verify_store_total_performance_data.sh
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#!/bin/bash
# 验证门店总业绩统计数据准确性
echo "=== 验证门店总业绩统计数据准确性 ==="
# 获取Token
TOKEN=$(curl -s -X POST "http://localhost:2011/api/oauth/Login" \
-H "Content-Type: application/x-www-form-urlencoded" \
-d "account=admin&password=e10adc3949ba59abbe56e057f20f883e" | python3 -c "import sys, json; print(json.load(sys.stdin)['data']['token'])" 2>/dev/null)
if [ -z "$TOKEN" ]; then
echo "❌ 获取Token失败"
exit 1
fi
echo "✅ Token获取成功"
echo ""
# 查询实时数据
echo "--- 查询实时数据（2025年12月，前5条） ---"
RESPONSE=$(curl -s -X POST "http://localhost:2011/api/Extend/LqStatistics/get-store-total-performance-statistics-list" \
-H "Authorization: $TOKEN" \
-H "Content-Type: application/json" \
-d '{"statisticsMonth": "202512", "pageIndex": 1, "pageSize": 5}')
echo "$RESPONSE" | python3 -c "
import sys, json
data = json.load(sys.stdin)
items = data.get('data', {}).get('list', [])[:5]
print('实时查询结果（前5条）：')
print('=' * 100)
for i, item in enumerate(items, 1):
print(f'{i}. {item.get(\"StoreName\", \"无\")}')
print(f' 总业绩: {item.get(\"TotalPerformance\", 0):,.2f}')
print(f' 总单业绩: {item.get(\"TotalOrderPerformance\", 0):,.2f}')
print(f' 实际业绩: {item.get(\"ActualPerformance\", 0):,.2f}')
print(f' 首开单: {item.get(\"FirstOrderCount\", 0)}, 升单: {item.get(\"UpgradeOrderCount\", 0)}')
print(f' 品项数量: {item.get(\"ItemQuantity\", 0)}')
print(f' 退款金额: {item.get(\"RefundAmount\", 0):,.2f}, 退款次数: {item.get(\"RefundCount\", 0)}')
print('')
" 2>/dev/null
# 验证数据完整性
echo "--- 数据完整性验证 ---"
TOTAL=$(echo "$RESPONSE" | python3 -c "import sys, json; data=json.load(sys.stdin); print(data.get('data', {}).get('pagination', {}).get('total', 0))" 2>/dev/null)
LIST_COUNT=$(echo "$RESPONSE" | python3 -c "import sys, json; data=json.load(sys.stdin); print(len(data.get('data', {}).get('list', [])))" 2>/dev/null)
echo "总记录数: $TOTAL"
echo "当前页记录数: $LIST_COUNT"
# 检查数据字段完整性
echo ""
echo "--- 字段完整性检查 ---"
echo "$RESPONSE" | python3 -c "
import sys, json
data = json.load(sys.stdin)
items = data.get('data', {}).get('list', [])
if items:
first_item = items[0]
required_fields = ['StoreId', 'StoreName', 'StatisticsMonth', 'TotalPerformance',
'TotalOrderPerformance', 'ActualPerformance', 'FirstOrderCount',
'UpgradeOrderCount', 'ItemQuantity', 'RefundAmount', 'RefundCount']
missing_fields = []
for field in required_fields:
if field not in first_item:
missing_fields.append(field)
if missing_fields:
print(f'❌ 缺少字段: {missing_fields}')
else:
print('✅ 所有必需字段都存在')
# 验证数据逻辑
print('')
print('--- 数据逻辑验证 ---')
for i, item in enumerate(items[:3], 1):
total_perf = item.get('TotalPerformance', 0)
total_order = item.get('TotalOrderPerformance', 0)
actual = item.get('ActualPerformance', 0)
refund = item.get('RefundAmount', 0)
# 验证：实际业绩 = 总单业绩 - 退款金额
expected_actual = total_order - refund
if abs(actual - expected_actual) < 0.01:
print(f'{i}. {item.get(\"StoreName\", \"无\")}: ✅ 实际业绩计算正确')
else:
print(f'{i}. {item.get(\"StoreName\", \"无\")}: ❌ 实际业绩计算错误 (期望: {expected_actual:.2f}, 实际: {actual:.2f})')
else:
print('❌ 未找到数据')
" 2>/dev/null
echo ""
echo "=== 验证完成 ==="