refactor: 統一設備維度資料來源至 resource_cache
- 重構 resource_history_service 使用 resource_cache 作為設備主檔來源 - 移除 Oracle JOIN，改用 HISTORYID IN 過濾 SHIFT 資料 - 新增 _get_filtered_resources、_build_resource_lookup 等輔助函數 - resource_cache 新增 WORKCENTERNAME IS NOT NULL 篩選條件 - 設備即時概況矩陣新增可點選篩選功能 - 新增 _clean_nan_values 處理 JSON 序列化 NaN/NaT 值 Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
beabigegg
@@ -4,10 +4,43 @@
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Contains Flask Blueprint for resource/equipment-related API endpoints.
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"""
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import math
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from flask import Blueprint, jsonify, request
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from mes_dashboard.core.database import get_db_connection
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from mes_dashboard.core.cache import cache_get, cache_set, make_cache_key
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def _clean_nan_values(data):
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"""Convert NaN and NaT values to None for JSON serialization.
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Args:
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data: List of dicts or single dict.
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Returns:
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Cleaned data with NaN/NaT replaced by None.
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"""
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if isinstance(data, list):
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return [_clean_nan_values(item) for item in data]
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elif isinstance(data, dict):
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cleaned = {}
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for key, value in data.items():
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if isinstance(value, float) and math.isnan(value):
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cleaned[key] = None
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elif isinstance(value, str) and value == 'NaT':
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cleaned[key] = None
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elif value != value: # NaN check (NaN != NaN)
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cleaned[key] = None
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elif isinstance(value, list):
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# Recursively clean nested lists (e.g., LOT_DETAILS)
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cleaned[key] = _clean_nan_values(value)
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elif isinstance(value, dict):
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# Recursively clean nested dicts
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cleaned[key] = _clean_nan_values(value)
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else:
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cleaned[key] = value
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return cleaned
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return data
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from mes_dashboard.core.utils import get_days_back
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from mes_dashboard.services.resource_service import (
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query_resource_status_summary,
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@@ -202,10 +235,12 @@ def api_resource_status():
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is_monitor=is_monitor,
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status_categories=status_categories,
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)
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# Clean NaN/NaT values for valid JSON
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cleaned_data = _clean_nan_values(data)
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return jsonify({
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'success': True,
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'data': data,
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'count': len(data),
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'data': cleaned_data,
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'count': len(cleaned_data),
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})
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except Exception as exc:
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return jsonify({'success': False, 'error': str(exc)}), 500
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@@ -264,7 +299,9 @@ def api_resource_status_summary():
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is_key=is_key,
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is_monitor=is_monitor,
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)
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return jsonify({'success': True, 'data': data})
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# Clean NaN/NaT values for valid JSON
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cleaned_data = _clean_nan_values(data)
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return jsonify({'success': True, 'data': cleaned_data})
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except Exception as exc:
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return jsonify({'success': False, 'error': str(exc)}), 500
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@@ -299,6 +336,8 @@ def api_resource_status_matrix():
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is_key=is_key,
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is_monitor=is_monitor,
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)
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return jsonify({'success': True, 'data': data})
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# Clean NaN/NaT values for valid JSON
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cleaned_data = _clean_nan_values(data)
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return jsonify({'success': True, 'data': cleaned_data})
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except Exception as exc:
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return jsonify({'success': False, 'error': str(exc)}), 500
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@@ -109,12 +109,35 @@ def _classify_status(status: Optional[str]) -> str:
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return STATUS_CATEGORY_MAP.get(status, 'OTHER')
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def _is_valid_value(value) -> bool:
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"""Check if a value is valid (not None, not NaN, not empty string).
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Args:
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value: The value to check.
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Returns:
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True if valid, False otherwise.
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"""
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if value is None:
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return False
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if isinstance(value, str) and (not value.strip() or value == 'NaT'):
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return False
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# Check for NaN (pandas NaN or float NaN)
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try:
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if value != value: # NaN != NaN is True
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return False
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except (TypeError, ValueError):
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pass
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return True
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def _aggregate_by_resourceid(records: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
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"""Aggregate equipment status records by RESOURCEID.
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For each RESOURCEID:
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- Status fields: take first (should be same for all records)
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- LOT_COUNT: count of records
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- LOT_COUNT: count of distinct RUNCARDLOTID values
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- LOT_DETAILS: list of LOT information for tooltip display
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- TOTAL_TRACKIN_QTY: sum of LOTTRACKINQTY_PCS
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- LATEST_TRACKIN_TIME: max of LOTTRACKINTIME
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@@ -141,12 +164,29 @@ def _aggregate_by_resourceid(records: List[Dict[str, Any]]) -> List[Dict[str, An
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for resource_id, group in grouped.items():
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first = group[0]
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# Calculate aggregates
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lot_count = len(group)
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total_qty = sum(
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r.get('LOTTRACKINQTY_PCS') or 0
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for r in group
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)
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# Collect unique LOTs by RUNCARDLOTID
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seen_lots = set()
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lot_details = []
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total_qty = 0
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for r in group:
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lot_id = r.get('RUNCARDLOTID')
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qty = r.get('LOTTRACKINQTY_PCS')
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# Sum only valid quantities
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if _is_valid_value(qty):
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total_qty += qty
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# Only add unique LOTs with valid RUNCARDLOTID
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if _is_valid_value(lot_id) and lot_id not in seen_lots:
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seen_lots.add(lot_id)
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trackin_time = r.get('LOTTRACKINTIME')
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trackin_employee = r.get('LOTTRACKINEMPLOYEE')
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lot_details.append({
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'RUNCARDLOTID': lot_id,
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'LOTTRACKINQTY_PCS': qty if _is_valid_value(qty) else None,
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'LOTTRACKINTIME': trackin_time if _is_valid_value(trackin_time) else None,
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'LOTTRACKINEMPLOYEE': trackin_employee if _is_valid_value(trackin_employee) else None,
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})
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# Find latest trackin time
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trackin_times = [
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@@ -170,7 +210,8 @@ def _aggregate_by_resourceid(records: List[Dict[str, Any]]) -> List[Dict[str, An
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'SYMPTOMCODE': first.get('SYMPTOMCODE'),
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'CAUSECODE': first.get('CAUSECODE'),
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'REPAIRCODE': first.get('REPAIRCODE'),
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'LOT_COUNT': lot_count,
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'LOT_COUNT': len(seen_lots), # Count distinct RUNCARDLOTID
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'LOT_DETAILS': lot_details, # LOT details for tooltip
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'TOTAL_TRACKIN_QTY': total_qty,
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'LATEST_TRACKIN_TIME': latest_trackin,
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})
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@@ -52,6 +52,9 @@ def _build_filter_sql() -> str:
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"""Build SQL WHERE clause for global filters."""
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conditions = [EQUIPMENT_TYPE_FILTER.strip()]
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# Workcenter filter - exclude resources without WORKCENTERNAME
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conditions.append("WORKCENTERNAME IS NOT NULL")
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# Location filter
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if EXCLUDED_LOCATIONS:
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locations_list = ", ".join(f"'{loc}'" for loc in EXCLUDED_LOCATIONS)
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@@ -6,24 +6,23 @@ Provides functions for querying historical equipment performance data including:
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- Summary data (KPI, trend, heatmap, workcenter comparison)
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- Hierarchical detail data (workcenter → family → resource)
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- CSV export with streaming
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Architecture:
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- Uses resource_cache as the single source of truth for equipment master data
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- Queries DW_MES_RESOURCESTATUS_SHIFT only for valid cached resource IDs
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- Merges dimension data (WORKCENTERNAME, RESOURCEFAMILYNAME, etc.) from cache
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"""
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import io
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import csv
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import logging
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from datetime import datetime, timedelta
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from datetime import datetime
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from typing import Optional, Dict, List, Any, Generator
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import pandas as pd
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from mes_dashboard.core.database import read_sql_df
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from mes_dashboard.config.constants import (
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EXCLUDED_LOCATIONS,
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EXCLUDED_ASSET_STATUSES,
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EQUIPMENT_TYPE_FILTER,
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EQUIPMENT_FLAG_FILTERS,
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)
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logger = logging.getLogger('mes_dashboard.resource_history')
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@@ -34,6 +33,139 @@ MAX_QUERY_DAYS = 730
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E10_STATUSES = ['PRD', 'SBY', 'UDT', 'SDT', 'EGT', 'NST']
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# ============================================================
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# Resource Cache Integration
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# ============================================================
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def _get_filtered_resources(
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workcenter_groups: Optional[List[str]] = None,
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families: Optional[List[str]] = None,
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is_production: bool = False,
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is_key: bool = False,
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is_monitor: bool = False,
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) -> List[Dict[str, Any]]:
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"""Get filtered resources from resource_cache.
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Applies additional filters on top of the cache's pre-applied global filters.
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Args:
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workcenter_groups: Optional list of WORKCENTER_GROUP names
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families: Optional list of RESOURCEFAMILYNAME values
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is_production: Filter by production flag
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is_key: Filter by key equipment flag
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is_monitor: Filter by monitor flag
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Returns:
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List of resource dicts matching the filters.
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"""
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from mes_dashboard.services.resource_cache import get_all_resources
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from mes_dashboard.services.filter_cache import get_workcenter_mapping
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resources = get_all_resources()
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if not resources:
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logger.warning("No resources available from cache")
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return []
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# Get workcenter mapping for group filtering
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wc_mapping = get_workcenter_mapping() or {}
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# Build set of workcenters if filtering by groups
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allowed_workcenters = None
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if workcenter_groups:
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allowed_workcenters = set()
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for wc_name, info in wc_mapping.items():
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if info.get('group') in workcenter_groups:
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allowed_workcenters.add(wc_name)
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# Apply filters
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filtered = []
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for r in resources:
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# Workcenter group filter
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if allowed_workcenters is not None:
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if r.get('WORKCENTERNAME') not in allowed_workcenters:
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continue
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# Family filter
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if families and r.get('RESOURCEFAMILYNAME') not in families:
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continue
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# Equipment flags filter
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if is_production and r.get('PJ_ISPRODUCTION') != 1:
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continue
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if is_key and r.get('PJ_ISKEY') != 1:
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continue
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if is_monitor and r.get('PJ_ISMONITOR') != 1:
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continue
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filtered.append(r)
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logger.debug(f"Filtered {len(resources)} resources to {len(filtered)}")
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return filtered
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def _build_resource_lookup(resources: List[Dict[str, Any]]) -> Dict[str, Dict[str, Any]]:
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"""Build a lookup dict from RESOURCEID to resource info.
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Args:
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resources: List of resource dicts from cache.
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Returns:
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Dict mapping RESOURCEID to resource dict.
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"""
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return {r['RESOURCEID']: r for r in resources if r.get('RESOURCEID')}
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def _get_resource_ids_sql_list(resources: List[Dict[str, Any]], max_chunk_size: int = 1000) -> List[str]:
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"""Build SQL IN clause lists for resource IDs.
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Oracle has a limit of ~1000 items per IN clause, so we chunk if needed.
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Args:
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resources: List of resource dicts.
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max_chunk_size: Maximum items per IN clause.
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Returns:
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List of SQL IN clause strings (e.g., "'ID1', 'ID2', 'ID3'").
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"""
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resource_ids = [r['RESOURCEID'] for r in resources if r.get('RESOURCEID')]
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if not resource_ids:
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return []
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# Escape single quotes
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escaped_ids = [rid.replace("'", "''") for rid in resource_ids]
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# Chunk into groups
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chunks = []
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for i in range(0, len(escaped_ids), max_chunk_size):
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chunk = escaped_ids[i:i + max_chunk_size]
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chunks.append("'" + "', '".join(chunk) + "'")
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return chunks
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def _build_historyid_filter(resources: List[Dict[str, Any]]) -> str:
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"""Build SQL WHERE clause for HISTORYID filtering.
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Handles chunking for large resource lists.
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Args:
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resources: List of resource dicts.
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Returns:
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SQL condition string (e.g., "HISTORYID IN ('ID1', 'ID2') OR HISTORYID IN ('ID3', 'ID4')").
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"""
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chunks = _get_resource_ids_sql_list(resources)
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if not chunks:
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return "1=0" # No resources = no results
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if len(chunks) == 1:
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return f"HISTORYID IN ({chunks[0]})"
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# Multiple chunks need OR
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conditions = [f"HISTORYID IN ({chunk})" for chunk in chunks]
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return "(" + " OR ".join(conditions) + ")"
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# ============================================================
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# Filter Options
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# ============================================================
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@@ -85,6 +217,9 @@ def query_summary(
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) -> Optional[Dict[str, Any]]:
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"""Query summary data including KPI, trend, heatmap, and workcenter comparison.
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Uses resource_cache as the source for equipment master data.
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Queries only DW_MES_RESOURCESTATUS_SHIFT for SHIFT data.
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Args:
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start_date: Start date in YYYY-MM-DD format
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end_date: End date in YYYY-MM-DD format
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@@ -105,123 +240,96 @@ def query_summary(
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return {'error': validation}
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try:
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# Get filtered resources from cache
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resources = _get_filtered_resources(
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workcenter_groups=workcenter_groups,
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families=families,
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is_production=is_production,
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is_key=is_key,
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is_monitor=is_monitor,
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)
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if not resources:
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logger.warning("No resources match the filter criteria")
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return {
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'kpi': _build_kpi_from_df(pd.DataFrame()),
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'trend': [],
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'heatmap': [],
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'workcenter_comparison': []
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}
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# Build resource lookup for dimension merging
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resource_lookup = _build_resource_lookup(resources)
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historyid_filter = _build_historyid_filter(resources)
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# Build SQL components
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date_trunc = _get_date_trunc(granularity)
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location_filter = _build_location_filter('r')
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asset_status_filter = _build_asset_status_filter('r')
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equipment_filter = _build_equipment_flags_filter(is_production, is_key, is_monitor, 'r')
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workcenter_filter = _build_workcenter_groups_filter(workcenter_groups, 'r')
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family_filter = _build_families_filter(families, 'r')
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# Common CTE with MATERIALIZE hint to force Oracle to materialize the subquery
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# This prevents the optimizer from inlining the CTE multiple times
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# Base CTE with resource filter
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base_cte = f"""
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WITH shift_data AS (
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SELECT /*+ MATERIALIZE */ HISTORYID, TXNDATE, OLDSTATUSNAME, HOURS
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FROM DWH.DW_MES_RESOURCESTATUS_SHIFT
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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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AND {historyid_filter}
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)
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"""
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# Common filter conditions
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common_filters = f"""
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WHERE {EQUIPMENT_TYPE_FILTER}
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{location_filter}
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{asset_status_filter}
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{equipment_filter}
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{workcenter_filter}
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{family_filter}
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"""
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# Build all 4 SQL queries
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# KPI query - aggregate all
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kpi_sql = f"""
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{base_cte}
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SELECT
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SUM(CASE WHEN ss.OLDSTATUSNAME = 'PRD' THEN ss.HOURS ELSE 0 END) as PRD_HOURS,
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SUM(CASE WHEN ss.OLDSTATUSNAME = 'SBY' THEN ss.HOURS ELSE 0 END) as SBY_HOURS,
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SUM(CASE WHEN ss.OLDSTATUSNAME = 'UDT' THEN ss.HOURS ELSE 0 END) as UDT_HOURS,
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SUM(CASE WHEN ss.OLDSTATUSNAME = 'SDT' THEN ss.HOURS ELSE 0 END) as SDT_HOURS,
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SUM(CASE WHEN ss.OLDSTATUSNAME = 'EGT' THEN ss.HOURS ELSE 0 END) as EGT_HOURS,
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SUM(CASE WHEN ss.OLDSTATUSNAME = 'NST' THEN ss.HOURS ELSE 0 END) as NST_HOURS,
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COUNT(DISTINCT ss.HISTORYID) as MACHINE_COUNT
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FROM shift_data ss
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JOIN DWH.DW_MES_RESOURCE r ON ss.HISTORYID = r.RESOURCEID
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{common_filters}
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SUM(CASE WHEN OLDSTATUSNAME = 'PRD' THEN HOURS ELSE 0 END) as PRD_HOURS,
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SUM(CASE WHEN OLDSTATUSNAME = 'SBY' THEN HOURS ELSE 0 END) as SBY_HOURS,
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SUM(CASE WHEN OLDSTATUSNAME = 'UDT' THEN HOURS ELSE 0 END) as UDT_HOURS,
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SUM(CASE WHEN OLDSTATUSNAME = 'SDT' THEN HOURS ELSE 0 END) as SDT_HOURS,
|
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SUM(CASE WHEN OLDSTATUSNAME = 'EGT' THEN HOURS ELSE 0 END) as EGT_HOURS,
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SUM(CASE WHEN OLDSTATUSNAME = 'NST' THEN HOURS ELSE 0 END) as NST_HOURS,
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COUNT(DISTINCT HISTORYID) as MACHINE_COUNT
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FROM shift_data
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"""
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# Trend query - group by date
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trend_sql = f"""
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{base_cte}
|
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SELECT
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{date_trunc} as DATA_DATE,
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SUM(CASE WHEN ss.OLDSTATUSNAME = 'PRD' THEN ss.HOURS ELSE 0 END) as PRD_HOURS,
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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 DWH.DW_MES_RESOURCE r ON ss.HISTORYID = r.RESOURCEID
|
||||
{common_filters}
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'PRD' THEN HOURS ELSE 0 END) as PRD_HOURS,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'SBY' THEN HOURS ELSE 0 END) as SBY_HOURS,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'UDT' THEN HOURS ELSE 0 END) as UDT_HOURS,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'SDT' THEN HOURS ELSE 0 END) as SDT_HOURS,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'EGT' THEN HOURS ELSE 0 END) as EGT_HOURS,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'NST' THEN HOURS ELSE 0 END) as NST_HOURS,
|
||||
COUNT(DISTINCT HISTORYID) as MACHINE_COUNT
|
||||
FROM shift_data
|
||||
GROUP BY {date_trunc}
|
||||
ORDER BY DATA_DATE
|
||||
"""
|
||||
|
||||
heatmap_sql = f"""
|
||||
# Heatmap/Comparison query - group by HISTORYID and date, merge dimension in Python
|
||||
heatmap_raw_sql = f"""
|
||||
{base_cte}
|
||||
SELECT
|
||||
r.WORKCENTERNAME,
|
||||
HISTORYID,
|
||||
{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 DWH.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
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'PRD' THEN HOURS ELSE 0 END) as PRD_HOURS,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'SBY' THEN HOURS ELSE 0 END) as SBY_HOURS,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'UDT' THEN HOURS ELSE 0 END) as UDT_HOURS,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'SDT' THEN HOURS ELSE 0 END) as SDT_HOURS,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'EGT' THEN HOURS ELSE 0 END) as EGT_HOURS
|
||||
FROM shift_data
|
||||
GROUP BY HISTORYID, {date_trunc}
|
||||
ORDER BY HISTORYID, 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 DWH.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
|
||||
# Execute queries in parallel
|
||||
results = {}
|
||||
with ThreadPoolExecutor(max_workers=4) as executor:
|
||||
with ThreadPoolExecutor(max_workers=3) 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',
|
||||
executor.submit(read_sql_df, heatmap_raw_sql): 'heatmap_raw',
|
||||
}
|
||||
for future in as_completed(futures):
|
||||
query_name = futures[future]
|
||||
@@ -234,8 +342,11 @@ def query_summary(
|
||||
# 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()))
|
||||
|
||||
# Build heatmap and comparison from raw data with dimension merge
|
||||
heatmap_raw_df = results.get('heatmap_raw', pd.DataFrame())
|
||||
heatmap = _build_heatmap_from_raw_df(heatmap_raw_df, resource_lookup, granularity)
|
||||
workcenter_comparison = _build_comparison_from_raw_df(heatmap_raw_df, resource_lookup)
|
||||
|
||||
return {
|
||||
'kpi': kpi,
|
||||
@@ -254,10 +365,6 @@ def query_summary(
|
||||
# Detail Query
|
||||
# ============================================================
|
||||
|
||||
# Maximum records limit for detail query (disabled - no limit)
|
||||
# MAX_DETAIL_RECORDS = 5000
|
||||
|
||||
|
||||
def query_detail(
|
||||
start_date: str,
|
||||
end_date: str,
|
||||
@@ -270,6 +377,7 @@ def query_detail(
|
||||
) -> Optional[Dict[str, Any]]:
|
||||
"""Query hierarchical detail data.
|
||||
|
||||
Uses resource_cache as the source for equipment master data.
|
||||
Returns flat data with workcenter, family, resource dimensions.
|
||||
Frontend handles hierarchy assembly.
|
||||
|
||||
@@ -293,58 +401,56 @@ def query_detail(
|
||||
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')
|
||||
# Get filtered resources from cache
|
||||
resources = _get_filtered_resources(
|
||||
workcenter_groups=workcenter_groups,
|
||||
families=families,
|
||||
is_production=is_production,
|
||||
is_key=is_key,
|
||||
is_monitor=is_monitor,
|
||||
)
|
||||
|
||||
# Common CTE with MATERIALIZE hint
|
||||
base_cte = f"""
|
||||
if not resources:
|
||||
logger.warning("No resources match the filter criteria")
|
||||
return {
|
||||
'data': [],
|
||||
'total': 0,
|
||||
'truncated': False,
|
||||
'max_records': None
|
||||
}
|
||||
|
||||
# Build resource lookup for dimension merging
|
||||
resource_lookup = _build_resource_lookup(resources)
|
||||
historyid_filter = _build_historyid_filter(resources)
|
||||
|
||||
# Query SHIFT data grouped by HISTORYID
|
||||
detail_sql = f"""
|
||||
WITH shift_data AS (
|
||||
SELECT /*+ MATERIALIZE */ HISTORYID, OLDSTATUSNAME, HOURS
|
||||
FROM DWH.DW_MES_RESOURCESTATUS_SHIFT
|
||||
WHERE TXNDATE >= TO_DATE('{start_date}', 'YYYY-MM-DD')
|
||||
AND TXNDATE < TO_DATE('{end_date}', 'YYYY-MM-DD') + 1
|
||||
AND {historyid_filter}
|
||||
)
|
||||
"""
|
||||
|
||||
# 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 DWH.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
|
||||
HISTORYID,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'PRD' THEN HOURS ELSE 0 END) as PRD_HOURS,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'SBY' THEN HOURS ELSE 0 END) as SBY_HOURS,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'UDT' THEN HOURS ELSE 0 END) as UDT_HOURS,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'SDT' THEN HOURS ELSE 0 END) as SDT_HOURS,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'EGT' THEN HOURS ELSE 0 END) as EGT_HOURS,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'NST' THEN HOURS ELSE 0 END) as NST_HOURS,
|
||||
SUM(HOURS) as TOTAL_HOURS
|
||||
FROM shift_data
|
||||
GROUP BY HISTORYID
|
||||
ORDER BY HISTORYID
|
||||
"""
|
||||
|
||||
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)
|
||||
# Build detail data with dimension merge from cache
|
||||
data = _build_detail_from_raw_df(detail_df, resource_lookup)
|
||||
total = len(data)
|
||||
|
||||
return {
|
||||
'data': data,
|
||||
@@ -375,6 +481,7 @@ def export_csv(
|
||||
) -> Generator[str, None, None]:
|
||||
"""Generate CSV data as a stream for export.
|
||||
|
||||
Uses resource_cache as the source for equipment master data.
|
||||
Yields CSV rows one at a time to avoid memory issues with large datasets.
|
||||
|
||||
Args:
|
||||
@@ -397,49 +504,51 @@ def export_csv(
|
||||
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')
|
||||
# Get filtered resources from cache
|
||||
resources = _get_filtered_resources(
|
||||
workcenter_groups=workcenter_groups,
|
||||
families=families,
|
||||
is_production=is_production,
|
||||
is_key=is_key,
|
||||
is_monitor=is_monitor,
|
||||
)
|
||||
|
||||
# Query all data with CTE and MATERIALIZE hint for performance optimization
|
||||
if not resources:
|
||||
yield "Error: No resources match the filter criteria\n"
|
||||
return
|
||||
|
||||
# Build resource lookup for dimension merging
|
||||
resource_lookup = _build_resource_lookup(resources)
|
||||
historyid_filter = _build_historyid_filter(resources)
|
||||
|
||||
# Get workcenter mapping for WORKCENTER_GROUP
|
||||
from mes_dashboard.services.filter_cache import get_workcenter_mapping
|
||||
wc_mapping = get_workcenter_mapping() or {}
|
||||
|
||||
# Query SHIFT data grouped by HISTORYID
|
||||
sql = f"""
|
||||
WITH shift_data AS (
|
||||
SELECT /*+ MATERIALIZE */ HISTORYID, OLDSTATUSNAME, HOURS
|
||||
FROM DWH.DW_MES_RESOURCESTATUS_SHIFT
|
||||
WHERE TXNDATE >= TO_DATE('{start_date}', 'YYYY-MM-DD')
|
||||
AND TXNDATE < TO_DATE('{end_date}', 'YYYY-MM-DD') + 1
|
||||
AND {historyid_filter}
|
||||
)
|
||||
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 DWH.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
|
||||
HISTORYID,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'PRD' THEN HOURS ELSE 0 END) as PRD_HOURS,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'SBY' THEN HOURS ELSE 0 END) as SBY_HOURS,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'UDT' THEN HOURS ELSE 0 END) as UDT_HOURS,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'SDT' THEN HOURS ELSE 0 END) as SDT_HOURS,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'EGT' THEN HOURS ELSE 0 END) as EGT_HOURS,
|
||||
SUM(CASE WHEN OLDSTATUSNAME = 'NST' THEN HOURS ELSE 0 END) as NST_HOURS,
|
||||
SUM(HOURS) as TOTAL_HOURS
|
||||
FROM shift_data
|
||||
GROUP BY HISTORYID
|
||||
ORDER BY HISTORYID
|
||||
"""
|
||||
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)
|
||||
@@ -455,47 +564,57 @@ def export_csv(
|
||||
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)
|
||||
if df is not None:
|
||||
for _, row in df.iterrows():
|
||||
historyid = row['HISTORYID']
|
||||
resource_info = resource_lookup.get(historyid, {})
|
||||
|
||||
# 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
|
||||
# Skip if no resource info found
|
||||
if not resource_info:
|
||||
continue
|
||||
|
||||
# Calculate percentages
|
||||
ou_pct = _calc_ou_pct(prd, sby, udt, sdt, egt)
|
||||
availability_pct = _calc_availability_pct(prd, sby, udt, sdt, egt, nst)
|
||||
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
|
||||
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)
|
||||
|
||||
csv_row = [
|
||||
wc_group,
|
||||
row['RESOURCEFAMILYNAME'],
|
||||
row['RESOURCENAME'],
|
||||
f"{ou_pct}%",
|
||||
f"{availability_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)
|
||||
# Get dimension data from cache
|
||||
wc_name = resource_info.get('WORKCENTERNAME', '')
|
||||
wc_info = wc_mapping.get(wc_name, {})
|
||||
wc_group = wc_info.get('group', wc_name)
|
||||
family = resource_info.get('RESOURCEFAMILYNAME', '')
|
||||
resource_name = resource_info.get('RESOURCENAME', '')
|
||||
|
||||
# Calculate percentages
|
||||
ou_pct = _calc_ou_pct(prd, sby, udt, sdt, egt)
|
||||
availability_pct = _calc_availability_pct(prd, sby, udt, sdt, egt, nst)
|
||||
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,
|
||||
family,
|
||||
resource_name,
|
||||
f"{ou_pct}%",
|
||||
f"{availability_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}")
|
||||
@@ -523,93 +642,17 @@ def _validate_date_range(start_date: str, end_date: str) -> Optional[str]:
|
||||
|
||||
|
||||
def _get_date_trunc(granularity: str) -> str:
|
||||
"""Get Oracle TRUNC expression for date granularity."""
|
||||
"""Get Oracle TRUNC expression for date granularity.
|
||||
|
||||
Note: Uses 'ss' as alias for shift_data CTE.
|
||||
"""
|
||||
trunc_map = {
|
||||
'day': "TRUNC(ss.TXNDATE)",
|
||||
'week': "TRUNC(ss.TXNDATE, 'IW')",
|
||||
'month': "TRUNC(ss.TXNDATE, 'MM')",
|
||||
'year': "TRUNC(ss.TXNDATE, 'YYYY')"
|
||||
'day': "TRUNC(TXNDATE)",
|
||||
'week': "TRUNC(TXNDATE, 'IW')",
|
||||
'month': "TRUNC(TXNDATE, 'MM')",
|
||||
'year': "TRUNC(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}')"
|
||||
return trunc_map.get(granularity, "TRUNC(TXNDATE)")
|
||||
|
||||
|
||||
def _safe_float(value, default=0.0) -> float:
|
||||
@@ -713,8 +756,23 @@ def _build_trend_from_df(df: pd.DataFrame, granularity: str) -> List[Dict]:
|
||||
return result
|
||||
|
||||
|
||||
def _build_heatmap_from_df(df: pd.DataFrame, granularity: str) -> List[Dict]:
|
||||
"""Build heatmap data from query result DataFrame."""
|
||||
def _build_heatmap_from_raw_df(
|
||||
df: pd.DataFrame,
|
||||
resource_lookup: Dict[str, Dict[str, Any]],
|
||||
granularity: str
|
||||
) -> List[Dict]:
|
||||
"""Build heatmap data from raw SHIFT query grouped by HISTORYID.
|
||||
|
||||
Merges dimension data from resource_lookup.
|
||||
|
||||
Args:
|
||||
df: DataFrame with HISTORYID, DATA_DATE, and status hours.
|
||||
resource_lookup: Dict mapping RESOURCEID to resource info.
|
||||
granularity: Time granularity for date formatting.
|
||||
|
||||
Returns:
|
||||
List of heatmap data dicts.
|
||||
"""
|
||||
if df is None or len(df) == 0:
|
||||
return []
|
||||
|
||||
@@ -725,10 +783,17 @@ def _build_heatmap_from_df(df: pd.DataFrame, granularity: str) -> List[Dict]:
|
||||
# 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):
|
||||
historyid = row['HISTORYID']
|
||||
resource_info = resource_lookup.get(historyid, {})
|
||||
|
||||
# Skip if no resource info
|
||||
if not resource_info:
|
||||
continue
|
||||
|
||||
wc_name = resource_info.get('WORKCENTERNAME', '')
|
||||
if not 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)
|
||||
@@ -756,8 +821,21 @@ def _build_heatmap_from_df(df: pd.DataFrame, granularity: str) -> List[Dict]:
|
||||
return result
|
||||
|
||||
|
||||
def _build_comparison_from_df(df: pd.DataFrame) -> List[Dict]:
|
||||
"""Build workcenter comparison data from query result DataFrame."""
|
||||
def _build_comparison_from_raw_df(
|
||||
df: pd.DataFrame,
|
||||
resource_lookup: Dict[str, Dict[str, Any]]
|
||||
) -> List[Dict]:
|
||||
"""Build workcenter comparison data from raw SHIFT query grouped by HISTORYID.
|
||||
|
||||
Merges dimension data from resource_lookup.
|
||||
|
||||
Args:
|
||||
df: DataFrame with HISTORYID and status hours (may have DATA_DATE if from heatmap query).
|
||||
resource_lookup: Dict mapping RESOURCEID to resource info.
|
||||
|
||||
Returns:
|
||||
List of comparison data dicts.
|
||||
"""
|
||||
if df is None or len(df) == 0:
|
||||
return []
|
||||
|
||||
@@ -765,25 +843,44 @@ def _build_comparison_from_df(df: pd.DataFrame) -> List[Dict]:
|
||||
from mes_dashboard.services.filter_cache import get_workcenter_mapping
|
||||
wc_mapping = get_workcenter_mapping() or {}
|
||||
|
||||
# Aggregate data by WORKCENTER_GROUP
|
||||
aggregated = {}
|
||||
# First aggregate by HISTORYID (in case df is by HISTORYID + date)
|
||||
by_resource = {}
|
||||
for _, row in df.iterrows():
|
||||
wc_name = row['WORKCENTERNAME']
|
||||
# Skip rows with NaN workcenter name
|
||||
if pd.isna(wc_name):
|
||||
historyid = row['HISTORYID']
|
||||
if historyid not in by_resource:
|
||||
by_resource[historyid] = {'prd': 0, 'sby': 0, 'udt': 0, 'sdt': 0, 'egt': 0}
|
||||
|
||||
by_resource[historyid]['prd'] += _safe_float(row['PRD_HOURS'])
|
||||
by_resource[historyid]['sby'] += _safe_float(row['SBY_HOURS'])
|
||||
by_resource[historyid]['udt'] += _safe_float(row['UDT_HOURS'])
|
||||
by_resource[historyid]['sdt'] += _safe_float(row['SDT_HOURS'])
|
||||
by_resource[historyid]['egt'] += _safe_float(row['EGT_HOURS'])
|
||||
|
||||
# Then aggregate by WORKCENTER_GROUP
|
||||
aggregated = {}
|
||||
for historyid, hours in by_resource.items():
|
||||
resource_info = resource_lookup.get(historyid, {})
|
||||
|
||||
# Skip if no resource info
|
||||
if not resource_info:
|
||||
continue
|
||||
|
||||
wc_name = resource_info.get('WORKCENTERNAME', '')
|
||||
if not 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']))
|
||||
aggregated[wc_group]['prd'] += hours['prd']
|
||||
aggregated[wc_group]['sby'] += hours['sby']
|
||||
aggregated[wc_group]['udt'] += hours['udt']
|
||||
aggregated[wc_group]['sdt'] += hours['sdt']
|
||||
aggregated[wc_group]['egt'] += hours['egt']
|
||||
aggregated[wc_group]['machine_count'] += 1
|
||||
|
||||
result = []
|
||||
for wc_group, data in aggregated.items():
|
||||
@@ -799,8 +896,21 @@ def _build_comparison_from_df(df: pd.DataFrame) -> List[Dict]:
|
||||
return result
|
||||
|
||||
|
||||
def _build_detail_from_df(df: pd.DataFrame) -> List[Dict]:
|
||||
"""Build detail data from query result DataFrame."""
|
||||
def _build_detail_from_raw_df(
|
||||
df: pd.DataFrame,
|
||||
resource_lookup: Dict[str, Dict[str, Any]]
|
||||
) -> List[Dict]:
|
||||
"""Build detail data from raw SHIFT query grouped by HISTORYID.
|
||||
|
||||
Merges dimension data from resource_lookup.
|
||||
|
||||
Args:
|
||||
df: DataFrame with HISTORYID and status hours.
|
||||
resource_lookup: Dict mapping RESOURCEID to resource info.
|
||||
|
||||
Returns:
|
||||
List of detail data dicts.
|
||||
"""
|
||||
if df is None or len(df) == 0:
|
||||
return []
|
||||
|
||||
@@ -810,9 +920,11 @@ def _build_detail_from_df(df: pd.DataFrame) -> List[Dict]:
|
||||
|
||||
result = []
|
||||
for _, row in df.iterrows():
|
||||
# Skip rows with NaN workcenter name
|
||||
wc_name = row['WORKCENTERNAME']
|
||||
if pd.isna(wc_name):
|
||||
historyid = row['HISTORYID']
|
||||
resource_info = resource_lookup.get(historyid, {})
|
||||
|
||||
# Skip if no resource info
|
||||
if not resource_info:
|
||||
continue
|
||||
|
||||
prd = _safe_float(row['PRD_HOURS'])
|
||||
@@ -823,18 +935,17 @@ def _build_detail_from_df(df: pd.DataFrame) -> List[Dict]:
|
||||
nst = _safe_float(row['NST_HOURS'])
|
||||
total = _safe_float(row['TOTAL_HOURS'])
|
||||
|
||||
# Map WORKCENTERNAME to WORKCENTER_GROUP
|
||||
# Get dimension data from cache
|
||||
wc_name = resource_info.get('WORKCENTERNAME', '')
|
||||
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']
|
||||
family = resource_info.get('RESOURCEFAMILYNAME', '')
|
||||
resource_name = resource_info.get('RESOURCENAME', '')
|
||||
|
||||
result.append({
|
||||
'workcenter': wc_group,
|
||||
'family': family if not pd.isna(family) else '',
|
||||
'resource': resource if not pd.isna(resource) else '',
|
||||
'family': family or '',
|
||||
'resource': resource_name or '',
|
||||
'ou_pct': _calc_ou_pct(prd, sby, udt, sdt, egt),
|
||||
'availability_pct': _calc_availability_pct(prd, sby, udt, sdt, egt, nst),
|
||||
'prd_hours': round(prd, 1),
|
||||
@@ -852,4 +963,6 @@ def _build_detail_from_df(df: pd.DataFrame) -> List[Dict]:
|
||||
'machine_count': 1
|
||||
})
|
||||
|
||||
# Sort by workcenter, family, resource
|
||||
result.sort(key=lambda x: (x['workcenter'], x['family'], x['resource']))
|
||||
return result
|
||||
|
||||
@@ -501,6 +501,7 @@ def get_merged_resource_status(
|
||||
'CAUSECODE': realtime.get('CAUSECODE'),
|
||||
'REPAIRCODE': realtime.get('REPAIRCODE'),
|
||||
'LOT_COUNT': realtime.get('LOT_COUNT'),
|
||||
'LOT_DETAILS': realtime.get('LOT_DETAILS'), # LOT details for tooltip
|
||||
'TOTAL_TRACKIN_QTY': realtime.get('TOTAL_TRACKIN_QTY'),
|
||||
'LATEST_TRACKIN_TIME': realtime.get('LATEST_TRACKIN_TIME'),
|
||||
}
|
||||
|
||||
@@ -283,6 +283,58 @@
|
||||
|
||||
.matrix-table .zero { color: #d1d5db; }
|
||||
|
||||
/* Clickable matrix cells */
|
||||
.matrix-table td.clickable {
|
||||
cursor: pointer;
|
||||
transition: background 0.15s;
|
||||
}
|
||||
|
||||
.matrix-table td.clickable:hover {
|
||||
background: #e0e7ff;
|
||||
}
|
||||
|
||||
.matrix-table td.clickable.selected {
|
||||
background: #dbeafe;
|
||||
box-shadow: inset 0 0 0 2px var(--primary);
|
||||
}
|
||||
|
||||
/* Matrix filter indicator */
|
||||
.matrix-filter-indicator {
|
||||
display: none;
|
||||
align-items: center;
|
||||
gap: 8px;
|
||||
padding: 8px 12px;
|
||||
background: #dbeafe;
|
||||
border-radius: 6px;
|
||||
margin-top: 12px;
|
||||
font-size: 13px;
|
||||
color: var(--primary-dark);
|
||||
}
|
||||
|
||||
.matrix-filter-indicator.active {
|
||||
display: inline-flex;
|
||||
}
|
||||
|
||||
.matrix-filter-indicator .filter-text {
|
||||
font-weight: 500;
|
||||
}
|
||||
|
||||
.btn-clear-filter {
|
||||
background: transparent;
|
||||
border: 1px solid var(--primary);
|
||||
color: var(--primary);
|
||||
padding: 4px 10px;
|
||||
border-radius: 4px;
|
||||
font-size: 12px;
|
||||
cursor: pointer;
|
||||
transition: all 0.2s;
|
||||
}
|
||||
|
||||
.btn-clear-filter:hover {
|
||||
background: var(--primary);
|
||||
color: white;
|
||||
}
|
||||
|
||||
.ou-badge {
|
||||
display: inline-block;
|
||||
padding: 2px 8px;
|
||||
@@ -389,6 +441,86 @@
|
||||
color: var(--muted);
|
||||
}
|
||||
|
||||
/* LOT Tooltip */
|
||||
.lot-info {
|
||||
position: relative;
|
||||
cursor: pointer;
|
||||
}
|
||||
|
||||
.lot-info:hover .lot-tooltip {
|
||||
display: block;
|
||||
}
|
||||
|
||||
.lot-tooltip {
|
||||
display: none;
|
||||
position: absolute;
|
||||
top: calc(100% + 8px);
|
||||
left: 0;
|
||||
background: #1e293b;
|
||||
color: #fff;
|
||||
padding: 12px;
|
||||
border-radius: 8px;
|
||||
font-size: 11px;
|
||||
white-space: nowrap;
|
||||
z-index: 1000;
|
||||
box-shadow: 0 4px 12px rgba(0,0,0,0.3);
|
||||
min-width: 280px;
|
||||
max-width: 400px;
|
||||
max-height: 300px;
|
||||
overflow-y: auto;
|
||||
}
|
||||
|
||||
.lot-tooltip::after {
|
||||
content: '';
|
||||
position: absolute;
|
||||
bottom: 100%;
|
||||
left: 20px;
|
||||
border: 6px solid transparent;
|
||||
border-bottom-color: #1e293b;
|
||||
}
|
||||
|
||||
.lot-tooltip-title {
|
||||
font-weight: 600;
|
||||
margin-bottom: 8px;
|
||||
padding-bottom: 6px;
|
||||
border-bottom: 1px solid #475569;
|
||||
color: #94a3b8;
|
||||
}
|
||||
|
||||
.lot-item {
|
||||
padding: 6px 0;
|
||||
border-bottom: 1px solid #334155;
|
||||
}
|
||||
|
||||
.lot-item:last-child {
|
||||
border-bottom: none;
|
||||
}
|
||||
|
||||
.lot-item-header {
|
||||
font-weight: 600;
|
||||
color: #60a5fa;
|
||||
margin-bottom: 4px;
|
||||
}
|
||||
|
||||
.lot-item-row {
|
||||
display: flex;
|
||||
gap: 12px;
|
||||
flex-wrap: wrap;
|
||||
}
|
||||
|
||||
.lot-item-field {
|
||||
display: flex;
|
||||
gap: 4px;
|
||||
}
|
||||
|
||||
.lot-item-label {
|
||||
color: #94a3b8;
|
||||
}
|
||||
|
||||
.lot-item-value {
|
||||
color: #e2e8f0;
|
||||
}
|
||||
|
||||
/* Responsive */
|
||||
@media (max-width: 1200px) {
|
||||
.summary-grid { grid-template-columns: repeat(3, 1fr); }
|
||||
@@ -498,6 +630,11 @@
|
||||
<span class="spinner"></span> 載入中...
|
||||
</div>
|
||||
</div>
|
||||
<div id="matrixFilterIndicator" class="matrix-filter-indicator">
|
||||
<span>篩選中：</span>
|
||||
<span class="filter-text" id="matrixFilterText"></span>
|
||||
<button class="btn-clear-filter" onclick="clearMatrixFilter()">清除篩選</button>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Equipment List -->
|
||||
@@ -516,6 +653,7 @@
|
||||
<script>
|
||||
let allEquipment = [];
|
||||
let workcenterGroups = [];
|
||||
let matrixFilter = null; // { workcenter_group, status }
|
||||
|
||||
function toggleFilter(checkbox, id) {
|
||||
const label = document.getElementById(id);
|
||||
@@ -637,18 +775,28 @@
|
||||
const avail = row.PRD + row.SBY + row.UDT + row.SDT + row.EGT;
|
||||
const ou = avail > 0 ? ((row.PRD / avail) * 100).toFixed(1) : 0;
|
||||
const ouClass = ou >= 80 ? 'high' : (ou >= 50 ? 'medium' : 'low');
|
||||
const wg = row.workcenter_group;
|
||||
|
||||
// Helper to render clickable cell
|
||||
const renderCell = (status, value, colClass) => {
|
||||
if (value === 0) {
|
||||
return `<td class="clickable ${colClass} zero" data-wg="${wg}" data-status="${status}">${value}</td>`;
|
||||
}
|
||||
const selected = matrixFilter && matrixFilter.workcenter_group === wg && matrixFilter.status === status ? 'selected' : '';
|
||||
return `<td class="clickable ${colClass} ${selected}" data-wg="${wg}" data-status="${status}" onclick="filterByMatrixCell('${wg}', '${status}')">${value}</td>`;
|
||||
};
|
||||
|
||||
html += `
|
||||
<tr>
|
||||
<td>${row.workcenter_group}</td>
|
||||
<td>${wg}</td>
|
||||
<td class="col-total">${row.total}</td>
|
||||
<td class="col-prd ${row.PRD === 0 ? 'zero' : ''}">${row.PRD}</td>
|
||||
<td class="col-sby ${row.SBY === 0 ? 'zero' : ''}">${row.SBY}</td>
|
||||
<td class="col-udt ${row.UDT === 0 ? 'zero' : ''}">${row.UDT}</td>
|
||||
<td class="col-sdt ${row.SDT === 0 ? 'zero' : ''}">${row.SDT}</td>
|
||||
<td class="col-egt ${row.EGT === 0 ? 'zero' : ''}">${row.EGT}</td>
|
||||
<td class="col-nst ${row.NST === 0 ? 'zero' : ''}">${row.NST}</td>
|
||||
<td class="col-other ${row.OTHER === 0 ? 'zero' : ''}">${row.OTHER}</td>
|
||||
${renderCell('PRD', row.PRD, 'col-prd')}
|
||||
${renderCell('SBY', row.SBY, 'col-sby')}
|
||||
${renderCell('UDT', row.UDT, 'col-udt')}
|
||||
${renderCell('SDT', row.SDT, 'col-sdt')}
|
||||
${renderCell('EGT', row.EGT, 'col-egt')}
|
||||
${renderCell('NST', row.NST, 'col-nst')}
|
||||
${renderCell('OTHER', row.OTHER, 'col-other')}
|
||||
<td><span class="ou-badge ${ouClass}">${ou}%</span></td>
|
||||
</tr>
|
||||
`;
|
||||
@@ -668,6 +816,10 @@
|
||||
async function loadEquipment() {
|
||||
const container = document.getElementById('equipmentContainer');
|
||||
|
||||
// Clear matrix filter when reloading data
|
||||
matrixFilter = null;
|
||||
document.getElementById('matrixFilterIndicator').classList.remove('active');
|
||||
|
||||
try {
|
||||
const queryString = getFilters();
|
||||
const resp = await fetch(`/api/resource/status?${queryString}`);
|
||||
@@ -688,6 +840,30 @@
|
||||
}
|
||||
}
|
||||
|
||||
function renderLotTooltip(lotDetails) {
|
||||
if (!lotDetails || lotDetails.length === 0) return '';
|
||||
|
||||
let tooltipHtml = '<div class="lot-tooltip"><div class="lot-tooltip-title">在製批次明細</div>';
|
||||
|
||||
lotDetails.forEach(lot => {
|
||||
const trackinTime = lot.LOTTRACKINTIME ? new Date(lot.LOTTRACKINTIME).toLocaleString('zh-TW') : '--';
|
||||
const qty = lot.LOTTRACKINQTY_PCS != null ? lot.LOTTRACKINQTY_PCS.toLocaleString() : '--';
|
||||
tooltipHtml += `
|
||||
<div class="lot-item">
|
||||
<div class="lot-item-header">${lot.RUNCARDLOTID || '--'}</div>
|
||||
<div class="lot-item-row">
|
||||
<div class="lot-item-field"><span class="lot-item-label">數量:</span><span class="lot-item-value">${qty} pcs</span></div>
|
||||
<div class="lot-item-field"><span class="lot-item-label">TrackIn:</span><span class="lot-item-value">${trackinTime}</span></div>
|
||||
<div class="lot-item-field"><span class="lot-item-label">操作員:</span><span class="lot-item-value">${lot.LOTTRACKINEMPLOYEE || '--'}</span></div>
|
||||
</div>
|
||||
</div>
|
||||
`;
|
||||
});
|
||||
|
||||
tooltipHtml += '</div>';
|
||||
return tooltipHtml;
|
||||
}
|
||||
|
||||
function renderEquipmentList(equipment) {
|
||||
const container = document.getElementById('equipmentContainer');
|
||||
|
||||
@@ -702,6 +878,13 @@
|
||||
const statusCat = (eq.STATUS_CATEGORY || 'OTHER').toLowerCase();
|
||||
const statusDisplay = getStatusDisplay(eq.EQUIPMENTASSETSSTATUS, eq.STATUS_CATEGORY);
|
||||
|
||||
// Build LOT info with tooltip
|
||||
let lotHtml = '';
|
||||
if (eq.LOT_COUNT > 0) {
|
||||
const tooltipHtml = renderLotTooltip(eq.LOT_DETAILS);
|
||||
lotHtml = `<span class="lot-info">📦 ${eq.LOT_COUNT} 批${tooltipHtml}</span>`;
|
||||
}
|
||||
|
||||
html += `
|
||||
<div class="equipment-card status-${statusCat}">
|
||||
<div class="eq-header">
|
||||
@@ -712,8 +895,8 @@
|
||||
<span title="工站">📍 ${eq.WORKCENTERNAME || '--'}</span>
|
||||
<span title="群組">🏭 ${eq.WORKCENTER_GROUP || '--'}</span>
|
||||
<span title="家族">🔧 ${eq.RESOURCEFAMILYNAME || '--'}</span>
|
||||
<span title="部門">🏢 ${eq.PJ_DEPARTMENT || '--'}</span>
|
||||
${eq.LOT_COUNT > 0 ? `<span title="在製批數">📦 ${eq.LOT_COUNT} 批</span>` : ''}
|
||||
<span title="區域">🏢 ${eq.LOCATIONNAME || '--'}</span>
|
||||
${lotHtml}
|
||||
${eq.JOBORDER ? `<span title="工單">📋 ${eq.JOBORDER}</span>` : ''}
|
||||
</div>
|
||||
</div>
|
||||
@@ -724,6 +907,86 @@
|
||||
container.innerHTML = html;
|
||||
}
|
||||
|
||||
function filterByMatrixCell(workcenterGroup, status) {
|
||||
// Status mapping from matrix column to STATUS_CATEGORY or EQUIPMENTASSETSSTATUS
|
||||
const statusMap = {
|
||||
'PRD': 'PRODUCTIVE',
|
||||
'SBY': 'STANDBY',
|
||||
'UDT': 'DOWN',
|
||||
'SDT': 'DOWN',
|
||||
'EGT': 'ENGINEERING',
|
||||
'NST': 'NOT_SCHEDULED',
|
||||
'OTHER': 'OTHER'
|
||||
};
|
||||
|
||||
// Toggle off if clicking same cell
|
||||
if (matrixFilter && matrixFilter.workcenter_group === workcenterGroup && matrixFilter.status === status) {
|
||||
clearMatrixFilter();
|
||||
return;
|
||||
}
|
||||
|
||||
matrixFilter = { workcenter_group: workcenterGroup, status: status };
|
||||
|
||||
// Update selected cell highlighting
|
||||
document.querySelectorAll('.matrix-table td.clickable').forEach(cell => {
|
||||
cell.classList.remove('selected');
|
||||
if (cell.dataset.wg === workcenterGroup && cell.dataset.status === status) {
|
||||
cell.classList.add('selected');
|
||||
}
|
||||
});
|
||||
|
||||
// Show filter indicator
|
||||
const statusLabels = {
|
||||
'PRD': '生產中',
|
||||
'SBY': '待機',
|
||||
'UDT': '非計畫停機',
|
||||
'SDT': '計畫停機',
|
||||
'EGT': '工程',
|
||||
'NST': '未排程',
|
||||
'OTHER': '其他'
|
||||
};
|
||||
document.getElementById('matrixFilterText').textContent = `${workcenterGroup} - ${statusLabels[status] || status}`;
|
||||
document.getElementById('matrixFilterIndicator').classList.add('active');
|
||||
|
||||
// Filter and render equipment list
|
||||
const standardStatuses = ['PRD', 'SBY', 'UDT', 'SDT', 'EGT', 'NST'];
|
||||
const filtered = allEquipment.filter(eq => {
|
||||
// Match workcenter group
|
||||
// Note: If matrix shows "UNKNOWN", it means equipment has no WORKCENTER_GROUP
|
||||
const eqGroup = eq.WORKCENTER_GROUP || 'UNKNOWN';
|
||||
if (eqGroup !== workcenterGroup) return false;
|
||||
|
||||
// Match status based on EQUIPMENTASSETSSTATUS (same logic as matrix calculation)
|
||||
const eqStatus = eq.EQUIPMENTASSETSSTATUS || '';
|
||||
if (status === 'OTHER') {
|
||||
// OTHER = any status NOT in the standard set
|
||||
return !standardStatuses.includes(eqStatus);
|
||||
} else {
|
||||
// For standard statuses, match exact EQUIPMENTASSETSSTATUS
|
||||
return eqStatus === status;
|
||||
}
|
||||
});
|
||||
|
||||
document.getElementById('equipmentCount').textContent = filtered.length;
|
||||
renderEquipmentList(filtered);
|
||||
}
|
||||
|
||||
function clearMatrixFilter() {
|
||||
matrixFilter = null;
|
||||
|
||||
// Remove selected highlighting
|
||||
document.querySelectorAll('.matrix-table td.clickable').forEach(cell => {
|
||||
cell.classList.remove('selected');
|
||||
});
|
||||
|
||||
// Hide filter indicator
|
||||
document.getElementById('matrixFilterIndicator').classList.remove('active');
|
||||
|
||||
// Show all equipment
|
||||
document.getElementById('equipmentCount').textContent = allEquipment.length;
|
||||
renderEquipmentList(allEquipment);
|
||||
}
|
||||
|
||||
function getStatusDisplay(status, category) {
|
||||
const statusMap = {
|
||||
'PRD': '生產中',
|
||||
|
||||
Reference in New Issue
Block a user