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4 Commits

Author SHA1 Message Date
aks07
d6298fd564 feat(data-export): add useClientExport dispatch hook
Frontend-driven export hook: narrows a V5 queryRange response by request type, serializes time_series (scalar lands with the next sub-issue), formats as csv/jsonl and downloads. Takes the builder query for chart-parity series naming. Backend-driven export stays in useServerExport.
2026-07-08 21:29:29 +05:30
aks07
b37617bdb3 feat(data-export): add csv/jsonl formatters and timestamped client download
toCsv/toJsonl turn a SerializedTable into CSV or newline-delimited JSON; downloadFile triggers a client-side blob download with a timestamped filename (base-YYYY-MM-DD_HH-mm-ss.ext) so repeated exports never collide and record when they were taken.
2026-07-08 20:35:42 +05:30
aks07
ebb60b99b5 feat(data-export): add time_series LONG/WIDE serializer
Pure serializer that walks the V5 time_series tree (results → aggregations → series) into a format-agnostic SerializedTable. Supports LONG (tidy) and WIDE (pivot) shapes; series names match the chart legend (getLabelName + getLegend resolve legend templates and aggregation aliases/expressions from the builder query); y-axis unit in headers, blank gaps, deduped columns.
2026-07-08 20:35:42 +05:30
aks07
9b9c461fbd feat: rename existing export logic to follow the new export data structure 2026-07-06 16:22:42 +05:30
12 changed files with 861 additions and 1 deletions

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@@ -3,7 +3,7 @@ import { Button, Popover, Tooltip } from 'antd';
import { RadioGroup, RadioGroupItem } from '@signozhq/ui/radio-group';
import { Typography } from '@signozhq/ui/typography';
import { TelemetryFieldKey } from 'api/v5/v5';
import { useExportRawData } from 'hooks/useDownloadOptionsMenu/useDownloadOptionsMenu';
import { useExportRawData } from 'hooks/useExportData/useServerExport';
import { Download, LoaderCircle } from '@signozhq/icons';
import { DataSource } from 'types/common/queryBuilder';

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@@ -0,0 +1,119 @@
import { act, renderHook } from '@testing-library/react';
import { downloadFile } from 'lib/exportData/downloadFile';
import { ExportFormat, TimeseriesShape } from 'lib/exportData/types';
import { QueryRangeResponseV5 } from 'types/api/v5/queryRange';
import { useClientExport } from '../useClientExport';
jest.mock('lib/exportData/downloadFile', () => ({
...jest.requireActual('lib/exportData/downloadFile'),
downloadFile: jest.fn(),
}));
const mockMessageError = jest.fn();
jest.mock('antd', () => {
const actual = jest.requireActual('antd');
return {
...actual,
message: { error: (...args: unknown[]): void => mockMessageError(...args) },
};
});
const mockDownloadFile = downloadFile as jest.Mock;
function timeSeriesResponse(): QueryRangeResponseV5 {
return {
type: 'time_series',
data: {
results: [
{
queryName: 'A',
aggregations: [
{
index: 0,
alias: '',
meta: {},
series: [
{
labels: [{ key: { name: 'service' }, value: 'a' }],
values: [{ timestamp: 1000, value: 12 }],
},
],
},
],
},
],
},
meta: {},
} as unknown as QueryRangeResponseV5;
}
describe('useClientExport', () => {
beforeEach(() => jest.clearAllMocks());
it('exports time_series as CSV to a timestamped <fileName>.csv', () => {
const { result } = renderHook(() =>
useClientExport({
response: timeSeriesResponse(),
fileName: 'chart',
legendMap: { A: '{{service}}' },
}),
);
act(() => {
result.current.handleExport({
format: ExportFormat.Csv,
shape: TimeseriesShape.Long,
});
});
expect(mockDownloadFile).toHaveBeenCalledTimes(1);
const [content, name, mime] = mockDownloadFile.mock.calls[0];
expect(name).toMatch(/^chart-\d{4}-\d{2}-\d{2}_\d{2}-\d{2}-\d{2}\.csv$/);
expect(mime).toContain('text/csv');
expect(content).toContain('service');
expect(content).toContain('a');
});
it('exports as JSONL to a timestamped <fileName>.jsonl with the ndjson mime', () => {
const { result } = renderHook(() =>
useClientExport({ response: timeSeriesResponse() }),
);
act(() => {
result.current.handleExport({ format: ExportFormat.Jsonl });
});
const [content, name, mime] = mockDownloadFile.mock.calls[0];
expect(name).toMatch(/^export-\d{4}-\d{2}-\d{2}_\d{2}-\d{2}-\d{2}\.jsonl$/);
expect(mime).toContain('ndjson');
expect(content).toContain('"series"');
});
it('does nothing when there is no response', () => {
const { result } = renderHook(() => useClientExport({}));
act(() => {
result.current.handleExport({ format: ExportFormat.Csv });
});
expect(mockDownloadFile).not.toHaveBeenCalled();
expect(mockMessageError).not.toHaveBeenCalled();
});
it('shows an error and does not download for unsupported result types', () => {
const raw = {
type: 'raw',
data: { results: [] },
meta: {},
} as unknown as QueryRangeResponseV5;
const { result } = renderHook(() => useClientExport({ response: raw }));
act(() => {
result.current.handleExport({ format: ExportFormat.Csv });
});
expect(mockDownloadFile).not.toHaveBeenCalled();
expect(mockMessageError).toHaveBeenCalled();
});
});

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@@ -0,0 +1,103 @@
import { message } from 'antd';
import {
downloadFile,
getTimestampedFileName,
} from 'lib/exportData/downloadFile';
import { exportTimeseriesData } from 'lib/exportData/exportTimeseriesData';
import { toCsv } from 'lib/exportData/toCsv';
import { toJsonl } from 'lib/exportData/toJsonl';
import {
ExportFormat,
SerializedTable,
TimeseriesShape,
} from 'lib/exportData/types';
import { useCallback, useState } from 'react';
import { Query } from 'types/api/queryBuilder/queryBuilderData';
import { QueryRangeResponseV5, TimeSeriesData } from 'types/api/v5/queryRange';
const FORMAT_META: Record<ExportFormat, { mime: string; extension: string }> = {
[ExportFormat.Csv]: { mime: 'text/csv;charset=utf-8;', extension: 'csv' },
[ExportFormat.Jsonl]: {
mime: 'application/x-ndjson;charset=utf-8;',
extension: 'jsonl',
},
};
// Picks the serializer for the response's request type. Narrows the results
// union via the response discriminant. scalar lands with #5591; raw/trace are
// server-exported, distribution is never emitted.
function serialize(
response: QueryRangeResponseV5,
shape: TimeseriesShape,
yAxisUnit?: string,
legendMap?: Record<string, string>,
query?: Query,
): SerializedTable {
if (response.type === 'time_series') {
return exportTimeseriesData({
data: response.data.results as TimeSeriesData[],
shape,
yAxisUnit,
legendMap,
query,
});
}
throw new Error(`Export is not supported for "${response.type}" results`);
}
interface UseClientExportProps {
response?: QueryRangeResponseV5;
// The builder query behind the response — series names resolve aggregation
// aliases/expressions from it, exactly like the chart legend.
query?: Query;
yAxisUnit?: string;
fileName?: string;
legendMap?: Record<string, string>;
}
interface ClientExportOptions {
format: ExportFormat;
shape?: TimeseriesShape;
}
interface UseClientExportReturn {
isExporting: boolean;
handleExport: (options: ClientExportOptions) => void;
}
// Frontend-driven export: serializes in-memory query results and downloads them
// client-side. Backend-driven export lives in useServerExport.
export function useClientExport({
response,
query,
yAxisUnit,
fileName = 'export',
legendMap,
}: UseClientExportProps): UseClientExportReturn {
const [isExporting, setIsExporting] = useState<boolean>(false);
const handleExport = useCallback(
({ format, shape = TimeseriesShape.Long }: ClientExportOptions): void => {
if (!response) {
return;
}
setIsExporting(true);
try {
const table = serialize(response, shape, yAxisUnit, legendMap, query);
const content =
format === ExportFormat.Jsonl ? toJsonl(table) : toCsv(table);
const { mime, extension } = FORMAT_META[format];
downloadFile(content, getTimestampedFileName(fileName, extension), mime);
} catch {
message.error('Failed to export data. Please try again.');
} finally {
setIsExporting(false);
}
},
[response, query, yAxisUnit, fileName, legendMap],
);
return { isExporting, handleExport };
}

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import { downloadFile, getTimestampedFileName } from '../downloadFile';
// jsdom doesn't implement the object-URL APIs; define stubs so jest.spyOn can wrap them.
if (typeof URL.createObjectURL !== 'function') {
URL.createObjectURL = (): string => '';
}
if (typeof URL.revokeObjectURL !== 'function') {
URL.revokeObjectURL = (): void => undefined;
}
describe('downloadFile', () => {
afterEach(() => {
jest.restoreAllMocks();
});
it('builds a blob anchor, clicks it, and revokes the object URL', () => {
const click = jest.fn();
const remove = jest.fn();
const anchor = {
href: '',
download: '',
click,
remove,
} as unknown as HTMLAnchorElement;
(
jest.spyOn(document, 'createElement') as unknown as jest.Mock
).mockReturnValue(anchor);
const createObjectURL = jest
.spyOn(URL, 'createObjectURL')
.mockReturnValue('blob:mock');
const revokeObjectURL = jest.spyOn(URL, 'revokeObjectURL');
downloadFile('hello', 'export.csv', 'text/csv');
expect(anchor.download).toBe('export.csv');
expect(anchor.href).toBe('blob:mock');
expect(click).toHaveBeenCalledTimes(1);
expect(createObjectURL).toHaveBeenCalled();
expect(revokeObjectURL).toHaveBeenCalledWith('blob:mock');
});
});
describe('getTimestampedFileName', () => {
afterEach(() => {
jest.useRealTimers();
});
it('appends a local timestamp between base and extension', () => {
jest.useFakeTimers().setSystemTime(new Date(2026, 6, 8, 14, 32, 5));
expect(getTimestampedFileName('logs-timeseries', 'csv')).toBe(
'logs-timeseries-2026-07-08_14-32-05.csv',
);
});
});

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@@ -0,0 +1,268 @@
import { Query } from 'types/api/queryBuilder/queryBuilderData';
import { TimeSeries, TimeSeriesData } from 'types/api/v5/queryRange';
import { exportTimeseriesData } from '../exportTimeseriesData';
import { TimeseriesShape } from '../types';
const iso = (ms: number): string => new Date(ms).toISOString();
function makeSeries(
labels: Record<string, string>,
values: [number, number][],
): TimeSeries {
return {
labels: Object.entries(labels).map(([name, value]) => ({
key: { name },
value,
})),
values: values.map(([timestamp, value]) => ({ timestamp, value })),
};
}
function makeQuery(
queryName: string,
buckets: { index?: number; alias?: string; series: TimeSeries[] }[],
): TimeSeriesData {
return {
queryName,
aggregations: buckets.map((bucket, i) => ({
index: bucket.index ?? i,
alias: bucket.alias ?? '',
meta: {},
series: bucket.series,
})),
};
}
describe('exportTimeseriesData', () => {
it('LONG: query column, label column, unit in value header, legend naming', () => {
const data = [
makeQuery('A', [
{
series: [
makeSeries({ service_name: 'frontend' }, [
[1000, 12],
[2000, 15],
]),
],
},
]),
];
const table = exportTimeseriesData({
data,
shape: TimeseriesShape.Long,
yAxisUnit: 'ms',
legendMap: { A: '{{service_name}}' },
});
expect(table.headers).toStrictEqual([
'timestamp',
'query',
'series',
'service_name',
'value (ms)',
]);
expect(table.rows).toStrictEqual([
[iso(1000), 'A', 'frontend', 'frontend', 12],
[iso(2000), 'A', 'frontend', 'frontend', 15],
]);
});
it('LONG: no legend falls back to the label-set name from getLabelName', () => {
const data = [
makeQuery('A', [
{ series: [makeSeries({ service_name: 'frontend' }, [[1000, 12]])] },
]),
];
const table = exportTimeseriesData({ data, shape: TimeseriesShape.Long });
expect(table.headers).toStrictEqual([
'timestamp',
'query',
'series',
'service_name',
'value',
]);
expect(table.rows).toStrictEqual([
[iso(1000), 'A', '{service_name="frontend"}', 'frontend', 12],
]);
});
it('WIDE: one column per series, sorted timestamps, blank for gaps', () => {
const data = [
makeQuery('A', [
{
series: [
makeSeries({ service: 'a' }, [
[1000, 1],
[2000, 2],
]),
makeSeries({ service: 'b' }, [[2000, 20]]),
],
},
]),
];
const table = exportTimeseriesData({
data,
shape: TimeseriesShape.Wide,
legendMap: { A: '{{service}}' },
});
expect(table.headers).toStrictEqual(['timestamp', 'a', 'b']);
expect(table.rows).toStrictEqual([
[iso(1000), 1, ''],
[iso(2000), 2, 20],
]);
});
it('WIDE: appends the y-axis unit to every series header', () => {
const data = [
makeQuery('A', [{ series: [makeSeries({ service: 'a' }, [[1000, 1]])] }]),
];
const table = exportTimeseriesData({
data,
shape: TimeseriesShape.Wide,
yAxisUnit: 'ms',
legendMap: { A: '{{service}}' },
});
expect(table.headers).toStrictEqual(['timestamp', 'a (ms)']);
expect(table.rows).toStrictEqual([[iso(1000), 1]]);
});
it('LONG multi-query: series column is not query-prefixed (query has its own column)', () => {
const data = [
makeQuery('A', [{ series: [makeSeries({ service: 'x' }, [[1000, 1]])] }]),
makeQuery('B', [{ series: [makeSeries({ service: 'y' }, [[1000, 2]])] }]),
];
const table = exportTimeseriesData({
data,
shape: TimeseriesShape.Long,
legendMap: { A: '{{service}}', B: '{{service}}' },
});
expect(table.headers).toStrictEqual([
'timestamp',
'query',
'series',
'service',
'value',
]);
expect(table.rows).toStrictEqual([
[iso(1000), 'A', 'x', 'x', 1],
[iso(1000), 'B', 'y', 'y', 2],
]);
});
it('WIDE multi-query: series headers stay distinct via their names', () => {
const data = [
makeQuery('A', [{ series: [makeSeries({ service: 'x' }, [[1000, 1]])] }]),
makeQuery('B', [{ series: [makeSeries({ service: 'y' }, [[1000, 2]])] }]),
];
const table = exportTimeseriesData({
data,
shape: TimeseriesShape.Wide,
legendMap: { A: '{{service}}', B: '{{service}}' },
});
expect(table.headers).toStrictEqual(['timestamp', 'x', 'y']);
expect(table.rows).toStrictEqual([[iso(1000), 1, 2]]);
});
it('multi-aggregation with the builder query: names match the chart legend', () => {
const data = [
makeQuery('A', [
{ index: 0, alias: '__result_0', series: [makeSeries({}, [[1000, 5]])] },
{
index: 1,
alias: '__result_1',
series: [makeSeries({}, [[1000, 300]])],
},
]),
makeQuery('B', [
{
index: 0,
alias: '__result_0',
series: [
makeSeries({ 'cloud.account.id': 'signoz-staging' }, [[1000, 7]]),
],
},
]),
];
const query = {
queryType: 'builder',
builder: {
queryData: [
{
queryName: 'A',
dataSource: 'logs',
aggregations: [
{ expression: 'count()' },
{ expression: 'avg(code.lineno)' },
],
groupBy: [],
},
{
queryName: 'B',
dataSource: 'logs',
aggregations: [{ expression: 'count()' }],
groupBy: [{ key: 'cloud.account.id' }],
},
],
queryFormulas: [],
},
} as unknown as Query;
const table = exportTimeseriesData({
data,
shape: TimeseriesShape.Wide,
query,
});
expect(table.headers).toStrictEqual([
'timestamp',
'count()-A',
'avg(code.lineno)-A',
'{cloud.account.id="signoz-staging"}',
]);
});
it('multi-aggregation without the builder query: falls back to base names, deduped', () => {
const data = [
makeQuery('A', [
{ index: 0, alias: '__result_0', series: [makeSeries({}, [[1000, 5]])] },
{
index: 1,
alias: '__result_1',
series: [makeSeries({}, [[1000, 300]])],
},
]),
];
const table = exportTimeseriesData({ data, shape: TimeseriesShape.Wide });
expect(table.headers).toStrictEqual(['timestamp', 'A', 'A (2)']);
});
it('empty data: returns a headers-only table', () => {
expect(
exportTimeseriesData({ data: [], shape: TimeseriesShape.Long }),
).toStrictEqual({
headers: ['timestamp', 'query', 'series', 'value'],
rows: [],
});
expect(
exportTimeseriesData({ data: [], shape: TimeseriesShape.Wide }),
).toStrictEqual({
headers: ['timestamp'],
rows: [],
});
});
});

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import { toCsv } from '../toCsv';
import { toJsonl } from '../toJsonl';
import { SerializedTable } from '../types';
const table: SerializedTable = {
headers: ['timestamp', 'value'],
rows: [
['t1', 12],
['t2', 15],
],
};
describe('toCsv', () => {
it('emits a header row then one row per record, in column order', () => {
expect(toCsv(table).split(/\r?\n/)).toStrictEqual([
'timestamp,value',
't1,12',
't2,15',
]);
});
it('quotes values containing the delimiter', () => {
const csv = toCsv({ headers: ['name', 'value'], rows: [['a,b', 1]] });
expect(csv.split(/\r?\n/)).toStrictEqual(['name,value', '"a,b",1']);
});
it('emits only the header row when there are no data rows', () => {
expect(toCsv({ headers: ['timestamp'], rows: [] })).toBe('timestamp\r\n');
});
});
describe('toJsonl', () => {
it('emits one JSON object per row keyed by header', () => {
expect(toJsonl(table)).toBe(
'{"timestamp":"t1","value":12}\n{"timestamp":"t2","value":15}',
);
});
it('emits an empty string when there are no rows', () => {
expect(toJsonl({ headers: ['timestamp'], rows: [] })).toBe('');
});
});

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/** Triggers a browser download of in-memory string content as a file. */
export function downloadFile(
content: string,
fileName: string,
mime: string,
): void {
const blob = new Blob([content], { type: mime });
const url = URL.createObjectURL(blob);
const link = document.createElement('a');
link.href = url;
link.download = fileName;
link.click();
link.remove();
URL.revokeObjectURL(url);
}
/** `base` + local timestamp + extension, e.g. `logs-timeseries-2026-07-08_14-32-05.csv`.
* Keeps repeated exports from colliding and records when the export was taken. */
export function getTimestampedFileName(
base: string,
extension: string,
): string {
const now = new Date();
const pad = (value: number): string => String(value).padStart(2, '0');
const stamp = `${now.getFullYear()}-${pad(now.getMonth() + 1)}-${pad(
now.getDate(),
)}_${pad(now.getHours())}-${pad(now.getMinutes())}-${pad(now.getSeconds())}`;
return `${base}-${stamp}.${extension}`;
}

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import { getLegend } from 'lib/dashboard/getQueryResults';
import getLabelName from 'lib/getLabelName';
import { Query } from 'types/api/queryBuilder/queryBuilderData';
import { TimeSeries, TimeSeriesData } from 'types/api/v5/queryRange';
import { QueryData } from 'types/api/widgets/getQuery';
import { SerializedTable, TimeseriesShape } from './types';
interface ExportTimeseriesDataArgs {
data: TimeSeriesData[];
shape: TimeseriesShape;
yAxisUnit?: string;
legendMap?: Record<string, string>;
// The builder query that produced the data — lets series names resolve
// aggregation aliases/expressions exactly like the chart legend does.
query?: Query;
}
// One row of the flattened V5 tree: a single (query, aggregation, label-set) series.
interface FlatSeries {
queryName: string;
labels: Record<string, string>;
name: string;
values: { timestamp: number; value: number }[];
}
// V5 labels [{key:{name}, value}] → {name: value} (the getLabelName contract).
function foldLabels(labels: TimeSeries['labels']): Record<string, string> {
const record: Record<string, string> = {};
(labels ?? []).forEach((label) => {
if (label.key?.name) {
record[label.key.name] = String(label.value);
}
});
return record;
}
// Series display name, matching the chart legend: getLabelName for the base
// (legend template / label-set), then getLegend to resolve the aggregation
// alias/expression from the builder query (the response only carries
// auto-generated `__result_N` aliases). Same chain the uPlot layer uses.
function seriesName(args: {
labels: Record<string, string>;
queryName: string;
legend: string;
aggIndex: number;
alias: string;
query?: Query;
}): string {
const { labels, queryName, legend, aggIndex, alias, query } = args;
const baseName = getLabelName(labels, queryName, legend);
if (!query) {
return baseName;
}
const legacySeries = {
queryName,
metric: labels,
values: [],
metaData: { alias, index: aggIndex, queryName },
} as QueryData;
return getLegend(legacySeries, query, baseName);
}
// Walk results → aggregations → series into a flat, named list.
function flatten(
data: TimeSeriesData[],
legendMap?: Record<string, string>,
query?: Query,
): FlatSeries[] {
const flat: FlatSeries[] = [];
data.forEach((result) => {
const queryName = result.queryName ?? '';
const legend = legendMap?.[queryName] ?? '';
(result.aggregations ?? []).forEach((bucket) => {
(bucket.series ?? []).forEach((series) => {
const labels = foldLabels(series.labels);
flat.push({
queryName,
labels,
name: seriesName({
labels,
queryName,
legend,
aggIndex: bucket.index ?? 0,
alias: bucket.alias ?? '',
query,
}),
values: (series.values ?? []).map((value) => ({
timestamp: value.timestamp,
value: value.value,
})),
});
});
});
});
return flat;
}
// Guarantee unique column headers if two series share a display name.
function dedupeHeaders(names: string[]): string[] {
const counts: Record<string, number> = {};
return names.map((name) => {
if (counts[name] === undefined) {
counts[name] = 1;
return name;
}
counts[name] += 1;
return `${name} (${counts[name]})`;
});
}
// Appends the y-axis unit to a header: `value` → `value (ms)`, `frontend` →
// `frontend (ms)`. Shared by LONG's value column and every WIDE series column.
function withUnit(header: string, yAxisUnit?: string): string {
return yAxisUnit ? `${header} (${yAxisUnit})` : header;
}
function toIso(timestamp: number): string {
return new Date(timestamp).toISOString();
}
// LONG (tidy): one row per (series, timestamp). query is its own column.
function buildLong(flat: FlatSeries[], yAxisUnit?: string): SerializedTable {
const labelKeySet = new Set<string>();
flat.forEach((series) => {
Object.keys(series.labels).forEach((key) => labelKeySet.add(key));
});
const labelKeys = Array.from(labelKeySet).sort();
const headers = [
'timestamp',
'query',
'series',
...labelKeys,
withUnit('value', yAxisUnit),
];
const rows: (string | number)[][] = [];
flat.forEach((series) => {
series.values.forEach(({ timestamp, value }) => {
rows.push([
toIso(timestamp),
series.queryName,
series.name,
...labelKeys.map((key) => series.labels[key] ?? ''),
value,
]);
});
});
return { headers, rows };
}
// WIDE (pivot): one row per timestamp, one column per series.
function buildWide(flat: FlatSeries[], yAxisUnit?: string): SerializedTable {
const timestampSet = new Set<number>();
flat.forEach((series) => {
series.values.forEach((value) => timestampSet.add(value.timestamp));
});
const timestamps = Array.from(timestampSet).sort((a, b) => a - b);
const valueBySeries = flat.map((series) => {
const map = new Map<number, number>();
series.values.forEach((value) => map.set(value.timestamp, value.value));
return map;
});
const seriesHeaders = dedupeHeaders(flat.map((series) => series.name)).map(
(header) => withUnit(header, yAxisUnit),
);
const headers = ['timestamp', ...seriesHeaders];
const rows: (string | number)[][] = timestamps.map((timestamp) => {
const row: (string | number)[] = [toIso(timestamp)];
valueBySeries.forEach((map) => {
const value = map.get(timestamp);
row.push(value === undefined ? '' : value);
});
return row;
});
return { headers, rows };
}
/**
* Serializes a V5 time_series result into a format-agnostic table (LONG or WIDE).
* Pure — walks the V5 tree directly; series names match the chart legend.
*/
export function exportTimeseriesData({
data,
shape,
yAxisUnit,
legendMap,
query,
}: ExportTimeseriesDataArgs): SerializedTable {
const flat = flatten(data, legendMap, query);
return shape === TimeseriesShape.Wide
? buildWide(flat, yAxisUnit)
: buildLong(flat, yAxisUnit);
}

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@@ -0,0 +1,8 @@
import { unparse } from 'papaparse';
import { SerializedTable } from './types';
/** Serializes a table to CSV. `fields` pins column order regardless of row keys. */
export function toCsv(table: SerializedTable): string {
return unparse({ fields: table.headers, data: table.rows });
}

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import { SerializedTable } from './types';
/** Serializes a table to newline-delimited JSON: one object per row, keyed by header. */
export function toJsonl(table: SerializedTable): string {
return table.rows
.map((row) =>
JSON.stringify(
Object.fromEntries(table.headers.map((header, i) => [header, row[i]])),
),
)
.join('\n');
}

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/** Format-agnostic tabular result produced by every exporter. Consumed by the
* CSV/JSONL formatters */
export interface SerializedTable {
headers: string[];
// One entry per header, in header order. Empty string marks a gap.
rows: (string | number)[][];
}
/** TimeSeries export layouts: LONG (tidy, one row per point) or WIDE (pivot). */
export enum TimeseriesShape {
Long = 'long',
Wide = 'wide',
}
/** File formats a client-side export can be downloaded as. */
export enum ExportFormat {
Csv = 'csv',
Jsonl = 'jsonl',
}