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Commit 6effdc91 by jiangxd2016
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release: v1.2.15

parent c7430477
Showing with 760 additions and 209 deletions
dist/.build-info.json
{
"name": "@grafana/vue",
"version": "1.2.0",
"builtAt": "2026-07-27T06:36:53.097Z",
"builtAt": "2026-07-29T09:13:54.277Z",
"mode": "library-esm-single-file",
"entries": {
"index": "src/index.ts",
......
dist/assets/frameWorker-C6D9tEGY.js deleted 100644 → 0
(function() {
"use strict";
function createDataFrame(opts) {
const fields = opts.fields.map((f) => ({
name: f.name,
type: f.type ?? inferType(f.values),
config: f.config ?? {},
values: f.values,
labels: f.labels
}));
const length = fields.reduce((max, f) => Math.max(max, f.values.length), 0);
return {
refId: opts.refId,
name: opts.name,
fields,
length,
meta: opts.meta
};
}
function inferType(values) {
const sample = values.find((v) => v != null);
if (typeof sample === "number") return "number";
if (typeof sample === "boolean") return "boolean";
if (sample instanceof Date) return "time";
if (typeof sample === "string" && !Number.isNaN(Date.parse(sample)) && /\d{4}-\d{2}-\d{2}/.test(sample)) {
return "time";
}
return typeof sample === "string" ? "string" : "other";
}
function itemLabel(item) {
const host = item.hosts?.[0]?.name || item.hosts?.[0]?.host || "";
return host ? `${host}: ${item.name}` : item.name || item.key_;
}
function seriesToDataFrame(series, refId, datasourceUid, valueMaps) {
const times = series.points.map((p) => p.time);
let values = series.points.map((p) => p.value);
const asString = values.some((v) => typeof v === "string");
const display = series.name || itemLabel(series.item);
const fields = [
{ name: "Time", type: "time", values: times },
{
name: "Value",
type: asString ? "string" : "number",
values: asString ? values.map((v) => v == null ? null : String(v)) : values.map((v) => v == null || v === "" ? null : Number(v)),
labels: {
itemid: series.item.itemid,
item: series.item.name,
host: series.item.hosts?.[0]?.name || ""
},
config: {
displayNameFromDS: display,
...series.item.units ? { unit: series.item.units } : {}
}
}
];
if (series.points.some((p) => p.valueRaw != null && p.valueRaw !== "")) {
fields.push({
name: "ValueRaw",
type: "string",
values: series.points.map(
(p) => p.valueRaw == null ? null : String(p.valueRaw)
)
});
}
if (series.meta?.source === "trend") {
fields.push(
{
name: "TrendMin",
type: "number",
values: series.points.map(
(p) => p.value_min == null ? null : Number(p.value_min)
)
},
{
name: "TrendAvg",
type: "number",
values: series.points.map(
(p) => p.value_avg == null ? null : Number(p.value_avg)
)
},
{
name: "TrendMax",
type: "number",
values: series.points.map(
(p) => p.value_max == null ? null : Number(p.value_max)
)
},
{
name: "TrendNum",
type: "number",
values: series.points.map(
(p) => p.num == null ? null : Number(p.num)
)
}
);
}
if (series.points.some(
(p) => p.logeventid != null || p.source != null || p.severity != null
)) {
fields.push(
{
name: "timestamp",
type: "string",
values: series.points.map((p) => p.timestamp ?? null)
},
{
name: "source",
type: "string",
values: series.points.map((p) => p.source ?? null)
},
{
name: "severity",
type: "string",
values: series.points.map((p) => p.severity ?? null)
},
{
name: "logeventid",
type: "string",
values: series.points.map((p) => p.logeventid ?? null)
},
{
name: "ns",
type: "string",
values: series.points.map((p) => p.ns ?? null)
}
);
}
const frame = createDataFrame({
refId,
name: display,
fields
});
frame.meta = {
...frame.meta,
source: "live",
datasourceUid,
custom: {
source: "zabbix",
itemid: series.item.itemid,
datasourceUid
},
notices: (series.notices || []).map((text) => ({
severity: "warning",
text
}))
};
return frame;
}
function seriesListToFrames(series, refId, datasourceUid, valueMaps) {
return series.map(
(s) => seriesToDataFrame(s, refId, datasourceUid)
);
}
const ctx = self;
ctx.onmessage = (e) => {
const { id, series, refId, datasourceUid } = e.data || {};
try {
const frames = seriesListToFrames(series || [], refId || "A", datasourceUid || "");
ctx.postMessage({ id, ok: true, frames });
} catch (err) {
ctx.postMessage({
id,
ok: false,
error: err instanceof Error ? err.message : String(err)
});
}
};
})();
//# sourceMappingURL=frameWorker-C6D9tEGY.js.map
dist/assets/frameWorker-C6D9tEGY.js.map deleted 100644 → 0
{"version":3,"file":"frameWorker-C6D9tEGY.js","sources":["../../grafana-data/src/dataframe.ts","../../grafana-plugin-zabbix/src/datasource/processing/frames.ts","../../grafana-plugin-zabbix/src/datasource/processing/frameWorker.ts"],"sourcesContent":["import type { DataFrame, Field, FieldType } from \"./types\";\n\nexport function createDataFrame(opts: {\n refId?: string;\n name?: string;\n meta?: Record<string, unknown>;\n fields: Array<\n Partial<Field> & { name: string; values: unknown[]; type?: FieldType }\n >;\n}): DataFrame {\n const fields: Field[] = opts.fields.map((f) => ({\n name: f.name,\n type: f.type ?? inferType(f.values),\n config: f.config ?? {},\n values: f.values,\n labels: f.labels,\n }));\n const length = fields.reduce((max, f) => Math.max(max, f.values.length), 0);\n return {\n refId: opts.refId,\n name: opts.name,\n fields,\n length,\n meta: opts.meta,\n };\n}\n\nfunction inferType(values: unknown[]): FieldType {\n const sample = values.find((v) => v != null);\n if (typeof sample === \"number\") return \"number\";\n if (typeof sample === \"boolean\") return \"boolean\";\n if (sample instanceof Date) return \"time\";\n if (\n typeof sample === \"string\" &&\n !Number.isNaN(Date.parse(sample)) &&\n /\\d{4}-\\d{2}-\\d{2}/.test(sample)\n ) {\n return \"time\";\n }\n return typeof sample === \"string\" ? \"string\" : \"other\";\n}\n\nconst TIME_SERIES_VALUE_FIELD_NAME = \"Value\";\nconst TIME_SERIES_TIME_FIELD_NAME = \"Time\";\n\n/** Format labels like Grafana: job=api, instance=localhost:9090 */\nexport function formatLabels(labels?: Record<string, string> | null): string {\n if (!labels) return \"\";\n return Object.entries(labels)\n .filter(([, v]) => v != null && v !== \"\")\n .map(([k, v]) => `${k}=${v}`)\n .join(\", \");\n}\n\n/**\n * Grafana-compatible field display name for legends / stats.\n * Priority: config.displayName → config.displayNameFromDS → labels / frame name → field name\n */\nexport function getFieldDisplayName(\n field: Field,\n frame?: DataFrame,\n allFrames?: DataFrame[],\n): string {\n // Recompute each time so label uniqueness across frames stays correct.\n // Only write field.state when the value actually changes — mutating reactive\n // DataFrame fields inside Vue computeds otherwise causes \"Maximum recursive updates\".\n const name = calculateFieldDisplayName(field, frame, allFrames);\n if (field.state?.displayName !== name) {\n field.state = { ...(field.state || {}), displayName: name };\n }\n return name;\n}\n\nfunction isGenericValueName(s: string): boolean {\n const t = s.trim();\n if (!t || t === TIME_SERIES_VALUE_FIELD_NAME) return true;\n // e.g. Value {job=\"api\", instance=\"localhost:9090\"}\n if (/^Value\\s*\\{/.test(t)) return true;\n return false;\n}\n\nfunction calculateFieldDisplayName(\n field: Field,\n frame?: DataFrame,\n allFrames?: DataFrame[],\n): string {\n const cfg = field.config ?? {};\n if (\n cfg.displayName &&\n String(cfg.displayName).length &&\n !isGenericValueName(String(cfg.displayName))\n ) {\n return String(cfg.displayName);\n }\n if (\n cfg.displayNameFromDS &&\n String(cfg.displayNameFromDS).length &&\n !isGenericValueName(String(cfg.displayNameFromDS))\n ) {\n return String(cfg.displayNameFromDS);\n }\n\n // Time field without labels → \"Time\"\n if (field.type === \"time\" && !field.labels) {\n return field.name || TIME_SERIES_TIME_FIELD_NAME;\n }\n\n const frames = allFrames?.length ? allFrames : frame ? [frame] : [];\n let frameNamesDiffer = false;\n if (frames.length > 1) {\n for (let i = 1; i < frames.length; i++) {\n if (frames[i].name !== frames[i - 1].name) {\n frameNamesDiffer = true;\n break;\n }\n }\n }\n\n const parts: string[] = [];\n let frameNameAdded = false;\n let labelsAdded = false;\n\n if (frameNamesDiffer && frame?.name) {\n parts.push(frame.name);\n frameNameAdded = true;\n }\n\n // Skip generic \"Value\" / \"Value {labels}\" field names — labels / frame name are more useful\n if (field.name && !isGenericValueName(field.name)) {\n parts.push(field.name);\n }\n\n if (field.labels && Object.keys(field.labels).length) {\n const singleLabel = getSingleLabelName(\n frames.length ? frames : frame ? [frame] : [],\n );\n if (\n singleLabel &&\n field.labels[singleLabel] != null &&\n field.labels[singleLabel] !== \"\"\n ) {\n parts.push(String(field.labels[singleLabel]));\n labelsAdded = true;\n } else {\n const allLabels = formatLabels(field.labels);\n if (allLabels) {\n parts.push(allLabels);\n labelsAdded = true;\n }\n }\n }\n\n // Value / Value {..} field with no labels → use frame name\n if (\n frame &&\n !frameNameAdded &&\n !labelsAdded &&\n isGenericValueName(field.name || \"\")\n ) {\n if (frame.name) {\n parts.push(frame.name);\n frameNameAdded = true;\n }\n }\n\n if (parts.length) return parts.join(\" \");\n if (field.name) return field.name;\n if (frame?.name) return frame.name;\n return TIME_SERIES_VALUE_FIELD_NAME;\n}\n\n/** If every frame only has one distinct label key across numeric fields, return that key. */\nfunction getSingleLabelName(frames: DataFrame[]): string | null {\n const keys = new Set<string>();\n for (const fr of frames) {\n for (const f of fr.fields) {\n if (!f.labels) continue;\n for (const k of Object.keys(f.labels)) keys.add(k);\n if (keys.size > 1) return null;\n }\n }\n if (keys.size === 1) return [...keys][0];\n return null;\n}\n\nexport function toDataFrameDTO(frame: DataFrame): DataFrame {\n return {\n ...frame,\n fields: frame.fields.map((f) => ({\n ...f,\n values: [...f.values],\n config: { ...f.config },\n })),\n };\n}\n","import { createDataFrame, type DataFrame } from \"@grafana/data\";\nimport type { ZabbixItem } from \"../types\";\nimport type { ZabbixSeries } from \"./types\";\nimport { mapSeriesValue as mapVal } from \"./valueMapping\";\n\nexport function emptyFrame(refId: string, notice?: string): DataFrame {\n const frame = createDataFrame({\n refId,\n fields: [\n { name: \"Time\", type: \"time\", values: [] },\n { name: \"Value\", type: \"number\", values: [] },\n ],\n });\n if (notice)\n (frame as any).meta = { notices: [{ severity: \"warning\", text: notice }] };\n return frame;\n}\n\nexport function itemLabel(item: ZabbixItem): string {\n const host = item.hosts?.[0]?.name || item.hosts?.[0]?.host || \"\";\n return host ? `${host}: ${item.name}` : item.name || item.key_;\n}\n\nexport function seriesToDataFrame(\n series: ZabbixSeries,\n refId: string,\n datasourceUid: string,\n valueMaps?: Map<\n string,\n import(\"./valueMapping\").ValueMapMapping[] | Record<string, string>\n >,\n): DataFrame {\n const times = series.points.map((p) => p.time);\n let values = series.points.map((p) => p.value);\n if (valueMaps && series.item.valuemapid) {\n values = values.map((v) =>\n mapVal(v as any, series.item.valuemapid, valueMaps),\n );\n }\n const asString = values.some((v) => typeof v === \"string\");\n const display = series.name || itemLabel(series.item);\n const fields: any[] = [\n { name: \"Time\", type: \"time\", values: times },\n {\n name: \"Value\",\n type: asString ? \"string\" : \"number\",\n values: asString\n ? values.map((v) => (v == null ? null : String(v)))\n : values.map((v) => (v == null || v === \"\" ? null : Number(v))),\n labels: {\n itemid: series.item.itemid,\n item: series.item.name,\n host: series.item.hosts?.[0]?.name || \"\",\n },\n config: {\n displayNameFromDS: display,\n ...(series.item.units ? { unit: series.item.units } : {}),\n },\n },\n ];\n if (series.points.some((p) => p.valueRaw != null && p.valueRaw !== \"\")) {\n fields.push({\n name: \"ValueRaw\",\n type: \"string\",\n values: series.points.map((p) =>\n p.valueRaw == null ? null : String(p.valueRaw),\n ),\n });\n }\n if (series.meta?.source === \"trend\") {\n fields.push(\n {\n name: \"TrendMin\",\n type: \"number\",\n values: series.points.map((p) =>\n p.value_min == null ? null : Number(p.value_min),\n ),\n },\n {\n name: \"TrendAvg\",\n type: \"number\",\n values: series.points.map((p) =>\n p.value_avg == null ? null : Number(p.value_avg),\n ),\n },\n {\n name: \"TrendMax\",\n type: \"number\",\n values: series.points.map((p) =>\n p.value_max == null ? null : Number(p.value_max),\n ),\n },\n {\n name: \"TrendNum\",\n type: \"number\",\n values: series.points.map((p) =>\n p.num == null ? null : Number(p.num),\n ),\n },\n );\n }\n if (\n series.points.some(\n (p) => p.logeventid != null || p.source != null || p.severity != null,\n )\n ) {\n fields.push(\n {\n name: \"timestamp\",\n type: \"string\",\n values: series.points.map((p) => p.timestamp ?? null),\n },\n {\n name: \"source\",\n type: \"string\",\n values: series.points.map((p) => p.source ?? null),\n },\n {\n name: \"severity\",\n type: \"string\",\n values: series.points.map((p) => p.severity ?? null),\n },\n {\n name: \"logeventid\",\n type: \"string\",\n values: series.points.map((p) => p.logeventid ?? null),\n },\n {\n name: \"ns\",\n type: \"string\",\n values: series.points.map((p) => p.ns ?? null),\n },\n );\n }\n const frame = createDataFrame({\n refId,\n name: display,\n fields,\n });\n (frame as any).meta = {\n ...(frame as any).meta,\n source: \"live\",\n datasourceUid,\n custom: {\n source: \"zabbix\",\n itemid: series.item.itemid,\n datasourceUid,\n },\n notices: (series.notices || []).map((text) => ({\n severity: \"warning\",\n text,\n })),\n };\n return frame;\n}\n\nexport function seriesListToFrames(\n series: ZabbixSeries[],\n refId: string,\n datasourceUid: string,\n valueMaps?: Map<\n string,\n import(\"./valueMapping\").ValueMapMapping[] | Record<string, string>\n >,\n): DataFrame[] {\n return series.map((s) =>\n seriesToDataFrame(s, refId, datasourceUid, valueMaps),\n );\n}\n\n/** Back-compat for metrics executor */\nexport function seriesToFrames(\n series: ZabbixSeries[],\n refId: string,\n): DataFrame[] {\n return seriesListToFrames(series, refId, \"\");\n}\n","import { seriesListToFrames } from \"./frames\";\nimport type { ZabbixSeries } from \"./types\";\n\nexport type FrameWorkerRequest = {\n id: string;\n series: ZabbixSeries[];\n refId: string;\n datasourceUid: string;\n};\n\nexport type FrameWorkerResponse =\n | { id: string; ok: true; frames: unknown[] }\n | { id: string; ok: false; error: string };\n\nconst ctx = self as unknown as Worker & { onmessage: ((e: MessageEvent) => void) | null };\n\nctx.onmessage = (e: MessageEvent<FrameWorkerRequest>) => {\n const { id, series, refId, datasourceUid } = e.data || ({} as FrameWorkerRequest);\n try {\n const frames = seriesListToFrames(series || [], refId || \"A\", datasourceUid || \"\");\n ctx.postMessage({ id, ok: true, frames } satisfies FrameWorkerResponse);\n } catch (err) {\n ctx.postMessage({\n id,\n ok: false,\n error: err instanceof Error ? 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dist/assets/frameWorker-D950i8VL.js 0 → 100644
(function() {
"use strict";
function createDataFrame(opts) {
const fields = opts.fields.map((f) => ({
name: f.name,
type: f.type ?? inferType(f.values),
config: f.config ?? {},
values: f.values,
labels: f.labels
}));
const length = fields.reduce((max, f) => Math.max(max, f.values.length), 0);
return {
refId: opts.refId,
name: opts.name,
fields,
length,
meta: opts.meta
};
}
function inferType(values) {
const sample = values.find((v) => v != null);
if (typeof sample === "number") return "number";
if (typeof sample === "boolean") return "boolean";
if (sample instanceof Date) return "time";
if (typeof sample === "string" && !Number.isNaN(Date.parse(sample)) && /\d{4}-\d{2}-\d{2}/.test(sample)) {
return "time";
}
return typeof sample === "string" ? "string" : "other";
}
function toFixed(value, decimals) {
if (decimals == null) {
if (!Number.isFinite(value)) return String(value);
if (Number.isInteger(value) || Math.abs(value - Math.round(value)) < 1e-9) {
return String(Math.round(value));
}
const abs = Math.abs(value);
const d = abs >= 100 ? 0 : abs >= 1 ? 1 : abs >= 0.01 ? 2 : 3;
return String(Number(value.toFixed(d)));
}
return value.toFixed(Math.max(0, Math.min(10, Math.floor(decimals))));
}
function toFixedUnit(unit = "") {
return (value, decimals) => ({
text: toFixed(value, decimals),
suffix: unit ? ` ${unit}` : void 0
});
}
function scaledUnits(factor, extArray, offset = 0) {
return (value, decimals) => {
if (value === null || value === void 0 || Number.isNaN(value)) {
return { text: "" };
}
let si = offset;
let v = Math.abs(value);
while (v >= factor && si < extArray.length - 1) {
v /= factor;
si += 1;
}
const sign = value < 0 ? "-" : "";
return {
// When decimals is null/undefined, toFixed uses auto precision (Grafana axis ticks).
text: `${sign}${toFixed(v, decimals)}`,
suffix: extArray[si] ? ` ${extArray[si]}` : void 0
};
};
}
function booleanValueFormatter(t = "True", f = "False") {
return (value) => ({ text: value ? t : f });
}
function locale(value, decimals) {
try {
return {
text: value.toLocaleString(void 0, {
maximumFractionDigits: decimals ?? 2,
minimumFractionDigits: decimals ?? void 0
})
};
} catch {
return { text: toFixed(value, decimals) };
}
}
function stringFormatter(value) {
return { text: value == null ? "" : String(value) };
}
function dtdhms(value) {
if (!Number.isFinite(value)) return { text: String(value) };
const sign = value < 0 ? "-" : "";
let s = Math.floor(Math.abs(value));
const d = Math.floor(s / 86400);
s -= d * 86400;
const h = Math.floor(s / 3600);
s -= h * 3600;
const m = Math.floor(s / 60);
s -= m * 60;
const parts = [];
if (d) parts.push(`${d}d`);
if (h || parts.length) parts.push(`${h}h`);
if (m || parts.length) parts.push(`${m}m`);
parts.push(`${s}s`);
return { text: `${sign}${parts.join(" ")}` };
}
function dateTimeAsIso(value) {
try {
return { text: new Date(value).toISOString() };
} catch {
return { text: String(value) };
}
}
function dateTimeAsSystem(value, _decimals, _scaled, timeZone) {
try {
const d = new Date(value);
if (Number.isNaN(d.getTime())) return { text: String(value) };
const pad = (n) => String(n).padStart(2, "0");
const tz = String(timeZone || "browser").toLowerCase();
const useUtc = tz === "utc" || tz === "gmt" || tz === "etc/utc";
const Y = useUtc ? d.getUTCFullYear() : d.getFullYear();
const M = useUtc ? d.getUTCMonth() + 1 : d.getMonth() + 1;
const D = useUtc ? d.getUTCDate() : d.getDate();
const h = useUtc ? d.getUTCHours() : d.getHours();
const m = useUtc ? d.getUTCMinutes() : d.getMinutes();
const s = useUtc ? d.getUTCSeconds() : d.getSeconds();
const text = `${Y}-${pad(M)}-${pad(D)} ${pad(h)}:${pad(m)}:${pad(s)}`;
return { text };
} catch {
return { text: String(value) };
}
}
const index = /* @__PURE__ */ new Map();
function register(id, fn) {
index.set(id, fn);
}
function build() {
if (index.size) return;
register("none", (v, d) => {
if (d != null) return { text: Number(v).toFixed(d) };
if (!Number.isFinite(v)) return { text: String(v) };
if (Number.isInteger(v) || Math.abs(v - Math.round(v)) < 1e-9)
return { text: String(Math.round(v)) };
const abs = Math.abs(v);
if (abs >= 100 && Math.abs(v - Math.round(v)) < 0.5)
return { text: String(Math.round(v)) };
const decimals = abs >= 1e3 ? 0 : abs >= 1 ? 1 : abs >= 0.01 ? 2 : 3;
return { text: String(Number(v.toFixed(decimals))) };
});
register("short", scaledUnits(1e3, ["", "K", "Mil", "Bil", "Tri"]));
register("percent", (v, d) => ({
text: d == null ? String(v) : v.toFixed(d),
suffix: "%"
}));
register("percentunit", (v, d) => {
const p = v * 100;
return {
text: d == null ? String(Number(p.toPrecision(12))) : p.toFixed(d),
suffix: "%"
};
});
register("locale", (v, d) => locale(v, d));
register("string", (_v) => stringFormatter(_v));
register("bool", booleanValueFormatter());
register("boolean", booleanValueFormatter());
for (const u of ["ns", "µs", "ms", "s", "m", "h", "d"]) {
register(u, toFixedUnit(u));
}
register(
"bytes",
scaledUnits(1024, ["B", "KiB", "MiB", "GiB", "TiB", "PiB"])
);
register("decbytes", scaledUnits(1e3, ["B", "kB", "MB", "GB", "TB", "PB"]));
register("bits", scaledUnits(1e3, ["b", "Kbit", "Mbit", "Gbit", "Tbit"]));
register("decbits", scaledUnits(1e3, ["b", "Kbit", "Mbit", "Gbit", "Tbit"]));
register("kbytes", scaledUnits(1024, ["KiB", "MiB", "GiB", "TiB"]));
register("mbytes", scaledUnits(1024, ["MiB", "GiB", "TiB"]));
for (const u of [
"cps",
"ops",
"reqps",
"rps",
"wps",
"iops",
"binBps",
"Bps",
"pps"
]) {
register(u, toFixedUnit(u));
}
register("dateTimeAsIso", (v) => dateTimeAsIso(v));
register("dateTimeAsSystem", (v) => dateTimeAsSystem(v));
register("sci", (v, d) => ({ text: v.toExponential(d ?? 2) }));
register("humidity", toFixedUnit("%H"));
register("dB", toFixedUnit("dB"));
register("dBm", toFixedUnit("dBm"));
register("celsius", toFixedUnit("°C"));
register("fahrenheit", toFixedUnit("°F"));
register("farenheit", toFixedUnit("°F"));
register("lengthm", toFixedUnit("m"));
register("lengthmm", toFixedUnit("mm"));
register("velocityms", toFixedUnit("m/s"));
register("bps", scaledUnits(1e3, ["b/s", "Kb/s", "Mb/s", "Gb/s", "Tb/s"]));
register("dtdhms", (v) => dtdhms(v));
register("qps", toFixedUnit("qps"));
register("hertz", scaledUnits(1e3, ["Hz", "kHz", "MHz", "GHz", "THz"]));
register("volt", scaledUnits(1e3, ["V", "kV", "MV", "GV"]));
register("rotrpm", toFixedUnit("rpm"));
}
function listValueFormatIds() {
build();
return [...index.keys()].sort();
}
const ZABBIX_UNIT_MAP = {
"%": "percent",
b: "decbits",
// bits(SI)
bps: "bps",
// bits/sec(SI)
B: "bytes",
// bytes(IEC)
Bps: "binBps",
// bytes/sec(IEC)
// 'unixtime': 'dateTimeAsSystem', // matches React: left commented out upstream
uptime: "dtdhms",
qps: "qps",
// requests/sec (rps)
iops: "iops",
// I/O ops/sec (iops)
Hz: "hertz",
// Hertz (1/s)
V: "volt",
// Volt (V)
C: "celsius",
// Celsius (°C)
RPM: "rotrpm",
// Revolutions per minute (rpm)
dBm: "dBm"
// Decibel-milliwatt (dBm)
};
let knownUnitIds = null;
function getKnownGrafanaUnitIds() {
if (!knownUnitIds) knownUnitIds = new Set(listValueFormatIds());
return knownUnitIds;
}
function convertZabbixUnit(zabbixUnit) {
if (!zabbixUnit) return void 0;
const mapped = ZABBIX_UNIT_MAP[zabbixUnit];
if (mapped) return mapped;
if (getKnownGrafanaUnitIds().has(zabbixUnit)) return zabbixUnit;
return void 0;
}
function itemLabel(item) {
const host = item.hosts?.[0]?.name || item.hosts?.[0]?.host || "";
return host ? `${host}: ${item.name}` : item.name || item.key_;
}
function seriesToDataFrame(series, refId, datasourceUid, valueMaps) {
const times = series.points.map((p) => p.time);
const values = series.points.map((p) => p.value);
const display = series.name || itemLabel(series.item);
const host = series.item.hosts?.[0];
const tagValues = /* @__PURE__ */ new Map();
for (const tag of series.item.tags || []) {
const key = tag.tag.replace(/[^A-Za-z0-9_]/g, "_");
if (!key) continue;
tagValues.set(key, [
...tagValues.get(key) || [],
String(tag.value ?? "")
]);
}
const scopedVars = {
__zbx_item: { value: series.item.name },
__zbx_item_name: { value: series.item.name },
__zbx_item_key: { value: series.item.key_ },
__zbx_item_interval: { value: String(series.item.delay || "") }
};
if (host) {
scopedVars.__zbx_host = { value: host.name || host.host || "" };
scopedVars.__zbx_host_id = { value: host.hostid };
scopedVars.__zbx_host_name = { value: host.name || host.host || "" };
}
for (const [key, entries] of tagValues) {
scopedVars[`__zbx_item_tag_${key}`] = { value: entries.sort().join(", ") };
}
const unit = convertZabbixUnit(series.item.units);
const mappings = void 0;
const fields = [
{
name: "Time",
type: "time",
values: times,
config: { custom: { itemInterval: series.item.delay } }
},
{
name: "Value",
type: "number",
values: values.map((v) => v == null || v === "" ? null : Number(v)),
labels: {
...host ? { host: host.name || host.host || "" } : {},
item: series.item.name,
item_key: series.item.key_
},
config: {
displayNameFromDS: display,
custom: { scopedVars, itemInterval: series.item.delay },
...unit ? { unit } : {},
...unit === "percent" ? { min: 0, max: 100 } : {},
...Array.isArray(mappings) && mappings.length ? {
mappings: mappings.map((mapping) => ({
type: "value",
options: {
[String(mapping.value)]: { text: mapping.newvalue }
}
}))
} : {}
}
}
];
const frame = createDataFrame({
refId,
name: display,
fields
});
frame.meta = {
source: "live",
datasourceUid,
...series.points.some((point) => point.valueRaw != null) ? {
custom: {
valueRaw: series.points.map(
(point) => point.valueRaw == null ? null : String(point.valueRaw)
)
}
} : {}
};
return frame;
}
function seriesListToFrames(series, refId, datasourceUid, valueMaps) {
return series.map(
(s) => seriesToDataFrame(s, refId, datasourceUid)
);
}
const ctx = self;
ctx.onmessage = (e) => {
const { id, series, refId, datasourceUid } = e.data || {};
try {
const frames = seriesListToFrames(series || [], refId || "A", datasourceUid || "");
ctx.postMessage({ id, ok: true, frames });
} catch (err) {
ctx.postMessage({
id,
ok: false,
error: err instanceof Error ? err.message : String(err)
});
}
};
})();
//# sourceMappingURL=frameWorker-D950i8VL.js.map
dist/assets/frameWorker-D950i8VL.js.map 0 → 100644
{"version":3,"file":"frameWorker-D950i8VL.js","sources":["../../grafana-data/src/dataframe.ts","../../grafana-data/src/valueFormats/formatters.ts","../../grafana-data/src/valueFormats/registry.ts","../../grafana-plugin-zabbix/src/datasource/processing/unitMapping.ts","../../grafana-plugin-zabbix/src/datasource/processing/frames.ts","../../grafana-plugin-zabbix/src/datasource/processing/frameWorker.ts"],"sourcesContent":["import type { DataFrame, Field, FieldType } from \"./types\";\n\nexport function createDataFrame(opts: {\n refId?: string;\n name?: string;\n meta?: Record<string, unknown>;\n fields: Array<\n Partial<Field> & { name: string; values: unknown[]; type?: FieldType }\n >;\n}): DataFrame {\n const fields: Field[] = opts.fields.map((f) => ({\n name: f.name,\n type: f.type ?? inferType(f.values),\n config: f.config ?? {},\n values: f.values,\n labels: f.labels,\n }));\n const length = fields.reduce((max, f) => Math.max(max, f.values.length), 0);\n return {\n refId: opts.refId,\n name: opts.name,\n fields,\n length,\n meta: opts.meta,\n };\n}\n\nfunction inferType(values: unknown[]): FieldType {\n const sample = values.find((v) => v != null);\n if (typeof sample === \"number\") return \"number\";\n if (typeof sample === \"boolean\") return \"boolean\";\n if (sample instanceof Date) return \"time\";\n if (\n typeof sample === \"string\" &&\n !Number.isNaN(Date.parse(sample)) &&\n /\\d{4}-\\d{2}-\\d{2}/.test(sample)\n ) {\n return \"time\";\n }\n return typeof sample === \"string\" ? \"string\" : \"other\";\n}\n\nconst TIME_SERIES_VALUE_FIELD_NAME = \"Value\";\nconst TIME_SERIES_TIME_FIELD_NAME = \"Time\";\n\n/** Format labels like Grafana: job=api, instance=localhost:9090 */\nexport function formatLabels(labels?: Record<string, string> | null): string {\n if (!labels) return \"\";\n return Object.entries(labels)\n .filter(([, v]) => v != null && v !== \"\")\n .map(([k, v]) => `${k}=${v}`)\n .join(\", \");\n}\n\n/**\n * Grafana-compatible field display name for legends / stats.\n * Priority: config.displayName → config.displayNameFromDS → labels / frame name → field name\n */\nexport function getFieldDisplayName(\n field: Field,\n frame?: DataFrame,\n allFrames?: DataFrame[],\n): string {\n // Recompute each time so label uniqueness across frames stays correct.\n // Only write field.state when the value actually changes — mutating reactive\n // DataFrame fields inside Vue computeds otherwise causes \"Maximum recursive updates\".\n const name = calculateFieldDisplayName(field, frame, allFrames);\n if (field.state?.displayName !== name) {\n field.state = { ...(field.state || {}), displayName: name };\n }\n return name;\n}\n\nfunction isGenericValueName(s: string): boolean {\n const t = s.trim();\n if (!t || t === TIME_SERIES_VALUE_FIELD_NAME) return true;\n // e.g. Value {job=\"api\", instance=\"localhost:9090\"}\n if (/^Value\\s*\\{/.test(t)) return true;\n return false;\n}\n\nfunction calculateFieldDisplayName(\n field: Field,\n frame?: DataFrame,\n allFrames?: DataFrame[],\n): string {\n const cfg = field.config ?? {};\n if (\n cfg.displayName &&\n String(cfg.displayName).length &&\n !isGenericValueName(String(cfg.displayName))\n ) {\n return String(cfg.displayName);\n }\n if (\n cfg.displayNameFromDS &&\n String(cfg.displayNameFromDS).length &&\n !isGenericValueName(String(cfg.displayNameFromDS))\n ) {\n return String(cfg.displayNameFromDS);\n }\n\n // Time field without labels → \"Time\"\n if (field.type === \"time\" && !field.labels) {\n return field.name || TIME_SERIES_TIME_FIELD_NAME;\n }\n\n const frames = allFrames?.length ? allFrames : frame ? [frame] : [];\n let frameNamesDiffer = false;\n if (frames.length > 1) {\n for (let i = 1; i < frames.length; i++) {\n if (frames[i].name !== frames[i - 1].name) {\n frameNamesDiffer = true;\n break;\n }\n }\n }\n\n const parts: string[] = [];\n let frameNameAdded = false;\n let labelsAdded = false;\n\n if (frameNamesDiffer && frame?.name) {\n parts.push(frame.name);\n frameNameAdded = true;\n }\n\n // Skip generic \"Value\" / \"Value {labels}\" field names — labels / frame name are more useful\n if (field.name && !isGenericValueName(field.name)) {\n parts.push(field.name);\n }\n\n if (field.labels && Object.keys(field.labels).length) {\n const singleLabel = getSingleLabelName(\n frames.length ? frames : frame ? [frame] : [],\n );\n if (\n singleLabel &&\n field.labels[singleLabel] != null &&\n field.labels[singleLabel] !== \"\"\n ) {\n parts.push(String(field.labels[singleLabel]));\n labelsAdded = true;\n } else {\n const allLabels = formatLabels(field.labels);\n if (allLabels) {\n parts.push(allLabels);\n labelsAdded = true;\n }\n }\n }\n\n // Value / Value {..} field with no labels → use frame name\n if (\n frame &&\n !frameNameAdded &&\n !labelsAdded &&\n isGenericValueName(field.name || \"\")\n ) {\n if (frame.name) {\n parts.push(frame.name);\n frameNameAdded = true;\n }\n }\n\n if (parts.length) return parts.join(\" \");\n if (field.name) return field.name;\n if (frame?.name) return frame.name;\n return TIME_SERIES_VALUE_FIELD_NAME;\n}\n\n/** If every frame only has one distinct label key across numeric fields, return that key. */\nfunction getSingleLabelName(frames: DataFrame[]): string | null {\n const keys = new Set<string>();\n for (const fr of frames) {\n for (const f of fr.fields) {\n if (!f.labels) continue;\n for (const k of Object.keys(f.labels)) keys.add(k);\n if (keys.size > 1) return null;\n }\n }\n if (keys.size === 1) return [...keys][0];\n return null;\n}\n\nexport function toDataFrameDTO(frame: DataFrame): DataFrame {\n return {\n ...frame,\n fields: frame.fields.map((f) => ({\n ...f,\n values: [...f.values],\n config: { ...f.config },\n })),\n };\n}\n","import type { FormattedValue } from \"../types/displayValue\";\n\nexport type ValueFormatter = (\n value: number,\n decimals?: number | null,\n scaledDecimals?: number | null,\n) => FormattedValue;\n\nfunction toFixed(value: number, decimals?: number | null): string {\n if (decimals == null) {\n // Auto decimals for axis/stat/gauge labels — avoid long floats like 37.5524.\n if (!Number.isFinite(value)) return String(value);\n if (Number.isInteger(value) || Math.abs(value - Math.round(value)) < 1e-9) {\n return String(Math.round(value));\n }\n const abs = Math.abs(value);\n const d = abs >= 100 ? 0 : abs >= 1 ? 1 : abs >= 0.01 ? 2 : 3;\n return String(Number(value.toFixed(d)));\n }\n return value.toFixed(Math.max(0, Math.min(10, Math.floor(decimals))));\n}\n\nexport function toFixedUnit(unit = \"\"): ValueFormatter {\n return (value, decimals) => ({\n text: toFixed(value, decimals),\n suffix: unit ? ` ${unit}` : undefined,\n });\n}\n\nexport function scaledUnits(\n factor: number,\n extArray: string[],\n offset = 0,\n): ValueFormatter {\n return (value, decimals) => {\n if (value === null || value === undefined || Number.isNaN(value)) {\n return { text: \"\" };\n }\n let si = offset;\n let v = Math.abs(value);\n while (v >= factor && si < extArray.length - 1) {\n v /= factor;\n si += 1;\n }\n const sign = value < 0 ? \"-\" : \"\";\n return {\n // When decimals is null/undefined, toFixed uses auto precision (Grafana axis ticks).\n text: `${sign}${toFixed(v, decimals)}`,\n suffix: extArray[si] ? ` ${extArray[si]}` : undefined,\n };\n };\n}\n\nconst simpleCountUnit = (symbol: string): ValueFormatter => toFixedUnit(symbol);\nvoid simpleCountUnit;\n\nexport function booleanValueFormatter(t = \"True\", f = \"False\"): ValueFormatter {\n return (value) => ({ text: value ? t : f });\n}\n\nexport function locale(\n value: number,\n decimals?: number | null,\n): FormattedValue {\n try {\n return {\n text: value.toLocaleString(undefined, {\n maximumFractionDigits: decimals ?? 2,\n minimumFractionDigits: decimals ?? undefined,\n }),\n };\n } catch {\n return { text: toFixed(value, decimals) };\n }\n}\n\nexport function stringFormatter(value: unknown): FormattedValue {\n return { text: value == null ? \"\" : String(value) };\n}\n\n/**\n * Grafana \"dtdhms\" (duration, days/hours/minutes/seconds) — used for Zabbix\n * `uptime` values (seconds). Renders the largest non-zero units down to\n * seconds, e.g. 90065 -> \"1d 1h 1m 5s\"; 0 -> \"0s\".\n */\nexport function dtdhms(value: number): FormattedValue {\n if (!Number.isFinite(value)) return { text: String(value) };\n const sign = value < 0 ? \"-\" : \"\";\n let s = Math.floor(Math.abs(value));\n const d = Math.floor(s / 86400);\n s -= d * 86400;\n const h = Math.floor(s / 3600);\n s -= h * 3600;\n const m = Math.floor(s / 60);\n s -= m * 60;\n const parts: string[] = [];\n if (d) parts.push(`${d}d`);\n if (h || parts.length) parts.push(`${h}h`);\n if (m || parts.length) parts.push(`${m}m`);\n parts.push(`${s}s`);\n return { text: `${sign}${parts.join(\" \")}` };\n}\n\nexport function dateTimeAsIso(value: number): FormattedValue {\n try {\n return { text: new Date(value).toISOString() };\n } catch {\n return { text: String(value) };\n }\n}\n\n/**\n * Grafana systemDateFormats.fullDate default: YYYY-MM-DD HH:mm:ss.\n * timeZone: 'utc' | 'browser' | IANA. Default browser/local.\n */\nexport function dateTimeAsSystem(\n value: number,\n _decimals?: number | null,\n _scaled?: number | null,\n timeZone?: string,\n): FormattedValue {\n try {\n const d = new Date(value);\n if (Number.isNaN(d.getTime())) return { text: String(value) };\n const pad = (n: number) => String(n).padStart(2, \"0\");\n const tz = String(timeZone || \"browser\").toLowerCase();\n const useUtc = tz === \"utc\" || tz === \"gmt\" || tz === \"etc/utc\";\n const Y = useUtc ? d.getUTCFullYear() : d.getFullYear();\n const M = useUtc ? d.getUTCMonth() + 1 : d.getMonth() + 1;\n const D = useUtc ? d.getUTCDate() : d.getDate();\n const h = useUtc ? d.getUTCHours() : d.getHours();\n const m = useUtc ? d.getUTCMinutes() : d.getMinutes();\n const s = useUtc ? d.getUTCSeconds() : d.getSeconds();\n const text = `${Y}-${pad(M)}-${pad(D)} ${pad(h)}:${pad(m)}:${pad(s)}`;\n return { text };\n } catch {\n return { text: String(value) };\n }\n}\n","import type { ValueFormatter } from \"./formatters\";\nimport {\n booleanValueFormatter,\n dateTimeAsIso,\n dateTimeAsSystem,\n dtdhms,\n locale,\n scaledUnits,\n // simpleCountUnit,\n stringFormatter,\n toFixedUnit,\n} from \"./formatters\";\nimport type { FormattedValue } from \"../types/displayValue\";\n\nconst index = new Map<string, ValueFormatter>();\n\nfunction register(id: string, fn: ValueFormatter) {\n index.set(id, fn);\n}\n\nfunction build() {\n if (index.size) return;\n register(\"none\", (v, d) => {\n if (d != null) return { text: Number(v).toFixed(d) };\n // Auto decimals (Grafana-ish): large near-integers collapse; else 1–3 places.\n if (!Number.isFinite(v)) return { text: String(v) };\n if (Number.isInteger(v) || Math.abs(v - Math.round(v)) < 1e-9)\n return { text: String(Math.round(v)) };\n const abs = Math.abs(v);\n // means like 549.17 → \"549\"; 12.33 → \"12.3\"\n if (abs >= 100 && Math.abs(v - Math.round(v)) < 0.5)\n return { text: String(Math.round(v)) };\n const decimals =\n abs >= 1000 ? 0 : abs >= 1 ? 1 : abs >= 0.01 ? 2 : 3;\n return { text: String(Number(v.toFixed(decimals))) };\n });\n register(\"short\", scaledUnits(1000, [\"\", \"K\", \"Mil\", \"Bil\", \"Tri\"]));\n register(\"percent\", (v, d) => ({\n text: d == null ? String(v) : v.toFixed(d),\n suffix: \"%\",\n }));\n register(\"percentunit\", (v, d) => {\n const p = v * 100;\n return {\n text: d == null ? 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dist/assets/panelPipelineWorker-5BqW8fRn.js.map deleted 100644 → 0
{"version":3,"file":"panelPipelineWorker-5BqW8fRn.js","sources":["../../grafana-data/src/transformations/registry.ts","../../grafana-data/src/transformations/runner.ts","../../grafana-data/src/field/matchers.ts","../../grafana-data/src/field/overrideProcessors.ts","../../grafana-data/src/fieldOverrides.ts","../../grafana-data/src/performance/compiledPipeline.ts","../../grafana-vue-dashboard/src/query/panelPipelineTransfer.ts","../../grafana-vue-dashboard/src/query/panelPipelineWorker.ts"],"sourcesContent":["import type { DataFrame } from \"../types\";\n\nexport type TransformerFn = (\n frames: DataFrame[],\n options?: Record<string, unknown>,\n) => DataFrame[];\n\nconst registry = new Map<string, TransformerFn>();\n\nexport function registerTransformer(id: string, fn: TransformerFn): void {\n registry.set(id, fn);\n}\n\nexport function getTransformer(id: string): TransformerFn | undefined {\n return registry.get(id);\n}\n\nexport function listTransformerIds(): string[] {\n return [...registry.keys()];\n}\n\nfunction getTransformerRegistry(): Map<string, TransformerFn> {\n return registry;\n}\nvoid getTransformerRegistry;\n","import type { DataFrame } from \"../types\";\nimport {\n getTransformer,\n listTransformerIds as listIdsFromRegistry,\n type TransformerFn,\n} from \"./registry\";\n\nexport type { TransformerFn };\n\nconst ALIASES: Record<string, string> = {\n // filterFieldsByName is first-class; filterByName is internal alias\n filterByName: \"filterFieldsByName\",\n filterFramesByRefId: \"filterByRefId\",\n seriesToColumns: \"joinByField\",\n};\n\nconst DEFAULT_OPTIONS: Record<string, Record<string, unknown>> = {\n limit: { limitField: 10 },\n sortBy: { sort: [] },\n reduce: { reducers: [\"sum\"] },\n histogram: { bucketCount: 10 },\n smoothing: { windowSize: 3 },\n filterByValue: { type: \"include\", filters: [] },\n prepareTimeSeries: { format: \"multi\" },\n};\n\nexport type TransformDiagnostic = {\n id: string;\n level: \"warn\" | \"error\";\n message: string;\n};\n\nexport function resolveTransformerId(id: string): string {\n return ALIASES[id] ?? id;\n}\n\n/** Detach frames from caller ownership (one entry copy). Prefer slice over spread. */\nfunction deepCloneFrames(frames: DataFrame[]): DataFrame[] {\n return frames.map((frame) => {\n const fields = frame.fields.map((f) => ({\n name: f.name,\n type: f.type,\n config: f.config ? { ...f.config } : {},\n values: f.values.slice(),\n labels: f.labels ? { ...f.labels } : undefined,\n state: f.state ? { ...f.state } : undefined,\n }));\n return {\n refId: frame.refId,\n name: frame.name,\n meta: frame.meta ? { ...frame.meta } : undefined,\n fields,\n length: frame.length ?? fields[0]?.values.length ?? 0,\n };\n });\n}\n\nfunction interpolateOptions<T>(\n value: T,\n interpolate?: (s: string) => string,\n): T {\n if (!interpolate) return value;\n if (typeof value === \"string\") return interpolate(value) as T;\n if (Array.isArray(value))\n return value.map((v) => interpolateOptions(v, interpolate)) as T;\n if (value && typeof value === \"object\") {\n const out: Record<string, unknown> = {};\n for (const [k, v] of Object.entries(value as Record<string, unknown>)) {\n out[k] = interpolateOptions(v, interpolate);\n }\n return out as T;\n }\n return value;\n}\n\n/** Grafana MatcherConfig-like frame filter on a transformation step. */\nexport type FrameFilterConfig =\n | string\n | {\n id?: string;\n options?: unknown;\n }\n | null\n | undefined;\n\nfunction patternFromFilterOptions(options: unknown): string {\n if (options == null) return \"\";\n if (typeof options === \"string\" || typeof options === \"number\")\n return String(options);\n if (typeof options === \"object\") {\n const o = options as Record<string, unknown>;\n if (o.pattern != null) return String(o.pattern);\n if (o.refId != null) return String(o.refId);\n if (o.value != null) return String(o.value);\n if (Array.isArray(o.names))\n return (o.names as unknown[]).map(String).join(\"|\");\n }\n return String(options);\n}\n\nfunction compileMatcher(raw: string): (value: string) => boolean {\n const s = raw.trim();\n if (!s) return () => true;\n // /regex/flags\n const m = s.match(/^\\/(.+)\\/([gimsuy]*)$/);\n if (m) {\n try {\n const re = new RegExp(m[1], m[2]);\n return (v) => re.test(v);\n } catch {\n return (v) => v === s;\n }\n }\n // plain regex or alternation without slashes\n try {\n const re = new RegExp(`^(?:${s})$`);\n return (v) => re.test(v);\n } catch {\n return (v) => v === s;\n }\n}\n\n/**\n * Select which frames a transform applies to (Grafana transformation.filter).\n * Non-matching frames pass through unchanged and keep relative order.\n */\nexport function matchFrameFilter(\n frame: DataFrame,\n filter: FrameFilterConfig,\n): boolean {\n if (filter == null || filter === \"\") return true;\n if (typeof filter === \"string\") {\n const hit = compileMatcher(filter);\n return hit(String(frame.refId ?? \"\")) || hit(String(frame.name ?? \"\"));\n }\n const id = String(filter.id || \"byRefId\");\n const pattern = patternFromFilterOptions(filter.options);\n const hit = compileMatcher(pattern);\n if (id === \"byName\" || id === \"byFrameName\") {\n return hit(String(frame.name ?? \"\"));\n }\n if (id === \"byRefId\" || id === \"byFrameRefID\" || id === \"byFrameRefId\") {\n return hit(String(frame.refId ?? \"\"));\n }\n // default: try refId then name\n return hit(String(frame.refId ?? \"\")) || hit(String(frame.name ?? \"\"));\n}\n\nfunction applyWithFrameFilter(\n frames: DataFrame[],\n filter: FrameFilterConfig,\n fn: TransformerFn,\n options: Record<string, unknown>,\n): DataFrame[] {\n if (filter == null || filter === \"\") {\n return fn(frames, options);\n }\n const matched: DataFrame[] = [];\n const matchedIdx: number[] = [];\n const passthrough = new Map<number, DataFrame>();\n frames.forEach((f, i) => {\n if (matchFrameFilter(f, filter)) {\n matchedIdx.push(i);\n matched.push(f);\n } else {\n passthrough.set(i, f);\n }\n });\n if (!matched.length) return frames;\n const transformed = fn(matched, options);\n // If transformer collapses/expands frame count, append results after passthrough in original order:\n // replace matched block with transformed sequence starting at first matched index.\n const out: DataFrame[] = [];\n let t = 0;\n let inserted = false;\n for (let i = 0; i < frames.length; i++) {\n if (passthrough.has(i)) {\n out.push(passthrough.get(i)!);\n } else if (!inserted) {\n out.push(...transformed);\n inserted = true;\n t = transformed.length;\n }\n }\n if (!inserted) out.push(...transformed);\n void t;\n return out;\n}\n\nexport type ApplyTransformationsContext = {\n interpolate?: (value: string) => string;\n /** When true, WithTrace records frame list after each step (editor debug). */\n includeFrameSnapshots?: boolean;\n};\n\nexport type TransformStepSnapshot = {\n id: string;\n resolvedId: string;\n disabled?: boolean;\n frameCount: number;\n fieldNames: string[];\n rowCounts: number[];\n error?: string;\n /** Sanitized option keys only (no secrets) */\n optionKeys: string[];\n filtered?: boolean;\n};\n\nexport type TransformPipelineResult = {\n frames: DataFrame[];\n steps: TransformStepSnapshot[];\n diagnostics: TransformDiagnostic[];\n /**\n * Frame list after each step (index 0 = input clone).\n * Only populated when context.includeFrameSnapshots is true (editor debug).\n */\n frameSnapshots?: DataFrame[][];\n};\n\nfunction snapshotFrames(\n frames: DataFrame[],\n): Pick<TransformStepSnapshot, \"frameCount\" | \"fieldNames\" | \"rowCounts\"> {\n return {\n frameCount: frames.length,\n fieldNames: frames.flatMap((f) => f.fields.map((field) => field.name)),\n rowCounts: frames.map((f) => f.length ?? f.fields[0]?.values?.length ?? 0),\n };\n}\n\nexport function applyTransformationsWithTrace(\n frames: DataFrame[],\n transformations: Array<{\n id: string;\n options?: Record<string, unknown>;\n disabled?: boolean;\n filter?: unknown;\n }> = [],\n context?: ApplyTransformationsContext,\n): TransformPipelineResult {\n const diagnostics: TransformDiagnostic[] = [];\n const steps: TransformStepSnapshot[] = [];\n const includeSnaps = !!context?.includeFrameSnapshots;\n const frameSnapshots: DataFrame[][] | undefined = includeSnaps ? [] : undefined;\n let acc = deepCloneFrames(frames);\n frameSnapshots?.push(acc);\n steps.push({\n id: \"__input__\",\n resolvedId: \"__input__\",\n frameCount: acc.length,\n fieldNames: acc.flatMap((f) => f.fields.map((field) => field.name)),\n rowCounts: acc.map((f) => f.length ?? f.fields[0]?.values?.length ?? 0),\n optionKeys: [],\n });\n\n for (const t of transformations) {\n const resolvedId = resolveTransformerId(t.id);\n if (t.disabled) {\n steps.push({\n id: t.id,\n resolvedId,\n disabled: true,\n ...snapshotFrames(acc),\n optionKeys: Object.keys(t.options || {}),\n });\n frameSnapshots?.push(acc);\n continue;\n }\n const fn = getTransformer(resolvedId) ?? getTransformer(t.id);\n if (!fn) {\n diagnostics.push({\n id: t.id,\n level: \"warn\",\n message: `Unknown transformation: ${t.id}`,\n });\n steps.push({\n id: t.id,\n resolvedId,\n ...snapshotFrames(acc),\n error: `Unknown transformation: ${t.id}`,\n optionKeys: Object.keys(t.options || {}),\n });\n frameSnapshots?.push(acc);\n continue;\n }\n const defaults = DEFAULT_OPTIONS[resolvedId] ?? DEFAULT_OPTIONS[t.id] ?? {};\n const merged = interpolateOptions(\n { ...defaults, ...(t.options || {}) },\n context?.interpolate,\n );\n try {\n // Entry clone already detached input. Transformers should not mutate in place;\n // avoid unconditional inter-step deepClone (Task 12).\n acc = applyWithFrameFilter(\n acc,\n t.filter as FrameFilterConfig,\n fn,\n merged as Record<string, unknown>,\n );\n steps.push({\n id: t.id,\n resolvedId,\n ...snapshotFrames(acc),\n optionKeys: Object.keys(t.options || {}),\n filtered: t.filter != null && t.filter !== \"\",\n });\n frameSnapshots?.push(acc);\n } catch (e) {\n const msg = e instanceof Error ? e.message : String(e);\n diagnostics.push({ id: t.id, level: \"error\", message: msg });\n steps.push({\n id: t.id,\n resolvedId,\n ...snapshotFrames(acc),\n error: msg,\n optionKeys: Object.keys(t.options || {}),\n });\n // Spec: transformer failure must not return pre-transform data as Done success\n throw e;\n }\n }\n return { frames: acc, steps, diagnostics, frameSnapshots };\n}\n\n\n/** Extract numeric limit from limit-transform options. */\nfunction readLimitOption(options: Record<string, unknown> | undefined): number | undefined {\n if (!options) return undefined;\n const raw = options.limit ?? options.limitField ?? options.limitValue;\n if (raw == null) return undefined;\n const n = Math.floor(Number(raw));\n return Number.isFinite(n) && n >= 0 ? n : undefined;\n}\n\n/**\n * When sortBy is immediately followed by limit (same filter / no disable),\n * fuse into one top-K sortBy call. Preserves final semantics; avoids O(N log N)\n * full reorder when only K rows are kept.\n */\nfunction tryFuseSortLimit(\n transformations: Array<{\n id: string;\n options?: Record<string, unknown>;\n disabled?: boolean;\n filter?: unknown;\n }>,\n index: number,\n): { fusedOptions: Record<string, unknown>; skipNext: boolean } | null {\n const cur = transformations[index];\n const next = transformations[index + 1];\n if (!cur || !next) return null;\n if (cur.disabled || next.disabled) return null;\n const curId = resolveTransformerId(cur.id);\n const nextId = resolveTransformerId(next.id);\n if (curId !== \"sortBy\" || nextId !== \"limit\") return null;\n const f1 = cur.filter ?? null;\n const f2 = next.filter ?? null;\n if (JSON.stringify(f1) !== JSON.stringify(f2)) return null;\n const lim = readLimitOption(next.options as Record<string, unknown> | undefined);\n if (lim == null) return null;\n return {\n fusedOptions: { ...(cur.options || {}), limit: lim, limitField: lim, limitValue: lim },\n skipNext: true,\n };\n}\n\n/**\n * Fast path: one entry detach, no step snapshots / fieldNames / rowCounts.\n * Use applyTransformationsWithTrace for editor debug.\n */\nexport function applyTransformations(\n frames: DataFrame[],\n transformations: Array<{\n id: string;\n options?: Record<string, unknown>;\n disabled?: boolean;\n filter?: unknown;\n }> = [],\n diagnostics?: TransformDiagnostic[],\n context?: ApplyTransformationsContext,\n): DataFrame[] {\n // Always return frames detached from the input (even with zero transforms).\n let acc = deepCloneFrames(frames);\n if (!transformations.length) return acc;\n\n const localDiag: TransformDiagnostic[] = diagnostics ?? [];\n\n for (let i = 0; i < transformations.length; i++) {\n const t = transformations[i];\n if (t.disabled) continue;\n const resolvedId = resolveTransformerId(t.id);\n const fn = getTransformer(resolvedId) ?? getTransformer(t.id);\n if (!fn) {\n localDiag.push({\n id: t.id,\n level: \"warn\",\n message: `Unknown transformation: ${t.id}`,\n });\n continue;\n }\n const defaults = DEFAULT_OPTIONS[resolvedId] ?? DEFAULT_OPTIONS[t.id] ?? {};\n const fuse = tryFuseSortLimit(transformations, i);\n const stepOptions = fuse\n ? { ...defaults, ...fuse.fusedOptions }\n : { ...defaults, ...(t.options || {}) };\n const merged = interpolateOptions(stepOptions, context?.interpolate);\n try {\n acc = applyWithFrameFilter(\n acc,\n t.filter as FrameFilterConfig,\n fn,\n merged as Record<string, unknown>,\n );\n if (fuse?.skipNext) i += 1; // skip fused limit step\n } catch (e) {\n const msg = e instanceof Error ? e.message : String(e);\n localDiag.push({ id: t.id, level: \"error\", message: msg });\n throw e;\n }\n }\n\n if (diagnostics && diagnostics !== localDiag) {\n diagnostics.push(...localDiag);\n }\n return acc;\n}\n\nexport function listTransformerIds(): string[] {\n return listIdsFromRegistry();\n}\n","/**\n * Field matcher registry (Task 5.3) — IDs aligned with Grafana FieldMatcherID.\n * @see grafana-main/packages/grafana-data/src/transformations/matchers\n */\nimport type { DataFrame, Field } from \"../types\";\n\nexport enum FieldMatcherID {\n numeric = \"numeric\",\n time = \"time\",\n first = \"first\",\n firstTimeField = \"firstTimeField\",\n byType = \"byType\",\n byTypes = \"byTypes\",\n byName = \"byName\",\n byNames = \"byNames\",\n byRegexp = \"byRegexp\",\n byRegexpOrNames = \"byRegexpOrNames\",\n byFrameRefID = \"byFrameRefID\",\n byValue = \"byValue\",\n}\n\nexport type MatcherConfig = { id: string; options?: unknown };\n\nexport type FieldMatcherFn = (\n field: Field,\n frame?: DataFrame,\n allFrames?: DataFrame[],\n) => boolean;\n\nexport interface FieldMatcherInfo {\n id: string;\n name: string;\n description?: string;\n /** Whether this matcher is offered in the field override picker */\n pickerDefault?: boolean;\n get: (options?: unknown) => FieldMatcherFn;\n}\n\nfunction asNames(options: unknown): string[] {\n if (Array.isArray(options)) return options.map(String);\n if (\n options &&\n typeof options === \"object\" &&\n Array.isArray((options as any).names)\n ) {\n return ((options as any).names as unknown[]).map(String);\n }\n return String((options as any)?.names ?? options ?? \"\")\n .split(\",\")\n .map((s) => s.trim())\n .filter(Boolean);\n}\n\nfunction safeRegExp(pattern: unknown): RegExp | null {\n try {\n return new RegExp(String(pattern ?? \"\"));\n } catch {\n return null;\n }\n}\n\nconst MATCHERS: FieldMatcherInfo[] = [\n {\n id: FieldMatcherID.byName,\n name: \"字段名称为\",\n pickerDefault: true,\n get: (options) => (field) => field.name === options,\n },\n {\n id: FieldMatcherID.byNames,\n name: \"字段名称为（列表）\",\n pickerDefault: true,\n get: (options) => (field) => {\n const names = asNames(options);\n const hit = names.includes(field.name);\n const mode =\n typeof options === \"object\" && options && !Array.isArray(options)\n ? ((options as any).mode as string) || \"include\"\n : \"include\";\n return mode === \"exclude\" ? !hit : hit;\n },\n },\n {\n id: FieldMatcherID.byRegexp,\n name: \"字段名匹配正则\",\n pickerDefault: true,\n get: (options) => {\n const re = safeRegExp(options);\n return (field) => (re ? re.test(field.name) : false);\n },\n },\n {\n id: FieldMatcherID.byRegexpOrNames,\n name: \"字段名匹配正则或列表\",\n pickerDefault: false,\n get: (options) => {\n const opts = options as\n { pattern?: string; names?: string[] } | string | undefined;\n const pattern = typeof opts === \"string\" ? opts : (opts?.pattern ?? \"\");\n const names = typeof opts === \"object\" && opts ? asNames(opts) : [];\n const re = safeRegExp(pattern);\n return (field) =>\n names.includes(field.name) || (!!re && re.test(field.name));\n },\n },\n {\n id: FieldMatcherID.byType,\n name: \"字段类型为\",\n pickerDefault: true,\n get: (options) => (field) => field.type === options,\n },\n {\n id: FieldMatcherID.byTypes,\n name: \"字段类型为（列表）\",\n pickerDefault: false,\n get: (options) => {\n const types = Array.isArray(options)\n ? options.map(String)\n : String(options ?? \"\")\n .split(\",\")\n .map((s) => s.trim())\n .filter(Boolean);\n return (field) => types.includes(String(field.type));\n },\n },\n {\n id: FieldMatcherID.byFrameRefID,\n name: \"查询返回的字段\",\n pickerDefault: true,\n get: (options) => (_field, frame) =>\n (frame?.refId ?? \"\") === String(options ?? \"\"),\n },\n {\n id: FieldMatcherID.byValue,\n name: \"值为\",\n pickerDefault: true,\n get: (options) => (field) => {\n // Grafana byValue reduces field and compares — simplified: any equal numeric/string\n if (options && typeof options === \"object\" && \"op\" in (options as any)) {\n const n = Number((options as any).value);\n return field.values.some((v) => Number(v) === n);\n }\n const n = Number(options);\n if (!Number.isNaN(n) && String(options).trim() !== \"\") {\n return field.values.some((v) => Number(v) === n);\n }\n return field.values.some((v) => String(v) === String(options ?? \"\"));\n },\n },\n {\n id: FieldMatcherID.numeric,\n name: \"数值字段\",\n pickerDefault: false,\n get: () => (field) => field.type === \"number\",\n },\n {\n id: FieldMatcherID.time,\n name: \"时间字段\",\n pickerDefault: false,\n get: () => (field) => field.type === \"time\",\n },\n {\n id: FieldMatcherID.first,\n name: \"第一个字段\",\n pickerDefault: false,\n get: () => (field, frame) => !!frame && frame.fields[0] === field,\n },\n {\n id: FieldMatcherID.firstTimeField,\n name: \"第一个时间字段\",\n pickerDefault: false,\n get: () => (field, frame) => {\n if (!frame) return field.type === \"time\";\n const first = frame.fields.find((f) => f.type === \"time\");\n return first === field;\n },\n },\n];\n\nconst byId = new Map(MATCHERS.map((m) => [m.id, m]));\n\nexport function listFieldMatchers(): FieldMatcherInfo[] {\n return [...MATCHERS];\n}\n\nexport function listOverridePickerMatchers(): FieldMatcherInfo[] {\n return MATCHERS.filter((m) => m.pickerDefault);\n}\n\nexport function getFieldMatcherInfo(id: string): FieldMatcherInfo | undefined {\n return byId.get(id);\n}\n\n/** Resolve matcher; unknown id returns always-false (does not throw — round-trip safe). */\nexport function getFieldMatcher(config: MatcherConfig): FieldMatcherFn {\n const info = byId.get(config.id);\n if (!info) {\n return () => false;\n }\n return info.get(config.options);\n}\n\nexport function matchFieldWithRegistry(\n field: Field,\n matcher: MatcherConfig,\n frame?: DataFrame,\n allFrames?: DataFrame[],\n): boolean {\n return getFieldMatcher(matcher)(field, frame, allFrames);\n}\n","/**\n * Override property processors — typed process/shouldApply for standard field props.\n * @see Grafana fieldConfig registry process functions\n */\nimport type { Field, FieldConfig } from \"../types\";\n\nexport type OverridePropertyId =\n | \"unit\"\n | \"decimals\"\n | \"min\"\n | \"max\"\n | \"fieldMinMax\"\n | \"displayName\"\n | \"noValue\"\n | \"color\"\n | \"thresholds\"\n | \"mappings\"\n | \"links\"\n | \"actions\"\n | \"filterable\"\n | string;\n\nexport interface OverridePropertyProcessor {\n id: OverridePropertyId;\n name: string;\n path: string;\n /** Process raw editor value into stored config value */\n process: (value: unknown) => unknown;\n shouldApply?: (field: Field) => boolean;\n /** Identity used when value is undefined / clear */\n isEmpty?: (value: unknown) => boolean;\n}\n\nfunction identity(v: unknown) {\n return v;\n}\n\nfunction numberOrUndefined(v: unknown): number | undefined {\n if (v === \"\" || v === null || v === undefined) return undefined;\n const n = Number(v);\n return Number.isFinite(n) ? n : undefined;\n}\n\nexport const STANDARD_OVERRIDE_PROCESSORS: OverridePropertyProcessor[] = [\n {\n id: \"unit\",\n name: \"单位\",\n path: \"unit\",\n process: (v) => (v == null || v === \"\" ? undefined : String(v)),\n },\n {\n id: \"decimals\",\n name: \"小数位\",\n path: \"decimals\",\n process: numberOrUndefined,\n },\n { id: \"min\", name: \"最小值\", path: \"min\", process: numberOrUndefined },\n { id: \"max\", name: \"最大值\", path: \"max\", process: numberOrUndefined },\n {\n id: \"fieldMinMax\",\n name: \"字段最小/最大\",\n path: \"fieldMinMax\",\n process: (v) => (v == null ? undefined : Boolean(v)),\n },\n {\n id: \"displayName\",\n name: \"显示名称\",\n path: \"displayName\",\n process: (v) => (v == null || v === \"\" ? undefined : String(v)),\n },\n {\n id: \"noValue\",\n name: \"空值显示\",\n path: \"noValue\",\n process: (v) => (v == null ? undefined : String(v)),\n },\n { id: \"color\", name: \"颜色\", path: \"color\", process: identity },\n { id: \"thresholds\", name: \"阈值\", path: \"thresholds\", process: identity },\n { id: \"mappings\", name: \"值映射\", path: \"mappings\", process: identity },\n { id: \"links\", name: \"数据链接\", path: \"links\", process: identity },\n { id: \"actions\", name: \"动作\", path: \"actions\", process: identity },\n {\n id: \"filterable\",\n name: \"可过滤\",\n path: \"filterable\",\n process: (v) => (v == null ? undefined : Boolean(v)),\n },\n];\n\nconst processorById = new Map(\n STANDARD_OVERRIDE_PROCESSORS.map((p) => [p.id, p]),\n);\n\nexport function getOverrideProcessor(\n id: string,\n): OverridePropertyProcessor | undefined {\n if (processorById.has(id)) return processorById.get(id);\n if (id.startsWith(\"custom.\")) {\n return {\n id,\n name: id.slice(7),\n path: id,\n process: identity,\n };\n }\n // unknown property: identity process — preserve lossless, never apply via shouldApply false\n return {\n id,\n name: id,\n path: id,\n process: identity,\n shouldApply: () => false,\n };\n}\n\nexport function processOverrideValue(id: string, value: unknown): unknown {\n return getOverrideProcessor(id)!.process(value);\n}\n\nexport function isKnownOverrideProperty(id: string): boolean {\n return processorById.has(id) || id.startsWith(\"custom.\");\n}\n\n/** Apply a single processed property onto field config (does not mutate). */\nexport function applyProcessedProperty(\n config: FieldConfig,\n id: string,\n raw: unknown,\n): FieldConfig {\n const processor = getOverrideProcessor(id)!;\n if (\n processor.shouldApply === undefined &&\n !isKnownOverrideProperty(id) &&\n !id.startsWith(\"custom.\")\n ) {\n // unknown: keep config unchanged (lossless rule stored separately by consumer)\n return config;\n }\n const value = processor.process(raw);\n if (value === undefined) {\n const next = { ...config } as Record<string, unknown>;\n if (id.startsWith(\"custom.\")) {\n const custom = { ...(config.custom ?? {}) } as Record<string, unknown>;\n delete custom[id.slice(7)];\n return { ...config, custom };\n }\n delete next[id];\n return next as FieldConfig;\n }\n if (id.startsWith(\"custom.\")) {\n const key = id.slice(7);\n return { ...config, custom: { ...(config.custom ?? {}), [key]: value } };\n }\n return { ...config, [id]: value };\n}\n","import type { DataFrame, Field, FieldConfig } from \"./types\";\nimport {\n getFieldMatcher,\n matchFieldWithRegistry,\n type FieldMatcherFn,\n type MatcherConfig,\n} from \"./field/matchers\";\nimport {\n applyProcessedProperty,\n isKnownOverrideProperty,\n processOverrideValue,\n} from \"./field/overrideProcessors\";\n\nexport interface DynamicConfigValue {\n id: string;\n value?: unknown;\n}\n\nexport interface ConfigOverrideRule {\n matcher: MatcherConfig;\n properties: DynamicConfigValue[];\n}\n\nexport interface CompiledOverrideRule {\n match: FieldMatcherFn;\n properties: DynamicConfigValue[];\n matcher: MatcherConfig;\n}\n\n/** Weak identity cache: same overrides array reference reuses compiled matchers. */\nconst compiledRulesCache = new WeakMap<\n ConfigOverrideRule[],\n { rules: CompiledOverrideRule[]; defaultsKey: string }\n>();\n\n/** Bound small strong cache for ephemeral override arrays (Task 13). */\nconst compiledRulesLru: Array<{\n key: string;\n rules: CompiledOverrideRule[];\n}> = [];\nconst COMPILED_RULES_LRU_MAX = 32;\n\nfunction defaultsCacheKey(defaults: FieldConfig): string {\n // Cheap identity-ish key for defaults (not full dashboard stringify).\n const unit = defaults.unit ?? \"\";\n const decimals = defaults.decimals ?? \"\";\n const displayName = defaults.displayName ?? \"\";\n const customKeys = defaults.custom ? Object.keys(defaults.custom).join(\",\") : \"\";\n return `${unit}|${decimals}|${displayName}|${customKeys}`;\n}\n\nfunction rulesSignature(overrides: ConfigOverrideRule[]): string {\n // Stable short signature for LRU when array identity changes but content is equal.\n let s = String(overrides.length);\n for (let i = 0; i < overrides.length; i++) {\n const r = overrides[i];\n s += `|${r.matcher?.id}:${JSON.stringify(r.matcher?.options)}:${r.properties?.length ?? 0}`;\n for (const p of r.properties || []) s += `:${p.id}`;\n }\n return s;\n}\n\nexport function compileOverrideRules(\n overrides: ConfigOverrideRule[] = [],\n): CompiledOverrideRule[] {\n return overrides.map((rule) => ({\n matcher: rule.matcher,\n properties: rule.properties || [],\n match: getFieldMatcher(rule.matcher || { id: \"\" }),\n }));\n}\n\nfunction getCompiledRules(\n overrides: ConfigOverrideRule[],\n defaults: FieldConfig,\n): CompiledOverrideRule[] {\n const dKey = defaultsCacheKey(defaults);\n const weakHit = compiledRulesCache.get(overrides);\n if (weakHit && weakHit.defaultsKey === dKey) return weakHit.rules;\n\n const sig = rulesSignature(overrides) + \"::\" + dKey;\n const lruHit = compiledRulesLru.find((e) => e.key === sig);\n if (lruHit) {\n compiledRulesCache.set(overrides, { rules: lruHit.rules, defaultsKey: dKey });\n return lruHit.rules;\n }\n\n const rules = compileOverrideRules(overrides);\n compiledRulesCache.set(overrides, { rules, defaultsKey: dKey });\n compiledRulesLru.unshift({ key: sig, rules });\n if (compiledRulesLru.length > COMPILED_RULES_LRU_MAX) compiledRulesLru.pop();\n return rules;\n}\n\n/** Test/helper: clear compile caches. */\nexport function clearFieldOverrideCompileCache(): void {\n compiledRulesLru.length = 0;\n}\n\nexport {\n FieldMatcherID,\n listFieldMatchers,\n listOverridePickerMatchers,\n getFieldMatcher,\n matchFieldWithRegistry,\n} from \"./field/matchers\";\nexport type { FieldMatcherInfo, FieldMatcherFn } from \"./field/matchers\";\nexport {\n STANDARD_OVERRIDE_PROCESSORS,\n getOverrideProcessor,\n processOverrideValue,\n isKnownOverrideProperty,\n applyProcessedProperty,\n} from \"./field/overrideProcessors\";\n\n/** @deprecated prefer matchFieldWithRegistry — kept for existing call sites */\nexport function matchField(\n field: Field,\n matcher: { id: string; options?: unknown },\n frame?: DataFrame,\n): boolean {\n return matchFieldWithRegistry(field, matcher, frame);\n}\n\nfunction normalizePropId(id: string): string {\n if (\n id === \"unit\" ||\n id === \"decimals\" ||\n id === \"displayName\" ||\n id === \"min\" ||\n id === \"max\" ||\n id === \"noValue\" ||\n id === \"fieldMinMax\" ||\n id === \"filterable\" ||\n id === \"color\" ||\n id === \"thresholds\" ||\n id === \"mappings\" ||\n id === \"links\" ||\n id === \"actions\"\n ) {\n return id;\n }\n if (id.startsWith(\"standardOptions.\"))\n return id.slice(\"standardOptions.\".length);\n if (id.startsWith(\"custom.\")) return id;\n const customKeys = [\n \"drawStyle\",\n \"lineInterpolation\",\n \"lineWidth\",\n \"fillOpacity\",\n \"gradientMode\",\n \"spanNulls\",\n \"showPoints\",\n \"pointSize\",\n \"stacking\",\n \"axisPlacement\",\n \"axisLabel\",\n \"axisSoftMin\",\n \"axisSoftMax\",\n \"axisCenteredZero\",\n \"hideFrom\",\n \"scaleDistribution\",\n \"thresholdsStyle\",\n \"barAlignment\",\n \"lineStyle\",\n \"insertNulls\",\n \"barWidthFactor\",\n ];\n if (customKeys.includes(id)) return `custom.${id}`;\n return id;\n}\n\nfunction setNested(\n config: FieldConfig,\n path: string,\n value: unknown,\n): FieldConfig {\n if (path.startsWith(\"custom.\")) {\n const rest = path.slice(7);\n const custom = { ...(config.custom ?? {}) } as Record<string, unknown>;\n const parts = rest.split(\".\");\n let cur: any = custom;\n for (let i = 0; i < parts.length - 1; i++) {\n cur[parts[i]] =\n cur[parts[i]] && typeof cur[parts[i]] === \"object\"\n ? { ...cur[parts[i]] }\n : {};\n cur = cur[parts[i]];\n }\n cur[parts[parts.length - 1]] = value;\n return { ...config, custom };\n }\n if (path.includes(\".\")) {\n const parts = path.split(\".\");\n const root = { ...(config as any) };\n let cur: any = root;\n for (let i = 0; i < parts.length - 1; i++) {\n cur[parts[i]] =\n cur[parts[i]] && typeof cur[parts[i]] === \"object\"\n ? { ...cur[parts[i]] }\n : {};\n cur = cur[parts[i]];\n }\n cur[parts[parts.length - 1]] = value;\n return root as FieldConfig;\n }\n return { ...config, [path]: value };\n}\n\n/**\n * Apply field config defaults + ordered override rules.\n * Unknown property ids are preserved on the rule (caller) but not applied to field config.\n * Rules execute in array order (Grafana semantics).\n */\nexport function applyFieldOverrides(\n frames: DataFrame[],\n defaults: FieldConfig = {},\n overrides: ConfigOverrideRule[] = [],\n): DataFrame[] {\n const compiled = getCompiledRules(overrides, defaults);\n return frames.map((frame) => ({\n ...frame,\n fields: frame.fields.map((field) => {\n let config: FieldConfig = { ...defaults, ...field.config };\n for (const rule of compiled) {\n if (!rule.match(field, frame, frames)) continue;\n for (const prop of rule.properties) {\n const id = normalizePropId(prop.id);\n // Unknown non-custom properties: do not apply, but keep rule intact (lossless)\n if (!isKnownOverrideProperty(id) && !id.includes(\".\")) {\n continue;\n }\n const processed = processOverrideValue(id, prop.value);\n if (id.startsWith(\"custom.\") || !isKnownOverrideProperty(id)) {\n config = setNested(config, id, processed);\n } else {\n config = applyProcessedProperty(config, id, prop.value);\n }\n if (\n id === \"color\" &&\n prop.value &&\n typeof prop.value === \"object\" &&\n (prop.value as any).fixedColor\n ) {\n config = {\n ...config,\n color: {\n ...(config.color as any),\n ...(prop.value as any),\n mode: (prop.value as any).mode ?? \"fixed\",\n },\n };\n }\n }\n }\n return { ...field, config };\n }),\n }));\n}\n","/**\n * Compile + cache panel pipeline config (transforms + field overrides) by revision.\n * Byte/entry limited LRU (Task 9). Does not change transform semantics.\n */\nimport type { DataFrame, FieldConfig } from \"../types\";\nimport {\n applyFieldOverrides,\n compileOverrideRules,\n type CompiledOverrideRule,\n type ConfigOverrideRule,\n} from \"../fieldOverrides\";\nimport {\n applyTransformations,\n applyTransformationsWithTrace,\n resolveTransformerId,\n type TransformDiagnostic,\n type TransformPipelineResult,\n} from \"../transformations/runner\";\n\nexport type PipelineTransformStep = {\n id: string;\n options?: Record<string, unknown>;\n disabled?: boolean;\n filter?: unknown;\n};\n\nexport type PanelPipelineConfig = {\n transformations?: PipelineTransformStep[];\n fieldConfigDefaults?: FieldConfig;\n fieldConfigOverrides?: ConfigOverrideRule[];\n};\n\nexport type CompiledPanelPipeline = {\n /** Stable content revision of the config. */\n revision: string;\n /** Original transform list (trace path / unknown round-trip). */\n transformations: PipelineTransformStep[];\n /**\n * Fast-path steps: disabled dropped, aliases resolved, sort+limit fused,\n * default options merged. Semantics match applyTransformations.\n */\n fastSteps: PipelineTransformStep[];\n defaults: FieldConfig;\n /** Stable overrides array identity while cache entry lives. */\n overrides: ConfigOverrideRule[];\n /** Precompiled matchers (also cached inside fieldOverrides). */\n compiledOverrides: CompiledOverrideRule[];\n estimatedBytes: number;\n};\n\nconst DEFAULT_MAX_ENTRIES = 64;\nconst DEFAULT_MAX_BYTES = 512 * 1024; // signature + shallow config estimate\n\ntype CacheEntry = {\n revision: string;\n compiled: CompiledPanelPipeline;\n bytes: number;\n};\n\nconst cache = new Map<string, CacheEntry>();\nlet cacheBytes = 0;\nlet maxEntries = DEFAULT_MAX_ENTRIES;\nlet maxBytes = DEFAULT_MAX_BYTES;\n\nconst DEFAULT_OPTIONS: Record<string, Record<string, unknown>> = {\n limit: { limitField: 10 },\n sortBy: { sort: [] },\n reduce: { reducers: [\"sum\"] },\n histogram: { bucketCount: 10 },\n smoothing: { windowSize: 3 },\n filterByValue: { type: \"include\", filters: [] },\n prepareTimeSeries: { format: \"multi\" },\n};\n\nfunction readLimitOption(\n options: Record<string, unknown> | undefined,\n): number | undefined {\n if (!options) return undefined;\n const raw = options.limit ?? options.limitField ?? options.limitValue;\n if (raw == null) return undefined;\n const n = Math.floor(Number(raw));\n return Number.isFinite(n) && n >= 0 ? n : undefined;\n}\n\nfunction tryFuseSortLimit(\n steps: PipelineTransformStep[],\n index: number,\n): { fused: PipelineTransformStep; skipNext: boolean } | null {\n const cur = steps[index];\n const next = steps[index + 1];\n if (!cur || !next) return null;\n if (cur.disabled || next.disabled) return null;\n const curId = resolveTransformerId(cur.id);\n const nextId = resolveTransformerId(next.id);\n if (curId !== \"sortBy\" || nextId !== \"limit\") return null;\n if (JSON.stringify(cur.filter ?? null) !== JSON.stringify(next.filter ?? null)) {\n return null;\n }\n const lim = readLimitOption(next.options);\n if (lim == null) return null;\n const defaults = DEFAULT_OPTIONS.sortBy ?? {};\n return {\n fused: {\n id: \"sortBy\",\n filter: cur.filter,\n options: {\n ...defaults,\n ...(cur.options || {}),\n limit: lim,\n limitField: lim,\n limitValue: lim,\n },\n },\n skipNext: true,\n };\n}\n\n/** Build fast-path steps: resolve aliases, merge defaults, fuse sort→limit. */\nexport function compileTransformSteps(\n transformations: PipelineTransformStep[] = [],\n): PipelineTransformStep[] {\n const out: PipelineTransformStep[] = [];\n const src = transformations ?? [];\n for (let i = 0; i < src.length; i++) {\n const t = src[i];\n if (t.disabled) continue;\n const fuse = tryFuseSortLimit(src, i);\n if (fuse) {\n out.push(fuse.fused);\n if (fuse.skipNext) i += 1;\n continue;\n }\n const resolvedId = resolveTransformerId(t.id);\n const defaults = DEFAULT_OPTIONS[resolvedId] ?? DEFAULT_OPTIONS[t.id] ?? {};\n out.push({\n id: resolvedId,\n filter: t.filter,\n options: { ...defaults, ...(t.options || {}) },\n });\n }\n return out;\n}\n\nfunction estimateConfigBytes(config: PanelPipelineConfig): number {\n // Avoid full JSON.stringify of large option trees on every call — sample keys.\n let n = 128;\n const transforms = config.transformations ?? [];\n n += transforms.length * 64;\n for (const t of transforms) {\n n += String(t.id).length + 16;\n if (t.options) n += Object.keys(t.options).length * 24;\n }\n const overrides = config.fieldConfigOverrides ?? [];\n n += overrides.length * 96;\n for (const r of overrides) {\n n += String(r.matcher?.id ?? \"\").length;\n n += (r.properties?.length ?? 0) * 32;\n }\n const defaults = config.fieldConfigDefaults;\n if (defaults) n += Object.keys(defaults).length * 24 + 32;\n return n;\n}\n\n/**\n * Content revision for pipeline config. Stable across equivalent plain objects.\n * Not a cryptographic hash — collision-resistant enough for cache keys.\n */\nexport function pipelineConfigRevision(config: PanelPipelineConfig): string {\n const transforms = config.transformations ?? [];\n const overrides = config.fieldConfigOverrides ?? [];\n const defaults = config.fieldConfigDefaults ?? {};\n // Structured, bounded signature (no full options deep dump of huge arrays).\n const parts: string[] = [`t${transforms.length}`, `o${overrides.length}`];\n for (let i = 0; i < transforms.length; i++) {\n const t = transforms[i];\n parts.push(\n `${t.disabled ? \"D\" : \"\"}${t.id}:${stableSmallJson(t.options)}:${stableSmallJson(t.filter)}`,\n );\n }\n for (let i = 0; i < overrides.length; i++) {\n const r = overrides[i];\n const props = (r.properties || [])\n .map((p) => `${p.id}=${stableSmallJson(p.value)}`)\n .join(\",\");\n parts.push(\n `m${r.matcher?.id}:${stableSmallJson(r.matcher?.options)}:${props}`,\n );\n }\n parts.push(`d:${stableSmallJson(defaults)}`);\n return parts.join(\"|\");\n}\n\nfunction stableSmallJson(value: unknown): string {\n if (value == null) return \"\";\n if (typeof value === \"string\") return value.length > 64 ? value.slice(0, 64) : value;\n if (typeof value === \"number\" || typeof value === \"boolean\") return String(value);\n try {\n const s = JSON.stringify(value);\n return s.length > 256 ? s.slice(0, 256) : s;\n } catch {\n return \"?\";\n }\n}\n\nfunction touch(revision: string, entry: CacheEntry): void {\n // Map preserves insertion order; re-insert for LRU.\n cache.delete(revision);\n cache.set(revision, entry);\n}\n\nfunction evictIfNeeded(): void {\n while (\n (cache.size > maxEntries || cacheBytes > maxBytes) &&\n cache.size > 0\n ) {\n const oldest = cache.keys().next().value as string | undefined;\n if (oldest == null) break;\n const e = cache.get(oldest);\n cache.delete(oldest);\n if (e) cacheBytes -= e.bytes;\n }\n if (cacheBytes < 0) cacheBytes = 0;\n}\n\nexport function getCompiledPipeline(\n config: PanelPipelineConfig,\n): CompiledPanelPipeline {\n const revision = pipelineConfigRevision(config);\n const hit = cache.get(revision);\n if (hit) {\n touch(revision, hit);\n return hit.compiled;\n }\n\n const transformations = (config.transformations ?? []).map((t) => ({\n id: t.id,\n options: t.options ? { ...t.options } : undefined,\n disabled: t.disabled,\n filter: t.filter,\n }));\n const defaults = { ...(config.fieldConfigDefaults ?? {}) };\n const overrides = (config.fieldConfigOverrides ?? []).map((r) => ({\n matcher: { ...(r.matcher || { id: \"\" }) },\n properties: (r.properties || []).map((p) => ({ ...p })),\n }));\n const fastSteps = compileTransformSteps(transformations);\n const compiledOverrides = compileOverrideRules(overrides);\n const estimatedBytes = estimateConfigBytes(config);\n const compiled: CompiledPanelPipeline = {\n revision,\n transformations,\n fastSteps,\n defaults,\n overrides,\n compiledOverrides,\n estimatedBytes,\n };\n const bytes = Math.max(estimatedBytes, revision.length + 64);\n cacheBytes += bytes;\n cache.set(revision, { revision, compiled, bytes });\n evictIfNeeded();\n return compiled;\n}\n\nexport function runCompiledPipeline(\n frames: DataFrame[],\n compiled: CompiledPanelPipeline,\n opts?: { withTrace?: boolean },\n): {\n frames: DataFrame[];\n steps: TransformPipelineResult[\"steps\"];\n diagnostics: TransformDiagnostic[];\n} {\n if (opts?.withTrace) {\n const pipeline = applyTransformationsWithTrace(\n frames,\n compiled.transformations as any,\n );\n const series = applyFieldOverrides(\n pipeline.frames,\n compiled.defaults,\n compiled.overrides,\n );\n return {\n frames: series,\n steps: pipeline.steps,\n diagnostics: pipeline.diagnostics,\n };\n }\n\n // Fast path: pre-fused steps. applyTransformations still clones entry once.\n // Pass steps that already have defaults + fusion so runner fuse is a no-op\n // (sortBy already carries limit; next is not limit).\n const transformed = applyTransformations(\n frames,\n compiled.fastSteps as any,\n );\n const series = applyFieldOverrides(\n transformed,\n compiled.defaults,\n compiled.overrides,\n );\n return { frames: series, steps: [], diagnostics: [] };\n}\n\nexport function clearCompiledPipelineCache(): void {\n cache.clear();\n cacheBytes = 0;\n}\n\nexport function compiledPipelineCacheStats(): {\n entries: number;\n bytes: number;\n maxEntries: number;\n maxBytes: number;\n} {\n return {\n entries: cache.size,\n bytes: cacheBytes,\n maxEntries,\n maxBytes,\n };\n}\n\n/** Test/ops: tighten or restore cache caps. */\nexport function configureCompiledPipelineCache(opts: {\n maxEntries?: number;\n maxBytes?: number;\n}): void {\n if (opts.maxEntries != null) maxEntries = Math.max(1, opts.maxEntries);\n if (opts.maxBytes != null) maxBytes = Math.max(1024, opts.maxBytes);\n evictIfNeeded();\n}\n","/**\n * Shared transferable DataFrame wire format for panel pipeline worker (Task 9).\n */\nimport type { DataFrame, Field, FieldConfig, FieldType } from \"@grafana/data\";\n\nexport type WireField = {\n name: string;\n type: FieldType;\n config: FieldConfig;\n labels?: Record<string, string>;\n /** 'f64' = transferable Float64Array + null mask; 'clone' = structured-clone values. */\n encoding: \"f64\" | \"clone\";\n f64?: Float64Array;\n nulls?: Uint8Array;\n values?: unknown[];\n};\n\nexport type WireFrame = {\n refId?: string;\n name?: string;\n meta?: Record<string, unknown>;\n length: number;\n fields: WireField[];\n};\n\n/** True when every non-null value is a number (not string/uint64/object). */\nexport function canEncodeF64(values: unknown[]): boolean {\n for (let i = 0; i < values.length; i++) {\n const v = values[i];\n if (v == null) continue;\n if (typeof v !== \"number\") return false;\n }\n return true;\n}\n\nexport function packFramesForTransfer(frames: DataFrame[]): {\n frames: WireFrame[];\n transfer: Transferable[];\n} {\n const transfer: Transferable[] = [];\n const wire: WireFrame[] = (frames ?? []).map((frame) => {\n const fields: WireField[] = (frame.fields ?? []).map((f) => {\n const values = f.values ?? [];\n const type = f.type;\n const numericLike =\n (type === \"number\" || type === \"time\") && canEncodeF64(values);\n if (numericLike) {\n const f64 = new Float64Array(values.length);\n const nulls = new Uint8Array(values.length);\n for (let i = 0; i < values.length; i++) {\n const v = values[i];\n if (v == null) {\n nulls[i] = 1;\n f64[i] = 0;\n } else {\n nulls[i] = 0;\n f64[i] = v as number;\n }\n }\n transfer.push(f64.buffer, nulls.buffer);\n return {\n name: f.name,\n type,\n config: f.config ? { ...f.config } : {},\n labels: f.labels ? { ...f.labels } : undefined,\n encoding: \"f64\" as const,\n f64,\n nulls,\n };\n }\n return {\n name: f.name,\n type,\n config: f.config ? { ...f.config } : {},\n labels: f.labels ? { ...f.labels } : undefined,\n encoding: \"clone\" as const,\n values: values.slice(),\n };\n });\n const len =\n frame.length ??\n fields[0]?.f64?.length ??\n fields[0]?.values?.length ??\n 0;\n return {\n refId: frame.refId,\n name: frame.name,\n meta: frame.meta ? { ...frame.meta } : undefined,\n length: len,\n fields,\n };\n });\n return { frames: wire, transfer };\n}\n\nexport function unpackWireFrames(frames: WireFrame[]): DataFrame[] {\n return (frames ?? []).map((frame) => {\n const fields: Field[] = (frame.fields ?? []).map((f) => {\n if (f.encoding === \"f64\" && f.f64) {\n const n = f.f64.length;\n const values = new Array<number | null>(n);\n const nulls = f.nulls;\n for (let i = 0; i < n; i++) {\n values[i] = nulls && nulls[i] ? null : f.f64[i];\n }\n return {\n name: f.name,\n type: f.type,\n config: f.config ?? {},\n values,\n labels: f.labels,\n };\n }\n return {\n name: f.name,\n type: f.type,\n config: f.config ?? {},\n values: f.values ?? [],\n labels: f.labels,\n };\n });\n return {\n refId: frame.refId,\n name: frame.name,\n meta: frame.meta,\n fields,\n length:\n frame.length ??\n fields.reduce((m, field) => Math.max(m, field.values.length), 0),\n } satisfies DataFrame;\n });\n}\n","/// <reference lib=\"webworker\" />\n/**\n * Worker entry: unpack frames → compiled pipeline → pack result (Task 9).\n * Supports run + cancel; transferable numeric/time columns via packFramesForTransfer.\n */\nimport {\n getCompiledPipeline,\n runCompiledPipeline,\n} from \"@grafana/data\";\n// Side-effect: register transformers in worker scope.\nimport \"@grafana/data\";\nimport {\n packFramesForTransfer,\n unpackWireFrames,\n type WireFrame,\n} from \"./panelPipelineTransfer\";\n\nexport type PanelPipelineWorkerRequest = {\n type?: \"run\" | \"cancel\";\n id: number;\n generation?: number;\n frames?: WireFrame[];\n transformations?: unknown[];\n fieldConfigDefaults?: unknown;\n fieldConfigOverrides?: unknown[];\n requestId?: string;\n};\n\nexport type PanelPipelineWorkerResponse =\n | {\n id: number;\n generation?: number;\n ok: true;\n frames: WireFrame[];\n }\n | {\n id: number;\n generation?: number;\n ok: false;\n error: string;\n aborted?: boolean;\n };\n\n/** Cancelled ids (cleared once observed). */\nconst cancelled = new Set<number>();\n\nexport function handlePanelPipelineMessage(\n msg: PanelPipelineWorkerRequest,\n post: (res: PanelPipelineWorkerResponse, transfer?: Transferable[]) => void,\n): void {\n if (msg == null || msg.id == null) return;\n if (msg.type === \"cancel\") {\n cancelled.add(msg.id);\n return;\n }\n if (cancelled.has(msg.id)) {\n cancelled.delete(msg.id);\n post({\n id: msg.id,\n generation: msg.generation,\n ok: false,\n error: \"aborted\",\n aborted: true,\n });\n return;\n }\n try {\n const series = unpackWireFrames(msg.frames ?? []);\n const compiled = getCompiledPipeline({\n transformations: (msg.transformations as any) ?? [],\n fieldConfigDefaults: (msg.fieldConfigDefaults as any) ?? {},\n fieldConfigOverrides: (msg.fieldConfigOverrides as any) ?? [],\n });\n if (cancelled.has(msg.id)) {\n cancelled.delete(msg.id);\n post({\n id: msg.id,\n generation: msg.generation,\n ok: false,\n error: \"aborted\",\n aborted: true,\n });\n return;\n }\n const out = runCompiledPipeline(series, compiled, { withTrace: false });\n if (cancelled.has(msg.id)) {\n cancelled.delete(msg.id);\n post({\n id: msg.id,\n generation: msg.generation,\n ok: false,\n error: \"aborted\",\n aborted: true,\n });\n return;\n }\n const packed = packFramesForTransfer(out.frames);\n post(\n {\n id: msg.id,\n generation: msg.generation,\n ok: true,\n frames: packed.frames,\n },\n packed.transfer,\n );\n } catch (e) {\n post({\n id: msg.id,\n generation: msg.generation,\n ok: false,\n error: e instanceof Error ? e.message : String(e),\n });\n }\n}\n\nfunction onMessage(ev: MessageEvent<PanelPipelineWorkerRequest>) {\n handlePanelPipelineMessage(ev.data, (res, transfer) => {\n const scope = self as DedicatedWorkerGlobalScope;\n if (transfer?.length) scope.postMessage(res, transfer);\n else scope.postMessage(res);\n });\n}\n\nconst isDedicatedWorker =\n typeof WorkerGlobalScope !== \"undefined\" &&\n typeof self !== \"undefined\" &&\n // eslint-disable-next-line no-undef\n self instanceof WorkerGlobalScope;\n\nif (isDedicatedWorker) {\n (self as DedicatedWorkerGlobalScope).onmessage = onMessage;\n}\n\nexport { onMessage as handlePanelPipelineWorkerMessage 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\ No newline at end of file
dist/assets/panelPipelineWorker-5BqW8fRn.js → dist/assets/panelPipelineWorker-Basypt6p.js
(function() {
"use strict";
const TIME_SERIES_VALUE_FIELD_NAME = "Value";
const TIME_SERIES_TIME_FIELD_NAME = "Time";
function formatLabels(labels) {
if (!labels) return "";
return Object.entries(labels).filter(([, v]) => v != null && v !== "").map(([k, v]) => `${k}=${v}`).join(", ");
}
function getFieldDisplayName(field, frame, allFrames) {
const name = calculateFieldDisplayName(field, frame, allFrames);
if (field.state?.displayName !== name) {
field.state = { ...field.state || {}, displayName: name };
}
return name;
}
function isGenericValueName(s) {
const t = s.trim();
if (!t || t === TIME_SERIES_VALUE_FIELD_NAME) return true;
if (/^Value\s*\{/.test(t)) return true;
return false;
}
function calculateFieldDisplayName(field, frame, allFrames) {
const cfg = field.config ?? {};
if (cfg.displayName && String(cfg.displayName).length && !isGenericValueName(String(cfg.displayName))) {
return String(cfg.displayName);
}
if (cfg.displayNameFromDS && String(cfg.displayNameFromDS).length && !isGenericValueName(String(cfg.displayNameFromDS))) {
return String(cfg.displayNameFromDS);
}
if (field.type === "time" && !field.labels) {
return field.name || TIME_SERIES_TIME_FIELD_NAME;
}
const frames = allFrames?.length ? allFrames : frame ? [frame] : [];
let frameNamesDiffer = false;
if (frames.length > 1) {
for (let i = 1; i < frames.length; i++) {
if (frames[i].name !== frames[i - 1].name) {
frameNamesDiffer = true;
break;
}
}
}
const parts = [];
let frameNameAdded = false;
let labelsAdded = false;
if (frameNamesDiffer && frame?.name) {
parts.push(frame.name);
frameNameAdded = true;
}
if (field.name && !isGenericValueName(field.name)) {
parts.push(field.name);
}
if (field.labels && Object.keys(field.labels).length) {
const singleLabel = getSingleLabelName(
frames.length ? frames : frame ? [frame] : []
);
if (singleLabel && field.labels[singleLabel] != null && field.labels[singleLabel] !== "") {
parts.push(String(field.labels[singleLabel]));
labelsAdded = true;
} else {
const allLabels = formatLabels(field.labels);
if (allLabels) {
parts.push(allLabels);
labelsAdded = true;
}
}
}
if (frame && !frameNameAdded && !labelsAdded && isGenericValueName(field.name || "")) {
if (frame.name) {
parts.push(frame.name);
frameNameAdded = true;
}
}
if (parts.length) return parts.join(" ");
if (field.name) return field.name;
if (frame?.name) return frame.name;
return TIME_SERIES_VALUE_FIELD_NAME;
}
function getSingleLabelName(frames) {
const keys = /* @__PURE__ */ new Set();
for (const fr of frames) {
for (const f of fr.fields) {
if (!f.labels) continue;
for (const k of Object.keys(f.labels)) keys.add(k);
if (keys.size > 1) return null;
}
}
if (keys.size === 1) return [...keys][0];
return null;
}
const registry = /* @__PURE__ */ new Map();
function getTransformer(id) {
return registry.get(id);
......@@ -185,20 +273,203 @@
}
return acc;
}
function asNames(options) {
if (Array.isArray(options)) return options.map(String);
if (options && typeof options === "object" && Array.isArray(options.names)) {
return options.names.map(String);
var ReducerID = /* @__PURE__ */ ((ReducerID2) => {
ReducerID2["sum"] = "sum";
ReducerID2["max"] = "max";
ReducerID2["min"] = "min";
ReducerID2["mean"] = "mean";
ReducerID2["last"] = "last";
ReducerID2["first"] = "first";
ReducerID2["count"] = "count";
ReducerID2["lastNotNull"] = "lastNotNull";
ReducerID2["firstNotNull"] = "firstNotNull";
ReducerID2["range"] = "range";
ReducerID2["diff"] = "diff";
ReducerID2["diffperc"] = "diffperc";
ReducerID2["delta"] = "delta";
ReducerID2["step"] = "step";
ReducerID2["variance"] = "variance";
ReducerID2["stdDev"] = "stdDev";
ReducerID2["median"] = "median";
ReducerID2["allIsZero"] = "allIsZero";
ReducerID2["allIsNull"] = "allIsNull";
ReducerID2["changeCount"] = "changeCount";
ReducerID2["distinctCount"] = "distinctCount";
ReducerID2["logmin"] = "logmin";
return ReducerID2;
})(ReducerID || {});
function numericValues(field) {
return field.values.map((v) => v == null || v === "" ? null : Number(v)).filter((v) => v != null && !Number.isNaN(v));
}
function reduceField(field, reducers = [
"lastNotNull"
/* lastNotNull */
]) {
const nums = numericValues(field);
const out = {};
for (const r of reducers) {
if (r === "count") {
out[r] = nums.length;
continue;
}
if (r === "allIsNull") {
out[r] = field.values.every((v) => v == null || v === "");
continue;
}
if (r === "allIsZero") {
out[r] = nums.length > 0 && nums.every((n) => n === 0);
continue;
}
if (r === "distinctCount") {
out[r] = new Set(nums).size;
continue;
}
if (r === "changeCount") {
let c = 0;
for (let i = 1; i < nums.length; i++) if (nums[i] !== nums[i - 1]) c++;
out[r] = c;
continue;
}
if (!nums.length) {
out[r] = null;
continue;
}
switch (r) {
case "last":
out[r] = Number(field.values[field.values.length - 1]);
break;
case "lastNotNull":
out[r] = nums[nums.length - 1];
break;
case "first":
out[r] = Number(field.values[0]);
break;
case "firstNotNull":
out[r] = nums[0];
break;
case "min":
out[r] = Math.min(...nums);
break;
case "max":
out[r] = Math.max(...nums);
break;
case "mean":
out[r] = nums.reduce((a, b) => a + b, 0) / nums.length;
break;
case "sum":
out[r] = nums.reduce((a, b) => a + b, 0);
break;
case "range":
out[r] = Math.max(...nums) - Math.min(...nums);
break;
case "diff":
out[r] = nums[nums.length - 1] - nums[0];
break;
case "diffperc": {
const a = nums[0];
out[r] = a === 0 ? null : (nums[nums.length - 1] - a) / Math.abs(a) * 100;
break;
}
case "delta": {
let d = 0;
for (let i = 1; i < nums.length; i++) {
const step = nums[i] - nums[i - 1];
if (step > 0) d += step;
}
out[r] = d;
break;
}
case "step": {
let maxStep = 0;
for (let i = 1; i < nums.length; i++)
maxStep = Math.max(maxStep, Math.abs(nums[i] - nums[i - 1]));
out[r] = maxStep;
break;
}
case "variance": {
const mean = nums.reduce((a, b) => a + b, 0) / nums.length;
out[r] = nums.reduce((a, b) => a + (b - mean) ** 2, 0) / nums.length;
break;
}
case "stdDev": {
const mean = nums.reduce((a, b) => a + b, 0) / nums.length;
const v = nums.reduce((a, b) => a + (b - mean) ** 2, 0) / nums.length;
out[r] = Math.sqrt(v);
break;
}
case "median": {
const s = [...nums].sort((a, b) => a - b);
const mid = Math.floor(s.length / 2);
out[r] = s.length % 2 ? s[mid] : (s[mid - 1] + s[mid]) / 2;
break;
}
case "logmin": {
const pos = nums.filter((n) => n > 0);
out[r] = pos.length ? Math.min(...pos) : null;
break;
}
default:
out[r] = nums[nums.length - 1];
}
}
return String(options?.names ?? options ?? "").split(",").map((s) => s.trim()).filter(Boolean);
return out;
}
function stringStartsAsRegEx(str) {
return Boolean(str) && str[0] === "/";
}
function stringToJsRegex(str) {
if (!stringStartsAsRegEx(str)) {
return new RegExp(`^${str}$`);
}
const match = str.match(/^\/(.*?)\/(g?i?m?y?s?)$/);
if (!match) {
throw new Error(`'${str}' is not a valid regular expression.`);
}
return new RegExp(match[1], match[2]);
}
function safeRegExp(pattern) {
function stringToJsRegexSafe(str) {
try {
return new RegExp(String(pattern ?? ""));
const s = String(str ?? "");
if (!s) return null;
return stringToJsRegex(s);
} catch {
return null;
}
}
function compareFieldValues(left, op, right) {
const o = String(op).toLowerCase();
const lv = left;
const rv = right;
switch (o) {
case "eq":
case "==":
return lv == rv;
case "neq":
case "!=":
return lv != rv;
case "gt":
case ">":
return Number(lv) > Number(rv);
case "gte":
case ">=":
return Number(lv) >= Number(rv);
case "lt":
case "<":
return Number(lv) < Number(rv);
case "lte":
case "<=":
return Number(lv) <= Number(rv);
default:
return lv == rv;
}
}
function asNames(options) {
if (Array.isArray(options)) return options.map(String);
if (options && typeof options === "object" && Array.isArray(options.names)) {
return options.names.map(String);
}
return String(options?.names ?? options ?? "").split(",").map((s) => s.trim()).filter(Boolean);
}
const MATCHERS = [
{
id: "byName",
......@@ -222,8 +493,12 @@
name: "字段名匹配正则",
pickerDefault: true,
get: (options) => {
const re = safeRegExp(options);
return (field) => re ? re.test(field.name) : false;
const re = stringToJsRegexSafe(options);
return (field, frame, allFrames) => {
if (!re) return false;
const displayName = getFieldDisplayName(field, frame, allFrames);
return re.test(displayName) || re.test(field.name);
};
}
},
{
......@@ -234,8 +509,13 @@
const opts = options;
const pattern = typeof opts === "string" ? opts : opts?.pattern ?? "";
const names = typeof opts === "object" && opts ? asNames(opts) : [];
const re = safeRegExp(pattern);
return (field) => names.includes(field.name) || !!re && re.test(field.name);
const re = stringToJsRegexSafe(pattern);
return (field, frame, allFrames) => {
if (names.includes(field.name)) return true;
if (!re) return false;
const displayName = getFieldDisplayName(field, frame, allFrames);
return re.test(displayName) || re.test(field.name);
};
}
},
{
......@@ -261,18 +541,28 @@
},
{
id: "byValue",
name: "值为",
name: "值为（reducer）",
description: "将字段 reduce 为单值后与阈值比较（对齐 Grafana fieldValueMatcher）",
pickerDefault: true,
get: (options) => (field) => {
if (options && typeof options === "object" && "op" in options) {
const n2 = Number(options.value);
return field.values.some((v) => Number(v) === n2);
}
const n = Number(options);
if (!Number.isNaN(n) && String(options).trim() !== "") {
return field.values.some((v) => Number(v) === n);
get: (options) => {
const props = options ?? {};
if (options != null && (typeof options === "number" || typeof options === "string")) {
const target = options;
return (field) => field.values.some((v) => {
if (typeof target === "number") return Number(v) === target;
return String(v) === String(target);
});
}
return field.values.some((v) => String(v) === String(options ?? ""));
const reducer = props.reducer;
if (!reducer) return () => false;
const op = props.op || "eq";
const isBoolean = reducer === ReducerID.allIsNull || reducer === ReducerID.allIsZero || reducer === "allIsNull" || reducer === "allIsZero";
return (field) => {
const reduced = reduceField(field, [reducer]);
const left = reduced[reducer];
if (isBoolean) return Boolean(left);
return compareFieldValues(left, op, props.value);
};
}
},
{
......@@ -520,10 +810,20 @@
return frames.map((frame) => ({
...frame,
fields: frame.fields.map((field) => {
let config = { ...defaults, ...field.config };
for (const rule of compiled) {
const mergedCustom = {
...defaults.custom ?? {},
...field.config?.custom ?? {}
};
let config = {
...defaults,
...field.config,
...Object.keys(mergedCustom).length ? { custom: mergedCustom } : {}
};
for (let ri = 0; ri < compiled.length; ri++) {
const rule = compiled[ri];
if (!rule.match(field, frame, frames)) continue;
for (const prop of rule.properties) {
const properties = overrides[ri]?.properties ?? rule.properties;
for (const prop of properties) {
const id = normalizePropId(prop.id);
if (!isKnownOverrideProperty(id) && !id.includes(".")) {
continue;
......@@ -903,10 +1203,9 @@
else scope.postMessage(res);
});
}
const isDedicatedWorker = typeof WorkerGlobalScope !== "undefined" && typeof self !== "undefined" && // eslint-disable-next-line no-undef
self instanceof WorkerGlobalScope;
const isDedicatedWorker = typeof WorkerGlobalScope !== "undefined" && typeof self !== "undefined" && self instanceof WorkerGlobalScope;
if (isDedicatedWorker) {
self.onmessage = onMessage;
}
})();
//# sourceMappingURL=panelPipelineWorker-5BqW8fRn.js.map
//# sourceMappingURL=panelPipelineWorker-Basypt6p.js.map
dist/assets/panelPipelineWorker-Basypt6p.js.map 0 → 100644
{"version":3,"file":"panelPipelineWorker-Basypt6p.js","sources":["../../grafana-data/src/dataframe.ts","../../grafana-data/src/transformations/registry.ts","../../grafana-data/src/transformations/runner.ts","../../grafana-data/src/reducers/registry.ts","../../grafana-data/src/text/string.ts","../../grafana-data/src/field/matchers.ts","../../grafana-data/src/field/overrideProcessors.ts","../../grafana-data/src/fieldOverrides.ts","../../grafana-data/src/performance/compiledPipeline.ts","../../grafana-vue-dashboard/src/query/panelPipelineTransfer.ts","../../grafana-vue-dashboard/src/query/panelPipelineWorker.ts"],"sourcesContent":["import type { DataFrame, Field, FieldType } from \"./types\";\n\nexport function createDataFrame(opts: {\n refId?: string;\n name?: string;\n meta?: Record<string, unknown>;\n fields: Array<\n Partial<Field> & { name: string; values: unknown[]; type?: FieldType }\n >;\n}): DataFrame {\n const fields: Field[] = opts.fields.map((f) => ({\n name: f.name,\n type: f.type ?? inferType(f.values),\n config: f.config ?? {},\n values: f.values,\n labels: f.labels,\n }));\n const length = fields.reduce((max, f) => Math.max(max, f.values.length), 0);\n return {\n refId: opts.refId,\n name: opts.name,\n fields,\n length,\n meta: opts.meta,\n };\n}\n\nfunction inferType(values: unknown[]): FieldType {\n const sample = values.find((v) => v != null);\n if (typeof sample === \"number\") return \"number\";\n if (typeof sample === \"boolean\") return \"boolean\";\n if (sample instanceof Date) return \"time\";\n if (\n typeof sample === \"string\" &&\n !Number.isNaN(Date.parse(sample)) &&\n /\\d{4}-\\d{2}-\\d{2}/.test(sample)\n ) {\n return \"time\";\n }\n return typeof sample === \"string\" ? \"string\" : \"other\";\n}\n\nconst TIME_SERIES_VALUE_FIELD_NAME = \"Value\";\nconst TIME_SERIES_TIME_FIELD_NAME = \"Time\";\n\n/** Format labels like Grafana: job=api, instance=localhost:9090 */\nexport function formatLabels(labels?: Record<string, string> | null): string {\n if (!labels) return \"\";\n return Object.entries(labels)\n .filter(([, v]) => v != null && v !== \"\")\n .map(([k, v]) => `${k}=${v}`)\n .join(\", \");\n}\n\n/**\n * Grafana-compatible field display name for legends / stats.\n * Priority: config.displayName → config.displayNameFromDS → labels / frame name → field name\n */\nexport function getFieldDisplayName(\n field: Field,\n frame?: DataFrame,\n allFrames?: DataFrame[],\n): string {\n // Recompute each time so label uniqueness across frames stays correct.\n // Only write field.state when the value actually changes — mutating reactive\n // DataFrame fields inside Vue computeds otherwise causes \"Maximum recursive updates\".\n const name = calculateFieldDisplayName(field, frame, allFrames);\n if (field.state?.displayName !== name) {\n field.state = { ...(field.state || {}), displayName: name };\n }\n return name;\n}\n\nfunction isGenericValueName(s: string): boolean {\n const t = s.trim();\n if (!t || t === TIME_SERIES_VALUE_FIELD_NAME) return true;\n // e.g. Value {job=\"api\", instance=\"localhost:9090\"}\n if (/^Value\\s*\\{/.test(t)) return true;\n return false;\n}\n\nfunction calculateFieldDisplayName(\n field: Field,\n frame?: DataFrame,\n allFrames?: DataFrame[],\n): string {\n const cfg = field.config ?? {};\n if (\n cfg.displayName &&\n String(cfg.displayName).length &&\n !isGenericValueName(String(cfg.displayName))\n ) {\n return String(cfg.displayName);\n }\n if (\n cfg.displayNameFromDS &&\n String(cfg.displayNameFromDS).length &&\n !isGenericValueName(String(cfg.displayNameFromDS))\n ) {\n return String(cfg.displayNameFromDS);\n }\n\n // Time field without labels → \"Time\"\n if (field.type === \"time\" && !field.labels) {\n return field.name || TIME_SERIES_TIME_FIELD_NAME;\n }\n\n const frames = allFrames?.length ? allFrames : frame ? [frame] : [];\n let frameNamesDiffer = false;\n if (frames.length > 1) {\n for (let i = 1; i < frames.length; i++) {\n if (frames[i].name !== frames[i - 1].name) {\n frameNamesDiffer = true;\n break;\n }\n }\n }\n\n const parts: string[] = [];\n let frameNameAdded = false;\n let labelsAdded = false;\n\n if (frameNamesDiffer && frame?.name) {\n parts.push(frame.name);\n frameNameAdded = true;\n }\n\n // Skip generic \"Value\" / \"Value {labels}\" field names — labels / frame name are more useful\n if (field.name && !isGenericValueName(field.name)) {\n parts.push(field.name);\n }\n\n if (field.labels && Object.keys(field.labels).length) {\n const singleLabel = getSingleLabelName(\n frames.length ? frames : frame ? [frame] : [],\n );\n if (\n singleLabel &&\n field.labels[singleLabel] != null &&\n field.labels[singleLabel] !== \"\"\n ) {\n parts.push(String(field.labels[singleLabel]));\n labelsAdded = true;\n } else {\n const allLabels = formatLabels(field.labels);\n if (allLabels) {\n parts.push(allLabels);\n labelsAdded = true;\n }\n }\n }\n\n // Value / Value {..} field with no labels → use frame name\n if (\n frame &&\n !frameNameAdded &&\n !labelsAdded &&\n isGenericValueName(field.name || \"\")\n ) {\n if (frame.name) {\n parts.push(frame.name);\n frameNameAdded = true;\n }\n }\n\n if (parts.length) return parts.join(\" \");\n if (field.name) return field.name;\n if (frame?.name) return frame.name;\n return TIME_SERIES_VALUE_FIELD_NAME;\n}\n\n/** If every frame only has one distinct label key across numeric fields, return that key. */\nfunction getSingleLabelName(frames: DataFrame[]): string | null {\n const keys = new Set<string>();\n for (const fr of frames) {\n for (const f of fr.fields) {\n if (!f.labels) continue;\n for (const k of Object.keys(f.labels)) keys.add(k);\n if (keys.size > 1) return null;\n }\n }\n if (keys.size === 1) return [...keys][0];\n return null;\n}\n\nexport function toDataFrameDTO(frame: DataFrame): DataFrame {\n return {\n ...frame,\n fields: frame.fields.map((f) => ({\n ...f,\n values: [...f.values],\n config: { ...f.config },\n })),\n };\n}\n","import type { DataFrame } from \"../types\";\n\nexport type TransformerFn = (\n frames: DataFrame[],\n options?: Record<string, unknown>,\n) => DataFrame[];\n\nconst registry = new Map<string, TransformerFn>();\n\nexport function registerTransformer(id: string, fn: TransformerFn): void {\n registry.set(id, fn);\n}\n\nexport function getTransformer(id: string): TransformerFn | undefined {\n return registry.get(id);\n}\n\nexport function listTransformerIds(): string[] {\n return [...registry.keys()];\n}\n\nfunction getTransformerRegistry(): Map<string, TransformerFn> {\n return registry;\n}\nvoid getTransformerRegistry;\n","import type { DataFrame } from \"../types\";\nimport {\n getTransformer,\n listTransformerIds as listIdsFromRegistry,\n type TransformerFn,\n} from \"./registry\";\n\nexport type { TransformerFn };\n\nconst ALIASES: Record<string, string> = {\n // filterFieldsByName is first-class; filterByName is internal alias\n filterByName: \"filterFieldsByName\",\n filterFramesByRefId: \"filterByRefId\",\n seriesToColumns: \"joinByField\",\n};\n\nconst DEFAULT_OPTIONS: Record<string, Record<string, unknown>> = {\n limit: { limitField: 10 },\n sortBy: { sort: [] },\n reduce: { reducers: [\"sum\"] },\n histogram: { bucketCount: 10 },\n smoothing: { windowSize: 3 },\n filterByValue: { type: \"include\", filters: [] },\n prepareTimeSeries: { format: \"multi\" },\n};\n\nexport type TransformDiagnostic = {\n id: string;\n level: \"warn\" | \"error\";\n message: string;\n};\n\nexport function resolveTransformerId(id: string): string {\n return ALIASES[id] ?? id;\n}\n\n/** Detach frames from caller ownership (one entry copy). Prefer slice over spread. */\nfunction deepCloneFrames(frames: DataFrame[]): DataFrame[] {\n return frames.map((frame) => {\n const fields = frame.fields.map((f) => ({\n name: f.name,\n type: f.type,\n config: f.config ? { ...f.config } : {},\n values: f.values.slice(),\n labels: f.labels ? { ...f.labels } : undefined,\n state: f.state ? { ...f.state } : undefined,\n }));\n return {\n refId: frame.refId,\n name: frame.name,\n meta: frame.meta ? { ...frame.meta } : undefined,\n fields,\n length: frame.length ?? fields[0]?.values.length ?? 0,\n };\n });\n}\n\nfunction interpolateOptions<T>(\n value: T,\n interpolate?: (s: string) => string,\n): T {\n if (!interpolate) return value;\n if (typeof value === \"string\") return interpolate(value) as T;\n if (Array.isArray(value))\n return value.map((v) => interpolateOptions(v, interpolate)) as T;\n if (value && typeof value === \"object\") {\n const out: Record<string, unknown> = {};\n for (const [k, v] of Object.entries(value as Record<string, unknown>)) {\n out[k] = interpolateOptions(v, interpolate);\n }\n return out as T;\n }\n return value;\n}\n\n/** Grafana MatcherConfig-like frame filter on a transformation step. */\nexport type FrameFilterConfig =\n | string\n | {\n id?: string;\n options?: unknown;\n }\n | null\n | undefined;\n\nfunction patternFromFilterOptions(options: unknown): string {\n if (options == null) return \"\";\n if (typeof options === \"string\" || typeof options === \"number\")\n return String(options);\n if (typeof options === \"object\") {\n const o = options as Record<string, unknown>;\n if (o.pattern != null) return String(o.pattern);\n if (o.refId != null) return String(o.refId);\n if (o.value != null) return String(o.value);\n if (Array.isArray(o.names))\n return (o.names as unknown[]).map(String).join(\"|\");\n }\n return String(options);\n}\n\nfunction compileMatcher(raw: string): (value: string) => boolean {\n const s = raw.trim();\n if (!s) return () => true;\n // /regex/flags\n const m = s.match(/^\\/(.+)\\/([gimsuy]*)$/);\n if (m) {\n try {\n const re = new RegExp(m[1], m[2]);\n return (v) => re.test(v);\n } catch {\n return (v) => v === s;\n }\n }\n // plain regex or alternation without slashes\n try {\n const re = new RegExp(`^(?:${s})$`);\n return (v) => re.test(v);\n } catch {\n return (v) => v === s;\n }\n}\n\n/**\n * Select which frames a transform applies to (Grafana transformation.filter).\n * Non-matching frames pass through unchanged and keep relative order.\n */\nexport function matchFrameFilter(\n frame: DataFrame,\n filter: FrameFilterConfig,\n): boolean {\n if (filter == null || filter === \"\") return true;\n if (typeof filter === \"string\") {\n const hit = compileMatcher(filter);\n return hit(String(frame.refId ?? \"\")) || hit(String(frame.name ?? \"\"));\n }\n const id = String(filter.id || \"byRefId\");\n const pattern = patternFromFilterOptions(filter.options);\n const hit = compileMatcher(pattern);\n if (id === \"byName\" || id === \"byFrameName\") {\n return hit(String(frame.name ?? \"\"));\n }\n if (id === \"byRefId\" || id === \"byFrameRefID\" || id === \"byFrameRefId\") {\n return hit(String(frame.refId ?? \"\"));\n }\n // default: try refId then name\n return hit(String(frame.refId ?? \"\")) || hit(String(frame.name ?? \"\"));\n}\n\nfunction applyWithFrameFilter(\n frames: DataFrame[],\n filter: FrameFilterConfig,\n fn: TransformerFn,\n options: Record<string, unknown>,\n): DataFrame[] {\n if (filter == null || filter === \"\") {\n return fn(frames, options);\n }\n const matched: DataFrame[] = [];\n const matchedIdx: number[] = [];\n const passthrough = new Map<number, DataFrame>();\n frames.forEach((f, i) => {\n if (matchFrameFilter(f, filter)) {\n matchedIdx.push(i);\n matched.push(f);\n } else {\n passthrough.set(i, f);\n }\n });\n if (!matched.length) return frames;\n const transformed = fn(matched, options);\n // If transformer collapses/expands frame count, append results after passthrough in original order:\n // replace matched block with transformed sequence starting at first matched index.\n const out: DataFrame[] = [];\n let t = 0;\n let inserted = false;\n for (let i = 0; i < frames.length; i++) {\n if (passthrough.has(i)) {\n out.push(passthrough.get(i)!);\n } else if (!inserted) {\n out.push(...transformed);\n inserted = true;\n t = transformed.length;\n }\n }\n if (!inserted) out.push(...transformed);\n void t;\n return out;\n}\n\nexport type ApplyTransformationsContext = {\n interpolate?: (value: string) => string;\n /** When true, WithTrace records frame list after each step (editor debug). */\n includeFrameSnapshots?: boolean;\n};\n\nexport type TransformStepSnapshot = {\n id: string;\n resolvedId: string;\n disabled?: boolean;\n frameCount: number;\n fieldNames: string[];\n rowCounts: number[];\n error?: string;\n /** Sanitized option keys only (no secrets) */\n optionKeys: string[];\n filtered?: boolean;\n};\n\nexport type TransformPipelineResult = {\n frames: DataFrame[];\n steps: TransformStepSnapshot[];\n diagnostics: TransformDiagnostic[];\n /**\n * Frame list after each step (index 0 = input clone).\n * Only populated when context.includeFrameSnapshots is true (editor debug).\n */\n frameSnapshots?: DataFrame[][];\n};\n\nfunction snapshotFrames(\n frames: DataFrame[],\n): Pick<TransformStepSnapshot, \"frameCount\" | \"fieldNames\" | \"rowCounts\"> {\n return {\n frameCount: frames.length,\n fieldNames: frames.flatMap((f) => f.fields.map((field) => field.name)),\n rowCounts: frames.map((f) => f.length ?? f.fields[0]?.values?.length ?? 0),\n };\n}\n\nexport function applyTransformationsWithTrace(\n frames: DataFrame[],\n transformations: Array<{\n id: string;\n options?: Record<string, unknown>;\n disabled?: boolean;\n filter?: unknown;\n }> = [],\n context?: ApplyTransformationsContext,\n): TransformPipelineResult {\n const diagnostics: TransformDiagnostic[] = [];\n const steps: TransformStepSnapshot[] = [];\n const includeSnaps = !!context?.includeFrameSnapshots;\n const frameSnapshots: DataFrame[][] | undefined = includeSnaps ? [] : undefined;\n let acc = deepCloneFrames(frames);\n frameSnapshots?.push(acc);\n steps.push({\n id: \"__input__\",\n resolvedId: \"__input__\",\n frameCount: acc.length,\n fieldNames: acc.flatMap((f) => f.fields.map((field) => field.name)),\n rowCounts: acc.map((f) => f.length ?? f.fields[0]?.values?.length ?? 0),\n optionKeys: [],\n });\n\n for (const t of transformations) {\n const resolvedId = resolveTransformerId(t.id);\n if (t.disabled) {\n steps.push({\n id: t.id,\n resolvedId,\n disabled: true,\n ...snapshotFrames(acc),\n optionKeys: Object.keys(t.options || {}),\n });\n frameSnapshots?.push(acc);\n continue;\n }\n const fn = getTransformer(resolvedId) ?? getTransformer(t.id);\n if (!fn) {\n diagnostics.push({\n id: t.id,\n level: \"warn\",\n message: `Unknown transformation: ${t.id}`,\n });\n steps.push({\n id: t.id,\n resolvedId,\n ...snapshotFrames(acc),\n error: `Unknown transformation: ${t.id}`,\n optionKeys: Object.keys(t.options || {}),\n });\n frameSnapshots?.push(acc);\n continue;\n }\n const defaults = DEFAULT_OPTIONS[resolvedId] ?? DEFAULT_OPTIONS[t.id] ?? {};\n const merged = interpolateOptions(\n { ...defaults, ...(t.options || {}) },\n context?.interpolate,\n );\n try {\n // Entry clone already detached input. Transformers should not mutate in place;\n // avoid unconditional inter-step deepClone (Task 12).\n acc = applyWithFrameFilter(\n acc,\n t.filter as FrameFilterConfig,\n fn,\n merged as Record<string, unknown>,\n );\n steps.push({\n id: t.id,\n resolvedId,\n ...snapshotFrames(acc),\n optionKeys: Object.keys(t.options || {}),\n filtered: t.filter != null && t.filter !== \"\",\n });\n frameSnapshots?.push(acc);\n } catch (e) {\n const msg = e instanceof Error ? e.message : String(e);\n diagnostics.push({ id: t.id, level: \"error\", message: msg });\n steps.push({\n id: t.id,\n resolvedId,\n ...snapshotFrames(acc),\n error: msg,\n optionKeys: Object.keys(t.options || {}),\n });\n // Spec: transformer failure must not return pre-transform data as Done success\n throw e;\n }\n }\n return { frames: acc, steps, diagnostics, frameSnapshots };\n}\n\n\n/** Extract numeric limit from limit-transform options. */\nfunction readLimitOption(options: Record<string, unknown> | undefined): number | undefined {\n if (!options) return undefined;\n const raw = options.limit ?? options.limitField ?? options.limitValue;\n if (raw == null) return undefined;\n const n = Math.floor(Number(raw));\n return Number.isFinite(n) && n >= 0 ? n : undefined;\n}\n\n/**\n * When sortBy is immediately followed by limit (same filter / no disable),\n * fuse into one top-K sortBy call. Preserves final semantics; avoids O(N log N)\n * full reorder when only K rows are kept.\n */\nfunction tryFuseSortLimit(\n transformations: Array<{\n id: string;\n options?: Record<string, unknown>;\n disabled?: boolean;\n filter?: unknown;\n }>,\n index: number,\n): { fusedOptions: Record<string, unknown>; skipNext: boolean } | null {\n const cur = transformations[index];\n const next = transformations[index + 1];\n if (!cur || !next) return null;\n if (cur.disabled || next.disabled) return null;\n const curId = resolveTransformerId(cur.id);\n const nextId = resolveTransformerId(next.id);\n if (curId !== \"sortBy\" || nextId !== \"limit\") return null;\n const f1 = cur.filter ?? null;\n const f2 = next.filter ?? null;\n if (JSON.stringify(f1) !== JSON.stringify(f2)) return null;\n const lim = readLimitOption(next.options as Record<string, unknown> | undefined);\n if (lim == null) return null;\n return {\n fusedOptions: { ...(cur.options || {}), limit: lim, limitField: lim, limitValue: lim },\n skipNext: true,\n };\n}\n\n/**\n * Fast path: one entry detach, no step snapshots / fieldNames / rowCounts.\n * Use applyTransformationsWithTrace for editor debug.\n */\nexport function applyTransformations(\n frames: DataFrame[],\n transformations: Array<{\n id: string;\n options?: Record<string, unknown>;\n disabled?: boolean;\n filter?: unknown;\n }> = [],\n diagnostics?: TransformDiagnostic[],\n context?: ApplyTransformationsContext,\n): DataFrame[] {\n // Always return frames detached from the input (even with zero transforms).\n let acc = deepCloneFrames(frames);\n if (!transformations.length) return acc;\n\n const localDiag: TransformDiagnostic[] = diagnostics ?? [];\n\n for (let i = 0; i < transformations.length; i++) {\n const t = transformations[i];\n if (t.disabled) continue;\n const resolvedId = resolveTransformerId(t.id);\n const fn = getTransformer(resolvedId) ?? getTransformer(t.id);\n if (!fn) {\n localDiag.push({\n id: t.id,\n level: \"warn\",\n message: `Unknown transformation: ${t.id}`,\n });\n continue;\n }\n const defaults = DEFAULT_OPTIONS[resolvedId] ?? DEFAULT_OPTIONS[t.id] ?? {};\n const fuse = tryFuseSortLimit(transformations, i);\n const stepOptions = fuse\n ? { ...defaults, ...fuse.fusedOptions }\n : { ...defaults, ...(t.options || {}) };\n const merged = interpolateOptions(stepOptions, context?.interpolate);\n try {\n acc = applyWithFrameFilter(\n acc,\n t.filter as FrameFilterConfig,\n fn,\n merged as Record<string, unknown>,\n );\n if (fuse?.skipNext) i += 1; // skip fused limit step\n } catch (e) {\n const msg = e instanceof Error ? e.message : String(e);\n localDiag.push({ id: t.id, level: \"error\", message: msg });\n throw e;\n }\n }\n\n if (diagnostics && diagnostics !== localDiag) {\n diagnostics.push(...localDiag);\n }\n return acc;\n}\n\nexport function listTransformerIds(): string[] {\n return listIdsFromRegistry();\n}\n","import type { Field } from \"../types\";\n\nexport enum ReducerID {\n sum = \"sum\",\n max = \"max\",\n min = \"min\",\n mean = \"mean\",\n last = \"last\",\n first = \"first\",\n count = \"count\",\n lastNotNull = \"lastNotNull\",\n firstNotNull = \"firstNotNull\",\n range = \"range\",\n diff = \"diff\",\n diffperc = \"diffperc\",\n delta = \"delta\",\n step = \"step\",\n variance = \"variance\",\n stdDev = \"stdDev\",\n median = \"median\",\n allIsZero = \"allIsZero\",\n allIsNull = \"allIsNull\",\n changeCount = \"changeCount\",\n distinctCount = \"distinctCount\",\n logmin = \"logmin\",\n}\n\nexport type FieldCalcs = Record<string, number | null | boolean | number[]>;\n\nfunction numericValues(field: Field): number[] {\n return field.values\n .map((v) => (v == null || v === \"\" ? null : Number(v)))\n .filter((v): v is number => v != null && !Number.isNaN(v));\n}\n\nexport function reduceField(\n field: Field,\n reducers: string[] = [ReducerID.lastNotNull],\n): FieldCalcs {\n const nums = numericValues(field);\n const out: FieldCalcs = {};\n for (const r of reducers) {\n if (r === ReducerID.count) {\n out[r] = nums.length;\n continue;\n }\n if (r === ReducerID.allIsNull) {\n out[r] = field.values.every((v) => v == null || v === \"\");\n continue;\n }\n if (r === ReducerID.allIsZero) {\n out[r] = nums.length > 0 && nums.every((n) => n === 0);\n continue;\n }\n if (r === ReducerID.distinctCount) {\n out[r] = new Set(nums).size;\n continue;\n }\n if (r === ReducerID.changeCount) {\n let c = 0;\n for (let i = 1; i < nums.length; i++) if (nums[i] !== nums[i - 1]) c++;\n out[r] = c;\n continue;\n }\n if (!nums.length) {\n out[r] = null;\n continue;\n }\n switch (r) {\n case ReducerID.last:\n out[r] = Number(field.values[field.values.length - 1]);\n break;\n case ReducerID.lastNotNull:\n out[r] = nums[nums.length - 1]!;\n break;\n case ReducerID.first:\n out[r] = Number(field.values[0]);\n break;\n case ReducerID.firstNotNull:\n out[r] = nums[0]!;\n break;\n case ReducerID.min:\n out[r] = Math.min(...nums);\n break;\n case ReducerID.max:\n out[r] = Math.max(...nums);\n break;\n case ReducerID.mean:\n out[r] = nums.reduce((a, b) => a + b, 0) / nums.length;\n break;\n case ReducerID.sum:\n out[r] = nums.reduce((a, b) => a + b, 0);\n break;\n case ReducerID.range:\n out[r] = Math.max(...nums) - Math.min(...nums);\n break;\n case ReducerID.diff:\n out[r] = nums[nums.length - 1]! - nums[0]!;\n break;\n case ReducerID.diffperc: {\n const a = nums[0]!;\n out[r] =\n a === 0 ? null : ((nums[nums.length - 1]! - a) / Math.abs(a)) * 100;\n break;\n }\n case ReducerID.delta: {\n let d = 0;\n for (let i = 1; i < nums.length; i++) {\n const step = nums[i]! - nums[i - 1]!;\n if (step > 0) d += step;\n }\n out[r] = d;\n break;\n }\n case ReducerID.step: {\n let maxStep = 0;\n for (let i = 1; i < nums.length; i++)\n maxStep = Math.max(maxStep, Math.abs(nums[i]! - nums[i - 1]!));\n out[r] = maxStep;\n break;\n }\n case ReducerID.variance: {\n const mean = nums.reduce((a, b) => a + b, 0) / nums.length;\n out[r] = nums.reduce((a, b) => a + (b - mean) ** 2, 0) / nums.length;\n break;\n }\n case ReducerID.stdDev: {\n const mean = nums.reduce((a, b) => a + b, 0) / nums.length;\n const v = nums.reduce((a, b) => a + (b - mean) ** 2, 0) / nums.length;\n out[r] = Math.sqrt(v);\n break;\n }\n case ReducerID.median: {\n const s = [...nums].sort((a, b) => a - b);\n const mid = Math.floor(s.length / 2);\n out[r] = s.length % 2 ? s[mid]! : (s[mid - 1]! + s[mid]!) / 2;\n break;\n }\n case ReducerID.logmin: {\n const pos = nums.filter((n) => n > 0);\n out[r] = pos.length ? Math.min(...pos) : null;\n break;\n }\n default:\n out[r] = nums[nums.length - 1]!;\n }\n }\n return out;\n}\n\nexport function listReducerIds(): string[] {\n return Object.values(ReducerID);\n}\n","/**\n * Grafana-compatible string helpers for field matchers / value mappings.\n * @see grafana-main/packages/grafana-data/src/text/string.ts\n */\n\nexport function stringStartsAsRegEx(str: string): boolean {\n return Boolean(str) && str[0] === \"/\";\n}\n\n/**\n * Convert a Grafana-style pattern to RegExp.\n * - bare string → anchored `^${str}$`\n * - `/pattern/flags` → RegExp(pattern, flags)\n */\nexport function stringToJsRegex(str: string): RegExp {\n if (!stringStartsAsRegEx(str)) {\n return new RegExp(`^${str}$`);\n }\n const match = str.match(/^\\/(.*?)\\/(g?i?m?y?s?)$/);\n if (!match) {\n throw new Error(`'${str}' is not a valid regular expression.`);\n }\n return new RegExp(match[1], match[2]);\n}\n\n/** Safe variant: invalid patterns return null instead of throwing. */\nexport function stringToJsRegexSafe(str: unknown): RegExp | null {\n try {\n const s = String(str ?? \"\");\n if (!s) return null;\n return stringToJsRegex(s);\n } catch {\n return null;\n }\n}\n","/**\n * Field matcher registry (Task 5.3) — IDs aligned with Grafana FieldMatcherID.\n * @see grafana-main/packages/grafana-data/src/transformations/matchers\n */\nimport type { DataFrame, Field } from \"../types\";\nimport { getFieldDisplayName } from \"../dataframe\";\nimport { stringToJsRegexSafe } from \"../text/string\";\nimport { reduceField, ReducerID } from \"../reducers/registry\";\n\n/** Grafana ComparisonOperation for byValue field matcher */\nexport type ComparisonOperation = \"eq\" | \"neq\" | \"gt\" | \"gte\" | \"lt\" | \"lte\" | \"EQ\" | \"NEQ\" | \"GT\" | \"GTE\" | \"LT\" | \"LTE\";\n\nfunction compareFieldValues(left: unknown, op: string, right: unknown): boolean {\n const o = String(op || \"eq\").toLowerCase();\n // boolean reducers already handled by caller\n const lv = left as any;\n const rv = right as any;\n // loose equality like Grafana for numbers/strings\n switch (o) {\n case \"eq\":\n case \"==\":\n \n return lv == rv;\n case \"neq\":\n case \"!=\":\n \n return lv != rv;\n case \"gt\":\n case \">\":\n return Number(lv) > Number(rv);\n case \"gte\":\n case \">=\":\n return Number(lv) >= Number(rv);\n case \"lt\":\n case \"<\":\n return Number(lv) < Number(rv);\n case \"lte\":\n case \"<=\":\n return Number(lv) <= Number(rv);\n default:\n \n return lv == rv;\n }\n}\n\n\nexport enum FieldMatcherID {\n numeric = \"numeric\",\n time = \"time\",\n first = \"first\",\n firstTimeField = \"firstTimeField\",\n byType = \"byType\",\n byTypes = \"byTypes\",\n byName = \"byName\",\n byNames = \"byNames\",\n byRegexp = \"byRegexp\",\n byRegexpOrNames = \"byRegexpOrNames\",\n byFrameRefID = \"byFrameRefID\",\n byValue = \"byValue\",\n}\n\nexport type MatcherConfig = { id: string; options?: unknown };\n\nexport type FieldMatcherFn = (\n field: Field,\n frame?: DataFrame,\n allFrames?: DataFrame[],\n) => boolean;\n\nexport interface FieldMatcherInfo {\n id: string;\n name: string;\n description?: string;\n /** Whether this matcher is offered in the field override picker */\n pickerDefault?: boolean;\n get: (options?: unknown) => FieldMatcherFn;\n}\n\nfunction asNames(options: unknown): string[] {\n if (Array.isArray(options)) return options.map(String);\n if (\n options &&\n typeof options === \"object\" &&\n Array.isArray((options as any).names)\n ) {\n return ((options as any).names as unknown[]).map(String);\n }\n return String((options as any)?.names ?? options ?? \"\")\n .split(\",\")\n .map((s) => s.trim())\n .filter(Boolean);\n}\n\n\nconst MATCHERS: FieldMatcherInfo[] = [\n {\n id: FieldMatcherID.byName,\n name: \"字段名称为\",\n pickerDefault: true,\n get: (options) => (field) => field.name === options,\n },\n {\n id: FieldMatcherID.byNames,\n name: \"字段名称为（列表）\",\n pickerDefault: true,\n get: (options) => (field) => {\n const names = asNames(options);\n const hit = names.includes(field.name);\n const mode =\n typeof options === \"object\" && options && !Array.isArray(options)\n ? ((options as any).mode as string) || \"include\"\n : \"include\";\n return mode === \"exclude\" ? !hit : hit;\n },\n },\n {\n id: FieldMatcherID.byRegexp,\n name: \"字段名匹配正则\",\n pickerDefault: true,\n get: (options) => {\n const re = stringToJsRegexSafe(options);\n // Grafana matches getFieldDisplayName (not only raw field.name)\n return (field, frame, allFrames) => {\n if (!re) return false;\n const displayName = getFieldDisplayName(field, frame, allFrames);\n return re.test(displayName) || re.test(field.name);\n };\n },\n },\n {\n id: FieldMatcherID.byRegexpOrNames,\n name: \"字段名匹配正则或列表\",\n pickerDefault: false,\n get: (options) => {\n const opts = options as\n | { pattern?: string; names?: string[] }\n | string\n | undefined;\n const pattern = typeof opts === \"string\" ? opts : (opts?.pattern ?? \"\");\n const names = typeof opts === \"object\" && opts ? asNames(opts) : [];\n const re = stringToJsRegexSafe(pattern);\n return (field, frame, allFrames) => {\n if (names.includes(field.name)) return true;\n if (!re) return false;\n const displayName = getFieldDisplayName(field, frame, allFrames);\n return re.test(displayName) || re.test(field.name);\n };\n },\n },\n {\n id: FieldMatcherID.byType,\n name: \"字段类型为\",\n pickerDefault: true,\n get: (options) => (field) => field.type === options,\n },\n {\n id: FieldMatcherID.byTypes,\n name: \"字段类型为（列表）\",\n pickerDefault: false,\n get: (options) => {\n const types = Array.isArray(options)\n ? options.map(String)\n : String(options ?? \"\")\n .split(\",\")\n .map((s) => s.trim())\n .filter(Boolean);\n return (field) => types.includes(String(field.type));\n },\n },\n {\n id: FieldMatcherID.byFrameRefID,\n name: \"查询返回的字段\",\n pickerDefault: true,\n get: (options) => (_field, frame) =>\n (frame?.refId ?? \"\") === String(options ?? \"\"),\n },\n {\n id: FieldMatcherID.byValue,\n name: \"值为（reducer）\",\n description: \"将字段 reduce 为单值后与阈值比较（对齐 Grafana fieldValueMatcher）\",\n pickerDefault: true,\n get: (options) => {\n // Grafana FieldValueMatcherConfig: { reducer, op?, value? }\n // Legacy simplified forms still accepted for older tests/fixtures.\n const props = (options ?? {}) as {\n reducer?: string;\n op?: string;\n value?: unknown;\n };\n // Legacy: bare number/string → any raw value equals (compat)\n if (\n options != null &&\n (typeof options === \"number\" || typeof options === \"string\")\n ) {\n const target = options;\n return (field) =>\n field.values.some((v) => {\n if (typeof target === \"number\") return Number(v) === target;\n return String(v) === String(target);\n });\n }\n const reducer = props.reducer;\n if (!reducer) return () => false;\n const op = props.op || \"eq\";\n const isBoolean =\n reducer === ReducerID.allIsNull ||\n reducer === ReducerID.allIsZero ||\n reducer === \"allIsNull\" ||\n reducer === \"allIsZero\";\n return (field) => {\n // reduceField(field, reducers[]) signature in this codebase\n const reduced = reduceField(field as any, [reducer]) as Record<\n string,\n unknown\n >;\n const left = reduced[reducer];\n if (isBoolean) return Boolean(left);\n return compareFieldValues(left, op, props.value);\n };\n },\n },\n {\n id: FieldMatcherID.numeric,\n name: \"数值字段\",\n pickerDefault: false,\n get: () => (field) => field.type === \"number\",\n },\n {\n id: FieldMatcherID.time,\n name: \"时间字段\",\n pickerDefault: false,\n get: () => (field) => field.type === \"time\",\n },\n {\n id: FieldMatcherID.first,\n name: \"第一个字段\",\n pickerDefault: false,\n get: () => (field, frame) => !!frame && frame.fields[0] === field,\n },\n {\n id: FieldMatcherID.firstTimeField,\n name: \"第一个时间字段\",\n pickerDefault: false,\n get: () => (field, frame) => {\n if (!frame) return field.type === \"time\";\n const first = frame.fields.find((f) => f.type === \"time\");\n return first === field;\n },\n },\n];\n\nconst byId = new Map(MATCHERS.map((m) => [m.id, m]));\n\nexport function listFieldMatchers(): FieldMatcherInfo[] {\n return [...MATCHERS];\n}\n\nexport function listOverridePickerMatchers(): FieldMatcherInfo[] {\n return MATCHERS.filter((m) => m.pickerDefault);\n}\n\nexport function getFieldMatcherInfo(id: string): FieldMatcherInfo | undefined {\n return byId.get(id);\n}\n\n/** Resolve matcher; unknown id returns always-false (does not throw — round-trip safe). */\nexport function getFieldMatcher(config: MatcherConfig): FieldMatcherFn {\n const info = byId.get(config.id);\n if (!info) {\n return () => false;\n }\n return info.get(config.options);\n}\n\nexport function matchFieldWithRegistry(\n field: Field,\n matcher: MatcherConfig,\n frame?: DataFrame,\n allFrames?: DataFrame[],\n): boolean {\n return getFieldMatcher(matcher)(field, frame, allFrames);\n}\n","/**\n * Override property processors — typed process/shouldApply for standard field props.\n * @see Grafana fieldConfig registry process functions\n */\nimport type { Field, FieldConfig } from \"../types\";\n\nexport type OverridePropertyId =\n | \"unit\"\n | \"decimals\"\n | \"min\"\n | \"max\"\n | \"fieldMinMax\"\n | \"displayName\"\n | \"noValue\"\n | \"color\"\n | \"thresholds\"\n | \"mappings\"\n | \"links\"\n | \"actions\"\n | \"filterable\"\n | string;\n\nexport interface OverridePropertyProcessor {\n id: OverridePropertyId;\n name: string;\n path: string;\n /** Process raw editor value into stored config value */\n process: (value: unknown) => unknown;\n shouldApply?: (field: Field) => boolean;\n /** Identity used when value is undefined / clear */\n isEmpty?: (value: unknown) => boolean;\n}\n\nfunction identity(v: unknown) {\n return v;\n}\n\nfunction numberOrUndefined(v: unknown): number | undefined {\n if (v === \"\" || v === null || v === undefined) return undefined;\n const n = Number(v);\n return Number.isFinite(n) ? n : undefined;\n}\n\nexport const STANDARD_OVERRIDE_PROCESSORS: OverridePropertyProcessor[] = [\n {\n id: \"unit\",\n name: \"单位\",\n path: \"unit\",\n process: (v) => (v == null || v === \"\" ? undefined : String(v)),\n },\n {\n id: \"decimals\",\n name: \"小数位\",\n path: \"decimals\",\n process: numberOrUndefined,\n },\n { id: \"min\", name: \"最小值\", path: \"min\", process: numberOrUndefined },\n { id: \"max\", name: \"最大值\", path: \"max\", process: numberOrUndefined },\n {\n id: \"fieldMinMax\",\n name: \"字段最小/最大\",\n path: \"fieldMinMax\",\n process: (v) => (v == null ? undefined : Boolean(v)),\n },\n {\n id: \"displayName\",\n name: \"显示名称\",\n path: \"displayName\",\n process: (v) => (v == null || v === \"\" ? undefined : String(v)),\n },\n {\n id: \"noValue\",\n name: \"空值显示\",\n path: \"noValue\",\n process: (v) => (v == null ? undefined : String(v)),\n },\n { id: \"color\", name: \"颜色\", path: \"color\", process: identity },\n { id: \"thresholds\", name: \"阈值\", path: \"thresholds\", process: identity },\n { id: \"mappings\", name: \"值映射\", path: \"mappings\", process: identity },\n { id: \"links\", name: \"数据链接\", path: \"links\", process: identity },\n { id: \"actions\", name: \"动作\", path: \"actions\", process: identity },\n {\n id: \"filterable\",\n name: \"可过滤\",\n path: \"filterable\",\n process: (v) => (v == null ? undefined : Boolean(v)),\n },\n];\n\nconst processorById = new Map(\n STANDARD_OVERRIDE_PROCESSORS.map((p) => [p.id, p]),\n);\n\nexport function getOverrideProcessor(\n id: string,\n): OverridePropertyProcessor | undefined {\n if (processorById.has(id)) return processorById.get(id);\n if (id.startsWith(\"custom.\")) {\n return {\n id,\n name: id.slice(7),\n path: id,\n process: identity,\n };\n }\n // unknown property: identity process — preserve lossless, never apply via shouldApply false\n return {\n id,\n name: id,\n path: id,\n process: identity,\n shouldApply: () => false,\n };\n}\n\nexport function processOverrideValue(id: string, value: unknown): unknown {\n return getOverrideProcessor(id)!.process(value);\n}\n\nexport function isKnownOverrideProperty(id: string): boolean {\n return processorById.has(id) || id.startsWith(\"custom.\");\n}\n\n/** Apply a single processed property onto field config (does not mutate). */\nexport function applyProcessedProperty(\n config: FieldConfig,\n id: string,\n raw: unknown,\n): FieldConfig {\n const processor = getOverrideProcessor(id)!;\n if (\n processor.shouldApply === undefined &&\n !isKnownOverrideProperty(id) &&\n !id.startsWith(\"custom.\")\n ) {\n // unknown: keep config unchanged (lossless rule stored separately by consumer)\n return config;\n }\n const value = processor.process(raw);\n if (value === undefined) {\n const next = { ...config } as Record<string, unknown>;\n if (id.startsWith(\"custom.\")) {\n const custom = { ...(config.custom ?? {}) } as Record<string, unknown>;\n delete custom[id.slice(7)];\n return { ...config, custom };\n }\n delete next[id];\n return next as FieldConfig;\n }\n if (id.startsWith(\"custom.\")) {\n const key = id.slice(7);\n return { ...config, custom: { ...(config.custom ?? {}), [key]: value } };\n }\n return { ...config, [id]: value };\n}\n","import type { DataFrame, Field, FieldConfig } from \"./types\";\nimport {\n getFieldMatcher,\n matchFieldWithRegistry,\n type FieldMatcherFn,\n type MatcherConfig,\n} from \"./field/matchers\";\nimport {\n applyProcessedProperty,\n isKnownOverrideProperty,\n processOverrideValue,\n} from \"./field/overrideProcessors\";\n\nexport interface DynamicConfigValue {\n id: string;\n value?: unknown;\n}\n\nexport interface ConfigOverrideRule {\n matcher: MatcherConfig;\n properties: DynamicConfigValue[];\n}\n\nexport interface CompiledOverrideRule {\n match: FieldMatcherFn;\n properties: DynamicConfigValue[];\n matcher: MatcherConfig;\n}\n\n/** Weak identity cache: same overrides array reference reuses compiled matchers. */\nconst compiledRulesCache = new WeakMap<\n ConfigOverrideRule[],\n { rules: CompiledOverrideRule[]; defaultsKey: string }\n>();\n\n/** Bound small strong cache for ephemeral override arrays (Task 13). */\nconst compiledRulesLru: Array<{\n key: string;\n rules: CompiledOverrideRule[];\n}> = [];\nconst COMPILED_RULES_LRU_MAX = 32;\n\nfunction defaultsCacheKey(defaults: FieldConfig): string {\n // Cheap identity-ish key for defaults (not full dashboard stringify).\n const unit = defaults.unit ?? \"\";\n const decimals = defaults.decimals ?? \"\";\n const displayName = defaults.displayName ?? \"\";\n const customKeys = defaults.custom ? Object.keys(defaults.custom).join(\",\") : \"\";\n return `${unit}|${decimals}|${displayName}|${customKeys}`;\n}\n\nfunction rulesSignature(overrides: ConfigOverrideRule[]): string {\n // Stable short signature for LRU when array identity changes but content is equal.\n let s = String(overrides.length);\n for (let i = 0; i < overrides.length; i++) {\n const r = overrides[i];\n s += `|${r.matcher?.id}:${JSON.stringify(r.matcher?.options)}:${r.properties?.length ?? 0}`;\n for (const p of r.properties || []) s += `:${p.id}`;\n }\n return s;\n}\n\nexport function compileOverrideRules(\n overrides: ConfigOverrideRule[] = [],\n): CompiledOverrideRule[] {\n return overrides.map((rule) => ({\n matcher: rule.matcher,\n properties: rule.properties || [],\n match: getFieldMatcher(rule.matcher || { id: \"\" }),\n }));\n}\n\nfunction getCompiledRules(\n overrides: ConfigOverrideRule[],\n defaults: FieldConfig,\n): CompiledOverrideRule[] {\n const dKey = defaultsCacheKey(defaults);\n const weakHit = compiledRulesCache.get(overrides);\n if (weakHit && weakHit.defaultsKey === dKey) return weakHit.rules;\n\n const sig = rulesSignature(overrides) + \"::\" + dKey;\n const lruHit = compiledRulesLru.find((e) => e.key === sig);\n if (lruHit) {\n compiledRulesCache.set(overrides, { rules: lruHit.rules, defaultsKey: dKey });\n return lruHit.rules;\n }\n\n const rules = compileOverrideRules(overrides);\n compiledRulesCache.set(overrides, { rules, defaultsKey: dKey });\n compiledRulesLru.unshift({ key: sig, rules });\n if (compiledRulesLru.length > COMPILED_RULES_LRU_MAX) compiledRulesLru.pop();\n return rules;\n}\n\n/** Test/helper: clear compile caches. */\nexport function clearFieldOverrideCompileCache(): void {\n compiledRulesLru.length = 0;\n}\n\nexport {\n FieldMatcherID,\n listFieldMatchers,\n listOverridePickerMatchers,\n getFieldMatcher,\n matchFieldWithRegistry,\n} from \"./field/matchers\";\nexport type { FieldMatcherInfo, FieldMatcherFn } from \"./field/matchers\";\nexport {\n STANDARD_OVERRIDE_PROCESSORS,\n getOverrideProcessor,\n processOverrideValue,\n isKnownOverrideProperty,\n applyProcessedProperty,\n} from \"./field/overrideProcessors\";\n\n/** @deprecated prefer matchFieldWithRegistry — kept for existing call sites */\nexport function matchField(\n field: Field,\n matcher: { id: string; options?: unknown },\n frame?: DataFrame,\n): boolean {\n return matchFieldWithRegistry(field, matcher, frame);\n}\n\nfunction normalizePropId(id: string): string {\n if (\n id === \"unit\" ||\n id === \"decimals\" ||\n id === \"displayName\" ||\n id === \"min\" ||\n id === \"max\" ||\n id === \"noValue\" ||\n id === \"fieldMinMax\" ||\n id === \"filterable\" ||\n id === \"color\" ||\n id === \"thresholds\" ||\n id === \"mappings\" ||\n id === \"links\" ||\n id === \"actions\"\n ) {\n return id;\n }\n if (id.startsWith(\"standardOptions.\"))\n return id.slice(\"standardOptions.\".length);\n if (id.startsWith(\"custom.\")) return id;\n const customKeys = [\n \"drawStyle\",\n \"lineInterpolation\",\n \"lineWidth\",\n \"fillOpacity\",\n \"gradientMode\",\n \"spanNulls\",\n \"showPoints\",\n \"pointSize\",\n \"stacking\",\n \"axisPlacement\",\n \"axisLabel\",\n \"axisSoftMin\",\n \"axisSoftMax\",\n \"axisCenteredZero\",\n \"hideFrom\",\n \"scaleDistribution\",\n \"thresholdsStyle\",\n \"barAlignment\",\n \"lineStyle\",\n \"insertNulls\",\n \"barWidthFactor\",\n ];\n if (customKeys.includes(id)) return `custom.${id}`;\n return id;\n}\n\nfunction setNested(\n config: FieldConfig,\n path: string,\n value: unknown,\n): FieldConfig {\n if (path.startsWith(\"custom.\")) {\n const rest = path.slice(7);\n const custom = { ...(config.custom ?? {}) } as Record<string, unknown>;\n const parts = rest.split(\".\");\n let cur: any = custom;\n for (let i = 0; i < parts.length - 1; i++) {\n cur[parts[i]] =\n cur[parts[i]] && typeof cur[parts[i]] === \"object\"\n ? { ...cur[parts[i]] }\n : {};\n cur = cur[parts[i]];\n }\n cur[parts[parts.length - 1]] = value;\n return { ...config, custom };\n }\n if (path.includes(\".\")) {\n const parts = path.split(\".\");\n const root = { ...(config as any) };\n let cur: any = root;\n for (let i = 0; i < parts.length - 1; i++) {\n cur[parts[i]] =\n cur[parts[i]] && typeof cur[parts[i]] === \"object\"\n ? { ...cur[parts[i]] }\n : {};\n cur = cur[parts[i]];\n }\n cur[parts[parts.length - 1]] = value;\n return root as FieldConfig;\n }\n return { ...config, [path]: value };\n}\n\n/**\n * Apply field config defaults + ordered override rules.\n * Unknown property ids are preserved on the rule (caller) but not applied to field config.\n * Rules execute in array order (Grafana semantics).\n */\nexport function applyFieldOverrides(\n frames: DataFrame[],\n defaults: FieldConfig = {},\n overrides: ConfigOverrideRule[] = [],\n): DataFrame[] {\n const compiled = getCompiledRules(overrides, defaults);\n return frames.map((frame) => ({\n ...frame,\n fields: frame.fields.map((field) => {\n // Deep-merge custom so field-level custom does not drop defaults.custom keys.\n const mergedCustom = {\n ...((defaults.custom as Record<string, unknown> | undefined) ?? {}),\n ...((field.config?.custom as Record<string, unknown> | undefined) ?? {}),\n };\n let config: FieldConfig = {\n ...defaults,\n ...field.config,\n ...(Object.keys(mergedCustom).length ? { custom: mergedCustom } : {}),\n };\n for (let ri = 0; ri < compiled.length; ri++) {\n const rule = compiled[ri]!;\n if (!rule.match(field, frame, frames)) continue;\n // Always read properties from the *current* overrides array.\n // Compiled LRU may reuse matcher fns from a prior array with the same\n // matcher/property-id signature but different values — stale\n // rule.properties would silently apply the wrong override values.\n const properties = overrides[ri]?.properties ?? rule.properties;\n for (const prop of properties) {\n const id = normalizePropId(prop.id);\n // Unknown non-custom properties: do not apply, but keep rule intact (lossless)\n if (!isKnownOverrideProperty(id) && !id.includes(\".\")) {\n continue;\n }\n const processed = processOverrideValue(id, prop.value);\n if (id.startsWith(\"custom.\") || !isKnownOverrideProperty(id)) {\n config = setNested(config, id, processed);\n } else {\n // applyProcessedProperty processes again — pass raw prop.value\n config = applyProcessedProperty(config, id, prop.value);\n }\n if (\n id === \"color\" &&\n prop.value &&\n typeof prop.value === \"object\" &&\n (prop.value as any).fixedColor\n ) {\n config = {\n ...config,\n color: {\n ...(config.color as any),\n ...(prop.value as any),\n mode: (prop.value as any).mode ?? \"fixed\",\n },\n };\n }\n }\n }\n return { ...field, config };\n }),\n }));\n}\n","/**\n * Compile + cache panel pipeline config (transforms + field overrides) by revision.\n * Byte/entry limited LRU (Task 9). Does not change transform semantics.\n */\nimport type { DataFrame, FieldConfig } from \"../types\";\nimport {\n applyFieldOverrides,\n compileOverrideRules,\n type CompiledOverrideRule,\n type ConfigOverrideRule,\n} from \"../fieldOverrides\";\nimport {\n applyTransformations,\n applyTransformationsWithTrace,\n resolveTransformerId,\n type TransformDiagnostic,\n type TransformPipelineResult,\n} from \"../transformations/runner\";\n\nexport type PipelineTransformStep = {\n id: string;\n options?: Record<string, unknown>;\n disabled?: boolean;\n filter?: unknown;\n};\n\nexport type PanelPipelineConfig = {\n transformations?: PipelineTransformStep[];\n fieldConfigDefaults?: FieldConfig;\n fieldConfigOverrides?: ConfigOverrideRule[];\n};\n\nexport type CompiledPanelPipeline = {\n /** Stable content revision of the config. */\n revision: string;\n /** Original transform list (trace path / unknown round-trip). */\n transformations: PipelineTransformStep[];\n /**\n * Fast-path steps: disabled dropped, aliases resolved, sort+limit fused,\n * default options merged. Semantics match applyTransformations.\n */\n fastSteps: PipelineTransformStep[];\n defaults: FieldConfig;\n /** Stable overrides array identity while cache entry lives. */\n overrides: ConfigOverrideRule[];\n /** Precompiled matchers (also cached inside fieldOverrides). */\n compiledOverrides: CompiledOverrideRule[];\n estimatedBytes: number;\n};\n\nconst DEFAULT_MAX_ENTRIES = 64;\nconst DEFAULT_MAX_BYTES = 512 * 1024; // signature + shallow config estimate\n\ntype CacheEntry = {\n revision: string;\n compiled: CompiledPanelPipeline;\n bytes: number;\n};\n\nconst cache = new Map<string, CacheEntry>();\nlet cacheBytes = 0;\nlet maxEntries = DEFAULT_MAX_ENTRIES;\nlet maxBytes = DEFAULT_MAX_BYTES;\n\nconst DEFAULT_OPTIONS: Record<string, Record<string, unknown>> = {\n limit: { limitField: 10 },\n sortBy: { sort: [] },\n reduce: { reducers: [\"sum\"] },\n histogram: { bucketCount: 10 },\n smoothing: { windowSize: 3 },\n filterByValue: { type: \"include\", filters: [] },\n prepareTimeSeries: { format: \"multi\" },\n};\n\nfunction readLimitOption(\n options: Record<string, unknown> | undefined,\n): number | undefined {\n if (!options) return undefined;\n const raw = options.limit ?? options.limitField ?? options.limitValue;\n if (raw == null) return undefined;\n const n = Math.floor(Number(raw));\n return Number.isFinite(n) && n >= 0 ? n : undefined;\n}\n\nfunction tryFuseSortLimit(\n steps: PipelineTransformStep[],\n index: number,\n): { fused: PipelineTransformStep; skipNext: boolean } | null {\n const cur = steps[index];\n const next = steps[index + 1];\n if (!cur || !next) return null;\n if (cur.disabled || next.disabled) return null;\n const curId = resolveTransformerId(cur.id);\n const nextId = resolveTransformerId(next.id);\n if (curId !== \"sortBy\" || nextId !== \"limit\") return null;\n if (JSON.stringify(cur.filter ?? null) !== JSON.stringify(next.filter ?? null)) {\n return null;\n }\n const lim = readLimitOption(next.options);\n if (lim == null) return null;\n const defaults = DEFAULT_OPTIONS.sortBy ?? {};\n return {\n fused: {\n id: \"sortBy\",\n filter: cur.filter,\n options: {\n ...defaults,\n ...(cur.options || {}),\n limit: lim,\n limitField: lim,\n limitValue: lim,\n },\n },\n skipNext: true,\n };\n}\n\n/** Build fast-path steps: resolve aliases, merge defaults, fuse sort→limit. */\nexport function compileTransformSteps(\n transformations: PipelineTransformStep[] = [],\n): PipelineTransformStep[] {\n const out: PipelineTransformStep[] = [];\n const src = transformations ?? [];\n for (let i = 0; i < src.length; i++) {\n const t = src[i];\n if (t.disabled) continue;\n const fuse = tryFuseSortLimit(src, i);\n if (fuse) {\n out.push(fuse.fused);\n if (fuse.skipNext) i += 1;\n continue;\n }\n const resolvedId = resolveTransformerId(t.id);\n const defaults = DEFAULT_OPTIONS[resolvedId] ?? DEFAULT_OPTIONS[t.id] ?? {};\n out.push({\n id: resolvedId,\n filter: t.filter,\n options: { ...defaults, ...(t.options || {}) },\n });\n }\n return out;\n}\n\nfunction estimateConfigBytes(config: PanelPipelineConfig): number {\n // Avoid full JSON.stringify of large option trees on every call — sample keys.\n let n = 128;\n const transforms = config.transformations ?? [];\n n += transforms.length * 64;\n for (const t of transforms) {\n n += String(t.id).length + 16;\n if (t.options) n += Object.keys(t.options).length * 24;\n }\n const overrides = config.fieldConfigOverrides ?? [];\n n += overrides.length * 96;\n for (const r of overrides) {\n n += String(r.matcher?.id ?? \"\").length;\n n += (r.properties?.length ?? 0) * 32;\n }\n const defaults = config.fieldConfigDefaults;\n if (defaults) n += Object.keys(defaults).length * 24 + 32;\n return n;\n}\n\n/**\n * Content revision for pipeline config. Stable across equivalent plain objects.\n * Not a cryptographic hash — collision-resistant enough for cache keys.\n */\nexport function pipelineConfigRevision(config: PanelPipelineConfig): string {\n const transforms = config.transformations ?? [];\n const overrides = config.fieldConfigOverrides ?? [];\n const defaults = config.fieldConfigDefaults ?? {};\n // Structured, bounded signature (no full options deep dump of huge arrays).\n const parts: string[] = [`t${transforms.length}`, `o${overrides.length}`];\n for (let i = 0; i < transforms.length; i++) {\n const t = transforms[i];\n parts.push(\n `${t.disabled ? \"D\" : \"\"}${t.id}:${stableSmallJson(t.options)}:${stableSmallJson(t.filter)}`,\n );\n }\n for (let i = 0; i < overrides.length; i++) {\n const r = overrides[i];\n const props = (r.properties || [])\n .map((p) => `${p.id}=${stableSmallJson(p.value)}`)\n .join(\",\");\n parts.push(\n `m${r.matcher?.id}:${stableSmallJson(r.matcher?.options)}:${props}`,\n );\n }\n parts.push(`d:${stableSmallJson(defaults)}`);\n return parts.join(\"|\");\n}\n\nfunction stableSmallJson(value: unknown): string {\n if (value == null) return \"\";\n if (typeof value === \"string\") return value.length > 64 ? value.slice(0, 64) : value;\n if (typeof value === \"number\" || typeof value === \"boolean\") return String(value);\n try {\n const s = JSON.stringify(value);\n return s.length > 256 ? s.slice(0, 256) : s;\n } catch {\n return \"?\";\n }\n}\n\nfunction touch(revision: string, entry: CacheEntry): void {\n // Map preserves insertion order; re-insert for LRU.\n cache.delete(revision);\n cache.set(revision, entry);\n}\n\nfunction evictIfNeeded(): void {\n while (\n (cache.size > maxEntries || cacheBytes > maxBytes) &&\n cache.size > 0\n ) {\n const oldest = cache.keys().next().value as string | undefined;\n if (oldest == null) break;\n const e = cache.get(oldest);\n cache.delete(oldest);\n if (e) cacheBytes -= e.bytes;\n }\n if (cacheBytes < 0) cacheBytes = 0;\n}\n\nexport function getCompiledPipeline(\n config: PanelPipelineConfig,\n): CompiledPanelPipeline {\n const revision = pipelineConfigRevision(config);\n const hit = cache.get(revision);\n if (hit) {\n touch(revision, hit);\n return hit.compiled;\n }\n\n const transformations = (config.transformations ?? []).map((t) => ({\n id: t.id,\n options: t.options ? { ...t.options } : undefined,\n disabled: t.disabled,\n filter: t.filter,\n }));\n const defaults = { ...(config.fieldConfigDefaults ?? {}) };\n const overrides = (config.fieldConfigOverrides ?? []).map((r) => ({\n matcher: { ...(r.matcher || { id: \"\" }) },\n properties: (r.properties || []).map((p) => ({ ...p })),\n }));\n const fastSteps = compileTransformSteps(transformations);\n const compiledOverrides = compileOverrideRules(overrides);\n const estimatedBytes = estimateConfigBytes(config);\n const compiled: CompiledPanelPipeline = {\n revision,\n transformations,\n fastSteps,\n defaults,\n overrides,\n compiledOverrides,\n estimatedBytes,\n };\n const bytes = Math.max(estimatedBytes, revision.length + 64);\n cacheBytes += bytes;\n cache.set(revision, { revision, compiled, bytes });\n evictIfNeeded();\n return compiled;\n}\n\nexport function runCompiledPipeline(\n frames: DataFrame[],\n compiled: CompiledPanelPipeline,\n opts?: { withTrace?: boolean },\n): {\n frames: DataFrame[];\n steps: TransformPipelineResult[\"steps\"];\n diagnostics: TransformDiagnostic[];\n} {\n if (opts?.withTrace) {\n const pipeline = applyTransformationsWithTrace(\n frames,\n compiled.transformations as any,\n );\n const series = applyFieldOverrides(\n pipeline.frames,\n compiled.defaults,\n compiled.overrides,\n );\n return {\n frames: series,\n steps: pipeline.steps,\n diagnostics: pipeline.diagnostics,\n };\n }\n\n // Fast path: pre-fused steps. applyTransformations still clones entry once.\n // Pass steps that already have defaults + fusion so runner fuse is a no-op\n // (sortBy already carries limit; next is not limit).\n const transformed = applyTransformations(\n frames,\n compiled.fastSteps as any,\n );\n const series = applyFieldOverrides(\n transformed,\n compiled.defaults,\n compiled.overrides,\n );\n return { frames: series, steps: [], diagnostics: [] };\n}\n\nexport function clearCompiledPipelineCache(): void {\n cache.clear();\n cacheBytes = 0;\n}\n\nexport function compiledPipelineCacheStats(): {\n entries: number;\n bytes: number;\n maxEntries: number;\n maxBytes: number;\n} {\n return {\n entries: cache.size,\n bytes: cacheBytes,\n maxEntries,\n maxBytes,\n };\n}\n\n/** Test/ops: tighten or restore cache caps. */\nexport function configureCompiledPipelineCache(opts: {\n maxEntries?: number;\n maxBytes?: number;\n}): void {\n if (opts.maxEntries != null) maxEntries = Math.max(1, opts.maxEntries);\n if (opts.maxBytes != null) maxBytes = Math.max(1024, opts.maxBytes);\n evictIfNeeded();\n}\n","/**\n * Shared transferable DataFrame wire format for panel pipeline worker (Task 9).\n */\nimport type { DataFrame, Field, FieldConfig, FieldType } from \"@grafana/data\";\n\nexport type WireField = {\n name: string;\n type: FieldType;\n config: FieldConfig;\n labels?: Record<string, string>;\n /** 'f64' = transferable Float64Array + null mask; 'clone' = structured-clone values. */\n encoding: \"f64\" | \"clone\";\n f64?: Float64Array;\n nulls?: Uint8Array;\n values?: unknown[];\n};\n\nexport type WireFrame = {\n refId?: string;\n name?: string;\n meta?: Record<string, unknown>;\n length: number;\n fields: WireField[];\n};\n\n/** True when every non-null value is a number (not string/uint64/object). */\nexport function canEncodeF64(values: unknown[]): boolean {\n for (let i = 0; i < values.length; i++) {\n const v = values[i];\n if (v == null) continue;\n if (typeof v !== \"number\") return false;\n }\n return true;\n}\n\nexport function packFramesForTransfer(frames: DataFrame[]): {\n frames: WireFrame[];\n transfer: Transferable[];\n} {\n const transfer: Transferable[] = [];\n const wire: WireFrame[] = (frames ?? []).map((frame) => {\n const fields: WireField[] = (frame.fields ?? []).map((f) => {\n const values = f.values ?? [];\n const type = f.type;\n const numericLike =\n (type === \"number\" || type === \"time\") && canEncodeF64(values);\n if (numericLike) {\n const f64 = new Float64Array(values.length);\n const nulls = new Uint8Array(values.length);\n for (let i = 0; i < values.length; i++) {\n const v = values[i];\n if (v == null) {\n nulls[i] = 1;\n f64[i] = 0;\n } else {\n nulls[i] = 0;\n f64[i] = v as number;\n }\n }\n transfer.push(f64.buffer, nulls.buffer);\n return {\n name: f.name,\n type,\n config: f.config ? { ...f.config } : {},\n labels: f.labels ? { ...f.labels } : undefined,\n encoding: \"f64\" as const,\n f64,\n nulls,\n };\n }\n return {\n name: f.name,\n type,\n config: f.config ? { ...f.config } : {},\n labels: f.labels ? { ...f.labels } : undefined,\n encoding: \"clone\" as const,\n values: values.slice(),\n };\n });\n const len =\n frame.length ??\n fields[0]?.f64?.length ??\n fields[0]?.values?.length ??\n 0;\n return {\n refId: frame.refId,\n name: frame.name,\n meta: frame.meta ? { ...frame.meta } : undefined,\n length: len,\n fields,\n };\n });\n return { frames: wire, transfer };\n}\n\nexport function unpackWireFrames(frames: WireFrame[]): DataFrame[] {\n return (frames ?? []).map((frame) => {\n const fields: Field[] = (frame.fields ?? []).map((f) => {\n if (f.encoding === \"f64\" && f.f64) {\n const n = f.f64.length;\n const values = new Array<number | null>(n);\n const nulls = f.nulls;\n for (let i = 0; i < n; i++) {\n values[i] = nulls && nulls[i] ? null : f.f64[i];\n }\n return {\n name: f.name,\n type: f.type,\n config: f.config ?? {},\n values,\n labels: f.labels,\n };\n }\n return {\n name: f.name,\n type: f.type,\n config: f.config ?? {},\n values: f.values ?? [],\n labels: f.labels,\n };\n });\n return {\n refId: frame.refId,\n name: frame.name,\n meta: frame.meta,\n fields,\n length:\n frame.length ??\n fields.reduce((m, field) => Math.max(m, field.values.length), 0),\n } satisfies DataFrame;\n });\n}\n","/// <reference lib=\"webworker\" />\n/**\n * Worker entry: unpack frames → compiled pipeline → pack result (Task 9).\n * Supports run + cancel; transferable numeric/time columns via packFramesForTransfer.\n */\nimport {\n getCompiledPipeline,\n runCompiledPipeline,\n} from \"@grafana/data\";\n// Side-effect: register transformers in worker scope.\nimport \"@grafana/data\";\nimport {\n packFramesForTransfer,\n unpackWireFrames,\n type WireFrame,\n} from \"./panelPipelineTransfer\";\n\nexport type PanelPipelineWorkerRequest = {\n type?: \"run\" | \"cancel\";\n id: number;\n generation?: number;\n frames?: WireFrame[];\n transformations?: unknown[];\n fieldConfigDefaults?: unknown;\n fieldConfigOverrides?: unknown[];\n requestId?: string;\n};\n\nexport type PanelPipelineWorkerResponse =\n | {\n id: number;\n generation?: number;\n ok: true;\n frames: WireFrame[];\n }\n | {\n id: number;\n generation?: number;\n ok: false;\n error: string;\n aborted?: boolean;\n };\n\n/** Cancelled ids (cleared once observed). */\nconst cancelled = new Set<number>();\n\nexport function handlePanelPipelineMessage(\n msg: PanelPipelineWorkerRequest,\n post: (res: PanelPipelineWorkerResponse, transfer?: Transferable[]) => void,\n): void {\n if (msg == null || msg.id == null) return;\n if (msg.type === \"cancel\") {\n cancelled.add(msg.id);\n return;\n }\n if (cancelled.has(msg.id)) {\n cancelled.delete(msg.id);\n post({\n id: msg.id,\n generation: msg.generation,\n ok: false,\n error: \"aborted\",\n aborted: true,\n });\n return;\n }\n try {\n const series = unpackWireFrames(msg.frames ?? []);\n const compiled = getCompiledPipeline({\n transformations: (msg.transformations as any) ?? [],\n fieldConfigDefaults: (msg.fieldConfigDefaults as any) ?? {},\n fieldConfigOverrides: (msg.fieldConfigOverrides as any) ?? [],\n });\n if (cancelled.has(msg.id)) {\n cancelled.delete(msg.id);\n post({\n id: msg.id,\n generation: msg.generation,\n ok: false,\n error: \"aborted\",\n aborted: true,\n });\n return;\n }\n const out = runCompiledPipeline(series, compiled, { withTrace: false });\n if (cancelled.has(msg.id)) {\n cancelled.delete(msg.id);\n post({\n id: msg.id,\n generation: msg.generation,\n ok: false,\n error: \"aborted\",\n aborted: true,\n });\n return;\n }\n const packed = packFramesForTransfer(out.frames);\n post(\n {\n id: msg.id,\n generation: msg.generation,\n ok: true,\n frames: packed.frames,\n },\n packed.transfer,\n );\n } catch (e) {\n post({\n id: msg.id,\n generation: msg.generation,\n ok: false,\n error: e instanceof Error ? e.message : String(e),\n });\n }\n}\n\nfunction onMessage(ev: MessageEvent<PanelPipelineWorkerRequest>) {\n handlePanelPipelineMessage(ev.data, (res, transfer) => {\n const scope = self as DedicatedWorkerGlobalScope;\n if (transfer?.length) scope.postMessage(res, transfer);\n else scope.postMessage(res);\n });\n}\n\nconst isDedicatedWorker =\n typeof WorkerGlobalScope !== \"undefined\" &&\n typeof self !== \"undefined\" &&\n \n self instanceof WorkerGlobalScope;\n\nif (isDedicatedWorker) {\n (self as DedicatedWorkerGlobalScope).onmessage = onMessage;\n}\n\nexport { onMessage as handlePanelPipelineWorkerMessage 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\ No newline at end of file
dist/index.css
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dist/index.d.ts
......@@ -234,6 +234,11 @@ interface PanelData {
state: LoadingStateValue;
series: DataFrame[];
timeRange: TimeRange;
/**
* Grafana panel timeFrom/timeShift badge text (PanelTimeRange.timeInfo).
* Empty/undefined when no override or hideTimeOverride.
*/
timeInfo?: string;
error?: {
message: string;
};
......@@ -307,10 +312,41 @@ declare function normalizeDataFrames(frames: DataFrame[], ctx?: FrameNormalizati
declare function frameFingerprint(frames: DataFrame[]): string;
declare function dateTime(input?: string | number | Date): Date;
/** Optional parse knobs (Grafana TimeModel / timepicker.nowDelay + fiscalYearStartMonth). */
type RangeParseOptions = {
/** Shift "now" backward by this many ms (timepicker.nowDelay). */
nowDelayMs?: number;
/** 0=January … 11=December — dashboard.fiscalYearStartMonth. */
fiscalYearStartMonth?: number;
/**
* Dashboard weekStart for `now/w` rounding.
* "" | monday | saturday | sunday (default monday like Grafana browser default).
*/
weekStart?: string;
/**
* Dashboard timezone. Grafana datemath: only `"utc"` changes unit rounding;
* anything else uses local/browser calendar bounds.
*/
timezone?: string;
};
/** True when range math should use UTC getters/setters (Grafana datemath). */
declare function isUtcTimezone(timezone?: string): boolean;
declare function rangeUtil_parse(raw: {
from: string | Date;
to: string | Date;
}, now?: Date): TimeRange;
}, now?: Date, opts?: RangeParseOptions): TimeRange;
/** Apply Grafana timepicker.nowDelay to wall-clock "now". */
declare function applyNowDelay(now: Date, nowDelayMs?: number): Date;
/** Grafana dashboard.fiscalYearStartMonth is 0-based (0=Jan … 11=Dec). */
declare function normalizeFiscalMonth(raw: unknown): number;
/** Start of fiscal year containing `now` (local TZ). */
declare function startOfFiscalYear(now: Date, fiscalYearStartMonth?: number): Date;
/** Exclusive end (= start of next fiscal year). */
declare function endOfFiscalYear(now: Date, fiscalYearStartMonth?: number): Date;
/** Start of fiscal quarter containing `now` (3-month buckets from fiscalYearStartMonth). */
declare function startOfFiscalQuarter(now: Date, fiscalYearStartMonth?: number): Date;
/** Exclusive end of fiscal quarter (= start of next fiscal quarter). */
declare function endOfFiscalQuarter(now: Date, fiscalYearStartMonth?: number): Date;
declare function getInterval(range: TimeRange, resolution?: number): string;
/** Grafana-aligned default auto-refresh intervals for RefreshPicker. */
declare const defaultRefreshIntervals: readonly ["5s", "10s", "30s", "1m", "5m", "15m", "30m", "1h", "2h", "1d"];
......@@ -1412,8 +1448,22 @@ declare function configureCompiledPipelineCache(opts: {
maxBytes?: number;
}): void;
export { CLASSIC_PALETTE, CLASSIC_PALETTE_DARK, CLASSIC_PALETTE_LIGHT, DATA_TRANSFORMER_IDS, DataLinkBuiltInVars, DataTransformerID, FALLBACK_COLOR, FieldMatcherID, FieldNamePickerBaseNameMode, LoadingStateEnum, ReducerID, STANDARD_OVERRIDE_PROCESSORS, V1_SCHEMA_VERSION, VariableOrigin, VariableSuggestionsScope, alpha, applyDocumentPatches, applyFieldOverrides, applyGlobalStyles, applyJsonPatch, applyProcessedProperty, applyResolvedTheme, applyTheme2CssVars, applyTransformations, applyTransformationsWithTrace, applyValueMappings, asHexString, asRgbString, assignFrameRevision, buildDataLinkUrl, buildDataLinkVars, bumpFrameRevision, canSkipNormalize, clearCompiledPipelineCache, clearFieldOverrideCompileCache, colorManipulator, compileOverrideRules, compileTransformSteps, compiledPipelineCacheStats, configureCompiledPipelineCache, continuousGrYlRd, convertV2DashboardToV1, createColors, createDataFrame, createGlobalStyles, createTheme, createThemeFromPreference, createVisualizationColors, darken, dashboardRoundTrip, dateTime, decomposeColor, defaultRefreshIntervals, detectSourceKind, diffJsonPaths, displayValueToString, emphasize, flattenV2Layout, formatLabels, formatSuggestionToken, formatUnit, formatValue, formatValueWithUnit, formattedValueToString, frameContextMatches, frameFingerprint, frameHasName, frameSetRevisionKey, getActiveThreshold, getAtPath, getClassicPalette, getCompiledPipeline, getContrastRatio, getContrastText, getDashboardLinkUrl, getDataFrameVars, getDataLinksVariableSuggestions, getDisplayProcessor, getFieldColor, getFieldDisplayName, getFieldLinks, getFieldMatcher, getFieldMatcherInfo, getFieldNameOptions, getFieldSeriesColor, getFrameFieldsDisplayNames, getFrameRevision, getInterval, getLuminance, getOverrideProcessor, getRawDisplayProcessor, getTemplateVariableSuggestions, getThresholdColor, getTransformer, getValueFormat, groupLabelForScope, hexToRgb, hslToRgb, interpolateDataLinkString, intervalToMs, isFrameNormalized, isKnownOverrideProperty, isV2Dashboard, lighten, listFieldMatchers, listOverridePickerMatchers, listReducerIds, listStandardTransformers, listTransformerIds, listValueFormatIds, markFrameNormalized, matchField, matchFieldWithRegistry, matchFrameFilter, migrateDashboard, migrateV1Dashboard, normalizeBaseNameMode, normalizeDashboard, normalizeDataFrames, palette, parseDashboardDocument, parsePath, pipelineConfigRevision, preProcessPanelData, preserveUnknownFields, processOverrideValue, rangeUtil_parse, recomposeColor, reduceField, reduceField$1 as reduceFieldFromRegistry, registerTransformer, removeAtPath, resolveDataLink, resolveThemeMode, resolveThemeModeHint, resolveTransformerId, resolveV2Datasource, resolveVizColor, rgbToHex, runCompiledPipeline, runMigrations, setAtPath, sortThresholds, standardTransformers, stringToMs, toDataFrameDTO, toSerializableDashboard, v1Migrations, v2ResourceToV1, watchSystemTheme };
export type { AbsoluteTimeRange, AnnotationQuery, ApplyTransformationsContext, CompiledOverrideRule, CompiledPanelPipeline, ConfigOverrideRule, CreateThemeOptions, DashboardDocumentEnvelope, DashboardModel, DashboardSourceKind, DataFrame, DataLink, DataLinkVars, DataQuery, DataSourceJsonData, DataSourceSettings, DecimalCount, DecomposeColor, DisplayProcessor, DisplayValue, DynamicConfigValue, Field, FieldCalcs, FieldConfig, FieldMatcherFn, FieldMatcherInfo, FieldType, FrameFieldsDisplayNames, FrameFilterConfig, FrameNormalizationContext, GrafanaTheme2, GridPos, JsonPatchOp, LayoutItem, LayoutRow, LoadingState, LoadingStateValue, MatcherConfig, MatcherScope, PaletteKey, PanelData, PanelDataLike, PanelLoadingState, PanelModel, PanelPipelineConfig, PipelineTransformStep, ResolveDataLinkContext, ScopedVars, ThemeColors, ThemeColorsBase, ThemeMode, ThemePreference, ThemeRichColor, ThemeSpacing, ThemeTypography, ThemeVisualizationColors$1 as ThemeVisualizationColors, ThemeVizHue, ThemeVizShade, Threshold, ThresholdsConfig, TimeRange, TimeZone, TransformDiagnostic, TransformPipelineResult, TransformStepSnapshot, TransformerFn, V2DashboardKind, ValueMapping, VariableModel, VariableSuggestion, VariableType };
/**
* Grafana-compatible string helpers for field matchers / value mappings.
* @see grafana-main/packages/grafana-data/src/text/string.ts
*/
declare function stringStartsAsRegEx(str: string): boolean;
/**
* Convert a Grafana-style pattern to RegExp.
* - bare string → anchored `^${str}$`
* - `/pattern/flags` → RegExp(pattern, flags)
*/
declare function stringToJsRegex(str: string): RegExp;
/** Safe variant: invalid patterns return null instead of throwing. */
declare function stringToJsRegexSafe(str: unknown): RegExp | null;
export { CLASSIC_PALETTE, CLASSIC_PALETTE_DARK, CLASSIC_PALETTE_LIGHT, DATA_TRANSFORMER_IDS, DataLinkBuiltInVars, DataTransformerID, FALLBACK_COLOR, FieldMatcherID, FieldNamePickerBaseNameMode, LoadingStateEnum, ReducerID, STANDARD_OVERRIDE_PROCESSORS, V1_SCHEMA_VERSION, VariableOrigin, VariableSuggestionsScope, alpha, applyDocumentPatches, applyFieldOverrides, applyGlobalStyles, applyJsonPatch, applyNowDelay, applyProcessedProperty, applyResolvedTheme, applyTheme2CssVars, applyTransformations, applyTransformationsWithTrace, applyValueMappings, asHexString, asRgbString, assignFrameRevision, buildDataLinkUrl, buildDataLinkVars, bumpFrameRevision, canSkipNormalize, clearCompiledPipelineCache, clearFieldOverrideCompileCache, colorManipulator, compileOverrideRules, compileTransformSteps, compiledPipelineCacheStats, configureCompiledPipelineCache, continuousGrYlRd, convertV2DashboardToV1, createColors, createDataFrame, createGlobalStyles, createTheme, createThemeFromPreference, createVisualizationColors, darken, dashboardRoundTrip, dateTime, decomposeColor, defaultRefreshIntervals, detectSourceKind, diffJsonPaths, displayValueToString, emphasize, endOfFiscalQuarter, endOfFiscalYear, flattenV2Layout, formatLabels, formatSuggestionToken, formatUnit, formatValue, formatValueWithUnit, formattedValueToString, frameContextMatches, frameFingerprint, frameHasName, frameSetRevisionKey, getActiveThreshold, getAtPath, getClassicPalette, getCompiledPipeline, getContrastRatio, getContrastText, getDashboardLinkUrl, getDataFrameVars, getDataLinksVariableSuggestions, getDisplayProcessor, getFieldColor, getFieldDisplayName, getFieldLinks, getFieldMatcher, getFieldMatcherInfo, getFieldNameOptions, getFieldSeriesColor, getFrameFieldsDisplayNames, getFrameRevision, getInterval, getLuminance, getOverrideProcessor, getRawDisplayProcessor, getTemplateVariableSuggestions, getThresholdColor, getTransformer, getValueFormat, groupLabelForScope, hexToRgb, hslToRgb, interpolateDataLinkString, intervalToMs, isFrameNormalized, isKnownOverrideProperty, isUtcTimezone, isV2Dashboard, lighten, listFieldMatchers, listOverridePickerMatchers, listReducerIds, listStandardTransformers, listTransformerIds, listValueFormatIds, markFrameNormalized, matchField, matchFieldWithRegistry, matchFrameFilter, migrateDashboard, migrateV1Dashboard, normalizeBaseNameMode, normalizeDashboard, normalizeDataFrames, normalizeFiscalMonth, palette, parseDashboardDocument, parsePath, pipelineConfigRevision, preProcessPanelData, preserveUnknownFields, processOverrideValue, rangeUtil_parse, recomposeColor, reduceField, reduceField$1 as reduceFieldFromRegistry, registerTransformer, removeAtPath, resolveDataLink, resolveThemeMode, resolveThemeModeHint, resolveTransformerId, resolveV2Datasource, resolveVizColor, rgbToHex, runCompiledPipeline, runMigrations, setAtPath, sortThresholds, standardTransformers, startOfFiscalQuarter, startOfFiscalYear, stringStartsAsRegEx, stringToJsRegex, stringToJsRegexSafe, stringToMs, toDataFrameDTO, toSerializableDashboard, v1Migrations, v2ResourceToV1, watchSystemTheme };
export type { AbsoluteTimeRange, AnnotationQuery, ApplyTransformationsContext, CompiledOverrideRule, CompiledPanelPipeline, ConfigOverrideRule, CreateThemeOptions, DashboardDocumentEnvelope, DashboardModel, DashboardSourceKind, DataFrame, DataLink, DataLinkVars, DataQuery, DataSourceJsonData, DataSourceSettings, DecimalCount, DecomposeColor, DisplayProcessor, DisplayValue, DynamicConfigValue, Field, FieldCalcs, FieldConfig, FieldMatcherFn, FieldMatcherInfo, FieldType, FrameFieldsDisplayNames, FrameFilterConfig, FrameNormalizationContext, GrafanaTheme2, GridPos, JsonPatchOp, LayoutItem, LayoutRow, LoadingState, LoadingStateValue, MatcherConfig, MatcherScope, PaletteKey, PanelData, PanelDataLike, PanelLoadingState, PanelModel, PanelPipelineConfig, PipelineTransformStep, RangeParseOptions, ResolveDataLinkContext, ScopedVars, ThemeColors, ThemeColorsBase, ThemeMode, ThemePreference, ThemeRichColor, ThemeSpacing, ThemeTypography, ThemeVisualizationColors$1 as ThemeVisualizationColors, ThemeVizHue, ThemeVizShade, Threshold, ThresholdsConfig, TimeRange, TimeZone, TransformDiagnostic, TransformPipelineResult, TransformStepSnapshot, TransformerFn, V2DashboardKind, ValueMapping, VariableModel, VariableSuggestion, VariableType };
// ----- @grafana/plugin-sdk -----
/**
......@@ -2901,6 +2951,12 @@ type __VLS_Props$E = {
filterOnDemandThreshold?: number;
/** Max options rendered into the dropdown at once. Default 100. */
maxVisibleOptions?: number;
/**
* Fixed width (e.g. "300px", "24em"). When omitted, the select fills its
* container (100%) — the pre-existing default, unchanged for callers that
* don't pass this.
*/
width?: string | number;
};
declare const __VLS_export$G: vue.DefineComponent<__VLS_Props$E, {}, {}, {}, {}, vue.ComponentOptionsMixin, vue.ComponentOptionsMixin, {
search: (args_0: string) => any;
......@@ -4528,6 +4584,7 @@ interface ZabbixItem {
value: string;
}>;
hosts?: Array<{
id?: string;
hostid: string;
name: string;
host?: string;
......@@ -4777,12 +4834,25 @@ declare class ZabbixApi {
getSlas(serviceids: string[], filter: string, signal?: AbortSignal): Promise<ZabbixPagedResult<Record<string, unknown>>>;
getSli(params: Record<string, unknown>, signal?: AbortSignal): Promise<any[]>;
getMacros(hostids: string[], filter: string, signal?: AbortSignal): Promise<ZabbixPagedResult<Record<string, unknown>>>;
/**
* Global (server-wide) user macros. Zabbix distinguishes these from host
* macros via `globalmacro: true` on usermacro.get — mirrors grafana-zabbix
* ZabbixAPIConnector.getGlobalMacros, used as the fallback when a host macro
* is not defined during {$MACRO} expansion in problem text.
*/
getGlobalMacros(signal?: AbortSignal): Promise<Array<Record<string, unknown>>>;
getValueMaps(signal?: AbortSignal): Promise<ZabbixPagedResult<Record<string, unknown>>>;
getCurrentUser(signal?: AbortSignal): Promise<{
userid: string;
type?: string;
roleid?: string;
}>;
/**
* Resolve acknowledge authors. Zabbix selectAcknowledges only returns userid,
* so the panel joins these rows to show the person who acknowledged — mirrors
* grafana-zabbix getUsers() + formatAcknowledges.
*/
getUsers(signal?: AbortSignal): Promise<Array<Record<string, unknown>>>;
getScripts(hostid: string, eventid: string, signal?: AbortSignal): Promise<ZabbixPagedResult<ZabbixScript>>;
getProblemDetail(eventid: string, signal?: AbortSignal): Promise<ZabbixProblemDetail | null>;
acknowledgeEvent(payload: Record<string, unknown>, signal?: AbortSignal): Promise<unknown>;
......@@ -4799,7 +4869,7 @@ declare function createZabbixDataSource(instance: DataSourceInstanceSettings, me
/** Surface write flag for panel four-way gate. */
enableWrites: boolean;
query: (request: DataSourceQueryRequest, signal?: AbortSignal) => Promise<{
data: DataFrame[];
data: _grafana_data.DataFrame[];
}>;
testDatasource: (signal?: AbortSignal) => Promise<{
status: string;
......@@ -4823,13 +4893,12 @@ declare function createZabbixDataSource(instance: DataSourceInstanceSettings, me
scopedVars?: Record<string, unknown>;
}) => Promise<{
text: string;
value: string;
id?: string;
expandable: false;
}[]>;
annotationQuery: (request: {
range: TimeRange;
annotation: Record<string, unknown>;
}, signal?: AbortSignal) => Promise<DataFrame[]>;
}, signal?: AbortSignal) => Promise<_grafana_data.DataFrame[]>;
getMetadata: (request: ZabbixMetadataRequest, signal?: AbortSignal) => Promise<ZabbixMetadataResponse>;
mutate: (request: {
action: string;
......
dist/index.js
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dist/index.js.map
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dist/register.css
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dist/register.js
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package.json
{
"name": "@grafana/vue",
"version": "1.2.14",
"version": "1.2.15",
"type": "module",
"main": "./dist/index.js",
"types": "./dist/index.d.ts",
......
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