@dapplion/benchmark/lib/esm/utils/file.js

Ensures that new code does not introduce performance regressions with CI. Tracks:

import fs from "node:fs";
import csvParse from "csv-parse/lib/sync.js";
import csvStringify from "csv-stringify/lib/sync.js";
export function readJson(filepath) {
    const jsonStr = fs.readFileSync(filepath, "utf8");
    let json;
    try {
        json = JSON.parse(jsonStr);
    }
    catch (e) {
        throw Error(`Error parsing JSON ${filepath}: ${e.message}`);
    }
    // TODO: Validate schema
    return json;
}
export function writeJson(filepath, json) {
    const jsonStr = JSON.stringify(json, null, 2);
    fs.writeFileSync(filepath, jsonStr);
}
export function fromCsv(str) {
    const { csv, metadata } = splitCsvMetadata(str);
    return {
        data: csvParse(csv, { columns: true, cast: true }),
        metadata,
    };
}
export function toCsv(data, metadata) {
    // Support Embedded Metadata https://www.w3.org/TR/tabular-data-model/#embedded-metadata
    const csv = csvStringify(data, { header: true });
    if (metadata) {
        const metadataStr = toCsvMetadata(metadata);
        return `${metadataStr}\n${csv}`;
    }
    else {
        return csv;
    }
}
// CSV metadata
export function toCsvMetadata(metadata) {
    return Object.entries(metadata)
        .map(([key, value]) => `#,${key},${value}`)
        .join("\n");
}
/**
 * Embedded Metadata https://www.w3.org/TR/tabular-data-model/#embedded-metadata
 */
function splitCsvMetadata(str) {
    const metadata = {};
    const rows = str.trim().split("\n");
    let i = 0;
    for (i = 0; i < rows.length; i++) {
        const row = rows[i];
        if (row.startsWith("#")) {
            const [key, value] = row.slice(2).split(",");
            metadata[key] = value;
        }
        else {
            break;
        }
    }
    return { csv: rows.slice(i).join("\n"), metadata };
}