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{};\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 eventTypeProp = props[PROPERTY_NAMES.eventType] as NotionSelectProperty | undefined;\n const eatingWindowProp = props[PROPERTY_NAMES.eatingWindow] as NotionSelectProperty | undefined;\n const normalizedItemsProp = props[PROPERTY_NAMES.normalizedItemsJson] as NotionTextProperty | undefined;\n const enrichmentSourceProp = props[PROPERTY_NAMES.enrichmentSource] as NotionTextProperty | undefined;\n const normalizedItems = extractNormalizedItems(normalizedItemsProp);\n const macros = extractMacros(props);\n const inferredEventType = inferEventType(food, normalizedItems);\n const inferredWindow = deriveEatingWindow(loggedAt);\n\n return {\n pageId: page.id,\n date: loggedAt.slice(0, 10),\n loggedAt,\n food,\n eventType: normalizeEventType(eventTypeProp?.select?.name) ?? inferredEventType,\n eatingWindow: normalizeEatingWindow(eatingWindowProp?.select?.name) ?? inferredWindow,\n normalizedItems,\n enrichmentConfidence: extractNumberProperty(props[PROPERTY_NAMES.enrichmentConfidence]),\n enrichmentSource: normalizeEnrichmentSource(extractRichTextValue(enrichmentSourceProp)),\n macros,\n };\n}\n\nexport function extractFoodName(\n prop: NotionTitleProperty | NotionTextProperty | undefined,\n): string | null {\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\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\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 !entry.normalizedItems.length ||\n entry.enrichmentConfidence === undefined\n );\n}\n\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\nexport function buildEntryProperties(\n entry: Entry,\n enrichment: {\n macros: Partial>;\n normalizedItems: NormalizedFoodItem[];\n confidence: number;\n source: EnrichmentSource;\n eventType?: EventType;\n eatingWindow?: EatingWindow;\n },\n): Record {\n const properties: Record = {};\n const missingMacros = Object.fromEntries(\n Object.entries(enrichment.macros).filter(([key]) => entry.macros[key as MacroKey] === undefined),\n ) as Partial>;\n\n Object.assign(properties, buildNutritionProperties(missingMacros));\n\n const eventType = enrichment.eventType ?? entry.eventType;\n const eatingWindow = enrichment.eatingWindow ?? entry.eatingWindow;\n properties[PROPERTY_NAMES.eventType] = { select: { name: eventType } };\n properties[PROPERTY_NAMES.eatingWindow] = { select: { name: eatingWindow } };\n properties[PROPERTY_NAMES.normalizedItemsJson] = {\n rich_text: [{ type: \"text\", text: { content: JSON.stringify(enrichment.normalizedItems) } }],\n };\n properties[PROPERTY_NAMES.enrichmentConfidence] = { number: enrichment.confidence };\n properties[PROPERTY_NAMES.enrichmentSource] = {\n rich_text: [{ type: \"text\", text: { content: enrichment.source } }],\n };\n return properties;\n}\n\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 const behaviorStats = calculateBehaviorStats(entries, dateRange);\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 daysWithOneEvent: behaviorStats.daysWithOneEvent,\n daysWithTwoEvents: behaviorStats.daysWithTwoEvents,\n daysWithThreePlusEvents: behaviorStats.daysWithThreePlusEvents,\n lateNightEntries: behaviorStats.lateNightEntries,\n snackEntries: behaviorStats.snackEntries,\n eatingWindowCounts: behaviorStats.eatingWindowCounts,\n avgFirstEventHour: behaviorStats.avgFirstEventHour,\n avgLastEventHour: behaviorStats.avgLastEventHour,\n avgDailyEatingSpanHours: behaviorStats.avgDailyEatingSpanHours,\n macroSummary,\n },\n runId: `food-${start}-${end}`,\n };\n}\n\nexport function roundNumber(value: number): number {\n return Number(value.toFixed(2));\n}\n\nexport function buildNutritionPrompt(food: string): string {\n return `Normalize and estimate macros for a food log entry: \"${food}\".`;\n}\n\nexport function safeParseJson(value: string): unknown {\n try {\n return JSON.parse(value);\n } catch {\n return null;\n }\n}\n\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(([, currentValue]) => typeof currentValue === \"number\" && Number.isFinite(currentValue)),\n ) as Partial>;\n}\n\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\nexport function deriveEatingWindow(loggedAt: string): EatingWindow {\n const hour = extractHourInTimeZone(loggedAt);\n if (hour >= 5 && hour <= 10) return \"morning\";\n if (hour >= 11 && hour <= 13) return \"midday\";\n if (hour >= 14 && hour <= 16) return \"afternoon\";\n if (hour >= 17 && hour <= 20) return \"evening\";\n return \"late_night\";\n}\n\nexport function inferEventType(food: string, items: NormalizedFoodItem[]): EventType {\n const sourceText = food.toLowerCase();\n if (/\\b(coffee|latte|tea|juice|smoothie|protein shake|soda|water)\\b/.test(sourceText)) return \"drink\";\n if (/\\b(snack|chips|trail mix|cookie|crackers|granola bar|yogurt|fruit|banana|apple)\\b/.test(sourceText)) {\n return \"snack\";\n }\n if (items.length === 1 && /\\b(espresso|coffee|tea|latte|juice|smoothie)\\b/.test(items[0].name.toLowerCase())) {\n return \"drink\";\n }\n if (items.length <= 2 && /\\b(handful|small|bar|cup|piece|slice)\\b/.test(sourceText)) return \"snack\";\n return \"meal\";\n}\n\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\nfunction calculateBehaviorStats(entries: Entry[], dateRange: string[]) {\n const perDay = new Map();\n for (const entry of entries) {\n const current = perDay.get(entry.date) ?? [];\n current.push(entry);\n perDay.set(entry.date, current);\n }\n\n let daysWithOneEvent = 0;\n let daysWithTwoEvents = 0;\n let daysWithThreePlusEvents = 0;\n let firstHourTotal = 0;\n let lastHourTotal = 0;\n let spanTotal = 0;\n let activeDays = 0;\n let lateNightEntries = 0;\n let snackEntries = 0;\n const eatingWindowCounts: Record = {\n morning: 0,\n midday: 0,\n afternoon: 0,\n evening: 0,\n late_night: 0,\n };\n\n for (const entry of entries) {\n if (entry.eventType === \"snack\") snackEntries += 1;\n if (entry.eatingWindow === \"late_night\") lateNightEntries += 1;\n eatingWindowCounts[entry.eatingWindow] += 1;\n }\n\n for (const date of dateRange) {\n const dayEntries = (perDay.get(date) ?? []).slice().sort((a, b) => a.loggedAt.localeCompare(b.loggedAt));\n const count = dayEntries.length;\n if (count === 1) daysWithOneEvent += 1;\n if (count === 2) daysWithTwoEvents += 1;\n if (count >= 3) daysWithThreePlusEvents += 1;\n if (!count) continue;\n activeDays += 1;\n const hours = dayEntries.map((entry) => extractHourFractionInTimeZone(entry.loggedAt)).filter(Number.isFinite);\n const firstHour = hours[0] ?? 0;\n const lastHour = hours[hours.length - 1] ?? firstHour;\n firstHourTotal += firstHour;\n lastHourTotal += lastHour;\n spanTotal += Math.max(0, lastHour - firstHour);\n }\n\n return {\n daysWithOneEvent,\n daysWithTwoEvents,\n daysWithThreePlusEvents,\n lateNightEntries,\n snackEntries,\n eatingWindowCounts,\n avgFirstEventHour: activeDays ? roundNumber(firstHourTotal / activeDays) : 0,\n avgLastEventHour: activeDays ? roundNumber(lastHourTotal / activeDays) : 0,\n avgDailyEatingSpanHours: activeDays ? roundNumber(spanTotal / activeDays) : 0,\n };\n}\n\nfunction extractNormalizedItems(prop: NotionTextProperty | undefined): NormalizedFoodItem[] {\n const value = extractRichTextValue(prop);\n if (!value) return [];\n const parsed = safeParseJson(value);\n if (!Array.isArray(parsed)) return [];\n return parsed.map(normalizeNormalizedItem).filter((item): item is NormalizedFoodItem => !!item);\n}\n\nfunction normalizeNormalizedItem(value: unknown): NormalizedFoodItem | null {\n if (!value || typeof value !== \"object\") return null;\n const record = value as Record;\n const name = typeof record.name === \"string\" ? record.name.trim() : \"\";\n if (!name) return null;\n const servings = sanitizeServings(coerceNumber(record.servings) ?? 1);\n const confidence = sanitizeConfidence(coerceNumber(record.confidence) ?? 0.5);\n const source = record.source === \"openai\" ? \"openai\" : \"heuristic\";\n const matchedName = typeof record.matchedName === \"string\" ? record.matchedName : undefined;\n const matchConfidence = record.matchConfidence === undefined\n ? undefined\n : sanitizeConfidence(coerceNumber(record.matchConfidence) ?? 0.5);\n const matchSource = record.matchSource === \"fatsecret_detail\" || record.matchSource === \"fatsecret_search\"\n ? record.matchSource\n : undefined;\n return { name, servings, confidence, source, matchedName, matchConfidence, matchSource };\n}\n\nfunction extractRichTextValue(prop: NotionTextProperty | undefined): string | null {\n if (!prop?.rich_text?.length) return null;\n const value = prop.rich_text.map((item) => item.plain_text).join(\"\").trim();\n return value || null;\n}\n\nfunction extractNumberProperty(value: unknown): number | undefined {\n const numeric = (value as NotionNumberProperty | undefined)?.number;\n return typeof numeric === \"number\" ? numeric : undefined;\n}\n\nfunction normalizeEventType(value?: string | null): EventType | null {\n if (value === \"meal\" || value === \"snack\" || value === \"drink\") return value;\n return null;\n}\n\nfunction normalizeEatingWindow(value?: string | null): EatingWindow | null {\n if (\n value === \"morning\" || value === \"midday\" || value === \"afternoon\" || value === \"evening\" ||\n value === \"late_night\"\n ) {\n return value;\n }\n return null;\n}\n\nfunction normalizeEnrichmentSource(value?: string | null): EnrichmentSource | undefined {\n if (\n value === \"heuristic\" || value === \"openai\" || value === \"fatsecret_detail\" || value === \"fatsecret_search\" ||\n value === \"manual\"\n ) {\n return value;\n }\n return undefined;\n}\n\nfunction extractHourInTimeZone(value: string): number {\n const parsed = new Date(value);\n if (Number.isNaN(parsed.getTime())) return 12;\n const formatter = new Intl.DateTimeFormat(\"en-US\", {\n timeZone: REPORT_TIMEZONE,\n hour: \"numeric\",\n hour12: false,\n });\n return Number(formatter.format(parsed));\n}\n\nfunction extractHourFractionInTimeZone(value: string): number {\n const parsed = new Date(value);\n if (Number.isNaN(parsed.getTime())) return 0;\n const parts = new Intl.DateTimeFormat(\"en-US\", {\n timeZone: REPORT_TIMEZONE,\n hour: \"2-digit\",\n minute: \"2-digit\",\n hour12: false,\n }).formatToParts(parsed);\n const lookup = parts.reduce>((acc, part) => {\n acc[part.type] = part.value;\n return acc;\n }, {});\n const hour = Number(lookup.hour ?? \"0\");\n const minute = Number(lookup.minute ?? \"0\");\n return hour + (minute / 60);\n}\n\nfunction sanitizeServings(value: number): number {\n if (!Number.isFinite(value) || value <= 0) return 1;\n return roundNumber(value);\n}\n\nfunction sanitizeConfidence(value: number): number {\n if (!Number.isFinite(value)) return 0.5;\n return roundNumber(Math.min(1, Math.max(0, value)));\n}\n","import {\n type NotionCreatedTimeProperty,\n type NotionDateProperty,\n type NotionNumberProperty,\n type NotionPage,\n type NotionSelectProperty,\n type NotionTextProperty,\n type NotionTitleProperty,\n} from \"./notion.ts\";\nimport { calculateCurrentStreak, countEntriesByDate, listDateRange } from \"./date.ts\";\n\nconst REPORT_TIMEZONE = \"America/New_York\";\n\nexport type MacroKey = \"calories\" | \"protein\" | \"carbs\" | \"fat\" | \"fiber\" | \"sugar\" | \"sodium\";\nexport type EventType = \"meal\" | \"snack\" | \"drink\";\nexport type EatingWindow = \"morning\" | \"midday\" | \"afternoon\" | \"evening\" | \"late_night\";\nexport type EnrichmentSource = \"heuristic\" | \"openai\" | \"fatsecret_detail\" | \"fatsecret_search\" | \"manual\";\n\nexport type NormalizedFoodItem = {\n name: string;\n servings: number;\n confidence: number;\n source: \"heuristic\" | \"openai\";\n matchedName?: string;\n matchConfidence?: number;\n matchSource?: \"fatsecret_detail\" | \"fatsecret_search\";\n};\n\nexport type Entry = {\n pageId: string;\n date: string;\n loggedAt: string;\n food: string;\n eventType: EventType;\n eatingWindow: EatingWindow;\n normalizedItems: NormalizedFoodItem[];\n enrichmentConfidence?: number;\n enrichmentSource?: EnrichmentSource;\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 daysWithOneEvent: number;\n daysWithTwoEvents: number;\n daysWithThreePlusEvents: number;\n lateNightEntries: number;\n snackEntries: number;\n eatingWindowCounts: Record;\n avgFirstEventHour: number;\n avgLastEventHour: number;\n avgDailyEatingSpanHours: 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\nexport const PROPERTY_NAMES = {\n title: \"food\",\n loggedAt: \"Created time\",\n eventType: \"event type\",\n eatingWindow: \"eating window\",\n normalizedItemsJson: \"normalized items json\",\n enrichmentConfidence: \"enrichment confidence\",\n enrichmentSource: \"enrichment source\",\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} as const;\n\nexport const FOOD_SCHEMA_PROPERTIES = {\n [PROPERTY_NAMES.eventType]: {\n select: {\n options: [\n { name: \"meal\", color: \"blue\" },\n { name: \"snack\", color: \"yellow\" },\n { name: \"drink\", color: \"green\" },\n ],\n },\n },\n [PROPERTY_NAMES.eatingWindow]: {\n select: {\n options: [\n { name: \"morning\", color: \"green\" },\n { name: \"midday\", color: \"blue\" },\n { name: \"afternoon\", color: \"orange\" },\n { name: \"evening\", color: \"purple\" },\n { name: \"late_night\", color: \"red\" },\n ],\n },\n },\n [PROPERTY_NAMES.normalizedItemsJson]: { rich_text: {} },\n [PROPERTY_NAMES.enrichmentConfidence]: { number: { format: \"number_with_commas\" } },\n [PROPERTY_NAMES.enrichmentSource]: { rich_text: {} },\n} as const;\n\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 eventTypeProp = props[PROPERTY_NAMES.eventType] as NotionSelectProperty | undefined;\n const eatingWindowProp = props[PROPERTY_NAMES.eatingWindow] as NotionSelectProperty | undefined;\n const normalizedItemsProp = props[PROPERTY_NAMES.normalizedItemsJson] as NotionTextProperty | undefined;\n const enrichmentSourceProp = props[PROPERTY_NAMES.enrichmentSource] as NotionTextProperty | undefined;\n const normalizedItems = extractNormalizedItems(normalizedItemsProp);\n const macros = extractMacros(props);\n const inferredEventType = inferEventType(food, normalizedItems);\n const inferredWindow = deriveEatingWindow(loggedAt);\n const date = extractDateInTimeZone(loggedAt);\n if (!date) return null;\n\n return {\n pageId: page.id,\n date,\n loggedAt,\n food,\n eventType: normalizeEventType(eventTypeProp?.select?.name) ?? inferredEventType,\n eatingWindow: normalizeEatingWindow(eatingWindowProp?.select?.name) ?? inferredWindow,\n normalizedItems,\n enrichmentConfidence: extractNumberProperty(props[PROPERTY_NAMES.enrichmentConfidence]),\n enrichmentSource: normalizeEnrichmentSource(extractRichTextValue(enrichmentSourceProp)),\n macros,\n };\n}\n\nexport function extractFoodName(\n prop: NotionTitleProperty | NotionTextProperty | undefined,\n): string | null {\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\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\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 !entry.normalizedItems.length ||\n entry.enrichmentConfidence === undefined\n );\n}\n\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\nexport function buildEntryProperties(\n entry: Entry,\n enrichment: {\n macros: Partial>;\n normalizedItems: NormalizedFoodItem[];\n confidence: number;\n source: EnrichmentSource;\n eventType?: EventType;\n eatingWindow?: EatingWindow;\n },\n): Record {\n const properties: Record = {};\n const missingMacros = Object.fromEntries(\n Object.entries(enrichment.macros).filter(([key]) => entry.macros[key as MacroKey] === undefined),\n ) as Partial>;\n\n Object.assign(properties, buildNutritionProperties(missingMacros));\n\n const eventType = enrichment.eventType ?? entry.eventType;\n const eatingWindow = enrichment.eatingWindow ?? entry.eatingWindow;\n properties[PROPERTY_NAMES.eventType] = { select: { name: eventType } };\n properties[PROPERTY_NAMES.eatingWindow] = { select: { name: eatingWindow } };\n properties[PROPERTY_NAMES.normalizedItemsJson] = {\n rich_text: [{ type: \"text\", text: { content: JSON.stringify(enrichment.normalizedItems) } }],\n };\n properties[PROPERTY_NAMES.enrichmentConfidence] = { number: enrichment.confidence };\n properties[PROPERTY_NAMES.enrichmentSource] = {\n rich_text: [{ type: \"text\", text: { content: enrichment.source } }],\n };\n return properties;\n}\n\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 const behaviorStats = calculateBehaviorStats(entries, dateRange);\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 daysWithOneEvent: behaviorStats.daysWithOneEvent,\n daysWithTwoEvents: behaviorStats.daysWithTwoEvents,\n daysWithThreePlusEvents: behaviorStats.daysWithThreePlusEvents,\n lateNightEntries: behaviorStats.lateNightEntries,\n snackEntries: behaviorStats.snackEntries,\n eatingWindowCounts: behaviorStats.eatingWindowCounts,\n avgFirstEventHour: behaviorStats.avgFirstEventHour,\n avgLastEventHour: behaviorStats.avgLastEventHour,\n avgDailyEatingSpanHours: behaviorStats.avgDailyEatingSpanHours,\n macroSummary,\n },\n runId: `food-${start}-${end}`,\n };\n}\n\nexport function roundNumber(value: number): number {\n return Number(value.toFixed(2));\n}\n\nexport function buildNutritionPrompt(food: string): string {\n return `Normalize and estimate macros for a food log entry: \"${food}\".`;\n}\n\nexport function safeParseJson(value: string): unknown {\n try {\n return JSON.parse(value);\n } catch {\n return null;\n }\n}\n\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(([, currentValue]) => typeof currentValue === \"number\" && Number.isFinite(currentValue)),\n ) as Partial>;\n}\n\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\nexport function deriveEatingWindow(loggedAt: string): EatingWindow {\n const hour = extractHourInTimeZone(loggedAt);\n if (hour >= 5 && hour <= 10) return \"morning\";\n if (hour >= 11 && hour <= 13) return \"midday\";\n if (hour >= 14 && hour <= 16) return \"afternoon\";\n if (hour >= 17 && hour <= 20) return \"evening\";\n return \"late_night\";\n}\n\nexport function inferEventType(food: string, items: NormalizedFoodItem[]): EventType {\n const sourceText = food.toLowerCase();\n if (/\\b(coffee|latte|tea|juice|smoothie|protein shake|soda|water)\\b/.test(sourceText)) return \"drink\";\n if (/\\b(snack|chips|trail mix|cookie|crackers|granola bar|yogurt|fruit|banana|apple)\\b/.test(sourceText)) {\n return \"snack\";\n }\n if (items.length === 1 && /\\b(espresso|coffee|tea|latte|juice|smoothie)\\b/.test(items[0].name.toLowerCase())) {\n return \"drink\";\n }\n if (items.length <= 2 && /\\b(handful|small|bar|cup|piece|slice)\\b/.test(sourceText)) return \"snack\";\n return \"meal\";\n}\n\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\nfunction calculateBehaviorStats(entries: Entry[], dateRange: string[]) {\n const perDay = new Map();\n for (const entry of entries) {\n const current = perDay.get(entry.date) ?? [];\n current.push(entry);\n perDay.set(entry.date, current);\n }\n\n let daysWithOneEvent = 0;\n let daysWithTwoEvents = 0;\n let daysWithThreePlusEvents = 0;\n let firstHourTotal = 0;\n let lastHourTotal = 0;\n let spanTotal = 0;\n let activeDays = 0;\n let lateNightEntries = 0;\n let snackEntries = 0;\n const eatingWindowCounts: Record = {\n morning: 0,\n midday: 0,\n afternoon: 0,\n evening: 0,\n late_night: 0,\n };\n\n for (const entry of entries) {\n if (entry.eventType === \"snack\") snackEntries += 1;\n if (entry.eatingWindow === \"late_night\") lateNightEntries += 1;\n eatingWindowCounts[entry.eatingWindow] += 1;\n }\n\n for (const date of dateRange) {\n const dayEntries = (perDay.get(date) ?? []).slice().sort((a, b) => a.loggedAt.localeCompare(b.loggedAt));\n const count = dayEntries.length;\n if (count === 1) daysWithOneEvent += 1;\n if (count === 2) daysWithTwoEvents += 1;\n if (count >= 3) daysWithThreePlusEvents += 1;\n if (!count) continue;\n activeDays += 1;\n const hours = dayEntries.map((entry) => extractHourFractionInTimeZone(entry.loggedAt)).filter(Number.isFinite);\n const firstHour = hours[0] ?? 0;\n const lastHour = hours[hours.length - 1] ?? firstHour;\n firstHourTotal += firstHour;\n lastHourTotal += lastHour;\n spanTotal += Math.max(0, lastHour - firstHour);\n }\n\n return {\n daysWithOneEvent,\n daysWithTwoEvents,\n daysWithThreePlusEvents,\n lateNightEntries,\n snackEntries,\n eatingWindowCounts,\n avgFirstEventHour: activeDays ? roundNumber(firstHourTotal / activeDays) : 0,\n avgLastEventHour: activeDays ? roundNumber(lastHourTotal / activeDays) : 0,\n avgDailyEatingSpanHours: activeDays ? roundNumber(spanTotal / activeDays) : 0,\n };\n}\n\nfunction extractNormalizedItems(prop: NotionTextProperty | undefined): NormalizedFoodItem[] {\n const value = extractRichTextValue(prop);\n if (!value) return [];\n const parsed = safeParseJson(value);\n if (!Array.isArray(parsed)) return [];\n return parsed.map(normalizeNormalizedItem).filter((item): item is NormalizedFoodItem => !!item);\n}\n\nfunction normalizeNormalizedItem(value: unknown): NormalizedFoodItem | null {\n if (!value || typeof value !== \"object\") return null;\n const record = value as Record;\n const name = typeof record.name === \"string\" ? record.name.trim() : \"\";\n if (!name) return null;\n const servings = sanitizeServings(coerceNumber(record.servings) ?? 1);\n const confidence = sanitizeConfidence(coerceNumber(record.confidence) ?? 0.5);\n const source = record.source === \"openai\" ? \"openai\" : \"heuristic\";\n const matchedName = typeof record.matchedName === \"string\" ? record.matchedName : undefined;\n const matchConfidence = record.matchConfidence === undefined\n ? undefined\n : sanitizeConfidence(coerceNumber(record.matchConfidence) ?? 0.5);\n const matchSource = record.matchSource === \"fatsecret_detail\" || record.matchSource === \"fatsecret_search\"\n ? record.matchSource\n : undefined;\n return { name, servings, confidence, source, matchedName, matchConfidence, matchSource };\n}\n\nfunction extractRichTextValue(prop: NotionTextProperty | undefined): string | null {\n if (!prop?.rich_text?.length) return null;\n const value = prop.rich_text.map((item) => item.plain_text).join(\"\").trim();\n return value || null;\n}\n\nfunction extractNumberProperty(value: unknown): number | undefined {\n const numeric = (value as NotionNumberProperty | undefined)?.number;\n return typeof numeric === \"number\" ? numeric : undefined;\n}\n\nfunction normalizeEventType(value?: string | null): EventType | null {\n if (value === \"meal\" || value === \"snack\" || value === \"drink\") return value;\n return null;\n}\n\nfunction normalizeEatingWindow(value?: string | null): EatingWindow | null {\n if (\n value === \"morning\" || value === \"midday\" || value === \"afternoon\" || value === \"evening\" ||\n value === \"late_night\"\n ) {\n return value;\n }\n return null;\n}\n\nfunction normalizeEnrichmentSource(value?: string | null): EnrichmentSource | undefined {\n if (\n value === \"heuristic\" || value === \"openai\" || value === \"fatsecret_detail\" || value === \"fatsecret_search\" ||\n value === \"manual\"\n ) {\n return value;\n }\n return undefined;\n}\n\nfunction extractHourInTimeZone(value: string): number {\n const parsed = new Date(value);\n if (Number.isNaN(parsed.getTime())) return 12;\n const formatter = new Intl.DateTimeFormat(\"en-US\", {\n timeZone: REPORT_TIMEZONE,\n hour: \"numeric\",\n hour12: false,\n });\n return Number(formatter.format(parsed));\n}\n\nfunction extractDateInTimeZone(value: string): string | null {\n const parsed = new Date(value);\n if (Number.isNaN(parsed.getTime())) return null;\n return formatDateInTimeZone(parsed, REPORT_TIMEZONE);\n}\n\nfunction extractHourFractionInTimeZone(value: string): number {\n const parsed = new Date(value);\n if (Number.isNaN(parsed.getTime())) return 0;\n const parts = new Intl.DateTimeFormat(\"en-US\", {\n timeZone: REPORT_TIMEZONE,\n hour: \"2-digit\",\n minute: \"2-digit\",\n hour12: false,\n }).formatToParts(parsed);\n const lookup = parts.reduce>((acc, part) => {\n acc[part.type] = part.value;\n return acc;\n }, {});\n const hour = Number(lookup.hour ?? \"0\");\n const minute = Number(lookup.minute ?? \"0\");\n return hour + (minute / 60);\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\nfunction sanitizeServings(value: number): number {\n if (!Number.isFinite(value) || value <= 0) return 1;\n return roundNumber(value);\n}\n\nfunction sanitizeConfidence(value: number): number {\n if (!Number.isFinite(value)) return 0.5;\n return roundNumber(Math.min(1, Math.max(0, 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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- `event type` (Select)\n- `eating window` (Select)\n- `normalized items json` (Text)\n- `enrichment confidence` (Number)\n- `enrichment source` (Text)\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 enrichment val will create/update the event metadata\nproperties automatically on the Notion database if they are missing.\nThe food val now treats each row as an eating event, stores normalized item JSON plus an enrichment confidence score,\nand uses a simpler enrichment flow: heuristic item parsing first, OpenAI only when needed, then a cached FatSecret lookup.\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\nvt create blood_sugar_live_dashboard\nvt create food_blood_sugar_correlation\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- `services/blood_sugar_live_dashboard.http.tsx`\n- `services/food_blood_sugar_correlation.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).\nThe blood sugar live dashboard val queries Notion in real time and shows all-time averages, AM/PM averages, and a consistency score across your full tracking history.\nThe food correlation dashboard val queries both Notion databases live and compares eating-event rhythm, late-night intake, and daily spread against blood sugar readings.\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- Blood sugar live dashboard is real time: each request re-reads the blood sugar Notion database and recalculates all-time stats.\n- Food correlation dashboard is real time: each request re-reads food and blood sugar entries from Notion and recalculates the correlation view.\n\n## Development\n\nRun tests:\n```\ndeno test --allow-import --allow-env=VAL_TOWN_API_KEY --reporter=dot\n```\n\nRun lint:\n```\ndeno lint\n```\n\nMade with 🖖 by Paul Chin Jr. and Markal.\n","label",[142],"65d27b16-fadf-11f0-bd8f-42dde27851f2","plan.md","ff57afba-f0c9-11f0-8caa-42dde27851f2",424,["D",1769449784132],12,"# 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? 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{ 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",[],[184,503],"b0c70922-1bcb-11f1-8ee7-42dde27851f2","notion_weekly_report.test.ts","46d7e2ba-f0ca-11f0-b918-42dde27851f2",651,["D",1773069708318],17,"import {\n buildAllTimeBloodSugarSummary,\n buildBadges,\n buildEncouragement,\n buildBloodSugarRollup,\n calculateMeasurementStats,\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 assertEquals(rollup.stats.morningAvg, 90);\n assertEquals(rollup.stats.eveningAvg, 100);\n assertEquals(rollup.stats.consistencyScore, 14);\n});\n\nDeno.test(\"calculateMeasurementStats tracks morning/evening averages and full-coverage days\", () => {\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: 110 },\n { date: \"2026-01-02\", createdTime: \"8:00 AM\", value: 100 },\n { date: \"2026-01-03\", createdTime: \"8:30 PM\", value: 120 },\n ];\n const stats = calculateMeasurementStats(entries, [\n \"2026-01-01\",\n \"2026-01-02\",\n \"2026-01-03\",\n ]);\n\n assertEquals(stats.morningAvg, 95);\n assertEquals(stats.eveningAvg, 115);\n assertEquals(stats.morningEntries, 2);\n assertEquals(stats.eveningEntries, 2);\n assertEquals(stats.fullyCoveredDays, 1);\n assertEquals(stats.consistencyScore, 33);\n});\n\nDeno.test(\"buildAllTimeBloodSugarSummary aggregates full-history blood sugar 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: 110 },\n { date: \"2026-01-03\", createdTime: \"8:00 AM\", value: 100 },\n { date: \"2026-01-03\", createdTime: \"8:00 PM\", value: 120 },\n { date: \"2026-01-04\", createdTime: \"8:00 AM\", value: 95 },\n ];\n\n const summary = buildAllTimeBloodSugarSummary(entries);\n\n assertEquals(summary.totalEntries, 5);\n assertEquals(summary.overallAvg, 103);\n assertEquals(summary.morningAvg, 95);\n assertEquals(summary.eveningAvg, 115);\n assertEquals(summary.firstMeasurementDate, \"2026-01-01\");\n assertEquals(summary.lastMeasurementDate, \"2026-01-04\");\n assertEquals(summary.trackedDays, 4);\n assertEquals(summary.activeDays, 3);\n assertEquals(summary.fullyCoveredDays, 2);\n assertEquals(summary.consistencyScore, 50);\n assertEquals(summary.currentStreak, 2);\n assertEquals(summary.min, 90);\n assertEquals(summary.max, 120);\n});\n",[],[184,511],"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",[],[184,520],"938a72fe-1bd5-11f1-a528-42dde27851f2","food_report.test.ts","e01ea7f2-f308-11f0-8ecb-42dde27851f2",665,["D",1773073954175],8,"import {\n buildEntryProperties,\n buildFoodRollup,\n buildNutritionPrompt,\n coerceMacros,\n coerceNumber,\n deriveEatingWindow,\n extractFoodName,\n extractMacros,\n inferEventType,\n parseEntry,\n PROPERTY_NAMES,\n roundNumber,\n safeParseJson,\n shouldEnrich,\n type Entry,\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 assertEquals(extractFoodName({ title: [{ plain_text: \"cheese omelette\" }] }), \"cheese omelette\");\n assertEquals(extractFoodName({ rich_text: [{ plain_text: \" tofu bowl \" }] }), \"tofu bowl\");\n assertEquals(extractFoodName(undefined), null);\n});\n\nDeno.test(\"parseEntry infers event metadata and parses stored normalized items\", () => {\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 and toast\" }] },\n [PROPERTY_NAMES.normalizedItemsJson]: {\n rich_text: [{\n plain_text:\n '[{\"name\":\"cheese omelette\",\"servings\":1,\"confidence\":0.8,\"source\":\"heuristic\"},{\"name\":\"toast\",\"servings\":1,\"confidence\":0.7,\"source\":\"heuristic\"}]',\n }],\n },\n [PROPERTY_NAMES.enrichmentConfidence]: { number: 0.76 },\n [PROPERTY_NAMES.enrichmentSource]: { rich_text: [{ plain_text: \"heuristic\" }] },\n [PROPERTY_NAMES.macros.calories]: { number: 320 },\n [PROPERTY_NAMES.macros.protein]: { number: 18 },\n [PROPERTY_NAMES.macros.carbs]: { number: null },\n },\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 and toast\");\n assertEquals(entry.eatingWindow, \"morning\");\n assertEquals(entry.eventType, \"meal\");\n assertEquals(entry.normalizedItems.length, 2);\n assertEquals(entry.enrichmentConfidence, 0.76);\n assertEquals(entry.enrichmentSource, \"heuristic\");\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 assertEquals(parseEntry(page), 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 core macros or event metadata 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 eventType: \"snack\",\n eatingWindow: \"morning\",\n normalizedItems: [{ name: \"toast\", servings: 1, confidence: 0.8, source: \"heuristic\" }],\n enrichmentConfidence: 0.8,\n enrichmentSource: \"heuristic\",\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 assertEquals(shouldEnrich({ ...base, normalizedItems: [] }), true);\n assertEquals(shouldEnrich({ ...base, enrichmentConfidence: undefined }), true);\n});\n\nDeno.test(\"buildEntryProperties only writes missing macros and event metadata\", () => {\n const entry: Entry = {\n pageId: \"page-4\",\n date: \"2026-01-16\",\n loggedAt: \"2026-01-16T23:30:00.000Z\",\n food: \"trail mix\",\n eventType: \"snack\",\n eatingWindow: \"late_night\",\n normalizedItems: [],\n macros: { calories: 200, protein: 6 },\n };\n\n const props = buildEntryProperties(entry, {\n macros: { calories: 240, protein: 6, carbs: 18, fat: 14 },\n normalizedItems: [{ name: \"trail mix\", servings: 1, confidence: 0.78, source: \"heuristic\" }],\n confidence: 0.78,\n source: \"heuristic\",\n });\n\n assertEquals(PROPERTY_NAMES.macros.calories in props, false);\n assertEquals(props[PROPERTY_NAMES.macros.carbs], { number: 18 });\n assertEquals(props[PROPERTY_NAMES.eventType], { select: { name: \"snack\" } });\n assertEquals(props[PROPERTY_NAMES.eatingWindow], { select: { name: \"late_night\" } });\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(\"deriveEatingWindow and inferEventType capture eating-event behavior\", () => {\n assertEquals(deriveEatingWindow(\"2026-01-16T12:30:00.000Z\"), \"morning\");\n assertEquals(deriveEatingWindow(\"2026-01-17T03:30:00.000Z\"), \"late_night\");\n assertEquals(inferEventType(\"coffee\", [{ name: \"coffee\", servings: 1, confidence: 0.9, source: \"heuristic\" }]), \"drink\");\n assertEquals(\n inferEventType(\"trail mix\", [{ name: \"trail mix\", servings: 1, confidence: 0.9, source: \"heuristic\" }]),\n \"snack\",\n );\n});\n\nDeno.test(\"roundNumber rounds to two decimals\", () => {\n assertEquals(roundNumber(3.14159), 3.14);\n});\n\nDeno.test(\"buildFoodRollup aggregates weekly behavior 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 eventType: \"meal\",\n eatingWindow: \"morning\",\n normalizedItems: [],\n macros: { calories: 100, protein: 4 },\n },\n {\n pageId: \"page-2\",\n date: \"2026-01-01\",\n loggedAt: \"2026-01-01T23:00:00.000Z\",\n food: \"chips\",\n eventType: \"snack\",\n eatingWindow: \"late_night\",\n normalizedItems: [],\n macros: { calories: 200, protein: 2 },\n },\n {\n pageId: \"page-3\",\n date: \"2026-01-02\",\n loggedAt: \"2026-01-02T17:00:00.000Z\",\n food: \"eggs\",\n eventType: \"meal\",\n eatingWindow: \"afternoon\",\n normalizedItems: [],\n macros: { calories: 200, protein: 12 },\n },\n ];\n\n const rollup = buildFoodRollup(entries, \"2026-01-01\", \"2026-01-07\");\n assertEquals(rollup.category, \"food\");\n assertEquals(rollup.stats.totalEntries, 3);\n assertEquals(rollup.stats.uniqueDays, 2);\n assertEquals(rollup.stats.entriesByDate[\"2026-01-01\"], 2);\n assertEquals(rollup.stats.entriesByDate[\"2026-01-02\"], 1);\n assertEquals(rollup.stats.daysWithOneEvent, 1);\n assertEquals(rollup.stats.daysWithTwoEvents, 1);\n assertEquals(rollup.stats.daysWithThreePlusEvents, 0);\n assertEquals(rollup.stats.lateNightEntries, 1);\n assertEquals(rollup.stats.snackEntries, 1);\n assertEquals(rollup.stats.eatingWindowCounts.late_night, 1);\n assertEquals(rollup.runId, \"food-2026-01-01-2026-01-07\");\n});\n",[],[184,528],"9370dcb8-1bd5-11f1-8854-42dde27851f2","food_correlation.test.ts","9370dd80-1bd5-11f1-8854-42dde27851f2",662,["D",1773073954037],"import { assertEquals } from \"https://deno.land/std@0.224.0/assert/mod.ts\";\nimport { buildFoodBloodSugarCorrelation } from \"../shared/food_correlation.ts\";\nimport type { Entry as FoodEntry } from \"../shared/food_enrich.ts\";\nimport type { Entry as BloodSugarEntry } from \"../shared/blood_sugar_logic.ts\";\n\nDeno.test(\"buildFoodBloodSugarCorrelation groups food rhythm against blood sugar\", () => {\n const foodEntries: FoodEntry[] = [\n {\n pageId: \"food-1\",\n date: \"2026-01-01\",\n loggedAt: \"2026-01-01T12:00:00.000Z\",\n food: \"eggs\",\n eventType: \"meal\",\n eatingWindow: \"morning\",\n normalizedItems: [],\n macros: {},\n },\n {\n pageId: \"food-2\",\n date: \"2026-01-01\",\n loggedAt: \"2026-01-02T03:00:00.000Z\",\n food: \"chips\",\n eventType: \"snack\",\n eatingWindow: \"late_night\",\n normalizedItems: [],\n macros: {},\n },\n {\n pageId: \"food-3\",\n date: \"2026-01-02\",\n loggedAt: \"2026-01-02T16:00:00.000Z\",\n food: \"salad\",\n eventType: \"meal\",\n eatingWindow: \"midday\",\n normalizedItems: [],\n macros: {},\n },\n ];\n\n const bloodSugarEntries: BloodSugarEntry[] = [\n { date: \"2026-01-01\", createdTime: \"8:00 AM\", value: 120 },\n { date: \"2026-01-01\", createdTime: \"8:00 PM\", value: 140 },\n { date: \"2026-01-02\", createdTime: \"7:00 AM\", value: 150 },\n { date: \"2026-01-02\", createdTime: \"7:00 PM\", value: 130 },\n { date: \"2026-01-03\", createdTime: \"7:00 AM\", value: 110 },\n ];\n\n const summary = buildFoodBloodSugarCorrelation(foodEntries, bloodSugarEntries);\n\n assertEquals(summary.totalFoodEvents, 3);\n assertEquals(summary.trackedDays, 2);\n assertEquals(summary.avgEventsPerTrackedDay, 1.5);\n assertEquals(summary.lateNightDays, 1);\n assertEquals(summary.nextMorningAfterLateNightAvg, 150);\n assertEquals(summary.nextMorningWithoutLateNightAvg, 110);\n assertEquals(summary.eventCountBuckets.find((bucket) => bucket.bucket === \"2\")?.avgSameDayBloodSugar, 130);\n assertEquals(summary.eventCountBuckets.find((bucket) => bucket.bucket === \"1\")?.avgSameDayBloodSugar, 140);\n});\n",[],[184,537],["D",1768588056443],[476,477,478,479,480],[184],"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",[],[191,548],"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 ${WEEKLY_ROLLUPS_TABLE}\n WHERE category = ?\n AND period_start >= ?\n AND period_end <= ?\n ORDER BY period_start ASC`,\n [category, start, end],\n );\n return result.rows;\n}\n",[],[191,556],["D",1768341095957],[473,474],[191],"46dda206-1bd9-11f1-b889-42dde27851f2","notion.ts","2dc9ba38-f23b-11f0-b902-42dde27851f2",680,["D",1773075543526],5,"export const NOTION_VERSION = \"2022-06-28\";\n\n// Minimal Notion types used by the collectors.\nexport type NotionRichText = { plain_text: string };\nexport type NotionDateProperty = { date: { start: string } | null };\nexport type NotionNumberProperty = { number: number | null };\nexport type NotionSelectProperty = { select: { name: string } | null };\nexport type NotionTextProperty = { rich_text: NotionRichText[] };\nexport type NotionCreatedTimeProperty = { created_time: string };\nexport type NotionTitleProperty = { title: NotionRichText[] };\n\nexport type NotionPage = {\n id: string;\n properties: Record;\n};\n\nexport type NotionQueryResponse = {\n results: NotionPage[];\n has_more: boolean;\n next_cursor: string | null;\n};\n\n// Fetch all pages from a Notion database (handles pagination).\nexport async function fetchNotionPages(\n databaseId: string,\n token: string,\n buildBody: (cursor?: string) => Record,\n): Promise {\n const url = `https://api.notion.com/v1/databases/${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} ${text}`);\n }\n}\n\n// Add or update Notion database properties used by the collectors.\nexport async function updateNotionDatabase(\n databaseId: string,\n token: string,\n properties: Record,\n): Promise {\n const url = `https://api.notion.com/v1/databases/${databaseId}`;\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 database 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",[],[197,568],"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",[],[197,577],"015d1506-1c7c-11f1-ae26-42dde27851f2",["D",1773145434937],[],[197,33],"936c5148-1bd5-11f1-a8de-42dde27851f2","food_correlation.ts","936c51f2-1bd5-11f1-a8de-42dde27851f2",661,["D",1773073954043],"import type { Entry as BloodSugarEntry } from \"./blood_sugar_logic.ts\";\nimport type { EatingWindow, Entry as FoodEntry } from \"./food_enrich.ts\";\nimport { roundNumber } from \"./food_enrich.ts\";\n\nexport type EventCountBucket = \"1\" | \"2\" | \"3\" | \"4+\";\n\nexport type CorrelationBucket = {\n bucket: EventCountBucket;\n days: number;\n avgSameDayBloodSugar: number;\n avgMorningBloodSugar: number;\n avgEveningBloodSugar: number;\n};\n\nexport type FoodBloodSugarCorrelation = {\n totalFoodEvents: number;\n trackedDays: number;\n avgEventsPerTrackedDay: number;\n lateNightDays: number;\n avgDailyEatingSpanHours: number;\n avgFirstEventHour: number;\n avgLastEventHour: number;\n eventCountBuckets: CorrelationBucket[];\n nextMorningAfterLateNightAvg: number;\n nextMorningWithoutLateNightAvg: number;\n sameDayEveningAvgAfterLateNight: number;\n sameDayEveningAvgWithoutLateNight: number;\n dailyRows: Array<{\n date: string;\n events: number;\n eventWindows: EatingWindow[];\n lateNight: boolean;\n firstEventHour: number;\n lastEventHour: number;\n eatingSpanHours: number;\n dayAvgBloodSugar: number;\n morningBloodSugar: number;\n eveningBloodSugar: number;\n nextMorningBloodSugar: number;\n }>;\n};\n\nexport function buildFoodBloodSugarCorrelation(\n foodEntries: FoodEntry[],\n bloodSugarEntries: BloodSugarEntry[],\n): FoodBloodSugarCorrelation {\n const foodByDate = new Map();\n const bloodSugarByDate = new Map();\n\n for (const entry of foodEntries) {\n const current = foodByDate.get(entry.date) ?? [];\n current.push(entry);\n foodByDate.set(entry.date, current);\n }\n\n for (const entry of bloodSugarEntries) {\n const current = bloodSugarByDate.get(entry.date) ?? [];\n current.push(entry);\n bloodSugarByDate.set(entry.date, current);\n }\n\n const dates = Array.from(foodByDate.keys()).sort();\n const dailyRows = dates.map((date) => {\n const events = (foodByDate.get(date) ?? []).slice().sort((a, b) => a.loggedAt.localeCompare(b.loggedAt));\n const bloodSugar = bloodSugarByDate.get(date) ?? [];\n const nextMorning = bloodSugarByDate.get(addDays(date, 1)) ?? [];\n const eventHours = events.map((entry) => extractHourFractionInTimeZone(entry.loggedAt));\n const lateNight = events.some((entry) => entry.eatingWindow === \"late_night\");\n\n return {\n date,\n events: events.length,\n eventWindows: Array.from(new Set(events.map((entry) => entry.eatingWindow))),\n lateNight,\n firstEventHour: eventHours.length ? roundNumber(eventHours[0]) : 0,\n lastEventHour: eventHours.length ? roundNumber(eventHours[eventHours.length - 1]) : 0,\n eatingSpanHours: eventHours.length ? roundNumber(eventHours[eventHours.length - 1] - eventHours[0]) : 0,\n dayAvgBloodSugar: average(bloodSugar.map((entry) => entry.value)),\n morningBloodSugar: average(filterBloodSugarByMeridiem(bloodSugar, \"AM\").map((entry) => entry.value)),\n eveningBloodSugar: average(filterBloodSugarByMeridiem(bloodSugar, \"PM\").map((entry) => entry.value)),\n nextMorningBloodSugar: average(filterBloodSugarByMeridiem(nextMorning, \"AM\").map((entry) => entry.value)),\n };\n });\n\n const lateNightDays = dailyRows.filter((row) => row.lateNight);\n const nonLateNightDays = dailyRows.filter((row) => !row.lateNight);\n\n return {\n totalFoodEvents: foodEntries.length,\n trackedDays: dailyRows.length,\n avgEventsPerTrackedDay: dailyRows.length ? roundNumber(foodEntries.length / dailyRows.length) : 0,\n lateNightDays: lateNightDays.length,\n avgDailyEatingSpanHours: average(dailyRows.map((row) => row.eatingSpanHours).filter((value) => value > 0)),\n avgFirstEventHour: average(dailyRows.map((row) => row.firstEventHour).filter((value) => value > 0)),\n avgLastEventHour: average(dailyRows.map((row) => row.lastEventHour).filter((value) => value > 0)),\n eventCountBuckets: buildEventCountBuckets(dailyRows),\n nextMorningAfterLateNightAvg: average(lateNightDays.map((row) => row.nextMorningBloodSugar).filter((value) => value > 0)),\n nextMorningWithoutLateNightAvg: average(\n nonLateNightDays.map((row) => row.nextMorningBloodSugar).filter((value) => value > 0),\n ),\n sameDayEveningAvgAfterLateNight: average(\n lateNightDays.map((row) => row.eveningBloodSugar).filter((value) => value > 0),\n ),\n sameDayEveningAvgWithoutLateNight: average(\n nonLateNightDays.map((row) => row.eveningBloodSugar).filter((value) => value > 0),\n ),\n dailyRows: dailyRows.sort((a, b) => b.date.localeCompare(a.date)),\n };\n}\n\nfunction buildEventCountBuckets(rows: FoodBloodSugarCorrelation[\"dailyRows\"]): CorrelationBucket[] {\n const buckets: EventCountBucket[] = [\"1\", \"2\", \"3\", \"4+\"];\n return buckets.map((bucket) => {\n const relevant = rows.filter((row) => bucketForCount(row.events) === bucket);\n return {\n bucket,\n days: relevant.length,\n avgSameDayBloodSugar: average(relevant.map((row) => row.dayAvgBloodSugar).filter((value) => value > 0)),\n avgMorningBloodSugar: average(relevant.map((row) => row.morningBloodSugar).filter((value) => value > 0)),\n avgEveningBloodSugar: average(relevant.map((row) => row.eveningBloodSugar).filter((value) => value > 0)),\n };\n });\n}\n\nfunction bucketForCount(count: number): EventCountBucket {\n if (count >= 4) return \"4+\";\n if (count === 3) return \"3\";\n if (count === 2) return \"2\";\n return \"1\";\n}\n\nfunction filterBloodSugarByMeridiem(entries: BloodSugarEntry[], meridiem: \"AM\" | \"PM\") {\n return entries.filter((entry) => entry.createdTime?.toUpperCase().includes(meridiem));\n}\n\nfunction average(values: number[]): number {\n if (!values.length) return 0;\n return roundNumber(values.reduce((sum, value) => sum + value, 0) / values.length);\n}\n\nfunction addDays(date: string, days: number): string {\n const cursor = new Date(`${date}T00:00:00Z`);\n cursor.setUTCDate(cursor.getUTCDate() + days);\n return cursor.toISOString().slice(0, 10);\n}\n\nfunction extractHourFractionInTimeZone(value: string): number {\n const parsed = new Date(value);\n if (Number.isNaN(parsed.getTime())) return 0;\n const parts = new Intl.DateTimeFormat(\"en-US\", {\n timeZone: \"America/New_York\",\n hour: \"2-digit\",\n minute: \"2-digit\",\n hour12: false,\n }).formatToParts(parsed);\n const lookup = parts.reduce>((acc, part) => {\n acc[part.type] = part.value;\n return acc;\n }, {});\n return Number(lookup.hour ?? \"0\") + (Number(lookup.minute ?? \"0\") / 60);\n}\n",[],[197,589],"3e22e566-1bd6-11f1-a463-42dde27851f2","fatsecret.ts","8ef372ba-f7ac-11f0-bbc1-42dde27851f2",674,["D",1773074240419],2,"import type { MacroKey } from \"./food_enrich.ts\";\nimport { roundNumber } from \"./food_enrich.ts\";\n\nexport type FatSecretConfig = {\n clientId: string;\n clientSecret: string;\n};\n\nexport type FoodMatch = {\n matchedName: string;\n macros: Partial>;\n confidence: number;\n source: \"fatsecret_detail\" | \"fatsecret_search\";\n};\n\nconst TOKEN_URL = \"https://oauth.fatsecret.com/connect/token\";\nconst SEARCH_URL = \"https://platform.fatsecret.com/rest/foods/search/v1\";\nconst FOOD_GET_URL = \"https://platform.fatsecret.com/rest/food/v2\";\n\nexport function getFatSecretConfig(): FatSecretConfig | null {\n const clientId = Deno.env.get(\"FATSECRET_CLIENT_ID\");\n const clientSecret = Deno.env.get(\"FATSECRET_CLIENT_SECRET\");\n if (!clientId || !clientSecret) return null;\n return { clientId, clientSecret };\n}\n\nexport async function requestAccessToken(config: FatSecretConfig): Promise {\n const body = new URLSearchParams({ grant_type: \"client_credentials\" });\n const basic = btoa(`${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} ${resp.statusText}`);\n }\n\n const payload = await resp.json() as Record;\n const token = payload.access_token;\n if (typeof token !== \"string\") {\n throw new Error(`FatSecret token response missing access_token.`);\n }\n return token;\n}\n\nexport async function fetchFoodMatch(term: string, token: string): Promise {\n const first = await searchFirstFood(term, token);\n if (!first) return null;\n\n if (first.foodId) {\n const detailed = await fetchFoodDetails(first.foodId, token);\n if (detailed && Object.keys(detailed).length) {\n return {\n matchedName: first.foodName,\n macros: detailed,\n confidence: 0.92,\n source: \"fatsecret_detail\",\n };\n }\n }\n\n const parsed = parseFoodDescription(first.description);\n if (!parsed || !Object.keys(parsed).length) return null;\n return {\n matchedName: first.foodName,\n macros: parsed,\n confidence: 0.72,\n source: \"fatsecret_search\",\n };\n}\n\nexport async function fetchFoodMacros(\n term: string,\n token: string,\n): Promise> | null> {\n const match = await fetchFoodMatch(term, token);\n return match?.macros ?? null;\n}\n\nexport function sumIfComplete(values: Array): number | undefined {\n if (!values.length) return undefined;\n if (values.some((value) => typeof value !== \"number\")) return undefined;\n const numericValues = values as number[];\n const total = numericValues.reduce((acc, value) => acc + value, 0);\n return roundNumber(total);\n}\n\nasync function searchFirstFood(\n term: string,\n token: string,\n): Promise<{ foodId: string | null; foodName: string; description?: string } | null> {\n const params = new URLSearchParams({\n search_expression: term,\n max_results: \"1\",\n format: \"json\",\n });\n const resp = await fetch(`${SEARCH_URL}?${params.toString()}`, {\n method: \"GET\",\n headers: { \"Authorization\": `Bearer ${token}` },\n });\n\n const text = await resp.text();\n if (!resp.ok) {\n throw new Error(`FatSecret search failed: ${resp.status} ${resp.statusText} ${text}`);\n }\n\n const payload = text ? JSON.parse(text) as Record : {};\n const foods = payload.foods as Record | undefined;\n const list = foods?.food;\n const first = Array.isArray(list) ? list[0] : list;\n if (!first || typeof first !== \"object\") return null;\n\n const food = first as Record;\n return {\n foodId: typeof food.food_id === \"string\" ? food.food_id : null,\n foodName: typeof food.food_name === \"string\" ? food.food_name : term,\n description: typeof food.food_description === \"string\" ? food.food_description : undefined,\n };\n}\n\nasync function fetchFoodDetails(foodId: string, token: string): Promise> | null> {\n const params = new URLSearchParams({\n food_id: foodId,\n format: \"json\",\n });\n const resp = await fetch(`${FOOD_GET_URL}?${params.toString()}`, {\n method: \"GET\",\n headers: { \"Authorization\": `Bearer ${token}` },\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\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 record = serving as Record;\n const macros: Partial> = {};\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): Partial> | 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 const macros: Partial> = {};\n if (caloriesMatch) macros.calories = roundNumber(Number(caloriesMatch[1]));\n if (proteinMatch) macros.protein = roundNumber(Number(proteinMatch[1]));\n if (carbsMatch) macros.carbs = roundNumber(Number(carbsMatch[1]));\n if (fatMatch) macros.fat = roundNumber(Number(fatMatch[1]));\n if (fiberMatch) macros.fiber = roundNumber(Number(fiberMatch[1]));\n if (sugarMatch) macros.sugar = roundNumber(Number(sugarMatch[1]));\n if (sodiumMatch) macros.sodium = roundNumber(Number(sodiumMatch[1]));\n return Object.keys(macros).length ? macros : null;\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",[],[197,597],"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",[],[197,606],"b0b2c66a-1bcb-11f1-8ee7-42dde27851f2","blood_sugar_logic.ts","e6a27e5e-f309-11f0-8d21-42dde27851f2",650,["D",1773069708182],13,"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 morningAvg: number;\n eveningAvg: number;\n min: number;\n max: number;\n morningEntries: number;\n eveningEntries: number;\n fullyCoveredDays: number;\n consistencyScore: 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\nexport type AllTimeBloodSugarSummary = {\n totalEntries: number;\n overallAvg: number;\n morningAvg: number;\n eveningAvg: number;\n min: number;\n max: number;\n firstMeasurementDate: string | null;\n lastMeasurementDate: string | null;\n trackedDays: number;\n activeDays: number;\n fullyCoveredDays: number;\n consistencyScore: number;\n currentStreak: number;\n entriesByDate: Record;\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 measurementStats = calculateMeasurementStats(entries, dateRange);\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 morningAvg: measurementStats.morningAvg,\n eveningAvg: measurementStats.eveningAvg,\n min,\n max,\n morningEntries: measurementStats.morningEntries,\n eveningEntries: measurementStats.eveningEntries,\n fullyCoveredDays: measurementStats.fullyCoveredDays,\n consistencyScore: measurementStats.consistencyScore,\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\nexport function calculateMeasurementStats(entries: Entry[], dateRange: string[]) {\n const morningValues: number[] = [];\n const eveningValues: number[] = [];\n const coverageByDate: Record = {};\n\n for (const date of dateRange) {\n coverageByDate[date] = { am: false, pm: false };\n }\n\n for (const entry of entries) {\n const meridiem = getMeridiem(entry.createdTime);\n if (meridiem === \"AM\") {\n morningValues.push(entry.value);\n coverageByDate[entry.date] ??= { am: false, pm: false };\n coverageByDate[entry.date].am = true;\n } else if (meridiem === \"PM\") {\n eveningValues.push(entry.value);\n coverageByDate[entry.date] ??= { am: false, pm: false };\n coverageByDate[entry.date].pm = true;\n }\n }\n\n const fullyCoveredDays = dateRange.filter((date) => coverageByDate[date]?.am && coverageByDate[date]?.pm).length;\n const consistencyScore = dateRange.length ? Math.round((fullyCoveredDays / dateRange.length) * 100) : 0;\n\n return {\n morningAvg: averageValues(morningValues),\n eveningAvg: averageValues(eveningValues),\n morningEntries: morningValues.length,\n eveningEntries: eveningValues.length,\n fullyCoveredDays,\n consistencyScore,\n };\n}\n\nexport function buildAllTimeBloodSugarSummary(entries: Entry[]): AllTimeBloodSugarSummary {\n if (!entries.length) {\n return {\n totalEntries: 0,\n overallAvg: 0,\n morningAvg: 0,\n eveningAvg: 0,\n min: 0,\n max: 0,\n firstMeasurementDate: null,\n lastMeasurementDate: null,\n trackedDays: 0,\n activeDays: 0,\n fullyCoveredDays: 0,\n consistencyScore: 0,\n currentStreak: 0,\n entriesByDate: {},\n };\n }\n\n const sorted = [...entries].sort(compareEntriesChronologically);\n const firstMeasurementDate = sorted[0].date;\n const lastMeasurementDate = sorted[sorted.length - 1].date;\n const dateRange = listDateRange(firstMeasurementDate, lastMeasurementDate);\n const values = sorted.map((entry) => entry.value);\n const entriesByDate = countEntriesByDate(sorted);\n const measurementStats = calculateMeasurementStats(sorted, dateRange);\n const activeDays = Object.keys(entriesByDate).length;\n\n return {\n totalEntries: sorted.length,\n overallAvg: averageValues(values),\n morningAvg: measurementStats.morningAvg,\n eveningAvg: measurementStats.eveningAvg,\n min: Math.min(...values),\n max: Math.max(...values),\n firstMeasurementDate,\n lastMeasurementDate,\n trackedDays: dateRange.length,\n activeDays,\n fullyCoveredDays: measurementStats.fullyCoveredDays,\n consistencyScore: measurementStats.consistencyScore,\n currentStreak: calculateCurrentStreak(dateRange, entriesByDate),\n entriesByDate,\n };\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: ${second}`;\n}\n\n// Type guard for Notion created_time fields.\nexport function isCreatedTimeProperty(value: unknown): value is NotionCreatedTimeProperty {\n return (\n !!value &&\n typeof value === \"object\" &&\n \"created_time\" in value &&\n typeof (value as { created_time?: unknown }).created_time === \"string\"\n );\n}\n\n// Type guard for Notion rich_text fields.\nexport function isTextProperty(value: unknown): value is NotionTextProperty {\n return (\n !!value &&\n typeof value === \"object\" &&\n \"rich_text\" in value &&\n Array.isArray((value as { rich_text?: unknown }).rich_text)\n );\n}\n\n// Extract AM/PM from a time string if possible.\nfunction getMeridiem(value: string | null): \"AM\" | \"PM\" | null {\n if (!value) return null;\n const match = value.match(/\\b(AM|PM)\\b/i);\n if (!match) return null;\n return match[1].toUpperCase() as \"AM\" | \"PM\";\n}\n\nfunction averageValues(values: number[]): number {\n if (!values.length) return 0;\n return Math.round((values.reduce((sum, value) => sum + value, 0) / values.length) * 10) / 10;\n}\n\nfunction compareEntriesChronologically(a: Entry, b: Entry): number {\n if (a.date !== b.date) return a.date.localeCompare(b.date);\n const aMinutes = parseTimeToMinutes(a.createdTime);\n const bMinutes = parseTimeToMinutes(b.createdTime);\n if (aMinutes === null && bMinutes === null) return 0;\n if (aMinutes === null) return 1;\n if (bMinutes === null) return -1;\n return aMinutes - bMinutes;\n}\n\n// Pick the first two readings (with an overflow indicator).\nfunction formatFirstSecondText(group: GroupedEntries): [string, string] {\n const ordered = orderEntries(group);\n if (!ordered.length) return [\"—\", \"—\"];\n const first = String(ordered[0].value);\n if (ordered.length === 1) return [first, \"—\"];\n const secondValue = String(ordered[1].value);\n const overflow = ordered.length > 2 ? ` (+${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",[],[197,614],["D",1768499629303],[465,466,467,468,469,470,471],[197],"2d1a4f62-f23b-11f0-a85a-42dde27851f2","weekly_rollup_persist.http.tsx","f84d1afa-f233-11f0-9eff-42dde27851f2",190,["D",1768499642189],"http","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",[],[203,626],"d9eced62-1bd5-11f1-bb7b-42dde27851f2","monthly_report_page.http.tsx","044f06e4-f31d-11f0-b40c-42dde27851f2",672,["D",1773074072318],24,"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 const allMeasurementsHref = \"https://pchinjr--dac9688c1bcb11f1855242dde27851f2.web.val.run\";\n const foodCorrelationHref = \"https://pchinjr--9367c0a61bd511f1a76c42dde27851f2.web.val.run\";\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 Open the live all-measurements blood sugar dashboard.\n {\" \"}\n Open the live food and blood sugar correlation dashboard.\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",[],[203,635],"9367bfca-1bd5-11f1-a76c-42dde27851f2","food_blood_sugar_correlation.http.tsx","9367c0a6-1bd5-11f1-a76c-42dde27851f2",660,["D",1773073954012],"import React from \"https://esm.sh/react@18.2.0\";\nimport { renderToString } from \"https://esm.sh/react-dom@18.2.0/server\";\nimport { fetchNotionPages, type NotionPage } from \"../shared/notion.ts\";\nimport {\n parseEntry as parseBloodSugarEntry,\n type BloodSugarNotionPage,\n type Entry as BloodSugarEntry,\n} from \"../shared/blood_sugar_logic.ts\";\nimport { buildFoodBloodSugarCorrelation } from \"../shared/food_correlation.ts\";\nimport { parseEntry as parseFoodEntry, type Entry as FoodEntry } from \"../shared/food_enrich.ts\";\n\ntype NotionConfig = {\n token: string;\n foodDatabaseId: string;\n bloodSugarDatabaseId: string;\n};\n\nexport default async function handler(req: Request): Promise {\n const notionConfig = getNotionConfig();\n if (!notionConfig) {\n return new Response(\"Missing required secrets.\", { status: 500 });\n }\n\n const [foodEntries, bloodSugarEntries] = await Promise.all([\n fetchAllFoodEntries(notionConfig),\n fetchAllBloodSugarEntries(notionConfig),\n ]);\n const correlation = buildFoodBloodSugarCorrelation(foodEntries, bloodSugarEntries);\n const html = renderToString(\n ,\n );\n\n return new Response(`${html}`, {\n headers: { \"Content-Type\": \"text/html; charset=utf-8\" },\n });\n}\n\nfunction getNotionConfig(): NotionConfig | null {\n const token = Deno.env.get(\"NOTION_TOKEN\");\n const foodDatabaseId = Deno.env.get(\"NOTION_FOOD_DB_ID\");\n const bloodSugarDatabaseId = Deno.env.get(\"NOTION_BLOOD_SUGAR_DB_ID\");\n if (!token || !foodDatabaseId || !bloodSugarDatabaseId) return null;\n return { token, foodDatabaseId, bloodSugarDatabaseId };\n}\n\nasync function fetchAllFoodEntries(config: NotionConfig): Promise {\n const pages = await fetchNotionPages(config.foodDatabaseId, config.token, (cursor) => ({\n sorts: [{ property: \"Created time\", direction: \"ascending\" }],\n ...(cursor ? { start_cursor: cursor } : {}),\n }));\n return pages.map(parseFoodEntry).filter((entry): entry is FoodEntry => !!entry);\n}\n\nasync function fetchAllBloodSugarEntries(config: NotionConfig): Promise {\n const pages = await fetchNotionPages(config.bloodSugarDatabaseId, config.token, (cursor) => ({\n sorts: [{ property: \"Created time\", direction: \"ascending\" }],\n ...(cursor ? { start_cursor: cursor } : {}),\n }));\n return pages.map(parseBloodSugarEntry).filter((entry): entry is BloodSugarEntry => !!entry);\n}\n\nfunction CorrelationPage(props: {\n correlation: ReturnType;\n refreshedAt: string;\n url: URL;\n}) {\n const { correlation, refreshedAt, url } = props;\n return (\n \n \n \n \n Food and Blood Sugar Correlation\n \n \n \n

Food Rhythm and Blood Sugar

\n This live view treats each food entry as an eating event and compares eating frequency,\n late-night intake, and daily spread against your blood sugar readings.\n

\n Food events: {correlation.totalFoodEvents}\n Tracked days: {correlation.trackedDays}\n Refreshed: {formatTimestamp(refreshedAt)}\n URL: {url.pathname}\n

\n\n

\n Avg Events / Day\n {correlation.avgEventsPerTrackedDay}\n

\n Late-Night Days\n {correlation.lateNightDays}\n

\n Avg First Event\n {formatHour(correlation.avgFirstEventHour)}\n

\n Avg Last Event\n {formatHour(correlation.avgLastEventHour)}\n

\n Avg Eating Span\n {correlation.avgDailyEatingSpanHours}h\n

\n Next Morning After Late Night\n {renderBloodSugar(correlation.nextMorningAfterLateNightAvg)}\n

\n\n

Event Count vs Blood Sugar

\n \n \n \n \n \n \n \n \n \n \n \n {correlation.eventCountBuckets.map((bucket) => (\n \n \n \n \n \n \n \n ))}\n \n

Events / Day	Days	Same-Day Avg	Morning Avg	Evening Avg
{bucket.bucket}	{bucket.days}	{renderBloodSugar(bucket.avgSameDayBloodSugar)}	{renderBloodSugar(bucket.avgMorningBloodSugar)}	{renderBloodSugar(bucket.avgEveningBloodSugar)}

\n\n

Late-Night Effect

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

Next-morning average after late-night days	{renderBloodSugar(correlation.nextMorningAfterLateNightAvg)}
Next-morning average without late-night days	{renderBloodSugar(correlation.nextMorningWithoutLateNightAvg)}
Same-day evening average on late-night days	{renderBloodSugar(correlation.sameDayEveningAvgAfterLateNight)}
Same-day evening average without late-night days	{renderBloodSugar(correlation.sameDayEveningAvgWithoutLateNight)}

\n\n

Daily Correlation

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n {correlation.dailyRows.slice(0, 45).map((row) => (\n \n \n \n \n \n \n \n \n \n \n \n \n ))}\n \n

Date	Events	Windows	First	Last	Span	Same-Day Avg	AM	PM	Next AM
{row.date}	{row.events}	\n {row.eventWindows.join(\", \")}\n	{formatHour(row.firstEventHour)}	{formatHour(row.lastEventHour)}	{row.eatingSpanHours ? `${row.eatingSpanHours}h` : \"—\"}	{renderBloodSugar(row.dayAvgBloodSugar)}	{renderBloodSugar(row.morningBloodSugar)}	{renderBloodSugar(row.eveningBloodSugar)}	{renderBloodSugar(row.nextMorningBloodSugar)}

\n \n \n );\n}\n\nfunction renderBloodSugar(value: number): string {\n return value > 0 ? String(value) : \"—\";\n}\n\nfunction formatTimestamp(value: string): string {\n const date = new Date(value);\n if (Number.isNaN(date.getTime())) return value;\n return date.toLocaleString(\"en-US\", {\n month: \"short\",\n day: \"numeric\",\n year: \"numeric\",\n hour: \"numeric\",\n minute: \"2-digit\",\n });\n}\n\nfunction formatHour(value: number): string {\n if (!value) return \"—\";\n const hour = Math.floor(value);\n const minute = Math.round((value - hour) * 60);\n const date = new Date(Date.UTC(2026, 0, 1, hour, minute));\n return date.toLocaleTimeString(\"en-US\", {\n hour: \"numeric\",\n minute: \"2-digit\",\n hour12: true,\n timeZone: \"UTC\",\n });\n}\n",[],[203,644],"dac967c4-1bcb-11f1-8552-42dde27851f2","blood_sugar_live_dashboard.http.tsx","dac9688c-1bcb-11f1-8552-42dde27851f2",653,["D",1773069778804],"import React from \"https://esm.sh/react@18.2.0\";\nimport { renderToString } from \"https://esm.sh/react-dom@18.2.0/server\";\nimport { fetchNotionPages } from \"../shared/notion.ts\";\nimport {\n buildAllTimeBloodSugarSummary,\n parseEntry,\n type BloodSugarNotionPage,\n type Entry,\n} from \"../shared/blood_sugar_logic.ts\";\n\ntype NotionConfig = {\n token: string;\n databaseId: string;\n};\n\nexport default async function handler(req: Request): Promise {\n const notionConfig = getNotionConfig();\n if (!notionConfig) {\n return new Response(\"Missing required secrets.\", { status: 500 });\n }\n\n const entries = await fetchAllEntries(notionConfig);\n const summary = buildAllTimeBloodSugarSummary(entries);\n const html = renderToString(\n ,\n );\n\n return new Response(`${html}`, {\n headers: { \"Content-Type\": \"text/html; charset=utf-8\" },\n });\n}\n\nfunction getNotionConfig(): NotionConfig | null {\n const token = Deno.env.get(\"NOTION_TOKEN\");\n const databaseId = Deno.env.get(\"NOTION_BLOOD_SUGAR_DB_ID\");\n if (!token || !databaseId) return null;\n return { token, databaseId };\n}\n\nasync function fetchAllEntries(config: NotionConfig): Promise {\n const pages = await fetchNotionPages(config.databaseId, config.token, (cursor) => ({\n sorts: [{ property: \"Created time\", 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 return entries;\n}\n\nfunction DashboardPage(props: {\n summary: ReturnType;\n recentEntries: Entry[];\n refreshedAt: string;\n url: URL;\n}) {\n const { summary, recentEntries, refreshedAt, url } = props;\n return (\n \n \n \n \n Blood Sugar Live Dashboard\n \n \n \n

All Measurements Blood Sugar Dashboard

\n Live view from Notion. This page recalculates from your full blood sugar database on every request.\n

Updated: {formatTimestamp(refreshedAt)}

Source: Notion database

\n Refresh\n

\n\n {summary.totalEntries === 0 ? : (\n <>\n

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

\n\n

Recent Measurements

\n \n \n \n \n \n \n \n \n \n {recentEntries.map((entry, index) => (\n \n \n \n \n \n ))}\n \n

Date	Time	Value
{entry.date}	{entry.createdTime ?? \"Unknown\"}	{entry.value}

How Consistency Works

\n Consistency measures how often you logged both a morning and an evening reading across the full span\n of your tracking history.\n

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

First Reading	{summary.firstMeasurementDate}
Latest Reading	{summary.lastMeasurementDate}
Tracked Days	{summary.trackedDays}
Fully Covered Days	{summary.fullyCoveredDays}
Active Days	{summary.activeDays}

\n \n )}\n

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

{props.label}

{props.value}

{props.detail}

\n );\n}\n\nfunction EmptyState() {\n return (\n

\n No blood sugar measurements were found in Notion.\n

\n );\n}\n\nfunction sortEntriesDesc(a: Entry, b: Entry): number {\n if (a.date !== b.date) return b.date.localeCompare(a.date);\n return compareTimesDesc(a.createdTime, b.createdTime);\n}\n\nfunction compareTimesDesc(a: string | null, b: string | null): number {\n const aMinutes = parseTimeToMinutes(a);\n const bMinutes = parseTimeToMinutes(b);\n if (aMinutes === null && bMinutes === null) return 0;\n if (aMinutes === null) return 1;\n if (bMinutes === null) return -1;\n return bMinutes - aMinutes;\n}\n\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\nfunction formatTimestamp(value: string): string {\n return new Date(value).toLocaleString(\"en-US\", {\n dateStyle: \"medium\",\n timeStyle: \"short\",\n timeZone: \"America/New_York\",\n });\n}\n",[],[203,652],["D",1768499628695],[460,461,462,463],[203],"46d29514-1bd9-11f1-b7d4-42dde27851f2","food_report.cron.tsx","f851115a-f233-11f0-a807-42dde27851f2",679,["D",1773075543511],44,"interval","import { getWeeklyRange } from \"../shared/date.ts\";\nimport { OpenAI } from \"https://esm.town/v/std/openai\";\nimport { fetchNotionPages, type NotionPage, updateNotionDatabase, updateNotionPage } from \"../shared/notion.ts\";\nimport { fetchFoodMatch, getFatSecretConfig, requestAccessToken, sumIfComplete, type FoodMatch } from \"../shared/fatsecret.ts\";\nimport {\n buildEntryProperties,\n buildFoodRollup,\n type EatingWindow,\n type Entry,\n FOOD_SCHEMA_PROPERTIES,\n inferEventType,\n type MacroKey,\n type NormalizedFoodItem,\n parseEntry,\n PROPERTY_NAMES,\n roundNumber,\n safeParseJson,\n shouldEnrich,\n deriveEatingWindow,\n} from \"../shared/food_enrich.ts\";\nimport { initRollupSchema, upsertWeeklyRollup } from \"../storage/rollups.ts\";\n\ntype NotionConfig = {\n token: string;\n databaseId: string;\n};\n\ntype EnrichmentResult = {\n macros: Partial>;\n normalizedItems: NormalizedFoodItem[];\n confidence: number;\n source: \"heuristic\" | \"openai\";\n eventType: Entry[\"eventType\"];\n eatingWindow: EatingWindow;\n};\n\nconst CORE_MACROS: MacroKey[] = [\"calories\", \"protein\", \"carbs\", \"fat\"];\nconst SUM_MACROS: MacroKey[] = [\"calories\", \"protein\", \"carbs\", \"fat\", \"fiber\", \"sugar\", \"sodium\"];\nconst ENRICHMENT_CONCURRENCY = 4;\nconst PROTECTED_PHRASES = [\n \"mac and cheese\",\n \"fish and chips\",\n \"cookies and cream\",\n \"chicken and waffles\",\n \"peanut butter and jelly\",\n \"pb&j\",\n];\n\nexport default async function () {\n try {\n const notionConfig = getNotionConfig();\n if (!notionConfig) {\n return new Response(\"Missing Notion secrets.\", { status: 500 });\n }\n\n console.log(\"Ensuring food schema properties\");\n await updateNotionDatabase(notionConfig.databaseId, notionConfig.token, FOOD_SCHEMA_PROPERTIES);\n\n const openai = new OpenAI();\n const fatSecretConfig = getFatSecretConfig();\n const fatSecretToken = fatSecretConfig ? await requestAccessToken(fatSecretConfig) : null;\n const { start, end } = getWeeklyRange();\n const entries = await fetchWeeklyEntries(start, end, notionConfig);\n const foodCache = new Map();\n\n let enriched = 0;\n await mapWithConcurrency(\n entries,\n ENRICHMENT_CONCURRENCY,\n async (entry) => {\n if (!shouldEnrich(entry)) return;\n if (!entry.food || entry.food === \"Unknown\") return;\n const enrichment = await fetchNutrition(entry, openai, fatSecretToken, foodCache);\n if (!enrichment) return;\n const properties = buildEntryProperties(entry, enrichment);\n if (!Object.keys(properties).length) return;\n console.log(\"Updating food entry\", { pageId: entry.pageId, food: entry.food });\n await updateNotionPage(entry.pageId, notionConfig.token, properties);\n entry.eventType = enrichment.eventType;\n entry.eatingWindow = enrichment.eatingWindow;\n entry.normalizedItems = enrichment.normalizedItems;\n entry.enrichmentConfidence = enrichment.confidence;\n entry.enrichmentSource = enrichment.source;\n entry.macros = { ...entry.macros, ...enrichment.macros };\n enriched += 1;\n },\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 } catch (error) {\n console.error(\"Food collector failed\", error instanceof Error ? error.stack ?? error.message : String(error));\n return new Response(\"Food collector failed.\", { status: 500 });\n }\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 fetchWeeklyEntries(start: string, end: string, config: NotionConfig): Promise {\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 return entries;\n}\n\nasync function fetchNutrition(\n entry: Entry,\n openai: OpenAI,\n token: string | null,\n cache: Map,\n): Promise {\n const normalized = entry.normalizedItems.length\n ? {\n items: entry.normalizedItems,\n source: entry.enrichmentSource === \"openai\" ? \"openai\" as const : \"heuristic\" as const,\n confidence: entry.enrichmentConfidence ?? averageConfidence(entry.normalizedItems.map((item) => item.confidence)),\n }\n : await normalizeFoodItems(entry.food, openai);\n\n const normalizedItems = normalized.items.map((item) => ({ ...item }));\n const macros = token ? await fetchFatSecretTotals(normalizedItems, entry.food, token, cache) : {};\n const itemConfidence = averageConfidence(normalizedItems.map((item) => item.matchConfidence ?? item.confidence));\n const confidence = roundNumber((normalized.confidence + itemConfidence) / 2);\n return {\n macros,\n normalizedItems,\n confidence,\n source: normalized.source,\n eventType: inferEventType(entry.food, normalizedItems),\n eatingWindow: deriveEatingWindow(entry.loggedAt),\n };\n}\n\nasync function normalizeFoodItems(\n foodName: string,\n openai: OpenAI,\n): Promise<{ items: NormalizedFoodItem[]; source: \"heuristic\" | \"openai\"; confidence: number }> {\n const heuristicItems = heuristicParseFoodItems(foodName);\n if (heuristicItems.length) {\n const confidence = averageConfidence(heuristicItems.map((item) => item.confidence));\n return { items: heuristicItems, source: \"heuristic\", confidence };\n }\n\n const completion = await openai.chat.completions.create({\n model: \"gpt-5-nano\",\n messages: [\n {\n role: \"system\",\n content:\n \"Normalize one food log entry into JSON only. \" +\n \"Return {\\\"items\\\":[{\\\"name\\\":\\\"...\\\",\\\"servings\\\":1,\\\"confidence\\\":0.8}]}. \" +\n \"Use short food names, keep branded or restaurant context when present, and do not invent sides.\",\n },\n {\n role: \"user\",\n content: `Food entry: \"${foodName}\".`,\n },\n ],\n max_tokens: 180,\n });\n\n const text = completion.choices[0]?.message?.content?.trim();\n const parsed = text ? safeParseJson(text) : null;\n const parsedItems = parsed && typeof parsed === \"object\" ? (parsed as { items?: unknown }).items : undefined;\n const items = Array.isArray(parsedItems)\n ? parsedItems.map(coerceFoodItem).filter((item): item is NormalizedFoodItem => !!item)\n : [];\n\n if (!items.length) {\n return {\n items: [{ name: foodName.trim(), servings: 1, confidence: 0.45, source: \"heuristic\" }],\n source: \"heuristic\",\n confidence: 0.45,\n };\n }\n\n return {\n items,\n source: \"openai\",\n confidence: averageConfidence(items.map((item) => item.confidence)),\n };\n}\n\nasync function fetchFatSecretTotals(\n items: NormalizedFoodItem[],\n original: string,\n token: string,\n cache: Map,\n): Promise>> {\n const components = await Promise.all(items.map(async (item) => {\n const match = await fetchCachedFoodMatch(item.name, token, cache);\n if (!match) return null;\n item.matchedName = match.matchedName;\n item.matchConfidence = match.confidence;\n item.matchSource = match.source;\n return scaleMacros(match.macros, item.servings);\n }));\n\n const totals = sumComponentMacros(components);\n if (totals && hasCoreMacros(totals)) return totals;\n\n const fallback = await fetchCachedFoodMatch(original, token, cache);\n if (!fallback) return {};\n return fallback.macros;\n}\n\nasync function fetchCachedFoodMatch(\n term: string,\n token: string,\n cache: Map,\n): Promise {\n const key = term.trim().toLowerCase();\n if (cache.has(key)) return cache.get(key) ?? null;\n const result = await fetchFoodMatch(term, token);\n cache.set(key, result);\n return result;\n}\n\nfunction heuristicParseFoodItems(foodName: string): NormalizedFoodItem[] {\n const text = foodName.trim();\n if (!text) return [];\n const lower = text.toLowerCase();\n if (PROTECTED_PHRASES.some((phrase) => lower.includes(phrase))) {\n return [{ name: text, servings: 1, confidence: 0.82, source: \"heuristic\" }];\n }\n\n const normalized = lower\n .replace(/\\s+w\\//g, \", \")\n .replace(/\\s+with\\s+/g, \", \")\n .replace(/\\s+\\+\\s+/g, \", \")\n .replace(/\\s+&\\s+/g, \", \")\n .replace(/\\s+and\\s+/g, \", \");\n\n const parts = normalized\n .split(\",\")\n .map((item) => item.trim())\n .filter(Boolean);\n\n if (!parts.length) return [];\n if (parts.length === 1) {\n return [{ name: cleanFoodItem(parts[0]), servings: inferServings(parts[0]), confidence: 0.86, source: \"heuristic\" }];\n }\n\n return parts\n .map((part) => ({\n name: cleanFoodItem(part),\n servings: inferServings(part),\n confidence: 0.7,\n source: \"heuristic\" as const,\n }))\n .filter((item) => item.name.length > 0);\n}\n\nfunction coerceFoodItem(item: unknown): NormalizedFoodItem | null {\n if (!item || typeof item !== \"object\") return null;\n const record = item as Record;\n const name = typeof record.name === \"string\" ? cleanFoodItem(record.name) : \"\";\n if (!name) return null;\n return {\n name,\n servings: inferServings(typeof record.servings === \"number\" ? String(record.servings) : String(record.servings ?? \"1\")),\n confidence: sanitizeConfidence(record.confidence),\n source: \"openai\",\n };\n}\n\nfunction inferServings(value: string): number {\n const explicit = value.match(/(\\d+(?:\\.\\d+)?)/);\n if (!explicit) return 1;\n const parsed = Number(explicit[1]);\n if (!Number.isFinite(parsed) || parsed <= 0) return 1;\n if (parsed > 6) return 1;\n return roundNumber(parsed);\n}\n\nfunction cleanFoodItem(value: string): string {\n return value.replace(/^\\d+(?:\\.\\d+)?\\s*/, \"\").trim();\n}\n\nfunction sanitizeConfidence(value: unknown): number {\n const numeric = typeof value === \"number\" ? value : Number(String(value ?? \"\").trim());\n if (!Number.isFinite(numeric)) return 0.75;\n return roundNumber(Math.min(1, Math.max(0, numeric)));\n}\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 || components.every((component) => component === null)) return null;\n const complete = components.filter((component): component is Partial> => !!component);\n const totals: Partial> = {};\n for (const key of SUM_MACROS) {\n const value = sumIfComplete(complete.map((entry) => entry[key]));\n if (value !== undefined) totals[key] = value;\n }\n return totals;\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\nfunction averageConfidence(values: number[]): number {\n if (!values.length) return 0.5;\n return roundNumber(values.reduce((sum, value) => sum + value, 0) / values.length);\n}\n\nasync function mapWithConcurrency(\n items: T[],\n concurrency: number,\n iteratee: (item: T, index: number) => Promise,\n): Promise {\n let index = 0;\n const workers = Array.from({ length: Math.max(1, Math.min(concurrency, items.length || 1)) }, async () => {\n while (index < items.length) {\n const currentIndex = index;\n index += 1;\n await iteratee(items[currentIndex], currentIndex);\n }\n });\n await Promise.all(workers);\n}\n",[],[209,663],"b08b81ea-1bcb-11f1-bf7e-42dde27851f2","blood_sugar_report.cron.tsx","905c839c-f0bf-11f0-b356-42dde27851f2",649,["D",1773069707922],59,"import { email } from \"https://esm.town/v/std/email\";\nimport { getWeeklyRange, listDateRange } from \"../shared/date.ts\";\nimport { fetchNotionPages } from \"../shared/notion.ts\";\nimport { initRollupSchema, upsertWeeklyRollup } from \"../storage/rollups.ts\";\nimport {\n buildEncouragement,\n buildBloodSugarRollup,\n formatGroupedEntryLine,\n groupEntriesByDate,\n parseEntry,\n type GroupedEntries,\n type BloodSugarNotionPage,\n type Entry,\n hasPerfectWeekStreak,\n} from \"../shared/blood_sugar_logic.ts\";\n\nexport default async function handler(): Promise {\n const notionConfig = getNotionConfig();\n const emailConfig = getEmailConfig();\n\n if (!notionConfig) {\n return new Response(\"Missing required secrets.\", { status: 500 });\n }\n\n // Use a fixed 7-day range ending today (UTC) for weekly rollups.\n const { start, end } = getWeeklyRange();\n console.log(`Weekly range: ${start} to ${end}`);\n const entries = await fetchEntries(start, end, notionConfig);\n console.log(`Fetched ${entries.length} entries from Notion`);\n const report = buildReport(entries, start, end);\n console.log(\"Report subject:\", report.subject);\n console.log(\"Sending email to Val Town account owner (free tier default).\");\n\n // Build the payload to match Val Town's std/email expectations.\n const emailPayload = {\n subject: report.subject,\n text: report.text,\n html: report.html,\n ...(buildFrom(emailConfig?.fromEmail, emailConfig?.fromName) ?? {}),\n ...(emailConfig?.replyTo ? { replyTo: emailConfig.replyTo } : {}),\n };\n\n await email(emailPayload);\n console.log(\"Email sent.\");\n\n await initRollupSchema();\n await upsertWeeklyRollup(report.rollup);\n\n return new Response(\"Weekly report sent.\", { status: 200 });\n}\n\nfunction buildFrom(email?: string | null, name?: string | null) {\n if (!email) return null;\n return {\n from: name ? { email, name } : { email },\n };\n}\n\ntype NotionConfig = {\n token: string;\n databaseId: string;\n};\n\ntype EmailConfig = {\n fromEmail?: string;\n fromName?: string;\n replyTo?: string;\n};\n\nfunction getNotionConfig(): NotionConfig | null {\n const token = Deno.env.get(\"NOTION_TOKEN\");\n const databaseId = Deno.env.get(\"NOTION_BLOOD_SUGAR_DB_ID\");\n if (!token || !databaseId) return null;\n return { token, databaseId };\n}\n\nfunction getEmailConfig(): EmailConfig | null {\n const fromEmail = Deno.env.get(\"REPORT_FROM_EMAIL\") ?? undefined;\n const fromName = Deno.env.get(\"REPORT_FROM_NAME\") ?? undefined;\n const replyTo = Deno.env.get(\"REPORT_REPLY_TO\") ?? undefined;\n if (!fromEmail && !fromName && !replyTo) return null;\n return { fromEmail, fromName, replyTo };\n}\n\nexport async function fetchEntries(\n start: string,\n end: string,\n notionConfig: NotionConfig,\n): Promise {\n const pages = await fetchNotionPages(notionConfig.databaseId, notionConfig.token, (cursor) => ({\n filter: {\n and: [\n { property: \"Created time\", created_time: { on_or_after: start } },\n { property: \"Created time\", created_time: { on_or_before: end } },\n ],\n },\n sorts: [{ property: \"Created time\", 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\nexport function buildReport(entries: Entry[], start: string, end: string) {\n // Compute summary stats and derive copy for email-friendly output.\n // Summary stats for the weekly rollup.\n const rollup = buildBloodSugarRollup(entries, start, end);\n const subject = `Blood Sugar Weekly Rollup (${start} → ${end})`;\n const dateRange = listDateRange(start, end);\n const groupedEntries = groupEntriesByDate(entries, dateRange);\n const encouragement = buildEncouragement(rollup.completionRate, rollup.streak);\n const disclaimer =\n \"Not medical advice. Educational info only. Source: https://www.ynhhs.org/articles/what-is-healthy-blood-sugar\";\n\n const lines = [\n `Range: ${start} to ${end}`,\n `Entries: ${rollup.stats.totalEntries} (expected ${rollup.stats.expected}, missing ${rollup.stats.missing})`,\n `Average (all): ${rollup.stats.avg}`,\n `Morning average: ${rollup.stats.morningAvg} (${rollup.stats.morningEntries} reading${rollup.stats.morningEntries === 1 ? \"\" : \"s\"})`,\n `Evening average: ${rollup.stats.eveningAvg} (${rollup.stats.eveningEntries} reading${rollup.stats.eveningEntries === 1 ? \"\" : \"s\"})`,\n `Min: ${rollup.stats.min}`,\n `Max: ${rollup.stats.max}`,\n `Completion: ${rollup.completionRate}%`,\n `Consistency: ${rollup.stats.consistencyScore}% (${rollup.stats.fullyCoveredDays}/${dateRange.length} days with both morning and evening readings)`,\n `Current streak: ${rollup.streak} day${rollup.streak === 1 ? \"\" : \"s\"}`,\n `Perfect week streak: ${hasPerfectWeekStreak(dateRange, rollup.stats.entriesByDate) ? \"Yes\" : \"No\"}`,\n `XP earned: ${rollup.xp}`,\n `Badges: ${rollup.badges.length ? rollup.badges.join(\", \") : \"No badges yet\"}`,\n `Encouragement: ${encouragement}`,\n `Disclaimer: ${disclaimer}`,\n \"\",\n \"Entries:\",\n ...groupedEntries.map(formatGroupedEntryLine),\n ];\n\n const text = lines.join(\"\\n\");\n const html = renderHtmlReport(groupedEntries, {\n start,\n end,\n count: rollup.stats.totalEntries,\n expected: rollup.stats.expected,\n missing: rollup.stats.missing,\n avg: rollup.stats.avg,\n morningAvg: rollup.stats.morningAvg,\n eveningAvg: rollup.stats.eveningAvg,\n min: rollup.stats.min,\n max: rollup.stats.max,\n completionRate: rollup.completionRate,\n consistencyScore: rollup.stats.consistencyScore,\n fullyCoveredDays: rollup.stats.fullyCoveredDays,\n totalDays: dateRange.length,\n currentStreak: rollup.streak,\n badges: rollup.badges,\n encouragement,\n disclaimer,\n xp: rollup.xp,\n perfectWeekStreak: hasPerfectWeekStreak(dateRange, rollup.stats.entriesByDate),\n });\n\n return { subject, text, html, rollup };\n}\n\nfunction formatFirstSecondHtml(group: GroupedEntries): [string, string] {\n const ordered = orderEntries(group);\n if (!ordered.length) return [\"—\", \"—\"];\n const first = String(ordered[0].value);\n if (ordered.length === 1) return [first, \"—\"];\n const secondValue = String(ordered[1].value);\n const overflow = ordered.length > 2 ? ` (+${ordered.length - 2})` : \"\";\n return [first, `${secondValue}${overflow}`];\n}\n\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\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\nexport function renderHtmlReport(\n groupedEntries: GroupedEntries[],\n stats: {\n start: string;\n end: string;\n count: number;\n expected: number;\n missing: number;\n avg: number;\n morningAvg: number;\n eveningAvg: number;\n min: number;\n max: number;\n completionRate: number;\n consistencyScore: number;\n fullyCoveredDays: number;\n totalDays: number;\n currentStreak: number;\n badges: string[];\n encouragement: string;\n disclaimer: string;\n xp: number;\n perfectWeekStreak: boolean;\n },\n): string {\n // Simple HTML table for quick scanning in email clients.\n const rows = groupedEntries\n .map((group) => {\n const [first, second] = formatFirstSecondHtml(group);\n return `\n ${group.date}\n ${escapeHtml(first)}\n ${escapeHtml(second)}\n `;\n })\n .join(\"\");\n\n return `\n

\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}

Morning Avg

${stats.morningAvg}

Evening Avg

${stats.eveningAvg}

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

\n \n Entries \n ${stats.count}/${stats.expected} \n \n	\n \n Consistency \n ${stats.consistencyScore}% \n \n
\n \n Min / Max \n ${stats.min} / ${stats.max} \n \n	\n \n Completion \n ${stats.completionRate}% \n \n

\n Consistency detail: ${stats.fullyCoveredDays}/${stats.totalDays} days had both morning and evening readings.\n

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

\n Current streak: ${stats.currentStreak} day${stats.currentStreak === 1 ? \"\" : \"s\"} | XP: ${stats.xp}\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",[],[209,673],["D",1768499629095],[457,458],[209],"2de47576-f23b-11f0-a135-42dde27851f2","settings.json","2de4762a-f23b-11f0-a135-42dde27851f2",228,["D",1768499643522],"{\n \"deno.enable\": true,\n \"deno.enablePaths\": [\"./\"]\n }",[],[215,685],"2de68492-f23b-11f0-93cf-42dde27851f2","extensions.json","2de68528-f23b-11f0-93cf-42dde27851f2",229,["D",1768499643540],"{\n \"recommendations\": [\n \"denoland.vscode-deno\"\n ]\n}",[],[215,693],["D",1768499629401],[454,455],[215],"a72bf240-fadf-11f0-9997-42dde27851f2","packed-refs","a72bf2e0-fadf-11f0-9997-42dde27851f2",597,["D",1769449893764],"# pack-refs with: peeled fully-peeled sorted \n",[],[221,704],"a88d09da-fadf-11f0-a64f-42dde27851f2","a88d0a84-fadf-11f0-a64f-42dde27851f2",633,["D",1769449893766],"Unnamed 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accessible CS and cron explanations\n5a1ff9648ccafde07f847ee948d24327b0f82ee0 0000000000000000000000000000000000000000 Paul Chin Jr 1768340243 -0500\tBranch: renamed refs/heads/main to refs/heads/main\n5a1ff9648ccafde07f847ee948d24327b0f82ee0 5a1ff9648ccafde07f847ee948d24327b0f82ee0 Paul Chin Jr 1768340243 -0500\tBranch: renamed refs/heads/main to refs/heads/main\n5a1ff9648ccafde07f847ee948d24327b0f82ee0 91ef03c3ddfe090d6f817d212bd5d2198b8b8ed7 Paul Chin Jr 1768341488 -0500\tcommit: Add tests and rollup storage plan\n91ef03c3ddfe090d6f817d212bd5d2198b8b8ed7 2aa2e676338bca67cc63c91fd7b3e3b9d5d0f5c8 Paul Chin Jr 1768342079 -0500\tcommit: Remove report recipient config for free tier\n2aa2e676338bca67cc63c91fd7b3e3b9d5d0f5c8 e062d0c7ccfbfac740507528cce815c212ae4306 Paul Chin Jr 1768343182 -0500\tcommit: Adjust base XP per entry\ne062d0c7ccfbfac740507528cce815c212ae4306 8d4cb7027b8f1f8ba00b19ef1f0d9fc0bc6d2656 Paul Chin Jr 1768343572 -0500\tcommit: Add Praise Cage badge names\n8d4cb7027b8f1f8ba00b19ef1f0d9fc0bc6d2656 bcb1bef64baf59ac5e5d5c672c30894010107320 Paul Chin Jr 1768344258 -0500\tcommit: Update docs and add creator credit\nbcb1bef64baf59ac5e5d5c672c30894010107320 6164f3be44cdf5054a4a80e572fe189d5e6a229e Paul Chin Jr 1768344849 -0500\tcommit: Parse time and remove notes field\n6164f3be44cdf5054a4a80e572fe189d5e6a229e 153ccfbc31492a7c22000a1f84c146f3dea7abc5 Paul Chin Jr 1768400162 -0500\tcommit: Simplify entry table to first/second readings\n153ccfbc31492a7c22000a1f84c146f3dea7abc5 ae063685cb25f35aaa7e1ed3a4a899d55aed37fb Paul Chin Jr 1768400752 -0500\tcommit: Tweak Memphis pattern strip\nae063685cb25f35aaa7e1ed3a4a899d55aed37fb 7c8e3e80690a0e46871b2d52d35fcef22657f89f Paul Chin Jr 1768401951 -0500\tcommit: Reword docs to friendly report\n7c8e3e80690a0e46871b2d52d35fcef22657f89f 5d47816014fd3da3e12159d5618e2ba914d955fe Paul Chin Jr 1768401989 -0500\tcommit: Add run_id dedupe for rollups\n5d47816014fd3da3e12159d5618e2ba914d955fe 400c3b7022a7e032a26dc950d992dc6badcb91ca Paul Chin Jr 1768402067 -0500\tcommit: Add next-session TODOs\n400c3b7022a7e032a26dc950d992dc6badcb91ca ccdc708e69c9b2e0ba5fd5f3abef8b3f14037456 Paul Chin Jr 1768587628 -0500\tcommit: Add OpenAI food log enrichment\nccdc708e69c9b2e0ba5fd5f3abef8b3f14037456 c06d85faf3039ca52287765879458d4bcc1b890b Paul Chin Jr 1768587721 -0500\tcommit: Remove docs and USDA schema\nc06d85faf3039ca52287765879458d4bcc1b890b e7fa51cf26f5ffe7d6b7534b61ca8c5d9a648563 Paul Chin Jr 1768587852 -0500\tcommit: Add remaining source files\ne7fa51cf26f5ffe7d6b7534b61ca8c5d9a648563 077f5e941a379c6d39aa25053f87a3a55edc8bfd Paul Chin Jr 1768588890 -0500\tcommit: Refactor logic for local tests\n077f5e941a379c6d39aa25053f87a3a55edc8bfd 6d860e5fea1ded7c96c9d4072f3081531ca135c9 Paul Chin Jr 1768589578 -0500\tcommit: Clarify setup docs and add code comments\n6d860e5fea1ded7c96c9d4072f3081531ca135c9 58e2b324b3c4d83fd7e4099eee587509299ed8f4 Paul Chin Jr 1768591628 -0500\tcommit: Persist weekly rollups to SQLite\n58e2b324b3c4d83fd7e4099eee587509299ed8f4 ad42f65d1cabb7f0c0395cd64b9fad66c173ced6 Paul Chin Jr 1768592011 -0500\tcommit: Expand rollup and persistence tests\nad42f65d1cabb7f0c0395cd64b9fad66c173ced6 8fc017ca7639f5a348ac38e5c7f89b5ddd75a39b Paul Chin Jr 1768592524 -0500\tcommit: Add Praise Cage monthly report page\n8fc017ca7639f5a348ac38e5c7f89b5ddd75a39b 8096894527e60ecd556308bde37fea21f24ed9e1 Paul Chin Jr 1768597793 -0500\tcommit: Fix monthly report month selection\n8096894527e60ecd556308bde37fea21f24ed9e1 bf75f3be2cd0e897f10d211c9e25a65bed5cedba Paul Chin Jr 1768601579 -0500\tcommit: Redesign monthly report page\nbf75f3be2cd0e897f10d211c9e25a65bed5cedba 63d1cfa746d5068353653f12a52290536548617b Paul Chin Jr 1768601975 -0500\tcommit: Add guidepost comments\n63d1cfa746d5068353653f12a52290536548617b 63d1cfa746d5068353653f12a52290536548617b Paul Chin Jr 1769091058 -0500\tcheckout: moving from main to food-api-integration\n63d1cfa746d5068353653f12a52290536548617b 264196ccb257dd650507e033d0644343b925bb0a Paul Chin Jr 1769097387 -0500\tcommit: Refine food enrichment and docs\n264196ccb257dd650507e033d0644343b925bb0a f326ea0b6bd07151d9fdadc420f790c9c3f21540 Paul Chin Jr 1769097965 -0500\tcommit (amend): Refine food enrichment and docs\nf326ea0b6bd07151d9fdadc420f790c9c3f21540 63d1cfa746d5068353653f12a52290536548617b Paul Chin Jr 1769098089 -0500\tcheckout: moving from food-api-integration to main\n63d1cfa746d5068353653f12a52290536548617b 9abd1a62978356a229862245c07f95213cc82085 Paul Chin Jr 1769098095 -0500\tmerge food-api-integration: Merge made by the 'ort' strategy.\n9abd1a62978356a229862245c07f95213cc82085 dffb8a31cc8a1e7044a2a89cf3c24393e05f0c61 Paul Chin Jr 1769100077 -0500\tcommit: removed walkthrough, not helpful\ndffb8a31cc8a1e7044a2a89cf3c24393e05f0c61 ab9e94f94c298091109796be4a10a3dbd5d4dab0 Paul Chin Jr 1769449772 -0500\tpull: Fast-forward\nab9e94f94c298091109796be4a10a3dbd5d4dab0 a6774e98240af8533a1b19e789c884741427e34a Paul Chin Jr 1769449853 -0500\tcommit: adding vt dotfiles\n",[],[221,2069,735],"logs","a8d3fa70-fadf-11f0-a64f-42dde27851f2","a8d3fb38-fadf-11f0-a64f-42dde27851f2","a70b814a-fadf-11f0-947e-42dde27851f2",643,["D",1769449896533],"0000000000000000000000000000000000000000 5a1ff9648ccafde07f847ee948d24327b0f82ee0 Paul Chin Jr 1768340244 -0500\tupdate by push\n5a1ff9648ccafde07f847ee948d24327b0f82ee0 91ef03c3ddfe090d6f817d212bd5d2198b8b8ed7 Paul Chin Jr 1768341497 -0500\tupdate by push\n91ef03c3ddfe090d6f817d212bd5d2198b8b8ed7 2aa2e676338bca67cc63c91fd7b3e3b9d5d0f5c8 Paul Chin Jr 1768342101 -0500\tupdate by push\n2aa2e676338bca67cc63c91fd7b3e3b9d5d0f5c8 e062d0c7ccfbfac740507528cce815c212ae4306 Paul Chin Jr 1768343191 -0500\tupdate by push\ne062d0c7ccfbfac740507528cce815c212ae4306 8d4cb7027b8f1f8ba00b19ef1f0d9fc0bc6d2656 Paul Chin Jr 1768343580 -0500\tupdate by push\n8d4cb7027b8f1f8ba00b19ef1f0d9fc0bc6d2656 bcb1bef64baf59ac5e5d5c672c30894010107320 Paul Chin Jr 1768344277 -0500\tupdate by push\nbcb1bef64baf59ac5e5d5c672c30894010107320 6164f3be44cdf5054a4a80e572fe189d5e6a229e Paul Chin Jr 1768344858 -0500\tupdate by push\n6164f3be44cdf5054a4a80e572fe189d5e6a229e 153ccfbc31492a7c22000a1f84c146f3dea7abc5 Paul Chin Jr 1768400171 -0500\tupdate by push\n153ccfbc31492a7c22000a1f84c146f3dea7abc5 ae063685cb25f35aaa7e1ed3a4a899d55aed37fb Paul Chin Jr 1768400819 -0500\tupdate by push\nae063685cb25f35aaa7e1ed3a4a899d55aed37fb 7c8e3e80690a0e46871b2d52d35fcef22657f89f Paul Chin Jr 1768401964 -0500\tupdate by push\n7c8e3e80690a0e46871b2d52d35fcef22657f89f 5d47816014fd3da3e12159d5618e2ba914d955fe Paul Chin Jr 1768401997 -0500\tupdate by push\n5d47816014fd3da3e12159d5618e2ba914d955fe 400c3b7022a7e032a26dc950d992dc6badcb91ca Paul Chin Jr 1768402079 -0500\tupdate by push\n400c3b7022a7e032a26dc950d992dc6badcb91ca 6d860e5fea1ded7c96c9d4072f3081531ca135c9 Paul Chin Jr 1768589638 -0500\tupdate by push\n6d860e5fea1ded7c96c9d4072f3081531ca135c9 ad42f65d1cabb7f0c0395cd64b9fad66c173ced6 Paul Chin Jr 1768592018 -0500\tupdate by push\nad42f65d1cabb7f0c0395cd64b9fad66c173ced6 63d1cfa746d5068353653f12a52290536548617b Paul Chin Jr 1768602005 -0500\tupdate by push\n63d1cfa746d5068353653f12a52290536548617b 9abd1a62978356a229862245c07f95213cc82085 Paul Chin Jr 1769098102 -0500\tupdate by push\n9abd1a62978356a229862245c07f95213cc82085 dffb8a31cc8a1e7044a2a89cf3c24393e05f0c61 Paul Chin Jr 1769100079 -0500\tupdate by push\ndffb8a31cc8a1e7044a2a89cf3c24393e05f0c61 ab9e94f94c298091109796be4a10a3dbd5d4dab0 Paul Chin Jr 1769449772 -0500\tpull: fast-forward\nab9e94f94c298091109796be4a10a3dbd5d4dab0 a6774e98240af8533a1b19e789c884741427e34a Paul Chin Jr 1769449855 -0500\tupdate by push\n",[],[221,2069,766,775,776,89],"a8cbbf40-fadf-11f0-adb1-42dde27851f2","a8cbbfe0-fadf-11f0-adb1-42dde27851f2",642,["D",1769449896501],"0000000000000000000000000000000000000000 f326ea0b6bd07151d9fdadc420f790c9c3f21540 Paul Chin Jr 1769098037 -0500\tupdate by push\n",[],[221,2069,766,775,776,778],"a70b80aa-fadf-11f0-947e-42dde27851f2","a6d9bd2c-fadf-11f0-a64f-42dde27851f2",595,["D",1769449893512],[260,261],[221,2069,766,775,776],"a6d9bc78-fadf-11f0-a64f-42dde27851f2","a6aec52c-fadf-11f0-a64f-42dde27851f2",593,["D",1769449893232],[259],[221,2069,766,775],"a8dcb304-fadf-11f0-94b8-42dde27851f2","a8dcb3d6-fadf-11f0-94b8-42dde27851f2","a6efff74-fadf-11f0-947e-42dde27851f2",644,["D",1769449896607],"0000000000000000000000000000000000000000 3b442191417c7c2bbcbb4b9477b4470c94e6f4dd Paul Chin Jr 1768336908 -0500\tcommit (initial): Add Notion weekly blood sugar report\n3b442191417c7c2bbcbb4b9477b4470c94e6f4dd e0bbbb9bce2a1bfcad5869c89edc28209294902d Paul Chin Jr 1768337021 -0500\tcommit: Add gitignore and env example\ne0bbbb9bce2a1bfcad5869c89edc28209294902d 29936d779d4a55118e78e31ae9a322459ce101ee Paul Chin Jr 1768337851 -0500\tcommit: working in progress\n29936d779d4a55118e78e31ae9a322459ce101ee 5f951a9ced12b9f0e0b6a88f3ce949726dccbe7a Paul Chin Jr 1768338337 -0500\tcommit: debug email api\n5f951a9ced12b9f0e0b6a88f3ce949726dccbe7a 33fba6a725859aceaf65c1c6b94bad5c3d3cab70 Paul Chin Jr 1768339195 -0500\tcommit: Clarify README and add runtime guards\n33fba6a725859aceaf65c1c6b94bad5c3d3cab70 f219b011b1f3e4a0c4b77a4cb55c411a26b572a9 Paul Chin Jr 1768339934 -0500\tcommit: adding lint and cleaning up code\nf219b011b1f3e4a0c4b77a4cb55c411a26b572a9 5a1ff9648ccafde07f847ee948d24327b0f82ee0 Paul Chin Jr 1768340136 -0500\tcommit: Add accessible CS and cron explanations\n5a1ff9648ccafde07f847ee948d24327b0f82ee0 5a1ff9648ccafde07f847ee948d24327b0f82ee0 Paul Chin Jr 1768340243 -0500\tBranch: renamed refs/heads/main to refs/heads/main\n5a1ff9648ccafde07f847ee948d24327b0f82ee0 91ef03c3ddfe090d6f817d212bd5d2198b8b8ed7 Paul Chin Jr 1768341488 -0500\tcommit: Add tests and rollup storage plan\n91ef03c3ddfe090d6f817d212bd5d2198b8b8ed7 2aa2e676338bca67cc63c91fd7b3e3b9d5d0f5c8 Paul Chin Jr 1768342079 -0500\tcommit: Remove report recipient config for free tier\n2aa2e676338bca67cc63c91fd7b3e3b9d5d0f5c8 e062d0c7ccfbfac740507528cce815c212ae4306 Paul Chin Jr 1768343182 -0500\tcommit: Adjust base XP per entry\ne062d0c7ccfbfac740507528cce815c212ae4306 8d4cb7027b8f1f8ba00b19ef1f0d9fc0bc6d2656 Paul Chin Jr 1768343572 -0500\tcommit: Add Praise Cage badge names\n8d4cb7027b8f1f8ba00b19ef1f0d9fc0bc6d2656 bcb1bef64baf59ac5e5d5c672c30894010107320 Paul Chin Jr 1768344258 -0500\tcommit: Update docs and add creator credit\nbcb1bef64baf59ac5e5d5c672c30894010107320 6164f3be44cdf5054a4a80e572fe189d5e6a229e Paul Chin Jr 1768344849 -0500\tcommit: Parse time and remove notes field\n6164f3be44cdf5054a4a80e572fe189d5e6a229e 153ccfbc31492a7c22000a1f84c146f3dea7abc5 Paul Chin Jr 1768400162 -0500\tcommit: Simplify entry table to first/second readings\n153ccfbc31492a7c22000a1f84c146f3dea7abc5 ae063685cb25f35aaa7e1ed3a4a899d55aed37fb Paul Chin Jr 1768400752 -0500\tcommit: Tweak Memphis pattern strip\nae063685cb25f35aaa7e1ed3a4a899d55aed37fb 7c8e3e80690a0e46871b2d52d35fcef22657f89f Paul Chin Jr 1768401951 -0500\tcommit: Reword docs to friendly report\n7c8e3e80690a0e46871b2d52d35fcef22657f89f 5d47816014fd3da3e12159d5618e2ba914d955fe Paul Chin Jr 1768401989 -0500\tcommit: Add run_id dedupe for rollups\n5d47816014fd3da3e12159d5618e2ba914d955fe 400c3b7022a7e032a26dc950d992dc6badcb91ca Paul Chin Jr 1768402067 -0500\tcommit: Add next-session TODOs\n400c3b7022a7e032a26dc950d992dc6badcb91ca ccdc708e69c9b2e0ba5fd5f3abef8b3f14037456 Paul Chin Jr 1768587628 -0500\tcommit: Add OpenAI food log enrichment\nccdc708e69c9b2e0ba5fd5f3abef8b3f14037456 c06d85faf3039ca52287765879458d4bcc1b890b Paul Chin Jr 1768587721 -0500\tcommit: Remove docs and USDA schema\nc06d85faf3039ca52287765879458d4bcc1b890b e7fa51cf26f5ffe7d6b7534b61ca8c5d9a648563 Paul Chin Jr 1768587852 -0500\tcommit: Add remaining source files\ne7fa51cf26f5ffe7d6b7534b61ca8c5d9a648563 077f5e941a379c6d39aa25053f87a3a55edc8bfd Paul Chin Jr 1768588890 -0500\tcommit: Refactor logic for local tests\n077f5e941a379c6d39aa25053f87a3a55edc8bfd 6d860e5fea1ded7c96c9d4072f3081531ca135c9 Paul Chin Jr 1768589578 -0500\tcommit: Clarify setup docs and add code comments\n6d860e5fea1ded7c96c9d4072f3081531ca135c9 58e2b324b3c4d83fd7e4099eee587509299ed8f4 Paul Chin Jr 1768591628 -0500\tcommit: Persist weekly rollups to SQLite\n58e2b324b3c4d83fd7e4099eee587509299ed8f4 ad42f65d1cabb7f0c0395cd64b9fad66c173ced6 Paul Chin Jr 1768592011 -0500\tcommit: Expand rollup and persistence tests\nad42f65d1cabb7f0c0395cd64b9fad66c173ced6 8fc017ca7639f5a348ac38e5c7f89b5ddd75a39b Paul Chin Jr 1768592524 -0500\tcommit: Add Praise Cage monthly report page\n8fc017ca7639f5a348ac38e5c7f89b5ddd75a39b 8096894527e60ecd556308bde37fea21f24ed9e1 Paul Chin Jr 1768597793 -0500\tcommit: Fix monthly report month selection\n8096894527e60ecd556308bde37fea21f24ed9e1 bf75f3be2cd0e897f10d211c9e25a65bed5cedba Paul Chin Jr 1768601579 -0500\tcommit: Redesign monthly report page\nbf75f3be2cd0e897f10d211c9e25a65bed5cedba 63d1cfa746d5068353653f12a52290536548617b Paul Chin Jr 1768601975 -0500\tcommit: Add guidepost comments\n63d1cfa746d5068353653f12a52290536548617b 9abd1a62978356a229862245c07f95213cc82085 Paul Chin Jr 1769098095 -0500\tmerge food-api-integration: Merge made by the 'ort' strategy.\n9abd1a62978356a229862245c07f95213cc82085 dffb8a31cc8a1e7044a2a89cf3c24393e05f0c61 Paul Chin Jr 1769100077 -0500\tcommit: removed walkthrough, not helpful\ndffb8a31cc8a1e7044a2a89cf3c24393e05f0c61 ab9e94f94c298091109796be4a10a3dbd5d4dab0 Paul Chin Jr 1769449772 -0500\tpull: Fast-forward\nab9e94f94c298091109796be4a10a3dbd5d4dab0 a6774e98240af8533a1b19e789c884741427e34a Paul Chin Jr 1769449853 -0500\tcommit: adding vt dotfiles\n",[],[221,2069,766,803,89],"a6effec0-fadf-11f0-947e-42dde27851f2",594,["D",1769449893360],[257],[221,2069,766,803],"a6aec446-fadf-11f0-a64f-42dde27851f2",591,["D",1769449892950],[256,258],[221,2069,766],"8505d33e-fadf-11f0-8b67-42dde27851f2",435,["D",1769449836426],[255,262],[221,2069],"a89a29bc-fadf-11f0-8b79-42dde27851f2","exclude","a89a2a70-fadf-11f0-8b79-42dde27851f2","84b74b6a-fadf-11f0-8f76-42dde27851f2",635,["D",1769449896141],"# git ls-files --others --exclude-from=.git/info/exclude\n# Lines that start with '#' are comments.\n# For a project mostly in C, the following would be a good set of\n# exclude patterns (uncomment them if you want to use them):\n# *.[oa]\n# *~\n",[],[221,824,2121],"84b74aac-fadf-11f0-8f76-42dde27851f2",433,["D",1769449835969],[253],[221,824],"a7b66cfe-fadf-11f0-b73b-42dde27851f2","update.sample","a7b66db2-fadf-11f0-b73b-42dde27851f2","846ccffe-fadf-11f0-a92d-42dde27851f2",606,["D",1769449894422],"#!/bin/sh\n#\n# An example hook script to block unannotated tags from entering.\n# Called by \"git receive-pack\" with arguments: refname sha1-old sha1-new\n#\n# To enable this hook, rename this file to \"update\".\n#\n# Config\n# ------\n# hooks.allowunannotated\n# This boolean sets whether unannotated tags will be allowed into the\n# repository. By default they won't be.\n# hooks.allowdeletetag\n# This boolean sets whether deleting tags will be allowed in the\n# repository. By default they won't be.\n# hooks.allowmodifytag\n# This boolean sets whether a tag may be modified after creation. By default\n# it won't be.\n# hooks.allowdeletebranch\n# This boolean sets whether deleting branches will be allowed in the\n# repository. By default they won't be.\n# hooks.denycreatebranch\n# This boolean sets whether remotely creating branches will be denied\n# in the repository. By default this is allowed.\n#\n\n# --- Command line\nrefname=\"$1\"\noldrev=\"$2\"\nnewrev=\"$3\"\n\n# --- Safety check\nif [ -z \"$GIT_DIR\" ]; then\n\techo \"Don't run this script from the command line.\" >&2\n\techo \" (if you want, you could supply GIT_DIR then run\" >&2\n\techo \" $0 )\" >&2\n\texit 1\nfi\n\nif [ -z \"$refname\" -o -z \"$oldrev\" -o -z \"$newrev\" ]; then\n\techo \"usage: $0 \" >&2\n\texit 1\nfi\n\n# --- Config\nallowunannotated=$(git config --type=bool hooks.allowunannotated)\nallowdeletebranch=$(git config --type=bool hooks.allowdeletebranch)\ndenycreatebranch=$(git config --type=bool hooks.denycreatebranch)\nallowdeletetag=$(git config --type=bool hooks.allowdeletetag)\nallowmodifytag=$(git config --type=bool hooks.allowmodifytag)\n\n# check for no description\nprojectdesc=$(sed -e '1q' \"$GIT_DIR/description\")\ncase \"$projectdesc\" in\n\"Unnamed repository\"* | \"\")\n\techo \"*** Project description file hasn't been set\" >&2\n\texit 1\n\t;;\nesac\n\n# --- Check types\n# if $newrev is 0000...0000, it's a commit to delete a ref.\nzero=$(git hash-object --stdin &2\n\t\t\techo \"*** Use 'git tag [ -a | -s ]' for tags you want to propagate.\" >&2\n\t\t\texit 1\n\t\tfi\n\t\t;;\n\trefs/tags/*,delete)\n\t\t# delete tag\n\t\tif [ \"$allowdeletetag\" != \"true\" ]; then\n\t\t\techo \"*** Deleting a tag is not allowed in this repository\" >&2\n\t\t\texit 1\n\t\tfi\n\t\t;;\n\trefs/tags/*,tag)\n\t\t# annotated tag\n\t\tif [ \"$allowmodifytag\" != \"true\" ] && git rev-parse $refname > /dev/null 2>&1\n\t\tthen\n\t\t\techo \"*** Tag '$refname' already exists.\" >&2\n\t\t\techo \"*** Modifying a tag is not allowed in this repository.\" >&2\n\t\t\texit 1\n\t\tfi\n\t\t;;\n\trefs/heads/*,commit)\n\t\t# branch\n\t\tif [ \"$oldrev\" = \"$zero\" -a \"$denycreatebranch\" = \"true\" ]; then\n\t\t\techo \"*** Creating a branch is not allowed in this repository\" >&2\n\t\t\texit 1\n\t\tfi\n\t\t;;\n\trefs/heads/*,delete)\n\t\t# delete branch\n\t\tif [ \"$allowdeletebranch\" != \"true\" ]; then\n\t\t\techo \"*** Deleting a branch is not allowed in this repository\" >&2\n\t\t\texit 1\n\t\tfi\n\t\t;;\n\trefs/remotes/*,commit)\n\t\t# tracking branch\n\t\t;;\n\trefs/remotes/*,delete)\n\t\t# delete tracking branch\n\t\tif [ \"$allowdeletebranch\" != \"true\" ]; then\n\t\t\techo \"*** Deleting a tracking branch is not allowed in this repository\" >&2\n\t\t\texit 1\n\t\tfi\n\t\t;;\n\t*)\n\t\t# Anything else (is there anything else?)\n\t\techo \"*** Update hook: unknown type of update to ref $refname of type $newrev_type\" >&2\n\t\texit 1\n\t\t;;\nesac\n\n# --- Finished\nexit 0\n",[],[221,2143,2135],"hooks","a7442680-fadf-11f0-9997-42dde27851f2","push-to-checkout.sample","a7442748-fadf-11f0-9997-42dde27851f2",601,["D",1769449893901],"#!/bin/sh\n\n# An example hook script to update a checked-out tree on a git push.\n#\n# This hook is invoked by git-receive-pack(1) when it reacts to git\n# push and updates reference(s) in its repository, and when the push\n# tries to update the branch that is currently checked out and the\n# receive.denyCurrentBranch configuration variable is set to\n# updateInstead.\n#\n# By default, such a push is refused if the working tree and the index\n# of the remote repository has any difference from the currently\n# checked out commit; when both the working tree and the index match\n# the current commit, they are updated to match the newly pushed tip\n# of the branch. This hook is to be used to override the default\n# behaviour; however the code below reimplements the default behaviour\n# as a starting point for convenient modification.\n#\n# The hook receives the commit with which the tip of the current\n# branch is going to be updated:\ncommit=$1\n\n# It can exit with a non-zero status to refuse the push (when it does\n# so, it must not modify the index or the working tree).\ndie () {\n\techo >&2 \"$*\"\n\texit 1\n}\n\n# Or it can make any necessary changes to the working tree and to the\n# index to bring them to the desired state when the tip of the current\n# branch is updated to the new commit, and exit with a zero status.\n#\n# For example, the hook can simply run git read-tree -u -m HEAD \"$1\"\n# in order to emulate git fetch that is run in the reverse direction\n# with git push, as the two-tree form of git read-tree -u -m is\n# essentially the same as git switch or git checkout that switches\n# branches while keeping the local changes in the working tree that do\n# not interfere with the difference between the branches.\n\n# The below is a more-or-less exact translation to shell of the C code\n# for the default behaviour for git's push-to-checkout hook defined in\n# the push_to_deploy() function in builtin/receive-pack.c.\n#\n# Note that the hook will be executed from the repository directory,\n# not from the working tree, so if you want to perform operations on\n# the working tree, you will have to adapt your code accordingly, e.g.\n# by adding \"cd ..\" or using relative paths.\n\nif ! git update-index -q --ignore-submodules --refresh\nthen\n\tdie \"Up-to-date check failed\"\nfi\n\nif ! git diff-files --quiet --ignore-submodules --\nthen\n\tdie \"Working directory has unstaged changes\"\nfi\n\n# This is a rough translation of:\n#\n# head_has_history() ? \"HEAD\" : EMPTY_TREE_SHA1_HEX\nif git cat-file -e HEAD 2>/dev/null\nthen\n\thead=HEAD\nelse\n\thead=$(git hash-object -t tree --stdin \\).*$/Signed-off-by: \\1/p')\n# git interpret-trailers --in-place --trailer \"$SOB\" \"$COMMIT_MSG_FILE\"\n# if test -z \"$COMMIT_SOURCE\"\n# then\n# /usr/bin/perl -i.bak -pe 'print \"\\n\" if !$first_line++' \"$COMMIT_MSG_FILE\"\n# fi\n",[],[221,2143,2153],"a80063ea-fadf-11f0-ab39-42dde27851f2","pre-receive.sample","a80064a8-fadf-11f0-ab39-42dde27851f2",615,["D",1769449894081],"#!/bin/sh\n#\n# An example hook script to make use of push options.\n# The example simply echoes all push options that start with 'echoback='\n# and rejects all pushes when the \"reject\" push option is used.\n#\n# To enable this hook, rename this file to \"pre-receive\".\n\nif test -n \"$GIT_PUSH_OPTION_COUNT\"\nthen\n\ti=0\n\twhile test \"$i\" -lt \"$GIT_PUSH_OPTION_COUNT\"\n\tdo\n\t\teval \"value=\\$GIT_PUSH_OPTION_$i\"\n\t\tcase \"$value\" in\n\t\techoback=*)\n\t\t\techo \"echo from the pre-receive-hook: ${value#*=}\" >&2\n\t\t\t;;\n\t\treject)\n\t\t\texit 1\n\t\tesac\n\t\ti=$((i + 1))\n\tdone\nfi\n",[],[221,2143,2161],"a7dae4ee-fadf-11f0-947e-42dde27851f2","pre-rebase.sample","a7dae5ac-fadf-11f0-947e-42dde27851f2",611,["D",1769449894912],"#!/bin/sh\n#\n# Copyright (c) 2006, 2008 Junio C Hamano\n#\n# The \"pre-rebase\" hook is run just before \"git rebase\" starts doing\n# its job, and can prevent the command from running by exiting with\n# non-zero status.\n#\n# The hook is called with the following parameters:\n#\n# $1 -- the upstream the series was forked from.\n# $2 -- the branch being rebased (or empty when rebasing the current branch).\n#\n# This sample shows how to prevent topic branches that are already\n# merged to 'next' branch from getting rebased, because allowing it\n# would result in rebasing already published history.\n\npublish=next\nbasebranch=\"$1\"\nif test \"$#\" = 2\nthen\n\ttopic=\"refs/heads/$2\"\nelse\n\ttopic=`git symbolic-ref HEAD` ||\n\texit 0 ;# we do not interrupt rebasing detached HEAD\nfi\n\ncase \"$topic\" in\nrefs/heads/??/*)\n\t;;\n*)\n\texit 0 ;# we do not interrupt others.\n\t;;\nesac\n\n# Now we are dealing with a topic branch being rebased\n# on top of master. Is it OK to rebase it?\n\n# Does the topic really exist?\ngit show-ref -q \"$topic\" || {\n\techo >&2 \"No such branch $topic\"\n\texit 1\n}\n\n# Is topic fully merged to master?\nnot_in_master=`git rev-list --pretty=oneline ^master \"$topic\"`\nif test -z \"$not_in_master\"\nthen\n\techo >&2 \"$topic is fully merged to master; better remove it.\"\n\texit 1 ;# we could allow it, but there is no point.\nfi\n\n# Is topic ever merged to next? If so you should not be rebasing it.\nonly_next_1=`git rev-list ^master \"^$topic\" ${publish} | sort`\nonly_next_2=`git rev-list ^master ${publish} | sort`\nif test \"$only_next_1\" = \"$only_next_2\"\nthen\n\tnot_in_topic=`git rev-list \"^$topic\" master`\n\tif test -z \"$not_in_topic\"\n\tthen\n\t\techo >&2 \"$topic is already up to date with master\"\n\t\texit 1 ;# we could allow it, but there is no point.\n\telse\n\t\texit 0\n\tfi\nelse\n\tnot_in_next=`git rev-list --pretty=oneline ^${publish} \"$topic\"`\n\t/usr/bin/perl -e '\n\t\tmy $topic = $ARGV[0];\n\t\tmy $msg = \"* $topic has commits already merged to public branch:\\n\";\n\t\tmy (%not_in_next) = map {\n\t\t\t/^([0-9a-f]+) /;\n\t\t\t($1 => 1);\n\t\t} split(/\\n/, $ARGV[1]);\n\t\tfor my $elem (map {\n\t\t\t\t/^([0-9a-f]+) (.*)$/;\n\t\t\t\t[$1 => $2];\n\t\t\t} split(/\\n/, $ARGV[2])) {\n\t\t\tif (!exists $not_in_next{$elem->[0]}) {\n\t\t\t\tif ($msg) {\n\t\t\t\t\tprint STDERR $msg;\n\t\t\t\t\tundef $msg;\n\t\t\t\t}\n\t\t\t\tprint STDERR \" $elem->[1]\\n\";\n\t\t\t}\n\t\t}\n\t' \"$topic\" \"$not_in_next\" \"$not_in_master\"\n\texit 1\nfi\n\n<<\\DOC_END\n\nThis sample hook safeguards topic branches that have been\npublished from being rewound.\n\nThe workflow assumed here is:\n\n * Once a topic branch forks from \"master\", \"master\" is never\n merged into it again (either directly or indirectly).\n\n * Once a topic branch is fully cooked and merged into \"master\",\n it is deleted. If you need to build on top of it to correct\n earlier mistakes, a new topic branch is created by forking at\n the tip of the \"master\". This is not strictly necessary, but\n it makes it easier to keep your history simple.\n\n * Whenever you need to test or publish your changes to topic\n branches, merge them into \"next\" branch.\n\nThe script, being an example, hardcodes the publish branch name\nto be \"next\", but it is trivial to make it configurable via\n$GIT_DIR/config mechanism.\n\nWith this workflow, you would want to know:\n\n(1) ... if a topic branch has ever been merged to \"next\". Young\n topic branches can have stupid mistakes you would rather\n clean up before publishing, and things that have not been\n merged into other branches can be easily rebased without\n affecting other people. But once it is published, you would\n not want to rewind it.\n\n(2) ... if a topic branch has been fully merged to \"master\".\n Then you can delete it. More importantly, you should not\n build on top of it -- other people may already want to\n change things related to the topic as patches against your\n \"master\", so if you need further changes, it is better to\n fork the topic (perhaps with the same name) afresh from the\n tip of \"master\".\n\nLet's look at this example:\n\n\t\t o---o---o---o---o---o---o---o---o---o \"next\"\n\t\t / / / /\n\t\t / a---a---b A / /\n\t\t/ / / /\n\t / / c---c---c---c B /\n\t / / / \\ /\n\t / / / b---b C \\ /\n\t / / / / \\ /\n ---o---o---o---o---o---o---o---o---o---o---o \"master\"\n\n\nA, B and C are topic branches.\n\n * A has one fix since it was merged up to \"next\".\n\n * B has finished. It has been fully merged up to \"master\" and \"next\",\n and is ready to be deleted.\n\n * C has not merged to \"next\" at all.\n\nWe would want to allow C to be rebased, refuse A, and encourage\nB to be deleted.\n\nTo compute (1):\n\n\tgit rev-list ^master ^topic next\n\tgit rev-list ^master next\n\n\tif these match, topic has not merged in next at all.\n\nTo compute (2):\n\n\tgit rev-list master..topic\n\n\tif this is empty, it is fully merged to \"master\".\n\nDOC_END\n",[],[221,2143,2169],"a7601f84-fadf-11f0-947e-42dde27851f2","pre-push.sample","a760202e-fadf-11f0-947e-42dde27851f2",602,["D",1769449894056],"#!/bin/sh\n\n# An example hook script to verify what is about to be pushed. Called by \"git\n# push\" after it has checked the remote status, but before anything has been\n# pushed. If this script exits with a non-zero status nothing will be pushed.\n#\n# This hook is called with the following parameters:\n#\n# $1 -- Name of the remote to which the push is being done\n# $2 -- URL to which the push is being done\n#\n# If pushing without using a named remote those arguments will be equal.\n#\n# Information about the commits which are being pushed is supplied as lines to\n# the standard input in the form:\n#\n# \n#\n# This sample shows how to prevent push of commits where the log message starts\n# with \"WIP\" (work in progress).\n\nremote=\"$1\"\nurl=\"$2\"\n\nzero=$(git hash-object --stdin &2 \"Found WIP commit in $local_ref, not pushing\"\n\t\t\texit 1\n\t\tfi\n\tfi\ndone\n\nexit 0\n",[],[221,2143,2177],"a78fbeb0-fadf-11f0-947e-42dde27851f2","pre-merge-commit.sample","a78fbf82-fadf-11f0-947e-42dde27851f2",603,["D",1769449894276],"#!/bin/sh\n#\n# An example hook script to verify what is about to be committed.\n# Called by \"git merge\" with no arguments. The hook should\n# exit with non-zero status after issuing an appropriate message to\n# stderr if it wants to stop the merge commit.\n#\n# To enable this hook, rename this file to \"pre-merge-commit\".\n\n. git-sh-setup\ntest -x \"$GIT_DIR/hooks/pre-commit\" &&\n exec \"$GIT_DIR/hooks/pre-commit\"\n:\n",[],[221,2143,2185],"a7c191b0-fadf-11f0-947e-42dde27851f2","pre-commit.sample","a7c19250-fadf-11f0-947e-42dde27851f2",607,["D",1769449894753],"#!/bin/sh\n#\n# An example hook script to verify what is about to be committed.\n# Called by \"git commit\" with no arguments. The hook should\n# exit with non-zero status after issuing an appropriate message if\n# it wants to stop the commit.\n#\n# To enable this hook, rename this file to \"pre-commit\".\n\nif git rev-parse --verify HEAD >/dev/null 2>&1\nthen\n\tagainst=HEAD\nelse\n\t# Initial commit: diff against an empty tree object\n\tagainst=$(git hash-object -t tree /dev/null)\nfi\n\n# If you want to allow non-ASCII filenames set this variable to true.\nallownonascii=$(git config --type=bool hooks.allownonascii)\n\n# Redirect output to stderr.\nexec 1>&2\n\n# Cross platform projects tend to avoid non-ASCII filenames; prevent\n# them from being added to the repository. We exploit the fact that the\n# printable range starts at the space character and ends with tilde.\nif [ \"$allownonascii\" != \"true\" ] &&\n\t# Note that the use of brackets around a tr range is ok here, (it's\n\t# even required, for portability to Solaris 10's /usr/bin/tr), since\n\t# the square bracket bytes happen to fall in the designated range.\n\ttest $(git diff --cached --name-only --diff-filter=A -z $against |\n\t LC_ALL=C tr -d '[ -~]\\0' | wc -c) != 0\nthen\n\tcat <<\\EOF\nError: Attempt to add a non-ASCII file name.\n\nThis can cause problems if you want to work with people on other platforms.\n\nTo be portable it is advisable to rename the file.\n\nIf you know what you are doing you can disable this check using:\n\n git config hooks.allownonascii true\nEOF\n\texit 1\nfi\n\n# If there are whitespace errors, print the offending file names and fail.\nexec git diff-index --check --cached $against --\n",[],[221,2143,2193],"a7a5a55e-fadf-11f0-9997-42dde27851f2","pre-applypatch.sample","a7a5a63a-fadf-11f0-9997-42dde27851f2",604,["D",1769449894411],"#!/bin/sh\n#\n# An example hook script to verify what is about to be committed\n# by applypatch from an e-mail message.\n#\n# The hook should exit with non-zero status after issuing an\n# appropriate message if it wants to stop the commit.\n#\n# To enable this hook, rename this file to \"pre-applypatch\".\n\n. git-sh-setup\nprecommit=\"$(git rev-parse --git-path hooks/pre-commit)\"\ntest -x \"$precommit\" && exec \"$precommit\" ${1+\"$@\"}\n:\n",[],[221,2143,2201],"a7d6e876-fadf-11f0-9997-42dde27851f2","post-update.sample","a7d6e92a-fadf-11f0-9997-42dde27851f2",610,["D",1769449894896],"#!/bin/sh\n#\n# An example hook script to prepare a packed repository for use over\n# dumb transports.\n#\n# To enable this hook, rename this file to \"post-update\".\n\nexec git update-server-info\n",[],[221,2143,2209],"a73fcebe-fadf-11f0-ab39-42dde27851f2","fsmonitor-watchman.sample","a73fcf86-fadf-11f0-ab39-42dde27851f2",600,["D",1769449893901],"#!/usr/bin/perl\n\nuse strict;\nuse warnings;\nuse IPC::Open2;\n\n# An example hook script to integrate Watchman\n# (https://facebook.github.io/watchman/) with git to speed up detecting\n# new and modified files.\n#\n# The hook is passed a version (currently 2) and last update token\n# formatted as a string and outputs to stdout a new update token and\n# all files that have been modified since the update token. Paths must\n# be relative to the root of the working tree and separated by a single NUL.\n#\n# To enable this hook, rename this file to \"query-watchman\" and set\n# 'git config core.fsmonitor .git/hooks/query-watchman'\n#\nmy ($version, $last_update_token) = @ARGV;\n\n# Uncomment for debugging\n# print STDERR \"$0 $version $last_update_token\\n\";\n\n# Check the hook interface version\nif ($version ne 2) {\n\tdie \"Unsupported query-fsmonitor hook version '$version'.\\n\" .\n\t \"Falling back to scanning...\\n\";\n}\n\nmy $git_work_tree = get_working_dir();\n\nmy $retry = 1;\n\nmy $json_pkg;\neval {\n\trequire JSON::XS;\n\t$json_pkg = \"JSON::XS\";\n\t1;\n} or do {\n\trequire JSON::PP;\n\t$json_pkg = \"JSON::PP\";\n};\n\nlaunch_watchman();\n\nsub launch_watchman {\n\tmy $o = watchman_query();\n\tif (is_work_tree_watched($o)) {\n\t\toutput_result($o->{clock}, @{$o->{files}});\n\t}\n}\n\nsub output_result {\n\tmy ($clockid, @files) = @_;\n\n\t# Uncomment for debugging watchman output\n\t# open (my $fh, \">\", \".git/watchman-output.out\");\n\t# binmode $fh, \":utf8\";\n\t# print $fh \"$clockid\\n@files\\n\";\n\t# close $fh;\n\n\tbinmode STDOUT, \":utf8\";\n\tprint $clockid;\n\tprint \"\\0\";\n\tlocal $, = \"\\0\";\n\tprint @files;\n}\n\nsub watchman_clock {\n\tmy $response = qx/watchman clock \"$git_work_tree\"/;\n\tdie \"Failed to get clock id on '$git_work_tree'.\\n\" .\n\t\t\"Falling back to scanning...\\n\" if $? != 0;\n\n\treturn $json_pkg->new->utf8->decode($response);\n}\n\nsub watchman_query {\n\tmy $pid = open2(\\*CHLD_OUT, \\*CHLD_IN, 'watchman -j --no-pretty')\n\tor die \"open2() failed: $!\\n\" .\n\t\"Falling back to scanning...\\n\";\n\n\t# In the query expression below we're asking for names of files that\n\t# changed since $last_update_token but not from the .git folder.\n\t#\n\t# To accomplish this, we're using the \"since\" generator to use the\n\t# recency index to select candidate nodes and \"fields\" to limit the\n\t# output to file names only. Then we're using the \"expression\" term to\n\t# further constrain the results.\n\tif (substr($last_update_token, 0, 1) eq \"c\") {\n\t\t$last_update_token = \"\\\"$last_update_token\\\"\";\n\t}\n\tmy $query = <<\"\tEND\";\n\t\t[\"query\", \"$git_work_tree\", {\n\t\t\t\"since\": $last_update_token,\n\t\t\t\"fields\": [\"name\"],\n\t\t\t\"expression\": [\"not\", [\"dirname\", \".git\"]]\n\t\t}]\n\tEND\n\n\t# Uncomment for debugging the watchman query\n\t# open (my $fh, \">\", \".git/watchman-query.json\");\n\t# print $fh $query;\n\t# close $fh;\n\n\tprint CHLD_IN $query;\n\tclose CHLD_IN;\n\tmy $response = do {local $/; };\n\n\t# Uncomment for debugging the watch response\n\t# open ($fh, \">\", \".git/watchman-response.json\");\n\t# print $fh $response;\n\t# close $fh;\n\n\tdie \"Watchman: command returned no output.\\n\" .\n\t\"Falling back to scanning...\\n\" if $response eq \"\";\n\tdie \"Watchman: command returned invalid output: $response\\n\" .\n\t\"Falling back to scanning...\\n\" unless $response =~ /^\\{/;\n\n\treturn $json_pkg->new->utf8->decode($response);\n}\n\nsub is_work_tree_watched {\n\tmy ($output) = @_;\n\tmy $error = $output->{error};\n\tif ($retry > 0 and $error and $error =~ m/unable to resolve root .* directory (.*) is not watched/) {\n\t\t$retry--;\n\t\tmy $response = qx/watchman watch \"$git_work_tree\"/;\n\t\tdie \"Failed to make watchman watch '$git_work_tree'.\\n\" .\n\t\t \"Falling back to scanning...\\n\" if $? != 0;\n\t\t$output = $json_pkg->new->utf8->decode($response);\n\t\t$error = $output->{error};\n\t\tdie \"Watchman: $error.\\n\" .\n\t\t\"Falling back to scanning...\\n\" if $error;\n\n\t\t# Uncomment for debugging watchman output\n\t\t# open (my $fh, \">\", \".git/watchman-output.out\");\n\t\t# close $fh;\n\n\t\t# Watchman will always return all files on the first query so\n\t\t# return the fast \"everything is dirty\" flag to git and do the\n\t\t# Watchman query just to get it over with now so we won't pay\n\t\t# the cost in git to look up each individual file.\n\t\tmy $o = watchman_clock();\n\t\t$error = $output->{error};\n\n\t\tdie \"Watchman: $error.\\n\" .\n\t\t\"Falling back to scanning...\\n\" if $error;\n\n\t\toutput_result($o->{clock}, (\"/\"));\n\t\t$last_update_token = $o->{clock};\n\n\t\teval { launch_watchman() };\n\t\treturn 0;\n\t}\n\n\tdie \"Watchman: $error.\\n\" .\n\t\"Falling back to scanning...\\n\" if $error;\n\n\treturn 1;\n}\n\nsub get_working_dir {\n\tmy $working_dir;\n\tif ($^O =~ 'msys' || $^O =~ 'cygwin') {\n\t\t$working_dir = Win32::GetCwd();\n\t\t$working_dir =~ tr/\\\\/\\//;\n\t} else {\n\t\trequire Cwd;\n\t\t$working_dir = Cwd::cwd();\n\t}\n\n\treturn $working_dir;\n}\n",[],[221,2143,2217],"a7ced456-fadf-11f0-b73b-42dde27851f2","commit-msg.sample","a7ced514-fadf-11f0-b73b-42dde27851f2",609,["D",1769449894840],"#!/bin/sh\n#\n# An example hook script to check the commit log message.\n# Called by \"git commit\" with one argument, the name of the file\n# that has the commit message. The hook should exit with non-zero\n# status after issuing an appropriate message if it wants to stop the\n# commit. The hook is allowed to edit the commit message file.\n#\n# To enable this hook, rename this file to \"commit-msg\".\n\n# Uncomment the below to add a Signed-off-by line to the message.\n# Doing this in a hook is a bad idea in general, but the prepare-commit-msg\n# hook is more suited to it.\n#\n# SOB=$(git var GIT_AUTHOR_IDENT | sed -n 's/^\$.*>\$.*$/Signed-off-by: \\1/p')\n# grep -qs \"^$SOB\" \"$1\" || echo \"$SOB\" >> \"$1\"\n\n# This example catches duplicate Signed-off-by lines.\n\ntest \"\" = \"$(grep '^Signed-off-by: ' \"$1\" |\n\t sort | uniq -c | sed -e '/^[ \t]*1[ \t]/d')\" || {\n\techo >&2 Duplicate Signed-off-by lines.\n\texit 1\n}\n",[],[221,2143,2225],"a7b2660e-fadf-11f0-947e-42dde27851f2","applypatch-msg.sample","a7b266fe-fadf-11f0-947e-42dde27851f2",605,["D",1769449894566],"#!/bin/sh\n#\n# An example hook script to check the commit log message taken by\n# applypatch from an e-mail message.\n#\n# The hook should exit with non-zero status after issuing an\n# appropriate message if it wants to stop the commit. The hook is\n# allowed to edit the commit message file.\n#\n# To enable this hook, rename this file to \"applypatch-msg\".\n\n. git-sh-setup\ncommitmsg=\"$(git rev-parse --git-path hooks/commit-msg)\"\ntest -x \"$commitmsg\" && exec \"$commitmsg\" ${1+\"$@\"}\n:\n",[],[221,2143,2233],"846ccf0e-fadf-11f0-a92d-42dde27851f2",431,["D",1769449835480],[239,240,241,242,243,244,245,246,247,248,249,250,251],[221,2143],"84568618-fadf-11f0-8f76-42dde27851f2","845686ae-fadf-11f0-8f76-42dde27851f2",430,["D",1769449835335],[],[221,227],["D",1769449835209],[237,238,252,254,263,438,446,447,448,449,450,451,452],[221],["D",1768332030028],["D",1789516910456],{"_99":98,"_106":102},{"_99":98,"_100":-5,"_101":102,"_18":56,"_103":104,"_105":25},{"_13":88,"_32":89,"_44":43,"_90":45,"_91":-5,"_92":-5,"_93":-5,"_94":-5,"_95":-5,"_96":46,"_97":98},"ctx",{"_81":-5,"_126":2292,"_2293":2294,"_2295":2296,"_2297":25,"_2298":25,"_2299":25,"_2300":124,"_2301":-5,"_2302":-7,"_2303":-7,"_2304":62,"_2305":25,"_2306":25,"_2307":-5,"_2308":25,"_2309":25,"_2310":25,"_2311":-5},"ENV",{"_2263":2264,"_2265":2266,"_2267":89,"_2268":2269,"_2270":2271,"_2272":2273,"_2274":2275,"_2276":2277,"_2278":2279,"_2280":2281,"_2282":2283,"_2284":2285,"_2286":2287,"_2288":2289,"_2290":2291},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","e87eb04e707cf64e7e532c8e8ec395f209e17f15","RENDER_GIT_BRANCH","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","VANITY_WEB_API_TEMPLATE","https://{label}.val.run/","DENOLS_URL","https://lsp.val.town","NODE_ENV","production","CLOUDFLARE_TURNSTILE_SITE_KEY","0x4AAAAAACtaIZJH7s9rBMZ6","GOOGLE_CLIENT_ID","875989696899-jtsqkhlbdv5jrlsk8631p7ipjg3c6o62.apps.googleusercontent.com","STRIPE_PUBLISHABLE_KEY","pk_live_51N2zvWEpZTTLipIkVEwXrUG9AT0yeOOEYxszarZT1jpsZV58Ly6wlg3SltZpHN26CUalOBmUSY7adQRQiSkCZz2500qSXNkf8Y","API_URL","https://api.val.town",[],"preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesCloseBrackets","preferencesChatPanelState","preferencesDprint","preferencesDenofmt","notificationCount","flagDenols","isBusinessOrgMember","businessOrgHandle","isBusinessOrgAdmin","isHigherTownieTier","navCollapsed","currentOrgId"]

Diff · v681