Update code from existing schedules in AzureML using Python SDK v2

I would like to update the code and / or other files uploaded to the code folder being used by a specific scheduled job, keeping everything else, in particular the schedule details (time of day etc.), using python SDK v2.

# --------------------------------------------------------------------------------------------------
# Connect to AML and set tracking URI in mlflow
# --------------------------------------------------------------------------------------------------
from azure.ai.ml import MLClient
from azure.identity import DefaultAzureCredential, InteractiveBrowserCredential
from azureml.core.experiment import Experiment
from azureml.core.workspace import Workspace

@pipeline
def my_pipeline (
   # some args...
):
   my_first_component = command(
      # some args ...
      code="my_new_code_folder_to_upload" # this is where the new code, config files, etc. are placed
   )
   my_first_component = my_first_component (
      # some args ...
   )

def update_schedule (schedule_name, experiment_name=None):
   # Connect to AML
   ml_client = MLClient(
         credential= InteractiveBrowserCredential(),
         subscription_id="my-subscription-id",
         resource_group_name="my-resource-group",
         workspace_name="my-workspace"
         )

   job_object = my_pipeline(
      # some args ...
   )

   job = (
        ml_client.jobs.create_or_update(job_object, experiment_name=experiment_name)
        if experiment_name is not None
        else ml_client.jobs.create_or_update(job_object)
    )
   
   job_schedule = ml_client.schedules.get(schedule_name)

   job_schedule = JobSchedule(
      name=schedule_name, trigger=job_schedule.trigger, create_job=job_object
   )

   job_schedule = ml_client.schedules.begin_create_or_update(
      schedule=job_schedule
   ).result()

   # Uncomment below if running asynchronously (to avoid blocking execution until job finishes)
   ml_client.jobs.stream(job.name)