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How to install and use the third-party module apscheduler in Python?

王林forward: 2023-05-08 10:04:171594browse

apscheduler module

Install apscheduler module

pip install apscheduler

apscheduler module introduction

APScheduler（ Advanced Python Scheduler) is a lightweight Python scheduled task scheduling framework (Python library).

APScheduler has three built-in scheduling systems, including:

cron-style scheduling (optional start/end time)
Interval-based execution (run the job at even intervals, you can also choose the start/end time)
One-time delayed execution of the task (run the job once at the specified date/time)

Supported backend storage jobs

APScheduler can arbitrarily mix and match the backend of the scheduling system and job storage. Supported backend storage jobs include:

Memory
##SQLAlchemy
MongoDB
Redis
RethinkDB
ZooKeeper

APScheduler has four components

Triggers (triggers) contain scheduling logic, and each job has its own trigger to determine the next running time. Apart from their own initial configuration, triggers are completely stateless.
job stores (job storage) store scheduled jobs. The default job store simply saves the job in memory, and other job stores save the job in the database. . When a job is saved to a persistent job store, the job's data is serialized and deserialized on load. Job storage cannot share the scheduler.
Executors handle the running of jobs. They usually do this by submitting specified callable objects to a thread or process pool in the job. When the job is completed, the executor will notify the scheduler.
schedulers (Scheduler) Configuring job storage and executors can be done in the scheduler, such as adding, modifying and removing jobs. Different schedulers can be selected according to different application scenarios. There are 7 options available: BlockingScheduler, BackgroundScheduler, AsyncIOScheduler, GeventScheduler, TornadoScheduler, TwistedScheduler, and QtScheduler.

Introduction to each component

Trigger

When you schedule a job, you need to select a trigger for this job to describe this When the job is triggered, APScheduler has three built-in trigger types:

date: a one-time specified date;
interval: at a certain time How often to execute within a time range;
cron: Linux crontab format is compatible and the most powerful.

date The most basic kind of scheduling, the job will only be executed once. Its parameters are as follows:

1.run_date

(datetime|str) – The running date or time of the job

2.timezone

(datetime.tzinfo|str) &ndash ; Specify time zone

Job Storage

If your application will re-create the job every time it is started, then use the default job store (MemoryJobStore), But if you need to retain jobs despite scheduler restarts or application crashes, you should choose a specific job store based on your application environment. For example: use Mongo or SQLAlchemy JobStore (used to support most RDBMS)

executor

The choice of executor depends on which of the above frameworks you use, most In this case, using the default ThreadPoolExecutor can already meet the needs. If your application involves

CPU-intensive operations, you may consider using ProcessPoolExecutor to use more CPU cores. You can also use both at the same time, using ProcessPoolExecutor as the second executor.

Choose the right scheduler

BlockingScheduler: When the scheduler is the only thing running in your application
BackgroundScheduler : Use when you are not running any other framework and want the scheduler to execute in the background of your app.
AsyncIOScheduler: Used when your program uses asyncio (an asynchronous framework).
GeventScheduler: Used when your program uses gevent (a high-performance Python concurrency framework).
TornadoScheduler: Used when your program is based on Tornado (a web framework).
TwistedScheduler: Use when your program uses Twisted (an asynchronous framework)
QtScheduler: If your application is a Qt Can be used when applying.

apscheduler module uses

Add job

There are two ways to add a new job:

add_job to add a job ;

# -*- coding:utf-8 -*-
from apscheduler.schedulers.blocking import BlockingScheduler
import datetime

def my_job1():
    print(&#39;my_job1 is running, Now is %s&#39; % datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"))

def my_job2():
    print(&#39;my_job2 is running, Now is %s&#39; % datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"))

sched = BlockingScheduler()
# 每隔5秒运行一次my_job1
sched.add_job(my_job1, &#39;interval&#39;, seconds=5, id=&#39;my_job1&#39;)
# 每隔5秒运行一次my_job2
sched.add_job(my_job2, &#39;cron&#39;, second=&#39;*/5&#39;, id=&#39;my_job2&#39;)
sched.start()

Decorator mode adds jobs.

# -*- coding:utf-8 -*-
from apscheduler.schedulers.blocking import BlockingScheduler
import datetime

sched = BlockingScheduler()

# 每隔5秒运行一次my_job1
@sched.scheduled_job(&#39;interval&#39;, seconds=5, id=&#39;my_job1&#39;)
def my_job1():
    print(&#39;my_job1 is running, Now is %s&#39; % datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"))

# 每隔5秒运行一次my_job2
@sched.scheduled_job(&#39;cron&#39;, second=&#39;*/5&#39;, id=&#39;my_job2&#39;)
def my_job2():
    print(&#39;my_job2 is running, Now is %s&#39; % datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"))

sched.start()