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It writes the same\n * blob key, so rangeLadder picks the data up with no change to that val or the JAR.\n *\n * Set DATABENTO_API_KEY in Val.town environment variables (key starts with \"db-\").\n *\n * ROUTES\n * GET / status + stored history summary\n * GET /cost price the backfill BEFORE running it (free, no data charge)\n * POST /sync fetch + rebuild the window {days?: 30, symbol?: \"NQ.v.0\"}\n * POST /sync/daily fetch just the last session and append (cron target)\n *\n * WHY ohlcv-1m AND NOT ohlcv-1h:\n * the session boundaries are 17:00 / 02:00 / 08:30 / 15:00 CT. 08:30 is not on an\n * hour mark, so hourly bars cannot resolve the RTH open or the Europe/RTH split.\n * Minute bars are ~1,380 records per session — a few MB for a full backfill.\n *\n * SYMBOLOGY: stype_in=continuous with \"NQ.v.0\" = front month by volume, which\n * matches how the model was fitted (dominant contract by volume, roll included).\n */\n\nimport { blob } from \"https://esm.town/v/std/blob\";\n\nconst KEY = \"rangeLadder:history:v1\"; // shared with rangeLadder val\nconst KEEP = 45;\nconst DATASET = \"GLBX.MDP3\";\nconst DEFAULT_SYMBOL = \"NQ.v.0\";\nconst HIST = \"https://hist.databento.com/v0\";\n\n// Session boundaries, minute-of-day, America/Chicago.\nconst ASIA_START = 17 * 60,\n EU_START = 2 * 60,\n RTH_START = 8 * 60 + 30,\n RTH_END = 15 * 60;\n\ntype Day = { date: string; rthRange: number; rthOpen: number };\n\n// ------------------------------------------------------------- CT helpers --\n\n/**\n * Offset lookup is cached per UTC hour: the America/Chicago offset only changes\n * at DST boundaries, so recomputing it per record would be wasted work on ~30k rows.\n */\nconst offsetCache = new Map();\nconst CT_FMT = new Intl.DateTimeFormat(\"en-US\", {\n timeZone: \"America/Chicago\",\n hour12: false,\n year: \"numeric\",\n month: \"2-digit\",\n day: \"2-digit\",\n hour: \"2-digit\",\n minute: \"2-digit\",\n});\n\nfunction ctParts(ms: number) {\n const hourKey = Math.floor(ms / 3_600_000);\n let off = offsetCache.get(hourKey);\n if (off === undefined) {\n const p = CT_FMT.formatToParts(new Date(ms));\n const g = (t: string) => Number(p.find((x) => x.type === t)!.value);\n // Reconstruct the CT wall-clock instant as if it were UTC, then difference.\n const asUtc = Date.UTC(\n g(\"year\"),\n g(\"month\") - 1,\n g(\"day\"),\n g(\"hour\") % 24,\n g(\"minute\"),\n );\n off = asUtc - Math.floor(ms / 60_000) * 60_000;\n offsetCache.set(hourKey, off);\n }\n const local = new Date(ms + off);\n return {\n y: local.getUTCFullYear(),\n m: local.getUTCMonth(),\n d: local.getUTCDate(),\n mod: local.getUTCHours() * 60 + local.getUTCMinutes(),\n };\n}\n\n/** Trade date: rolls at 17:00 CT, weekend stamps pushed to Monday. */\nexport function tradeDate(ms: number): { date: string; mod: number } {\n const { y, m, d, mod } = ctParts(ms);\n const dt = new Date(Date.UTC(y, m, d));\n if (mod >= ASIA_START) dt.setUTCDate(dt.getUTCDate() + 1);\n const wd = dt.getUTCDay();\n if (wd === 6) dt.setUTCDate(dt.getUTCDate() + 2);\n else if (wd === 0) dt.setUTCDate(dt.getUTCDate() + 1);\n return { date: dt.toISOString().slice(0, 10), mod };\n}\n\nexport function sessionOf(mod: number): \"RTH\" | \"ASIA\" | \"EU\" | \"POST\" {\n if (mod >= RTH_START && mod < RTH_END) return \"RTH\";\n if (mod >= ASIA_START || mod < EU_START) return \"ASIA\";\n if (mod >= EU_START && mod < RTH_START) return \"EU\";\n return \"POST\";\n}\n\n// ------------------------------------------------------------- parsing ----\n\n/**\n * Databento JSON-lines. Prices may arrive as fixed-point 1e-9 integers (default)\n * or as decimals when pretty_px is honoured, so scale defensively: no real NQ\n * price approaches 1e9, which makes the magnitude an unambiguous discriminator.\n */\nfunction px(v: unknown): number {\n const n = typeof v === \"string\" ? Number(v) : (v as number);\n if (!Number.isFinite(n)) return NaN;\n return Math.abs(n) > 1e9 ? n / 1e9 : n;\n}\n\nexport type Bar = { ts: number; o: number; h: number; l: number };\n\nexport function parseBars(body: string): Bar[] {\n const out: Bar[] = [];\n for (const line of body.split(\"\\n\")) {\n const s = line.trim();\n if (!s) continue;\n let r: any;\n try {\n r = JSON.parse(s);\n } catch {\n continue;\n }\n const tsRaw = r.hd?.ts_event ?? r.ts_event;\n if (tsRaw === undefined) continue;\n // ts_event is nanoseconds since epoch (string or number).\n const ts = Math.floor(Number(tsRaw) / 1e6);\n const o = px(r.open), h = px(r.high), l = px(r.low);\n if (!Number.isFinite(ts) || !Number.isFinite(h) || !Number.isFinite(l)) {\n continue;\n }\n // OHLCV bars with no trades report zeros; they'd wreck a session low.\n if (h <= 0 || l <= 0) continue;\n out.push({ ts, o, h, l });\n }\n return out;\n}\n\n/** Fold minute bars into per-trade-date session stats. */\nexport function foldSessions(bars: Bar[]) {\n type S = { rthOpen: number; rthHi: number; rthLo: number; rthBars: number };\n const map = new Map();\n for (const b of bars) {\n const { date, mod } = tradeDate(b.ts);\n if (sessionOf(mod) !== \"RTH\") continue;\n let s = map.get(date);\n if (!s) {\n s = { rthOpen: 0, rthHi: 0, rthLo: 0, rthBars: 0 };\n map.set(date, s);\n }\n if (s.rthBars === 0) {\n s.rthOpen = b.o;\n s.rthHi = b.h;\n s.rthLo = b.l;\n } else {\n s.rthHi = Math.max(s.rthHi, b.h);\n s.rthLo = Math.min(s.rthLo, b.l);\n }\n s.rthBars++;\n }\n const days: Day[] = [];\n for (const [date, s] of map) {\n // Half-days (~210 min) and partial pulls would bias the range distribution\n // the model was fitted on, so require most of a 390-minute session.\n if (s.rthBars < 300 || s.rthHi <= s.rthLo) continue;\n days.push({\n date,\n rthRange: +(s.rthHi - s.rthLo).toFixed(2),\n rthOpen: +s.rthOpen.toFixed(2),\n });\n }\n return days.sort((a, b) => (a.date < b.date ? 1 : -1));\n}\n\nfunction normalise(days: Day[]): Day[] {\n const seen = new Map();\n for (const d of days) {\n if (!/^\\d{4}-\\d{2}-\\d{2}$/.test(d?.date ?? \"\")) continue;\n if (!(d.rthRange > 0) || !(d.rthOpen > 0)) continue;\n if (seen.has(d.date)) continue; // first wins = newest/authoritative\n seen.set(d.date, d);\n }\n return [...seen.values()].sort((a, b) => (a.date < b.date ? 1 : -1)).slice(\n 0,\n KEEP,\n );\n}\n\n// ------------------------------------------------------------- databento ---\n\nfunction auth(): string {\n const key = Deno.env.get(\"DATABENTO_API_KEY\");\n if (!key) throw new Error(\"DATABENTO_API_KEY not set in Val.town env vars\");\n return \"Basic \" + btoa(key + \":\");\n}\n\nasync function db(\n method: string,\n params: Record,\n): Promise {\n const r = await fetch(`${HIST}/${method}`, {\n method: \"POST\",\n headers: {\n Authorization: auth(),\n \"content-type\": \"application/x-www-form-urlencoded\",\n },\n body: new URLSearchParams(params).toString(),\n });\n const text = await r.text();\n if (!r.ok) {\n throw new Error(`databento ${method} ${r.status}: ${text.slice(0, 300)}`);\n }\n return text;\n}\n\nfunction range(days: number) {\n const end = new Date();\n const start = new Date(end.getTime() - days * 86_400_000);\n return {\n start: start.toISOString().slice(0, 10),\n end: end.toISOString().slice(0, 10),\n };\n}\n\nasync function fetchBars(symbol: string, days: number): Promise {\n const { start, end } = range(days);\n const body = await db(\"timeseries.get_range\", {\n dataset: DATASET,\n symbols: symbol,\n schema: \"ohlcv-1m\",\n stype_in: \"continuous\",\n start,\n end,\n encoding: \"json\",\n compression: \"none\",\n });\n return parseBars(body);\n}\n\n// ---------------------------------------------------------------- routes ---\n\nexport default async function (req: Request): Promise {\n const json = (o: unknown, s = 200) =>\n new Response(JSON.stringify(o, null, 1), {\n status: s,\n headers: { \"content-type\": \"application/json\" },\n });\n const path = new URL(req.url).pathname.replace(/\\/+$/, \"\") || \"/\";\n\n try {\n if (req.method === \"GET\" && path === \"/\") {\n const h = ((await blob.getJSON(KEY)) as Day[]) ?? [];\n return json({\n ok: true,\n service: \"syncHistory\",\n dataset: DATASET,\n schema: \"ohlcv-1m\",\n keyConfigured: !!Deno.env.get(\"DATABENTO_API_KEY\"),\n stored: h.length,\n newest: h[0]?.date ?? null,\n oldest: h[h.length - 1]?.date ?? null,\n });\n }\n\n // Price the pull before spending anything. Metadata calls are not billed.\n if (req.method === \"GET\" && path === \"/cost\") {\n const u = new URL(req.url);\n const days = Number(u.searchParams.get(\"days\") ?? 30);\n const symbol = u.searchParams.get(\"symbol\") ?? DEFAULT_SYMBOL;\n const { start, end } = range(days);\n const cost = await db(\"metadata.get_cost\", {\n dataset: DATASET,\n symbols: symbol,\n schema: \"ohlcv-1m\",\n stype_in: \"continuous\",\n start,\n end,\n });\n const size = await db(\"metadata.get_billable_size\", {\n dataset: DATASET,\n symbols: symbol,\n schema: \"ohlcv-1m\",\n stype_in: \"continuous\",\n start,\n end,\n });\n return json({\n ok: true,\n symbol,\n days,\n start,\n end,\n costUsd: Number(cost),\n billableBytes: Number(size),\n });\n }\n\n if (req.method === \"POST\" && (path === \"/sync\" || path === \"/sync/daily\")) {\n const b = await req.json().catch(() => ({}));\n const symbol = b.symbol ?? DEFAULT_SYMBOL;\n // Daily top-up needs a few days of slack for weekends and holidays.\n const days = path === \"/sync/daily\" ? (b.days ?? 5) : (b.days ?? 32);\n\n const bars = await fetchBars(symbol, days);\n const fresh = foldSessions(bars);\n if (!fresh.length) {\n return json({\n ok: false,\n error: \"no complete RTH sessions returned\",\n bars: bars.length,\n }, 422);\n }\n\n const existing = ((await blob.getJSON(KEY)) as Day[]) ?? [];\n // Fresh first so a corrected session overrides the stored one.\n const merged = normalise([...fresh, ...existing]);\n await blob.setJSON(KEY, merged);\n\n return json({\n ok: true,\n mode: path === \"/sync/daily\" ? \"daily\" : \"backfill\",\n symbol,\n barsFetched: bars.length,\n sessionsParsed: fresh.length,\n stored: merged.length,\n newest: merged[0]?.date,\n oldest: merged[merged.length - 1]?.date,\n ready: merged.length >= 22,\n });\n }\n\n return json(\n { ok: false, error: `no route for ${req.method} ${path}` },\n 404,\n );\n } catch (e) {\n return json({\n ok: false,\n error: String(e instanceof Error ? e.message : e),\n }, 500);\n }\n}","label",[142],"3ae13b9d-0be8-43d8-bdf8-6281bb467cec",["D",1787915818438],"curl -s -X POST 'https://jfkll--0e439a08a2d011f1b6081607ee4eb77e.web.val.run/sync/daily'",[173],"ca112034-c665-4ab1-9429-b5e51da7c886",["D",1787912642689],"/**\n * rangeLadder v2 — calibrated expected-range ladder for NQ RTH, with server-side history.\n * Val.town HTTP val. Replaces v1 wholesale; v1's stateless POST still works unchanged.\n *\n * Model: log(RTH range %) ~ HAR-RV(1d,5d,22d) + log(Asia range %) + log(Europe range %)\n * Fit: 2244 NQ trade days, walk-forward OOS R2 = 0.547\n * Anchor: RTH open (MAD 0.322 sigma vs 0.488 for settlement)\n *\n * ROUTES\n * GET / health check + history status\n * GET /history inspect the stored window\n * POST / compute ladder (omit rthRanges/rthOpens to use stored history)\n * POST /history append one realized session {date,rthRange,rthOpen}\n * POST /history/bulk one-time backfill {days:[{date,rthRange,rthOpen},...]}\n * DELETE /history wipe (dev only)\n *\n * The JAR should: GET / on startup, and if history.ready is false or history.stale\n * is true, read 22 sessions off the chart and POST /history/bulk once. Thereafter\n * POST /history once per session with the day that just closed.\n */\n\nimport { blob } from \"https://esm.town/v/std/blob\";\n\nconst KEY = \"rangeLadder:history:v1\";\nconst WINDOW = 22; // days the model needs\nconst KEEP = 45; // days retained, gives headroom for gaps/holidays\nconst STALE_DAYS = 5; // newest entry older than this => flag for re-backfill\n\nconst COEF = {\n const: 0.321487,\n lp: 0.115356, // prior day log range %\n m5: 0.267034, // 5d mean log range %\n m22: 0.114478, // 22d mean log range %\n la: 0.144729, // Asia log range %\n le: 0.247273, // Europe log range %\n};\n\nconst RESID_SD = 0.385;\n\n// k -> [empirical touch probability, 80th-pct overshoot in sigma units]\nconst LADDER: Array<[number, number, number]> = [\n [0.15, 0.808, 0.794],\n [0.20, 0.743, 0.780],\n [0.25, 0.678, 0.769],\n [0.30, 0.622, 0.754],\n [0.35, 0.573, 0.735],\n [0.40, 0.529, 0.718],\n [0.45, 0.487, 0.706],\n [0.50, 0.440, 0.695],\n [0.55, 0.397, 0.691],\n [0.60, 0.359, 0.687],\n [0.65, 0.323, 0.680],\n [0.70, 0.291, 0.673],\n [0.75, 0.259, 0.671],\n [0.80, 0.231, 0.669],\n [0.85, 0.205, 0.676],\n [0.90, 0.183, 0.684],\n [0.95, 0.162, 0.693],\n [1.00, 0.143, 0.702],\n [1.10, 0.110, 0.707],\n [1.20, 0.088, 0.700],\n [1.30, 0.070, 0.676],\n [1.40, 0.056, 0.692],\n [1.50, 0.045, 0.658],\n [1.60, 0.036, 0.622],\n [1.70, 0.029, 0.557],\n [1.80, 0.023, 0.601],\n];\n\nconst RUNGS = [0.30, 0.45, 0.60, 0.80, 1.00, 1.30];\nconst GATE = { gap: [0.204, 0.476], ovn: [0.599, 0.774] };\n\nconst GATE_STATS: Record = {\n GREEN: {\n fadeWin: 0.556,\n note: \"quiet ON + small gap — fades viable, edge is thin (n=162)\",\n },\n AMBER: {\n fadeWin: 0.416,\n note: \"mixed — no fade edge, levels are targets only\",\n },\n RED: { fadeWin: 0.186, note: \"large gap — do NOT fade, trend day risk\" },\n};\n\n// ---------------------------------------------------------------- history --\n\ntype Day = { date: string; rthRange: number; rthOpen: number };\n\nasync function loadHistory(): Promise {\n try {\n const h = await blob.getJSON(KEY);\n return Array.isArray(h) ? h : [];\n } catch {\n return [];\n }\n}\n\nconst ISO_DATE = /^\\d{4}-\\d{2}-\\d{2}$/;\n\n/**\n * Newest first, de-duplicated by date, trimmed to KEEP.\n * FIRST occurrence of a date wins: callers put the authoritative record first\n * (the append route prepends the new session), so a re-post of a corrected\n * session must override the stored one rather than be discarded by it.\n */\nfunction normalise(days: Day[]): Day[] {\n const seen = new Map();\n for (const d of days) {\n if (!d?.date || !ISO_DATE.test(d.date)) continue;\n if (Number.isNaN(Date.parse(d.date + \"T00:00:00Z\"))) continue;\n if (!(d.rthRange > 0) || !(d.rthOpen > 0)) continue;\n if (seen.has(d.date)) continue;\n seen.set(d.date, {\n date: d.date,\n rthRange: +d.rthRange,\n rthOpen: +d.rthOpen,\n });\n }\n return [...seen.values()]\n .sort((a, b) => (a.date < b.date ? 1 : -1))\n .slice(0, KEEP);\n}\n\nasync function saveHistory(days: Day[]): Promise {\n const clean = normalise(days);\n await blob.setJSON(KEY, clean);\n return clean;\n}\n\nfunction historyStatus(h: Day[]) {\n const newest = h[0]?.date ?? null;\n const ageDays = newest\n ? Math.floor((Date.now() - Date.parse(newest + \"T00:00:00Z\")) / 86_400_000)\n : null;\n\n // Chart-sourced history develops holes on days MotiveWave isn't opened.\n // Count size lies in that case: 22 entries can span far more than 22 sessions.\n // Flag it by comparing the window's calendar span against expected weekdays.\n let gaps: string[] = [];\n const win = h.slice(0, WINDOW);\n if (win.length >= 2) {\n for (let i = 0; i < win.length - 1; i++) {\n const a = Date.parse(win[i].date + \"T00:00:00Z\");\n const b = Date.parse(win[i + 1].date + \"T00:00:00Z\");\n let weekdays = 0;\n for (let t = b + 86_400_000; t < a; t += 86_400_000) {\n const wd = new Date(t).getUTCDay();\n if (wd !== 0 && wd !== 6) weekdays++;\n }\n // >2 intervening weekdays is more than a holiday; treat as a real hole.\n if (weekdays > 2) gaps.push(`${win[i + 1].date}..${win[i].date}`);\n }\n }\n\n return {\n ready: h.length >= WINDOW,\n count: h.length,\n needed: WINDOW,\n newest,\n oldest: h[h.length - 1]?.date ?? null,\n ageDays,\n stale: ageDays === null ? true : ageDays > STALE_DAYS,\n contiguous: gaps.length === 0,\n gaps,\n dates: win.map((d) => d.date),\n };\n}\n\n// ---------------------------------------------------------------- compute --\n\nfunction interp(k: number, col: 1 | 2): number {\n if (k <= LADDER[0][0]) return LADDER[0][col];\n const last = LADDER[LADDER.length - 1];\n if (k >= last[0]) return last[col];\n for (let i = 0; i < LADDER.length - 1; i++) {\n const a = LADDER[i], b = LADDER[i + 1];\n if (k >= a[0] && k <= b[0]) {\n const t = (k - a[0]) / (b[0] - a[0]);\n return a[col] + t * (b[col] - a[col]);\n }\n }\n return last[col];\n}\n\nconst mean = (a: number[]) => a.reduce((s, x) => s + x, 0) / a.length;\nconst round2 = (x: number) => Math.round(x * 100) / 100;\nconst snap = (px: number, tick: number, grid: number) =>\n grid > 0 ? Math.round(px / grid) * grid : Math.round(px / tick) * tick;\n\nexport function computeLadder(b: any, history: Day[] = []) {\n const tick = b.tickSize ?? 0.25;\n const grid = b.strikeGrid ?? 0;\n\n if (!(b.open > 0)) throw new Error(\"open is required and must be positive\");\n if (!(b.asiaRange > 0) || !(b.euRange > 0)) {\n throw new Error(\"asiaRange and euRange are required and must be positive\");\n }\n\n // Inline history wins if supplied (stateless mode); otherwise use the store.\n let ranges: number[], opens: number[], source: string;\n if (b.rthRanges?.length >= WINDOW && b.rthOpens?.length >= WINDOW) {\n ranges = b.rthRanges.slice(0, WINDOW);\n opens = b.rthOpens.slice(0, WINDOW);\n source = \"request\";\n } else if (history.length >= WINDOW) {\n ranges = history.slice(0, WINDOW).map((d) => d.rthRange);\n opens = history.slice(0, WINDOW).map((d) => d.rthOpen);\n source = \"store\";\n } else {\n throw new Error(\n `need ${WINDOW} prior sessions: store has ${history.length}. ` +\n `POST /history/bulk to backfill, or pass rthRanges/rthOpens inline.`,\n );\n }\n\n // Ranges -> % of that day's open -> logs. Scale-free, so it stays valid as\n // NQ's price level drifts across years.\n const lrPct = ranges.map((r, i) => Math.log((100 * r) / opens[i]));\n const lp = lrPct[0];\n const m5 = mean(lrPct.slice(0, 5));\n const m22 = mean(lrPct.slice(0, 22));\n const la = Math.log((100 * b.asiaRange) / b.open);\n const le = Math.log((100 * b.euRange) / b.open);\n\n const logSigPct = COEF.const + COEF.lp * lp + COEF.m5 * m5 + COEF.m22 * m22 +\n COEF.la * la + COEF.le * le;\n\n const sigma = (Math.exp(logSigPct) / 100) * b.open;\n const sigLo = (Math.exp(logSigPct - RESID_SD) / 100) * b.open;\n const sigHi = (Math.exp(logSigPct + RESID_SD) / 100) * b.open;\n\n const gapSig = b.prevSettle ? Math.abs(b.open - b.prevSettle) / sigma : 0;\n const ovnSig = b.ovnRange ? b.ovnRange / sigma : 0;\n let state: \"GREEN\" | \"AMBER\" | \"RED\";\n if (gapSig > GATE.gap[1] || ovnSig > GATE.ovn[1]) state = \"RED\";\n else if (gapSig < GATE.gap[0] && ovnSig < GATE.ovn[0]) state = \"GREEN\";\n else state = \"AMBER\";\n\n const levels = RUNGS.flatMap((k) => {\n const dist = k * sigma;\n const touch = interp(k, 1);\n const band = interp(k, 2) * sigma; // 80th-pct overshoot — the honest error bar\n return [\n {\n side: \"up\",\n k,\n price: snap(b.open + dist, tick, grid),\n touchProb: round2(touch * 100),\n bandOuter: snap(b.open + dist + band, tick, grid),\n },\n {\n side: \"dn\",\n k,\n price: snap(b.open - dist, tick, grid),\n touchProb: round2(touch * 100),\n bandOuter: snap(b.open - dist - band, tick, grid),\n },\n ];\n });\n\n return {\n ok: true,\n model: \"HAR+Asia+Europe\",\n historySource: source,\n anchor: snap(b.open, tick, grid),\n sigma: round2(sigma),\n sigmaLo: round2(sigLo),\n sigmaHi: round2(sigHi),\n gate: {\n state,\n gapSigma: round2(gapSig),\n ovnSigma: round2(ovnSig),\n fadeWinRate: GATE_STATS[state].fadeWin,\n note: GATE_STATS[state].note,\n },\n levels,\n // Seams for v3 — JAR renders these when non-null, ignores them otherwise.\n impliedEM: null,\n gammaState: null,\n disclaimer:\n \"Levels are probability targets, not entries. No pivot or ladder \" +\n \"level showed a standalone fade edge in 12y of NQ.\",\n };\n}\n\n// ----------------------------------------------------------------- routes --\n\nexport default async function (req: Request): Promise {\n const json = (o: unknown, s = 200) =>\n new Response(JSON.stringify(o), {\n status: s,\n headers: { \"content-type\": \"application/json\" },\n });\n\n const path = new URL(req.url).pathname.replace(/\\/+$/, \"\") || \"/\";\n\n try {\n if (req.method === \"GET\" && path === \"/\") {\n return json({\n ok: true,\n service: \"rangeLadder\",\n version: 2,\n model: \"HAR+Asia+Europe\",\n oosR2: 0.547,\n history: historyStatus(await loadHistory()),\n });\n }\n\n if (req.method === \"GET\" && path === \"/history\") {\n const h = await loadHistory();\n return json({ ok: true, ...historyStatus(h), days: h });\n }\n\n if (req.method === \"DELETE\" && path === \"/history\") {\n await saveHistory([]);\n return json({ ok: true, cleared: true });\n }\n\n if (req.method === \"POST\" && path === \"/history/bulk\") {\n const b = await req.json();\n if (!Array.isArray(b?.days) || !b.days.length) {\n return json({ ok: false, error: \"days[] required\" }, 400);\n }\n // Replaces the window outright — this is a backfill, not an append.\n const h = await saveHistory(b.days);\n return json({ ok: true, mode: \"bulk\", ...historyStatus(h) });\n }\n\n if (req.method === \"POST\" && path === \"/history\") {\n const b = await req.json();\n if (!b?.date || !(b.rthRange > 0) || !(b.rthOpen > 0)) {\n return json(\n { ok: false, error: \"date, rthRange and rthOpen required\" },\n 400,\n );\n }\n const existing = await loadHistory();\n // normalise() de-dupes by date, so a repeated post for the same session\n // overwrites rather than double-counting.\n const h = await saveHistory([{\n date: b.date,\n rthRange: b.rthRange,\n rthOpen: b.rthOpen,\n }, ...existing]);\n return json({ ok: true, mode: \"append\", ...historyStatus(h) });\n }\n\n if (req.method === \"POST\" && path === \"/\") {\n const b = await req.json();\n const h = await loadHistory();\n const out = computeLadder(b, h);\n const st = historyStatus(h);\n return json(\n out.historySource === \"store\" && st.stale\n ? 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