本文目录导读：
Python脚本（推荐）
基础结构
import pandas as pd
import os
from datetime import datetime
class InspectionSummary:
def __init__(self, data_dir='./inspection_data'):
self.data_dir = data_dir
self.all_data = []
def read_data(self):
"""读取所有巡检数据文件"""
for filename in os.listdir(self.data_dir):
if filename.endswith(('.csv', '.xlsx', '.txt')):
filepath = os.path.join(self.data_dir, filename)
try:
if filename.endswith('.csv'):
df = pd.read_csv(filepath)
elif filename.endswith('.xlsx'):
df = pd.read_excel(filepath)
self.all_data.append(df)
except Exception as e:
print(f"读取文件 {filename} 失败: {e}")
def summarize(self):
"""生成汇总报告"""
if not self.all_data:
return pd.DataFrame()
# 合并所有数据
combined_df = pd.concat(self.all_data, ignore_index=True)
# 生成汇总统计
summary = {
'总巡检次数': len(combined_df),
'巡检日期范围': f"{combined_df['巡检日期'].min()} 至 {combined_df['巡检日期'].max()}",
'异常数量': len(combined_df[combined_df['状态'] == '异常']),
'正常数量': len(combined_df[combined_df['状态'] == '正常']),
'异常率': f"{(len(combined_df[combined_df['状态'] == '异常']) / len(combined_df) * 100):.2f}%"
}
return summary
# 使用示例
if __name__ == "__main__":
inspector = InspectionSummary('./inspection_data')
inspector.read_data()
summary = inspector.summarize()
print("巡检汇总结果:", summary)
Shell脚本（适合Linux环境）
#!/bin/bash
# 巡检数据汇总脚本
DATA_DIR="./inspection_data"
SUMMARY_FILE="./summary_report.txt"
# 初始化汇总文件
echo "========== 巡检数据汇总报告 ==========" > $SUMMARY_FILE
echo "生成时间: $(date)" >> $SUMMARY_FILE
echo "" >> $SUMMARY_FILE
# 统计各类信息
total_files=0
total_records=0
abnormal_count=0
for file in $DATA_DIR/*.log; do
if [ -f "$file" ]; then
total_files=$((total_files + 1))
records=$(wc -l < "$file")
total_records=$((total_records + records))
# 统计异常记录
abnormal=$(grep -c "异常\|FAIL\|ERROR\|WARNING" "$file")
abnormal_count=$((abnormal_count + abnormal))
fi
done
# 写入汇总结果
echo "文件总数: $total_files" >> $SUMMARY_FILE
echo "总记录数: $total_records" >> $SUMMARY_FILE
echo "异常记录数: $abnormal_count" >> $SUMMARY_FILE
echo "异常率: $(echo "scale=2; $abnormal_count/$total_records*100" | bc)%" >> $SUMMARY_FILE
echo "" >> $SUMMARY_FILE
echo "详细文件列表:" >> $SUMMARY_FILE
ls -la $DATA_DIR/ >> $SUMMARY_FILE
echo "汇总报告已生成: $SUMMARY_FILE"
SQL查询（数据库巡检数据）
-- 巡检数据汇总查询
SELECT
DATE_FORMAT(inspection_date, '%Y-%m-%d') as 巡检日期,
COUNT(*) as 巡检次数,
SUM(CASE WHEN status = 'normal' THEN 1 ELSE 0 END) as 正常次数,
SUM(CASE WHEN status = 'abnormal' THEN 1 ELSE 0 END) as 异常次数,
CONCAT(
ROUND(
SUM(CASE WHEN status = 'abnormal' THEN 1 ELSE 0 END) / COUNT(*) * 100,
2
),
'%'
) as 异常率,
GROUP_CONCAT(DISTINCT location) as 巡检地点
FROM inspection_records
WHERE inspection_date BETWEEN '2024-01-01' AND '2024-12-31'
GROUP BY DATE_FORMAT(inspection_date, '%Y-%m-%d')
ORDER BY inspection_date;
-- 汇总统计
SELECT
COUNT(DISTINCT inspection_date) as 巡检天数,
COUNT(*) as 总巡检次数,
SUM(CASE WHEN status = 'abnormal' THEN 1 ELSE 0 END) as 总异常次数,
ROUND(AVG(
CASE WHEN status = 'abnormal' THEN 1 ELSE 0 END
) * 100, 2) as 平均异常率
FROM inspection_records;
高级功能实现
带邮件通知的Python脚本
import smtplib
from email.mime.text import MIMEText
from email.mime.multipart import MIMEMultipart
class InspectionReport:
def __init__(self):
self.data = []
self.summary = {}
def generate_report(self):
"""生成HTML格式报告"""
html = """
<html>
<body>
<h2>巡检数据汇总报告</h2>
<table border="1">
<tr>
<th>指标</th>
<th>数值</th>
</tr>
"""
for key, value in self.summary.items():
html += f"<tr><td>{key}</td><td>{value}</td></tr>"
html += """
</table>
</body>
</html>
"""
return html
def send_email(self, subject, html_content):
"""发送邮件报告"""
sender = 'your_email@example.com'
receiver = 'manager@example.com'
password = 'your_password'
msg = MIMEMultipart('alternative')
msg['Subject'] = subject
msg['From'] = sender
msg['To'] = receiver
msg.attach(MIMEText(html_content, 'html'))
with smtplib.SMTP_SSL('smtp.example.com', 465) as server:
server.login(sender, password)
server.sendmail(sender, receiver, msg.as_string())
定时执行脚本（crontab配置）
# 每天早上8点执行 0 8 * * * /usr/bin/python3 /path/to/inspection_summary.py # 每周一执行 0 9 * * 1 /path/to/shell_script.sh # 每月1号执行 0 10 1 * * /path/to/script.sh
使用建议
- 数据格式：统一使用CSV或Excel格式存储巡检数据
- 字段规范：包含日期、时间、地点、巡检人员、状态、备注等字段
- 异常处理：添加try-catch处理文件读取异常
- 日志记录：记录脚本执行日志便于排查问题
- 权限控制：设置合适的文件读写权限
- 备份机制：自动备份原始数据和汇总结果
根据你的具体需求（文件格式、输出要求、运行环境等），选择适合的方案进行修改和扩展。
