After the running, I checked in the web UI if the status changed, and it didn't —the running finishing without any errors or replies.

Hi TimelyPenguin76 ,
the code example is:
task = Task.create(project_name="projectX", task_name='Y') task.completed(ignore_errors=False)

AgitatedDove14
In the first scenario, there is no repo at all (client end), so which repo will detect?
According to the UI, the task status is complete, and I don't see the diff.
I will try to run this line task._wait_for_repo_detection() ,but I suspect the run will get stuck in an infinite loop.

No. I am working on my local machine (python file) and running a simple example. Note that Trains working on a local server.

I got the following Error:
2020-10-27 19:26:57,222 - trains.Task - ERROR - Action failed <500/0: tasks.completed/v2.2 (unsupported operand type(s) for -: 'NoneType' and 'datetime.datetime')> (force=False, task=9bbd60866e5646c8aacad418ae7fc86f, status_reason=completed)

AgitatedDove14 Yes, the expected result that I aim to is a string of the experiment source code.

TimelyPenguin76 I am using Task.Create() function and not Task.init(). The question is: can I change the output_uri member by calling the output_uri setter like:
task = Task.create()
task.output_uri(my_output_uri)

TimelyPenguin76 Wonderful!

TimelyPenguin76 Thanks! To make sure I understand it correctly, now I can do something like:
task.upload_artifact('my_name',<S3-ADDRESS>)
And when it runs, it will navigate in the S3 storage to find the exact file.
Am I get it right?

AgitatedDove14
Not sure if I got it right. Consider the following scenarios:
I wrote some code in kernel.py file and used the following line at the beginning: task = Task.init(project_name="my project", task_name="my task") . The kernel.py file exists only on my local machine (no git repo). At the end of the experiment running, the kernel.py source code will be in the "uncommitted changes" section in the task? If not, can the kernel.py file be reached from the task? I wrote some code in...

AgitatedDove14
I tried scenario number one, and task_dict didn't contain the source code of the experiment.

Please advice.

task_dict value:
` {'id': 'b37dfbfbfc0c46c68dadc013fc775ab4', 'name': 'Hello Kaggle', 'user': '479fb9f76304483ba0bbc49e7118c70d', 'company': 'd1bd92a3b039400cbafc60a7a5b1e52b', 'type': 'training', 'status': 'completed', 'comment': 'Auto-generated at 2020-11-25 22:29:10 by tmankita@Tomers-MacBook-Pro.local', 'created': datetime.datetime(2020, 11, 25, 22, 23, 27, 947000...

Task.completed(ignore_errors=True)

I tried to use it, but the status still unchanged.

AgitatedDove14 Yes, the artifact is already in S3. The best match for me is programmatically changing the artifact destination server to S3 and uploading it as usual. How I change the artifact destination of a specific experiment?

Great! now it's working. The status changed to completed.
Thanks TimelyPenguin76 !

AgitatedDove14 After running the line: task._wait_for_repo_detection()
I got the same empty result (diff:''). please advice.