[{"data":1,"prerenderedAt":4159},["ShallowReactive",2],{"wrun-open-editor-url":3,"indicators:core-concepts/lambdas-and-reducers":4},"https://openmarket.xyz/chart/#wrun-open=v1",{"slug":5,"filePath":6,"frontmatter":7,"rawMarkdown":12,"tree":13},"core-concepts/lambdas-and-reducers","core-concepts/lambdas-and-reducers.md",{"title":8,"description":9,"order":10,"section":11},"Lambdas and reducers","Arrow functions, function values, and the loops that do the work of the reducer methods (map, filter, reduce, forEach, some, every). A wrun indicator has arrow…",21,"core-concepts","---\ntitle: \"Lambdas and reducers\"\ndescription: \"Arrow functions, function values, and the loops that do the work of the reducer methods (map, filter, reduce, forEach, some, every). A wrun indicator has arrow…\"\norder: 21\nsection: \"core-concepts\"\n---\n\n\u003C!-- source: docs/indicators/core-concepts/lambdas-and-reducers.md; generated by packages/cli/scripts/gen-indicator-docs.ts, do not edit -->\n\n# Lambdas and reducers\n\nArrow functions, function values, and the loops that do the work of the\nreducer methods (`map`, `filter`, `reduce`, `forEach`, `some`, `every`).\nA wrun indicator has arrow functions, with one rule that changes how you\nuse them: a function cannot capture a local variable, so the \"closure\" is\nmodule-level state and a reducer is a plain loop over a buffer.\n\n## Lambda syntax\n\nAn arrow function has typed parameters and a typed return, in either the\nexpression or the block form. It is a value: store it in a variable typed\n`(x: f64) => f64`, pass it to a function, call it.\n\n```text\nconst double = (x: f64): f64 => x * 2.0;\nconst label = (side: f64): string => {\n  return side > 0.0 ? \"bid\" : \"ask\";\n};\n\nlet pick: (x: f64) => bool = above;   // a named function is a value too\nconst y = double(21.0);               // 42\n```\n\nBoth forms need every type written out: an untyped parameter or a missing\nreturn type is a parse error (`Type expected.`).\n\n## The one rule: no captured locals\n\nThe JavaScript habit is a lambda that closes over the surrounding scope:\n`const threshold = high * 0.99; prices.filter((p) => p > threshold)`. In\nan indicator that exact shape, an arrow function inside `onBar()` reading\na `const` of `onBar()`, is refused at compile time:\n\n```text\nERROR AS100: Not implemented: Closures\n```\n\nThe compiler cannot build a function that carries a copy of another\nfunction's locals. What a function **can** read is module-level state,\nwhich is where an indicator keeps everything that matters anyway. So the\npattern is: put the threshold in a module-level `let`, write the predicate\nas a named function (or an arrow at module scope), and pass it.\n\n```typescript sample=cc-lambdas-pointer\nparam(\"bars\", 20, { min: 1, max: 200, description: \"Bars in the window\" });\noutput(\"above_count\", line, lower, { color: \"#16a34a\", description: \"Bars in the window closing above the window mean\" });\noutput(\"near_high_count\", line, lower, { color: \"#f59e0b\", description: \"Bars in the window within 1% of the window high\" });\n\nconst MAX_BARS = 200;\nconst closes = new StaticArray\u003Cf64>(MAX_BARS);\nlet n: i32 = 20;\nlet cursor: i32 = 0;\nlet count: i32 = 0;\nlet mean: f64 = NaN; // module-level: the \"closure\" every predicate reads\nlet nearHighLevel: f64 = NaN;\n\n// Predicates are named functions over module-level state, never over a local.\nfunction aboveMean(x: f64): bool {\n  return x > mean;\n}\n\nfunction nearHigh(x: f64): bool {\n  return x >= nearHighLevel;\n}\n\n// A reducer is a loop that takes the predicate as a value.\nfunction countWhere(xs: StaticArray\u003Cf64>, len: i32, pred: (x: f64) => bool): i32 {\n  let hits = 0;\n  for (let i = 0; i \u003C len; i++) if (pred(xs[i])) hits += 1;\n  return hits;\n}\n\nfunction windowMax(xs: StaticArray\u003Cf64>, len: i32): f64 {\n  let m = -Infinity;\n  for (let i = 0; i \u003C len; i++) if (xs[i] > m) m = xs[i];\n  return m;\n}\n\nfunction windowMean(xs: StaticArray\u003Cf64>, len: i32): f64 {\n  let s = 0.0;\n  for (let i = 0; i \u003C len; i++) s += xs[i];\n  return s / f64(len);\n}\n\nfunction onStart(): void {\n  n = i32(p_bars());\n}\n\nfunction onBar(): void {\n  closes[cursor] = bar.close();\n  cursor = (cursor + 1) % n;\n  if (count \u003C n) count += 1;\n  if (count \u003C n) return;\n  mean = windowMean(closes, n);\n  nearHighLevel = windowMax(closes, n) * 0.99;\n  out_above_count(f64(countWhere(closes, n, aboveMean)));\n  out_near_high_count(f64(countWhere(closes, n, nearHigh)));\n}\n```\n\n`countWhere` is the reducer; `aboveMean` and `nearHigh` are the lambdas,\nreading `mean` and `nearHighLevel` from module scope instead of capturing\nthem. The same function value can be passed to any loop that takes a\n`(x: f64) => bool`.\n\n## The reducer methods\n\n`Array\u003Cf64>` has the familiar methods, and each callback is a non-capturing\nfunction with typed parameters (trailing parameters may be omitted):\n\n| Method | Callback | Returns | Allocates? |\n| --- | --- | --- | --- |\n| `map\u003CU>(fn)` | `(value: f64, index?: i32) => U` | a new array | yes |\n| `filter(fn)` | `(value: f64, index?: i32) => bool` | a new array | yes |\n| `reduce\u003CU>(fn, initial)` | `(acc: U, value: f64, index?: i32) => U` | the final accumulator | no |\n| `forEach(fn)` | `(value: f64, index?: i32) => void` | nothing | no |\n| `findIndex(fn)` | `(value: f64, index?: i32) => bool` | the first matching index, or `-1` | no |\n| `some(fn)` | `(value: f64, index?: i32) => bool` | `true` if any match | no |\n| `every(fn)` | `(value: f64, index?: i32) => bool` | `true` if all match | no |\n\nThere is no `find`: use `findIndex` and read the element. `map` and\n`filter` return a **new** array every call, and the module never frees\nmemory, so they belong in `onStart()` (building a lookup table once) and not\nin `onBar()`. On the per-bar path, write the loop over a `StaticArray` you\nallocated once; the window example above is the template, and\n`collections.md` has every numeric reducer as a method.\n\n```text\n// onStart(): fine, once\nconst doubled = periods.map\u003Cf64>((p: f64): f64 => p * 2.0);\n\n// onBar(): a loop over a preallocated buffer, no allocation\nlet sum = 0.0;\nfor (let i = 0; i \u003C n; i++) sum += window[i];\n```\n\n## The microstructure idiom\n\nWhere you would reach for a `map` and a `reduce` over order-flow rows\n(buy minus sell per bucket, summed), an indicator reads the bar's cells\n(one `[low, high, buy, sell]` row per price bucket) through the input's\nview and loops over them: the net delta of the bar, and the price of its\nlargest-volume bucket (the point of control).\n\n```typescript sample=cc-lambdas-delta\ninput(\"close\", ohlcv.close);\ninput(\"profile\", volume_profile.cells, { max_cells: 8192 });\noutput(\"delta\", line, lower, { color: \"#2563eb\", description: \"Net per-bar delta: buy minus sell volume across every price bucket\" });\noutput(\"poc\", line, overlay, { color: \"#f59e0b\", description: \"Price of the bucket that traded the most volume\" });\n\nfunction onBar(): void {\n  const n = in_profile_cells();\n  if (n \u003C= 0) return; // no block this bar\n  const cells = in_profile_view(); // max_cells tuples of 4 f64; only the first n values are this bar's\n  let net = 0.0;\n  let best = -1.0;\n  let bestPrice = NaN;\n  for (let i = 0; i + 3 \u003C n; i += 4) {\n    const buy = cells[i + 2];\n    const sell = cells[i + 3];\n    net += buy - sell; // the map + reduce, as one pass\n    if (buy + sell > best) {\n      best = buy + sell;\n      bestPrice = (cells[i] + cells[i + 1]) / 2.0; // the bucket's midpoint\n    }\n  }\n  out_delta(net);\n  out_poc(bestPrice);\n}\n```\n\nEvery windowed class in the TA kit accepts any number, so `rsi.update(delta)`\nis a delta-RSI in one line. The celled input, its accessors, and the\n`max_cells` contract are in `data-sources.md`.\n\n## Loops still exist, and you bound them\n\n`for`, `while`, and `do` are the iteration tools (`for...of` is not\nimplemented: `Not implemented: Iterators`, so index loops it is). There is\nno per-loop ceiling inside the module; size every loop by a param with a\ndeclared `max`. A loop that runs away is stopped by the host's execution\ntimeout and the evaluation is refused: it cannot hang the chart, and it\ncannot produce a value either.\n",{"type":14,"children":15,"data":4152,"position":4154},"root",[16,26,29,30,165,166,184,185,219,220,298,299,335,336,352,353,446,447,464,465,521,522,2138,2139,2258,2259,2274,2275,2302,2304,2929,2930,3112,3113,3174,3175,3189,3190,3259,3260,3947,3948,4016,4017,4032,4033],{"type":17,"value":18,"position":19},"comment"," source: docs/indicators/core-concepts/lambdas-and-reducers.md; generated by packages/cli/scripts/gen-indicator-docs.ts, do not edit ",{"start":20,"end":23},{"line":21,"column":21,"offset":22},1,0,{"line":21,"column":24,"offset":25},141,140,{"type":27,"value":28},"text","\n",{"type":27,"value":28},{"type":31,"tagName":32,"properties":33,"children":34,"position":162},"element","p",{},[35,45,59,66,79,85,98,104,117,123,136,142,155],{"type":27,"value":36,"position":37},"Arrow functions, function values, and the loops that do the work of the\nreducer methods (",{"start":38,"end":41},{"line":39,"column":21,"offset":40},5,166,{"line":42,"column":43,"offset":44},6,18,255,{"type":31,"tagName":46,"properties":47,"children":48,"position":56},"code",{},[49],{"type":27,"value":50,"position":51},"map",{"start":52,"end":53},{"line":42,"column":43,"offset":44},{"line":42,"column":54,"offset":55},23,260,{"start":57,"end":58},{"line":42,"column":43,"offset":44},{"line":42,"column":54,"offset":55},{"type":27,"value":60,"position":61},", ",{"start":62,"end":63},{"line":42,"column":54,"offset":55},{"line":42,"column":64,"offset":65},25,262,{"type":31,"tagName":46,"properties":67,"children":68,"position":76},{},[69],{"type":27,"value":70,"position":71},"filter",{"start":72,"end":73},{"line":42,"column":64,"offset":65},{"line":42,"column":74,"offset":75},33,270,{"start":77,"end":78},{"line":42,"column":64,"offset":65},{"line":42,"column":74,"offset":75},{"type":27,"value":60,"position":80},{"start":81,"end":82},{"line":42,"column":74,"offset":75},{"line":42,"column":83,"offset":84},35,272,{"type":31,"tagName":46,"properties":86,"children":87,"position":95},{},[88],{"type":27,"value":89,"position":90},"reduce",{"start":91,"end":92},{"line":42,"column":83,"offset":84},{"line":42,"column":93,"offset":94},43,280,{"start":96,"end":97},{"line":42,"column":83,"offset":84},{"line":42,"column":93,"offset":94},{"type":27,"value":60,"position":99},{"start":100,"end":101},{"line":42,"column":93,"offset":94},{"line":42,"column":102,"offset":103},45,282,{"type":31,"tagName":46,"properties":105,"children":106,"position":114},{},[107],{"type":27,"value":108,"position":109},"forEach",{"start":110,"end":111},{"line":42,"column":102,"offset":103},{"line":42,"column":112,"offset":113},54,291,{"start":115,"end":116},{"line":42,"column":102,"offset":103},{"line":42,"column":112,"offset":113},{"type":27,"value":60,"position":118},{"start":119,"end":120},{"line":42,"column":112,"offset":113},{"line":42,"column":121,"offset":122},56,293,{"type":31,"tagName":46,"properties":124,"children":125,"position":133},{},[126],{"type":27,"value":127,"position":128},"some",{"start":129,"end":130},{"line":42,"column":121,"offset":122},{"line":42,"column":131,"offset":132},62,299,{"start":134,"end":135},{"line":42,"column":121,"offset":122},{"line":42,"column":131,"offset":132},{"type":27,"value":60,"position":137},{"start":138,"end":139},{"line":42,"column":131,"offset":132},{"line":42,"column":140,"offset":141},64,301,{"type":31,"tagName":46,"properties":143,"children":144,"position":152},{},[145],{"type":27,"value":146,"position":147},"every",{"start":148,"end":149},{"line":42,"column":140,"offset":141},{"line":42,"column":150,"offset":151},71,308,{"start":153,"end":154},{"line":42,"column":140,"offset":141},{"line":42,"column":150,"offset":151},{"type":27,"value":156,"position":157},").\nA wrun indicator has arrow functions, with one rule that changes how you\nuse them: a function cannot capture a local variable, so the \"closure\" is\nmodule-level state and a reducer is a plain loop over a buffer.",{"start":158,"end":159},{"line":42,"column":150,"offset":151},{"line":160,"column":140,"offset":161},9,521,{"start":163,"end":164},{"line":39,"column":21,"offset":40},{"line":160,"column":140,"offset":161},{"type":27,"value":28},{"type":31,"tagName":167,"properties":168,"children":169,"position":180},"h2",{},[170],{"type":27,"value":171,"position":172},"Lambda syntax",{"start":173,"end":177},{"line":174,"column":175,"offset":176},11,4,526,{"line":174,"column":178,"offset":179},17,539,{"start":181,"end":183},{"line":174,"column":21,"offset":182},523,{"line":174,"column":178,"offset":179},{"type":27,"value":28},{"type":31,"tagName":32,"properties":186,"children":187,"position":216},{},[188,197,209],{"type":27,"value":189,"position":190},"An arrow function has typed parameters and a typed return, in either the\nexpression or the block form. It is a value: store it in a variable typed\n",{"start":191,"end":194},{"line":192,"column":21,"offset":193},13,541,{"line":195,"column":21,"offset":196},15,688,{"type":31,"tagName":46,"properties":198,"children":199,"position":206},{},[200],{"type":27,"value":201,"position":202},"(x: f64) => f64",{"start":203,"end":204},{"line":195,"column":21,"offset":196},{"line":195,"column":43,"offset":205},705,{"start":207,"end":208},{"line":195,"column":21,"offset":196},{"line":195,"column":43,"offset":205},{"type":27,"value":210,"position":211},", pass it to a function, call it.",{"start":212,"end":213},{"line":195,"column":43,"offset":205},{"line":195,"column":214,"offset":215},51,738,{"start":217,"end":218},{"line":192,"column":21,"offset":193},{"line":195,"column":214,"offset":215},{"type":27,"value":28},{"type":14,"children":221},[222],{"type":31,"tagName":223,"properties":224,"children":228,"data":-1},"pre",{"class":225,"style":226,"tabindex":227},"shiki shiki-themes github-dark github-light","--shiki-dark:#e1e4e8;--shiki-light:#24292e;--shiki-dark-bg:#24292e;--shiki-light-bg:#fff","0",[229],{"type":31,"tagName":46,"properties":230,"children":233},{"class":231},[232],"language-text",[234,244,245,253,254,262,263,271,272,280,281,289,290],{"type":31,"tagName":235,"properties":236,"children":238},"span",{"class":237},"line",[239],{"type":31,"tagName":235,"properties":240,"children":241},{},[242],{"type":27,"value":243},"const double = (x: f64): f64 => x * 2.0;",{"type":27,"value":28},{"type":31,"tagName":235,"properties":246,"children":247},{"class":237},[248],{"type":31,"tagName":235,"properties":249,"children":250},{},[251],{"type":27,"value":252},"const label = (side: f64): string => {",{"type":27,"value":28},{"type":31,"tagName":235,"properties":255,"children":256},{"class":237},[257],{"type":31,"tagName":235,"properties":258,"children":259},{},[260],{"type":27,"value":261},"  return side > 0.0 ? \"bid\" : \"ask\";",{"type":27,"value":28},{"type":31,"tagName":235,"properties":264,"children":265},{"class":237},[266],{"type":31,"tagName":235,"properties":267,"children":268},{},[269],{"type":27,"value":270},"};",{"type":27,"value":28},{"type":31,"tagName":235,"properties":273,"children":274},{"class":237},[275],{"type":31,"tagName":235,"properties":276,"children":277},{},[278],{"type":27,"value":279},"",{"type":27,"value":28},{"type":31,"tagName":235,"properties":282,"children":283},{"class":237},[284],{"type":31,"tagName":235,"properties":285,"children":286},{},[287],{"type":27,"value":288},"let pick: (x: f64) => bool = above;   // a named function is a value too",{"type":27,"value":28},{"type":31,"tagName":235,"properties":291,"children":292},{"class":237},[293],{"type":31,"tagName":235,"properties":294,"children":295},{},[296],{"type":27,"value":297},"const y = double(21.0);               // 42",{"type":27,"value":28},{"type":31,"tagName":32,"properties":300,"children":301,"position":332},{},[302,312,325],{"type":27,"value":303,"position":304},"Both forms need every type written out: an untyped parameter or a missing\nreturn type is a parse error (",{"start":305,"end":308},{"line":306,"column":21,"offset":307},27,991,{"line":309,"column":310,"offset":311},28,31,1095,{"type":31,"tagName":46,"properties":313,"children":314,"position":322},{},[315],{"type":27,"value":316,"position":317},"Type expected.",{"start":318,"end":319},{"line":309,"column":310,"offset":311},{"line":309,"column":320,"offset":321},47,1111,{"start":323,"end":324},{"line":309,"column":310,"offset":311},{"line":309,"column":320,"offset":321},{"type":27,"value":326,"position":327},").",{"start":328,"end":329},{"line":309,"column":320,"offset":321},{"line":309,"column":330,"offset":331},49,1113,{"start":333,"end":334},{"line":306,"column":21,"offset":307},{"line":309,"column":330,"offset":331},{"type":27,"value":28},{"type":31,"tagName":167,"properties":337,"children":338,"position":348},{},[339],{"type":27,"value":340,"position":341},"The one rule: no captured locals",{"start":342,"end":345},{"line":343,"column":175,"offset":344},30,1118,{"line":343,"column":346,"offset":347},36,1150,{"start":349,"end":351},{"line":343,"column":21,"offset":350},1115,{"line":343,"column":346,"offset":347},{"type":27,"value":28},{"type":31,"tagName":32,"properties":354,"children":355,"position":443},{},[356,364,377,385,398,405,418,425,436],{"type":27,"value":357,"position":358},"The JavaScript habit is a lambda that closes over the surrounding scope:\n",{"start":359,"end":362},{"line":360,"column":21,"offset":361},32,1152,{"line":74,"column":21,"offset":363},1225,{"type":31,"tagName":46,"properties":365,"children":366,"position":374},{},[367],{"type":27,"value":368,"position":369},"const threshold = high * 0.99; prices.filter((p) => p > threshold)",{"start":370,"end":371},{"line":74,"column":21,"offset":363},{"line":74,"column":372,"offset":373},69,1293,{"start":375,"end":376},{"line":74,"column":21,"offset":363},{"line":74,"column":372,"offset":373},{"type":27,"value":378,"position":379},". 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