@trap_stevo/metrictide
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Unlock powerful analytics through this modular, event-driven solution built for real-time metric tracking, aggregation, and forecasting. Capture actionable trends, segment data with flexible tag structures, and generate predictive insights using built-in
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JavaScript
;
function _typeof(o) { "@babel/helpers - typeof"; return _typeof = "function" == typeof Symbol && "symbol" == typeof Symbol.iterator ? function (o) { return typeof o; } : function (o) { return o && "function" == typeof Symbol && o.constructor === Symbol && o !== Symbol.prototype ? "symbol" : typeof o; }, _typeof(o); }
function _createForOfIteratorHelper(r, e) { var t = "undefined" != typeof Symbol && r[Symbol.iterator] || r["@@iterator"]; if (!t) { if (Array.isArray(r) || (t = _unsupportedIterableToArray(r)) || e && r && "number" == typeof r.length) { t && (r = t); var _n = 0, F = function F() {}; return { s: F, n: function n() { return _n >= r.length ? { done: !0 } : { done: !1, value: r[_n++] }; }, e: function e(r) { throw r; }, f: F }; } throw new TypeError("Invalid attempt to iterate non-iterable instance.\nIn order to be iterable, non-array objects must have a [Symbol.iterator]() method."); } var o, a = !0, u = !1; return { s: function s() { t = t.call(r); }, n: function n() { var r = t.next(); return a = r.done, r; }, e: function e(r) { u = !0, o = r; }, f: function f() { try { a || null == t["return"] || t["return"](); } finally { if (u) throw o; } } }; }
function _toConsumableArray(r) { return _arrayWithoutHoles(r) || _iterableToArray(r) || _unsupportedIterableToArray(r) || _nonIterableSpread(); }
function _nonIterableSpread() { throw new TypeError("Invalid attempt to spread non-iterable instance.\nIn order to be iterable, non-array objects must have a [Symbol.iterator]() method."); }
function _unsupportedIterableToArray(r, a) { if (r) { if ("string" == typeof r) return _arrayLikeToArray(r, a); var t = {}.toString.call(r).slice(8, -1); return "Object" === t && r.constructor && (t = r.constructor.name), "Map" === t || "Set" === t ? Array.from(r) : "Arguments" === t || /^(?:Ui|I)nt(?:8|16|32)(?:Clamped)?Array$/.test(t) ? _arrayLikeToArray(r, a) : void 0; } }
function _iterableToArray(r) { if ("undefined" != typeof Symbol && null != r[Symbol.iterator] || null != r["@@iterator"]) return Array.from(r); }
function _arrayWithoutHoles(r) { if (Array.isArray(r)) return _arrayLikeToArray(r); }
function _arrayLikeToArray(r, a) { (null == a || a > r.length) && (a = r.length); for (var e = 0, n = Array(a); e < a; e++) n[e] = r[e]; return n; }
function _classCallCheck(a, n) { if (!(a instanceof n)) throw new TypeError("Cannot call a class as a function"); }
function _defineProperties(e, r) { for (var t = 0; t < r.length; t++) { var o = r[t]; o.enumerable = o.enumerable || !1, o.configurable = !0, "value" in o && (o.writable = !0), Object.defineProperty(e, _toPropertyKey(o.key), o); } }
function _createClass(e, r, t) { return r && _defineProperties(e.prototype, r), t && _defineProperties(e, t), Object.defineProperty(e, "prototype", { writable: !1 }), e; }
function _toPropertyKey(t) { var i = _toPrimitive(t, "string"); return "symbol" == _typeof(i) ? i : i + ""; }
function _toPrimitive(t, r) { if ("object" != _typeof(t) || !t) return t; var e = t[Symbol.toPrimitive]; if (void 0 !== e) { var i = e.call(t, r || "default"); if ("object" != _typeof(i)) return i; throw new TypeError("@@toPrimitive must return a primitive value."); } return ("string" === r ? String : Number)(t); }
var _require = require("@trap_stevo/timetide"),
toMilliseconds = _require.toMilliseconds;
var MetricTrendManager = /*#__PURE__*/function () {
function MetricTrendManager() {
_classCallCheck(this, MetricTrendManager);
this.records = [];
}
return _createClass(MetricTrendManager, [{
key: "feed",
value: function feed(record) {
this.records.push(record);
}
}, {
key: "clearRecords",
value: function clearRecords() {
var records = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : [];
if (!records.length) {
return 0;
}
var idsToDelete = new Set(records.map(function (r) {
return r.metricID;
}));
this.records = this.records.filter(function (r) {
return !idsToDelete.has(r.metricID);
});
return idsToDelete.size;
}
}, {
key: "clear",
value: function clear() {
this.records = [];
}
}, {
key: "aggregateByName",
value: function aggregateByName(name) {
var filtered = this.records.filter(function (r) {
return r.name === name && typeof r.value === "number";
});
var count = filtered.length;
var sum = filtered.reduce(function (acc, r) {
return acc + r.value;
}, 0);
var avg = count > 0 ? sum / count : 0;
var min = Math.min.apply(Math, _toConsumableArray(filtered.map(function (r) {
return r.value;
})));
var max = Math.max.apply(Math, _toConsumableArray(filtered.map(function (r) {
return r.value;
})));
return {
name: name,
count: count,
sum: sum,
avg: avg,
min: min,
max: max
};
}
}, {
key: "aggregateByType",
value: function aggregateByType(type) {
var filtered = this.records.filter(function (r) {
return r.type === type && typeof r.value === "number";
});
var count = filtered.length;
var sum = filtered.reduce(function (acc, r) {
return acc + r.value;
}, 0);
var avg = count > 0 ? sum / count : 0;
var min = Math.min.apply(Math, _toConsumableArray(filtered.map(function (r) {
return r.value;
})));
var max = Math.max.apply(Math, _toConsumableArray(filtered.map(function (r) {
return r.value;
})));
return {
type: type,
count: count,
sum: sum,
avg: avg,
min: min,
max: max
};
}
}, {
key: "groupByTag",
value: function groupByTag(tagKey) {
var result = {};
var _iterator = _createForOfIteratorHelper(this.records),
_step;
try {
for (_iterator.s(); !(_step = _iterator.n()).done;) {
var _record$tags;
var record = _step.value;
var key = ((_record$tags = record.tags) === null || _record$tags === void 0 ? void 0 : _record$tags[tagKey]) || "undefined";
if (!result[key]) {
result[key] = [];
}
result[key].push(record);
}
} catch (err) {
_iterator.e(err);
} finally {
_iterator.f();
}
return result;
}
}, {
key: "groupByInterval",
value: function groupByInterval(name, interval, rangeMs) {
var method = arguments.length > 3 && arguments[3] !== undefined ? arguments[3] : "sum";
var now = Date.now();
var start = now - rangeMs;
var step = toMilliseconds(interval);
var buckets = {};
var _iterator2 = _createForOfIteratorHelper(this.records),
_step2;
try {
for (_iterator2.s(); !(_step2 = _iterator2.n()).done;) {
var record = _step2.value;
if (record.name !== name || typeof record.value !== "number") {
continue;
}
if (record.timestamp < start || record.timestamp > now) {
continue;
}
var bucket = Math.floor((record.timestamp - start) / step);
if (!buckets[bucket]) {
buckets[bucket] = [];
}
buckets[bucket].push(record.value);
}
} catch (err) {
_iterator2.e(err);
} finally {
_iterator2.f();
}
var points = [];
var totalSteps = Math.ceil(rangeMs / step);
for (var i = 0; i < totalSteps; i++) {
var values = buckets[i] || [];
var y = 0;
if (method === "sum") {
y = values.reduce(function (a, b) {
return a + b;
}, 0);
}
if (method === "avg") {
y = values.length ? values.reduce(function (a, b) {
return a + b;
}, 0) / values.length : 0;
}
if (method === "count") {
y = values.length;
}
if (method === "min") {
y = values.length ? Math.min.apply(Math, _toConsumableArray(values)) : 0;
}
if (method === "max") {
y = values.length ? Math.max.apply(Math, _toConsumableArray(values)) : 0;
}
points.push({
x: start + i * step,
y: y
});
}
return points;
}
}, {
key: "predictNext",
value: function predictNext(name) {
var _toMilliseconds, _toMilliseconds2;
var _ref = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {},
_ref$interval = _ref.interval,
interval = _ref$interval === void 0 ? this.records.length > 100 ? "1m" : "1s" : _ref$interval,
_ref$rangeAdjustmentF = _ref.rangeAdjustmentFactor,
rangeAdjustmentFactor = _ref$rangeAdjustmentF === void 0 ? 3 : _ref$rangeAdjustmentF,
_ref$range = _ref.range,
range = _ref$range === void 0 ? "5m" : _ref$range,
_ref$stepsAhead = _ref.stepsAhead,
stepsAhead = _ref$stepsAhead === void 0 ? Math.max(3, Math.floor(this.records.length / 4)) : _ref$stepsAhead,
_ref$method = _ref.method,
method = _ref$method === void 0 ? "linear" : _ref$method;
var currentRange = (_toMilliseconds = toMilliseconds(range)) !== null && _toMilliseconds !== void 0 ? _toMilliseconds : toMilliseconds("1m");
var now = Date.now();
var step = (_toMilliseconds2 = toMilliseconds(interval)) !== null && _toMilliseconds2 !== void 0 ? _toMilliseconds2 : toMilliseconds("1m");
var start = now - currentRange;
var values = [];
if (step >= currentRange) {
console.log("[MetricTide] ~ Interval larger than range. Adjusting range to ".concat(rangeAdjustmentFactor, "x interval."));
currentRange = step * rangeAdjustmentFactor;
}
var _iterator3 = _createForOfIteratorHelper(this.records),
_step3;
try {
for (_iterator3.s(); !(_step3 = _iterator3.n()).done;) {
var r = _step3.value;
if (r.name !== name || typeof r.value !== "number") {
continue;
}
if (r.timestamp >= start && r.timestamp <= now) {
var bucket = Math.floor((r.timestamp - start) / step);
values[bucket] = values[bucket] || [];
values[bucket].push(r.value);
}
}
} catch (err) {
_iterator3.e(err);
} finally {
_iterator3.f();
}
var series = values.map(function (group) {
return group ? group.reduce(function (a, b) {
return a + b;
}, 0) / group.length : 0;
});
for (var i = 0; i < Math.ceil(currentRange / step); i++) {
if (series[i] === undefined) {
series[i] = 0;
}
}
var N = series.length;
var sumX = series.map(function (_, i) {
return i;
}).reduce(function (a, b) {
return a + b;
}, 0);
var sumY = series.reduce(function (a, b) {
return a + b;
}, 0);
var sumXY = series.map(function (y, i) {
return y * i;
}).reduce(function (a, b) {
return a + b;
}, 0);
var sumX2 = series.map(function (_, i) {
return i * i;
}).reduce(function (a, b) {
return a + b;
}, 0);
var slope = (N * sumXY - sumX * sumY) / (N * sumX2 - sumX * sumX) || 0;
var intercept = (sumY - slope * sumX) / N || 0;
var predictions = [];
for (var _i = 1; _i <= stepsAhead; _i++) {
var x = N + _i - 1;
predictions.push({
x: now + _i * step,
y: intercept + slope * x
});
}
return {
slope: slope,
intercept: intercept,
historical: series.map(function (y, i) {
return {
x: start + i * step,
y: y
};
}),
predicted: predictions
};
}
}]);
}();
module.exports = MetricTrendManager;