Scheduled jobs and workflows#

Oftentimes you may want to run a job on a regular schedule. For example, fetching from a datasource every morning, compiling an analytics report every month, or detecting model drift every hour.

Create a job#

MLRun makes it very simple to add a schedule to a given job. To showcase this, the following job runs the code below, which resides in a file titled schedule.py:

def hello(context):
    print("You just ran a scheduled job!")

To create the job, use the code_to_function syntax and specify the kind like below:

import mlrun

job = mlrun.code_to_function(
    name="my-scheduled-job",      # Name of the job (displayed in console and UI)
    filename="schedule.py",       # Python file or Jupyter notebook to run
    kind="job",                   # Run as a job
    image="mlrun/mlrun",          # Use this Docker image
    handler="hello"               # Execute the function hello() within code.py
)

Add a schedule#

To add a schedule, run the job and specify the schedule parameter using Cron syntax like so:

job.run(schedule="0 * * * *")

This runs the job every hour. An excellent resource for generating Cron schedules is Crontab.guru.