Do you have the same python version locally as remotely?
Some ways you could continue now:
you can reuse an existing python virtual environment: https://clear.ml/docs/latest/docs/clearml_agent/#virtual-environment-reuse

You can also run the agent in docker mode: https://clear.ml/docs/latest/docs/clearml_agent/#docker-mode

I'll have a look at the differences concerning the dev disappearing.

Have you tried --verbose ?

Just checking, are you just trying to use a different docker image in a task? Because then you might want to use this: https://clear.ml/docs/latest/docs/apps/clearml_task/#docker
https://clear.ml/docs/latest/docs/clearml_agent#docker-mode

Can you elaborate on the hidden project? Is this part of a task you created and something is not showing up?

I'm not sure if you can delete it when using pipelines but I would say try it on a new project?

It looks like there is this option under Settings->Configuration->Show Hidden Projects

I also learned :p

I think if you use explicit logging it only logs things you've selected but I'm not entirely sure
https://clear.ml/docs/latest/docs/guides/reporting/clearml_logging_example/

Also have a look at --memory-swap
It seems you might not anticipated this usage:

If --memory-swap is unset, and --memory is set, the container can use as much swap as the --memory setting, if the host container has swap memory configured. For instance, if --memory="300m" and --memory-swap is not set, the container can use 600m in total of memory and swap.

Wait, I noticed you need another set of quotes:
Sample in the docs is: --memory="300m"

https://docs.docker.com/config/containers/resource_constraints/

Wait... Will it limit memory usage but not show it in overview or just plain stop the container if it happens to use more memory?

Can you try again with "-m 16g" ?

Can you try: '${pipeline.docker_image}' ?

AnxiousSeal95 Do you know this one?

You can configure what to log and what not in the task init: https://clear.ml/docs/latest/docs/clearml_sdk/task_sdk/#automatic-logging

You can turn it all off by setting auto_connect_frameworks to false but you can do a finer grained control of logged frameworks with framework-boolean pairs

Typo will be fixed 🙂 https://github.com/allegroai/clearml-docs/pull/362

You can explicitly log them: https://clear.ml/docs/latest/docs/guides/reporting/scalar_reporting/

You can set where to store it via this config file: https://clear.ml/docs/latest/docs/fundamentals/artifacts/#setting-upload-destination

You can use the same project name and the same Taskname if that helps?

I don't think it's possible to set a custom ID if it doesn't exist yet. But I'll double check!

You can add them in env files:
https://clear.ml/docs/latest/docs/clearml_serving/clearml_serving_setup/#advanced-setup---s3gsazure-access-optional

PIP can install from git repositories!
So you can point to your own repository or even a specific commit hash.

https://pip.pypa.io/en/stable/topics/vcs-support/

Have you tried
logger = Logger.current_logger()in your code?
Logger is a singleton so you should get the same object from your previously created task
https://clear.ml/docs/latest/docs/references/sdk/logger/#loggercurrent_logger

I'm not sure about the preview part but after uploading I think you might find the images with list and --filter
https://clear.ml/docs/latest/docs/clearml_data/clearml_data_cli#list
I'm not sure if that helps?

To use a specific binary you can set in in the config: https://clear.ml/docs/latest/docs/configs/clearml_conf/#:~:text=python%20version%20(default)-,agent.python_binary,-(string)

But if you're trying to cache virtual environments you might be more interested in: https://clear.ml/docs/latest/docs/clearml_agent#environment-caching

Could it be multiple metrics that were combined into a single metric later on? Before the optimizer?

Do you mean in the WebUI or via the API?

You can get all tasks: https://clear.ml/docs/latest/docs/references/sdk/task#taskget_all

You can search tasks: https://clear.ml/docs/latest/docs/clearml_sdk/task_sdk#querying--searching-tasks

And you can get the status:
https://clear.ml/docs/latest/docs/references/sdk/task#get_status

Did you first init the Task?
https://clear.ml/docs/latest/docs/references/sdk/task/

ReassuredTiger98 you can set different parameters per task:
https://clear.ml/docs/latest/docs/clearml_sdk/task_sdk#configuration

Do you mean what's visible in the UI, projects -> Execution: Installed Packages?

If you're just looking to reuse virtual environments, have a look here: https://clear.ml/docs/latest/docs/clearml_agent/#environment-caching