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accounted/lib/import/opening-balance/column-detector.ts
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Jakob Wennberg ec27228a8e style: remove em/en dashes repo-wide, add CLAUDE.md rule against them (#890)
Em dashes (—) and en dashes (–) had spread across comments, docs, tests,
and a few UI strings, reading as AI-generated boilerplate rather than
house style. Replaced each with punctuation matching its context: colon
for explanatory clauses, comma for asides, plain hyphen for numeric/legal
ranges (e.g. "21-23§"), "to"/"till" for date ranges, parentheses for
paired-dash asides. messages/en.json and messages/sv.json were fixed by
hand together to keep sv/en in sync.

Left untouched where the dash is the functional subject rather than
decorative punctuation: date-range-parser.ts's separator regex,
charset-repair.ts's CP1252 byte-mapping table (and its test), the SIE
encoding mojibake docs, generic-csv.ts's minus-sign normalizer, the
agent system-prompt files that already instruct against em dashes, and
a golden iXBRL test fixture compared byte-for-byte.

Also fixes two bugs surfaced along the way: an off-by-one in
ApiKeysPanel's scope-label split (a leftover from an earlier partial
pass), and a charset-repair test that had lost the literal en-dash it
exists to verify.

Regenerated the agent atom seed migration (skills:generate) since 27
SKILL.md files changed. Added a CLAUDE.md rule against em/en dashes,
with an explicit carve-out for the functional-dash cases above.

Co-authored-by: Claude Sonnet 5 <noreply@anthropic.com>
2026-07-04 15:58:06 +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,
}
}