Taehoon/ITAM
2
0
Fork 0
Code Issues 24 Pull Requests Actions Packages Projects Releases Wiki Activity

refactor: 프로젝트 정리 및 최적화 (미사용 파일 제거, 코드 중복 제거, 정적 이미지 빌드 경로 수정)

Browse Source 
- 미사용 목업 파일(dummyData.ts, realServerData.ts, server_data.json) 및 중복 기획서 제거

- excelHandler.ts 내 미사용 대용량 엑셀 처리 함수들을 삭제하여 xlsx 의존성 제거 및 클라이언트 빌드 크기 최적화

- ListFactory.ts와 utils.ts 간에 중복으로 존재하던 calculatePcScoreDeductive 함수를 하나로 일원화

- 기획서 및 계획 문서들을 docs/plans/ 하위 폴더로 이동하여 프로젝트 루트 정리

- 정적 이미지 폴더(img/)를 public/img/로 이동하여 프로덕션 빌드 시 로고 및 장비 사진 엑박 오류 해결
This commit is contained in:
이태훈
2026-06-19 15:12:25 +09:00
parent e8bc42e5de
commit af578a63bc
47 changed files with 2 additions and 13078 deletions
Download Patch File Download Diff File Expand all files Collapse all files

10695
src/core/dummyData.ts
View File

File diff suppressed because it is too large Load Diff

213
src/core/excelHandler.ts
View File

@@ -1,167 +1,7 @@
import * as XLSX from 'xlsx';
import { ASSET_SCHEMA } from './schema';
import { HardwareAsset, SoftwareAsset, SWUser, HardwareLog, MasterAssetData } from './types';
/**
* ITAM 엑셀 핸들러 (Database Synchronized Edition)
* 데이터베이스 실제 스키마 컬럼과 엑셀 헤더를 1:1로 일치시킵니다.
* ITAM 엑셀 핸들러 (지정 날짜 포맷팅 유틸리티)
*/
/**
* DB 컬럼 순서 및 구성 정의 (실제 DB 스키마 dump 기준)
*/
const DB_MAPPING: Record<string, (keyof typeof ASSET_SCHEMA)[]> = {
pc: [
'ASSET_TYPE', 'HW_STATUS', 'CURRENT_DEPT', 'PREV_DEPT', 'USER_POSITION',
'EMP_NO', 'CURRENT_USER',
'CPU', 'RAM', 'GPU', 'SSD1', 'SSD2', 'HDD1', 'HDD2', 'HDD3', 'HDD4', 'MAC_ADDR',
'MANAGER_MAIN', 'MANAGER_SUB', 'PURCHASE_CORP', 'PURCHASE_DATE', 'PURCHASE_AMOUNT',
'PURCHASE_VENDOR', 'MEMO', 'MAINBOARD'
],
server: [
'ASSET_TYPE', 'MODEL_NAME', 'ASSET_PURPOSE', 'HW_STATUS',
'CURRENT_DEPT', 'CPU', 'RAM', 'GPU', 'SSD1', 'SSD2', 'HDD1', 'HDD2', 'IP_ADDR',
'REMOTE_TOOL', 'REMOTE_ID', 'REMOTE_PW', 'LOCATION', 'LOC_DETAIL', 'MANAGER_MAIN',
'PURCHASE_CORP', 'PURCHASE_DATE', 'PURCHASE_AMOUNT', 'PURCHASE_VENDOR',
'MEMO', 'PREV_DEPT', 'MANAGER_SUB', 'IP_ADDR2', 'MONITORING', 'HDD3', 'HDD4', 'EMP_NO'
],
storage: [
'ASSET_TYPE', 'HW_STATUS', 'VOLUME', 'MODEL_NAME',
'EMP_NO', 'CURRENT_USER',
'SERIAL_NUM', 'LOCATION', 'LOC_DETAIL', 'MANAGER_MAIN', 'MANAGER_SUB',
'PURCHASE_CORP', 'PURCHASE_DATE', 'PURCHASE_AMOUNT', 'PURCHASE_VENDOR',
'MEMO', 'CURRENT_DEPT', 'PREV_DEPT'
],
network: [
'PURCHASE_CORP', 'HW_STATUS', 'CURRENT_DEPT', 'PREV_DEPT',
'EMP_NO', 'CURRENT_USER',
'ASSET_TYPE', 'ASSET_MFR', 'MODEL_NAME', 'LOCATION', 'LOC_DETAIL', 'MANAGER_MAIN',
'MANAGER_SUB', 'PURCHASE_DATE', 'PURCHASE_AMOUNT', 'PURCHASE_VENDOR', 'MEMO'
],
survey: [ // asset_survey (공간정보장비)
'HW_STATUS', 'ASSET_NAME', 'LOCATION', 'LOC_DETAIL',
'EMP_NO', 'CURRENT_USER',
'MANAGER_MAIN', 'MANAGER_SUB', 'PURCHASE_CORP', 'PURCHASE_DATE', 'PURCHASE_AMOUNT',
'PURCHASE_VENDOR', 'MEMO'
],
pcParts: [
'HW_STATUS', 'ASSET_TYPE', 'ASSET_MFR', 'MODEL_NAME', 'VOLUME',
'EMP_NO', 'CURRENT_USER',
'MONITOR_INCH', 'LOCATION', 'LOC_DETAIL', 'PURCHASE_CORP', 'PURCHASE_DATE',
'PURCHASE_AMOUNT', 'PURCHASE_VENDOR', 'MEMO'
],
equipment: [
'HW_STATUS', 'ASSET_STATUS', 'ASSET_TYPE', 'ASSET_MFR',
'EMP_NO', 'CURRENT_USER',
'MODEL_NAME', 'LOCATION', 'LOC_DETAIL', 'MANAGER_MAIN', 'MANAGER_SUB',
'PURCHASE_CORP', 'PURCHASE_DATE', 'PURCHASE_AMOUNT', 'PURCHASE_VENDOR',
'MEMO'
],
officeSupplies: [ // asset_office_supplies (시설자산)
'HW_STATUS', 'ASSET_TYPE', 'ASSET_MFR', 'MODEL_NAME',
'EMP_NO', 'CURRENT_USER',
'ASSET_COUNT', 'LOCATION', 'LOC_DETAIL', 'MANAGER_MAIN', 'MANAGER_SUB',
'PURCHASE_CORP', 'PURCHASE_DATE', 'PURCHASE_AMOUNT', 'PURCHASE_VENDOR',
'MEMO'
],
swInternal: [
'SW_FIELD', 'DEV_OBJ', 'SW_STATUS', 'SW_TYPE', 'MANAGER_MAIN',
'DEV_MGR', 'PLANNING_MGR', 'SALES_MGR', 'PURCHASE_CORP', 'MEMO'
],
swExternal: [
'PRODUCT_NAME', 'SW_TYPE', 'SW_STATUS', 'SW_FIELD', 'CURRENT_DEPT',
'PREV_DEPT', 'MANAGER_MAIN', 'PURCHASE_CORP', 'PURCHASE_DATE', 'PURCHASE_AMOUNT',
'PURCHASE_VENDOR', 'EMAIL_ACCOUNT', 'MEMO', 'EMP_NO', 'CURRENT_USER'
],
cloud: [
'ASSET_PURPOSE', 'PURCHASE_METHOD', 'PURCHASE_VENDOR', 'PURCHASE_CORP',
'PURCHASE_DATE', 'PURCHASE_AMOUNT', 'MANAGER_MAIN', 'MANAGER_SUB',
'MEMO', 'SW_ID', 'SW_PW'
],
domain: [
'DOMAIN_ADDR', 'ASSET_PURPOSE', 'PURCHASE_VENDOR', 'ASSET_TYPE',
'PURCHASE_CORP', 'PURCHASE_DATE', 'PURCHASE_AMOUNT', 'MANAGER_MAIN', 'MANAGER_SUB',
'MEMO'
],
cost: [
'ASSET_TYPE', 'ASSET_PURPOSE', 'LOCATION', 'LOC_DETAIL', 'MANAGER_MAIN',
'MANAGER_SUB', 'PURCHASE_CORP', 'PURCHASE_DATE', 'PURCHASE_AMOUNT', 'PURCHASE_VENDOR',
'EMAIL_ACCOUNT', 'EMAIL_PW', 'MEMO', 'EMP_NO', 'CURRENT_USER'
],
vip: [ // asset_vip (선물)
'ASSET_NAME', 'MODEL_NAME', 'LOCATION', 'LOC_DETAIL',
'PURCHASE_CORP', 'PURCHASE_DATE', 'EXPIRED_DATE', 'PURCHASE_VENDOR', 'MEMO'
]
};
export function downloadTemplate() {
const wb = XLSX.utils.book_new();
const tabConfigs = [
{ name: 'PC', key: 'pc' },
{ name: '서버', key: 'server' },
{ name: '스토리지', key: 'storage' },
{ name: '공간정보장비', key: 'survey' },
{ name: 'PC부품', key: 'pcParts' },
{ name: '네트워크', key: 'network' },
{ name: '업무지원장비', key: 'equipment' },
{ name: '내부SW', key: 'swInternal' },
{ name: '외부SW', key: 'swExternal' },
{ name: '클라우드', key: 'cloud' },
{ name: '도메인', key: 'domain' },
{ name: '비용관리', key: 'cost' },
{ name: '선물', key: 'vip' },
{ name: '시설자산', key: 'officeSupplies' }
];
tabConfigs.forEach(config => {
const keys = DB_MAPPING[config.key];
const headers = keys.map(k => ASSET_SCHEMA[k].ui);
const ws = XLSX.utils.aoa_to_sheet([headers]);
ws['!cols'] = Array(headers.length).fill({ wch: 20 });
XLSX.utils.book_append_sheet(wb, ws, config.name);
});
XLSX.writeFile(wb, 'itam_template_db_aligned.xlsx');
}
export function exportToExcel(masterData: MasterAssetData) {
const wb = XLSX.utils.book_new();
const exportConfigs = [
{ name: 'PC', list: masterData.pc, key: 'pc' },
{ name: '서버', list: masterData.server, key: 'server' },
{ name: '스토리지', list: masterData.storage, key: 'storage' },
{ name: '공간정보장비', list: masterData.survey || [], key: 'survey' },
{ name: 'PC부품', list: masterData.pcParts || [], key: 'pcParts' },
{ name: '네트워크', list: masterData.network || [], key: 'network' },
{ name: '업무지원장비', list: masterData.equipment || [], key: 'equipment' },
{ name: '내부SW', list: masterData.swInternal, key: 'swInternal' },
{ name: '외부SW', list: masterData.swExternal, key: 'swExternal' },
{ name: '클라우드', list: masterData.cloud || [], key: 'cloud' },
{ name: '도메인', list: masterData.domain || [], key: 'domain' },
{ name: '비용관리', list: masterData.cost || [], key: 'cost' },
{ name: '선물', list: masterData.vip || [], key: 'vip' },
{ name: '시설자산', list: masterData.officeSupplies || [], key: 'officeSupplies' }
];
exportConfigs.forEach(config => {
const schemaKeys = DB_MAPPING[config.key];
const headers = schemaKeys.map(k => ASSET_SCHEMA[k].ui);
const rows = config.list.map(asset =>
schemaKeys.map(k => {
const dbField = ASSET_SCHEMA[k].db;
return asset[dbField] || asset[ASSET_SCHEMA[k].key] || '';
})
);
const ws = XLSX.utils.aoa_to_sheet([headers, ...rows]);
XLSX.utils.book_append_sheet(wb, ws, config.name);
});
XLSX.writeFile(wb, `itam_export_${new Date().toISOString().split('T')[0]}.xlsx`);
}
export function formatExcelDate(val: any): string {
if (!val) return '';
if (typeof val === 'number') {
@@ -173,54 +13,3 @@ export function formatExcelDate(val: any): string {
}
return String(val);
}
export async function parseExcel(file: File): Promise<any> {
return new Promise((resolve, reject) => {
const reader = new FileReader();
reader.onload = (e) => {
try {
const workbook = XLSX.read(e.target?.result, { type: 'array' });
const parsedData: any = {};
workbook.SheetNames.forEach(sheetName => {
const ws = workbook.Sheets[sheetName];
const rows = XLSX.utils.sheet_to_json(ws, { defval: "" }) as any[];
const list: any[] = [];
rows.forEach(r => {
const data: any = { id: Math.random().toString(36).substring(2, 9) };
// Set default category based on sheet name
data['category'] = sheetName;
Object.keys(r).forEach(label => {
const schemaEntry = Object.values(ASSET_SCHEMA).find(s => s.ui === label);
const key = schemaEntry ? schemaEntry.db : label;
let val = r[label];
if (label.includes('일자') || label.includes('연월') || label.includes('만료일') || label.includes('시작일')) {
val = formatExcelDate(val);
}
data[key] = val;
});
list.push(data);
});
// Sheet Name Mapping back to state keys
const nameMap: Record<string, string> = {
'PC': 'pc', '서버': 'server', '스토리지': 'storage', '공간정보장비': 'survey',
'PC부품': 'pcParts', '네트워크': 'network', '업무지원장비': 'equipment',
'내부SW': 'swInternal', '외부SW': 'swExternal', '클라우드': 'cloud',
'도메인': 'domain', '비용관리': 'cost', '선물': 'vip', '시설자산': 'officeSupplies'
};
const stateKey = nameMap[sheetName] || sheetName;
if (list.length > 0) parsedData[stateKey] = list;
});
resolve(parsedData);
} catch (err) { reject(err); }
};
reader.readAsArrayBuffer(file);
});
}

1603
src/core/realServerData.ts
View File

File diff suppressed because it is too large Load Diff

1
src/core/state.ts
View File

@@ -1,6 +1,5 @@
import { HardwareAsset, SoftwareAsset, SWUser, HardwareLog, MasterAssetData, SystemUser } from './types';
import { API_BASE_URL } from './utils';
import { dummyPCs, dummyServers, dummyStorages, dummyEquips, dummySubSw, dummyPermSw, dummyCloud, dummyDomain, dummySwUsers, dummyLogs } from './dummyData';
// --- State Definitions ---
export interface AppState {

13
src/server_data.json
View File

@@ -1,13 +0,0 @@
[
{
"법인": "(주)회사1",
"자산코드": "ASSET-100",
"명칭": "서버 모델A",
"위치": "본사 1층",
"관리자": "관리자A",
"IP주소": "192.168.0.1",
"MACaddress": "00:00:00:00:00:01",
"HW사양": "Core i7, 16GB RAM",
"OS": "Windows 10"
}
]

126
src/views/List/ListFactory.ts
View File

@@ -1,5 +1,5 @@
import { ASSET_SCHEMA, UI_TEXT } from '../../core/schema';
import { dynamicSort, renderPageHeader, calculateAssetAge, formatInline, isWindows11Incompatible } from '../../core/utils';
import { dynamicSort, renderPageHeader, calculateAssetAge, formatInline, isWindows11Incompatible, calculatePcScoreDeductive } from '../../core/utils';
import { setupTableSorting, SortState } from '../../core/tableHandler';
import { renderFilterBar, applyCommonFilters } from '../../core/filterHandler';
import { state } from '../../core/state';
@@ -9,130 +9,6 @@ import './table.css';
declare var Chart: any;
let pcFlowChartInstance: any = null;
// ─── 100점 만점 감점형 성능 점수 계산 (CPU + RAM + GPU + 연식) ───
function calculatePcScoreDeductive(cpu: string, ram: string, gpu: string, purchaseDate: string): number {
let score = 100;
if (!cpu) cpu = '';
if (!ram) ram = '';
if (!gpu) gpu = '';
const cpuUpper = cpu.toUpperCase();
const ramUpper = ram.toUpperCase();
const gpuUpper = gpu.toUpperCase();
// 1. CPU 등급 감점 (최대 -30점)
let cpuDeduction = 0;
if (cpuUpper.includes('I9') || cpuUpper.includes('RYZEN 9') || cpuUpper.includes('RYZEN9')) {
cpuDeduction = 0;
} else if (cpuUpper.includes('I7') || cpuUpper.includes('RYZEN 7') || cpuUpper.includes('RYZEN7')) {
cpuDeduction = 5;
} else if (cpuUpper.includes('I5') || cpuUpper.includes('RYZEN 5') || cpuUpper.includes('RYZEN5')) {
cpuDeduction = 15;
} else if (cpuUpper.includes('I3') || cpuUpper.includes('RYZEN 3') || cpuUpper.includes('RYZEN3')) {
cpuDeduction = 25;
} else {
cpuDeduction = 30;
}
score -= cpuDeduction;
// 2. CPU 세대 노후 감점 (최대 -15점)
let genDeduction = 0;
const intelMatch = cpuUpper.match(/I\d-?(\d+)/);
let gen = 0;
if (intelMatch && intelMatch[1]) {
const numStr = intelMatch[1];
if (numStr.length === 5) gen = parseInt(numStr.substring(0, 2), 10);
else if (numStr.length === 4) gen = parseInt(numStr.substring(0, 1), 10);
}
const amdMatch = cpuUpper.match(/RYZEN\s?\d\s?-?(\d+)/);
let amdGen = 0;
if (amdMatch && amdMatch[1] && !intelMatch) {
const numStr = amdMatch[1];
if (numStr.length === 4) amdGen = parseInt(numStr.substring(0, 1), 10);
}
if (intelMatch) {
if (gen >= 12) genDeduction = 0;
else if (gen >= 10) genDeduction = 5;
else if (gen >= 8) genDeduction = 10;
else genDeduction = 15;
} else if (amdMatch) {
if (amdGen >= 5) genDeduction = 0;
else if (amdGen >= 3) genDeduction = 5;
else genDeduction = 10;
} else {
genDeduction = 15;
}
score -= genDeduction;
// 3. RAM 용량 감점 (최대 -25점)
const ramMatch = ramUpper.match(/(\d+)\s*GB/);
let ramDeduction = 25;
if (ramMatch && ramMatch[1]) {
const ramVal = parseInt(ramMatch[1], 10);
if (ramVal >= 32) ramDeduction = 0;
else if (ramVal >= 16) ramDeduction = 10;
else if (ramVal >= 8) ramDeduction = 20;
else ramDeduction = 25;
}
score -= ramDeduction;
// 4. GPU 성능 감점 (최대 -25점)
let gpuDeduction = 25;
if (!gpuUpper || gpuUpper === '-' || gpuUpper.trim() === '') {
gpuDeduction = 25;
} else if (
gpuUpper.includes('RTX 4090') || gpuUpper.includes('RTX 4080') || gpuUpper.includes('RTX 4070') ||
gpuUpper.includes('RTX 3090') || gpuUpper.includes('RTX 3080') ||
gpuUpper.includes('RTX A5000') || gpuUpper.includes('RTX A6000') || gpuUpper.includes('RTX A4000')
) {
gpuDeduction = 0;
} else if (
gpuUpper.includes('RTX 3070') || gpuUpper.includes('RTX 3060') || gpuUpper.includes('RTX 2060') ||
gpuUpper.includes('RTX A2000') || gpuUpper.includes('RTX A3000') || gpuUpper.includes('QUADRO')
) {
gpuDeduction = 5;
} else if (
gpuUpper.includes('GTX 1660') || gpuUpper.includes('GTX 1080') || gpuUpper.includes('GTX 1070') ||
gpuUpper.includes('GTX 1060') || gpuUpper.includes('RX 6700') || gpuUpper.includes('RX 6600')
) {
gpuDeduction = 15;
} else {
gpuDeduction = 25;
}
score -= gpuDeduction;
// 5. 연식(노후도) 감점 (최대 -15점)
let age = 0;
if (purchaseDate && purchaseDate !== '-') {
let normalized = purchaseDate.replace(/\./g, '-').trim();
if (/^\d{6}$/.test(normalized)) {
normalized = `${normalized.substring(0, 4)}-${normalized.substring(4, 6)}`;
}
const purchase = new Date(normalized);
if (!isNaN(purchase.getTime())) {
// 2026년 5월 31일 기준 경과연수 계산
const mockToday = new Date('2026-05-31');
const diffMs = mockToday.getTime() - purchase.getTime();
age = diffMs / (1000 * 60 * 60 * 24 * 365.25);
age = Math.max(0, parseFloat(age.toFixed(1)));
}
}
let ageDeduction = 0;
if (age < 1) ageDeduction = 0;
else if (age < 2) ageDeduction = 3;
else if (age < 3) ageDeduction = 6;
else if (age < 4) ageDeduction = 9;
else if (age < 5) ageDeduction = 12;
else ageDeduction = 15;
score -= ageDeduction;
return Math.max(10, score);
}
export interface ColumnDef {
header: string;
sortKey?: string;