>pip show clearml
WARNING: Ignoring invalid distribution -upyterlab (c:\users\...\lib\site-packages)
WARNING: Ignoring invalid distribution -illow (c:\users\...\lib\site-packages)
Name: clearml
Version: 1.6.4
Summary: ClearML - Auto-Magical Experiment Manager, Version Control, and MLOps for AI
Home-page: None
`Auth...

Ah, wait, when I run the entire script, I do see the respective information in "execution".

But then I do not see the "installed packages" in "excecution".

It means "The syntax for the file name, folder name or volume label / disk is wrong" somthing along those lines. The [...] is the directory path to my project, which I opened in PyCharm and from which I run the commands in the Python Console.

"uncommitted changes" and "container" is also empty.

My entire code is

from clearml import Task, TaskTypes
task = Task.init(project_name='FirstTrial', task_name='first_trial', task_type=TaskTypes.training)
PACKAGE_VERSION = '0.4.1'
dataset_name = "Demodata"

which I - now - also ran as a whole script.

GrittyStarfish67 : Thanks! But how are those for ClearML vs MLRun? Granted, ClearML has a ~5 times more github stars than MLRun, but besides that: Both are from mid 2019 according to releases on git. I have not been in their slack and I know nothing about community adoption. (Btw, Kedro has twice as many stars than ClearML - even if it has far fewer feature, those that it does have, seem pretty well done.)

AgitatedDove14 : Not sure: They also have the feature store (data management), as mentioned, which is pretty MLOps-y 🙂 . Also, they do have workflows ( https://docs.mlrun.org/en/latest/concepts/multi-stage-workflows.html ) and artifacts/model management ( https://docs.mlrun.org/en/latest/store/artifacts.html ) and serving ( https://docs.mlrun.org/en/latest/serving/serving-graph.html ).

How would you compare those to ClearML?

I am using professional version 1.6.4.

@<1523701083040387072:profile|UnevenDolphin73>

But still, in the web app the task is considered to be still "running". I am not sure what to do, so that the task is considered to be "completed".

I have... its included in None

@<1523701205467926528:profile|AgitatedDove14>

@<1523701205467926528:profile|AgitatedDove14> : "does that make sense ?" Not really.

"you do not need to automatically Add/Log/Track things into the Task in the current process." - I do not need to automatically do [...]? You mean I can do it automatically, but alternatively I can do it manually? Do you mean I use close within a process to prevent automatic logging/adding/tracking? But, as far as I know, after I used close I am not able to log etc. manually either. So...

"Mark...

Ah... if I run the same script not from PyCharm, but from the terminal, then it gets completed... puh...

GrittyStarfish67 : In terms of "has a good name" you literally mean the name or do you mean, they have a good reputation 😄 ?

@<1523701205467926528:profile|AgitatedDove14> In the documentation it warns about .close() "Only call Task.close if you are certain the Task is not needed."
What does the documentation refer to? My understanding would be that if close the task within a program, I am not able to use the task object anymore as before and I need to retrieve it via query_tasks to get it again. Is that correct?

I am running it in the Python Console in PyCharm with Task.init. I get with the log:

ClearML Task: overwriting (reusing) task id=dfa2dff538d54c18ad97ea1593cbd357
2023-02-14 13:06:44,336 - clearml.Task - WARNING - Failed auto-detecting task repository: [WinError 123] Die Syntax für den Dateinamen, Verzeichnisnamen oder die Datenträgerbezeichnung ist falsch: '[...]\<input>'
ClearML results page: [None](https://app.clear.ml/projects/9acc061c880344a881790461a4baa837/experiments/dfa2dff538d54c1...

Ok, I checked: A is terminated. This is not what I thought would happen and not what I intended with my documentation. I should clarify that.

Secondly, I do not understand this:

None says

Manually mark a Task as completed. This will close the running process and will change the Task’s status to Completed (Use this function to close and change status of remotely executed tasks). To simply change the Task’s status to completed, use task.close()

None says

Closes the current Task and cha...

I mean those, that you see in the screen shot. The difference in code is - at least for me - to write

• parameters_data = {'custom1': 'no', 'custom2': False}; parameters_data = task.connect(parameters_data , name='data')
• task.set_user_properties(custom1='no', custom2=False)
  

I created None

@<1523701205467926528:profile|AgitatedDove14> : Wait, so, if a task is initialized in process A and I call mark_completed in a process B, which process is terminated? A or B?