chore: import upstream snapshot with attribution

benchmarks/src/formatters.ts

@@ -0,0 +1,89 @@
+import type { Dataset } from './types.ts'
+import { stringify as stringifyCSV } from 'csv-stringify/sync'
+import { XMLBuilder } from 'fast-xml-parser'
+import { stringify as stringifyYAML } from 'yaml'
+import { encode as encodeToon } from '../../packages/toon/src/index.ts'
+
+/**
+ * Format converters registry
+ *
+ * @remarks
+ * All formatters attempt to preserve semantic equivalence with the source data,
+ * meaning the converted data should represent the same information. However,
+ * CSV has inherent limitations with nested structures (see `toCSV` docs).
+ */
+export const formatters: Record<string, (data: unknown) => string> = {
+  'json-pretty': data => JSON.stringify(data, undefined, 2),
+  'json-compact': data => JSON.stringify(data),
+  'toon': data => encodeToon(data),
+  'csv': data => toCSV(data),
+  'xml': data => toXML(data),
+  'yaml': data => stringifyYAML(data),
+}
+
+/**
+ * Convert data to CSV format
+ *
+ * @remarks
+ * Limitations: CSV is designed for flat tabular data only.
+ *
+ * This formatter:
+ *   - Only handles top-level objects with arrays of flat objects
+ *   - Cannot properly represent deeply nested structures (nested arrays/objects within rows)
+ *   - Loses nested structure information during conversion
+ *   - May produce misleading results for datasets with complex nesting (e.g., e-commerce orders with nested items)
+ *
+ * For datasets with nested structures, CSV comparisons may not be fair or representative
+ * of how CSV would typically be used in practice.
+ */
+function toCSV(data: unknown): string {
+  const sections: string[] = []
+
+  // Handle top-level object with arrays
+  if (typeof data === 'object' && data !== null && !Array.isArray(data)) {
+    for (const [key, value] of Object.entries(data)) {
+      if (Array.isArray(value) && value.length > 0) {
+        sections.push(`# ${key}`)
+        sections.push(stringifyCSV(value, { header: true }))
+      }
+    }
+    return sections.join('\n').trim()
+  }
+
+  // Root-level array
+  if (Array.isArray(data) && data.length > 0) {
+    return stringifyCSV(data, { header: true }).trim()
+  }
+
+  return ''
+}
+
+/**
+ * Convert data to XML format
+ *
+ * @remarks
+ * Uses `fast-xml-parser` to generate well-formatted XML with:
+ * - 2-space indentation for readability
+ * - Empty nodes suppressed
+ * - Proper escaping of special characters
+ */
+function toXML(data: unknown): string {
+  const builder = new XMLBuilder({
+    format: true,
+    indentBy: '  ',
+    suppressEmptyNode: true,
+  })
+
+  return builder.build(data)
+}
+
+/**
+ * Check if a dataset supports CSV format
+ *
+ * @remarks
+ * CSV is only suitable for flat tabular data. Datasets with nested structures
+ * should not be compared using CSV as it cannot properly represent the data.
+ */
+export function supportsCSV(dataset: Dataset): boolean {
+  return dataset.metadata.supportsCSV
+}