2d6ddeafc5
* feat(import/export): article import + register export (xlsx/csv)
Add CSV/Excel import for the article register (artiklar), mirroring the
existing customer/supplier import pipeline, plus Excel + CSV export for
articles, customers and suppliers.
Import (lib/import/articles + app/api/import/articles):
- Column auto-detection tuned to Fortnox/Visma/Bokio export headers,
Swedish-decimal price parsing, VAT snapped to {0,6,12,25}, type/unit
normalization.
- Dedup by article number then name; 23505 soft-skip; auto-number
backfill; revenue-account override kept only when active, otherwise
dropped with a warning (never mutates the chart of accounts).
- New "Artiklar" flow in the /import hub.
Export (app/api/export/* + lib/export/register-export):
- Read-only xlsx (default) / csv (?format=csv, UTF-8 BOM) downloads.
- Headers chosen so files round-trip back through the importer.
- "Exportera" menu added to the articles, customers and suppliers pages.
Refs #746. Direct Fortnox/Visma API article fetch tracked in #749.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* fix(import/export): address PR review — lint ratchet + export hardening
- xlsx-export: keep `SheetSpec<any>` on the eslint-disabled line (fixes the
core-only lint ratchet regression: no-explicit-any 16 -> 15) and define
UTF8_BOM as an explicit `` escape instead of a raw BOM character.
- export routes (articles/customers/suppliers): move the data queries inside
the try/catch, add `Cache-Control: no-store`, and emit a `register exported`
audit log line (entity, format, rowCount).
- articles parse route: validate `column_overrides` against a Zod schema before
trusting it to drive the parser.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* fix(import): drop öre-round pattern on article column-detector confidence
The confidence score is a 0-1 heuristic, not money, and is only compared
against the 0.8 skip-mapping threshold. Removing the Math.round(x*100)/100
form clears the core-only antipattern ratchet (naive-ore-round 660 -> 659).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(import): flag adjusted VAT rows in the article import edit step
Surface VAT snapping/defaulting per row, not just as a file-level warning:
the parser sets `vat_rate_adjusted`, the edit step highlights those rows'
VAT selector and shows a count banner, and confirming a rate clears the flag.
Addresses the Swedish-compliance review note that silent snapping could
otherwise store a wrong VAT rate at scale.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
120 lines
4.5 KiB
TypeScript
120 lines
4.5 KiB
TypeScript
import { findColumn } from '../shared/column-utils'
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import type { DetectedArticleColumns } from './types'
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// Keyword lists cover the export headers of Fortnox, Visma and Bokio so files
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// from those systems auto-map. Header-only matching (register imports always
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// have a header row).
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const NAME_KEYWORDS = [
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'benämning', 'benamning', 'artikelnamn', 'artikel namn', 'namn', 'name',
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'produktnamn', 'produkt namn', 'product name', 'article name', 'beskrivning',
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'description', 'title',
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]
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const NAME_EN_KEYWORDS = [
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'engelska', 'english', 'name en', 'name english', 'name_english',
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'engelskt namn', 'benämning engelska',
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]
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// Note: bare 'kod'/'code' are deliberately excluded — they collide with
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// Fortnox's "Momskod" (a VAT column). EAN is detected first so "EAN-nummer"
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// is claimed before the generic 'nummer'/'number' here.
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const ARTICLE_NUMBER_KEYWORDS = [
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'artikelnummer', 'artikelnr', 'artnr', 'art nr', 'art no', 'artikelkod',
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'article code', 'sku', 'nummer', 'number',
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]
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const TYPE_KEYWORDS = ['typ', 'type', 'artikeltyp', 'article type', 'varutyp']
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const UNIT_KEYWORDS = ['enhet', 'unit', 'enh', 'uom', 'måttenhet', 'mattenhet']
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const VAT_RATE_KEYWORDS = [
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'momssats', 'momskod', 'moms %', 'moms', 'momsprocent', 'vat rate', 'vat code',
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'vat %', 'vat', 'tax rate',
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]
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const REVENUE_ACCOUNT_KEYWORDS = [
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'försäljningskonto', 'forsaljningskonto', 'intäktskonto', 'intaktskonto',
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'bokföringskonto', 'bokforingskonto', 'sales account', 'revenue account',
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'kontering', 'coding', 'konto', 'account',
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]
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const COST_PRICE_KEYWORDS = [
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'inköpspris', 'inkopspris', 'självkostnad', 'sjalvkostnad', 'kostpris',
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'kostnadspris', 'purchase price', 'cost price', 'cost',
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]
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const PRICE_KEYWORDS = [
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'försäljningspris', 'forsaljningspris', 'pris exkl moms', 'pris exkl. moms',
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'à-pris', 'a-pris', 'apris', 'styckpris', 'nettopris', 'net price',
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'unit price', 'pris', 'price', 'belopp', 'sales price',
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]
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const EAN_KEYWORDS = ['ean', 'ean-kod', 'streckkod', 'gtin', 'barcode']
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const HOUSEWORK_KEYWORDS = [
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'rot/rut', 'rot rut', 'arbetstyp', 'husarbete', 'housework', 'rot', 'rut',
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]
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const NOTES_KEYWORDS = [
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'anteckning', 'anteckningar', 'kommentar', 'kommentarer', 'comment', 'notes',
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'note', 'övrigt', 'ovrigt',
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]
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/**
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* Detect article-register columns from headers.
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*
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* Detection order matters: more specific columns are claimed first (via the
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* shared `taken` set) so a generic keyword can't swallow them — e.g. EAN before
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* the article number ("EAN-nummer" must not be read as the article number), and
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* the English name before the generic name column.
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*/
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export function detectArticleColumns(headers: string[]): DetectedArticleColumns {
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const taken = new Set<number>()
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// Order matters (shared `taken` set): claim specific columns before generic
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// ones. EAN before the article number ("EAN-nummer"), the price columns
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// before VAT (so "Pris exkl moms" isn't read as the VAT column), and the
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// generic name column dead last.
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const name_en_col = findColumn(headers, NAME_EN_KEYWORDS, taken)
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const ean_col = findColumn(headers, EAN_KEYWORDS, taken)
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const article_number_col = findColumn(headers, ARTICLE_NUMBER_KEYWORDS, taken)
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const revenue_account_col = findColumn(headers, REVENUE_ACCOUNT_KEYWORDS, taken)
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const cost_price_col = findColumn(headers, COST_PRICE_KEYWORDS, taken)
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const price_col = findColumn(headers, PRICE_KEYWORDS, taken)
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const vat_rate_col = findColumn(headers, VAT_RATE_KEYWORDS, taken)
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const type_col = findColumn(headers, TYPE_KEYWORDS, taken)
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const unit_col = findColumn(headers, UNIT_KEYWORDS, taken)
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const housework_type_col = findColumn(headers, HOUSEWORK_KEYWORDS, taken)
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const notes_col = findColumn(headers, NOTES_KEYWORDS, taken)
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const name_col = findColumn(headers, NAME_KEYWORDS, taken) ?? -1
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// Confidence: name is required; bonus from how many other columns matched.
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let confidence = 0
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if (name_col >= 0) {
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const matched = [
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article_number_col, price_col, vat_rate_col, unit_col,
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revenue_account_col, type_col,
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].filter((c) => c !== null).length
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confidence = 0.55 + Math.min(matched, 6) * 0.075
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}
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return {
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name_col: name_col >= 0 ? name_col : 0,
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article_number_col,
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name_en_col,
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type_col,
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unit_col,
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price_col,
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vat_rate_col,
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revenue_account_col,
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cost_price_col,
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ean_col,
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housework_type_col,
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notes_col,
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// Confidence is a 0–1 heuristic score (not money), only compared against the
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// 0.8 skip-mapping threshold — no öre rounding needed.
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confidence: Math.min(confidence, 1),
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}
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}
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