148 lines
7.5 KiB
Python
148 lines
7.5 KiB
Python
#!/usr/bin/env python3
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"""复刻6月干预说明配色，并将达标分类改为一行一人。"""
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from copy import copy
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from collections import defaultdict
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from pathlib import Path
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import openpyxl
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BASE = Path('/Users/kkfluous/Downloads')
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JUL = BASE / '7月核算结果/租赁任务考核_2026年7月_干预情况说明.xlsx'
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JUN = BASE / '6月核算结果/租赁任务考核_2026年6月_干预情况说明.xlsx'
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SRC = BASE / '7月核算结果/租赁任务考核_2026年7月.xlsx'
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BAK = BASE / '7月核算结果/租赁任务考核_2026年7月_原版备份.xlsx'
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TEST = Path('/Users/kkfluous/Library/Containers/com.tencent.xinWeChat/Data/Documents/xwechat_files/wxid_1704407055112_3af8/temp/RWTemp/2026-08/4340099467fbf08b4c6583c49adba4ee/7月测试车辆明细.xlsx')
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def recs(path):
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wb = openpyxl.load_workbook(path, data_only=True)
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ws = wb['业务考核视图']
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h = [c.value for c in ws[1]]
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out = [dict(zip(h, r)) for r in ws.iter_rows(min_row=2, values_only=True) if r[0]]
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wb.close()
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return out
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def clone_style(src, dst):
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dst.font = copy(src.font)
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dst.fill = copy(src.fill)
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dst.border = copy(src.border)
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dst.alignment = copy(src.alignment)
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dst.protection = copy(src.protection)
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dst.number_format = src.number_format
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def style_row(ws, row, cols, ref_ws, ref_row, ref_cols=None):
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ref_cols = ref_cols or cols
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for c, rc in zip(cols, ref_cols):
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clone_style(ref_ws.cell(ref_row, rc), ws.cell(row, c))
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new = recs(SRC)
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old = recs(BAK)
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old_map = {}
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for r in old:
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old_map[r['车牌号']] = r
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twb = openpyxl.load_workbook(TEST, data_only=True)
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test_plates = {str(r[0]).strip() for r in twb.active.iter_rows(min_row=2, values_only=True) if r[0]}
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test_plates.discard('粤AG37316')
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twb.close()
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intervention = [r for r in new if r['车牌号'] in test_plates]
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flip = []
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for r in intervention:
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old_r = old_map.get(r['车牌号'])
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if old_r and old_r.get('是否达标') == '达标' and r.get('是否达标') != '达标':
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flip.append(r)
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groups = defaultdict(lambda: defaultdict(int))
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for r in flip:
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groups[r.get('考核目标') or '未知'][(r.get('部门名称') or '', r.get('销售经理') or '')] += 1
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wb = openpyxl.load_workbook(JUL)
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ref = openpyxl.load_workbook(JUN)
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ws = wb['测试与考核情况说明']
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rws = ref['测试与考核情况说明']
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# 清空原说明页后，按6月视觉规范重建。
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for merged in list(ws.merged_cells.ranges):
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ws.unmerge_cells(str(merged))
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ws.delete_rows(1, ws.max_row)
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for col in range(1, 8):
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letter = openpyxl.utils.get_column_letter(col)
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ws.column_dimensions[letter].width = rws.column_dimensions[letter].width
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total_plates = len({r['车牌号'] for r in new})
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interv_plates = len({r['车牌号'] for r in intervention})
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total_tbox = sum(float(r.get('原TBOX里程(km)') or 0) for r in new)
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total_actual = sum(float(r.get('实际行驶里程(km)') or 0) for r in new)
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total_test = sum(float(r.get('测试里程(km)') or 0) for r in new)
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interv_tbox = sum(float(r.get('原TBOX里程(km)') or 0) for r in intervention)
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interv_actual = sum(float(r.get('实际行驶里程(km)') or 0) for r in intervention)
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interv_test = sum(float(r.get('测试里程(km)') or 0) for r in intervention)
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# 标题及说明：深蓝标题、浅黄说明，与6月一致。
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ws.merge_cells('A1:G1'); ws['A1'] = '2026年7月 业务考核 — 测试与考核情况说明'; clone_style(rws['A1'], ws['A1'])
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ws.row_dimensions[1].height = rws.row_dimensions[1].height
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ws.merge_cells('A2:G3'); ws['A2'] = ('7月业务考核车辆中，测试车辆统一以指定GPS日里程按考核期汇总替换TBOX里程，差额作为测试里程剥离且最低取0。\n'
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'粤AG37316因GPS缺失，经业务确认暂按0核算。'); clone_style(rws['A2'], ws['A2'])
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ws.row_dimensions[2].height = rws.row_dimensions[2].height
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ws.merge_cells('A5:G5'); ws['A5'] = '一、7月业务考核与干预情况'; clone_style(rws['A5'], ws['A5'])
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headers = ['项目', '7月业务考核车辆', '涉及测试的车辆', '占比']
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for c, v in enumerate(headers, 1): ws.cell(6,c,v); clone_style(rws.cell(6,c), ws.cell(6,c))
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stats = [
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('车辆数(辆)', total_plates, interv_plates),
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('产生考核记录数(条)', len(new), len(intervention)),
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('仪表盘里程(km)', round(total_tbox), round(interv_tbox)),
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('业务考核里程 GPS(km)', round(total_actual), round(interv_actual)),
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('测试里程(km)', round(total_test), round(interv_test)),
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]
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for rr, (label, allv, partv) in enumerate(stats, 7):
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for c, v in enumerate([label, allv, partv, partv/allv if allv else 0], 1):
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ws.cell(rr,c,v); clone_style(rws.cell(7 + ((rr-7)%2),c), ws.cell(rr,c))
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# “测试里程”比例改为测试车辆剔除率，避免原100%被理解成车辆全部里程均为测试。
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ws['D6'] = '占比/剔除率'
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ws['D11'] = interv_test / interv_tbox if interv_tbox else 0
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negative_floor_adjustment = sum(max(0, float(r.get('实际行驶里程(km)') or 0) - float(r.get('原TBOX里程(km)') or 0)) for r in intervention)
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ws.merge_cells('A12:G12')
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ws['A12'] = (f'勾稽：测试里程 {round(interv_tbox):,} − {round(interv_actual):,} ＋ '
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f'{round(negative_floor_adjustment):,}（负差归0调整）＝ {round(interv_test):,} km')
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clone_style(rws['A2'], ws['A12'])
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ws.row_dimensions[12].height = 22
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ws.merge_cells('A13:G13'); ws['A13']='二、干预车辆考核达标情况说明'; clone_style(rws['A13'],ws['A13'])
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ws.merge_cells('A14:G14'); ws['A14']=f'共 {len(intervention)} 条考核记录涉及里程干预；替换为GPS里程后，共 {len(flip)} 条考核车辆记录由“达标”转判为“未达标”。按车型分类如下：'; clone_style(rws['A14'],ws['A14'])
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target_order = ['羚牛136辆4.5T冷链车','羚牛100辆18T','交投40辆4.5T普货','交投190辆4.5T冷链车','恒运50辆4.5T普货','恒运50辆4.5T 普货']
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rn = 16
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for target in target_order:
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items = sorted(groups.get(target, {}).items())
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if not items: continue
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total = sum(v for _, v in items)
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ws.merge_cells(start_row=rn,start_column=1,end_row=rn,end_column=3)
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ws.cell(rn,1,f'◎{target}（{total} 辆）'); clone_style(rws['A15'],ws.cell(rn,1)); rn += 1
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for c,v in enumerate(['部门','销售经理','数量'],1): ws.cell(rn,c,v); clone_style(rws.cell(16,c),ws.cell(rn,c))
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rn += 1
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for idx, ((dept,sales),cnt) in enumerate(items):
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for c,v in enumerate([dept,sales,cnt],1): ws.cell(rn,c,v); clone_style(rws.cell(17 + idx%2,c),ws.cell(rn,c))
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rn += 1
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rn += 1
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# 数据来源说明沿用6月蓝色区域。
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ws.merge_cells(start_row=rn,start_column=1,end_row=rn,end_column=7); ws.cell(rn,1,'三、里程三列数据来源说明'); clone_style(rws['A13'],ws.cell(rn,1)); rn += 1
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for c,v in enumerate(['列','字段名','数据来源','说明'],1): ws.cell(rn,c,v); clone_style(rws.cell(6,c),ws.cell(rn,c))
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rn += 1
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descs = [
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('O','原TBOX里程(km)','车辆 T-Box / 仪表盘读数','业务系统原始TBOX里程，包含运营、测试及调试里程。'),
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('P','实际行驶里程(km)','指定GPS日里程文件','按考核日期逐日汇总GPS里程；粤AG37316经确认暂按0核算。'),
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('Q','测试里程(km)','O − P（最低取0）','原TBOX里程与GPS里程的非负差额，不计入考核。'),
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]
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for idx,row in enumerate(descs):
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for c,v in enumerate(row,1): ws.cell(rn,c,v); clone_style(rws.cell(28 + idx,c),ws.cell(rn,c))
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ws.row_dimensions[rn].height = rws.row_dimensions[28 + idx].height
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rn += 1
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ws.sheet_view.showGridLines = rws.sheet_view.showGridLines
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ws.freeze_panes = rws.freeze_panes
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wb.save(JUL)
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wb.close(); ref.close()
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print(f'updated={JUL}')
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print(f'rows={rn-1} flip={len(flip)} groups={sum(len(v) for v in groups.values())}')
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