Python定时任务工具之APScheduler使用方式

from apscheduler.schedulers.background import BlockingScheduler
#
 创建定时任务的调度器对象
scheduler = BlockingScheduler()
# 创建执行器
executors = {
 'default': ThreadPoolExecutor(20),
}
# 定义定时任务
def my_job(param1, param2): # 参数通过add_job()args传递传递过来
 print(param1) # 100
 print(param2) # python
# 向调度器中添加定时任务
scheduler.add_job(my_job, 'date', args=[100, 'python'], executors=executors)
# 启动定时任务调度器工作
scheduler.start()

from apscheduler.schedulers.blocking import BlockingScheduler
scheduler = BlockingScheduler()
scheduler.start() # 此处程序会发生阻塞
BackgroundScheduler : 在框架程序（如Django、Flask）中使用.
from apscheduler.schedulers.background import BackgroundScheduler
scheduler = BackgroundScheduler()
scheduler.start() # 此处程序不会发生阻塞

ThreadPoolExecutor
from apscheduler.executors.pool import ThreadPoolExecutor
ThreadPoolExecutor(max_workers) 

from apscheduler.executors.pool import ThreadPoolExecutor
executors = {
  'default': ThreadPoolExecutor(20) # 最多20个线程同时执行
 }
 scheduler = BackgroundScheduler(executors=executors)
ProcessPoolExecutor

from apscheduler.executors.pool import ProcessPoolExecutor
ProcessPoolExecutor(max_workers)

from apscheduler.executors.pool import ProcessPoolExecutor
executors = {
  'default': ProcessPoolExecutor(5) # 最多5个进程同时执行
 }
scheduler = BackgroundScheduler(executors=executors)

from datetime import date
# 在2019年11月6日00:00:00执行
sched.add_job(my_job, 'date', run_date=date(2019, 11, 6))
# 在2019年11月6日16:30:05
sched.add_job(my_job, 'date', run_date=datetime(2009, 11, 6, 16, 30, 5))
sched.add_job(my_job, 'date', run_date='2009-11-06 16:30:05')
# 立即执行
sched.add_job(my_job, 'date') 
sched.start()

weeks (int) – number of weeks to wait
days (int) – number of days to wait
hours (int) – number of hours to wait
minutes (int) – number of minutes to wait
seconds (int) – number of seconds to wait
start_date (datetime|str) – starting point for the interval calculation
end_date (datetime|str) – latest possible date/time to trigger on
timezone (datetime.tzinfo|str) – time zone to use for the date/time calculations
from datetime import datetime
# 每两小时执行一次
sched.add_job(job_function, 'interval', hours=2)
# 在2012年10月10日09:30:00 到2014年6月15日11:00:00的时间内，每两小时执行一次
sched.add_job(job_function, 'interval', hours=2, start_date='2012-10-10 09:30:00', end_date='2014-06-15 11:00:00')

year (int|str) – 4-digit year

month (int|str) – month (1-12)

day (int|str) – day of the (1-31)

week (int|str) – ISO week (1-53)

day_of_week (int|str) – number or name of weekday (0-6 or mon,tue,wed,thu,fri,sat,sun)

hour (int|str) – hour (0-23)

minute (int|str) – minute (0-59)

second (int|str) – second (0-59)

start_date (datetime|str) – earliest possible date/time to trigger on (inclusive)

end_date (datetime|str) – latest possible date/time to trigger on (inclusive)

timezone (datetime.tzinfo|str) – time zone to use for the date/time calculations (defaults to scheduler timezone)

# 在6、7、8、11、12月的第三个周五的00:00, 01:00, 02:00和03:00 执行
sched.add_job(job_function, 'cron', month='6-8,11-12', day='3rd fri', hour='0-3')

# 在2014年5月30日前的周一到周五的5:30执行
sched.add_job(job_function, 'cron', day_of_week='mon-fri', hour=5, minute=30, end_date='2014-05-30')

MemoryJobStore 默认内存存储
MongoDBJobStore 任务保存到MongoDB
from apscheduler.jobstores.mongodb import MongoDB
JobStoreMongoDBJobStore()复制代码
RedisJobStore 任务保存到redis
from apscheduler.jobstores.redis import RedisJobStore
RedisJobStore()

from apscheduler.schedulers.background import BackgroundScheduler
from apscheduler.executors.pool import ThreadPoolExecutor

executors = {
 'default': ThreadPoolExecutor(20),
}
conf = { # redis配置
 "host":127.0.0.1,
 "port":6379,
 "db":15, # 连接15号数据库
 "max_connections":10 # redis最大支持300个连接数
}
scheduler = BackgroundScheduler(executors=executors)
scheduler.add_jobstore(jobstore='redis', **conf) # 添加任务持久化存储方式,如果未安装redis可省略此步骤

from pytz import utc

from apscheduler.schedulers.background import BackgroundScheduler
from apscheduler.jobstores.sqlalchemy import SQLAlchemyJobStore
from apscheduler.executors.pool import ProcessPoolExecutor
executors = {
 'default': {'type': 'threadpool', 'max_workers': 20},
 'processpool': ProcessPoolExecutor(max_workers=5)
}
scheduler = BackgroundScheduler()
# .. 此处可以编写其他代码
# 使用configure方法进行配置
scheduler.configure(executors=executors)

job = scheduler.add_job(myfunc, 'interval', minutes=2) # 添加任务
job.remove() # 删除任务
job.pause() # 暂定任务
job.resume() # 恢复任务

scheduler.add_job(myfunc, 'interval', minutes=2, id='my_job_id') # 添加任务 
scheduler.remove_job('my_job_id') # 删除任务
scheduler.pause_job('my_job_id') # 暂定任务
scheduler.resume_job('my_job_id') # 恢复任务

job.modify(max_instances=6, name='Alternate name')
scheduler.reschedule_job('my_job_id', trigger='cron', minute='*/5')复制代码
停止APScheduler运行
scheduler.shutdown()

from apscheduler.executors.pool import ThreadPoolExecutor
from datetime import datetime, timedelta
from apscheduler.schedulers.blocking import BackgroundScheduler
from goods.models import SKU
from orders.models import OrderGoods
def cancel_order_job(order_id, sku_id, stock, sales):
 # 将订单商品和订单信息筛选出来
 order_goods = OrderGoods.objects.filter( order_id=order_id, sku_id=sku_id)
 order_goods.delete() # 删除订单
 try:
  sku = SKU.objects.get(id=sku_id)
  sku.stock += stock # 订单删掉后商品表里的库存恢复
  sku.sales -= sales # 商品表里销量还原
  sku.save()
 except Exception as e:
  print(e)

from datetime import datetime, timedelta

class OrderCommitView(View)：

 def post(self, request):
 # ... 此处省略生成订单相关逻辑
   if status == OrderInfo.STATUS.UNPADED: # 待支付状态
  
    executors = {
    'default': ThreadPoolExecutor(10) 
    }
    now = datetime.now()
    delay = now + timedelta(minutes=30) # 从当前下订单延时30分钟后
    scheduler = BackgroundScheduler(executors=executors)
    # 添加定时任务
    scheduler.add_job(cancel_order_job, 'date', run_date=delay,
    args=[order_id, sku.id, sku.stock, sku.sales])
    scheduler.start()
    # ....省略其他业务及返回