feat: 新增機台稼動歷史分析功能
新增 Resource History Analysis 功能模組： - 後端服務：query_summary、query_detail、export_csv 查詢函數 - API 路由：/api/resource/history/* 端點 (options/summary/detail/export) - 前端頁面：KPI 卡片、OU% 趨勢圖、E10 狀態堆疊圖、熱力圖、階層式表格 - 支援時間粒度切換（日/週/月/年）與多維度篩選 - 查詢範圍擴展至 730 天（兩年） 其他改進： - 新增 filter_cache 服務統一管理工站與型號快取 - MesApi 修復 JSON 解析失敗時誤觸重試的問題 - 新增 _safe_float() 處理 NaN 值避免 JSON 序列化錯誤 - E10 狀態分布圖表 tooltip 顯示各狀態百分比 - 新增完整測試套件（單元/整合/E2E） Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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claude.md
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claude.md
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# MES Dashboard - Claude Code Instructions
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## Project Overview
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MES Dashboard 是一個工廠製造執行系統的儀表板應用，使用 Flask + Oracle 資料庫 + ECharts 前端圖表。
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## Before Starting Any Task
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1. **Review architecture documentation**: Read `docs/architecture_findings.md` to understand:
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- Database connection management patterns
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- Caching mechanisms and TTL constants
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- Filter cache (workcenter/family) usage
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- Frontend global components (Toast, MesApi)
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- Data table filtering rules and column mappings
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- E10 status definitions and OU% calculation
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- Testing conventions
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## When Making Changes
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If any of the following patterns are modified or new patterns are discovered:
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- Database connection or pooling approach
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- Caching strategy or TTL values
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- Global frontend components usage
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- Data table column names or filtering rules
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- New shared utilities or services
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- Testing conventions or setup patterns
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**Update `docs/architecture_findings.md`** to reflect the changes.
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## Key Architecture Rules
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### Database
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- Always use `mes_dashboard.core.database.read_sql_df()` for queries
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- Never create direct connections in services
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- Reset `db._ENGINE = None` in test setUp
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### Caching
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- Use `mes_dashboard.core.cache` for all caching operations
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- Use `mes_dashboard.services.filter_cache` for workcenter/family lookups
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- Always convert WORKCENTERNAME → WORKCENTER_GROUP for display
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### Frontend
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- Toast notifications: Use `Toast.warning()`, `Toast.error()`, `Toast.success()` (NOT MESToast)
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- API calls: Use `MesApi.get()` with proper timeout
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- Array operations: Remember `.reverse()` modifies in-place
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### Data Tables
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- DW_MES_RESOURCE: Use `PJ_ASSETSSTATUS` (not ASSETSTATUS), `LOCATIONNAME` (not LOCATION)
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- DW_MES_RESOURCESTATUS_SHIFT: HISTORYID maps to RESOURCEID
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- DW_PJ_LOT_V: Source for WORKCENTER_GROUP mapping
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### SQL
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- Use `/*+ MATERIALIZE */` hint for Oracle CTEs used multiple times
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- Date range: `TXNDATE >= start AND TXNDATE < end + 1`
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- Apply EQUIPMENT_TYPE_FILTER, location exclusions, asset status exclusions
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## Testing
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- Unit tests: `tests/test_*_service.py`
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- Integration tests: `tests/test_*_routes.py`
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- E2E tests: `tests/e2e/test_*_e2e.py`
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- For parallel queries (ThreadPoolExecutor), mock with function-based side_effect, not list
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docs/architecture_findings.md
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docs/architecture_findings.md
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# MES Dashboard - Architecture Findings
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本文件記錄專案開發過程中確立的架構設計、全局規範與資料處理規則。
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---
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## 1. 資料庫連線管理
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### 連線池統一使用
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所有資料庫操作必須透過 `mes_dashboard.core.database` 模組：
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```python
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from mes_dashboard.core.database import read_sql_df, get_engine
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# 讀取資料
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df = read_sql_df(sql)
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# 取得 engine（若需要直接操作）
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engine = get_engine()
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```
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### 注意事項
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- **禁止**在各 service 中自行建立連線
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- 連線池由 `database.py` 統一管理，避免連線洩漏
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- 測試環境需在 setUp 中重置：`db._ENGINE = None`
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---
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## 2. 快取機制
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### 全局快取 API
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使用 `mes_dashboard.core.cache` 模組：
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```python
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from mes_dashboard.core.cache import cache_get, cache_set, make_cache_key
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# 建立快取 key（支援 filters dict）
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cache_key = make_cache_key("resource_history_summary", filters={
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'start_date': start_date,
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'workcenter_groups': sorted(groups) if groups else None,
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})
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# 讀取/寫入快取
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result = cache_get(cache_key)
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if result is None:
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result = query_data()
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cache_set(cache_key, result, ttl=CACHE_TTL_TREND)
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```
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### 快取 TTL 常數
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定義於 `mes_dashboard.config.constants`：
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- `CACHE_TTL_FILTER_OPTIONS`: 篩選選項（較長）
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- `CACHE_TTL_TREND`: 趨勢資料（中等）
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- `CACHE_TTL_REALTIME`: 即時資料（較短）
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---
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## 3. Filter Cache（篩選選項快取）
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### 位置
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`mes_dashboard.services.filter_cache`
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### 用途
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快取全站共用的篩選選項，避免重複查詢資料庫：
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```python
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from mes_dashboard.services.filter_cache import (
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get_workcenter_groups, # 取得 workcenter group 列表
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get_workcenter_mapping, # 取得 workcentername → group 對應
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get_workcenters_for_groups, # 根據 group 取得 workcentername 列表
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get_resource_families, # 取得 resource family 列表
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)
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```
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### Workcenter 對應關係
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```
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WORKCENTERNAME (資料庫) → WORKCENTER_GROUP (顯示)
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焊接_DB_1 → 焊接_DB
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焊接_DB_2 → 焊接_DB
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成型_1 → 成型
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```
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### 資料來源
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- Workcenter Groups: `DW_PJ_LOT_V` (WORKCENTER_GROUP, WORKCENTERSEQUENCE_GROUP)
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- Resource Families: `DW_MES_RESOURCE` (RESOURCEFAMILYNAME)
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---
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## 4. 前端全局組件
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### Toast 通知
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定義於 `static/js/toast.js`，透過 `_base.html` 載入：
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```javascript
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// 正確用法
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Toast.info('訊息');
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Toast.success('成功');
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Toast.warning('警告');
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Toast.error('錯誤');
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Toast.loading('載入中...');
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// 錯誤用法（不存在）
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MESToast.warning('...'); // ❌ 錯誤
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```
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### MesApi（HTTP 請求）
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定義於 `static/js/api.js`，提供統一的 API 呼叫介面：
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```javascript
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const result = await MesApi.get('/api/endpoint', { timeout: 30000 });
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if (result.success) {
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// 處理資料
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} else {
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Toast.error(result.error);
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}
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```
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---
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## 5. 資料表預篩選規則
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### 設備類型篩選
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定義於 `mes_dashboard.config.constants.EQUIPMENT_TYPE_FILTER`：
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```sql
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-- 只查詢特定設備類型
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r.EQUIPMENTTYPE IN ('主要設備', '輔助設備')
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```
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### 排除條件
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```python
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# 排除的地點
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EXCLUDED_LOCATIONS = ['TEST', 'LAB', ...]
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# 排除的資產狀態
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EXCLUDED_ASSET_STATUSES = ['報廢', '停用', ...]
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```
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### SQL 範例
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```python
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# 建立篩選條件
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location_filter = _build_location_filter('r')
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# → AND (r.LOCATIONNAME IS NULL OR r.LOCATIONNAME NOT IN ('TEST', 'LAB'))
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asset_status_filter = _build_asset_status_filter('r')
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# → AND r.PJ_ASSETSSTATUS NOT IN ('報廢', '停用')
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```
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---
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## 6. 資料庫欄位對應
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### DW_MES_RESOURCE
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| 常見錯誤 | 正確欄位名 |
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|---------|-----------|
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| ASSETSTATUS | PJ_ASSETSSTATUS（雙 S）|
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| LOCATION | LOCATIONNAME |
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| ISPRODUCTION | PJ_ISPRODUCTION |
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| ISKEY | PJ_ISKEY |
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| ISMONITOR | PJ_ISMONITOR |
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### DW_MES_RESOURCESTATUS_SHIFT
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| 欄位 | 說明 |
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|-----|------|
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| HISTORYID | 對應 DW_MES_RESOURCE.RESOURCEID |
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| TXNDATE | 交易日期 |
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| OLDSTATUSNAME | E10 狀態 (PRD, SBY, UDT, SDT, EGT, NST) |
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| HOURS | 該狀態時數 |
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### DW_PJ_LOT_V
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| 欄位 | 說明 |
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|-----|------|
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| WORKCENTERNAME | 站點名稱（細分）|
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| WORKCENTER_GROUP | 站點群組（顯示用）|
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| WORKCENTERSEQUENCE_GROUP | 群組排序 |
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---
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## 7. E10 狀態定義
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| 狀態 | 說明 | 計入 OU% |
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|-----|------|---------|
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| PRD | Production（生產）| 是（分子）|
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| SBY | Standby（待機）| 是（分母）|
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| UDT | Unscheduled Downtime（非計畫停機）| 是（分母）|
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| SDT | Scheduled Downtime（計畫停機）| 是（分母）|
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| EGT | Engineering Time（工程時間）| 是（分母）|
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| NST | Non-Scheduled Time（非排程時間）| 否 |
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### OU% 計算公式
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```
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OU% = PRD / (PRD + SBY + UDT + SDT + EGT) × 100
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```
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---
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## 8. 平行查詢
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### ThreadPoolExecutor
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對於多個獨立查詢，使用平行執行提升效能：
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```python
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from concurrent.futures import ThreadPoolExecutor, as_completed
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with ThreadPoolExecutor(max_workers=4) as executor:
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futures = {
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executor.submit(read_sql_df, kpi_sql): 'kpi',
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executor.submit(read_sql_df, trend_sql): 'trend',
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executor.submit(read_sql_df, heatmap_sql): 'heatmap',
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executor.submit(read_sql_df, comparison_sql): 'comparison',
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}
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for future in as_completed(futures):
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query_name = futures[future]
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results[query_name] = future.result()
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```
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### 注意事項
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- Mock 測試時不能使用 `side_effect` 列表（順序不可預測）
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- 應使用函式判斷 SQL 內容來回傳對應的 mock 資料
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---
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## 9. Oracle SQL 優化
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### CTE MATERIALIZE Hint
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防止 Oracle 優化器將 CTE inline 多次執行：
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```sql
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WITH shift_data AS (
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SELECT /*+ MATERIALIZE */ HISTORYID, TXNDATE, OLDSTATUSNAME, HOURS
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FROM DW_MES_RESOURCESTATUS_SHIFT
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WHERE TXNDATE >= TO_DATE('2024-01-01', 'YYYY-MM-DD')
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AND TXNDATE < TO_DATE('2024-01-07', 'YYYY-MM-DD') + 1
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)
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SELECT ...
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```
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### 日期範圍查詢
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```sql
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-- 包含 end_date 當天
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WHERE TXNDATE >= TO_DATE('{start_date}', 'YYYY-MM-DD')
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AND TXNDATE < TO_DATE('{end_date}', 'YYYY-MM-DD') + 1
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```
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---
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## 10. 前端資料限制
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### 明細資料上限
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為避免瀏覽器記憶體問題，明細查詢有筆數限制：
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```python
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MAX_DETAIL_RECORDS = 5000
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if total > MAX_DETAIL_RECORDS:
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df = df.head(MAX_DETAIL_RECORDS)
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truncated = True
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```
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前端顯示警告：
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```javascript
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if (result.truncated) {
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Toast.warning(`資料超過 ${result.max_records} 筆，請使用篩選條件縮小範圍。`);
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}
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```
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---
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## 11. JavaScript 注意事項
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### Array.reverse() 原地修改
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```javascript
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// 錯誤 - 原地修改陣列
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const arr = [1, 2, 3];
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arr.reverse(); // arr 被修改為 [3, 2, 1]
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// 正確 - 建立新陣列
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const reversed = arr.slice().reverse(); // arr 不變
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// 或
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const reversed = [...arr].reverse();
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```
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||||
---
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## 12. 測試規範
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### 測試檔案結構
|
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```
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tests/
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├── test_*_service.py # 單元測試（service layer）
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├── test_*_routes.py # 整合測試（API endpoints）
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└── e2e/
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└── test_*_e2e.py # 端對端測試（完整流程）
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```
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### 測試前重置
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```python
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def setUp(self):
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db._ENGINE = None # 重置連線池
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self.app = create_app('testing')
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```
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### 執行測試
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```bash
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# 單一模組
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pytest tests/test_resource_history_service.py -v
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# 全部相關測試
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pytest tests/test_resource_history_*.py tests/e2e/test_resource_history_e2e.py -v
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```
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@@ -0,0 +1,177 @@
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## Context
|
||||
|
||||
目前系統的 /resource 頁面混合即時與歷史資料展示，歷史分析功能受限於現有架構。資料來源為：
|
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|
||||
- **DW_MES_RESOURCESTATUS_SHIFT**：班次級狀態彙總表（約 74M 筆），包含 HOURS 欄位可直接計算各狀態工時
|
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- **DW_MES_RESOURCE**：機台維度資料（約 90K 筆），包含 WORKCENTERNAME、RESOURCEFAMILYNAME、RESOURCENAME 等維度
|
||||
|
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現有 `dashboard_service.py` 已有 `query_ou_trend()` 和 `query_utilization_heatmap()` 函數可參考，使用相同的 OU% 計算公式：`PRD / (PRD + SBY + EGT + SDT + UDT) * 100`
|
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|
||||
## Goals / Non-Goals
|
||||
|
||||
**Goals:**
|
||||
|
||||
- 建立獨立的歷史分析頁面，支援多維度、多時間粒度的機台效能分析
|
||||
- 實現三層階層式下鑽：站點 → 型號 → 個別機台
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- 提供完整的 SEMI E10 設備狀態分析（時數 + 佔比）
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||||
- 支援日/週/月/年的時間粒度切換
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||||
- 採用查詢觸發模式，避免頁面載入時的效能衝擊
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||||
|
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**Non-Goals:**
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|
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- 不修改現有 /resource 頁面的即時機況功能（僅移除歷史圖表）
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||||
- 不實作即時資料推送或自動刷新
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||||
- 不整合其他資料來源（如 SECS/GEM 設備訊號）
|
||||
- 不實作機台詳細事件時間軸（甘特圖）—— 可作為後續擴充
|
||||
|
||||
## Decisions
|
||||
|
||||
### 1. 頁面架構：完全獨立頁面
|
||||
|
||||
**決定**：建立 `/resource-history` 作為完全獨立的頁面
|
||||
|
||||
**替代方案**：
|
||||
- (A) 在 /resource 頁面新增 Tab 切換 → 會增加頁面複雜度，且兩者篩選條件不同
|
||||
- (B) 子路由 `/resource/history` → 與現有 /resource 頁面產生關聯，不符合獨立需求
|
||||
|
||||
**理由**：完全獨立的頁面便於維護，不影響現有 /resource 即時機況功能。
|
||||
|
||||
### 2. 資料服務：獨立 Service 模組
|
||||
|
||||
**決定**：建立 `resource_history_service.py` 獨立模組
|
||||
|
||||
**替代方案**：
|
||||
- (A) 擴展現有 `resource_service.py` → 會使檔案過大且職責混淆
|
||||
- (B) 擴展 `dashboard_service.py` → 該模組已有多個功能，不適合再擴展
|
||||
|
||||
**理由**：單一職責原則，便於維護與測試。可重用 `dashboard_service.py` 中的 OU 計算邏輯。
|
||||
|
||||
### 3. 時間粒度處理：SQL 層聚合
|
||||
|
||||
**決定**：在 SQL 查詢中使用 `TRUNC()` 進行時間聚合
|
||||
|
||||
```sql
|
||||
-- 日：TRUNC(TXNDATE)
|
||||
-- 週：TRUNC(TXNDATE, 'IW') -- ISO week
|
||||
-- 月：TRUNC(TXNDATE, 'MM')
|
||||
-- 年：TRUNC(TXNDATE, 'YYYY')
|
||||
```
|
||||
|
||||
**替代方案**：
|
||||
- (A) Python 層聚合 → 需拉取更多資料，效能差
|
||||
- (B) 預計算彙總表 → 需額外 ETL 流程，增加維護成本
|
||||
|
||||
**理由**：利用 Oracle 原生函數在資料庫層高效聚合，減少網路傳輸。
|
||||
|
||||
### 4. 階層式資料結構：單次查詢 + 前端組裝
|
||||
|
||||
**決定**：後端回傳扁平化資料，包含 WORKCENTERNAME、RESOURCEFAMILYNAME、RESOURCENAME 三個維度欄位，前端根據需要進行階層組裝
|
||||
|
||||
**替代方案**：
|
||||
- (A) 後端回傳巢狀 JSON → 結構複雜，不利於匯出
|
||||
- (B) 三次獨立查詢（各層級） → 網路請求多，延遲增加
|
||||
|
||||
**理由**：單次查詢減少延遲，扁平結構便於表格渲染與匯出，前端可靈活控制展開/收合邏輯。
|
||||
|
||||
### 5. 圖表實作：ECharts
|
||||
|
||||
**決定**：沿用現有 ECharts 套件
|
||||
|
||||
**理由**：與現有頁面一致，減少學習成本和套件依賴。已有 OU 趨勢圖和熱力圖的實作可參考。
|
||||
|
||||
### 6. 匯出功能：CSV 格式
|
||||
|
||||
**決定**：提供 CSV 匯出，由後端生成
|
||||
|
||||
**替代方案**：
|
||||
- (A) Excel 格式 → 需額外套件（openpyxl），增加依賴
|
||||
- (B) 前端匯出 → 資料量大時效能問題
|
||||
|
||||
**理由**：CSV 輕量且通用，後端處理可支援大量資料。
|
||||
|
||||
## Risks / Trade-offs
|
||||
|
||||
| 風險 | 影響 | 緩解措施 |
|
||||
|------|------|----------|
|
||||
| 大量資料查詢效能 | 74M 筆資料表的聚合查詢可能緩慢 | 強制要求日期範圍限制（最多 1 年）；使用 TXNDATE 索引；考慮查詢超時設定 |
|
||||
| 前端渲染效能 | 大量機台明細可能導致表格卡頓 | 實作分頁或虛擬捲動；限制單次回傳筆數（如 1000 筆） |
|
||||
| 記憶體使用 | pandas DataFrame 處理大量資料 | 使用 chunked 讀取或直接串流輸出 |
|
||||
| 使用者誤操作 | 選擇過長時間範圍導致查詢卡住 | 前端驗證時間範圍；顯示預估資料量警告 |
|
||||
|
||||
## API 設計
|
||||
|
||||
### 主要 API 端點
|
||||
|
||||
```
|
||||
GET /api/resource/history/summary
|
||||
?start_date=2024-01-01
|
||||
&end_date=2024-01-31
|
||||
&granularity=day|week|month|year
|
||||
&workcenter=WC01 (optional)
|
||||
&family=FAM01 (optional)
|
||||
&is_production=1 (optional)
|
||||
&is_key=1 (optional)
|
||||
|
||||
Response: {
|
||||
kpi: { ou_pct, prd_hours, sby_hours, udt_hours, sdt_hours, egt_hours, nst_hours, machine_count },
|
||||
trend: [{ date, ou_pct, prd_hours, ... }],
|
||||
heatmap: [{ workcenter, date, ou_pct }],
|
||||
workcenter_comparison: [{ workcenter, ou_pct, prd_hours, ... }]
|
||||
}
|
||||
|
||||
GET /api/resource/history/detail
|
||||
?start_date=2024-01-01
|
||||
&end_date=2024-01-31
|
||||
&granularity=day|week|month|year
|
||||
&workcenter=WC01 (optional)
|
||||
&family=FAM01 (optional)
|
||||
&page=1
|
||||
&page_size=100
|
||||
|
||||
Response: {
|
||||
data: [{ workcenter, family, resource, ou_pct, prd_hours, prd_pct, sby_hours, sby_pct, ... }],
|
||||
total: 1234,
|
||||
page: 1,
|
||||
page_size: 100
|
||||
}
|
||||
|
||||
GET /api/resource/history/export
|
||||
?start_date=2024-01-01
|
||||
&end_date=2024-01-31
|
||||
&granularity=day
|
||||
&format=csv
|
||||
|
||||
Response: CSV file download
|
||||
```
|
||||
|
||||
## 前端元件結構
|
||||
|
||||
```
|
||||
resource_history.html
|
||||
├── Filter Bar
|
||||
│ ├── Date Range Picker (start_date, end_date)
|
||||
│ ├── Granularity Buttons (日/週/月/年)
|
||||
│ ├── Workcenter Select (多選)
|
||||
│ ├── Family Select (多選)
|
||||
│ ├── Checkbox Filters (生產機/關鍵機/監控機)
|
||||
│ └── Query Button
|
||||
├── KPI Cards Row
|
||||
│ ├── OU% Card
|
||||
│ ├── PRD Hours Card
|
||||
│ ├── UDT Hours Card
|
||||
│ ├── SDT Hours Card
|
||||
│ ├── EGT Hours Card
|
||||
│ └── Machine Count Card
|
||||
├── Charts Row 1
|
||||
│ ├── OU% Trend Line Chart
|
||||
│ └── E10 Stacked Bar Chart
|
||||
├── Charts Row 2
|
||||
│ ├── Workcenter Comparison Bar Chart
|
||||
│ └── Utilization Heatmap
|
||||
└── Detail Table
|
||||
├── Toolbar (Export, Expand All)
|
||||
└── Hierarchical Table
|
||||
├── Workcenter Level (expandable)
|
||||
│ ├── Family Level (expandable)
|
||||
│ │ └── Resource Level
|
||||
```
|
||||
@@ -0,0 +1,65 @@
|
||||
## Why
|
||||
|
||||
目前缺乏機台歷史效能的深度分析工具。使用者需要：
|
||||
|
||||
- 分析各站點、各型號的歷史稼動率趨勢
|
||||
- 了解 SEMI E10 設備狀態（PRD、SBY、UDT、SDT、EGT、NST）的時間分布
|
||||
- 支援日/週/月/年等多時間粒度的效能分析
|
||||
- 從站點下鑽至型號、再到個別機台的詳細數據
|
||||
|
||||
## What Changes
|
||||
|
||||
### 新增機台歷史表現分析頁面
|
||||
|
||||
建立完全獨立的歷史分析頁面 `/resource-history`，提供：
|
||||
|
||||
1. **篩選條件區**
|
||||
- 日期範圍選擇器
|
||||
- 時間粒度切換（日/週/月/年）
|
||||
- 站點（Workcenter）下拉選單
|
||||
- 機台型號（Resource Family）下拉選單
|
||||
- 查詢按鈕（預設不載入資料，需使用者主動觸發）
|
||||
|
||||
2. **KPI 摘要卡片**
|
||||
- OU%（整體稼動率）
|
||||
- PRD 時數（生產時間）
|
||||
- UDT/SDT/EGT 時數（各類停機時間）
|
||||
- 機台數量
|
||||
|
||||
3. **分析圖表**
|
||||
- OU% 趨勢折線圖（含時間軸）
|
||||
- E10 狀態堆疊長條圖（各狀態時數分布）
|
||||
- 工站 OU% 對比水平條形圖
|
||||
- 設備狀態熱力圖（站點 × 時間）
|
||||
|
||||
4. **明細表格**
|
||||
- 階層式展開：站點 → 型號 → 個別機台
|
||||
- 欄位：OU%、PRD（時數/佔比）、SBY（時數/佔比）、UDT（時數/佔比）、SDT（時數/佔比）、EGT（時數/佔比）、NST（時數/佔比）、機台數
|
||||
- 支援匯出功能
|
||||
|
||||
## Capabilities
|
||||
|
||||
### New Capabilities
|
||||
|
||||
- `resource-history-page`: 機台歷史表現分析頁面，包含篩選、KPI、圖表、明細表格
|
||||
- `resource-history-service`: 歷史資料查詢服務，支援多維度聚合與階層式資料結構
|
||||
|
||||
### Modified Capabilities
|
||||
|
||||
- （無需修改現有 spec，/resource 頁面的調整為實作層級變更）
|
||||
|
||||
## Impact
|
||||
|
||||
- **新增檔案**:
|
||||
- `src/mes_dashboard/templates/resource_history.html` - 歷史分析頁面模板
|
||||
- `src/mes_dashboard/routes/resource_history_routes.py` - 歷史分析路由
|
||||
- `src/mes_dashboard/services/resource_history_service.py` - 歷史資料查詢服務
|
||||
|
||||
- **修改檔案**:
|
||||
- `src/mes_dashboard/__init__.py` - 註冊新路由
|
||||
|
||||
- **資料來源**:
|
||||
- `DW_MES_RESOURCESTATUS_SHIFT` - 機台狀態班別資料（約 74M 筆）
|
||||
- `DW_MES_RESOURCE` - 機台維度資料
|
||||
|
||||
- **向後相容**：本變更為純新增功能，不影響任何現有頁面
|
||||
@@ -0,0 +1,253 @@
|
||||
## ADDED Requirements
|
||||
|
||||
### Requirement: 頁面路由與存取
|
||||
|
||||
系統 SHALL 提供 `/resource-history` 路由存取機台歷史表現分析頁面。
|
||||
|
||||
#### Scenario: 存取歷史分析頁面
|
||||
- **WHEN** 使用者導航至 `/resource-history`
|
||||
- **THEN** 系統顯示機台歷史表現分析頁面
|
||||
|
||||
#### Scenario: 頁面初始狀態
|
||||
- **WHEN** 頁面首次載入
|
||||
- **THEN** 系統顯示篩選條件區但不載入任何資料
|
||||
- **THEN** 圖表和表格區域顯示「請設定查詢條件」提示
|
||||
|
||||
---
|
||||
|
||||
### Requirement: 日期範圍篩選
|
||||
|
||||
系統 SHALL 提供日期範圍選擇器，允許使用者指定查詢的起迄日期。
|
||||
|
||||
#### Scenario: 選擇日期範圍
|
||||
- **WHEN** 使用者設定開始日期為 2024-01-01，結束日期為 2024-01-31
|
||||
- **THEN** 系統記錄查詢範圍為該期間
|
||||
|
||||
#### Scenario: 日期範圍限制
|
||||
- **WHEN** 使用者選擇超過 365 天的日期範圍
|
||||
- **THEN** 系統顯示警告訊息「查詢範圍不可超過一年」
|
||||
- **THEN** 系統阻止查詢執行
|
||||
|
||||
#### Scenario: 預設日期範圍
|
||||
- **WHEN** 頁面載入時
|
||||
- **THEN** 日期範圍預設為最近 7 天（不含今日）
|
||||
|
||||
---
|
||||
|
||||
### Requirement: 時間粒度切換
|
||||
|
||||
系統 SHALL 提供日/週/月/年四種時間粒度選項，用於控制資料聚合方式。
|
||||
|
||||
#### Scenario: 切換至日粒度
|
||||
- **WHEN** 使用者選擇「日」粒度
|
||||
- **THEN** 後續查詢以每日為單位聚合資料
|
||||
|
||||
#### Scenario: 切換至週粒度
|
||||
- **WHEN** 使用者選擇「週」粒度
|
||||
- **THEN** 後續查詢以 ISO 週為單位聚合資料
|
||||
|
||||
#### Scenario: 切換至月粒度
|
||||
- **WHEN** 使用者選擇「月」粒度
|
||||
- **THEN** 後續查詢以每月為單位聚合資料
|
||||
|
||||
#### Scenario: 切換至年粒度
|
||||
- **WHEN** 使用者選擇「年」粒度
|
||||
- **THEN** 後續查詢以每年為單位聚合資料
|
||||
|
||||
#### Scenario: 預設粒度
|
||||
- **WHEN** 頁面載入時
|
||||
- **THEN** 時間粒度預設為「日」
|
||||
|
||||
---
|
||||
|
||||
### Requirement: 站點與型號篩選
|
||||
|
||||
系統 SHALL 提供站點（Workcenter）和機台型號（Resource Family）下拉選單進行資料篩選。
|
||||
|
||||
#### Scenario: 篩選特定站點
|
||||
- **WHEN** 使用者從站點下拉選單選擇「WC01」
|
||||
- **THEN** 查詢結果僅包含該站點的資料
|
||||
|
||||
#### Scenario: 篩選特定型號
|
||||
- **WHEN** 使用者從型號下拉選單選擇「FAM01」
|
||||
- **THEN** 查詢結果僅包含該型號的資料
|
||||
|
||||
#### Scenario: 組合篩選
|
||||
- **WHEN** 使用者同時選擇站點「WC01」和型號「FAM01」
|
||||
- **THEN** 查詢結果僅包含同時符合兩個條件的資料
|
||||
|
||||
#### Scenario: 動態載入篩選選項
|
||||
- **WHEN** 頁面載入時
|
||||
- **THEN** 系統從資料庫載入可用的站點和型號列表
|
||||
|
||||
---
|
||||
|
||||
### Requirement: 設備旗標篩選
|
||||
|
||||
系統 SHALL 提供生產機、關鍵機、監控機三個 checkbox 篩選選項。
|
||||
|
||||
#### Scenario: 篩選生產機
|
||||
- **WHEN** 使用者勾選「生產機」checkbox
|
||||
- **THEN** 查詢結果僅包含 PJ_ISPRODUCTION = 1 的機台
|
||||
|
||||
#### Scenario: 篩選關鍵機
|
||||
- **WHEN** 使用者勾選「關鍵機」checkbox
|
||||
- **THEN** 查詢結果僅包含 PJ_ISKEY = 1 的機台
|
||||
|
||||
#### Scenario: 篩選監控機
|
||||
- **WHEN** 使用者勾選「監控機」checkbox
|
||||
- **THEN** 查詢結果僅包含 PJ_ISMONITOR = 1 的機台
|
||||
|
||||
---
|
||||
|
||||
### Requirement: 查詢觸發
|
||||
|
||||
系統 SHALL 提供查詢按鈕，使用者點擊後才執行資料查詢。
|
||||
|
||||
#### Scenario: 執行查詢
|
||||
- **WHEN** 使用者設定完篩選條件後點擊「查詢」按鈕
|
||||
- **THEN** 系統根據篩選條件執行查詢
|
||||
- **THEN** 系統顯示載入指示器
|
||||
- **THEN** 查詢完成後更新 KPI、圖表、表格
|
||||
|
||||
#### Scenario: 查詢失敗處理
|
||||
- **WHEN** 查詢執行失敗（如網路錯誤、超時）
|
||||
- **THEN** 系統顯示錯誤訊息 toast 通知
|
||||
- **THEN** 系統隱藏載入指示器
|
||||
|
||||
---
|
||||
|
||||
### Requirement: KPI 摘要卡片
|
||||
|
||||
系統 SHALL 顯示 6 個 KPI 摘要卡片：OU%、PRD 時數、UDT 時數、SDT 時數、EGT 時數、機台數。
|
||||
|
||||
#### Scenario: 顯示 OU%
|
||||
- **WHEN** 查詢完成
|
||||
- **THEN** 系統顯示查詢範圍內的整體 OU%
|
||||
- **THEN** OU% 計算公式為 PRD / (PRD + SBY + EGT + SDT + UDT) * 100
|
||||
|
||||
#### Scenario: 顯示各狀態時數
|
||||
- **WHEN** 查詢完成
|
||||
- **THEN** 系統顯示 PRD、UDT、SDT、EGT 的總時數（小時）
|
||||
|
||||
#### Scenario: 顯示機台數
|
||||
- **WHEN** 查詢完成
|
||||
- **THEN** 系統顯示符合篩選條件的不重複機台數量
|
||||
|
||||
---
|
||||
|
||||
### Requirement: OU% 趨勢折線圖
|
||||
|
||||
系統 SHALL 顯示 OU% 隨時間變化的折線圖。
|
||||
|
||||
#### Scenario: 顯示趨勢圖
|
||||
- **WHEN** 查詢完成
|
||||
- **THEN** 系統顯示 X 軸為時間、Y 軸為 OU% 的折線圖
|
||||
- **THEN** X 軸根據時間粒度顯示對應的日期標籤
|
||||
|
||||
#### Scenario: 圖表互動
|
||||
- **WHEN** 使用者將滑鼠移至圖表上的數據點
|
||||
- **THEN** 系統顯示該時間點的詳細數值（日期、OU%、PRD 時數等）
|
||||
|
||||
---
|
||||
|
||||
### Requirement: E10 狀態堆疊長條圖
|
||||
|
||||
系統 SHALL 顯示各時間點的 E10 設備狀態時數分布堆疊長條圖。
|
||||
|
||||
#### Scenario: 顯示堆疊圖
|
||||
- **WHEN** 查詢完成
|
||||
- **THEN** 系統顯示 X 軸為時間、Y 軸為時數的堆疊長條圖
|
||||
- **THEN** 每個長條包含 PRD、SBY、UDT、SDT、EGT、NST 六種狀態的堆疊
|
||||
|
||||
#### Scenario: 圖表圖例
|
||||
- **WHEN** 圖表顯示時
|
||||
- **THEN** 系統顯示各狀態的顏色圖例
|
||||
- **THEN** 使用者可點擊圖例切換該狀態的顯示/隱藏
|
||||
|
||||
---
|
||||
|
||||
### Requirement: 工站 OU% 對比水平條形圖
|
||||
|
||||
系統 SHALL 顯示各站點 OU% 的水平條形圖比較。
|
||||
|
||||
#### Scenario: 顯示對比圖
|
||||
- **WHEN** 查詢完成
|
||||
- **THEN** 系統顯示各站點的 OU% 水平條形圖
|
||||
- **THEN** 條形圖按 OU% 由高到低排序
|
||||
|
||||
---
|
||||
|
||||
### Requirement: 設備狀態熱力圖
|
||||
|
||||
系統 SHALL 顯示站點 × 時間的 OU% 熱力圖。
|
||||
|
||||
#### Scenario: 顯示熱力圖
|
||||
- **WHEN** 查詢完成
|
||||
- **THEN** 系統顯示 X 軸為時間、Y 軸為站點的熱力圖
|
||||
- **THEN** 顏色深淺表示該站點在該時間的 OU%
|
||||
|
||||
#### Scenario: 熱力圖顏色編碼
|
||||
- **WHEN** 熱力圖顯示時
|
||||
- **THEN** OU% 高（> 80%）顯示綠色
|
||||
- **THEN** OU% 中（50-80%）顯示黃色
|
||||
- **THEN** OU% 低（< 50%）顯示紅色
|
||||
|
||||
---
|
||||
|
||||
### Requirement: 階層式明細表格
|
||||
|
||||
系統 SHALL 顯示可展開的階層式明細表格，支援站點 → 型號 → 個別機台三層結構。
|
||||
|
||||
#### Scenario: 顯示站點層級
|
||||
- **WHEN** 查詢完成
|
||||
- **THEN** 表格預設顯示站點層級的彙總資料
|
||||
- **THEN** 每列顯示展開/收合按鈕
|
||||
|
||||
#### Scenario: 展開至型號層級
|
||||
- **WHEN** 使用者點擊站點列的展開按鈕
|
||||
- **THEN** 系統顯示該站點下各型號的彙總資料
|
||||
- **THEN** 型號列以縮排方式呈現
|
||||
|
||||
#### Scenario: 展開至機台層級
|
||||
- **WHEN** 使用者點擊型號列的展開按鈕
|
||||
- **THEN** 系統顯示該型號下各機台的詳細資料
|
||||
- **THEN** 機台列以更深縮排方式呈現
|
||||
|
||||
#### Scenario: 全部展開
|
||||
- **WHEN** 使用者點擊「全部展開」按鈕
|
||||
- **THEN** 系統展開所有層級顯示完整明細
|
||||
|
||||
---
|
||||
|
||||
### Requirement: 表格欄位
|
||||
|
||||
系統 SHALL 在明細表格中顯示以下欄位：站點/型號/機台、OU%、PRD（時數/佔比）、SBY（時數/佔比）、UDT（時數/佔比）、SDT（時數/佔比）、EGT（時數/佔比）、NST（時數/佔比）、機台數。
|
||||
|
||||
#### Scenario: 顯示時數與佔比
|
||||
- **WHEN** 表格顯示資料時
|
||||
- **THEN** 各 E10 狀態欄位同時顯示時數（小時）和佔比（百分比）
|
||||
- **THEN** 格式為「123.4h (45.6%)」
|
||||
|
||||
#### Scenario: 機台數欄位
|
||||
- **WHEN** 顯示站點或型號層級時
|
||||
- **THEN** 機台數欄位顯示該群組的不重複機台數量
|
||||
- **WHEN** 顯示機台層級時
|
||||
- **THEN** 機台數欄位顯示 1
|
||||
|
||||
---
|
||||
|
||||
### Requirement: 資料匯出
|
||||
|
||||
系統 SHALL 提供 CSV 格式的資料匯出功能。
|
||||
|
||||
#### Scenario: 匯出明細資料
|
||||
- **WHEN** 使用者點擊「匯出」按鈕
|
||||
- **THEN** 系統生成包含所有明細資料的 CSV 檔案
|
||||
- **THEN** 瀏覽器自動下載該檔案
|
||||
- **THEN** 檔案名稱包含查詢日期範圍
|
||||
|
||||
#### Scenario: 匯出大量資料
|
||||
- **WHEN** 查詢結果超過 10000 筆
|
||||
- **THEN** 系統仍完整匯出所有資料
|
||||
- **THEN** 系統顯示匯出進度提示
|
||||
@@ -0,0 +1,154 @@
|
||||
## ADDED Requirements
|
||||
|
||||
### Requirement: 歷史資料摘要查詢
|
||||
|
||||
系統 SHALL 提供 API 端點 `GET /api/resource/history/summary` 查詢機台歷史效能摘要資料。
|
||||
|
||||
#### Scenario: 查詢日粒度摘要
|
||||
- **WHEN** 呼叫 API 並傳入 start_date=2024-01-01, end_date=2024-01-07, granularity=day
|
||||
- **THEN** 系統回傳該期間以日為單位聚合的 KPI、趨勢、熱力圖、站點比較資料
|
||||
|
||||
#### Scenario: 查詢週粒度摘要
|
||||
- **WHEN** 呼叫 API 並傳入 granularity=week
|
||||
- **THEN** 系統使用 TRUNC(TXNDATE, 'IW') 以 ISO 週為單位聚合資料
|
||||
|
||||
#### Scenario: 查詢月粒度摘要
|
||||
- **WHEN** 呼叫 API 並傳入 granularity=month
|
||||
- **THEN** 系統使用 TRUNC(TXNDATE, 'MM') 以月為單位聚合資料
|
||||
|
||||
#### Scenario: 查詢年粒度摘要
|
||||
- **WHEN** 呼叫 API 並傳入 granularity=year
|
||||
- **THEN** 系統使用 TRUNC(TXNDATE, 'YYYY') 以年為單位聚合資料
|
||||
|
||||
#### Scenario: 帶篩選條件查詢
|
||||
- **WHEN** 呼叫 API 並傳入 workcenter=WC01, family=FAM01
|
||||
- **THEN** 系統回傳僅符合該站點和型號的資料
|
||||
|
||||
#### Scenario: 回傳資料結構
|
||||
- **WHEN** 查詢成功
|
||||
- **THEN** 回傳 JSON 包含 kpi、trend、heatmap、workcenter_comparison 四個區塊
|
||||
|
||||
---
|
||||
|
||||
### Requirement: OU% 計算公式
|
||||
|
||||
系統 SHALL 使用標準 OU% 計算公式：PRD / (PRD + SBY + EGT + SDT + UDT) * 100。
|
||||
|
||||
#### Scenario: 計算 OU%
|
||||
- **WHEN** PRD=800, SBY=100, EGT=50, SDT=30, UDT=20
|
||||
- **THEN** OU% = 800 / (800+100+50+30+20) * 100 = 80%
|
||||
|
||||
#### Scenario: 排除 NST
|
||||
- **WHEN** 計算 OU% 時
|
||||
- **THEN** 分母不包含 NST（Not Scheduled Time）
|
||||
|
||||
#### Scenario: 處理零分母
|
||||
- **WHEN** PRD + SBY + EGT + SDT + UDT = 0
|
||||
- **THEN** OU% 回傳 0 而非錯誤
|
||||
|
||||
---
|
||||
|
||||
### Requirement: E10 狀態時數與佔比計算
|
||||
|
||||
系統 SHALL 計算各 E10 狀態（PRD、SBY、UDT、SDT、EGT、NST）的時數和佔比。
|
||||
|
||||
#### Scenario: 計算狀態時數
|
||||
- **WHEN** 查詢特定期間的資料
|
||||
- **THEN** 系統從 DW_MES_RESOURCESTATUS_SHIFT.HOURS 欄位聚合各狀態時數
|
||||
|
||||
#### Scenario: 計算狀態佔比
|
||||
- **WHEN** 計算各狀態佔比
|
||||
- **THEN** 佔比 = 該狀態時數 / 全部狀態時數總和 * 100
|
||||
|
||||
#### Scenario: 按狀態分組聚合
|
||||
- **WHEN** 聚合資料時
|
||||
- **THEN** 系統根據 OLDSTATUSNAME 欄位識別 PRD、SBY、UDT、SDT、EGT、NST
|
||||
|
||||
---
|
||||
|
||||
### Requirement: 階層式明細資料查詢
|
||||
|
||||
系統 SHALL 提供 API 端點 `GET /api/resource/history/detail` 查詢階層式明細資料。
|
||||
|
||||
#### Scenario: 查詢明細資料
|
||||
- **WHEN** 呼叫 API 並傳入日期範圍和粒度
|
||||
- **THEN** 系統回傳包含 WORKCENTERNAME、RESOURCEFAMILYNAME、RESOURCENAME 三個維度的扁平化資料
|
||||
|
||||
#### Scenario: 分頁查詢
|
||||
- **WHEN** 呼叫 API 並傳入 page=2, page_size=100
|
||||
- **THEN** 系統回傳第 101-200 筆資料
|
||||
- **THEN** 回傳包含 total 總筆數供前端分頁
|
||||
|
||||
#### Scenario: 回傳欄位
|
||||
- **WHEN** 查詢成功
|
||||
- **THEN** 每筆資料包含：workcenter、family、resource、ou_pct、prd_hours、prd_pct、sby_hours、sby_pct、udt_hours、udt_pct、sdt_hours、sdt_pct、egt_hours、egt_pct、nst_hours、nst_pct、machine_count
|
||||
|
||||
---
|
||||
|
||||
### Requirement: 篩選選項查詢
|
||||
|
||||
系統 SHALL 提供 API 端點查詢可用的篩選選項。
|
||||
|
||||
#### Scenario: 查詢站點列表
|
||||
- **WHEN** 頁面載入時呼叫篩選選項 API
|
||||
- **THEN** 系統回傳所有可用的 WORKCENTERNAME 列表
|
||||
|
||||
#### Scenario: 查詢型號列表
|
||||
- **WHEN** 頁面載入時呼叫篩選選項 API
|
||||
- **THEN** 系統回傳所有可用的 RESOURCEFAMILYNAME 列表
|
||||
|
||||
---
|
||||
|
||||
### Requirement: 資料匯出服務
|
||||
|
||||
系統 SHALL 提供 API 端點 `GET /api/resource/history/export` 匯出 CSV 格式資料。
|
||||
|
||||
#### Scenario: 匯出 CSV
|
||||
- **WHEN** 呼叫 API 並傳入 format=csv 和篩選條件
|
||||
- **THEN** 系統回傳 Content-Type: text/csv 的檔案下載
|
||||
- **THEN** 檔案包含所有符合條件的明細資料
|
||||
|
||||
#### Scenario: CSV 欄位
|
||||
- **WHEN** 匯出 CSV 時
|
||||
- **THEN** 包含欄位：站點、型號、機台、OU%、PRD(h)、PRD(%)、SBY(h)、SBY(%)、UDT(h)、UDT(%)、SDT(h)、SDT(%)、EGT(h)、EGT(%)、NST(h)、NST(%)
|
||||
|
||||
#### Scenario: 處理大量資料匯出
|
||||
- **WHEN** 匯出資料量超過 10000 筆
|
||||
- **THEN** 系統使用串流方式輸出避免記憶體溢出
|
||||
|
||||
---
|
||||
|
||||
### Requirement: 資料來源與關聯
|
||||
|
||||
系統 SHALL 從 DW_MES_RESOURCESTATUS_SHIFT 表查詢歷史狀態資料，並關聯 DW_MES_RESOURCE 表取得機台維度資訊。
|
||||
|
||||
#### Scenario: 資料表關聯
|
||||
- **WHEN** 查詢資料時
|
||||
- **THEN** 系統使用 HISTORYID = RESOURCEID 關聯兩表
|
||||
|
||||
#### Scenario: 篩選條件
|
||||
- **WHEN** 查詢資料時
|
||||
- **THEN** 系統套用 OBJECTCATEGORY/OBJECTTYPE 篩選（ASSEMBLY 或 WAFERSORT）
|
||||
- **THEN** 系統排除 EXCLUDED_LOCATIONS 和 EXCLUDED_ASSET_STATUSES 中定義的資料
|
||||
|
||||
#### Scenario: 時間範圍篩選
|
||||
- **WHEN** 查詢資料時
|
||||
- **THEN** 系統使用 TXNDATE 欄位進行日期範圍篩選
|
||||
|
||||
---
|
||||
|
||||
### Requirement: 查詢效能優化
|
||||
|
||||
系統 SHALL 實作查詢效能優化措施。
|
||||
|
||||
#### Scenario: 日期範圍限制
|
||||
- **WHEN** 查詢日期範圍超過 365 天
|
||||
- **THEN** 系統回傳錯誤訊息「查詢範圍不可超過一年」
|
||||
|
||||
#### Scenario: 索引使用
|
||||
- **WHEN** 執行查詢時
|
||||
- **THEN** 系統確保 SQL 查詢能使用 TXNDATE 索引
|
||||
|
||||
#### Scenario: 查詢超時
|
||||
- **WHEN** 查詢執行超過 60 秒
|
||||
- **THEN** 系統中斷查詢並回傳超時錯誤
|
||||
@@ -0,0 +1,68 @@
|
||||
## 1. 後端服務模組
|
||||
|
||||
- [x] 1.1 建立 `src/mes_dashboard/services/resource_history_service.py` 模組結構
|
||||
- [x] 1.2 實作 `get_filter_options()` 函數：查詢可用的站點、型號列表
|
||||
- [x] 1.3 實作 `query_summary()` 函數：查詢 KPI、趨勢、熱力圖、站點比較資料
|
||||
- [x] 1.4 實作 `query_detail()` 函數：查詢階層式明細資料（支援分頁）
|
||||
- [x] 1.5 實作 `export_csv()` 函數：串流輸出 CSV 格式資料
|
||||
- [x] 1.6 實作時間粒度聚合邏輯（日/週/月/年 TRUNC 函數）
|
||||
- [x] 1.7 實作 OU% 計算公式（PRD / (PRD+SBY+EGT+SDT+UDT) * 100）
|
||||
- [x] 1.8 實作各 E10 狀態時數與佔比計算
|
||||
|
||||
## 2. API 路由
|
||||
|
||||
- [x] 2.1 建立 `src/mes_dashboard/routes/resource_history_routes.py` 路由模組
|
||||
- [x] 2.2 實作 `GET /api/resource/history/options` 端點：篩選選項
|
||||
- [x] 2.3 實作 `GET /api/resource/history/summary` 端點：摘要資料
|
||||
- [x] 2.4 實作 `GET /api/resource/history/detail` 端點：明細資料
|
||||
- [x] 2.5 實作 `GET /api/resource/history/export` 端點：CSV 匯出
|
||||
- [x] 2.6 在 `__init__.py` 註冊新路由 Blueprint
|
||||
|
||||
## 3. 前端頁面模板
|
||||
|
||||
- [x] 3.1 建立 `src/mes_dashboard/templates/resource_history.html` 頁面模板
|
||||
- [x] 3.2 實作篩選條件區（日期範圍、粒度按鈕、站點/型號下拉、checkbox）
|
||||
- [x] 3.3 實作 KPI 摘要卡片區（OU%、PRD、UDT、SDT、EGT、機台數）
|
||||
- [x] 3.4 實作頁面路由 `GET /resource-history`
|
||||
|
||||
## 4. 前端圖表
|
||||
|
||||
- [x] 4.1 實作 OU% 趨勢折線圖（ECharts line chart）
|
||||
- [x] 4.2 實作 E10 狀態堆疊長條圖（ECharts stacked bar chart）
|
||||
- [x] 4.3 實作工站 OU% 對比水平條形圖（ECharts horizontal bar）
|
||||
- [x] 4.4 實作設備狀態熱力圖（ECharts heatmap）
|
||||
|
||||
## 5. 前端表格
|
||||
|
||||
- [x] 5.1 實作階層式明細表格結構
|
||||
- [x] 5.2 實作站點層級展開/收合功能
|
||||
- [x] 5.3 實作型號層級展開/收合功能
|
||||
- [x] 5.4 實作「全部展開」按鈕
|
||||
- [x] 5.5 實作表格欄位格式化（時數/佔比顯示）
|
||||
- [x] 5.6 實作匯出按鈕與 CSV 下載
|
||||
|
||||
## 6. 前端互動邏輯
|
||||
|
||||
- [x] 6.1 實作查詢按鈕點擊事件與載入指示器
|
||||
- [x] 6.2 實作日期範圍驗證（不超過 730 天 / 兩年）
|
||||
- [x] 6.3 實作時間粒度切換邏輯
|
||||
- [x] 6.4 實作篩選條件變更處理
|
||||
- [x] 6.5 實作查詢失敗的錯誤處理與 toast 通知
|
||||
- [x] 6.6 實作初始狀態提示（「請設定查詢條件」）
|
||||
|
||||
## 7. 測試與驗證
|
||||
|
||||
- [x] 7.1 驗證 API 回傳資料格式正確
|
||||
- [x] 7.2 驗證 OU% 計算結果正確
|
||||
- [x] 7.3 驗證各時間粒度聚合正確
|
||||
- [x] 7.4 驗證階層式表格展開/收合正常
|
||||
- [x] 7.5 驗證 CSV 匯出內容正確
|
||||
- [x] 7.6 驗證大量資料查詢效能（日期範圍限制生效）
|
||||
|
||||
## 8. 後續優化
|
||||
|
||||
- [x] 8.1 放寬查詢日期範圍至 730 天（兩年）
|
||||
- [x] 8.2 移除明細查詢筆數上限（原 5000 筆）
|
||||
- [x] 8.3 修復 NaN 值造成 JSON 序列化錯誤
|
||||
- [x] 8.4 修復 MesApi 成功回應後誤觸重試機制
|
||||
- [x] 8.5 E10 狀態分布圖表 tooltip 加入百分比顯示
|
||||
@@ -175,6 +175,11 @@ def create_app(config_name: str | None = None) -> Flask:
|
||||
"""Excel batch query tool page."""
|
||||
return render_template('excel_query.html')
|
||||
|
||||
@app.route('/resource-history')
|
||||
def resource_history_page():
|
||||
"""Resource history analysis page."""
|
||||
return render_template('resource_history.html')
|
||||
|
||||
# ========================================================
|
||||
# Table Query APIs (for table_data_viewer)
|
||||
# ========================================================
|
||||
|
||||
@@ -11,6 +11,7 @@ from .excel_query_routes import excel_query_bp
|
||||
from .hold_routes import hold_bp
|
||||
from .auth_routes import auth_bp
|
||||
from .admin_routes import admin_bp
|
||||
from .resource_history_routes import resource_history_bp
|
||||
|
||||
|
||||
def register_routes(app) -> None:
|
||||
@@ -20,6 +21,7 @@ def register_routes(app) -> None:
|
||||
app.register_blueprint(dashboard_bp)
|
||||
app.register_blueprint(excel_query_bp)
|
||||
app.register_blueprint(hold_bp)
|
||||
app.register_blueprint(resource_history_bp)
|
||||
|
||||
__all__ = [
|
||||
'wip_bp',
|
||||
@@ -29,5 +31,6 @@ __all__ = [
|
||||
'hold_bp',
|
||||
'auth_bp',
|
||||
'admin_bp',
|
||||
'resource_history_bp',
|
||||
'register_routes',
|
||||
]
|
||||
|
||||
239
src/mes_dashboard/routes/resource_history_routes.py
Normal file
239
src/mes_dashboard/routes/resource_history_routes.py
Normal file
@@ -0,0 +1,239 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
"""Resource History Analysis API routes.
|
||||
|
||||
Contains Flask Blueprint for historical equipment performance analysis endpoints.
|
||||
"""
|
||||
|
||||
from flask import Blueprint, jsonify, request, render_template, Response
|
||||
|
||||
from mes_dashboard.core.cache import cache_get, cache_set, make_cache_key
|
||||
from mes_dashboard.config.constants import CACHE_TTL_FILTER_OPTIONS, CACHE_TTL_TREND
|
||||
from mes_dashboard.services.resource_history_service import (
|
||||
get_filter_options,
|
||||
query_summary,
|
||||
query_detail,
|
||||
export_csv,
|
||||
)
|
||||
|
||||
# Create Blueprint
|
||||
resource_history_bp = Blueprint(
|
||||
'resource_history',
|
||||
__name__,
|
||||
url_prefix='/api/resource/history'
|
||||
)
|
||||
|
||||
|
||||
# ============================================================
|
||||
# Page Route (for template rendering)
|
||||
# ============================================================
|
||||
|
||||
@resource_history_bp.route('/page', methods=['GET'], endpoint='page_alias')
|
||||
def api_resource_history_page():
|
||||
"""Render the resource history analysis page.
|
||||
|
||||
Note: The actual page route /resource-history is registered separately
|
||||
in the main app initialization.
|
||||
"""
|
||||
return render_template('resource_history.html')
|
||||
|
||||
|
||||
# ============================================================
|
||||
# API Endpoints
|
||||
# ============================================================
|
||||
|
||||
@resource_history_bp.route('/options', methods=['GET'])
|
||||
def api_resource_history_options():
|
||||
"""API: Get filter options (workcenters and families).
|
||||
|
||||
Returns:
|
||||
JSON with workcenters and families lists.
|
||||
"""
|
||||
cache_key = make_cache_key("resource_history_options")
|
||||
options = cache_get(cache_key)
|
||||
|
||||
if options is None:
|
||||
options = get_filter_options()
|
||||
if options is not None:
|
||||
cache_set(cache_key, options, ttl=CACHE_TTL_FILTER_OPTIONS)
|
||||
|
||||
if options is not None:
|
||||
return jsonify({'success': True, 'data': options})
|
||||
return jsonify({'success': False, 'error': '查詢篩選選項失敗'}), 500
|
||||
|
||||
|
||||
@resource_history_bp.route('/summary', methods=['GET'])
|
||||
def api_resource_history_summary():
|
||||
"""API: Get summary data (KPI, trend, heatmap, workcenter comparison).
|
||||
|
||||
Query Parameters:
|
||||
start_date: Start date (YYYY-MM-DD)
|
||||
end_date: End date (YYYY-MM-DD)
|
||||
granularity: day|week|month|year (default: day)
|
||||
workcenter_groups: Optional workcenter group filter (multi-select)
|
||||
families: Optional resource family filter (multi-select)
|
||||
is_production: 1 to filter production equipment
|
||||
is_key: 1 to filter key equipment
|
||||
is_monitor: 1 to filter monitored equipment
|
||||
|
||||
Returns:
|
||||
JSON with kpi, trend, heatmap, workcenter_comparison sections.
|
||||
"""
|
||||
# Parse query parameters
|
||||
start_date = request.args.get('start_date')
|
||||
end_date = request.args.get('end_date')
|
||||
granularity = request.args.get('granularity', 'day')
|
||||
workcenter_groups = request.args.getlist('workcenter_groups') or None
|
||||
families = request.args.getlist('families') or None
|
||||
is_production = request.args.get('is_production') == '1'
|
||||
is_key = request.args.get('is_key') == '1'
|
||||
is_monitor = request.args.get('is_monitor') == '1'
|
||||
|
||||
# Validate required parameters
|
||||
if not start_date or not end_date:
|
||||
return jsonify({
|
||||
'success': False,
|
||||
'error': '必須提供 start_date 和 end_date 參數'
|
||||
}), 400
|
||||
|
||||
# Build cache key with filters dict
|
||||
cache_filters = {
|
||||
'start_date': start_date,
|
||||
'end_date': end_date,
|
||||
'granularity': granularity,
|
||||
'workcenter_groups': sorted(workcenter_groups) if workcenter_groups else None,
|
||||
'families': sorted(families) if families else None,
|
||||
'is_production': is_production,
|
||||
'is_key': is_key,
|
||||
'is_monitor': is_monitor,
|
||||
}
|
||||
cache_key = make_cache_key("resource_history_summary", filters=cache_filters)
|
||||
result = cache_get(cache_key)
|
||||
|
||||
if result is None:
|
||||
result = query_summary(
|
||||
start_date=start_date,
|
||||
end_date=end_date,
|
||||
granularity=granularity,
|
||||
workcenter_groups=workcenter_groups,
|
||||
families=families,
|
||||
is_production=is_production,
|
||||
is_key=is_key,
|
||||
is_monitor=is_monitor,
|
||||
)
|
||||
if result is not None and 'error' not in result:
|
||||
cache_set(cache_key, result, ttl=CACHE_TTL_TREND)
|
||||
|
||||
if result is not None:
|
||||
if 'error' in result:
|
||||
return jsonify({'success': False, 'error': result['error']}), 400
|
||||
return jsonify({'success': True, 'data': result})
|
||||
return jsonify({'success': False, 'error': '查詢摘要資料失敗'}), 500
|
||||
|
||||
|
||||
@resource_history_bp.route('/detail', methods=['GET'])
|
||||
def api_resource_history_detail():
|
||||
"""API: Get hierarchical detail data.
|
||||
|
||||
Query Parameters:
|
||||
start_date: Start date (YYYY-MM-DD)
|
||||
end_date: End date (YYYY-MM-DD)
|
||||
granularity: day|week|month|year (default: day)
|
||||
workcenter_groups: Optional workcenter group filter (multi-select)
|
||||
families: Optional resource family filter (multi-select)
|
||||
is_production: 1 to filter production equipment
|
||||
is_key: 1 to filter key equipment
|
||||
is_monitor: 1 to filter monitored equipment
|
||||
|
||||
Returns:
|
||||
JSON with data array, total count, truncated flag.
|
||||
"""
|
||||
# Parse query parameters
|
||||
start_date = request.args.get('start_date')
|
||||
end_date = request.args.get('end_date')
|
||||
granularity = request.args.get('granularity', 'day')
|
||||
workcenter_groups = request.args.getlist('workcenter_groups') or None
|
||||
families = request.args.getlist('families') or None
|
||||
is_production = request.args.get('is_production') == '1'
|
||||
is_key = request.args.get('is_key') == '1'
|
||||
is_monitor = request.args.get('is_monitor') == '1'
|
||||
|
||||
# Validate required parameters
|
||||
if not start_date or not end_date:
|
||||
return jsonify({
|
||||
'success': False,
|
||||
'error': '必須提供 start_date 和 end_date 參數'
|
||||
}), 400
|
||||
|
||||
result = query_detail(
|
||||
start_date=start_date,
|
||||
end_date=end_date,
|
||||
granularity=granularity,
|
||||
workcenter_groups=workcenter_groups,
|
||||
families=families,
|
||||
is_production=is_production,
|
||||
is_key=is_key,
|
||||
is_monitor=is_monitor,
|
||||
)
|
||||
|
||||
if result is not None:
|
||||
if 'error' in result:
|
||||
return jsonify({'success': False, 'error': result['error']}), 400
|
||||
return jsonify({'success': True, **result})
|
||||
return jsonify({'success': False, 'error': '查詢明細資料失敗'}), 500
|
||||
|
||||
|
||||
@resource_history_bp.route('/export', methods=['GET'])
|
||||
def api_resource_history_export():
|
||||
"""API: Export detail data as CSV.
|
||||
|
||||
Query Parameters:
|
||||
start_date: Start date (YYYY-MM-DD)
|
||||
end_date: End date (YYYY-MM-DD)
|
||||
granularity: day|week|month|year (default: day)
|
||||
workcenter_groups: Optional workcenter group filter (multi-select)
|
||||
families: Optional resource family filter (multi-select)
|
||||
is_production: 1 to filter production equipment
|
||||
is_key: 1 to filter key equipment
|
||||
is_monitor: 1 to filter monitored equipment
|
||||
|
||||
Returns:
|
||||
CSV file download.
|
||||
"""
|
||||
# Parse query parameters
|
||||
start_date = request.args.get('start_date')
|
||||
end_date = request.args.get('end_date')
|
||||
granularity = request.args.get('granularity', 'day')
|
||||
workcenter_groups = request.args.getlist('workcenter_groups') or None
|
||||
families = request.args.getlist('families') or None
|
||||
is_production = request.args.get('is_production') == '1'
|
||||
is_key = request.args.get('is_key') == '1'
|
||||
is_monitor = request.args.get('is_monitor') == '1'
|
||||
|
||||
# Validate required parameters
|
||||
if not start_date or not end_date:
|
||||
return jsonify({
|
||||
'success': False,
|
||||
'error': '必須提供 start_date 和 end_date 參數'
|
||||
}), 400
|
||||
|
||||
# Generate filename
|
||||
filename = f"resource_history_{start_date}_to_{end_date}.csv"
|
||||
|
||||
# Stream CSV response
|
||||
return Response(
|
||||
export_csv(
|
||||
start_date=start_date,
|
||||
end_date=end_date,
|
||||
granularity=granularity,
|
||||
workcenter_groups=workcenter_groups,
|
||||
families=families,
|
||||
is_production=is_production,
|
||||
is_key=is_key,
|
||||
is_monitor=is_monitor,
|
||||
),
|
||||
mimetype='text/csv',
|
||||
headers={
|
||||
'Content-Disposition': f'attachment; filename={filename}',
|
||||
'Content-Type': 'text/csv; charset=utf-8-sig'
|
||||
}
|
||||
)
|
||||
292
src/mes_dashboard/services/filter_cache.py
Normal file
292
src/mes_dashboard/services/filter_cache.py
Normal file
@@ -0,0 +1,292 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
"""Cached filter options for MES Dashboard.
|
||||
|
||||
Provides cached workcenter groups and resource families for filter dropdowns.
|
||||
Data is loaded from database and cached in memory with periodic refresh.
|
||||
"""
|
||||
|
||||
import logging
|
||||
import threading
|
||||
from datetime import datetime, timedelta
|
||||
from typing import Optional, Dict, List, Any
|
||||
|
||||
from mes_dashboard.core.database import read_sql_df
|
||||
from mes_dashboard.config.constants import (
|
||||
EXCLUDED_LOCATIONS,
|
||||
EXCLUDED_ASSET_STATUSES,
|
||||
EQUIPMENT_TYPE_FILTER,
|
||||
)
|
||||
|
||||
logger = logging.getLogger('mes_dashboard.filter_cache')
|
||||
|
||||
# ============================================================
|
||||
# Cache Configuration
|
||||
# ============================================================
|
||||
|
||||
CACHE_TTL_SECONDS = 3600 # 1 hour cache TTL
|
||||
WIP_VIEW = "DWH.DW_PJ_LOT_V"
|
||||
|
||||
# ============================================================
|
||||
# Cache Storage
|
||||
# ============================================================
|
||||
|
||||
_CACHE = {
|
||||
'workcenter_groups': None, # List of {name, sequence}
|
||||
'workcenter_mapping': None, # Dict {workcentername: {group, sequence}}
|
||||
'resource_families': None, # List of family names
|
||||
'last_refresh': None,
|
||||
'is_loading': False,
|
||||
}
|
||||
|
||||
_CACHE_LOCK = threading.Lock()
|
||||
|
||||
|
||||
# ============================================================
|
||||
# Workcenter Group Functions
|
||||
# ============================================================
|
||||
|
||||
def get_workcenter_groups(force_refresh: bool = False) -> Optional[List[Dict[str, Any]]]:
|
||||
"""Get list of workcenter groups with sequence order.
|
||||
|
||||
Returns:
|
||||
List of {name, sequence} sorted by sequence, or None if loading fails.
|
||||
"""
|
||||
_ensure_cache_loaded(force_refresh)
|
||||
return _CACHE.get('workcenter_groups')
|
||||
|
||||
|
||||
def get_workcenter_mapping(force_refresh: bool = False) -> Optional[Dict[str, Dict[str, Any]]]:
|
||||
"""Get workcenter name to group mapping.
|
||||
|
||||
Returns:
|
||||
Dict mapping workcentername to {group, sequence}, or None if loading fails.
|
||||
"""
|
||||
_ensure_cache_loaded(force_refresh)
|
||||
return _CACHE.get('workcenter_mapping')
|
||||
|
||||
|
||||
def get_workcenters_for_groups(groups: List[str]) -> List[str]:
|
||||
"""Get list of workcenter names that belong to specified groups.
|
||||
|
||||
Args:
|
||||
groups: List of WORKCENTER_GROUP names
|
||||
|
||||
Returns:
|
||||
List of WORKCENTERNAME values belonging to those groups
|
||||
"""
|
||||
mapping = get_workcenter_mapping()
|
||||
if not mapping:
|
||||
return []
|
||||
|
||||
result = []
|
||||
for wc_name, info in mapping.items():
|
||||
if info.get('group') in groups:
|
||||
result.append(wc_name)
|
||||
return result
|
||||
|
||||
|
||||
# ============================================================
|
||||
# Resource Family Functions
|
||||
# ============================================================
|
||||
|
||||
def get_resource_families(force_refresh: bool = False) -> Optional[List[str]]:
|
||||
"""Get list of resource family names.
|
||||
|
||||
Returns:
|
||||
Sorted list of RESOURCEFAMILYNAME values, or None if loading fails.
|
||||
"""
|
||||
_ensure_cache_loaded(force_refresh)
|
||||
return _CACHE.get('resource_families')
|
||||
|
||||
|
||||
# ============================================================
|
||||
# Cache Management
|
||||
# ============================================================
|
||||
|
||||
def get_cache_status() -> Dict[str, Any]:
|
||||
"""Get current cache status.
|
||||
|
||||
Returns:
|
||||
Dict with cache status information
|
||||
"""
|
||||
with _CACHE_LOCK:
|
||||
last_refresh = _CACHE.get('last_refresh')
|
||||
return {
|
||||
'loaded': last_refresh is not None,
|
||||
'last_refresh': last_refresh.isoformat() if last_refresh else None,
|
||||
'is_loading': _CACHE.get('is_loading', False),
|
||||
'workcenter_groups_count': len(_CACHE.get('workcenter_groups') or []),
|
||||
'workcenter_mapping_count': len(_CACHE.get('workcenter_mapping') or {}),
|
||||
'resource_families_count': len(_CACHE.get('resource_families') or []),
|
||||
}
|
||||
|
||||
|
||||
def refresh_cache() -> bool:
|
||||
"""Force refresh the cache.
|
||||
|
||||
Returns:
|
||||
True if refresh succeeded, False otherwise
|
||||
"""
|
||||
return _load_cache()
|
||||
|
||||
|
||||
def _ensure_cache_loaded(force_refresh: bool = False):
|
||||
"""Ensure cache is loaded and not stale."""
|
||||
with _CACHE_LOCK:
|
||||
now = datetime.now()
|
||||
last_refresh = _CACHE.get('last_refresh')
|
||||
is_loading = _CACHE.get('is_loading', False)
|
||||
|
||||
# Check if cache is valid
|
||||
cache_valid = (
|
||||
last_refresh is not None and
|
||||
(now - last_refresh).total_seconds() < CACHE_TTL_SECONDS
|
||||
)
|
||||
|
||||
if cache_valid and not force_refresh:
|
||||
return
|
||||
|
||||
if is_loading:
|
||||
return # Another thread is loading
|
||||
|
||||
# Load cache (outside lock to avoid blocking)
|
||||
_load_cache()
|
||||
|
||||
|
||||
def _load_cache() -> bool:
|
||||
"""Load all cache data from database.
|
||||
|
||||
Returns:
|
||||
True if loading succeeded, False otherwise
|
||||
"""
|
||||
with _CACHE_LOCK:
|
||||
if _CACHE.get('is_loading'):
|
||||
return False
|
||||
_CACHE['is_loading'] = True
|
||||
|
||||
try:
|
||||
# Load workcenter groups from DW_PJ_LOT_V
|
||||
wc_groups, wc_mapping = _load_workcenter_data()
|
||||
|
||||
# Load resource families from DW_MES_RESOURCE
|
||||
families = _load_resource_families()
|
||||
|
||||
with _CACHE_LOCK:
|
||||
_CACHE['workcenter_groups'] = wc_groups
|
||||
_CACHE['workcenter_mapping'] = wc_mapping
|
||||
_CACHE['resource_families'] = families
|
||||
_CACHE['last_refresh'] = datetime.now()
|
||||
_CACHE['is_loading'] = False
|
||||
|
||||
logger.info(
|
||||
f"Filter cache refreshed: {len(wc_groups or [])} groups, "
|
||||
f"{len(wc_mapping or {})} workcenters, {len(families or [])} families"
|
||||
)
|
||||
return True
|
||||
|
||||
except Exception as exc:
|
||||
logger.error(f"Failed to load filter cache: {exc}")
|
||||
with _CACHE_LOCK:
|
||||
_CACHE['is_loading'] = False
|
||||
return False
|
||||
|
||||
|
||||
def _load_workcenter_data():
|
||||
"""Load workcenter group data from DW_PJ_LOT_V.
|
||||
|
||||
Returns:
|
||||
Tuple of (groups_list, mapping_dict)
|
||||
"""
|
||||
try:
|
||||
sql = f"""
|
||||
SELECT DISTINCT
|
||||
WORKCENTERNAME,
|
||||
WORKCENTERID,
|
||||
WORKCENTER_GROUP,
|
||||
WORKCENTERSEQUENCE_GROUP
|
||||
FROM {WIP_VIEW}
|
||||
WHERE WORKCENTER_GROUP IS NOT NULL
|
||||
AND WORKCENTERNAME IS NOT NULL
|
||||
"""
|
||||
df = read_sql_df(sql)
|
||||
|
||||
if df is None or df.empty:
|
||||
logger.warning("No workcenter data found in DW_PJ_LOT_V")
|
||||
return [], {}
|
||||
|
||||
# Build groups list (unique groups, take minimum sequence for each group)
|
||||
groups_df = df.groupby('WORKCENTER_GROUP')['WORKCENTERSEQUENCE_GROUP'].min().reset_index()
|
||||
groups_df = groups_df.sort_values('WORKCENTERSEQUENCE_GROUP')
|
||||
|
||||
groups = []
|
||||
for _, row in groups_df.iterrows():
|
||||
groups.append({
|
||||
'name': row['WORKCENTER_GROUP'],
|
||||
'sequence': int(row['WORKCENTERSEQUENCE_GROUP'] or 999)
|
||||
})
|
||||
|
||||
# Build mapping dict
|
||||
mapping = {}
|
||||
for _, row in df.iterrows():
|
||||
wc_name = row['WORKCENTERNAME']
|
||||
mapping[wc_name] = {
|
||||
'id': row.get('WORKCENTERID'),
|
||||
'group': row['WORKCENTER_GROUP'],
|
||||
'sequence': int(row['WORKCENTERSEQUENCE_GROUP'] or 999)
|
||||
}
|
||||
|
||||
return groups, mapping
|
||||
|
||||
except Exception as exc:
|
||||
logger.error(f"Failed to load workcenter data: {exc}")
|
||||
return [], {}
|
||||
|
||||
|
||||
def _load_resource_families():
|
||||
"""Load resource family data from DW_MES_RESOURCE.
|
||||
|
||||
Returns:
|
||||
Sorted list of family names
|
||||
"""
|
||||
try:
|
||||
# Build exclusion filters (note: column name is LOCATIONNAME, not LOCATION)
|
||||
location_list = ", ".join(f"'{loc}'" for loc in EXCLUDED_LOCATIONS)
|
||||
location_filter = f"AND (r.LOCATIONNAME IS NULL OR r.LOCATIONNAME NOT IN ({location_list}))" if EXCLUDED_LOCATIONS else ""
|
||||
|
||||
# Note: Column name is PJ_ASSETSSTATUS (double S), not ASSETSTATUS
|
||||
status_list = ", ".join(f"'{s}'" for s in EXCLUDED_ASSET_STATUSES)
|
||||
asset_status_filter = f"AND r.PJ_ASSETSSTATUS NOT IN ({status_list})" if EXCLUDED_ASSET_STATUSES else ""
|
||||
|
||||
sql = f"""
|
||||
SELECT DISTINCT RESOURCEFAMILYNAME
|
||||
FROM DW_MES_RESOURCE r
|
||||
WHERE {EQUIPMENT_TYPE_FILTER}
|
||||
{location_filter}
|
||||
{asset_status_filter}
|
||||
AND RESOURCEFAMILYNAME IS NOT NULL
|
||||
"""
|
||||
df = read_sql_df(sql)
|
||||
|
||||
if df is None or df.empty:
|
||||
logger.warning("No resource family data found")
|
||||
return []
|
||||
|
||||
families = df['RESOURCEFAMILYNAME'].dropna().unique().tolist()
|
||||
return sorted(families)
|
||||
|
||||
except Exception as exc:
|
||||
logger.error(f"Failed to load resource families: {exc}")
|
||||
return []
|
||||
|
||||
|
||||
# ============================================================
|
||||
# Initialization
|
||||
# ============================================================
|
||||
|
||||
def init_cache():
|
||||
"""Initialize the cache on application startup.
|
||||
|
||||
Should be called during app initialization.
|
||||
"""
|
||||
logger.info("Initializing filter cache...")
|
||||
_load_cache()
|
||||
844
src/mes_dashboard/services/resource_history_service.py
Normal file
844
src/mes_dashboard/services/resource_history_service.py
Normal file
@@ -0,0 +1,844 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
"""Resource History Analysis Service.
|
||||
|
||||
Provides functions for querying historical equipment performance data including:
|
||||
- Filter options (workcenters, families)
|
||||
- Summary data (KPI, trend, heatmap, workcenter comparison)
|
||||
- Hierarchical detail data (workcenter → family → resource)
|
||||
- CSV export with streaming
|
||||
"""
|
||||
|
||||
import io
|
||||
import csv
|
||||
import logging
|
||||
from concurrent.futures import ThreadPoolExecutor, as_completed
|
||||
from datetime import datetime, timedelta
|
||||
from typing import Optional, Dict, List, Any, Generator
|
||||
|
||||
import pandas as pd
|
||||
|
||||
from mes_dashboard.core.database import read_sql_df
|
||||
from mes_dashboard.config.constants import (
|
||||
EXCLUDED_LOCATIONS,
|
||||
EXCLUDED_ASSET_STATUSES,
|
||||
EQUIPMENT_TYPE_FILTER,
|
||||
EQUIPMENT_FLAG_FILTERS,
|
||||
)
|
||||
|
||||
logger = logging.getLogger('mes_dashboard.resource_history')
|
||||
|
||||
# Maximum allowed query range in days
|
||||
MAX_QUERY_DAYS = 730
|
||||
|
||||
# E10 Status definitions
|
||||
E10_STATUSES = ['PRD', 'SBY', 'UDT', 'SDT', 'EGT', 'NST']
|
||||
|
||||
|
||||
# ============================================================
|
||||
# Filter Options
|
||||
# ============================================================
|
||||
|
||||
def get_filter_options() -> Optional[Dict[str, Any]]:
|
||||
"""Get filter options from cache.
|
||||
|
||||
Uses cached workcenter groups from DW_PJ_LOT_V and resource families from DW_MES_RESOURCE.
|
||||
|
||||
Returns:
|
||||
Dict with:
|
||||
- 'workcenter_groups': List of {name, sequence} sorted by sequence
|
||||
- 'families': List of family names sorted alphabetically
|
||||
Or None if cache loading fails.
|
||||
"""
|
||||
from mes_dashboard.services.filter_cache import (
|
||||
get_workcenter_groups,
|
||||
get_resource_families,
|
||||
)
|
||||
|
||||
try:
|
||||
groups = get_workcenter_groups()
|
||||
families = get_resource_families()
|
||||
|
||||
if groups is None or families is None:
|
||||
logger.error("Filter cache not available")
|
||||
return None
|
||||
|
||||
return {
|
||||
'workcenter_groups': groups,
|
||||
'families': families
|
||||
}
|
||||
except Exception as exc:
|
||||
logger.error(f"Filter options query failed: {exc}")
|
||||
return None
|
||||
|
||||
|
||||
# ============================================================
|
||||
# Summary Query
|
||||
# ============================================================
|
||||
|
||||
def query_summary(
|
||||
start_date: str,
|
||||
end_date: str,
|
||||
granularity: str = 'day',
|
||||
workcenter_groups: Optional[List[str]] = None,
|
||||
families: Optional[List[str]] = None,
|
||||
is_production: bool = False,
|
||||
is_key: bool = False,
|
||||
is_monitor: bool = False,
|
||||
) -> Optional[Dict[str, Any]]:
|
||||
"""Query summary data including KPI, trend, heatmap, and workcenter comparison.
|
||||
|
||||
Args:
|
||||
start_date: Start date in YYYY-MM-DD format
|
||||
end_date: End date in YYYY-MM-DD format
|
||||
granularity: Time granularity ('day', 'week', 'month', 'year')
|
||||
workcenter_groups: Optional list of WORKCENTER_GROUP names to filter
|
||||
families: Optional list of RESOURCEFAMILYNAME values to filter
|
||||
is_production: Filter by production flag
|
||||
is_key: Filter by key equipment flag
|
||||
is_monitor: Filter by monitor flag
|
||||
|
||||
Returns:
|
||||
Dict with 'kpi', 'trend', 'heatmap', 'workcenter_comparison' sections,
|
||||
or None if query fails.
|
||||
"""
|
||||
# Validate date range
|
||||
validation = _validate_date_range(start_date, end_date)
|
||||
if validation:
|
||||
return {'error': validation}
|
||||
|
||||
try:
|
||||
# Build SQL components
|
||||
date_trunc = _get_date_trunc(granularity)
|
||||
location_filter = _build_location_filter('r')
|
||||
asset_status_filter = _build_asset_status_filter('r')
|
||||
equipment_filter = _build_equipment_flags_filter(is_production, is_key, is_monitor, 'r')
|
||||
workcenter_filter = _build_workcenter_groups_filter(workcenter_groups, 'r')
|
||||
family_filter = _build_families_filter(families, 'r')
|
||||
|
||||
# Common CTE with MATERIALIZE hint to force Oracle to materialize the subquery
|
||||
# This prevents the optimizer from inlining the CTE multiple times
|
||||
base_cte = f"""
|
||||
WITH shift_data AS (
|
||||
SELECT /*+ MATERIALIZE */ HISTORYID, TXNDATE, OLDSTATUSNAME, HOURS
|
||||
FROM DW_MES_RESOURCESTATUS_SHIFT
|
||||
WHERE TXNDATE >= TO_DATE('{start_date}', 'YYYY-MM-DD')
|
||||
AND TXNDATE < TO_DATE('{end_date}', 'YYYY-MM-DD') + 1
|
||||
)
|
||||
"""
|
||||
|
||||
# Common filter conditions
|
||||
common_filters = f"""
|
||||
WHERE {EQUIPMENT_TYPE_FILTER}
|
||||
{location_filter}
|
||||
{asset_status_filter}
|
||||
{equipment_filter}
|
||||
{workcenter_filter}
|
||||
{family_filter}
|
||||
"""
|
||||
|
||||
# Build all 4 SQL queries
|
||||
kpi_sql = f"""
|
||||
{base_cte}
|
||||
SELECT
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'PRD' THEN ss.HOURS ELSE 0 END) as PRD_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'SBY' THEN ss.HOURS ELSE 0 END) as SBY_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'UDT' THEN ss.HOURS ELSE 0 END) as UDT_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'SDT' THEN ss.HOURS ELSE 0 END) as SDT_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'EGT' THEN ss.HOURS ELSE 0 END) as EGT_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'NST' THEN ss.HOURS ELSE 0 END) as NST_HOURS,
|
||||
COUNT(DISTINCT ss.HISTORYID) as MACHINE_COUNT
|
||||
FROM shift_data ss
|
||||
JOIN DW_MES_RESOURCE r ON ss.HISTORYID = r.RESOURCEID
|
||||
{common_filters}
|
||||
"""
|
||||
|
||||
trend_sql = f"""
|
||||
{base_cte}
|
||||
SELECT
|
||||
{date_trunc} as DATA_DATE,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'PRD' THEN ss.HOURS ELSE 0 END) as PRD_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'SBY' THEN ss.HOURS ELSE 0 END) as SBY_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'UDT' THEN ss.HOURS ELSE 0 END) as UDT_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'SDT' THEN ss.HOURS ELSE 0 END) as SDT_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'EGT' THEN ss.HOURS ELSE 0 END) as EGT_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'NST' THEN ss.HOURS ELSE 0 END) as NST_HOURS,
|
||||
COUNT(DISTINCT ss.HISTORYID) as MACHINE_COUNT
|
||||
FROM shift_data ss
|
||||
JOIN DW_MES_RESOURCE r ON ss.HISTORYID = r.RESOURCEID
|
||||
{common_filters}
|
||||
GROUP BY {date_trunc}
|
||||
ORDER BY DATA_DATE
|
||||
"""
|
||||
|
||||
heatmap_sql = f"""
|
||||
{base_cte}
|
||||
SELECT
|
||||
r.WORKCENTERNAME,
|
||||
{date_trunc} as DATA_DATE,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'PRD' THEN ss.HOURS ELSE 0 END) as PRD_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'SBY' THEN ss.HOURS ELSE 0 END) as SBY_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'UDT' THEN ss.HOURS ELSE 0 END) as UDT_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'SDT' THEN ss.HOURS ELSE 0 END) as SDT_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'EGT' THEN ss.HOURS ELSE 0 END) as EGT_HOURS
|
||||
FROM shift_data ss
|
||||
JOIN DW_MES_RESOURCE r ON ss.HISTORYID = r.RESOURCEID
|
||||
WHERE r.WORKCENTERNAME IS NOT NULL
|
||||
AND {EQUIPMENT_TYPE_FILTER}
|
||||
{location_filter}
|
||||
{asset_status_filter}
|
||||
{equipment_filter}
|
||||
{workcenter_filter}
|
||||
{family_filter}
|
||||
GROUP BY r.WORKCENTERNAME, {date_trunc}
|
||||
ORDER BY r.WORKCENTERNAME, DATA_DATE
|
||||
"""
|
||||
|
||||
comparison_sql = f"""
|
||||
{base_cte}
|
||||
SELECT
|
||||
r.WORKCENTERNAME,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'PRD' THEN ss.HOURS ELSE 0 END) as PRD_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'SBY' THEN ss.HOURS ELSE 0 END) as SBY_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'UDT' THEN ss.HOURS ELSE 0 END) as UDT_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'SDT' THEN ss.HOURS ELSE 0 END) as SDT_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'EGT' THEN ss.HOURS ELSE 0 END) as EGT_HOURS,
|
||||
COUNT(DISTINCT ss.HISTORYID) as MACHINE_COUNT
|
||||
FROM shift_data ss
|
||||
JOIN DW_MES_RESOURCE r ON ss.HISTORYID = r.RESOURCEID
|
||||
WHERE r.WORKCENTERNAME IS NOT NULL
|
||||
AND {EQUIPMENT_TYPE_FILTER}
|
||||
{location_filter}
|
||||
{asset_status_filter}
|
||||
{equipment_filter}
|
||||
{workcenter_filter}
|
||||
{family_filter}
|
||||
GROUP BY r.WORKCENTERNAME
|
||||
ORDER BY PRD_HOURS DESC
|
||||
"""
|
||||
|
||||
# Execute all 4 queries in parallel using ThreadPoolExecutor
|
||||
results = {}
|
||||
with ThreadPoolExecutor(max_workers=4) as executor:
|
||||
futures = {
|
||||
executor.submit(read_sql_df, kpi_sql): 'kpi',
|
||||
executor.submit(read_sql_df, trend_sql): 'trend',
|
||||
executor.submit(read_sql_df, heatmap_sql): 'heatmap',
|
||||
executor.submit(read_sql_df, comparison_sql): 'comparison',
|
||||
}
|
||||
for future in as_completed(futures):
|
||||
query_name = futures[future]
|
||||
try:
|
||||
results[query_name] = future.result()
|
||||
except Exception as exc:
|
||||
logger.error(f"{query_name} query failed: {exc}")
|
||||
results[query_name] = pd.DataFrame()
|
||||
|
||||
# Build response from results
|
||||
kpi = _build_kpi_from_df(results.get('kpi', pd.DataFrame()))
|
||||
trend = _build_trend_from_df(results.get('trend', pd.DataFrame()), granularity)
|
||||
heatmap = _build_heatmap_from_df(results.get('heatmap', pd.DataFrame()), granularity)
|
||||
workcenter_comparison = _build_comparison_from_df(results.get('comparison', pd.DataFrame()))
|
||||
|
||||
return {
|
||||
'kpi': kpi,
|
||||
'trend': trend,
|
||||
'heatmap': heatmap,
|
||||
'workcenter_comparison': workcenter_comparison
|
||||
}
|
||||
except Exception as exc:
|
||||
logger.error(f"Summary query failed: {exc}")
|
||||
import traceback
|
||||
traceback.print_exc()
|
||||
return None
|
||||
|
||||
|
||||
# ============================================================
|
||||
# Detail Query
|
||||
# ============================================================
|
||||
|
||||
# Maximum records limit for detail query (disabled - no limit)
|
||||
# MAX_DETAIL_RECORDS = 5000
|
||||
|
||||
|
||||
def query_detail(
|
||||
start_date: str,
|
||||
end_date: str,
|
||||
granularity: str = 'day',
|
||||
workcenter_groups: Optional[List[str]] = None,
|
||||
families: Optional[List[str]] = None,
|
||||
is_production: bool = False,
|
||||
is_key: bool = False,
|
||||
is_monitor: bool = False,
|
||||
) -> Optional[Dict[str, Any]]:
|
||||
"""Query hierarchical detail data.
|
||||
|
||||
Returns flat data with workcenter, family, resource dimensions.
|
||||
Frontend handles hierarchy assembly.
|
||||
|
||||
Args:
|
||||
start_date: Start date in YYYY-MM-DD format
|
||||
end_date: End date in YYYY-MM-DD format
|
||||
granularity: Time granularity ('day', 'week', 'month', 'year')
|
||||
workcenter_groups: Optional list of WORKCENTER_GROUP names to filter
|
||||
families: Optional list of RESOURCEFAMILYNAME values to filter
|
||||
is_production: Filter by production flag
|
||||
is_key: Filter by key equipment flag
|
||||
is_monitor: Filter by monitor flag
|
||||
|
||||
Returns:
|
||||
Dict with 'data', 'total', 'truncated' fields,
|
||||
or None if query fails.
|
||||
"""
|
||||
# Validate date range
|
||||
validation = _validate_date_range(start_date, end_date)
|
||||
if validation:
|
||||
return {'error': validation}
|
||||
|
||||
try:
|
||||
# Build SQL components
|
||||
location_filter = _build_location_filter('r')
|
||||
asset_status_filter = _build_asset_status_filter('r')
|
||||
equipment_filter = _build_equipment_flags_filter(is_production, is_key, is_monitor, 'r')
|
||||
workcenter_filter = _build_workcenter_groups_filter(workcenter_groups, 'r')
|
||||
family_filter = _build_families_filter(families, 'r')
|
||||
|
||||
# Common CTE with MATERIALIZE hint
|
||||
base_cte = f"""
|
||||
WITH shift_data AS (
|
||||
SELECT /*+ MATERIALIZE */ HISTORYID, OLDSTATUSNAME, HOURS
|
||||
FROM DW_MES_RESOURCESTATUS_SHIFT
|
||||
WHERE TXNDATE >= TO_DATE('{start_date}', 'YYYY-MM-DD')
|
||||
AND TXNDATE < TO_DATE('{end_date}', 'YYYY-MM-DD') + 1
|
||||
)
|
||||
"""
|
||||
|
||||
# Common filter conditions
|
||||
common_filters = f"""
|
||||
WHERE {EQUIPMENT_TYPE_FILTER}
|
||||
{location_filter}
|
||||
{asset_status_filter}
|
||||
{equipment_filter}
|
||||
{workcenter_filter}
|
||||
{family_filter}
|
||||
"""
|
||||
|
||||
# Query all detail data (no pagination)
|
||||
detail_sql = f"""
|
||||
{base_cte}
|
||||
SELECT
|
||||
r.WORKCENTERNAME,
|
||||
r.RESOURCEFAMILYNAME,
|
||||
r.RESOURCENAME,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'PRD' THEN ss.HOURS ELSE 0 END) as PRD_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'SBY' THEN ss.HOURS ELSE 0 END) as SBY_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'UDT' THEN ss.HOURS ELSE 0 END) as UDT_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'SDT' THEN ss.HOURS ELSE 0 END) as SDT_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'EGT' THEN ss.HOURS ELSE 0 END) as EGT_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'NST' THEN ss.HOURS ELSE 0 END) as NST_HOURS,
|
||||
SUM(ss.HOURS) as TOTAL_HOURS
|
||||
FROM shift_data ss
|
||||
JOIN DW_MES_RESOURCE r ON ss.HISTORYID = r.RESOURCEID
|
||||
{common_filters}
|
||||
GROUP BY r.WORKCENTERNAME, r.RESOURCEFAMILYNAME, r.RESOURCENAME
|
||||
ORDER BY r.WORKCENTERNAME, r.RESOURCEFAMILYNAME, r.RESOURCENAME
|
||||
"""
|
||||
|
||||
detail_df = read_sql_df(detail_sql)
|
||||
total = len(detail_df) if detail_df is not None else 0
|
||||
|
||||
data = _build_detail_from_df(detail_df)
|
||||
|
||||
return {
|
||||
'data': data,
|
||||
'total': total,
|
||||
'truncated': False,
|
||||
'max_records': None
|
||||
}
|
||||
except Exception as exc:
|
||||
logger.error(f"Detail query failed: {exc}")
|
||||
import traceback
|
||||
traceback.print_exc()
|
||||
return None
|
||||
|
||||
|
||||
# ============================================================
|
||||
# CSV Export
|
||||
# ============================================================
|
||||
|
||||
def export_csv(
|
||||
start_date: str,
|
||||
end_date: str,
|
||||
granularity: str = 'day',
|
||||
workcenter_groups: Optional[List[str]] = None,
|
||||
families: Optional[List[str]] = None,
|
||||
is_production: bool = False,
|
||||
is_key: bool = False,
|
||||
is_monitor: bool = False,
|
||||
) -> Generator[str, None, None]:
|
||||
"""Generate CSV data as a stream for export.
|
||||
|
||||
Yields CSV rows one at a time to avoid memory issues with large datasets.
|
||||
|
||||
Args:
|
||||
start_date: Start date in YYYY-MM-DD format
|
||||
end_date: End date in YYYY-MM-DD format
|
||||
granularity: Time granularity
|
||||
workcenter_groups: Optional list of WORKCENTER_GROUP names to filter
|
||||
families: Optional list of RESOURCEFAMILYNAME values to filter
|
||||
is_production: Filter by production flag
|
||||
is_key: Filter by key equipment flag
|
||||
is_monitor: Filter by monitor flag
|
||||
|
||||
Yields:
|
||||
CSV rows as strings
|
||||
"""
|
||||
# Validate date range
|
||||
validation = _validate_date_range(start_date, end_date)
|
||||
if validation:
|
||||
yield f"Error: {validation}\n"
|
||||
return
|
||||
|
||||
try:
|
||||
# Build SQL components
|
||||
location_filter = _build_location_filter('r')
|
||||
asset_status_filter = _build_asset_status_filter('r')
|
||||
equipment_filter = _build_equipment_flags_filter(is_production, is_key, is_monitor, 'r')
|
||||
workcenter_filter = _build_workcenter_groups_filter(workcenter_groups, 'r')
|
||||
family_filter = _build_families_filter(families, 'r')
|
||||
|
||||
# Query all data with CTE and MATERIALIZE hint for performance optimization
|
||||
sql = f"""
|
||||
WITH shift_data AS (
|
||||
SELECT /*+ MATERIALIZE */ HISTORYID, OLDSTATUSNAME, HOURS
|
||||
FROM DW_MES_RESOURCESTATUS_SHIFT
|
||||
WHERE TXNDATE >= TO_DATE('{start_date}', 'YYYY-MM-DD')
|
||||
AND TXNDATE < TO_DATE('{end_date}', 'YYYY-MM-DD') + 1
|
||||
)
|
||||
SELECT
|
||||
r.WORKCENTERNAME,
|
||||
r.RESOURCEFAMILYNAME,
|
||||
r.RESOURCENAME,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'PRD' THEN ss.HOURS ELSE 0 END) as PRD_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'SBY' THEN ss.HOURS ELSE 0 END) as SBY_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'UDT' THEN ss.HOURS ELSE 0 END) as UDT_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'SDT' THEN ss.HOURS ELSE 0 END) as SDT_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'EGT' THEN ss.HOURS ELSE 0 END) as EGT_HOURS,
|
||||
SUM(CASE WHEN ss.OLDSTATUSNAME = 'NST' THEN ss.HOURS ELSE 0 END) as NST_HOURS,
|
||||
SUM(ss.HOURS) as TOTAL_HOURS
|
||||
FROM shift_data ss
|
||||
JOIN DW_MES_RESOURCE r ON ss.HISTORYID = r.RESOURCEID
|
||||
WHERE {EQUIPMENT_TYPE_FILTER}
|
||||
{location_filter}
|
||||
{asset_status_filter}
|
||||
{equipment_filter}
|
||||
{workcenter_filter}
|
||||
{family_filter}
|
||||
GROUP BY r.WORKCENTERNAME, r.RESOURCEFAMILYNAME, r.RESOURCENAME
|
||||
ORDER BY r.WORKCENTERNAME, r.RESOURCEFAMILYNAME, r.RESOURCENAME
|
||||
"""
|
||||
df = read_sql_df(sql)
|
||||
|
||||
# Get workcenter mapping to convert WORKCENTERNAME to WORKCENTER_GROUP
|
||||
from mes_dashboard.services.filter_cache import get_workcenter_mapping
|
||||
wc_mapping = get_workcenter_mapping() or {}
|
||||
|
||||
# Write CSV header
|
||||
output = io.StringIO()
|
||||
writer = csv.writer(output)
|
||||
headers = [
|
||||
'站點', '型號', '機台', 'OU%',
|
||||
'PRD(h)', 'PRD(%)', 'SBY(h)', 'SBY(%)',
|
||||
'UDT(h)', 'UDT(%)', 'SDT(h)', 'SDT(%)',
|
||||
'EGT(h)', 'EGT(%)', 'NST(h)', 'NST(%)'
|
||||
]
|
||||
writer.writerow(headers)
|
||||
yield output.getvalue()
|
||||
output.truncate(0)
|
||||
output.seek(0)
|
||||
|
||||
# Write data rows
|
||||
for _, row in df.iterrows():
|
||||
prd = float(row['PRD_HOURS'] or 0)
|
||||
sby = float(row['SBY_HOURS'] or 0)
|
||||
udt = float(row['UDT_HOURS'] or 0)
|
||||
sdt = float(row['SDT_HOURS'] or 0)
|
||||
egt = float(row['EGT_HOURS'] or 0)
|
||||
nst = float(row['NST_HOURS'] or 0)
|
||||
total = float(row['TOTAL_HOURS'] or 0)
|
||||
|
||||
# Map WORKCENTERNAME to WORKCENTER_GROUP
|
||||
wc_name = row['WORKCENTERNAME']
|
||||
wc_info = wc_mapping.get(wc_name, {})
|
||||
wc_group = wc_info.get('group', wc_name) # Fallback to workcentername if no mapping
|
||||
|
||||
# Calculate percentages
|
||||
ou_pct = _calc_ou_pct(prd, sby, udt, sdt, egt)
|
||||
prd_pct = round(prd / total * 100, 1) if total > 0 else 0
|
||||
sby_pct = round(sby / total * 100, 1) if total > 0 else 0
|
||||
udt_pct = round(udt / total * 100, 1) if total > 0 else 0
|
||||
sdt_pct = round(sdt / total * 100, 1) if total > 0 else 0
|
||||
egt_pct = round(egt / total * 100, 1) if total > 0 else 0
|
||||
nst_pct = round(nst / total * 100, 1) if total > 0 else 0
|
||||
|
||||
csv_row = [
|
||||
wc_group,
|
||||
row['RESOURCEFAMILYNAME'],
|
||||
row['RESOURCENAME'],
|
||||
f"{ou_pct}%",
|
||||
round(prd, 1), f"{prd_pct}%",
|
||||
round(sby, 1), f"{sby_pct}%",
|
||||
round(udt, 1), f"{udt_pct}%",
|
||||
round(sdt, 1), f"{sdt_pct}%",
|
||||
round(egt, 1), f"{egt_pct}%",
|
||||
round(nst, 1), f"{nst_pct}%"
|
||||
]
|
||||
writer.writerow(csv_row)
|
||||
yield output.getvalue()
|
||||
output.truncate(0)
|
||||
output.seek(0)
|
||||
|
||||
except Exception as exc:
|
||||
logger.error(f"CSV export failed: {exc}")
|
||||
yield f"Error: {exc}\n"
|
||||
|
||||
|
||||
# ============================================================
|
||||
# Helper Functions
|
||||
# ============================================================
|
||||
|
||||
def _validate_date_range(start_date: str, end_date: str) -> Optional[str]:
|
||||
"""Validate date range doesn't exceed MAX_QUERY_DAYS."""
|
||||
try:
|
||||
start = datetime.strptime(start_date, '%Y-%m-%d')
|
||||
end = datetime.strptime(end_date, '%Y-%m-%d')
|
||||
diff = (end - start).days
|
||||
|
||||
if diff > MAX_QUERY_DAYS:
|
||||
return f'查詢範圍不可超過 {MAX_QUERY_DAYS} 天（兩年）'
|
||||
if diff < 0:
|
||||
return '結束日期必須大於起始日期'
|
||||
return None
|
||||
except ValueError as e:
|
||||
return f'日期格式錯誤: {e}'
|
||||
|
||||
|
||||
def _get_date_trunc(granularity: str) -> str:
|
||||
"""Get Oracle TRUNC expression for date granularity."""
|
||||
trunc_map = {
|
||||
'day': "TRUNC(ss.TXNDATE)",
|
||||
'week': "TRUNC(ss.TXNDATE, 'IW')",
|
||||
'month': "TRUNC(ss.TXNDATE, 'MM')",
|
||||
'year': "TRUNC(ss.TXNDATE, 'YYYY')"
|
||||
}
|
||||
return trunc_map.get(granularity, "TRUNC(ss.TXNDATE)")
|
||||
|
||||
|
||||
def _build_location_filter(alias: str) -> str:
|
||||
"""Build SQL filter for excluded locations."""
|
||||
if not EXCLUDED_LOCATIONS:
|
||||
return ""
|
||||
excluded = "', '".join(EXCLUDED_LOCATIONS)
|
||||
return f"AND ({alias}.LOCATIONNAME IS NULL OR {alias}.LOCATIONNAME NOT IN ('{excluded}'))"
|
||||
|
||||
|
||||
def _build_asset_status_filter(alias: str) -> str:
|
||||
"""Build SQL filter for excluded asset statuses."""
|
||||
if not EXCLUDED_ASSET_STATUSES:
|
||||
return ""
|
||||
excluded = "', '".join(EXCLUDED_ASSET_STATUSES)
|
||||
return f"AND ({alias}.PJ_ASSETSSTATUS IS NULL OR {alias}.PJ_ASSETSSTATUS NOT IN ('{excluded}'))"
|
||||
|
||||
|
||||
def _build_equipment_flags_filter(
|
||||
is_production: bool,
|
||||
is_key: bool,
|
||||
is_monitor: bool,
|
||||
alias: str
|
||||
) -> str:
|
||||
"""Build SQL filter for equipment flags."""
|
||||
conditions = []
|
||||
if is_production:
|
||||
conditions.append(f"NVL({alias}.PJ_ISPRODUCTION, 0) = 1")
|
||||
if is_key:
|
||||
conditions.append(f"NVL({alias}.PJ_ISKEY, 0) = 1")
|
||||
if is_monitor:
|
||||
conditions.append(f"NVL({alias}.PJ_ISMONITOR, 0) = 1")
|
||||
return "AND " + " AND ".join(conditions) if conditions else ""
|
||||
|
||||
|
||||
def _build_workcenter_groups_filter(groups: Optional[List[str]], alias: str) -> str:
|
||||
"""Build SQL filter for workcenter groups.
|
||||
|
||||
Uses filter_cache to get workcentername list for selected groups.
|
||||
|
||||
Args:
|
||||
groups: List of WORKCENTER_GROUP names, or None for no filter
|
||||
alias: Table alias for WORKCENTERNAME column
|
||||
|
||||
Returns:
|
||||
SQL filter clause (empty string if no filter)
|
||||
"""
|
||||
if not groups:
|
||||
return ""
|
||||
|
||||
from mes_dashboard.services.filter_cache import get_workcenters_for_groups
|
||||
workcenters = get_workcenters_for_groups(groups)
|
||||
|
||||
if not workcenters:
|
||||
return ""
|
||||
|
||||
# Escape single quotes and build IN clause
|
||||
escaped = [wc.replace("'", "''") for wc in workcenters]
|
||||
in_list = "', '".join(escaped)
|
||||
return f"AND {alias}.WORKCENTERNAME IN ('{in_list}')"
|
||||
|
||||
|
||||
def _build_families_filter(families: Optional[List[str]], alias: str) -> str:
|
||||
"""Build SQL filter for resource families.
|
||||
|
||||
Args:
|
||||
families: List of RESOURCEFAMILYNAME values, or None for no filter
|
||||
alias: Table alias for RESOURCEFAMILYNAME column
|
||||
|
||||
Returns:
|
||||
SQL filter clause (empty string if no filter)
|
||||
"""
|
||||
if not families:
|
||||
return ""
|
||||
|
||||
# Escape single quotes and build IN clause
|
||||
escaped = [f.replace("'", "''") for f in families]
|
||||
in_list = "', '".join(escaped)
|
||||
return f"AND {alias}.RESOURCEFAMILYNAME IN ('{in_list}')"
|
||||
|
||||
|
||||
def _safe_float(value, default=0.0) -> float:
|
||||
"""Safely convert value to float, handling NaN and None."""
|
||||
if value is None or pd.isna(value):
|
||||
return default
|
||||
return float(value)
|
||||
|
||||
|
||||
def _calc_ou_pct(prd: float, sby: float, udt: float, sdt: float, egt: float) -> float:
|
||||
"""Calculate OU% = PRD / (PRD + SBY + UDT + SDT + EGT) * 100."""
|
||||
denominator = prd + sby + udt + sdt + egt
|
||||
return round(prd / denominator * 100, 1) if denominator > 0 else 0
|
||||
|
||||
|
||||
def _build_kpi_from_df(df: pd.DataFrame) -> Dict[str, Any]:
|
||||
"""Build KPI dict from query result DataFrame."""
|
||||
if df is None or len(df) == 0:
|
||||
return {
|
||||
'ou_pct': 0,
|
||||
'prd_hours': 0,
|
||||
'sby_hours': 0,
|
||||
'udt_hours': 0,
|
||||
'sdt_hours': 0,
|
||||
'egt_hours': 0,
|
||||
'nst_hours': 0,
|
||||
'machine_count': 0
|
||||
}
|
||||
|
||||
row = df.iloc[0]
|
||||
prd = _safe_float(row['PRD_HOURS'])
|
||||
sby = _safe_float(row['SBY_HOURS'])
|
||||
udt = _safe_float(row['UDT_HOURS'])
|
||||
sdt = _safe_float(row['SDT_HOURS'])
|
||||
egt = _safe_float(row['EGT_HOURS'])
|
||||
nst = _safe_float(row['NST_HOURS'])
|
||||
machine_count = int(_safe_float(row['MACHINE_COUNT']))
|
||||
|
||||
return {
|
||||
'ou_pct': _calc_ou_pct(prd, sby, udt, sdt, egt),
|
||||
'prd_hours': round(prd, 1),
|
||||
'sby_hours': round(sby, 1),
|
||||
'udt_hours': round(udt, 1),
|
||||
'sdt_hours': round(sdt, 1),
|
||||
'egt_hours': round(egt, 1),
|
||||
'nst_hours': round(nst, 1),
|
||||
'machine_count': machine_count
|
||||
}
|
||||
|
||||
|
||||
def _format_date(date_val, granularity: str) -> Optional[str]:
|
||||
"""Format date value based on granularity."""
|
||||
if pd.isna(date_val):
|
||||
return None
|
||||
|
||||
if granularity == 'year':
|
||||
return date_val.strftime('%Y')
|
||||
elif granularity == 'month':
|
||||
return date_val.strftime('%Y-%m')
|
||||
elif granularity == 'week':
|
||||
return date_val.strftime('%Y-%m-%d') # Week start date
|
||||
else:
|
||||
return date_val.strftime('%Y-%m-%d')
|
||||
|
||||
|
||||
def _build_trend_from_df(df: pd.DataFrame, granularity: str) -> List[Dict]:
|
||||
"""Build trend data from query result DataFrame."""
|
||||
if df is None or len(df) == 0:
|
||||
return []
|
||||
|
||||
result = []
|
||||
for _, row in df.iterrows():
|
||||
prd = _safe_float(row['PRD_HOURS'])
|
||||
sby = _safe_float(row['SBY_HOURS'])
|
||||
udt = _safe_float(row['UDT_HOURS'])
|
||||
sdt = _safe_float(row['SDT_HOURS'])
|
||||
egt = _safe_float(row['EGT_HOURS'])
|
||||
nst = _safe_float(row['NST_HOURS'])
|
||||
|
||||
result.append({
|
||||
'date': _format_date(row['DATA_DATE'], granularity),
|
||||
'ou_pct': _calc_ou_pct(prd, sby, udt, sdt, egt),
|
||||
'prd_hours': round(prd, 1),
|
||||
'sby_hours': round(sby, 1),
|
||||
'udt_hours': round(udt, 1),
|
||||
'sdt_hours': round(sdt, 1),
|
||||
'egt_hours': round(egt, 1),
|
||||
'nst_hours': round(nst, 1)
|
||||
})
|
||||
|
||||
return result
|
||||
|
||||
|
||||
def _build_heatmap_from_df(df: pd.DataFrame, granularity: str) -> List[Dict]:
|
||||
"""Build heatmap data from query result DataFrame."""
|
||||
if df is None or len(df) == 0:
|
||||
return []
|
||||
|
||||
# Get workcenter mapping to convert WORKCENTERNAME to WORKCENTER_GROUP
|
||||
from mes_dashboard.services.filter_cache import get_workcenter_mapping
|
||||
wc_mapping = get_workcenter_mapping() or {}
|
||||
|
||||
# Aggregate data by WORKCENTER_GROUP and date
|
||||
aggregated = {}
|
||||
for _, row in df.iterrows():
|
||||
wc_name = row['WORKCENTERNAME']
|
||||
# Skip rows with NaN workcenter name
|
||||
if pd.isna(wc_name):
|
||||
continue
|
||||
wc_info = wc_mapping.get(wc_name, {})
|
||||
wc_group = wc_info.get('group', wc_name)
|
||||
date_str = _format_date(row['DATA_DATE'], granularity)
|
||||
key = (wc_group, date_str)
|
||||
|
||||
if key not in aggregated:
|
||||
aggregated[key] = {'prd': 0, 'sby': 0, 'udt': 0, 'sdt': 0, 'egt': 0}
|
||||
|
||||
aggregated[key]['prd'] += _safe_float(row['PRD_HOURS'])
|
||||
aggregated[key]['sby'] += _safe_float(row['SBY_HOURS'])
|
||||
aggregated[key]['udt'] += _safe_float(row['UDT_HOURS'])
|
||||
aggregated[key]['sdt'] += _safe_float(row['SDT_HOURS'])
|
||||
aggregated[key]['egt'] += _safe_float(row['EGT_HOURS'])
|
||||
|
||||
result = []
|
||||
for (wc_group, date_str), data in aggregated.items():
|
||||
result.append({
|
||||
'workcenter': wc_group,
|
||||
'date': date_str,
|
||||
'ou_pct': _calc_ou_pct(data['prd'], data['sby'], data['udt'], data['sdt'], data['egt'])
|
||||
})
|
||||
|
||||
# Sort by workcenter and date
|
||||
result.sort(key=lambda x: (x['workcenter'], x['date'] or ''))
|
||||
return result
|
||||
|
||||
|
||||
def _build_comparison_from_df(df: pd.DataFrame) -> List[Dict]:
|
||||
"""Build workcenter comparison data from query result DataFrame."""
|
||||
if df is None or len(df) == 0:
|
||||
return []
|
||||
|
||||
# Get workcenter mapping to convert WORKCENTERNAME to WORKCENTER_GROUP
|
||||
from mes_dashboard.services.filter_cache import get_workcenter_mapping
|
||||
wc_mapping = get_workcenter_mapping() or {}
|
||||
|
||||
# Aggregate data by WORKCENTER_GROUP
|
||||
aggregated = {}
|
||||
for _, row in df.iterrows():
|
||||
wc_name = row['WORKCENTERNAME']
|
||||
# Skip rows with NaN workcenter name
|
||||
if pd.isna(wc_name):
|
||||
continue
|
||||
wc_info = wc_mapping.get(wc_name, {})
|
||||
wc_group = wc_info.get('group', wc_name)
|
||||
|
||||
if wc_group not in aggregated:
|
||||
aggregated[wc_group] = {'prd': 0, 'sby': 0, 'udt': 0, 'sdt': 0, 'egt': 0, 'machine_count': 0}
|
||||
|
||||
aggregated[wc_group]['prd'] += _safe_float(row['PRD_HOURS'])
|
||||
aggregated[wc_group]['sby'] += _safe_float(row['SBY_HOURS'])
|
||||
aggregated[wc_group]['udt'] += _safe_float(row['UDT_HOURS'])
|
||||
aggregated[wc_group]['sdt'] += _safe_float(row['SDT_HOURS'])
|
||||
aggregated[wc_group]['egt'] += _safe_float(row['EGT_HOURS'])
|
||||
aggregated[wc_group]['machine_count'] += int(_safe_float(row['MACHINE_COUNT']))
|
||||
|
||||
result = []
|
||||
for wc_group, data in aggregated.items():
|
||||
result.append({
|
||||
'workcenter': wc_group,
|
||||
'ou_pct': _calc_ou_pct(data['prd'], data['sby'], data['udt'], data['sdt'], data['egt']),
|
||||
'prd_hours': round(data['prd'], 1),
|
||||
'machine_count': data['machine_count']
|
||||
})
|
||||
|
||||
# Sort by OU% descending
|
||||
result.sort(key=lambda x: x['ou_pct'], reverse=True)
|
||||
return result
|
||||
|
||||
|
||||
def _build_detail_from_df(df: pd.DataFrame) -> List[Dict]:
|
||||
"""Build detail data from query result DataFrame."""
|
||||
if df is None or len(df) == 0:
|
||||
return []
|
||||
|
||||
# Get workcenter mapping to convert WORKCENTERNAME to WORKCENTER_GROUP
|
||||
from mes_dashboard.services.filter_cache import get_workcenter_mapping
|
||||
wc_mapping = get_workcenter_mapping() or {}
|
||||
|
||||
result = []
|
||||
for _, row in df.iterrows():
|
||||
# Skip rows with NaN workcenter name
|
||||
wc_name = row['WORKCENTERNAME']
|
||||
if pd.isna(wc_name):
|
||||
continue
|
||||
|
||||
prd = _safe_float(row['PRD_HOURS'])
|
||||
sby = _safe_float(row['SBY_HOURS'])
|
||||
udt = _safe_float(row['UDT_HOURS'])
|
||||
sdt = _safe_float(row['SDT_HOURS'])
|
||||
egt = _safe_float(row['EGT_HOURS'])
|
||||
nst = _safe_float(row['NST_HOURS'])
|
||||
total = _safe_float(row['TOTAL_HOURS'])
|
||||
|
||||
# Map WORKCENTERNAME to WORKCENTER_GROUP
|
||||
wc_info = wc_mapping.get(wc_name, {})
|
||||
wc_group = wc_info.get('group', wc_name) # Fallback to workcentername if no mapping
|
||||
|
||||
# Handle NaN in string fields
|
||||
family = row['RESOURCEFAMILYNAME']
|
||||
resource = row['RESOURCENAME']
|
||||
|
||||
result.append({
|
||||
'workcenter': wc_group,
|
||||
'family': family if not pd.isna(family) else '',
|
||||
'resource': resource if not pd.isna(resource) else '',
|
||||
'ou_pct': _calc_ou_pct(prd, sby, udt, sdt, egt),
|
||||
'prd_hours': round(prd, 1),
|
||||
'prd_pct': round(prd / total * 100, 1) if total > 0 else 0,
|
||||
'sby_hours': round(sby, 1),
|
||||
'sby_pct': round(sby / total * 100, 1) if total > 0 else 0,
|
||||
'udt_hours': round(udt, 1),
|
||||
'udt_pct': round(udt / total * 100, 1) if total > 0 else 0,
|
||||
'sdt_hours': round(sdt, 1),
|
||||
'sdt_pct': round(sdt / total * 100, 1) if total > 0 else 0,
|
||||
'egt_hours': round(egt, 1),
|
||||
'egt_pct': round(egt / total * 100, 1) if total > 0 else 0,
|
||||
'nst_hours': round(nst, 1),
|
||||
'nst_pct': round(nst / total * 100, 1) if total > 0 else 0,
|
||||
'machine_count': 1
|
||||
})
|
||||
|
||||
return result
|
||||
@@ -173,8 +173,18 @@ const MesApi = (function() {
|
||||
Toast.dismiss(loadingToastId);
|
||||
}
|
||||
|
||||
const data = await response.json();
|
||||
return data;
|
||||
try {
|
||||
const data = await response.json();
|
||||
return data;
|
||||
} catch (parseError) {
|
||||
// JSON parse error on successful response - don't retry
|
||||
console.error(`[MesApi] ${reqId} ✗ JSON parse failed:`, parseError.message);
|
||||
if (!silent) {
|
||||
Toast.error('回應資料解析失敗，資料量可能過大');
|
||||
}
|
||||
parseError.isParseError = true;
|
||||
throw parseError;
|
||||
}
|
||||
}
|
||||
|
||||
// Non-OK response
|
||||
@@ -205,6 +215,14 @@ const MesApi = (function() {
|
||||
throw error;
|
||||
}
|
||||
|
||||
// JSON parse error on successful response - don't retry
|
||||
if (error.isParseError) {
|
||||
if (loadingToastId) {
|
||||
Toast.dismiss(loadingToastId);
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
|
||||
lastError = error;
|
||||
}
|
||||
|
||||
|
||||
@@ -154,6 +154,9 @@
|
||||
{% if can_view_page('/excel-query') %}
|
||||
<button class="tab" data-target="excelQueryFrame">Excel 批次查詢</button>
|
||||
{% endif %}
|
||||
{% if can_view_page('/resource-history') %}
|
||||
<button class="tab" data-target="resourceHistoryFrame">機台歷史分析</button>
|
||||
{% endif %}
|
||||
</div>
|
||||
|
||||
<div class="panel">
|
||||
@@ -170,6 +173,9 @@
|
||||
{% if can_view_page('/excel-query') %}
|
||||
<iframe id="excelQueryFrame" data-src="/excel-query" title="Excel 批次查詢"></iframe>
|
||||
{% endif %}
|
||||
{% if can_view_page('/resource-history') %}
|
||||
<iframe id="resourceHistoryFrame" data-src="/resource-history" title="機台歷史分析"></iframe>
|
||||
{% endif %}
|
||||
</div>
|
||||
</div>
|
||||
{% endblock %}
|
||||
|
||||
1423
src/mes_dashboard/templates/resource_history.html
Normal file
1423
src/mes_dashboard/templates/resource_history.html
Normal file
File diff suppressed because it is too large
Load Diff
312
tests/e2e/test_resource_history_e2e.py
Normal file
312
tests/e2e/test_resource_history_e2e.py
Normal file
@@ -0,0 +1,312 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
"""End-to-end tests for resource history analysis page.
|
||||
|
||||
These tests simulate real user workflows through the resource history analysis feature.
|
||||
Run with: pytest tests/e2e/test_resource_history_e2e.py -v --run-integration
|
||||
"""
|
||||
|
||||
import json
|
||||
import pytest
|
||||
from unittest.mock import patch, MagicMock
|
||||
import pandas as pd
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
import sys
|
||||
import os
|
||||
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..', 'src'))
|
||||
|
||||
import mes_dashboard.core.database as db
|
||||
from mes_dashboard.app import create_app
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def app():
|
||||
"""Create application for testing."""
|
||||
db._ENGINE = None
|
||||
app = create_app('testing')
|
||||
app.config['TESTING'] = True
|
||||
return app
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def client(app):
|
||||
"""Create test client."""
|
||||
return app.test_client()
|
||||
|
||||
|
||||
class TestResourceHistoryPageAccess:
|
||||
"""E2E tests for page access and navigation."""
|
||||
|
||||
def test_page_loads_successfully(self, client):
|
||||
"""Resource history page should load without errors."""
|
||||
response = client.get('/resource-history')
|
||||
|
||||
assert response.status_code == 200
|
||||
content = response.data.decode('utf-8')
|
||||
assert '機台歷史表現分析' in content
|
||||
|
||||
def test_page_contains_filter_elements(self, client):
|
||||
"""Page should contain all filter elements."""
|
||||
response = client.get('/resource-history')
|
||||
content = response.data.decode('utf-8')
|
||||
|
||||
# Check for filter elements
|
||||
assert 'startDate' in content
|
||||
assert 'endDate' in content
|
||||
# Multi-select dropdowns
|
||||
assert 'workcenterGroupsDropdown' in content
|
||||
assert 'familiesDropdown' in content
|
||||
assert 'isProduction' in content
|
||||
assert 'isKey' in content
|
||||
assert 'isMonitor' in content
|
||||
|
||||
def test_page_contains_kpi_cards(self, client):
|
||||
"""Page should contain KPI card elements."""
|
||||
response = client.get('/resource-history')
|
||||
content = response.data.decode('utf-8')
|
||||
|
||||
assert 'kpiOuPct' in content
|
||||
assert 'kpiPrdHours' in content
|
||||
assert 'kpiUdtHours' in content
|
||||
assert 'kpiSdtHours' in content
|
||||
assert 'kpiEgtHours' in content
|
||||
assert 'kpiMachineCount' in content
|
||||
|
||||
def test_page_contains_chart_containers(self, client):
|
||||
"""Page should contain chart container elements."""
|
||||
response = client.get('/resource-history')
|
||||
content = response.data.decode('utf-8')
|
||||
|
||||
assert 'trendChart' in content
|
||||
assert 'stackedChart' in content
|
||||
assert 'comparisonChart' in content
|
||||
assert 'heatmapChart' in content
|
||||
|
||||
def test_page_contains_table_elements(self, client):
|
||||
"""Page should contain table elements."""
|
||||
response = client.get('/resource-history')
|
||||
content = response.data.decode('utf-8')
|
||||
|
||||
assert 'detailTableBody' in content
|
||||
assert 'expandAllBtn' in content
|
||||
assert 'collapseAllBtn' in content
|
||||
assert 'exportBtn' in content
|
||||
|
||||
|
||||
class TestResourceHistoryAPIWorkflow:
|
||||
"""E2E tests for API workflows."""
|
||||
|
||||
@patch('mes_dashboard.services.filter_cache.get_workcenter_groups')
|
||||
@patch('mes_dashboard.services.filter_cache.get_resource_families')
|
||||
def test_filter_options_workflow(self, mock_families, mock_groups, client):
|
||||
"""Filter options should be loadable."""
|
||||
mock_groups.return_value = [
|
||||
{'name': '焊接_DB', 'sequence': 1},
|
||||
{'name': '焊接_WB', 'sequence': 2},
|
||||
{'name': '成型', 'sequence': 4},
|
||||
]
|
||||
mock_families.return_value = ['FAM001', 'FAM002']
|
||||
|
||||
response = client.get('/api/resource/history/options')
|
||||
|
||||
assert response.status_code == 200
|
||||
data = json.loads(response.data)
|
||||
assert data['success'] is True
|
||||
assert 'workcenter_groups' in data['data']
|
||||
assert 'families' in data['data']
|
||||
|
||||
@patch('mes_dashboard.services.resource_history_service.read_sql_df')
|
||||
def test_complete_query_workflow(self, mock_read_sql, client):
|
||||
"""Complete query workflow should return all data sections."""
|
||||
# Mock responses for the 4 queries in query_summary
|
||||
kpi_df = pd.DataFrame([{
|
||||
'PRD_HOURS': 8000, 'SBY_HOURS': 1000, 'UDT_HOURS': 500,
|
||||
'SDT_HOURS': 300, 'EGT_HOURS': 200, 'NST_HOURS': 1000,
|
||||
'MACHINE_COUNT': 100
|
||||
}])
|
||||
|
||||
trend_df = pd.DataFrame([
|
||||
{'DATA_DATE': datetime(2024, 1, 1), 'PRD_HOURS': 1000, 'SBY_HOURS': 100,
|
||||
'UDT_HOURS': 50, 'SDT_HOURS': 30, 'EGT_HOURS': 20, 'NST_HOURS': 100, 'MACHINE_COUNT': 100},
|
||||
{'DATA_DATE': datetime(2024, 1, 2), 'PRD_HOURS': 1100, 'SBY_HOURS': 90,
|
||||
'UDT_HOURS': 40, 'SDT_HOURS': 25, 'EGT_HOURS': 15, 'NST_HOURS': 100, 'MACHINE_COUNT': 100},
|
||||
])
|
||||
|
||||
heatmap_df = pd.DataFrame([
|
||||
{'WORKCENTERNAME': '焊接_DB', 'DATA_DATE': datetime(2024, 1, 1),
|
||||
'PRD_HOURS': 400, 'SBY_HOURS': 50, 'UDT_HOURS': 25, 'SDT_HOURS': 15, 'EGT_HOURS': 10},
|
||||
{'WORKCENTERNAME': '成型', 'DATA_DATE': datetime(2024, 1, 1),
|
||||
'PRD_HOURS': 600, 'SBY_HOURS': 50, 'UDT_HOURS': 25, 'SDT_HOURS': 15, 'EGT_HOURS': 10},
|
||||
])
|
||||
|
||||
comparison_df = pd.DataFrame([
|
||||
{'WORKCENTERNAME': '焊接_DB', 'PRD_HOURS': 4000, 'SBY_HOURS': 500,
|
||||
'UDT_HOURS': 250, 'SDT_HOURS': 150, 'EGT_HOURS': 100, 'MACHINE_COUNT': 50},
|
||||
{'WORKCENTERNAME': '成型', 'PRD_HOURS': 4000, 'SBY_HOURS': 500,
|
||||
'UDT_HOURS': 250, 'SDT_HOURS': 150, 'EGT_HOURS': 100, 'MACHINE_COUNT': 50},
|
||||
])
|
||||
|
||||
# Use function-based side_effect for ThreadPoolExecutor parallel queries
|
||||
def mock_sql(sql):
|
||||
sql_upper = sql.upper()
|
||||
if 'DATA_DATE' in sql_upper and 'WORKCENTERNAME' in sql_upper:
|
||||
return heatmap_df
|
||||
elif 'DATA_DATE' in sql_upper:
|
||||
return trend_df
|
||||
elif 'WORKCENTERNAME' in sql_upper:
|
||||
return comparison_df
|
||||
else:
|
||||
return kpi_df
|
||||
|
||||
mock_read_sql.side_effect = mock_sql
|
||||
|
||||
response = client.get(
|
||||
'/api/resource/history/summary'
|
||||
'?start_date=2024-01-01'
|
||||
'&end_date=2024-01-07'
|
||||
'&granularity=day'
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
data = json.loads(response.data)
|
||||
assert data['success'] is True
|
||||
|
||||
# Verify KPI
|
||||
assert data['data']['kpi']['ou_pct'] == 80.0
|
||||
assert data['data']['kpi']['machine_count'] == 100
|
||||
|
||||
# Verify trend
|
||||
assert len(data['data']['trend']) == 2
|
||||
|
||||
# Verify heatmap
|
||||
assert len(data['data']['heatmap']) == 2
|
||||
|
||||
# Verify comparison
|
||||
assert len(data['data']['workcenter_comparison']) == 2
|
||||
|
||||
@patch('mes_dashboard.services.resource_history_service.read_sql_df')
|
||||
def test_detail_query_workflow(self, mock_read_sql, client):
|
||||
"""Detail query workflow should return hierarchical data."""
|
||||
detail_df = pd.DataFrame([
|
||||
{'WORKCENTERNAME': '焊接_DB', 'RESOURCEFAMILYNAME': 'FAM001', 'RESOURCENAME': 'RES001',
|
||||
'PRD_HOURS': 80, 'SBY_HOURS': 10, 'UDT_HOURS': 5, 'SDT_HOURS': 3, 'EGT_HOURS': 2,
|
||||
'NST_HOURS': 10, 'TOTAL_HOURS': 110},
|
||||
{'WORKCENTERNAME': '焊接_DB', 'RESOURCEFAMILYNAME': 'FAM001', 'RESOURCENAME': 'RES002',
|
||||
'PRD_HOURS': 75, 'SBY_HOURS': 15, 'UDT_HOURS': 5, 'SDT_HOURS': 3, 'EGT_HOURS': 2,
|
||||
'NST_HOURS': 10, 'TOTAL_HOURS': 110},
|
||||
])
|
||||
|
||||
mock_read_sql.return_value = detail_df
|
||||
|
||||
response = client.get(
|
||||
'/api/resource/history/detail'
|
||||
'?start_date=2024-01-01'
|
||||
'&end_date=2024-01-07'
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
data = json.loads(response.data)
|
||||
assert data['success'] is True
|
||||
assert data['total'] == 2
|
||||
assert len(data['data']) == 2
|
||||
assert data['truncated'] is False
|
||||
|
||||
# Verify data structure
|
||||
first_row = data['data'][0]
|
||||
assert 'workcenter' in first_row
|
||||
assert 'family' in first_row
|
||||
assert 'resource' in first_row
|
||||
assert 'ou_pct' in first_row
|
||||
assert 'prd_hours' in first_row
|
||||
assert 'prd_pct' in first_row
|
||||
|
||||
@patch('mes_dashboard.services.resource_history_service.read_sql_df')
|
||||
def test_export_workflow(self, mock_read_sql, client):
|
||||
"""Export workflow should return valid CSV."""
|
||||
mock_read_sql.return_value = pd.DataFrame([
|
||||
{'WORKCENTERNAME': '焊接_DB', 'RESOURCEFAMILYNAME': 'FAM001', 'RESOURCENAME': 'RES001',
|
||||
'PRD_HOURS': 80, 'SBY_HOURS': 10, 'UDT_HOURS': 5, 'SDT_HOURS': 3, 'EGT_HOURS': 2,
|
||||
'NST_HOURS': 10, 'TOTAL_HOURS': 110},
|
||||
])
|
||||
|
||||
response = client.get(
|
||||
'/api/resource/history/export'
|
||||
'?start_date=2024-01-01'
|
||||
'&end_date=2024-01-07'
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
assert 'text/csv' in response.content_type
|
||||
|
||||
content = response.data.decode('utf-8-sig')
|
||||
lines = content.strip().split('\n')
|
||||
|
||||
# Should have header + data rows
|
||||
assert len(lines) >= 2
|
||||
|
||||
# Verify header
|
||||
header = lines[0]
|
||||
assert '站點' in header
|
||||
assert 'OU%' in header
|
||||
|
||||
|
||||
class TestResourceHistoryValidation:
|
||||
"""E2E tests for input validation."""
|
||||
|
||||
def test_date_range_validation(self, client):
|
||||
"""Date range exceeding 730 days should be rejected."""
|
||||
response = client.get(
|
||||
'/api/resource/history/summary'
|
||||
'?start_date=2024-01-01'
|
||||
'&end_date=2026-01-02'
|
||||
)
|
||||
|
||||
assert response.status_code == 400
|
||||
data = json.loads(response.data)
|
||||
assert data['success'] is False
|
||||
assert '730' in data['error']
|
||||
|
||||
def test_missing_required_params(self, client):
|
||||
"""Missing required parameters should return error."""
|
||||
response = client.get('/api/resource/history/summary')
|
||||
|
||||
assert response.status_code == 400
|
||||
data = json.loads(response.data)
|
||||
assert data['success'] is False
|
||||
|
||||
@patch('mes_dashboard.services.resource_history_service.read_sql_df')
|
||||
def test_granularity_options(self, mock_read_sql, client):
|
||||
"""Different granularity options should work."""
|
||||
mock_df = pd.DataFrame([{
|
||||
'PRD_HOURS': 100, 'SBY_HOURS': 10, 'UDT_HOURS': 5,
|
||||
'SDT_HOURS': 3, 'EGT_HOURS': 2, 'NST_HOURS': 10, 'MACHINE_COUNT': 5
|
||||
}])
|
||||
mock_read_sql.return_value = mock_df
|
||||
|
||||
for granularity in ['day', 'week', 'month', 'year']:
|
||||
mock_read_sql.side_effect = [mock_df, pd.DataFrame(), pd.DataFrame(), pd.DataFrame()]
|
||||
|
||||
response = client.get(
|
||||
f'/api/resource/history/summary'
|
||||
f'?start_date=2024-01-01'
|
||||
f'&end_date=2024-01-31'
|
||||
f'&granularity={granularity}'
|
||||
)
|
||||
|
||||
assert response.status_code == 200, f"Failed for granularity={granularity}"
|
||||
|
||||
|
||||
class TestResourceHistoryNavigation:
|
||||
"""E2E tests for navigation integration."""
|
||||
|
||||
def test_portal_includes_history_tab(self, client):
|
||||
"""Portal should include resource history tab."""
|
||||
response = client.get('/')
|
||||
content = response.data.decode('utf-8')
|
||||
|
||||
assert '機台歷史分析' in content
|
||||
assert 'resourceHistoryFrame' in content
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
pytest.main([__file__, '-v'])
|
||||
297
tests/test_resource_history_routes.py
Normal file
297
tests/test_resource_history_routes.py
Normal file
@@ -0,0 +1,297 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
"""Integration tests for resource history API endpoints.
|
||||
|
||||
Tests API endpoints for proper response format, error handling,
|
||||
and parameter validation.
|
||||
"""
|
||||
|
||||
import unittest
|
||||
from unittest.mock import patch, MagicMock
|
||||
import json
|
||||
|
||||
import sys
|
||||
import os
|
||||
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
|
||||
|
||||
import mes_dashboard.core.database as db
|
||||
from mes_dashboard.app import create_app
|
||||
|
||||
|
||||
class TestResourceHistoryOptionsAPI(unittest.TestCase):
|
||||
"""Integration tests for /api/resource/history/options endpoint."""
|
||||
|
||||
def setUp(self):
|
||||
"""Set up test client."""
|
||||
db._ENGINE = None
|
||||
self.app = create_app('testing')
|
||||
self.app.config['TESTING'] = True
|
||||
self.client = self.app.test_client()
|
||||
|
||||
@patch('mes_dashboard.routes.resource_history_routes.get_filter_options')
|
||||
def test_options_success(self, mock_get_options):
|
||||
"""Successful options request should return workcenter_groups and families."""
|
||||
mock_get_options.return_value = {
|
||||
'workcenter_groups': [
|
||||
{'name': '焊接_DB', 'sequence': 1},
|
||||
{'name': '成型', 'sequence': 4}
|
||||
],
|
||||
'families': ['FAM01', 'FAM02']
|
||||
}
|
||||
|
||||
response = self.client.get('/api/resource/history/options')
|
||||
|
||||
self.assertEqual(response.status_code, 200)
|
||||
data = json.loads(response.data)
|
||||
self.assertTrue(data['success'])
|
||||
self.assertIn('data', data)
|
||||
self.assertEqual(len(data['data']['workcenter_groups']), 2)
|
||||
self.assertEqual(data['data']['workcenter_groups'][0]['name'], '焊接_DB')
|
||||
self.assertEqual(data['data']['families'], ['FAM01', 'FAM02'])
|
||||
|
||||
@patch('mes_dashboard.routes.resource_history_routes.get_filter_options')
|
||||
def test_options_failure(self, mock_get_options):
|
||||
"""Failed options request should return error."""
|
||||
mock_get_options.return_value = None
|
||||
|
||||
response = self.client.get('/api/resource/history/options')
|
||||
|
||||
self.assertEqual(response.status_code, 500)
|
||||
data = json.loads(response.data)
|
||||
self.assertFalse(data['success'])
|
||||
self.assertIn('error', data)
|
||||
|
||||
|
||||
class TestResourceHistorySummaryAPI(unittest.TestCase):
|
||||
"""Integration tests for /api/resource/history/summary endpoint."""
|
||||
|
||||
def setUp(self):
|
||||
"""Set up test client."""
|
||||
db._ENGINE = None
|
||||
self.app = create_app('testing')
|
||||
self.app.config['TESTING'] = True
|
||||
self.client = self.app.test_client()
|
||||
|
||||
def test_missing_start_date(self):
|
||||
"""Missing start_date should return 400."""
|
||||
response = self.client.get('/api/resource/history/summary?end_date=2024-01-31')
|
||||
|
||||
self.assertEqual(response.status_code, 400)
|
||||
data = json.loads(response.data)
|
||||
self.assertFalse(data['success'])
|
||||
self.assertIn('start_date', data['error'])
|
||||
|
||||
def test_missing_end_date(self):
|
||||
"""Missing end_date should return 400."""
|
||||
response = self.client.get('/api/resource/history/summary?start_date=2024-01-01')
|
||||
|
||||
self.assertEqual(response.status_code, 400)
|
||||
data = json.loads(response.data)
|
||||
self.assertFalse(data['success'])
|
||||
self.assertIn('end_date', data['error'])
|
||||
|
||||
@patch('mes_dashboard.routes.resource_history_routes.query_summary')
|
||||
def test_date_range_exceeds_limit(self, mock_query):
|
||||
"""Date range exceeding 730 days should return error."""
|
||||
mock_query.return_value = {'error': '查詢範圍不可超過 730 天（兩年）'}
|
||||
|
||||
response = self.client.get(
|
||||
'/api/resource/history/summary?start_date=2024-01-01&end_date=2026-01-02'
|
||||
)
|
||||
|
||||
self.assertEqual(response.status_code, 400)
|
||||
data = json.loads(response.data)
|
||||
self.assertFalse(data['success'])
|
||||
self.assertIn('730', data['error'])
|
||||
|
||||
@patch('mes_dashboard.routes.resource_history_routes.query_summary')
|
||||
def test_successful_summary(self, mock_query):
|
||||
"""Successful summary request should return all data sections."""
|
||||
mock_query.return_value = {
|
||||
'kpi': {
|
||||
'ou_pct': 80.0,
|
||||
'prd_hours': 800,
|
||||
'sby_hours': 100,
|
||||
'udt_hours': 50,
|
||||
'sdt_hours': 30,
|
||||
'egt_hours': 20,
|
||||
'nst_hours': 100,
|
||||
'machine_count': 10
|
||||
},
|
||||
'trend': [{'date': '2024-01-01', 'ou_pct': 80.0}],
|
||||
'heatmap': [{'workcenter': 'WC01', 'date': '2024-01-01', 'ou_pct': 80.0}],
|
||||
'workcenter_comparison': [{'workcenter': 'WC01', 'ou_pct': 80.0}]
|
||||
}
|
||||
|
||||
response = self.client.get(
|
||||
'/api/resource/history/summary?start_date=2024-01-01&end_date=2024-01-07'
|
||||
)
|
||||
|
||||
self.assertEqual(response.status_code, 200)
|
||||
data = json.loads(response.data)
|
||||
self.assertTrue(data['success'])
|
||||
self.assertIn('kpi', data['data'])
|
||||
self.assertIn('trend', data['data'])
|
||||
self.assertIn('heatmap', data['data'])
|
||||
self.assertIn('workcenter_comparison', data['data'])
|
||||
|
||||
@patch('mes_dashboard.routes.resource_history_routes.query_summary')
|
||||
def test_summary_with_filters(self, mock_query):
|
||||
"""Summary with filters should pass them to service."""
|
||||
mock_query.return_value = {'kpi': {}, 'trend': [], 'heatmap': [], 'workcenter_comparison': []}
|
||||
|
||||
response = self.client.get(
|
||||
'/api/resource/history/summary'
|
||||
'?start_date=2024-01-01'
|
||||
'&end_date=2024-01-07'
|
||||
'&granularity=week'
|
||||
'&workcenter_groups=焊接_DB'
|
||||
'&workcenter_groups=成型'
|
||||
'&families=FAM01'
|
||||
'&families=FAM02'
|
||||
'&is_production=1'
|
||||
'&is_key=1'
|
||||
)
|
||||
|
||||
self.assertEqual(response.status_code, 200)
|
||||
mock_query.assert_called_once()
|
||||
call_kwargs = mock_query.call_args[1]
|
||||
self.assertEqual(call_kwargs['granularity'], 'week')
|
||||
self.assertEqual(call_kwargs['workcenter_groups'], ['焊接_DB', '成型'])
|
||||
self.assertEqual(call_kwargs['families'], ['FAM01', 'FAM02'])
|
||||
self.assertTrue(call_kwargs['is_production'])
|
||||
self.assertTrue(call_kwargs['is_key'])
|
||||
|
||||
|
||||
class TestResourceHistoryDetailAPI(unittest.TestCase):
|
||||
"""Integration tests for /api/resource/history/detail endpoint."""
|
||||
|
||||
def setUp(self):
|
||||
"""Set up test client."""
|
||||
db._ENGINE = None
|
||||
self.app = create_app('testing')
|
||||
self.app.config['TESTING'] = True
|
||||
self.client = self.app.test_client()
|
||||
|
||||
def test_missing_dates(self):
|
||||
"""Missing dates should return 400."""
|
||||
response = self.client.get('/api/resource/history/detail')
|
||||
|
||||
self.assertEqual(response.status_code, 400)
|
||||
data = json.loads(response.data)
|
||||
self.assertFalse(data['success'])
|
||||
|
||||
@patch('mes_dashboard.routes.resource_history_routes.query_detail')
|
||||
def test_successful_detail(self, mock_query):
|
||||
"""Successful detail request should return data with total and truncated flag."""
|
||||
mock_query.return_value = {
|
||||
'data': [
|
||||
{'workcenter': 'WC01', 'family': 'FAM01', 'resource': 'RES01', 'ou_pct': 80.0}
|
||||
],
|
||||
'total': 100,
|
||||
'truncated': False,
|
||||
'max_records': None
|
||||
}
|
||||
|
||||
response = self.client.get(
|
||||
'/api/resource/history/detail?start_date=2024-01-01&end_date=2024-01-07'
|
||||
)
|
||||
|
||||
self.assertEqual(response.status_code, 200)
|
||||
data = json.loads(response.data)
|
||||
self.assertTrue(data['success'])
|
||||
self.assertIn('data', data)
|
||||
self.assertIn('total', data)
|
||||
self.assertIn('truncated', data)
|
||||
self.assertFalse(data['truncated'])
|
||||
|
||||
@patch('mes_dashboard.routes.resource_history_routes.query_detail')
|
||||
def test_detail_truncated_warning(self, mock_query):
|
||||
"""Detail with truncated data should return truncated flag and max_records."""
|
||||
mock_query.return_value = {
|
||||
'data': [{'workcenter': 'WC01', 'family': 'FAM01', 'resource': 'RES01', 'ou_pct': 80.0}],
|
||||
'total': 6000,
|
||||
'truncated': True,
|
||||
'max_records': 5000
|
||||
}
|
||||
|
||||
response = self.client.get(
|
||||
'/api/resource/history/detail'
|
||||
'?start_date=2024-01-01'
|
||||
'&end_date=2024-01-07'
|
||||
)
|
||||
|
||||
self.assertEqual(response.status_code, 200)
|
||||
data = json.loads(response.data)
|
||||
self.assertTrue(data['success'])
|
||||
self.assertTrue(data['truncated'])
|
||||
self.assertEqual(data['max_records'], 5000)
|
||||
self.assertEqual(data['total'], 6000)
|
||||
|
||||
|
||||
class TestResourceHistoryExportAPI(unittest.TestCase):
|
||||
"""Integration tests for /api/resource/history/export endpoint."""
|
||||
|
||||
def setUp(self):
|
||||
"""Set up test client."""
|
||||
db._ENGINE = None
|
||||
self.app = create_app('testing')
|
||||
self.app.config['TESTING'] = True
|
||||
self.client = self.app.test_client()
|
||||
|
||||
def test_missing_dates(self):
|
||||
"""Missing dates should return 400."""
|
||||
response = self.client.get('/api/resource/history/export')
|
||||
|
||||
self.assertEqual(response.status_code, 400)
|
||||
data = json.loads(response.data)
|
||||
self.assertFalse(data['success'])
|
||||
|
||||
@patch('mes_dashboard.routes.resource_history_routes.export_csv')
|
||||
def test_successful_export(self, mock_export):
|
||||
"""Successful export should return CSV with correct headers."""
|
||||
mock_export.return_value = iter(['站點,型號,機台,OU%\n', 'WC01,FAM01,RES01,80%\n'])
|
||||
|
||||
response = self.client.get(
|
||||
'/api/resource/history/export?start_date=2024-01-01&end_date=2024-01-07'
|
||||
)
|
||||
|
||||
self.assertEqual(response.status_code, 200)
|
||||
self.assertIn('text/csv', response.content_type)
|
||||
self.assertIn('attachment', response.headers['Content-Disposition'])
|
||||
self.assertIn('resource_history', response.headers['Content-Disposition'])
|
||||
|
||||
@patch('mes_dashboard.routes.resource_history_routes.export_csv')
|
||||
def test_export_filename_includes_dates(self, mock_export):
|
||||
"""Export filename should include date range."""
|
||||
mock_export.return_value = iter(['header\n'])
|
||||
|
||||
response = self.client.get(
|
||||
'/api/resource/history/export?start_date=2024-01-01&end_date=2024-01-07'
|
||||
)
|
||||
|
||||
self.assertIn('2024-01-01', response.headers['Content-Disposition'])
|
||||
self.assertIn('2024-01-07', response.headers['Content-Disposition'])
|
||||
|
||||
|
||||
class TestAPIContentType(unittest.TestCase):
|
||||
"""Test that APIs return proper content types."""
|
||||
|
||||
def setUp(self):
|
||||
"""Set up test client."""
|
||||
db._ENGINE = None
|
||||
self.app = create_app('testing')
|
||||
self.app.config['TESTING'] = True
|
||||
self.client = self.app.test_client()
|
||||
|
||||
@patch('mes_dashboard.routes.resource_history_routes.get_filter_options')
|
||||
def test_json_content_type(self, mock_get_options):
|
||||
"""API endpoints should return application/json content type."""
|
||||
mock_get_options.return_value = {'workcenter_groups': [], 'families': []}
|
||||
|
||||
response = self.client.get('/api/resource/history/options')
|
||||
|
||||
self.assertIn('application/json', response.content_type)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
||||
374
tests/test_resource_history_service.py
Normal file
374
tests/test_resource_history_service.py
Normal file
@@ -0,0 +1,374 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
"""Unit tests for resource_history_service.py.
|
||||
|
||||
Tests the service layer functions for resource history analysis.
|
||||
"""
|
||||
|
||||
import unittest
|
||||
from unittest.mock import patch, MagicMock
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
import pandas as pd
|
||||
|
||||
import sys
|
||||
import os
|
||||
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
|
||||
|
||||
from mes_dashboard.services.resource_history_service import (
|
||||
get_filter_options,
|
||||
query_summary,
|
||||
query_detail,
|
||||
export_csv,
|
||||
_validate_date_range,
|
||||
_get_date_trunc,
|
||||
_calc_ou_pct,
|
||||
_build_kpi_from_df,
|
||||
_build_detail_from_df,
|
||||
MAX_QUERY_DAYS,
|
||||
)
|
||||
|
||||
|
||||
class TestValidateDateRange(unittest.TestCase):
|
||||
"""Test date range validation."""
|
||||
|
||||
def test_valid_date_range(self):
|
||||
"""Valid date range should return None."""
|
||||
result = _validate_date_range('2024-01-01', '2024-01-31')
|
||||
self.assertIsNone(result)
|
||||
|
||||
def test_date_range_exceeds_max(self):
|
||||
"""Date range exceeding MAX_QUERY_DAYS should return error message."""
|
||||
result = _validate_date_range('2024-01-01', '2026-01-02')
|
||||
self.assertIsNotNone(result)
|
||||
self.assertIn('730', result)
|
||||
|
||||
def test_end_date_before_start_date(self):
|
||||
"""End date before start date should return error message."""
|
||||
result = _validate_date_range('2024-01-31', '2024-01-01')
|
||||
self.assertIsNotNone(result)
|
||||
self.assertIn('起始日期', result)
|
||||
|
||||
def test_invalid_date_format(self):
|
||||
"""Invalid date format should return error message."""
|
||||
result = _validate_date_range('invalid', '2024-01-01')
|
||||
self.assertIsNotNone(result)
|
||||
self.assertIn('日期格式錯誤', result)
|
||||
|
||||
|
||||
class TestGetDateTrunc(unittest.TestCase):
|
||||
"""Test date truncation SQL generation."""
|
||||
|
||||
def test_day_granularity(self):
|
||||
"""Day granularity should use TRUNC without format."""
|
||||
result = _get_date_trunc('day')
|
||||
self.assertIn('TRUNC(ss.TXNDATE)', result)
|
||||
self.assertNotIn('IW', result)
|
||||
|
||||
def test_week_granularity(self):
|
||||
"""Week granularity should use TRUNC with IW format."""
|
||||
result = _get_date_trunc('week')
|
||||
self.assertIn("'IW'", result)
|
||||
|
||||
def test_month_granularity(self):
|
||||
"""Month granularity should use TRUNC with MM format."""
|
||||
result = _get_date_trunc('month')
|
||||
self.assertIn("'MM'", result)
|
||||
|
||||
def test_year_granularity(self):
|
||||
"""Year granularity should use TRUNC with YYYY format."""
|
||||
result = _get_date_trunc('year')
|
||||
self.assertIn("'YYYY'", result)
|
||||
|
||||
def test_unknown_granularity(self):
|
||||
"""Unknown granularity should default to day."""
|
||||
result = _get_date_trunc('unknown')
|
||||
self.assertIn('TRUNC(ss.TXNDATE)', result)
|
||||
self.assertNotIn("'IW'", result)
|
||||
|
||||
|
||||
class TestCalcOuPct(unittest.TestCase):
|
||||
"""Test OU% calculation."""
|
||||
|
||||
def test_normal_calculation(self):
|
||||
"""OU% should be calculated correctly."""
|
||||
# PRD=800, SBY=100, UDT=50, SDT=30, EGT=20
|
||||
# OU% = 800 / (800+100+50+30+20) * 100 = 80%
|
||||
result = _calc_ou_pct(800, 100, 50, 30, 20)
|
||||
self.assertEqual(result, 80.0)
|
||||
|
||||
def test_zero_denominator(self):
|
||||
"""Zero denominator should return 0, not error."""
|
||||
result = _calc_ou_pct(0, 0, 0, 0, 0)
|
||||
self.assertEqual(result, 0)
|
||||
|
||||
def test_all_prd(self):
|
||||
"""100% PRD should result in 100% OU."""
|
||||
result = _calc_ou_pct(100, 0, 0, 0, 0)
|
||||
self.assertEqual(result, 100.0)
|
||||
|
||||
def test_no_prd(self):
|
||||
"""No PRD should result in 0% OU."""
|
||||
result = _calc_ou_pct(0, 100, 50, 30, 20)
|
||||
self.assertEqual(result, 0)
|
||||
|
||||
|
||||
class TestBuildKpiFromDf(unittest.TestCase):
|
||||
"""Test KPI building from DataFrame."""
|
||||
|
||||
def test_empty_dataframe(self):
|
||||
"""Empty DataFrame should return default KPI values."""
|
||||
df = pd.DataFrame()
|
||||
result = _build_kpi_from_df(df)
|
||||
|
||||
self.assertEqual(result['ou_pct'], 0)
|
||||
self.assertEqual(result['prd_hours'], 0)
|
||||
self.assertEqual(result['machine_count'], 0)
|
||||
|
||||
def test_normal_dataframe(self):
|
||||
"""Normal DataFrame should build correct KPI."""
|
||||
df = pd.DataFrame([{
|
||||
'PRD_HOURS': 800,
|
||||
'SBY_HOURS': 100,
|
||||
'UDT_HOURS': 50,
|
||||
'SDT_HOURS': 30,
|
||||
'EGT_HOURS': 20,
|
||||
'NST_HOURS': 100,
|
||||
'MACHINE_COUNT': 10
|
||||
}])
|
||||
result = _build_kpi_from_df(df)
|
||||
|
||||
self.assertEqual(result['ou_pct'], 80.0)
|
||||
self.assertEqual(result['prd_hours'], 800)
|
||||
self.assertEqual(result['machine_count'], 10)
|
||||
|
||||
def test_none_values_in_dataframe(self):
|
||||
"""None values should be treated as 0."""
|
||||
df = pd.DataFrame([{
|
||||
'PRD_HOURS': None,
|
||||
'SBY_HOURS': None,
|
||||
'UDT_HOURS': None,
|
||||
'SDT_HOURS': None,
|
||||
'EGT_HOURS': None,
|
||||
'NST_HOURS': None,
|
||||
'MACHINE_COUNT': None
|
||||
}])
|
||||
result = _build_kpi_from_df(df)
|
||||
|
||||
self.assertEqual(result['ou_pct'], 0)
|
||||
self.assertEqual(result['prd_hours'], 0)
|
||||
self.assertEqual(result['machine_count'], 0)
|
||||
|
||||
|
||||
class TestBuildDetailFromDf(unittest.TestCase):
|
||||
"""Test detail data building from DataFrame."""
|
||||
|
||||
def test_empty_dataframe(self):
|
||||
"""Empty DataFrame should return empty list."""
|
||||
df = pd.DataFrame()
|
||||
result = _build_detail_from_df(df)
|
||||
self.assertEqual(result, [])
|
||||
|
||||
def test_normal_dataframe(self):
|
||||
"""Normal DataFrame should build correct detail data."""
|
||||
df = pd.DataFrame([{
|
||||
'WORKCENTERNAME': 'WC01',
|
||||
'RESOURCEFAMILYNAME': 'FAM01',
|
||||
'RESOURCENAME': 'RES01',
|
||||
'PRD_HOURS': 80,
|
||||
'SBY_HOURS': 10,
|
||||
'UDT_HOURS': 5,
|
||||
'SDT_HOURS': 3,
|
||||
'EGT_HOURS': 2,
|
||||
'NST_HOURS': 10,
|
||||
'TOTAL_HOURS': 110
|
||||
}])
|
||||
result = _build_detail_from_df(df)
|
||||
|
||||
self.assertEqual(len(result), 1)
|
||||
self.assertEqual(result[0]['workcenter'], 'WC01')
|
||||
self.assertEqual(result[0]['family'], 'FAM01')
|
||||
self.assertEqual(result[0]['resource'], 'RES01')
|
||||
self.assertEqual(result[0]['machine_count'], 1)
|
||||
# OU% = 80 / (80+10+5+3+2) * 100 = 80%
|
||||
self.assertEqual(result[0]['ou_pct'], 80.0)
|
||||
|
||||
|
||||
class TestGetFilterOptions(unittest.TestCase):
|
||||
"""Test filter options retrieval."""
|
||||
|
||||
@patch('mes_dashboard.services.filter_cache.get_workcenter_groups')
|
||||
@patch('mes_dashboard.services.filter_cache.get_resource_families')
|
||||
def test_cache_failure(self, mock_families, mock_groups):
|
||||
"""Cache failure should return None."""
|
||||
mock_groups.return_value = None
|
||||
mock_families.return_value = None
|
||||
result = get_filter_options()
|
||||
self.assertIsNone(result)
|
||||
|
||||
@patch('mes_dashboard.services.filter_cache.get_workcenter_groups')
|
||||
@patch('mes_dashboard.services.filter_cache.get_resource_families')
|
||||
def test_successful_query(self, mock_families, mock_groups):
|
||||
"""Successful query should return workcenter groups and families."""
|
||||
mock_groups.return_value = [
|
||||
{'name': '焊接_DB', 'sequence': 1},
|
||||
{'name': '成型', 'sequence': 4},
|
||||
]
|
||||
mock_families.return_value = ['FAM01', 'FAM02']
|
||||
|
||||
result = get_filter_options()
|
||||
|
||||
self.assertIsNotNone(result)
|
||||
self.assertEqual(len(result['workcenter_groups']), 2)
|
||||
self.assertEqual(result['workcenter_groups'][0]['name'], '焊接_DB')
|
||||
self.assertEqual(result['families'], ['FAM01', 'FAM02'])
|
||||
|
||||
|
||||
class TestQuerySummary(unittest.TestCase):
|
||||
"""Test summary query function."""
|
||||
|
||||
def test_invalid_date_range(self):
|
||||
"""Invalid date range should return error."""
|
||||
result = query_summary(
|
||||
start_date='2024-01-01',
|
||||
end_date='2026-01-02', # More than 730 days
|
||||
granularity='day'
|
||||
)
|
||||
self.assertIsNotNone(result)
|
||||
self.assertIn('error', result)
|
||||
|
||||
@patch('mes_dashboard.services.resource_history_service.read_sql_df')
|
||||
def test_successful_query(self, mock_read_sql):
|
||||
"""Successful query should return all sections."""
|
||||
# Mock data for all queries
|
||||
kpi_df = pd.DataFrame([{
|
||||
'PRD_HOURS': 800, 'SBY_HOURS': 100, 'UDT_HOURS': 50,
|
||||
'SDT_HOURS': 30, 'EGT_HOURS': 20, 'NST_HOURS': 100,
|
||||
'MACHINE_COUNT': 10
|
||||
}])
|
||||
|
||||
trend_df = pd.DataFrame([{
|
||||
'DATA_DATE': datetime(2024, 1, 1),
|
||||
'PRD_HOURS': 100, 'SBY_HOURS': 10, 'UDT_HOURS': 5,
|
||||
'SDT_HOURS': 3, 'EGT_HOURS': 2, 'NST_HOURS': 10,
|
||||
'MACHINE_COUNT': 5
|
||||
}])
|
||||
|
||||
heatmap_df = pd.DataFrame([{
|
||||
'WORKCENTERNAME': 'WC01', 'DATA_DATE': datetime(2024, 1, 1),
|
||||
'PRD_HOURS': 80, 'SBY_HOURS': 10, 'UDT_HOURS': 5,
|
||||
'SDT_HOURS': 3, 'EGT_HOURS': 2
|
||||
}])
|
||||
|
||||
comparison_df = pd.DataFrame([{
|
||||
'WORKCENTERNAME': 'WC01',
|
||||
'PRD_HOURS': 800, 'SBY_HOURS': 100, 'UDT_HOURS': 50,
|
||||
'SDT_HOURS': 30, 'EGT_HOURS': 20, 'MACHINE_COUNT': 10
|
||||
}])
|
||||
|
||||
# Use a function to return appropriate mock based on SQL content
|
||||
# (ThreadPoolExecutor runs queries in parallel, so side_effect list is unreliable)
|
||||
def mock_sql(sql):
|
||||
sql_upper = sql.upper()
|
||||
if 'DATA_DATE' in sql_upper and 'WORKCENTERNAME' in sql_upper:
|
||||
return heatmap_df # heatmap has both DATA_DATE and WORKCENTERNAME
|
||||
elif 'DATA_DATE' in sql_upper:
|
||||
return trend_df # trend has DATA_DATE but no WORKCENTERNAME
|
||||
elif 'WORKCENTERNAME' in sql_upper:
|
||||
return comparison_df # comparison has WORKCENTERNAME but no DATA_DATE
|
||||
else:
|
||||
return kpi_df # kpi has neither
|
||||
|
||||
mock_read_sql.side_effect = mock_sql
|
||||
|
||||
result = query_summary(
|
||||
start_date='2024-01-01',
|
||||
end_date='2024-01-07',
|
||||
granularity='day'
|
||||
)
|
||||
|
||||
self.assertIsNotNone(result)
|
||||
self.assertIn('kpi', result)
|
||||
self.assertIn('trend', result)
|
||||
self.assertIn('heatmap', result)
|
||||
self.assertIn('workcenter_comparison', result)
|
||||
|
||||
|
||||
class TestQueryDetail(unittest.TestCase):
|
||||
"""Test detail query function."""
|
||||
|
||||
def test_invalid_date_range(self):
|
||||
"""Invalid date range should return error."""
|
||||
result = query_detail(
|
||||
start_date='2024-01-01',
|
||||
end_date='2026-01-02', # More than 730 days
|
||||
granularity='day'
|
||||
)
|
||||
self.assertIsNotNone(result)
|
||||
self.assertIn('error', result)
|
||||
|
||||
@patch('mes_dashboard.services.resource_history_service.read_sql_df')
|
||||
def test_successful_query(self, mock_read_sql):
|
||||
"""Successful query should return data with total count."""
|
||||
# Mock detail query
|
||||
detail_df = pd.DataFrame([{
|
||||
'WORKCENTERNAME': 'WC01',
|
||||
'RESOURCEFAMILYNAME': 'FAM01',
|
||||
'RESOURCENAME': 'RES01',
|
||||
'PRD_HOURS': 80, 'SBY_HOURS': 10, 'UDT_HOURS': 5,
|
||||
'SDT_HOURS': 3, 'EGT_HOURS': 2, 'NST_HOURS': 10,
|
||||
'TOTAL_HOURS': 110
|
||||
}])
|
||||
|
||||
mock_read_sql.return_value = detail_df
|
||||
|
||||
result = query_detail(
|
||||
start_date='2024-01-01',
|
||||
end_date='2024-01-07',
|
||||
granularity='day',
|
||||
)
|
||||
|
||||
self.assertIsNotNone(result)
|
||||
self.assertIn('data', result)
|
||||
self.assertIn('total', result)
|
||||
self.assertIn('truncated', result)
|
||||
self.assertEqual(result['total'], 1)
|
||||
self.assertFalse(result['truncated'])
|
||||
|
||||
|
||||
class TestExportCsv(unittest.TestCase):
|
||||
"""Test CSV export function."""
|
||||
|
||||
def test_invalid_date_range(self):
|
||||
"""Invalid date range should yield error."""
|
||||
result = list(export_csv(
|
||||
start_date='2024-01-01',
|
||||
end_date='2026-01-02', # More than 730 days
|
||||
))
|
||||
self.assertTrue(any('Error' in r for r in result))
|
||||
|
||||
@patch('mes_dashboard.services.resource_history_service.read_sql_df')
|
||||
def test_successful_export(self, mock_read_sql):
|
||||
"""Successful export should yield CSV rows."""
|
||||
mock_read_sql.return_value = pd.DataFrame([{
|
||||
'WORKCENTERNAME': 'WC01',
|
||||
'RESOURCEFAMILYNAME': 'FAM01',
|
||||
'RESOURCENAME': 'RES01',
|
||||
'PRD_HOURS': 80, 'SBY_HOURS': 10, 'UDT_HOURS': 5,
|
||||
'SDT_HOURS': 3, 'EGT_HOURS': 2, 'NST_HOURS': 10,
|
||||
'TOTAL_HOURS': 110
|
||||
}])
|
||||
|
||||
result = list(export_csv(
|
||||
start_date='2024-01-01',
|
||||
end_date='2024-01-07',
|
||||
))
|
||||
|
||||
# Should have header row + data row
|
||||
self.assertGreaterEqual(len(result), 2)
|
||||
# Header should contain column names
|
||||
self.assertIn('站點', result[0])
|
||||
self.assertIn('OU%', result[0])
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
unittest.main()
|
||||
Reference in New Issue
Block a user