Add/csv import options (#420)
* feat(import): add customer and supplier parsing functionality - Implemented customer file parsing in `lib/import/customers/parser.ts` with support for Excel and CSV formats. - Created types for detected customer columns and parsed customer rows in `lib/import/customers/types.ts`. - Added tests for customer classification logic in `lib/import/shared/__tests__/classify.test.ts`. - Developed classification functions for customers and suppliers in `lib/import/shared/classify.ts`. - Introduced shared column utility functions in `lib/import/shared/column-utils.ts`. - Implemented supplier file parsing in `lib/import/suppliers/parser.ts` with validation for various fields. - Created types for detected supplier columns and parsed supplier rows in `lib/import/suppliers/types.ts`. - Added tests for supplier column detection and parsing in `lib/import/suppliers/__tests__/column-detector.test.ts` and `lib/import/suppliers/__tests__/parser.test.ts`. * fix(labels): update 'Svenskt företag' to 'Svenskt företag eller organisation' for clarity * feat(import): refactor encoding handling for Swedish files and add tests for character preservation * feat(recapt): implement clearRecaptIdentity function and integrate into logout flow * feat(bookkeeping): implement copy functionality and next voucher sequence retrieval * feat(import): enhance customer and supplier import functionality with normalization and event handling
This commit is contained in:
Mattsson
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import type { CustomerType } from '@/types'
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import { detectCustomerColumns } from './column-detector'
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import { cellOrNull, parsePaymentTerms } from '../shared/column-utils'
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import { classifyCustomer } from '../shared/classify'
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import { readBestSheet } from '../shared/workbook-reader'
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import type {
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DetectedCustomerColumns,
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ParsedCustomerRow,
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} from './types'
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const VALID_CUSTOMER_TYPES: CustomerType[] = [
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'individual',
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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 EMAIL_RE = /^[^\s@]+@[^\s@]+\.[^\s@]+$/
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function normalizeCustomerType(value: string | null): CustomerType | null {
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if (!value) return null
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const lower = value.toLowerCase().trim()
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if (lower === 'individual' || lower === 'privat' || lower === 'privatperson' || lower === 'person') {
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return 'individual'
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}
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if (lower === 'swedish_business' || lower === 'swedish' || 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_CUSTOMER_TYPES.includes(lower as CustomerType)
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? (lower as CustomerType)
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: null
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}
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function normalizeCountry(value: string | null): string {
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if (!value) return 'Sweden'
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const trimmed = value.trim()
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const lower = trimmed.toLowerCase()
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if (lower === 'se' || lower === 'sverige' || lower === 'sweden') return 'Sweden'
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return trimmed
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}
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/**
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* Parse a customer-register file (Excel or CSV) and return structured rows.
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*
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* @param buffer - Raw file buffer
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* @param filename - Original filename
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* @param columnOverrides - Optional manual column mapping
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*/
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export function parseCustomersFile(
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buffer: ArrayBuffer,
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filename: string,
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columnOverrides?: DetectedCustomerColumns,
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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: DetectedCustomerColumns
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headers: string[]
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preview_rows: string[][]
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rows: ParsedCustomerRow[]
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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: DetectedCustomerColumns = columnOverrides ?? {
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name_col: 0,
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org_number_col: null,
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customer_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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payment_terms_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 || detectCustomerColumns(headers)
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const rows: ParsedCustomerRow[] = []
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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 // skip empty rows silently
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const orgNumber = columns.org_number_col !== null
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? cellOrNull(row[columns.org_number_col])
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: null
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const email = columns.email_col !== null
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? cellOrNull(row[columns.email_col])
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: null
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const phone = columns.phone_col !== null
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? cellOrNull(row[columns.phone_col])
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: null
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const addressLine1 = columns.address_line1_col !== null
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? cellOrNull(row[columns.address_line1_col])
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: null
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const addressLine2 = columns.address_line2_col !== null
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? cellOrNull(row[columns.address_line2_col])
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: null
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const postalCode = columns.postal_code_col !== null
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? cellOrNull(row[columns.postal_code_col])
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: null
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const city = columns.city_col !== null
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? cellOrNull(row[columns.city_col])
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: null
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const countryRaw = columns.country_col !== null
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? cellOrNull(row[columns.country_col])
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: null
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const country = normalizeCountry(countryRaw)
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const vatNumber = columns.vat_number_col !== null
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? cellOrNull(row[columns.vat_number_col])
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: 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 notes = columns.notes_col !== null
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? cellOrNull(row[columns.notes_col])
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: null
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const explicitType = columns.customer_type_col !== null
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? normalizeCustomerType(cellOrNull(row[columns.customer_type_col]))
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: null
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const customerType: CustomerType =
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explicitType ?? classifyCustomer({
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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 (orgNumber && !/^[\d\s\-]{6,20}$/.test(orgNumber)) {
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validationErrors.push('Ogiltigt org-/personnummer')
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}
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rows.push({
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row_index: i + 2, // 1-based + header
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name,
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customer_type: customerType,
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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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default_payment_terms: parsePaymentTerms(paymentTermsRaw, 30),
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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 kundrader 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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