Python Scheduler

A Python library supporting task scheduling.

Installation

Install the package using pip:

pip install python-cli-scheduler

Schedule Format

The scheduler format defines how tasks are executed. Use:

^<run_now>@<interval>/<delay>$<end_timestamp>#<retry>

Parameters

Usage

Use a Decorator

You can use the scheduler_handle decorator to execute recurring tasks. Below is an example that prints a random "lucky number" every 10 seconds, starting at the 3rd second, and continues for 30 seconds.

import random
import time

from cli_scheduler import scheduler_handle

end_time = int(time.time()) + 30


@scheduler_handle(schedule=f'^true@10/3${end_time}#true')
def rotation_lucky(start=0, end=1000):
    n = random.randint(start, end)
    print(f'The lucky number is {n}')


if __name__ == '__main__':
    rotation_lucky(10, end=100)

Using a Scheduler Job Class

With SchedulerJob, you gain more control over the task execution lifecycle. This example runs a job every 60 seconds, starting at the 3rd second, for 5 minutes. It logs the task lifecycle phases and prints a "lucky number."

import time
import random

from cli_scheduler import SchedulerJob


class RotationLuckJob(SchedulerJob):
    def __init__(self, scheduler):
        super().__init__(scheduler=scheduler)

    def _pre_start(self):
        self.logger.info('Rotation luck. Have fun !')
        
    def _start(self):
        self.n = random.randint(0, 1000)

    def _execute(self, *args, **kwargs):
        self.logger.info(f'The lucky number is {self.n}')
    
    def _end(self):
        del self.n
        
    def _follow_end(self):
        self.logger.info('Done')

        
if __name__ == '__main__':
    end_time = int(time.time()) + 5 * 60

    # ^false: Not execute now
    # @60: Repeat execute every 60 second
    # /3: Execute at second 3
    # ${end_time}: Run until end_time
    # #false: Don't retry if exception when execute
    job = RotationLuckJob(scheduler=f'^false@60/3${end_time}#false')
    job.run()

Features

• Task Scheduling: Automates task execution using a flexible crontab-like syntax.

• Decorator Support: Simplifies task scheduling using Python function decorators.

• Lifecycle Hooks: Gain fine-grained control with SchedulerJob methods:

  • _pre_start: Preparation before starting the task.
  • _start: Runs once before task execution begins.
  • _execute: The core task logic is implemented here.
  • _end: Final cleanup after task execution ends.
  • _follow_end: Actions to follow the end of the task lifecycle.

• Retry Support: Retry tasks in case of runtime exceptions.

License

This library is licensed under the MIT License. See the LICENSE file for more details.

Contributing

Contributions are welcome! Feel free to submit issues, feature requests, or pull requests to improve the library.