chore: initialize tuhui repository
This commit is contained in:
Codex
214
backend/smart_dispatch_poller.py
Executable file
214
backend/smart_dispatch_poller.py
Executable file
@@ -0,0 +1,214 @@
|
||||
#!/usr/bin/env python3
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
智能轮询派单系统
|
||||
- 自动轮询派单队列
|
||||
- 负载均衡：轮流分配 + 工作量感知
|
||||
- 自动重试机制
|
||||
- 详细日志记录
|
||||
"""
|
||||
|
||||
import requests
|
||||
import time
|
||||
import json
|
||||
from datetime import datetime
|
||||
from collections import deque
|
||||
|
||||
# 配置
|
||||
API_BASE = "http://1.12.50.92:8005"
|
||||
API_KEY = "tuhui_dispatch_key_2026"
|
||||
HEADERS = {"X-API-Key": API_KEY}
|
||||
|
||||
# 轮询间隔（秒）
|
||||
POLL_INTERVAL = 10
|
||||
MAX_RETRIES = 3
|
||||
RETRY_DELAY = 3
|
||||
|
||||
# 负载均衡：记录最近分配的设计师（轮询分配）
|
||||
recent_assignments = deque(maxlen=10)
|
||||
|
||||
def log(message: str, level: str = "INFO"):
|
||||
"""打印日志"""
|
||||
timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
|
||||
print(f"[{timestamp}] [{level}] {message}")
|
||||
|
||||
def get_online_designers() -> list:
|
||||
"""获取在线设计师"""
|
||||
try:
|
||||
response = requests.get(f"{API_BASE}/online/designers", headers=HEADERS, timeout=5)
|
||||
if response.status_code == 200:
|
||||
data = response.json()
|
||||
return data["online_users"]
|
||||
except Exception as e:
|
||||
log(f"获取在线设计师失败：{e}", "ERROR")
|
||||
return []
|
||||
|
||||
def get_pending_tasks(limit: int = 10) -> list:
|
||||
"""获取待分配任务"""
|
||||
try:
|
||||
response = requests.get(f"{API_BASE}/tasks/pending", headers=HEADERS, timeout=5, params={"limit": limit})
|
||||
if response.status_code == 200:
|
||||
data = response.json()
|
||||
return data["tasks"]
|
||||
except Exception as e:
|
||||
log(f"获取待分配任务失败：{e}", "ERROR")
|
||||
return []
|
||||
|
||||
def get_designer_workload() -> dict:
|
||||
"""获取设计师工作量"""
|
||||
try:
|
||||
response = requests.get(f"{API_BASE}/designers/workload", headers=HEADERS, timeout=5)
|
||||
if response.status_code == 200:
|
||||
data = response.json()
|
||||
# 转换为字典：设计师 -> 待处理任务数
|
||||
return {d["designer"]: d["pending_tasks"] for d in data["designers"]}
|
||||
except Exception as e:
|
||||
log(f"获取工作量失败：{e}", "ERROR")
|
||||
return {}
|
||||
|
||||
def select_designer_smart(online_designers: list) -> str:
|
||||
"""
|
||||
智能选择设计师（负载均衡）
|
||||
|
||||
策略：
|
||||
1. 优先选最近没被分配的设计师（轮询）
|
||||
2. 如果都有任务，选工作量最少的
|
||||
3. 如果都没数据，随机选
|
||||
"""
|
||||
if not online_designers:
|
||||
return None
|
||||
|
||||
if len(online_designers) == 1:
|
||||
return online_designers[0]
|
||||
|
||||
# 策略 1：找最近没被分配的
|
||||
for designer in online_designers:
|
||||
if designer not in recent_assignments:
|
||||
log(f"选择设计师（轮询）：{designer}")
|
||||
return designer
|
||||
|
||||
# 策略 2：找工作量最少的
|
||||
workload = get_designer_workload()
|
||||
min_workload = float('inf')
|
||||
selected = None
|
||||
|
||||
for designer in online_designers:
|
||||
pending = workload.get(designer, 0)
|
||||
if pending < min_workload:
|
||||
min_workload = pending
|
||||
selected = designer
|
||||
|
||||
if selected:
|
||||
log(f"选择设计师（工作量最少：{min_workload}）：{selected}")
|
||||
return selected
|
||||
|
||||
# 策略 3：随机选第一个
|
||||
log(f"选择设计师（默认）：{online_designers[0]}")
|
||||
return online_designers[0]
|
||||
|
||||
def assign_task_with_retry(task_id: str, designer: str, max_retries: int = MAX_RETRIES) -> bool:
|
||||
"""带重试的分配任务"""
|
||||
for attempt in range(max_retries):
|
||||
try:
|
||||
response = requests.post(
|
||||
f"{API_BASE}/tasks/{task_id}/assign",
|
||||
headers=HEADERS,
|
||||
json={
|
||||
"designer_name": designer,
|
||||
"notes": "系统自动派单"
|
||||
},
|
||||
timeout=5
|
||||
)
|
||||
|
||||
if response.status_code == 200:
|
||||
log(f"✅ 任务 {task_id} 已分配给 {designer}", "SUCCESS")
|
||||
# 记录分配历史
|
||||
recent_assignments.append(designer)
|
||||
return True
|
||||
else:
|
||||
log(f"派单失败 (尝试 {attempt+1}/{max_retries}): {response.text}", "ERROR")
|
||||
|
||||
except Exception as e:
|
||||
log(f"网络错误 (尝试 {attempt+1}/{max_retries}): {e}", "ERROR")
|
||||
|
||||
if attempt < max_retries - 1:
|
||||
time.sleep(RETRY_DELAY)
|
||||
|
||||
return False
|
||||
|
||||
def poll_and_dispatch():
|
||||
"""主轮询函数"""
|
||||
log("🚀 智能轮询派单系统启动", "START")
|
||||
log(f"轮询间隔：{POLL_INTERVAL}秒")
|
||||
log(f"API 地址：{API_BASE}")
|
||||
|
||||
consecutive_errors = 0
|
||||
max_consecutive_errors = 10
|
||||
|
||||
while True:
|
||||
try:
|
||||
# 1. 获取待分配任务
|
||||
tasks = get_pending_tasks(limit=20)
|
||||
|
||||
if not tasks:
|
||||
log("📭 暂无待分配任务")
|
||||
consecutive_errors = 0
|
||||
time.sleep(POLL_INTERVAL)
|
||||
continue
|
||||
|
||||
log(f"📋 待分配任务：{len(tasks)} 个")
|
||||
|
||||
# 2. 获取在线设计师
|
||||
online_designers = get_online_designers()
|
||||
|
||||
if not online_designers:
|
||||
log("😴 暂无设计师在线")
|
||||
consecutive_errors = 0
|
||||
time.sleep(POLL_INTERVAL)
|
||||
continue
|
||||
|
||||
log(f"👥 在线设计师：{len(online_designers)} 人 - {', '.join(online_designers)}")
|
||||
|
||||
# 3. 按优先级排序任务
|
||||
tasks.sort(key=lambda x: x["priority"], reverse=True)
|
||||
|
||||
# 4. 智能分配
|
||||
assigned_count = 0
|
||||
for task in tasks:
|
||||
designer = select_designer_smart(online_designers)
|
||||
|
||||
if designer:
|
||||
success = assign_task_with_retry(task["task_id"], designer)
|
||||
if success:
|
||||
assigned_count += 1
|
||||
# 短暂等待，避免并发冲突
|
||||
time.sleep(0.5)
|
||||
else:
|
||||
log(f"❌ 任务 {task['task_id']} 分配失败", "ERROR")
|
||||
break # 停止分配，下次轮询再试
|
||||
else:
|
||||
log("⚠️ 无法选择设计师", "ERROR")
|
||||
break
|
||||
|
||||
log(f"📊 本轮分配：{assigned_count}/{len(tasks)} 个任务", "SUCCESS")
|
||||
consecutive_errors = 0
|
||||
|
||||
except Exception as e:
|
||||
log(f"❌ 轮询异常：{e}", "ERROR")
|
||||
consecutive_errors += 1
|
||||
|
||||
if consecutive_errors >= max_consecutive_errors:
|
||||
log(f"⚠️ 连续 {consecutive_errors} 次错误，等待 30 秒...", "WARNING")
|
||||
time.sleep(30)
|
||||
consecutive_errors = 0
|
||||
else:
|
||||
time.sleep(POLL_INTERVAL)
|
||||
|
||||
# 正常轮询间隔
|
||||
time.sleep(POLL_INTERVAL)
|
||||
|
||||
if __name__ == "__main__":
|
||||
try:
|
||||
poll_and_dispatch()
|
||||
except KeyboardInterrupt:
|
||||
log("👋 轮询派单系统已停止", "INFO")
|
||||
Reference in New Issue
Block a user