* 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
139 lines
4.7 KiB
TypeScript
139 lines
4.7 KiB
TypeScript
/**
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* SEB CSV format parser
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*
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* Format: Semicolon-delimited, comma decimal separator
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* Columns vary but typically: Bokföringsdag, Valutadag, Verifikationsnummer,
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* Text/mottagare, Belopp, Saldo
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* Date format: YYYY-MM-DD
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* Encoding: UTF-8 or Windows-1252
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*/
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import type { BankFileFormat, BankFileParseResult, ParsedBankTransaction, BankFileParseIssue } from '../types'
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import { prepareContent } from '../../shared/encoding'
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import { normalizeDate } from '../date-utils'
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function parseCommaDecimal(value: string): number {
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const cleaned = value.replace(/\s/g, '').replace(',', '.')
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return parseFloat(cleaned)
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}
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export const sebFormat: BankFileFormat = {
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id: 'seb',
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name: 'SEB',
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description: 'SEB CSV (semicolon-delimited)',
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fileExtensions: ['.csv', '.txt'],
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detect(content: string, _filename: string): boolean {
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const prepared = prepareContent(content)
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const firstLine = prepared.split('\n')[0]?.toLowerCase() || ''
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// SEB uses semicolon delimiter. Header always has a bokföringsdag/bokföringsdatum
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// column plus either valutadag/valutadatum or verifikationsnummer. The secondary
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// check distinguishes SEB from Länsförsäkringar (which also has bokföringsdag).
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const hasBookingDate = /bokf(ö|o)ringsda(g|tum)/.test(firstLine)
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const hasSebSecondary =
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/valuta(dag|datum)/.test(firstLine) || firstLine.includes('verifikationsnummer')
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return firstLine.includes(';') && hasBookingDate && hasSebSecondary
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},
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parse(content: string): BankFileParseResult {
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const prepared = prepareContent(content)
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const lines = prepared.split('\n').filter((line) => line.trim() !== '')
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const transactions: ParsedBankTransaction[] = []
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const issues: BankFileParseIssue[] = []
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let skippedRows = 0
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// Parse header to find column indices
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const headerLine = lines[0] || ''
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const headers = headerLine.split(';').map((h) => h.trim().toLowerCase().replace(/"/g, ''))
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// Find column indices dynamically
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const dateIdx = headers.findIndex((h) => /bokf(ö|o)ringsda(g|tum)/.test(h))
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const descIdx = headers.findIndex(
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(h) => h.includes('text') || h.includes('mottagare') || h.includes('beskrivning')
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)
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const amountIdx = headers.findIndex((h) => h.includes('belopp'))
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const balanceIdx = headers.findIndex((h) => h.includes('saldo'))
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if (dateIdx === -1 || amountIdx === -1) {
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issues.push({
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row: 1,
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message: 'Could not identify required columns (date, amount)',
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severity: 'error',
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})
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return {
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format: 'seb',
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format_name: 'SEB',
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transactions: [],
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date_from: null,
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date_to: null,
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issues,
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stats: { total_rows: 0, parsed_rows: 0, skipped_rows: 0, total_income: 0, total_expenses: 0 },
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}
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}
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for (let i = 1; i < lines.length; i++) {
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const line = lines[i].trim()
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if (!line) continue
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const fields = line.split(';').map((f) => f.trim().replace(/^"|"$/g, ''))
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const date = fields[dateIdx]
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const description = fields[descIdx >= 0 ? descIdx : dateIdx + 1] || 'Unknown'
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const amountStr = fields[amountIdx]
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const balanceStr = balanceIdx >= 0 ? fields[balanceIdx] : undefined
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if (!date || !amountStr) {
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issues.push({ row: i + 1, message: 'Missing required fields', severity: 'warning' })
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skippedRows++
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continue
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}
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const amount = parseCommaDecimal(amountStr)
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if (isNaN(amount)) {
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issues.push({ row: i + 1, message: `Invalid amount: ${amountStr}`, severity: 'warning' })
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skippedRows++
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continue
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}
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const normalizedDate = normalizeDate(date)
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if (!normalizedDate) {
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issues.push({ row: i + 1, message: `Invalid date: ${date}`, severity: 'warning' })
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skippedRows++
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continue
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}
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const balance = balanceStr ? parseCommaDecimal(balanceStr) : null
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transactions.push({
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date: normalizedDate,
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description: description.trim(),
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amount,
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currency: 'SEK',
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balance: isNaN(balance as number) ? null : balance,
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reference: null,
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counterparty: null,
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raw_line: line,
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})
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}
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const dates = transactions.map((t) => t.date).sort()
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return {
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format: 'seb',
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format_name: 'SEB',
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transactions,
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date_from: dates[0] || null,
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date_to: dates[dates.length - 1] || null,
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issues,
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stats: {
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total_rows: lines.length - 1,
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parsed_rows: transactions.length,
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skipped_rows: skippedRows,
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total_income: Math.round(transactions.filter((t) => t.amount > 0).reduce((s, t) => s + t.amount, 0) * 100) / 100,
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total_expenses: Math.round(transactions.filter((t) => t.amount < 0).reduce((s, t) => s + t.amount, 0) * 100) / 100,
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},
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}
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},
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}
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