = await fetch(`${SEARCH_URL}?${params.toString()}`, {\n method: \"GET\",\n headers: {\n \"Authorization\": `Bearer ${token}`,\n },\n });\n\n const text = await resp.text();\n if (!resp.ok) {\n throw new Error(`FatSecret search failed: ${resp.status} ${resp.statusText} ${text}`);\n }\n const payload = text ? JSON.parse(text) as Record : {};\n const foods = payload.foods as Record | undefined;\n const list = foods?.food;\n const first = Array.isArray(list) ? list[0] : list;\n if (!first || typeof first !== \"object\") return null;\n const food = first as Record;\n return typeof food.food_id === \"string\" ? food.food_id : null;\n}\n\nasync function fetchFoodDetails(foodId: string, token: string): Promise> | null> {\n const params = new URLSearchParams({\n food_id: foodId,\n format: \"json\",\n });\n const resp = await fetch(`${FOOD_GET_URL}?${params.toString()}`, {\n method: \"GET\",\n headers: {\n \"Authorization\": `Bearer ${token}`,\n },\n });\n\n const text = await resp.text();\n if (!resp.ok) {\n throw new Error(`FatSecret food.get failed: ${resp.status} ${resp.statusText} ${text}`);\n }\n const payload = text ? JSON.parse(text) as Record : {};\n const food = payload.food as Record | undefined;\n if (!food) return null;\n const servings = (food.servings as Record | undefined)?.serving;\n const serving = Array.isArray(servings) ? servings[0] : servings;\n if (!serving || typeof serving !== \"object\") return null;\n\n const macros: Partial> = {};\n const record = serving as Record;\n const calories = toNumber(record.calories);\n const protein = toNumber(record.protein);\n const carbs = toNumber(record.carbohydrate);\n const fat = toNumber(record.fat);\n const fiber = toNumber(record.fiber);\n const sugar = toNumber(record.sugar);\n const sodium = toNumber(record.sodium);\n\n if (calories !== undefined) macros.calories = roundNumber(calories);\n if (protein !== undefined) macros.protein = roundNumber(protein);\n if (carbs !== undefined) macros.carbs = roundNumber(carbs);\n if (fat !== undefined) macros.fat = roundNumber(fat);\n if (fiber !== undefined) macros.fiber = roundNumber(fiber);\n if (sugar !== undefined) macros.sugar = roundNumber(sugar);\n if (sodium !== undefined) macros.sodium = roundNumber(sodium);\n\n return Object.keys(macros).length ? macros : null;\n}\n\nfunction parseFoodDescription(desc?: string): {\n calories?: number;\n fat?: number;\n carbs?: number;\n protein?: number;\n fiber?: number;\n sugar?: number;\n sodium?: number;\n} | null {\n if (!desc) return null;\n const caloriesMatch = desc.match(/Calories:\\s*([0-9.]+)kcal/i);\n const fatMatch = desc.match(/Fat:\\s*([0-9.]+)g/i);\n const carbsMatch = desc.match(/Carbs:\\s*([0-9.]+)g/i);\n const proteinMatch = desc.match(/Protein:\\s*([0-9.]+)g/i);\n const fiberMatch = desc.match(/(?:Dietary\\s+)?Fiber:\\s*([0-9.]+)g/i);\n const sugarMatch = desc.match(/Sugar[s]?:\\s*([0-9.]+)g/i);\n const sodiumMatch = desc.match(/Sodium:\\s*([0-9.]+)mg/i);\n\n return {\n calories: caloriesMatch ? Number(caloriesMatch[1]) : undefined,\n fat: fatMatch ? Number(fatMatch[1]) : undefined,\n carbs: carbsMatch ? Number(carbsMatch[1]) : undefined,\n protein: proteinMatch ? Number(proteinMatch[1]) : undefined,\n fiber: fiberMatch ? Number(fiberMatch[1]) : undefined,\n sugar: sugarMatch ? Number(sugarMatch[1]) : undefined,\n sodium: sodiumMatch ? Number(sodiumMatch[1]) : undefined,\n };\n}\n\nfunction toNumber(value: unknown): number | undefined {\n if (typeof value === \"number\" && Number.isFinite(value)) return value;\n if (typeof value === \"string\") {\n const parsed = Number(value.trim());\n if (Number.isFinite(parsed)) return parsed;\n }\n return undefined;\n}\n",[],[1911,1938],{"_105":1946,"_97":1947,"_161":1948,"_163":1912,"_164":146,"_165":1949,"_167":168,"_107":1950,"_101":1951,"_170":1923,"_172":1952,"_173":22,"_174":-5,"_175":1953,"_100":1954},"fe2fb036-f328-11f0-b456-42dde27851f2","food_enrich.ts","659ce588-f309-11f0-b22d-42dde27851f2",355,["D",1768601783718],6,"import {\n type NotionCreatedTimeProperty,\n type NotionDateProperty,\n type NotionNumberProperty,\n type NotionPage,\n type NotionTextProperty,\n type NotionTitleProperty,\n} from \"./notion.ts\";\nimport { calculateCurrentStreak, countEntriesByDate, listDateRange } from \"./date.ts\";\n\n// Macro keys and entry types for the food log.\nexport type MacroKey = \"calories\" | \"protein\" | \"carbs\" | \"fat\" | \"fiber\" | \"sugar\" | \"sodium\";\n\nexport type Entry = {\n pageId: string;\n date: string;\n loggedAt: string;\n food: string;\n macros: Partial>;\n};\n\nexport type MacroStats = {\n count: number;\n total: number;\n avg: number;\n};\n\nexport type FoodStats = {\n totalEntries: number;\n uniqueDays: number;\n entriesByDate: Record;\n avgEntriesPerDay: number;\n minEntriesPerDay: number;\n maxEntriesPerDay: number;\n macroSummary: Partial>;\n};\n\nexport type FoodRollup = {\n category: string;\n periodStart: string;\n periodEnd: string;\n streak: number;\n completionRate: number;\n xp: number;\n badges: string[];\n stats: FoodStats;\n runId: string;\n};\n\n// Mapping from Notion property names to macro fields.\nexport const PROPERTY_NAMES = {\n title: \"food\",\n loggedAt: \"Created time\",\n macros: {\n calories: \"calories\",\n protein: \"protein\",\n carbs: \"carbs\",\n fat: \"fats\",\n fiber: \"fiber\",\n sugar: \"sugar\",\n sodium: \"sodium\",\n },\n};\n\n// Parse a Notion page into a normalized food entry.\nexport function parseEntry(page: NotionPage): Entry | null {\n const props = page.properties ?? {};\n const loggedAtProp = props[PROPERTY_NAMES.loggedAt] as\n | NotionDateProperty\n | NotionCreatedTimeProperty\n | undefined;\n let loggedAt: string | null = null;\n if (loggedAtProp) {\n if (\"date\" in loggedAtProp) loggedAt = loggedAtProp.date?.start ?? null;\n if (\"created_time\" in loggedAtProp) loggedAt = loggedAtProp.created_time ?? null;\n }\n if (!loggedAt) return null;\n\n const foodProp = props[PROPERTY_NAMES.title] as NotionTitleProperty | NotionTextProperty | undefined;\n const food = extractFoodName(foodProp) ?? \"Unknown\";\n const macros = extractMacros(props);\n\n return {\n pageId: page.id,\n date: loggedAt.slice(0, 10),\n loggedAt,\n food,\n macros,\n };\n}\n\n// Normalize Notion title/rich_text into a single plain string.\nexport function extractFoodName(\n prop:\n | NotionTitleProperty\n | NotionTextProperty\n | undefined,\n): string | null {\n // Normalize Notion title/rich_text into a single plain string.\n if (!prop) return null;\n if (\"title\" in prop) {\n const value = prop.title?.map((item) => item.plain_text).join(\"\").trim();\n return value ? value : null;\n }\n if (\"rich_text\" in prop) {\n const value = prop.rich_text?.map((item) => item.plain_text).join(\"\").trim();\n return value ? value : null;\n }\n return null;\n}\n\n// Read macro number properties from a Notion page.\nexport function extractMacros(\n props: Record,\n): Partial> {\n const macros: Partial> = {};\n for (const key of Object.keys(PROPERTY_NAMES.macros) as MacroKey[]) {\n const propName = PROPERTY_NAMES.macros[key];\n const value = (props[propName] as NotionNumberProperty | undefined)?.number;\n if (typeof value === \"number\") macros[key] = value;\n }\n return macros;\n}\n\n// Only enrich entries missing core macros.\nexport function shouldEnrich(entry: Entry): boolean {\n return (\n entry.macros.calories === undefined ||\n entry.macros.protein === undefined ||\n entry.macros.carbs === undefined ||\n entry.macros.fat === undefined\n );\n}\n\n// Shape Notion property updates for numeric columns only.\nexport function buildNutritionProperties(macros: Partial>): Record {\n const props: Record = {};\n if (macros.calories !== undefined) props[PROPERTY_NAMES.macros.calories] = { number: macros.calories };\n if (macros.protein !== undefined) props[PROPERTY_NAMES.macros.protein] = { number: macros.protein };\n if (macros.carbs !== undefined) props[PROPERTY_NAMES.macros.carbs] = { number: macros.carbs };\n if (macros.fat !== undefined) props[PROPERTY_NAMES.macros.fat] = { number: macros.fat };\n if (macros.fiber !== undefined) props[PROPERTY_NAMES.macros.fiber] = { number: macros.fiber };\n if (macros.sugar !== undefined) props[PROPERTY_NAMES.macros.sugar] = { number: macros.sugar };\n if (macros.sodium !== undefined) props[PROPERTY_NAMES.macros.sodium] = { number: macros.sodium };\n return props;\n}\n\n// Build the weekly food rollup stored in SQLite.\nexport function buildFoodRollup(entries: Entry[], start: string, end: string): FoodRollup {\n const dateRange = listDateRange(start, end);\n const entriesByDate = countEntriesByDate(entries);\n const uniqueDays = dateRange.filter((date) => (entriesByDate[date] ?? 0) > 0).length;\n const totalEntries = entries.length;\n const avgEntriesPerDay = dateRange.length ? Number((totalEntries / dateRange.length).toFixed(2)) : 0;\n const minEntriesPerDay = dateRange.length\n ? Math.min(...dateRange.map((date) => entriesByDate[date] ?? 0))\n : 0;\n const maxEntriesPerDay = dateRange.length\n ? Math.max(...dateRange.map((date) => entriesByDate[date] ?? 0))\n : 0;\n const completionRate = dateRange.length ? Math.round((uniqueDays / dateRange.length) * 100) : 0;\n const streak = calculateCurrentStreak(dateRange, entriesByDate);\n const macroSummary = calculateMacroSummary(entries);\n\n const runId = `food-${start}-${end}`;\n\n return {\n category: \"food\",\n periodStart: start,\n periodEnd: end,\n streak,\n completionRate,\n xp: 0,\n badges: [],\n stats: {\n totalEntries,\n uniqueDays,\n entriesByDate,\n avgEntriesPerDay,\n minEntriesPerDay,\n maxEntriesPerDay,\n macroSummary,\n },\n runId,\n };\n}\n\n// Consistent rounding helper for macro math.\nexport function roundNumber(value: number): number {\n return Number(value.toFixed(2));\n}\n\n// Simple prompt for the macro estimation model.\nexport function buildNutritionPrompt(food: string): string {\n return `Estimate macros for: \"${food}\". Assume a typical single serving.`;\n}\n\n// Guard against non-JSON responses from the model.\nexport function safeParseJson(value: string): unknown {\n try {\n return JSON.parse(value);\n } catch {\n return null;\n }\n}\n\n// Aggregate macro stats across entries.\nfunction calculateMacroSummary(entries: Entry[]): Partial> {\n const summary: Partial> = {};\n for (const entry of entries) {\n for (const key of Object.keys(entry.macros) as MacroKey[]) {\n const value = entry.macros[key];\n if (typeof value !== \"number\") continue;\n const current = summary[key] ?? { count: 0, total: 0, avg: 0 };\n current.count += 1;\n current.total += value;\n current.avg = Number((current.total / current.count).toFixed(2));\n summary[key] = current;\n }\n }\n return summary;\n}\n\n// Coerce model output into numeric macro fields.\nexport function coerceMacros(value: Record): Partial> {\n const macros: Partial> = {};\n macros.calories = coerceNumber(value.calories);\n macros.protein = coerceNumber(value.protein);\n macros.carbs = coerceNumber(value.carbs);\n macros.fat = coerceNumber(value.fat);\n macros.fiber = coerceNumber(value.fiber);\n macros.sugar = coerceNumber(value.sugar);\n macros.sodium = coerceNumber(value.sodium);\n return Object.fromEntries(\n Object.entries(macros).filter(([, v]) => typeof v === \"number\" && Number.isFinite(v)),\n ) as Partial>;\n}\n\n// Convert a string or number into a rounded macro value.\nexport function coerceNumber(value: unknown): number | undefined {\n if (typeof value === \"number\" && Number.isFinite(value)) return roundNumber(value);\n if (typeof value === \"string\") {\n const trimmed = value.trim();\n const parsed = Number(trimmed);\n if (Number.isFinite(parsed)) return roundNumber(parsed);\n }\n return undefined;\n}\n",[],[1911,1947],{"_105":1956,"_97":1957,"_161":1958,"_163":1912,"_164":146,"_165":1959,"_167":168,"_107":1960,"_101":1904,"_170":1923,"_172":1961,"_173":22,"_174":-5,"_175":1962,"_100":1963},"0459b77c-f329-11f0-9209-42dde27851f2","monthly_report.ts","045b9332-f31d-11f0-9776-42dde27851f2",356,["D",1768601794059],"import { calculateCurrentStreak, listDateRange } from \"./date.ts\";\n\n// Types shared by the monthly rollup page.\nexport type Rollup = {\n category: string;\n periodStart: string;\n periodEnd: string;\n streak: number;\n completionRate: number;\n xp: number;\n badges: string[];\n stats: Record;\n runId: string;\n};\n\nexport type MonthlySummary = {\n monthStart: string;\n monthEnd: string;\n rollupsIncluded: number;\n};\n\nexport type BloodSugarMonthlySummary = MonthlySummary & {\n totalEntries: number;\n average: number;\n min: number;\n max: number;\n completionRate: number;\n streak: number;\n xp: number;\n badges: string[];\n entriesByDate: Record;\n};\n\nexport type FoodMacroStats = {\n count: number;\n total: number;\n avg: number;\n};\n\nexport type FoodMonthlySummary = MonthlySummary & {\n totalEntries: number;\n uniqueDays: number;\n avgEntriesPerDay: number;\n minEntriesPerDay: number;\n maxEntriesPerDay: number;\n completionRate: number;\n streak: number;\n macroSummary: Record;\n entriesByDate: Record;\n};\n\ntype FoodStatsShape = {\n entriesByDate?: Record;\n macroSummary?: Record;\n totalEntries?: number;\n};\n\ntype BloodSugarStatsShape = {\n entriesByDate?: Record;\n avg?: number;\n min?: number;\n max?: number;\n totalEntries?: number;\n};\n\n// Aggregate blood sugar rollups into a single monthly summary.\nexport function aggregateBloodSugarMonth(\n rollups: Rollup[],\n monthStart: string,\n monthEnd: string,\n options: { includePartialWeeks?: boolean } = {},\n): BloodSugarMonthlySummary {\n // Default to full-week rollups to avoid double counting across overlaps.\n const dateRange = listDateRange(monthStart, monthEnd);\n const filtered = filterRollups(rollups, monthStart, monthEnd, options.includePartialWeeks ?? false);\n const entriesByDate = mergeEntriesByDate(filtered, monthStart, monthEnd);\n const totalEntries = sumValues(entriesByDate);\n\n // Use weighted average and min/max across weeks that are fully included.\n let weightedSum = 0;\n let weightedCount = 0;\n let min = Number.POSITIVE_INFINITY;\n let max = Number.NEGATIVE_INFINITY;\n let xp = 0;\n const badgeSet = new Set();\n\n for (const rollup of filtered) {\n const stats = (rollup.stats ?? {}) as BloodSugarStatsShape;\n const count = stats.totalEntries ?? 0;\n if (typeof stats.avg === \"number\" && count > 0) {\n weightedSum += stats.avg * count;\n weightedCount += count;\n }\n if (typeof stats.min === \"number\") min = Math.min(min, stats.min);\n if (typeof stats.max === \"number\") max = Math.max(max, stats.max);\n xp += rollup.xp;\n for (const badge of rollup.badges ?? []) badgeSet.add(badge);\n }\n\n const average = weightedCount ? Number((weightedSum / weightedCount).toFixed(1)) : 0;\n const resolvedMin = Number.isFinite(min) ? min : 0;\n const resolvedMax = Number.isFinite(max) ? max : 0;\n const expected = dateRange.length * 2;\n const completionRate = expected ? Math.round((totalEntries / expected) * 100) : 0;\n const streak = calculateCurrentStreak(dateRange, entriesByDate);\n\n return {\n monthStart,\n monthEnd,\n rollupsIncluded: filtered.length,\n totalEntries,\n average,\n min: resolvedMin,\n max: resolvedMax,\n completionRate,\n streak,\n xp,\n badges: Array.from(badgeSet),\n entriesByDate,\n };\n}\n\n// Aggregate food rollups into a single monthly summary.\nexport function aggregateFoodMonth(\n rollups: Rollup[],\n monthStart: string,\n monthEnd: string,\n options: { includePartialWeeks?: boolean } = {},\n): FoodMonthlySummary {\n const dateRange = listDateRange(monthStart, monthEnd);\n const filtered = filterRollups(rollups, monthStart, monthEnd, options.includePartialWeeks ?? false);\n const entriesByDate = mergeEntriesByDate(filtered, monthStart, monthEnd);\n const totalEntries = sumValues(entriesByDate);\n const uniqueDays = Object.values(entriesByDate).filter((count) => count > 0).length;\n const avgEntriesPerDay = dateRange.length ? Number((totalEntries / dateRange.length).toFixed(2)) : 0;\n const minEntriesPerDay = dateRange.length\n ? Math.min(...dateRange.map((date) => entriesByDate[date] ?? 0))\n : 0;\n const maxEntriesPerDay = dateRange.length\n ? Math.max(...dateRange.map((date) => entriesByDate[date] ?? 0))\n : 0;\n const completionRate = dateRange.length ? Math.round((uniqueDays / dateRange.length) * 100) : 0;\n const streak = calculateCurrentStreak(dateRange, entriesByDate);\n const macroSummary = aggregateMacroSummary(filtered);\n\n return {\n monthStart,\n monthEnd,\n rollupsIncluded: filtered.length,\n totalEntries,\n uniqueDays,\n avgEntriesPerDay,\n minEntriesPerDay,\n maxEntriesPerDay,\n completionRate,\n streak,\n macroSummary,\n entriesByDate,\n };\n}\n\n// Resolve the month range from a YYYY-MM string (or default to last month).\nexport function resolveMonthRange(monthParam?: string | null, now = new Date()) {\n if (monthParam) {\n const match = monthParam.match(/^(\\d{4})-(\\d{2})$/);\n if (match) {\n const year = Number(match[1]);\n const month = Number(match[2]) - 1;\n const start = new Date(Date.UTC(year, month, 1));\n const end = new Date(Date.UTC(year, month + 1, 0));\n return { start: formatDate(start), end: formatDate(end) };\n }\n }\n const year = now.getUTCFullYear();\n const month = now.getUTCMonth();\n const start = new Date(Date.UTC(year, month - 1, 1));\n const end = new Date(Date.UTC(year, month, 0));\n return { start: formatDate(start), end: formatDate(end) };\n}\n\n// Filter rollups to the desired month window.\nfunction filterRollups(\n rollups: Rollup[],\n monthStart: string,\n monthEnd: string,\n includePartialWeeks: boolean,\n) {\n return rollups.filter((rollup) => {\n if (includePartialWeeks) {\n return rollup.periodStart <= monthEnd && rollup.periodEnd >= monthStart;\n }\n return rollup.periodStart >= monthStart && rollup.periodEnd <= monthEnd;\n });\n}\n\n// Merge per-day counts across rollups (handling overlap safely).\nfunction mergeEntriesByDate(rollups: Rollup[], monthStart: string, monthEnd: string) {\n const entriesByDate: Record = {};\n for (const rollup of rollups) {\n const stats = rollup.stats as FoodStatsShape | BloodSugarStatsShape;\n const entries = stats.entriesByDate ?? {};\n for (const [date, count] of Object.entries(entries)) {\n if (date < monthStart || date > monthEnd) continue;\n const current = entriesByDate[date];\n // When rollups overlap, prefer the larger count for a given day.\n entriesByDate[date] = current === undefined ? count : Math.max(current, count);\n }\n }\n return entriesByDate;\n}\n\n// Roll up macro stats across all matching rollups.\nfunction aggregateMacroSummary(rollups: Rollup[]) {\n const summary: Record = {};\n for (const rollup of rollups) {\n const stats = rollup.stats as FoodStatsShape;\n const macroSummary = stats.macroSummary ?? {};\n for (const [key, value] of Object.entries(macroSummary)) {\n const existing = summary[key] ?? { count: 0, total: 0, avg: 0 };\n existing.count += value.count ?? 0;\n existing.total += value.total ?? 0;\n existing.avg = existing.count ? Number((existing.total / existing.count).toFixed(2)) : 0;\n summary[key] = existing;\n }\n }\n return summary;\n}\n\n// Sum values of a date->count map.\nfunction sumValues(record: Record) {\n return Object.values(record).reduce((sum, value) => sum + value, 0);\n}\n\n// Format a Date as YYYY-MM-DD (UTC).\nfunction formatDate(value: Date) {\n return value.toISOString().slice(0, 10);\n}\n",[],[1911,1957],{"_105":1965,"_97":1966,"_161":1967,"_163":1912,"_164":146,"_165":1968,"_167":168,"_107":1969,"_101":1970,"_170":1923,"_172":1971,"_173":22,"_174":-5,"_175":1972,"_100":1973},"e86bd2c0-f328-11f0-b05e-42dde27851f2","notion.ts","2dc9ba38-f23b-11f0-b902-42dde27851f2",353,["D",1768601747203],2,"export const NOTION_VERSION = \"2022-06-28\";\n\n// Minimal Notion types used by the collectors.\nexport type NotionRichText = { plain_text: string };\nexport type NotionDateProperty = { date: { start: string } | null };\nexport type NotionNumberProperty = { number: number | null };\nexport type NotionTextProperty = { rich_text: NotionRichText[] };\nexport type NotionCreatedTimeProperty = { created_time: string };\nexport type NotionTitleProperty = { title: NotionRichText[] };\n\nexport type NotionPage = {\n id: string;\n properties: Record;\n};\n\nexport type NotionQueryResponse = {\n results: NotionPage[];\n has_more: boolean;\n next_cursor: string | null;\n};\n\n// Fetch all pages from a Notion database (handles pagination).\nexport async function fetchNotionPages(\n databaseId: string,\n token: string,\n buildBody: (cursor?: string) => Record,\n): Promise {\n const url = `https://api.notion.com/v1/databases/${databaseId}/query`;\n const headers = {\n Authorization: `Bearer ${token}`,\n \"Notion-Version\": NOTION_VERSION,\n \"Content-Type\": \"application/json\",\n };\n\n const pages: T[] = [];\n let cursor: string | null | undefined;\n\n do {\n const body = buildBody(cursor ?? undefined);\n const response = await fetch(url, {\n method: \"POST\",\n headers,\n body: JSON.stringify(body),\n });\n\n if (!response.ok) {\n const text = await response.text();\n throw new Error(`Notion query failed: ${response.status} ${text}`);\n }\n\n const data = (await response.json()) as unknown;\n if (!isNotionQueryResponse(data)) {\n throw new Error(\"Notion query returned unexpected shape.\");\n }\n\n pages.push(...(data.results as T[]));\n cursor = data.has_more && data.next_cursor ? data.next_cursor : undefined;\n } while (cursor);\n\n return pages;\n}\n\n// Update a Notion page's properties.\nexport async function updateNotionPage(\n pageId: string,\n token: string,\n properties: Record,\n): Promise {\n const url = `https://api.notion.com/v1/pages/${pageId}`;\n const headers = {\n Authorization: `Bearer ${token}`,\n \"Notion-Version\": NOTION_VERSION,\n \"Content-Type\": \"application/json\",\n };\n\n const response = await fetch(url, {\n method: \"PATCH\",\n headers,\n body: JSON.stringify({ properties }),\n });\n\n if (!response.ok) {\n const text = await response.text();\n throw new Error(`Notion update failed: ${response.status} ${text}`);\n }\n}\n\n// Runtime guard for Notion query responses.\nfunction isNotionQueryResponse(value: unknown): value is NotionQueryResponse {\n if (!value || typeof value !== \"object\") return false;\n const record = value as Record;\n return (\n Array.isArray(record.results) &&\n typeof record.has_more === \"boolean\" &&\n (typeof record.next_cursor === \"string\" || record.next_cursor === null)\n );\n}\n",[],[1911,1966],[1911],{"_105":1976,"_97":1977,"_161":1978,"_163":-5,"_164":146,"_165":1979,"_167":168,"_107":1980,"_101":33,"_170":171,"_172":-5,"_173":22,"_174":-5,"_175":1981,"_100":2001},"082c3930-f0ca-11f0-9dc7-42dde27851f2","storage","082c3a0c-f0ca-11f0-9dc7-42dde27851f2",27,["D",1768341095957],[1982,1992],{"_105":1983,"_97":1984,"_161":1985,"_163":1978,"_164":146,"_165":1986,"_167":168,"_107":1987,"_101":1988,"_170":1923,"_172":1989,"_173":22,"_174":-5,"_175":1990,"_100":1991},"65d5f0f2-fadf-11f0-8ad9-42dde27851f2","rollups.ts","08468100-f0ca-11f0-80e1-42dde27851f2",425,["D",1769449784146],4,"import { sqlite } from \"./sqlite.ts\";\n\n// Provides typed helpers for the val-scoped SQLite tables that back weekly rollups and badge history.\n\nconst WEEKLY_ROLLUPS_TABLE = \"weekly_rollups_1\";\nconst BADGE_EVENTS_TABLE = \"badge_events_1\";\n\nexport type WeeklyRollup = {\n category: string;\n periodStart: string; // YYYY-MM-DD\n periodEnd: string; // YYYY-MM-DD\n streak: number;\n completionRate: number;\n xp: number;\n badges: string[];\n stats: Record;\n runId: string;\n};\n\nexport type BadgeEvent = {\n category: string;\n badge: string;\n periodStart: string; // YYYY-MM-DD\n periodEnd: string; // YYYY-MM-DD\n awardedAt: string; // ISO timestamp\n reason?: string;\n};\n\nexport async function initRollupSchema() {\n await sqlite.execute(`CREATE TABLE IF NOT EXISTS ${WEEKLY_ROLLUPS_TABLE} (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n category TEXT NOT NULL,\n period_start TEXT NOT NULL,\n period_end TEXT NOT NULL,\n streak INTEGER NOT NULL,\n completion_rate REAL NOT NULL,\n xp INTEGER NOT NULL,\n badges_json TEXT NOT NULL,\n stats_json TEXT NOT NULL,\n run_id TEXT NOT NULL,\n created_at TEXT NOT NULL,\n UNIQUE(category, period_start),\n UNIQUE(run_id)\n )`);\n\n await sqlite.execute(`CREATE TABLE IF NOT EXISTS ${BADGE_EVENTS_TABLE} (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n category TEXT NOT NULL,\n badge TEXT NOT NULL,\n period_start TEXT NOT NULL,\n period_end TEXT NOT NULL,\n awarded_at TEXT NOT NULL,\n reason TEXT\n )`);\n}\n\nexport async function upsertWeeklyRollup(rollup: WeeklyRollup) {\n const createdAt = new Date().toISOString();\n await sqlite.execute(\n buildUpsertWeeklyRollupQuery(rollup, createdAt),\n );\n}\n\nexport function buildUpsertWeeklyRollupQuery(rollup: WeeklyRollup, createdAt: string) {\n return {\n sql: `INSERT OR REPLACE INTO ${WEEKLY_ROLLUPS_TABLE} (\n category,\n period_start,\n period_end,\n streak,\n completion_rate,\n xp,\n badges_json,\n stats_json,\n run_id,\n created_at\n ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)`,\n args: [\n rollup.category,\n rollup.periodStart,\n rollup.periodEnd,\n rollup.streak,\n rollup.completionRate,\n rollup.xp,\n JSON.stringify(rollup.badges),\n JSON.stringify(rollup.stats),\n rollup.runId,\n createdAt,\n ],\n };\n}\n\nexport async function insertBadgeEvents(events: BadgeEvent[]) {\n for (const event of events) {\n await sqlite.execute(\n `INSERT INTO ${BADGE_EVENTS_TABLE} (\n category,\n badge,\n period_start,\n period_end,\n awarded_at,\n reason\n ) VALUES (?, ?, ?, ?, ?, ?)`,\n [\n event.category,\n event.badge,\n event.periodStart,\n event.periodEnd,\n event.awardedAt,\n event.reason ?? null,\n ],\n );\n }\n}\n\nexport async function getWeeklyRollups(category: string, start: string, end: string) {\n const result = await sqlite.execute(\n `SELECT * FROM ${WEEKLY_ROLLUPS_TABLE}\n WHERE category = ?\n AND period_start >= ?\n AND period_end <= ?\n ORDER BY period_start ASC`,\n [category, start, end],\n );\n return result.rows;\n}\n",[],[1977,1984],{"_105":1993,"_97":1994,"_161":1995,"_163":1978,"_164":146,"_165":1996,"_167":168,"_107":1997,"_101":33,"_170":1923,"_172":1998,"_173":22,"_174":-5,"_175":1999,"_100":2000},"65c8e5b0-fadf-11f0-98dc-42dde27851f2","sqlite.ts","65c8e678-fadf-11f0-98dc-42dde27851f2",423,["D",1769449784071],"import sqlite from \"https://esm.town/v/std/sqlite/main.ts\";\n\n// Central import to keep DB client switches (std vs legacy) in one place.\nexport { sqlite };\n",[],[1977,1994],[1977],{"_105":2003,"_97":2004,"_161":2005,"_163":-5,"_164":146,"_165":2006,"_167":168,"_107":2007,"_101":33,"_170":171,"_172":-5,"_173":22,"_174":-5,"_175":2008,"_100":2047},"0817ce82-f309-11f0-9638-42dde27851f2","tests","0817cf4a-f309-11f0-9638-42dde27851f2",272,["D",1768588056443],[2009,2019,2028,2038],{"_105":2010,"_97":2011,"_161":2012,"_163":2005,"_164":146,"_165":2013,"_167":168,"_107":2014,"_101":2015,"_170":1923,"_172":2016,"_173":22,"_174":-5,"_175":2017,"_100":2018},"dc4d3266-f311-11f0-b56a-42dde27851f2","food_report.test.ts","e01ea7f2-f308-11f0-8ecb-42dde27851f2",328,["D",1768591848438],7,"import {\n buildNutritionProperties,\n buildNutritionPrompt,\n coerceMacros,\n coerceNumber,\n extractFoodName,\n extractMacros,\n parseEntry,\n PROPERTY_NAMES,\n roundNumber,\n safeParseJson,\n shouldEnrich,\n type Entry,\n buildFoodRollup,\n} from \"../shared/food_enrich.ts\";\nimport { assert, assertEquals, assertStringIncludes } from \"https://deno.land/std@0.224.0/assert/mod.ts\";\n\nDeno.test(\"extractFoodName handles title and rich text\", () => {\n const titleName = extractFoodName({\n title: [{ plain_text: \"cheese omelette\" }],\n });\n assertEquals(titleName, \"cheese omelette\");\n\n const richTextName = extractFoodName({\n rich_text: [{ plain_text: \" tofu bowl \" }],\n });\n assertEquals(richTextName, \"tofu bowl\");\n\n const missingName = extractFoodName(undefined);\n assertEquals(missingName, null);\n});\n\nDeno.test(\"parseEntry uses Created time and extracts food/macros\", () => {\n const page = {\n id: \"page-1\",\n properties: {\n [PROPERTY_NAMES.loggedAt]: { created_time: \"2026-01-16T14:12:00.000Z\" },\n [PROPERTY_NAMES.title]: { title: [{ plain_text: \"cheese omelette\" }] },\n [PROPERTY_NAMES.macros.calories]: { number: 320 },\n [PROPERTY_NAMES.macros.protein]: { number: 18 },\n [PROPERTY_NAMES.macros.carbs]: { number: null },\n },\n };\n const entry = parseEntry(page);\n assert(entry);\n assertEquals(entry.pageId, \"page-1\");\n assertEquals(entry.date, \"2026-01-16\");\n assertEquals(entry.food, \"cheese omelette\");\n assertEquals(entry.macros, { calories: 320, protein: 18 });\n});\n\nDeno.test(\"parseEntry ignores pages without a timestamp\", () => {\n const page = {\n id: \"page-2\",\n properties: {\n [PROPERTY_NAMES.title]: { title: [{ plain_text: \"missing time\" }] },\n },\n };\n const entry = parseEntry(page);\n assertEquals(entry, null);\n});\n\nDeno.test(\"extractMacros only returns numeric values\", () => {\n const macros = extractMacros({\n [PROPERTY_NAMES.macros.calories]: { number: 300 },\n [PROPERTY_NAMES.macros.protein]: { number: null },\n [PROPERTY_NAMES.macros.carbs]: { number: 12 },\n [PROPERTY_NAMES.macros.fat]: { number: \"10\" },\n });\n assertEquals(macros, { calories: 300, carbs: 12 });\n});\n\nDeno.test(\"shouldEnrich returns true if any core macros are missing\", () => {\n const base: Entry = {\n pageId: \"page-3\",\n date: \"2026-01-16\",\n loggedAt: \"2026-01-16T10:00:00.000Z\",\n food: \"toast\",\n macros: { calories: 200, protein: 8, carbs: 20, fat: 4 },\n };\n assertEquals(shouldEnrich(base), false);\n assertEquals(shouldEnrich({ ...base, macros: { ...base.macros, fat: undefined } }), true);\n});\n\nDeno.test(\"buildNutritionProperties maps to Notion property names\", () => {\n const props = buildNutritionProperties({\n calories: 120,\n protein: 6,\n carbs: 10,\n fat: 4,\n fiber: 2,\n sugar: 1,\n sodium: 300,\n });\n assertEquals(props, {\n [PROPERTY_NAMES.macros.calories]: { number: 120 },\n [PROPERTY_NAMES.macros.protein]: { number: 6 },\n [PROPERTY_NAMES.macros.carbs]: { number: 10 },\n [PROPERTY_NAMES.macros.fat]: { number: 4 },\n [PROPERTY_NAMES.macros.fiber]: { number: 2 },\n [PROPERTY_NAMES.macros.sugar]: { number: 1 },\n [PROPERTY_NAMES.macros.sodium]: { number: 300 },\n });\n});\n\nDeno.test(\"buildNutritionPrompt includes the food text\", () => {\n const prompt = buildNutritionPrompt(\"cheese omelette\");\n assertStringIncludes(prompt, \"cheese omelette\");\n});\n\nDeno.test(\"safeParseJson returns null for invalid JSON\", () => {\n assertEquals(safeParseJson(\"{oops}\"), null);\n assertEquals(safeParseJson(\"\"), null);\n assertEquals(safeParseJson('{\"ok\":true}'), { ok: true });\n});\n\nDeno.test(\"coerceNumber handles strings and rounds\", () => {\n assertEquals(coerceNumber(2.345), 2.35);\n assertEquals(coerceNumber(\"12.1\"), 12.1);\n assertEquals(coerceNumber(\"bad\"), undefined);\n});\n\nDeno.test(\"coerceMacros filters invalid fields\", () => {\n const macros = coerceMacros({\n calories: \"100.4\",\n protein: 12,\n carbs: \"bad\",\n fat: null,\n fiber: 3.333,\n sugar: \"4.2\",\n sodium: \"350\",\n });\n assertEquals(macros, {\n calories: 100.4,\n protein: 12,\n fiber: 3.33,\n sugar: 4.2,\n sodium: 350,\n });\n});\n\nDeno.test(\"roundNumber rounds to two decimals\", () => {\n assertEquals(roundNumber(3.14159), 3.14);\n});\n\n// Rollup should aggregate entries and use deterministic runId.\nDeno.test(\"buildFoodRollup aggregates weekly stats\", () => {\n const entries: Entry[] = [\n {\n pageId: \"page-1\",\n date: \"2026-01-01\",\n loggedAt: \"2026-01-01T12:00:00.000Z\",\n food: \"toast\",\n macros: { calories: 100, protein: 4 },\n },\n {\n pageId: \"page-2\",\n date: \"2026-01-02\",\n loggedAt: \"2026-01-02T12:00:00.000Z\",\n food: \"eggs\",\n macros: { calories: 200, protein: 12 },\n },\n ];\n const rollup = buildFoodRollup(entries, \"2026-01-01\", \"2026-01-07\");\n assertEquals(rollup.category, \"food\");\n assertEquals(rollup.stats.totalEntries, 2);\n assertEquals(rollup.stats.uniqueDays, 2);\n assertEquals(rollup.stats.entriesByDate[\"2026-01-01\"], 1);\n assertEquals(rollup.stats.entriesByDate[\"2026-01-02\"], 1);\n assertEquals(rollup.runId, \"food-2026-01-01-2026-01-07\");\n});\n",[],[2004,2011],{"_105":2020,"_97":2021,"_161":2022,"_163":2005,"_164":146,"_165":2023,"_167":168,"_107":2024,"_101":33,"_170":1923,"_172":2025,"_173":22,"_174":-5,"_175":2026,"_100":2027},"0452ba82-f31d-11f0-9bc9-42dde27851f2","monthly_report.test.ts","0452bb22-f31d-11f0-9bc9-42dde27851f2",331,["D",1768596640052],"import {\n aggregateBloodSugarMonth,\n aggregateFoodMonth,\n resolveMonthRange,\n type Rollup,\n} from \"../shared/monthly_report.ts\";\nimport { assertEquals } from \"https://deno.land/std@0.224.0/assert/mod.ts\";\n\n// Overlapping rollups should not double-count entries by date.\nDeno.test(\"aggregateFoodMonth de-dupes overlapping entriesByDate\", () => {\n const rollups: Rollup[] = [\n {\n category: \"food\",\n periodStart: \"2026-01-01\",\n periodEnd: \"2026-01-07\",\n streak: 2,\n completionRate: 50,\n xp: 0,\n badges: [],\n stats: { entriesByDate: { \"2026-01-02\": 1 } },\n runId: \"food-2026-01-01-2026-01-07\",\n },\n {\n category: \"food\",\n periodStart: \"2026-01-05\",\n periodEnd: \"2026-01-11\",\n streak: 1,\n completionRate: 40,\n xp: 0,\n badges: [],\n stats: { entriesByDate: { \"2026-01-02\": 1, \"2026-01-06\": 2 } },\n runId: \"food-2026-01-05-2026-01-11\",\n },\n ];\n const summary = aggregateFoodMonth(rollups, \"2026-01-01\", \"2026-01-31\", {\n includePartialWeeks: true,\n });\n assertEquals(summary.entriesByDate[\"2026-01-02\"], 1);\n assertEquals(summary.entriesByDate[\"2026-01-06\"], 2);\n assertEquals(summary.totalEntries, 3);\n});\n\n// Monthly aggregation should compute weighted averages and totals.\nDeno.test(\"aggregateBloodSugarMonth computes weighted average and totals\", () => {\n const rollups: Rollup[] = [\n {\n category: \"blood_sugar\",\n periodStart: \"2026-01-01\",\n periodEnd: \"2026-01-07\",\n streak: 3,\n completionRate: 70,\n xp: 120,\n badges: [\"A\"],\n stats: {\n entriesByDate: { \"2026-01-01\": 2 },\n avg: 90,\n min: 80,\n max: 110,\n totalEntries: 2,\n },\n runId: \"blood_sugar-2026-01-01-2026-01-07\",\n },\n {\n category: \"blood_sugar\",\n periodStart: \"2026-01-08\",\n periodEnd: \"2026-01-14\",\n streak: 1,\n completionRate: 50,\n xp: 60,\n badges: [\"B\"],\n stats: {\n entriesByDate: { \"2026-01-08\": 2 },\n avg: 110,\n min: 85,\n max: 130,\n totalEntries: 2,\n },\n runId: \"blood_sugar-2026-01-08-2026-01-14\",\n },\n ];\n const summary = aggregateBloodSugarMonth(rollups, \"2026-01-01\", \"2026-01-31\");\n assertEquals(summary.totalEntries, 4);\n assertEquals(summary.average, 100);\n assertEquals(summary.min, 80);\n assertEquals(summary.max, 130);\n assertEquals(summary.xp, 180);\n});\n\nDeno.test(\"resolveMonthRange defaults to previous month\", () => {\n const now = new Date(\"2026-02-15T10:00:00.000Z\");\n const range = resolveMonthRange(null, now);\n assertEquals(range.start, \"2026-01-01\");\n assertEquals(range.end, \"2026-01-31\");\n});\n",[],[2004,2021],{"_105":2029,"_97":2030,"_161":2031,"_163":2005,"_164":146,"_165":2032,"_167":168,"_107":2033,"_101":2034,"_170":1923,"_172":2035,"_173":22,"_174":-5,"_175":2036,"_100":2037},"65de0ac6-fadf-11f0-9be4-42dde27851f2","notion_weekly_report.test.ts","46d7e2ba-f0ca-11f0-b918-42dde27851f2",426,["D",1769449784204],16,"import {\n buildBadges,\n buildEncouragement,\n buildBloodSugarRollup,\n calculateXp,\n formatCreatedTime,\n formatGroupedEntryLine,\n groupEntriesByDate,\n hasPerfectWeekStreak,\n type Entry,\n} from \"../shared/blood_sugar_logic.ts\";\nimport { calculateCurrentStreak, countEntriesByDate, listDateRange } from \"../shared/date.ts\";\nimport { assertEquals, assertStringIncludes } from \"https://deno.land/std@0.224.0/assert/mod.ts\";\n\nDeno.test(\"listDateRange returns inclusive dates\", () => {\n const dates = listDateRange(\"2026-01-01\", \"2026-01-03\");\n assertEquals(dates, [\"2026-01-01\", \"2026-01-02\", \"2026-01-03\"]);\n});\n\nDeno.test(\"calculateCurrentStreak counts trailing days with entries\", () => {\n const range = [\"2026-01-01\", \"2026-01-02\", \"2026-01-03\", \"2026-01-04\"];\n const counts = { \"2026-01-02\": 1, \"2026-01-03\": 2, \"2026-01-04\": 1 };\n const streak = calculateCurrentStreak(range, counts);\n assertEquals(streak, 3);\n});\n\nDeno.test(\"calculateCurrentStreak stops at first missing day\", () => {\n const range = [\"2026-01-01\", \"2026-01-02\", \"2026-01-03\"];\n const counts = { \"2026-01-01\": 1, \"2026-01-03\": 1 };\n const streak = calculateCurrentStreak(range, counts);\n assertEquals(streak, 1);\n});\n\nDeno.test(\"countEntriesByDate aggregates by date\", () => {\n const entries: Entry[] = [\n { date: \"2026-01-01\", createdTime: null, value: 90 },\n { date: \"2026-01-01\", createdTime: null, value: 95 },\n { date: \"2026-01-02\", createdTime: null, value: 100 },\n ];\n assertEquals(countEntriesByDate(entries), { \"2026-01-01\": 2, \"2026-01-02\": 1 });\n});\n\nDeno.test(\"buildBadges awards consistency and healthy average\", () => {\n const range = [\n \"2026-01-01\",\n \"2026-01-02\",\n \"2026-01-03\",\n \"2026-01-04\",\n \"2026-01-05\",\n \"2026-01-06\",\n \"2026-01-07\",\n ];\n const counts = {\n \"2026-01-01\": 2,\n \"2026-01-02\": 2,\n \"2026-01-03\": 2,\n \"2026-01-04\": 2,\n \"2026-01-05\": 2,\n \"2026-01-06\": 2,\n \"2026-01-07\": 2,\n };\n const badges = buildBadges(range, counts, 14, 95, true);\n assertEquals(badges.includes(\"Cage Match: Double-Check Champion\"), true);\n assertEquals(badges.includes(\"National Treasure: Healthy Average\"), true);\n});\n\nDeno.test(\"buildEncouragement returns positive message\", () => {\n const message = buildEncouragement(85, 2);\n assertStringIncludes(message, \"Great\");\n});\n\nDeno.test(\"hasPerfectWeekStreak requires two entries per day\", () => {\n const range = [\n \"2026-01-01\",\n \"2026-01-02\",\n \"2026-01-03\",\n \"2026-01-04\",\n \"2026-01-05\",\n \"2026-01-06\",\n \"2026-01-07\",\n ];\n const counts = {\n \"2026-01-01\": 2,\n \"2026-01-02\": 2,\n \"2026-01-03\": 2,\n \"2026-01-04\": 2,\n \"2026-01-05\": 2,\n \"2026-01-06\": 2,\n \"2026-01-07\": 1,\n };\n assertEquals(hasPerfectWeekStreak(range, counts), false);\n});\n\nDeno.test(\"calculateXp applies streak and healthy average bonuses\", () => {\n const xp = calculateXp(14, 95, true);\n assertEquals(xp, 242);\n});\n\n// Boundary check: average at threshold should not get the healthy bonus.\nDeno.test(\"calculateXp does not apply healthy bonus at threshold\", () => {\n const xp = calculateXp(10, 100, true);\n assertEquals(xp, 144);\n});\n\n// Ensure minimum thresholds gate badges.\nDeno.test(\"buildBadges respects minimum thresholds\", () => {\n const range = [\"2026-01-01\", \"2026-01-02\", \"2026-01-03\", \"2026-01-04\", \"2026-01-05\", \"2026-01-06\", \"2026-01-07\"];\n const counts = Object.fromEntries(range.map((date) => [date, 2]));\n const badges = buildBadges(range, counts, 6, 110, false);\n assertEquals(badges.includes(\"Mandy-Mode Consistency\"), false);\n assertEquals(badges.includes(\"Cage Match: Double-Check Champion\"), false);\n});\n\n// Perfect week requires 2+ entries every day in a 7-day window.\nDeno.test(\"hasPerfectWeekStreak returns true for full week\", () => {\n const range = [\"2026-01-01\", \"2026-01-02\", \"2026-01-03\", \"2026-01-04\", \"2026-01-05\", \"2026-01-06\", \"2026-01-07\"];\n const counts = Object.fromEntries(range.map((date) => [date, 2]));\n assertEquals(hasPerfectWeekStreak(range, counts), true);\n});\n\nDeno.test(\"formatCreatedTime extracts time from Notion-style string\", () => {\n const formatted = formatCreatedTime(\"January 13, 2026 6:33 PM\");\n assertEquals(formatted, \"6:33 PM\");\n});\n\nDeno.test(\"formatCreatedTime formats ISO timestamps\", () => {\n const formatted = formatCreatedTime(\"2026-01-13T18:33:00.000Z\");\n assertEquals(formatted, \"1:33 PM\");\n});\n\nDeno.test(\"formatGroupedEntryLine orders entries by time\", () => {\n const entries: Entry[] = [\n { date: \"2026-01-01\", createdTime: \"6:30 PM\", value: 110 },\n { date: \"2026-01-01\", createdTime: \"6:30 AM\", value: 90 },\n ];\n const grouped = groupEntriesByDate(entries, [\"2026-01-01\"]);\n const line = formatGroupedEntryLine(grouped[0]);\n assertEquals(line, \"2026-01-01 | 1st: 90 | 2nd: 110\");\n});\n\nDeno.test(\"buildBloodSugarRollup uses deterministic runId and stats\", () => {\n const entries: Entry[] = [\n { date: \"2026-01-01\", createdTime: \"7:00 AM\", value: 90 },\n { date: \"2026-01-01\", createdTime: \"7:00 PM\", value: 100 },\n ];\n const rollup = buildBloodSugarRollup(entries, \"2026-01-01\", \"2026-01-07\");\n assertEquals(rollup.category, \"blood_sugar\");\n assertEquals(rollup.runId, \"blood_sugar-2026-01-01-2026-01-07\");\n assertEquals(rollup.stats.totalEntries, 2);\n assertEquals(rollup.stats.entriesByDate[\"2026-01-01\"], 2);\n});\n",[],[2004,2030],{"_105":2039,"_97":2040,"_161":2041,"_163":2005,"_164":146,"_165":2042,"_167":168,"_107":2043,"_101":1904,"_170":1923,"_172":2044,"_173":22,"_174":-5,"_175":2045,"_100":2046},"d38333c4-f311-11f0-9c46-42dde27851f2","rollups.test.ts","cf244a02-f311-11f0-8a46-42dde27851f2",326,["D",1768591833699],"import { buildUpsertWeeklyRollupQuery, type WeeklyRollup } from \"../storage/rollups.ts\";\nimport { assertEquals } from \"https://deno.land/std@0.224.0/assert/mod.ts\";\n\n// Ensures persistence overwrites by runId instead of inserting duplicates.\nDeno.test(\"buildUpsertWeeklyRollupQuery uses INSERT OR REPLACE with runId\", () => {\n const rollup: WeeklyRollup = {\n category: \"food\",\n periodStart: \"2026-01-01\",\n periodEnd: \"2026-01-07\",\n streak: 3,\n completionRate: 57,\n xp: 12,\n badges: [\"A\"],\n stats: { totalEntries: 4 },\n runId: \"food-2026-01-01-2026-01-07\",\n };\n const createdAt = \"2026-01-08T00:00:00.000Z\";\n const query = buildUpsertWeeklyRollupQuery(rollup, createdAt);\n assertEquals(query.sql.startsWith(\"INSERT OR REPLACE\"), true);\n assertEquals(query.args[8], rollup.runId);\n assertEquals(query.args[9], createdAt);\n});\n",[],[2004,2040],[2004],{"_105":2049,"_97":2050,"_161":2051,"_163":-5,"_164":146,"_165":2052,"_167":168,"_107":2053,"_101":2054,"_170":198,"_172":2055,"_173":22,"_174":-5,"_175":2056,"_100":2057},"8ef158b8-f7ac-11f0-868c-42dde27851f2",".env.example","8ac592f0-f0c1-11f0-b3c8-42dde27851f2",412,["D",1769098095301],14,"NOTION_TOKEN=\nNOTION_BLOOD_SUGAR_DB_ID=\nNOTION_FOOD_DB_ID=\nREPORT_FROM_EMAIL=\nREPORT_FROM_NAME=\nREPORT_REPLY_TO=\nROLLUP_PERSIST_URL=\nROLLUP_PERSIST_TOKEN=\nFATSECRET_CLIENT_ID=\nFATSECRET_CLIENT_SECRET=\n",[],[2050],{"_105":2059,"_97":2060,"_161":2061,"_163":-5,"_164":146,"_165":2062,"_167":22,"_107":2063,"_101":33,"_170":198,"_172":2064,"_173":22,"_174":-5,"_175":2065,"_100":2066},"8ac8f058-f0c1-11f0-8753-42dde27851f2",".gitignore","8ac8f116-f0c1-11f0-8753-42dde27851f2",8,["D",1768337449610],".DS_Store\n.env\n*.log\n.vt\n",[],[2060],{"_105":2068,"_97":2069,"_161":2070,"_163":-5,"_164":146,"_165":2071,"_167":168,"_107":2072,"_101":1904,"_170":198,"_172":2073,"_173":22,"_174":-5,"_175":2074,"_100":2075},"65e49bf2-fadf-11f0-ad5b-42dde27851f2","deno.json","4e7388d6-f23b-11f0-8424-42dde27851f2",427,["D",1769449784218],"{\n \"$schema\": \"https://raw.githubusercontent.com/denoland/deno/98f62cee78e85bfc47c62ed703777c6bc8794f1c/cli/schemas/config-file.v1.json\",\n \"lock\": false,\n \"compilerOptions\": {\n \"noImplicitAny\": false,\n \"strict\": true,\n \"types\": [\"https://www.val.town/types/valtown.d.ts\"],\n \"lib\": [\n \"dom\",\n \"dom.iterable\",\n \"dom.asynciterable\",\n \"deno.ns\",\n \"deno.unstable\"\n ]\n },\n \"lint\": {\n \"include\": [\"**/*.ts\", \"**/*.tsx\", \"deno:/https/esm.town/**/*\"],\n \"rules\": {\n \"exclude\": [\"no-explicit-any\", \"no-import-prefix\"]\n }\n },\n \"node_modules_dir\": false,\n \"experimental\": {\n \"unstable-node-globals\": true,\n \"unstable-temporal\": true,\n \"unstable-worker-options\": true,\n \"unstable-sloppy-imports\": true\n },\n \"tasks\": {\n \"test\": \"deno test --allow-import --allow-env=VAL_TOWN_API_KEY --reporter=dot\"\n }\n}\n",[],[2069],{"_105":2077,"_97":2078,"_161":2079,"_163":-5,"_164":146,"_165":2080,"_167":168,"_107":2081,"_101":1922,"_170":198,"_172":2082,"_173":22,"_174":-5,"_175":2083,"_100":2084},"65d27b16-fadf-11f0-bd8f-42dde27851f2","plan.md","ff57afba-f0c9-11f0-8caa-42dde27851f2",424,["D",1769449784132],"# Notion Life Tracker Plan\n\n## What we've built so far\n\n- A Notion database for blood sugar readings\n- A Val Town script that pulls the last 7 days of entries\n- Weekly stats with streaks, XP, and Praise Cage-themed badges\n- A friendly email report sent on a schedule (free tier friendly)\n- Tests for core logic (streaks, badges, XP)\n- A SQLite rollup module stub for future storage\n- A food log enricher that reads Notion entries, estimates macros with OpenAI, and writes them back\n- Food enrichment now normalizes entries with OpenAI, infers serving sizes, and uses FatSecret's detailed nutrition\n- Weekly rollups persisted to SQLite for blood sugar and food\n- Monthly rollup report page with a month selector (Memphis-styled)\n\n## Why this works well\n\n- We only query Notion for a small time window (fast even as Notion grows)\n- We compute the rollup once per week and send it as a summary\n- We can reuse the same pattern for other life areas (exercise, meals, goals)\n\n## Next step: extend rollup reporting\n\nWe store weekly rollups (badges, streaks, XP) in Val Town’s SQLite so we can:\n- build monthly and yearly summaries without re-reading Notion\n- compare across categories (e.g., blood sugar vs exercise)\n- keep a long-term history even if we rename Notion pages\n\n## Proposed storage shape\n\n- `weekly_rollups`: one row per category per week\n- `badge_events`: a history of badges earned\n\nEach rollup stores:\n- category (e.g., `blood_sugar`)\n- period start/end (YYYY-MM-DD)\n- streak, completion rate, XP\n- badges as JSON\n- summary stats as JSON\n\n## How new trackers fit in\n\nFor each new Notion database:\n1) Add a small “collector” val that maps entries into a shared event format.\n2) Reuse the rollup logic and write weekly results to SQLite.\n3) Generate emails or dashboards from the stored rollups.\n\nThis keeps the system simple while still scaling to many life areas.\n\n## What's left to do\n\n- Define XP/badge rule config so new trackers can reuse it\n- Add yearly rollup report (from SQLite, not Notion)\n- Add a sample “collector” val for another Notion database (e.g., exercise)\n - Add run_id generation strategy (UUID or deterministic) and document it\n - Validate email layout on Gmail mobile and adjust spacing if needed\n- Add serving-size overrides and caching for food enrichment\n\n## New feature: Val-scoped rollup workspace\n\nThe new **val-scoped SQLite databases** (see “Every val gets a database!”, Jan 23, 2026) let each val persist its own data with a built-in browser and forkable state. We can lean into this by turning every collector into a self-serve insights workspace that ships with its data. Key ideas:\n\n- **Goal:** capture raw Notion snapshots + derived rollups inside the val-scoped DB so maintainers can inspect/patch rows via Val Town’s new DB UI and forks inherit the historical data.\n- **Why now:** previously we used a shared `stevekrouse/sqlite` database, so tables mixed across vals and forks lost history. Scoped DBs fix isolation, give us point-in-time forks, and expose schema editing + CSV export without extra tooling.\n\n### User stories\n- As a maintainer, I can open the Val Town DB browser for `blood_sugar_report` and see weekly rollups + the raw Notion entries that fed them.\n- When I fork the val, I can choose to fork the database so I get a sample dataset (perfect for demos/tests).\n- I can alter or backfill rows right from the UI if a Notion entry was missing, then re-run the val and it reuses those edits.\n\n### Technical plan\n1. **Adopt the new client**\n - Introduce `storage/sqlite.ts` that re-exports `std/sqlite` so every module uses the scoped DB (no more `stevekrouse/sqlite` import).\n - Update `storage/rollups.ts`, `collectors/*.ts(x)`, and `services/monthly_report_page.http.tsx` to consume the new helper.\n2. **Expand schema per val**\n - Add tables: `notion_entries` (raw JSON per sync run), `collector_runs` (metadata + errors), and keep the existing `weekly_rollups` / `badge_events`.\n - Ensure schema setup runs on every execution (idempotent `CREATE TABLE IF NOT EXISTS`).\n3. **Persist richer data**\n - In collectors, before building reports, upsert `collector_runs` + `notion_entries` with the fetched payload, keyed by `run_id`.\n - Store derived stats/badges in `weekly_rollups` referencing the same `run_id`.\n4. **Ship a DB-backed UI**\n - Add a new HTTP val (e.g., `services/rollup_workspace.http.tsx`) that queries the scoped DB and renders:\n - latest sync runs with status + row counts\n - raw entry drill-down (JSON pretty print) and weekly rollups\n - Provide download links that hit lightweight CSV/JSON routes backed by SQL queries (can reuse Val Town DB UI exports too).\n5. **Migration + docs**\n - Write a one-off `scripts/migrate_shared_db.ts` to copy data from the legacy shared database into the val-scoped DB (optional but documented).\n - Update `readme.md` with “Using the val-scoped database” instructions (link to DB UI, how to fork with data, etc.).\n\n### Open questions\n- Do we need to keep writing to the old shared database for compatibility with the existing monthly report? (Probably no once UI + service switch to the scoped DB.)\n- Should food + blood sugar share one val (single DB) or live in separate vals with their own scoped DBs? (Decide before migrating.)\n- How much sample data should we ship when people fork the val—full history or a trimmed seed week?\n",[],[2078],{"_105":2086,"_97":2087,"_161":2088,"_163":-5,"_164":146,"_165":2089,"_167":168,"_107":2090,"_101":2091,"_170":198,"_172":2092,"_173":22,"_174":-5,"_175":2093,"_100":2094},"8f23b9ca-f7ac-11f0-97ba-42dde27851f2","readme.md","904dec56-f0bf-11f0-a3c7-42dde27851f2",419,["D",1769098095303],32,"# Notion Life Tracker (Val Town)\n\nThis repo contains Val Town-ready scripts that:\n- fetch Notion entries for the last 7 days (UTC)\n- send a weekly blood sugar rollup via email\n- enrich food log entries with estimated macros and write them back to Notion\n\n## What this does (plain language)\n\nThink of this as two simple helpers:\n- You write down blood sugar readings in Notion.\n- Once a week, the script looks at the last 7 days and emails you a summary.\n- You write down foods you ate in another Notion database.\n- The food script estimates macros and fills them in.\n\n## A tiny bit of computer science (friendly version)\n\nEven though this feels simple, it uses a few classic CS ideas:\n- **Data modeling:** you define what a “reading” is (date, time, value).\n- **Filtering:** you only look at a specific window of time (last 7 days).\n- **Aggregation:** you summarize many values into a few stats (avg/min/max).\n- **Automation:** a scheduled job runs the same steps every week.\n\nIf you can build or understand this, you’re already practicing real CS thinking—just without the scary jargon.\n\n## Praise Cage mode\n\nThis project includes playful, Praise Cage-themed badges:\n- “Mandy-Mode Consistency”\n- “Cage Match: Full Week”\n- “Cage Match: Double-Check Champion”\n- “National Treasure: Healthy Average”\n\nYou can rename or swap these in `collectors/blood_sugar_report.cron.tsx`.\n\n## Medical disclaimer\n\nThis report is for informational purposes only and is not medical advice.\nHealthy blood sugar ranges referenced here come from:\nhttps://www.ynhhs.org/articles/what-is-healthy-blood-sugar\n\n## 1) Create the Notion databases\n\n### Blood Sugar Log\n\nCreate a new database in Notion (table view is easiest) with these properties:\n\n- **Entry** (Title)\n- **Created time** (Created time)\n- **Blood Sugar Level** (Number)\n\nYou can name the database anything (e.g., \"Blood Sugar Log\").\n\n### Food Log (Macro Enrichment)\n\nCreate another Notion database with these properties (exact names expected):\n\n- `food` (Title or Text)\n- `Created time` (Created time)\n- `calories` (Number)\n- `protein` (Number)\n- `carbs` (Number)\n- `fats` (Number)\n- `fiber` (Number)\n- `sugar` (Number)\n- `sodium` (Number)\n\nOnly `food` and `Created time` are required for reading. The rest are written by the val.\nThe food val uses OpenAI to normalize entries and infer a reasonable serving size, then pulls detailed\nnutrition from FatSecret (`food.get`) for calories, protein, carbs, fat, fiber, sugar, and sodium.\nMacros are scaled by the inferred serving size using FatSecret's default serving.\n\nExample:\n- Input: `shrimp lo mein`\n- OpenAI normalization: `{ \"items\": [{ \"name\": \"shrimp lo mein\", \"servings\": 1 }] }`\n- FatSecret returns macros per default serving, and the val writes those directly.\n- Input: `2 slices pepperoni pizza and salad`\n- OpenAI normalization: `{ \"items\": [{ \"name\": \"pepperoni pizza\", \"servings\": 2 }, { \"name\": \"salad\", \"servings\": 1 }] }`\n- The val scales each item's macros by its servings and sums the results.\n\n## 2) Create a Notion integration\n\n1. Go to https://www.notion.so/my-integrations and create a new integration.\n2. Copy the **Internal Integration Token**.\n3. Open your database in Notion, click **Share**, and invite the integration.\n\n### Database IDs\nOpen each database in the browser and copy the 32‑character ID in the URL.\n\n## 3) Configure Val Town (CLI)\n\nCreate new Vals with the `vt` CLI, then sync from this repo:\n\n```\nvt create blood_sugar_report\nvt create food_report\nvt create monthly_report_page\n```\n\nReplace each generated Val file with the corresponding script from this repo:\n- `collectors/blood_sugar_report.cron.tsx`\n- `collectors/food_report.cron.tsx`\n- `services/monthly_report_page.http.tsx`\n\nThen push each Val:\n\n```\nvt push\n```\n\n### Secrets\n\nShared:\n- `NOTION_TOKEN`\n\nBlood sugar val:\n- `NOTION_BLOOD_SUGAR_DB_ID`\n- `REPORT_FROM_EMAIL` (optional, must be `your_username.valname@valtown.email`)\n- `REPORT_FROM_NAME` (optional)\n- `REPORT_REPLY_TO` (optional)\n\nFood log val:\n- `NOTION_FOOD_DB_ID`\n\nFree tier note: the blood sugar val emails the account owner by default.\n\nThe food val uses Val Town's `std/openai` proxy with `gpt-5-nano`, so no OpenAI API key is required.\n\nThe monthly report val renders a Memphis-inspired report page from SQLite rollups, with a month selector and partial-week toggle (auto-refresh).\n\n## 4) Schedule the report\n\nIn Val Town, schedule the Val to run weekly at 9:30am on Tuesdays (EST).\n\nSuggested cron (set Val Town timezone to EST):\n```\n30 9 * * 2\n```\n\n### What the cron line means\n\nCron is a simple way to say “run this on a schedule.” It has five fields:\n\n```\nminute hour day-of-month month day-of-week\n```\n\nSo `30 9 * * 2` means:\n- minute = 30\n- hour = 9\n- day-of-month = * (every day of the month)\n- month = * (every month)\n- day-of-week = 2 (Tuesday)\n\nIn other words: every Tuesday at 9:30am.\n\n## 5) Customize\n\n- Adjust the stats, date range, or email formatting in `collectors/blood_sugar_report.cron.tsx`.\n- If you prefer different property names, update them in the script.\n- Weekly rollups for both categories are persisted to Val Town SQLite for monthly/quarterly summaries.\n- Monthly report page supports query params:\n - `?month=YYYY-MM` (defaults to previous month)\n - `?partial=true` to include overlapping weeks\n\n## Development\n\nRun tests:\n```\ndeno test --allow-import --reporter=dot\n```\n\nRun lint:\n```\ndeno lint\n```\n\nMade with 🖖 by Paul Chin Jr. and Markal.\n",[],[2087],"files",[158,177,185,192,202,211,220,229,238,247,256,265,274,283,292,301,311,319,326,333,341,348,359,366,374,382,390,397,407,415,423,431,439,447,455,463,471,479,487,495,503,511,519,527,535,543,551,558,568,575,585,593,601,609,617,625,633,641,649,657,665,673,681,688,698,706,714,722,730,738,746,753,763,771,779,787,795,803,811,819,827,835,842,852,860,868,876,884,892,900,908,916,924,931,941,949,957,965,973,981,989,997,1004,1014,1022,1029,1038,1046,1054,1062,1070,1078,1085,1095,1103,1110,1120,1128,1135,1145,1153,1161,1169,1177,1184,1194,1202,1210,1218,1226,1234,1242,1250,1258,1266,1274,1282,1289,1299,1306,1316,1324,1332,1340,1348,1356,1364,1372,1380,1388,1396,1404,1412,1420,1428,1436,1444,1452,1460,1468,1476,1484,1492,1500,1508,1516,1524,1532,1540,1548,1556,1564,1572,1580,1588,1596,1604,1612,1619,1629,1636,1646,1654,1662,1670,1678,1686,1694,1702,1709,1719,1727,1734,1743,1749,1756,1762,1770,1779,1788,1797,1806,1815,1825,1832,1841,1851,1858,1869,1880,1887,1898,1909,1916,1927,1936,1945,1955,1964,1975,1982,1992,2002,2009,2019,2028,2038,2048,2058,2067,2076,2085],"counts",{"_2099":33,"_179":1904,"_2100":33,"_2101":2102,"_2105":2106},"pulls","forks","envVars",{"_2103":1922,"_2104":33},"count","emptyCount","connections",{"_2103":33,"_2107":33},"unfilledCount","contents",[2110,2113,2116,2119,2122,2125,2128,2131,2134,2137,2140,2143],{"_105":159,"_97":160,"_161":162,"_163":-5,"_164":146,"_165":166,"_167":168,"_107":2111,"_101":33,"_170":171,"_172":-5,"_173":22,"_174":-5,"_100":2112},["D",1769449835209],[160],{"_105":1826,"_97":1827,"_161":1828,"_163":-5,"_164":146,"_165":1829,"_167":168,"_107":2114,"_101":33,"_170":171,"_172":-5,"_173":22,"_174":-5,"_100":2115},["D",1768499629401],[1827],{"_105":1852,"_97":1853,"_161":1854,"_163":-5,"_164":146,"_165":1855,"_167":168,"_107":2117,"_101":33,"_170":171,"_172":-5,"_173":22,"_174":-5,"_100":2118},["D",1768499629095],[1853],{"_105":1881,"_97":1882,"_161":1883,"_163":-5,"_164":146,"_165":1884,"_167":168,"_107":2120,"_101":33,"_170":171,"_172":-5,"_173":22,"_174":-5,"_100":2121},["D",1768499628695],[1882],{"_105":1910,"_97":1911,"_161":1912,"_163":-5,"_164":146,"_165":1913,"_167":168,"_107":2123,"_101":33,"_170":171,"_172":-5,"_173":22,"_174":-5,"_100":2124},["D",1768499629303],[1911],{"_105":1976,"_97":1977,"_161":1978,"_163":-5,"_164":146,"_165":1979,"_167":168,"_107":2126,"_101":33,"_170":171,"_172":-5,"_173":22,"_174":-5,"_100":2127},["D",1768341095957],[1977],{"_105":2003,"_97":2004,"_161":2005,"_163":-5,"_164":146,"_165":2006,"_167":168,"_107":2129,"_101":33,"_170":171,"_172":-5,"_173":22,"_174":-5,"_100":2130},["D",1768588056443],[2004],{"_105":2049,"_97":2050,"_161":2051,"_163":-5,"_164":146,"_165":2052,"_167":168,"_107":2132,"_101":2054,"_170":198,"_172":2055,"_173":22,"_174":-5,"_100":2133},["D",1769098095301],[2050],{"_105":2059,"_97":2060,"_161":2061,"_163":-5,"_164":146,"_165":2062,"_167":22,"_107":2135,"_101":33,"_170":198,"_172":2064,"_173":22,"_174":-5,"_100":2136},["D",1768337449610],[2060],{"_105":2068,"_97":2069,"_161":2070,"_163":-5,"_164":146,"_165":2071,"_167":168,"_107":2138,"_101":1904,"_170":198,"_172":2073,"_173":22,"_174":-5,"_100":2139},["D",1769449784218],[2069],{"_105":2077,"_97":2078,"_161":2079,"_163":-5,"_164":146,"_165":2080,"_167":168,"_107":2141,"_101":1922,"_170":198,"_172":2082,"_173":22,"_174":-5,"_100":2142},["D",1769449784132],[2078],{"_105":2086,"_97":2087,"_161":2088,"_163":-5,"_164":146,"_165":2089,"_167":168,"_107":2144,"_101":2091,"_170":198,"_172":2092,"_173":22,"_174":-5,"_100":2145},["D",1769098095303],[2087],"upstreamProject","upstreamBranch","emptyEnvVars","isNew","flags",[],"routes/_app.x.$handle.$name.branch.$branch.version.$version.diff",{"_103":2154,"_101":102,"_2159":2160},{"_105":106,"_97":98,"_107":2155,"_109":-5,"_110":22,"_111":112,"_113":74,"_114":-5,"_14":115,"_116":-5,"_117":22,"_118":-5,"_119":-5,"_120":33,"_16":121,"_122":123,"_124":125,"_126":127,"_128":127,"_129":130,"_131":130,"_132":130,"_133":127,"_134":127,"_23":2156,"_138":2157,"_143":2158,"_155":22},["D",1768332030028],{"_95":96,"_136":137},{"_95":96,"_140":137,"_14":115,"_141":142},{"_101":145,"_97":45,"_105":146,"_147":106,"_148":-5,"_149":-5,"_150":-5,"_151":-5,"_152":-5,"_153":98,"_154":96},"changes",[2161],{"_198":2162,"_2164":-7,"_173":22,"_100":2165,"_2166":2165},{"_161":1032,"_97":1031,"_170":198,"_172":1034,"_107":2163,"_165":102,"_164":146},["D",1769449895926],"previous",".git/objects/80/96894527e60ecd556308bde37fea21f24ed9e1","latestPath","actionData","errors"]

pchinjr

notion_weekly_report