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# JSON格式日志输出示例
## 优化后的 `log_callback_request` 方法 - JSON格式日志
### 1. site_id 日志输出
```json
📝 site_id: "test-site-123"
```
### 2. 请求头日志输出（JSON格式）
```json
📋 请求头: {
"content-type": "application/json",
"authorization": "***REDACTED***",
"x-api-key": "***REDACTED***",
"user-agent": "python-httpx/0.25.2",
"accept": "application/json",
"content-length": "1024",
"host": "localhost:8000"
}
```
### 3. 请求体日志输出（JSON格式）
```json
📄 请求体: {
"count": 2,
"data": [
{
"bill": 100,
"duration": 60,
"callid": "test-call-123",
"calldate": "2024-01-01 12:00:00",
"number": "13800138000",
"numberid": "number-123",
"customer_id": "customer-123",
"status": 0,
"status_str": "失败",
"user_id": "user-123",
"type": 1,
"number_data": {
"number": "13800138000",
"province": "广东",
"city": "深圳",
"operator": "移动"
},
"group": {
"id": 1,
"name": "测试组"
},
"task": {
"id": "task-123",
"name": "测试任务"
},
"user": {
"id": "user-123",
"name": "测试用户"
},
"customer_data": {
"name": "测试客户",
"email": "test@example.com",
"company": "测试公司",
"extra": "额外信息"
}
}
]
}
```
### 4. server_ip 日志输出（JSON格式）
```json
🏠 server_ip: {
"ip": "0.0.0.0",
"port": 8000
}
```
### 5. client_ip 日志输出（JSON格式）
```json
🖥️ client_ip: {
"ip": "127.0.0.1",
"port": 52345
}
```
### 6. callback_data 日志输出（JSON格式）
```json
📦 callback_data: {
"count": 2,
"data_count": 1,
"data_sample": {
"bill": 100,
"duration": 60,
"callid": "test-call-123",
"calldate": "2024-01-01 12:00:00",
"number": "13800138000",
"numberid": "number-123",
"customer_id": "customer-123",
"status": 0,
"status_str": "失败",
"user_id": "user-123",
"type": 1,
"number_data": {
"number": "13800138000",
"province": "广东",
"city": "深圳",
"operator": "移动"
},
"group": {
"id": 1,
"name": "测试组"
},
"task": {
"id": "task-123",
"name": "测试任务"
},
"user": {
"id": "user-123",
"name": "测试用户"
},
"customer_data": {
"name": "测试客户",
"email": "test@example.com",
"company": "测试公司",
"extra": "额外信息"
}
}
}
```
## 完整的请求处理日志流程
### 单次请求的完整日志输出
```
2024-12-02 16:30:15 - routes - INFO - 🔥 收到AI Talk回调请求: siteId=test-site-123, count=2, data_count=1
2024-12-02 16:30:15 - routes - INFO - 📝 site_id: "test-site-123"
2024-12-02 16:30:15 - routes - INFO - 📋 请求头: {
"content-type": "application/json",
"authorization": "***REDACTED***",
"user-agent": "python-httpx/0.25.2",
"accept": "application/json",
"content-length": "1024",
"host": "localhost:8000"
}
2024-12-02 16:30:15 - routes - INFO - 📄 请求体: {
"count": 2,
"data": [
{
"bill": 100,
"duration": 60,
"callid": "test-call-123",
"calldate": "2024-01-01 12:00:00",
"number": "13800138000",
"numberid": "number-123",
"customer_id": "customer-123",
"status": 0,
"status_str": "失败",
"user_id": "user-123",
"type": 1,
"number_data": {
"number": "13800138000",
"province": "广东",
"city": "深圳",
"operator": "移动"
},
"group": {
"id": 1,
"name": "测试组"
},
"task": {
"id": "task-123",
"name": "测试任务"
},
"user": {
"id": "user-123",
"name": "测试用户"
},
"customer_data": {
"name": "测试客户",
"email": "test@example.com",
"company": "测试公司",
"extra": "额外信息"
}
}
]
}
2024-12-02 16:30:15 - routes - INFO - 🏠 server_ip: {
"ip": "0.0.0.0",
"port": 8000
}
2024-12-02 16:30:15 - routes - INFO - 🖥️ client_ip: {
"ip": "127.0.0.1",
"port": 52345
}
2024-12-02 16:30:15 - routes - INFO - 📦 callback_data: {
"count": 2,
"data_count": 1,
"data_sample": {
"bill": 100,
"duration": 60,
"callid": "test-call-123",
"calldate": "2024-01-01 12:00:00",
"number": "13800138000",
"numberid": "number-123",
"customer_id": "customer-123",
"status": 0,
"status_str": "失败",
"user_id": "user-123",
"type": 1,
"number_data": {
"number": "13800138000",
"province": "广东",
"city": "深圳",
"operator": "移动"
},
"group": {
"id": 1,
"name": "测试组"
},
"task": {
"id": "task-123",
"name": "测试任务"
},
"user": {
"id": "user-123",
"name": "测试用户"
},
"customer_data": {
"name": "测试客户",
"email": "test@example.com",
"company": "测试公司",
"extra": "额外信息"
}
}
}
2024-12-02 16:30:15 - routes - INFO - ✅ 回调请求记录成功保存到数据库，ID: 123
2024-12-02 16:30:15 - routes - INFO - 📞 count=2 < 3，调用外部API
2024-12-02 16:30:15 - routes - DEBUG - 🔒 获取Redis锁成功: external_api_call_test-site-123_2
```
## JSON格式日志的优势
### 1. 结构化数据
- 每个字段都以标准JSON格式输出
- 便于程序解析和处理
- 支持复杂的嵌套数据结构
### 2. 可读性强
- JSON格式具有良好的层次结构
- 缩进格式便于人工阅读
- 支持中文字符（`ensure_ascii=False`）
### 3. 便于分析
- 可以直接使用JSON工具解析
- 支持日志分析工具（如ELK、Fluentd等）
- 便于数据提取和统计
### 4. 安全性
- 敏感信息自动过滤为 `***REDACTED***`
- 保持数据结构完整性
- 避免敏感信息泄露
## 日志分析示例
### 使用jq工具分析JSON日志
```bash
# 提取所有site_id
grep "📝 site_id:" logs/app.log | jq -r '.📝 site_id'
# 提取所有client_ip信息
grep "🖥️ client_ip:" logs/app.log | jq -r '.🖥️ client_ip.ip'
# 统计不同count值的请求
grep "📦 callback_data:" logs/app.log | jq -r '.📦 callback_data.count' | sort | uniq -c
# 提取包含特定号码的请求
grep "📄 请求体:" logs/app.log | jq 'select(.📄 请求_body.data[].number == "13800138000")'
```
### 使用Python分析JSON日志
```python
import json
import re
# 解析日志中的JSON数据
def parse_json_logs(log_file):
site_ids = []
client_ips = []
with open(log_file, 'r', encoding='utf-8') as f:
for line in f:
if '📝 site_id:' in line:
# 提取JSON部分
json_str = line.split('📝 site_id: ')[1].strip()
site_id = json.loads(json_str)
site_ids.append(site_id)
elif '🖥️ client_ip:' in line:
json_str = line.split('🖥️ client_ip: ')[1].strip()
client_info = json.loads(json_str)
client_ips.append(client_info['ip'])
return site_ids, client_ips
```
## 性能考虑
### 1. JSON序列化开销
- 使用标准库`json.dumps()`
- `ensure_ascii=False` 支持中文但略慢
- 对于高频调用，可考虑关闭详细日志
### 2. 日志文件大小
- JSON格式比纯文本占用更多空间
- 建议合理设置日志轮转大小
- 生产环境可考虑使用压缩存储
### 3. 内存使用
- 大型请求体会占用较多内存
- `callback_data` 只记录摘要信息，避免完整数据
## 配置建议
### 开发环境
```bash
LOG_LEVEL=INFO # 显示所有JSON日志
```
### 生产环境
```bash
LOG_LEVEL=WARNING # 只显示重要信息，减少JSON日志量
```
### 调试特定问题
```bash
# 临时开启详细日志
LOG_LEVEL=DEBUG
# 问题解决后恢复
LOG_LEVEL=INFO
```
现在 `log_callback_request` 方法以JSON格式输出所有关键信息，便于日志分析和系统监控！