forked from baron/baron-sso
org chart 연동기능 추가
This commit is contained in:
@@ -0,0 +1,92 @@
|
||||
import { describe, expect, it } from "vitest";
|
||||
import type { TenantSummary } from "../../../lib/adminApi";
|
||||
import {
|
||||
buildTenantImportPreview,
|
||||
parseTenantCSV,
|
||||
serializeTenantImportCSV,
|
||||
} from "./tenantCsvImport";
|
||||
|
||||
const tenants: TenantSummary[] = [
|
||||
{
|
||||
id: "tenant-1",
|
||||
type: "COMPANY",
|
||||
name: "Hanmac Technology",
|
||||
slug: "hanmac",
|
||||
description: "",
|
||||
status: "active",
|
||||
domains: ["hanmac.example.com"],
|
||||
memberCount: 0,
|
||||
createdAt: "",
|
||||
updatedAt: "",
|
||||
},
|
||||
{
|
||||
id: "tenant-2",
|
||||
type: "COMPANY",
|
||||
name: "Saman Engineering",
|
||||
slug: "saman",
|
||||
description: "",
|
||||
status: "active",
|
||||
domains: [],
|
||||
memberCount: 0,
|
||||
createdAt: "",
|
||||
updatedAt: "",
|
||||
},
|
||||
];
|
||||
|
||||
describe("tenantCsvImport", () => {
|
||||
it("parses tenant CSV rows with the supported import columns", () => {
|
||||
const rows = parseTenantCSV(
|
||||
"tenant_id,name,type,parent_tenant_id,slug,memo,email_domain\n,Hanmac Tech,COMPANY,,hanmac-tech,Memo,hanmac-tech.example.com\n",
|
||||
);
|
||||
|
||||
expect(rows).toEqual([
|
||||
{
|
||||
rowNumber: 2,
|
||||
tenantId: "",
|
||||
name: "Hanmac Tech",
|
||||
type: "COMPANY",
|
||||
parentTenantId: "",
|
||||
slug: "hanmac-tech",
|
||||
memo: "Memo",
|
||||
emailDomain: "hanmac-tech.example.com",
|
||||
},
|
||||
]);
|
||||
});
|
||||
|
||||
it("puts tenant_id-less rows with exact or similar matches first", () => {
|
||||
const rows = parseTenantCSV(
|
||||
"tenant_id,name,type,parent_tenant_id,slug,memo,email_domain\n,New Tenant,COMPANY,,new-tenant,,\n,Hanmac Tech,COMPANY,,hanmac-tech,,\n,Saman Engineering,COMPANY,,saman-copy,,\n",
|
||||
);
|
||||
|
||||
const preview = buildTenantImportPreview(rows, tenants);
|
||||
|
||||
expect(preview.map((row) => row.row.name)).toEqual([
|
||||
"Saman Engineering",
|
||||
"Hanmac Tech",
|
||||
"New Tenant",
|
||||
]);
|
||||
expect(preview[0].candidates[0]).toMatchObject({
|
||||
tenantId: "tenant-2",
|
||||
reason: "exact_name",
|
||||
});
|
||||
expect(preview[1].candidates[0]).toMatchObject({
|
||||
tenantId: "tenant-1",
|
||||
reason: "similar_name",
|
||||
});
|
||||
expect(preview[2].candidates).toEqual([]);
|
||||
});
|
||||
|
||||
it("serializes selected matches by filling tenant_id before upload", () => {
|
||||
const rows = parseTenantCSV(
|
||||
"tenant_id,name,type,parent_tenant_id,slug,memo,email_domain\n,Hanmac Tech,COMPANY,,hanmac-tech,Memo,hanmac-tech.example.com\n",
|
||||
);
|
||||
const preview = buildTenantImportPreview(rows, tenants);
|
||||
const csv = serializeTenantImportCSV(preview, {
|
||||
2: "tenant-1",
|
||||
});
|
||||
|
||||
expect(csv).toContain(
|
||||
"tenant-1,Hanmac Tech,COMPANY,,hanmac-tech,Memo,hanmac-tech.example.com",
|
||||
);
|
||||
});
|
||||
});
|
||||
264
adminfront/src/features/tenants/utils/tenantCsvImport.ts
Normal file
264
adminfront/src/features/tenants/utils/tenantCsvImport.ts
Normal file
@@ -0,0 +1,264 @@
|
||||
import type { TenantSummary } from "../../../lib/adminApi";
|
||||
|
||||
export type TenantCSVRow = {
|
||||
rowNumber: number;
|
||||
tenantId: string;
|
||||
name: string;
|
||||
type: string;
|
||||
parentTenantId: string;
|
||||
slug: string;
|
||||
memo: string;
|
||||
emailDomain: string;
|
||||
};
|
||||
|
||||
export type TenantImportCandidate = {
|
||||
tenantId: string;
|
||||
name: string;
|
||||
slug: string;
|
||||
score: number;
|
||||
reason: "exact_name" | "exact_slug" | "similar_name";
|
||||
};
|
||||
|
||||
export type TenantImportPreviewRow = {
|
||||
row: TenantCSVRow;
|
||||
candidates: TenantImportCandidate[];
|
||||
defaultTenantId: string;
|
||||
};
|
||||
|
||||
const importHeaders = [
|
||||
"tenant_id",
|
||||
"name",
|
||||
"type",
|
||||
"parent_tenant_id",
|
||||
"slug",
|
||||
"memo",
|
||||
"email_domain",
|
||||
];
|
||||
|
||||
const headerAliases: Record<string, keyof TenantCSVRow> = {
|
||||
id: "tenantId",
|
||||
tenantid: "tenantId",
|
||||
tenant_id: "tenantId",
|
||||
name: "name",
|
||||
type: "type",
|
||||
parentid: "parentTenantId",
|
||||
parent_id: "parentTenantId",
|
||||
parenttenantid: "parentTenantId",
|
||||
parent_tenant_id: "parentTenantId",
|
||||
slug: "slug",
|
||||
memo: "memo",
|
||||
description: "memo",
|
||||
"email-domain": "emailDomain",
|
||||
emaildomain: "emailDomain",
|
||||
email_domain: "emailDomain",
|
||||
domain: "emailDomain",
|
||||
domains: "emailDomain",
|
||||
};
|
||||
|
||||
export function parseTenantCSV(text: string): TenantCSVRow[] {
|
||||
const records = parseCSV(text.replace(/^\uFEFF/, ""));
|
||||
if (records.length === 0) return [];
|
||||
|
||||
const header = new Map<keyof TenantCSVRow, number>();
|
||||
records[0].forEach((column, index) => {
|
||||
const normalized = normalizeHeader(column);
|
||||
const key = headerAliases[normalized];
|
||||
if (key) header.set(key, index);
|
||||
});
|
||||
|
||||
return records.slice(1).flatMap((record, index) => {
|
||||
if (record.every((value) => value.trim() === "")) return [];
|
||||
const value = (key: keyof TenantCSVRow) => {
|
||||
const columnIndex = header.get(key);
|
||||
if (columnIndex === undefined) return "";
|
||||
return (record[columnIndex] ?? "").trim();
|
||||
};
|
||||
|
||||
return {
|
||||
rowNumber: index + 2,
|
||||
tenantId: value("tenantId"),
|
||||
name: value("name"),
|
||||
type: value("type"),
|
||||
parentTenantId: value("parentTenantId"),
|
||||
slug: value("slug"),
|
||||
memo: value("memo"),
|
||||
emailDomain: value("emailDomain"),
|
||||
};
|
||||
});
|
||||
}
|
||||
|
||||
export function buildTenantImportPreview(
|
||||
rows: TenantCSVRow[],
|
||||
tenants: TenantSummary[],
|
||||
): TenantImportPreviewRow[] {
|
||||
return rows
|
||||
.map((row) => {
|
||||
const candidates = row.tenantId ? [] : findTenantCandidates(row, tenants);
|
||||
return {
|
||||
row,
|
||||
candidates,
|
||||
defaultTenantId:
|
||||
candidates[0] && candidates[0].score >= 0.95
|
||||
? candidates[0].tenantId
|
||||
: "",
|
||||
};
|
||||
})
|
||||
.sort((a, b) => {
|
||||
const aScore = a.candidates[0]?.score ?? 0;
|
||||
const bScore = b.candidates[0]?.score ?? 0;
|
||||
if (bScore !== aScore) return bScore - aScore;
|
||||
return a.row.rowNumber - b.row.rowNumber;
|
||||
});
|
||||
}
|
||||
|
||||
export function serializeTenantImportCSV(
|
||||
previewRows: TenantImportPreviewRow[],
|
||||
selectedTenantIds: Record<number, string>,
|
||||
) {
|
||||
const lines = [importHeaders];
|
||||
for (const preview of [...previewRows].sort(
|
||||
(a, b) => a.row.rowNumber - b.row.rowNumber,
|
||||
)) {
|
||||
const selectedTenantId = selectedTenantIds[preview.row.rowNumber] ?? "";
|
||||
lines.push([
|
||||
preview.row.tenantId || selectedTenantId,
|
||||
preview.row.name,
|
||||
preview.row.type,
|
||||
preview.row.parentTenantId,
|
||||
preview.row.slug,
|
||||
preview.row.memo,
|
||||
preview.row.emailDomain,
|
||||
]);
|
||||
}
|
||||
return lines.map(formatCSVRecord).join("\n") + "\n";
|
||||
}
|
||||
|
||||
function findTenantCandidates(
|
||||
row: TenantCSVRow,
|
||||
tenants: TenantSummary[],
|
||||
): TenantImportCandidate[] {
|
||||
return tenants
|
||||
.map((tenant) => {
|
||||
const nameScore = similarity(row.name, tenant.name);
|
||||
const slugScore =
|
||||
normalizeToken(row.slug) &&
|
||||
normalizeToken(row.slug) === normalizeToken(tenant.slug)
|
||||
? 0.98
|
||||
: 0;
|
||||
const exactName =
|
||||
normalizeToken(row.name) === normalizeToken(tenant.name);
|
||||
const score = exactName ? 1 : Math.max(slugScore, nameScore);
|
||||
const reason: TenantImportCandidate["reason"] = exactName
|
||||
? "exact_name"
|
||||
: slugScore >= 0.98
|
||||
? "exact_slug"
|
||||
: "similar_name";
|
||||
return {
|
||||
tenantId: tenant.id,
|
||||
name: tenant.name,
|
||||
slug: tenant.slug,
|
||||
score,
|
||||
reason,
|
||||
};
|
||||
})
|
||||
.filter((candidate) => candidate.score >= 0.45)
|
||||
.sort((a, b) => b.score - a.score)
|
||||
.slice(0, 3);
|
||||
}
|
||||
|
||||
function parseCSV(text: string): string[][] {
|
||||
const rows: string[][] = [];
|
||||
let current = "";
|
||||
let row: string[] = [];
|
||||
let quoted = false;
|
||||
|
||||
for (let i = 0; i < text.length; i += 1) {
|
||||
const char = text[i];
|
||||
const next = text[i + 1];
|
||||
|
||||
if (char === '"' && quoted && next === '"') {
|
||||
current += '"';
|
||||
i += 1;
|
||||
continue;
|
||||
}
|
||||
if (char === '"') {
|
||||
quoted = !quoted;
|
||||
continue;
|
||||
}
|
||||
if (char === "," && !quoted) {
|
||||
row.push(current);
|
||||
current = "";
|
||||
continue;
|
||||
}
|
||||
if ((char === "\n" || char === "\r") && !quoted) {
|
||||
if (char === "\r" && next === "\n") i += 1;
|
||||
row.push(current);
|
||||
rows.push(row);
|
||||
row = [];
|
||||
current = "";
|
||||
continue;
|
||||
}
|
||||
current += char;
|
||||
}
|
||||
|
||||
if (current !== "" || row.length > 0) {
|
||||
row.push(current);
|
||||
rows.push(row);
|
||||
}
|
||||
|
||||
return rows;
|
||||
}
|
||||
|
||||
function formatCSVRecord(record: string[]) {
|
||||
return record
|
||||
.map((value) => {
|
||||
if (!/[",\r\n]/.test(value)) return value;
|
||||
return `"${value.replaceAll('"', '""')}"`;
|
||||
})
|
||||
.join(",");
|
||||
}
|
||||
|
||||
function normalizeHeader(value: string) {
|
||||
return value.trim().toLowerCase().replaceAll(" ", "_");
|
||||
}
|
||||
|
||||
function normalizeToken(value: string) {
|
||||
return value
|
||||
.trim()
|
||||
.toLowerCase()
|
||||
.replace(/[\s_-]+/g, "")
|
||||
.replace(/[^\p{L}\p{N}]/gu, "");
|
||||
}
|
||||
|
||||
function similarity(left: string, right: string) {
|
||||
const a = normalizeToken(left);
|
||||
const b = normalizeToken(right);
|
||||
if (!a || !b) return 0;
|
||||
if (a === b) return 1;
|
||||
if (a.includes(b) || b.includes(a)) {
|
||||
return Math.min(a.length, b.length) / Math.max(a.length, b.length);
|
||||
}
|
||||
|
||||
const distance = levenshtein(a, b);
|
||||
return 1 - distance / Math.max(a.length, b.length);
|
||||
}
|
||||
|
||||
function levenshtein(left: string, right: string) {
|
||||
const previous = Array.from({ length: right.length + 1 }, (_, i) => i);
|
||||
const current = Array.from({ length: right.length + 1 }, () => 0);
|
||||
|
||||
for (let i = 1; i <= left.length; i += 1) {
|
||||
current[0] = i;
|
||||
for (let j = 1; j <= right.length; j += 1) {
|
||||
const cost = left[i - 1] === right[j - 1] ? 0 : 1;
|
||||
current[j] = Math.min(
|
||||
current[j - 1] + 1,
|
||||
previous[j] + 1,
|
||||
previous[j - 1] + cost,
|
||||
);
|
||||
}
|
||||
previous.splice(0, previous.length, ...current);
|
||||
}
|
||||
|
||||
return previous[right.length];
|
||||
}
|
||||
Reference in New Issue
Block a user