You can use Google Cloud Scheduler which is a fully managed enterprise-grade cron job scheduler. It allows you to schedule virtually any job, including batch, big data jobs, cloud infrastructure operations.

The first 3 jobs per month are free. Next are $0.10 per job/month.

Cloud functions aren't really suited to batch jobs that may be longer running than 10 minutes. I'd suggest running your job using a Compute Engine VM and scheduling it with a combination of Cloud functions / Cloud scheduler.

Here's a rough outline:

1. Set up a containerized Compute Engine VM.
2. Create a Cloud function to start the VM on a pub-sub trigger.

import googleapiclient.discovery

def start_job(event, context):
    """Triggered from a message on a Cloud Pub/Sub topic.
    Args:
         event (dict): Event payload.
         context (google.cloud.functions.Context): Metadata for the event.
    """
    compute = googleapiclient.discovery.build('compute', 'v1')
    compute.instances().insert(
        project='project_id',
        zone='us-east1-b',
        body=vm_config).execute()

3. Create a Cloud Scheduler to trigger the pub-sub according to your schedule.

This lets you avoid the cost of an always-on VM. See this blog post for more detail.

I think a Cloud Scheduler may a be a good first solution/approach. It can, for example, make some http request, or push a message into a pubsub (which can be used as a pull or push trigger for your script).

Under the script I understand any required functionality. It can be implemented in many different ways - Cloud Function (or a group of different Cloud Functions working together to archive one goal), a Cloud Run, or anything else.

My usual personal preference is a pattern Cloud Scheduler => PubSub Topic => push Cloud Function. Other people may prefer other variations.

The choice of the solution (including the "script" implementation) in your case - I think - depends on functional and non functional requirements, context, scope, skills and knowledge of people who are to develop and maintain the solution, time, CAPEX and OPEX budget, etc.

Like guillaume blaquiere and glen yu mentioned you can’t trigger a python script from gcs storage directly either you need to deploy it as a cloud function or cloud run. I think you have misinterpreted the google cloud docs, while creating a cloud function there is a step for uploading your code into GCS for version control and for having a backup, then you will create an entry point and a pub sub topic for your cloud scheduler to trigger the cloud function. Deploying your code using cloud storage steps in cloud function documentation, there is more information provided in this documentation on how to achieve this. Now once you have deployed your cloud function using gcs bucket you just need to create a trigger by using a pub/sub topic which will be used in your cloud scheduler for triggering the cloud function, follow this document for more information.

Note: This solution has been framed using the information available in google cloud docs and official links are embedded into the post at respective topics.