that seems like a bit of extra thing a user needs to bother about.. better deployment model should be that its part of api-server deployment and configurable from UI itself.. may be i am asking too much 😛

yes delete experiments which are old or for some other reason are not required to keep around

Hi PompousParrot44 , you mean delete experiment?

PompousParrot44 obviously you can just archive a task and run the cleanup service, it will actually delete archived tasks older than X days.
https://github.com/allegroai/trains/blob/master/examples/services/cleanup/cleanup_service.py

Unfortunately, it is not possible to delete an experiment using the UI. You can run the script as a service like in the example or run it with job scheduler (crontab for example in linux) to execute it.

Can this do the trick?

i think for now it should do the trick... was just thinking about the roadmap part

You can loop over the tasks you want to delete, Based on the cleanup service:

` import logging

from trains.backend_api.session.client import APIClient

client = APIClient()

you can get the tasks you want to delete with client.tasks.get_all, in this example we will get you all the tasks in a project, but you have other filters too

tasks = client.tasks.get_all(project=[<your project id>])
for task in tasks:
try:
# try delete a task from system
client.tasks.delete(task=task.id) # you also have a force param, you can add force=True if you like
except Exception as ex:
logging.warning(
"Could not delete Task ID={}, {}".format(
task.id, ex.message if hasattr(ex, "message") else ex
)
) `This will delete all the tasks in a project for example

TimelyPenguin76 is there any way to do this using UI directly or as a schedule... otherwise i think i will run the cleanup_service as given in docs...