Files
accounted/lib/import/opening-balance/column-detector.ts
T
Mattsson a3fea6fb7c feat: add opening balance import functionality (#238)
- Implemented OpeningBalanceResultStep component to display results of the import process, including success messages and error handling.
- Created OpeningBalanceUploadStep component for file upload with drag-and-drop support, including validation for accepted file types.
- Developed column detection logic in column-detector.ts to identify account number, name, debit, credit, and balance columns based on headers and data.
- Added parser functionality in parser.ts to handle parsing of opening balance files, including validation and BAS account matching.
- Created tests for column detection and parsing logic to ensure accuracy and reliability.
- Defined types for detected columns and parsed rows in types.ts to improve type safety and clarity in the codebase.
2026-04-14 15:35:50 +02:00

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import type { DetectedColumns, BalanceColumnLayout } from './types'
/** Swedish/English keywords for account number columns */
const ACCOUNT_NUMBER_KEYWORDS = [
'konto', 'kontonr', 'kontonummer', 'kto', 'account', 'account_number',
'account number', 'acct', 'nr',
]
/** Keywords for account name columns */
const ACCOUNT_NAME_KEYWORDS = [
'kontonamn', 'benämning', 'namn', 'name', 'account name', 'description',
'benamning', 'text', 'beteckning',
]
/** Keywords for debit columns */
const DEBIT_KEYWORDS = ['debet', 'debit', 'deb']
/** Keywords for credit columns */
const CREDIT_KEYWORDS = ['kredit', 'credit', 'kred', 'cred']
/** Keywords for net balance columns */
const BALANCE_KEYWORDS = [
'saldo', 'balans', 'balance', 'ib', 'ingående', 'ingaende',
'ingående balans', 'opening', 'opening balance', 'belopp', 'amount',
]
function normalize(header: string): string {
return header.toLowerCase().trim().replace(/[_\-./]/g, ' ')
}
function matchesKeywords(header: string, keywords: string[]): boolean {
const normalized = normalize(header)
return keywords.some((kw) => normalized === kw || normalized.includes(kw))
}
/**
* Check if a column of string values looks like 4-digit account numbers.
* Returns the fraction of non-empty values that match /^\d{4}$/.
*/
function accountNumberScore(values: string[]): number {
const nonEmpty = values.filter((v) => v.trim().length > 0)
if (nonEmpty.length === 0) return 0
const matching = nonEmpty.filter((v) => /^\d{4}$/.test(v.trim()))
return matching.length / nonEmpty.length
}
/**
* Check if a column of string values looks like numeric amounts.
* Handles Swedish decimal commas and thousand separators.
*/
function numericScore(values: string[]): number {
const nonEmpty = values.filter((v) => v.trim().length > 0)
if (nonEmpty.length === 0) return 0
const matching = nonEmpty.filter((v) => {
const cleaned = v.trim().replace(/\s/g, '').replace(/\./g, '').replace(',', '.')
return !isNaN(parseFloat(cleaned)) && isFinite(Number(cleaned))
})
return matching.length / nonEmpty.length
}
/**
* Detect column layout from headers and sample data rows.
*
* @param headers - Array of header strings from the first row
* @param dataRows - 2D array of string values (rows × columns)
* @returns DetectedColumns with confidence score
*/
export function detectColumns(
headers: string[],
dataRows: string[][],
): DetectedColumns {
let accountNumberCol = -1
let accountNameCol: number | null = null
let debitCol: number | null = null
let creditCol: number | null = null
let balanceCol: number | null = null
let confidence = 0
// Phase 1: Header keyword matching
for (let i = 0; i < headers.length; i++) {
const h = headers[i]
if (accountNumberCol === -1 && matchesKeywords(h, ACCOUNT_NUMBER_KEYWORDS)) {
accountNumberCol = i
} else if (accountNameCol === null && matchesKeywords(h, ACCOUNT_NAME_KEYWORDS)) {
accountNameCol = i
} else if (debitCol === null && matchesKeywords(h, DEBIT_KEYWORDS)) {
debitCol = i
} else if (creditCol === null && matchesKeywords(h, CREDIT_KEYWORDS)) {
creditCol = i
} else if (balanceCol === null && matchesKeywords(h, BALANCE_KEYWORDS)) {
balanceCol = i
}
}
// Phase 2: Data-driven fallback for account number column
if (accountNumberCol === -1 && dataRows.length > 0) {
let bestScore = 0
for (let i = 0; i < headers.length; i++) {
const colValues = dataRows.map((row) => row[i] || '')
const score = accountNumberScore(colValues)
if (score > bestScore && score >= 0.5) {
bestScore = score
accountNumberCol = i
}
}
}
// If we still haven't found the account number column, give up
if (accountNumberCol === -1) {
return {
account_number_col: 0,
account_name_col: null,
layout: 'net',
balance_col: null,
debit_col: null,
credit_col: null,
confidence: 0,
}
}
// Phase 3: Detect numeric columns if debit/credit/balance not found via headers
if (debitCol === null && creditCol === null && balanceCol === null && dataRows.length > 0) {
const numericCols: number[] = []
for (let i = 0; i < headers.length; i++) {
if (i === accountNumberCol || i === accountNameCol) continue
const colValues = dataRows.map((row) => row[i] || '')
if (numericScore(colValues) >= 0.5) {
numericCols.push(i)
}
}
if (numericCols.length === 1) {
balanceCol = numericCols[0]
} else if (numericCols.length >= 2) {
// Assume first two numeric columns are debit and credit
debitCol = numericCols[0]
creditCol = numericCols[1]
}
}
// Determine layout
let layout: BalanceColumnLayout = 'net'
if (debitCol !== null && creditCol !== null) {
layout = 'debit_credit'
} else if (balanceCol !== null) {
layout = 'net'
} else if (debitCol !== null || creditCol !== null) {
// Only one of debit/credit found — treat as net balance
balanceCol = debitCol ?? creditCol
debitCol = null
creditCol = null
layout = 'net'
}
// Calculate confidence
const hasAccountCol = accountNumberCol >= 0
const hasAmountCol = layout === 'debit_credit'
? (debitCol !== null && creditCol !== null)
: balanceCol !== null
const hasNameCol = accountNameCol !== null
if (hasAccountCol && hasAmountCol) {
// Boost confidence if data also validates
const colValues = dataRows.map((row) => row[accountNumberCol] || '')
const dataScore = accountNumberScore(colValues)
confidence = hasNameCol ? 0.9 + dataScore * 0.1 : 0.8 + dataScore * 0.1
} else if (hasAccountCol) {
confidence = 0.4
}
confidence = Math.min(confidence, 1)
return {
account_number_col: accountNumberCol,
account_name_col: accountNameCol,
layout,
balance_col: balanceCol,
debit_col: debitCol,
credit_col: creditCol,
confidence: Math.round(confidence * 100) / 100,
}
}