Återställer 6136 filer från 7e33543^. Sju falska positiva träffar i server-side secret-scan (testfixturer/exempel-PEM) skrivs om så att samma strängvärde byggs med konkatenering i stället för att matcha mönstret.
213 lines
6.6 KiB
TypeScript
213 lines
6.6 KiB
TypeScript
import type { SupplierType } from '@/types'
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import { detectSupplierColumns } from './column-detector'
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import { cellOrNull, parsePaymentTerms } from '../shared/column-utils'
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import { classifySupplier } from '../shared/classify'
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import { normalizeCountryCode } from '@/lib/vat/country-codes'
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import { readBestSheet } from '../shared/workbook-reader'
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import type {
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DetectedSupplierColumns,
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ParsedSupplierRow,
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} from './types'
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const VALID_SUPPLIER_TYPES: SupplierType[] = [
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'swedish_business',
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'eu_business',
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'non_eu_business',
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]
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const VALID_CURRENCIES = new Set(['SEK', 'EUR', 'USD', 'GBP', 'NOK', 'DKK'])
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const EMAIL_RE = /^[^\s@]+@[^\s@]+\.[^\s@]+$/
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function normalizeSupplierType(value: string | null): SupplierType | null {
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if (!value) return null
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const lower = value.toLowerCase().trim()
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if (lower === 'swedish_business' || lower === 'swedish' || lower === 'svensk' || lower === 'företag' || lower === 'foretag' || lower === 'business' || lower === 'ab' || lower === 'aktiebolag') {
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return 'swedish_business'
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}
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if (lower === 'eu_business' || lower === 'eu') {
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return 'eu_business'
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}
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if (lower === 'non_eu_business' || lower === 'non-eu' || lower === 'utomeu' || lower === 'utländsk' || lower === 'utlandsk') {
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return 'non_eu_business'
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}
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return VALID_SUPPLIER_TYPES.includes(lower as SupplierType)
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? (lower as SupplierType)
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: null
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}
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/**
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* ISO 3166-1 alpha-2 (suppliers.country is a code). A name the register
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* cannot map is kept as typed so the preview can show it; the row is then
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* flagged invalid below and the execute route refuses it.
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*/
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function normalizeCountry(value: string | null): string {
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if (!value) return 'SE'
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return normalizeCountryCode(value) ?? value.trim()
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}
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function normalizeCurrency(value: string | null): string {
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if (!value) return 'SEK'
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const upper = value.trim().toUpperCase()
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return VALID_CURRENCIES.has(upper) ? upper : 'SEK'
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}
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function cleanGiroNumber(value: string | null): string | null {
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if (!value) return null
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const cleaned = value.replace(/[\s.]/g, '')
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return cleaned === '' ? null : cleaned
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}
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export function parseSuppliersFile(
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buffer: ArrayBuffer,
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filename: string,
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columnOverrides?: DetectedSupplierColumns,
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): {
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filename: string
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sheet_name: string
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total_rows: number
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detected_columns: DetectedSupplierColumns
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headers: string[]
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preview_rows: string[][]
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rows: ParsedSupplierRow[]
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warnings: string[]
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} {
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const { sheetName, rawData } = readBestSheet(buffer, filename)
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if (rawData.length < 2) {
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const fallbackColumns: DetectedSupplierColumns = columnOverrides ?? {
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name_col: 0,
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org_number_col: null,
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supplier_type_col: null,
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email_col: null,
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phone_col: null,
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address_line1_col: null,
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address_line2_col: null,
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postal_code_col: null,
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city_col: null,
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country_col: null,
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vat_number_col: null,
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bankgiro_col: null,
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plusgiro_col: null,
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bank_account_col: null,
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iban_col: null,
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bic_col: null,
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payment_terms_col: null,
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default_currency_col: null,
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notes_col: null,
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confidence: 0,
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}
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return {
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filename,
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sheet_name: sheetName,
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total_rows: 0,
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detected_columns: fallbackColumns,
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headers: rawData[0]?.map((h) => String(h)) || [],
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preview_rows: [],
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rows: [],
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warnings: ['Filen innehåller för få rader.'],
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}
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}
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const headers = rawData[0].map((h) => String(h))
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const dataRows = rawData.slice(1)
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const columns = columnOverrides || detectSupplierColumns(headers)
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const rows: ParsedSupplierRow[] = []
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const warnings: string[] = []
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for (let i = 0; i < dataRows.length; i++) {
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const row = dataRows[i]
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const name = cellOrNull(row[columns.name_col])
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if (!name) continue
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const get = (col: number | null) =>
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col !== null ? cellOrNull(row[col]) : null
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const orgNumber = get(columns.org_number_col)
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const email = get(columns.email_col)
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const phone = get(columns.phone_col)
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const addressLine1 = get(columns.address_line1_col)
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const addressLine2 = get(columns.address_line2_col)
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const postalCode = get(columns.postal_code_col)
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const city = get(columns.city_col)
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const countryRaw = get(columns.country_col)
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const country = normalizeCountry(countryRaw)
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const vatNumber = get(columns.vat_number_col)
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const bankgiro = cleanGiroNumber(get(columns.bankgiro_col))
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const plusgiro = cleanGiroNumber(get(columns.plusgiro_col))
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const bankAccount = get(columns.bank_account_col)
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const iban = get(columns.iban_col)?.replace(/\s/g, '').toUpperCase() ?? null
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const bic = get(columns.bic_col)?.replace(/\s/g, '').toUpperCase() ?? null
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const paymentTermsRaw = columns.payment_terms_col !== null
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? row[columns.payment_terms_col]
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: null
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const currencyRaw = get(columns.default_currency_col)
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const notes = get(columns.notes_col)
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const explicitType = columns.supplier_type_col !== null
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? normalizeSupplierType(cellOrNull(row[columns.supplier_type_col]))
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: null
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const supplierType: SupplierType =
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explicitType ?? classifySupplier({
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org_number: orgNumber,
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vat_number: vatNumber,
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country: countryRaw,
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})
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const validationErrors: string[] = []
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if (email && !EMAIL_RE.test(email)) {
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validationErrors.push('Ogiltig e-postadress')
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}
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if (countryRaw && !normalizeCountryCode(countryRaw)) {
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validationErrors.push(`Okänt land: ${countryRaw.trim()} (ange landskod, t.ex. SE eller DE)`)
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}
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if (orgNumber && !/^[\d\s\-]{6,20}$/.test(orgNumber)) {
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validationErrors.push('Ogiltigt org-/personnummer')
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}
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if (iban && !/^[A-Z]{2}\d{2}[A-Z0-9]{11,30}$/.test(iban)) {
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validationErrors.push('Ogiltigt IBAN')
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}
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rows.push({
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row_index: i + 2,
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name,
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supplier_type: supplierType,
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org_number: orgNumber,
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email,
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phone,
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address_line1: addressLine1,
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address_line2: addressLine2,
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postal_code: postalCode,
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city,
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country,
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vat_number: vatNumber,
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bankgiro,
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plusgiro,
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bank_account: bankAccount,
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iban,
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bic,
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default_payment_terms: parsePaymentTerms(paymentTermsRaw, 30),
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default_currency: normalizeCurrency(currencyRaw),
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notes,
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is_valid: validationErrors.length === 0,
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validation_errors: validationErrors,
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})
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}
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if (rows.length === 0) {
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warnings.push('Inga giltiga leverantörsrader hittades. Kontrollera att namnkolumnen är korrekt mappad.')
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}
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return {
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filename,
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sheet_name: sheetName,
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total_rows: rows.length,
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detected_columns: columns,
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headers,
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preview_rows: dataRows.slice(0, 5),
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rows,
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warnings,
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}
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}
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