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