Yes it would be 🙂
Visualization is always a difficult topic... I'm not sure about that, but a callback would be nice.

One idea that comes to mind (this is of course limited to DataFrames), but think the git diff , where I imagine 3 independent section:
Removed columns (+ truncated preview of removed values) (see below) Added columns (+ truncated preview of removed values)
The middle column is then a bit complicated, but I would see some kind of "shared columns" dataframe, where each ...

When is the next release expected? 😄

Debugging. It's very useful for us to be able to see the contents of the configuration and understand what is going on and what is meant to be going on. Without a preview (which in our case is the entire content of the configuration file), one has to take an annoying route of downloading the files etc. The configurations are uploaded to a single task and then linked across all task to conserve storage space (so the S3 storage point is identical across tasks) Sure, sounds good. I think it's a ...

Basically when running remotely, the first argument to any configuration (whether object or string, or whatever) is ignored, right?

Same result 😞 This is frustrating, wtf happened :shocked_face_with_exploding_head:
This is also specifically the services queue worker I'm trying to debug 🤔

I'll have yet another look at both the latest agent RC and at the docker-compose, thanks!

There was no "default" services agent btw, just the queue, I had to launch an agent myself (not sure if it's relevant)

Yes; I tried running it both outside venv and inside a venv. No idea why it uses 2.7?

My current workaround is to use poetry and tell users to delete poetry.lock if they want their environment copied verbatim

JitteryCoyote63 I use clearml.config.get_remote_task_id()

I created a new task with the project name internal tests , and no task name (so it's derived by ClearML).
The task was a simple print out.
The project does not appear in the project space and does not turn up on searches (the task does)

So where should I install the latest clearml version? On the client that's running a task, or on the worker machine?

Oh! Nice! I'll have a go at it and report back at the PR if it's in a functional state 🙂 Thanks AgitatedDove14 !

Any follow up thoughts SuccessfulKoala55 or CostlyOstrich36 ?

It's not exactly "debugging", but rather a description of the generated model/framework (generated with pygraphviz).

Opened a matching feature request issue for this -> https://github.com/allegroai/clearml/issues/418

Actually, it appears some elements (scalars, plots, etc) have no migrated by moving mongodb data.
Where are these stored? Any idea @<1523701827080556544:profile|JuicyFox94> ?

Sure, for example when reporting HTML files:

One way to circumvent this btw would be to also add/use the --python flag for virtualenv

Great, thanks!

Should this be under the clearml or clearml-agent repo?

AFAIU, something like this happens (oversimplified):

` from clearml import Task # <--- Crash already happens here
import argparse
import dotenv

if name == "main":
# set up argparse with optional flag for a dotenv file
dotenv.load_dotenv(args.env_file)
# more stuff `

Based on where it hangs, I think this has to do with reporting the scatter plots.

This is with:
Task.set_offline_mode(True) task = Task.init(..., auto_connect_streams=False)

Thanks LazyFish41 , that explains it 👍

But there's nothing of that sort happening. The process where it's failing is on getting tasks for a project.

Hm, just a small update - I just verified and it does indeed work on linux:

` import clearml
import dotenv

if name == "main":
dotenv.load_dotenv()
config = clearml.backend_api.Config.load() # Success, parsed with environment variables `

It's given as the second form you suggested in the mini config ( http://${...}:8080 ). The quotation marks are added later by pyhocon.

Running a self-hosted server indeed. It's part of a code that simply adds or uploads an artifact 🤔

No, I have no running agents listening to that queue. It's as if it's retained in some memory somewhere and the server keeps creating it.

Ah. Apparently getting a task ID while it’s running can cause this behaviour 🤔