Examples: query, "exact match", wildcard*, wild?ard, wild*rd
Fuzzy search: cake~ (finds cakes, bake)
Term boost: "red velvet"^4, chocolate^2
Field grouping: tags:(+work -"fun-stuff")
Escaping: Escape characters +-&|!(){}[]^"~*?:\ with \, e.g. \+
Range search: properties.timestamp:[1587729413488 TO *] (inclusive), properties.title:{A TO Z}(excluding A and Z)
Combinations: chocolate AND vanilla, chocolate OR vanilla, (chocolate OR vanilla) NOT "vanilla pudding"
Field search: properties.title:"The Title" AND text
I Am Using Vscode And S3 As My Output Directory, Which I Specify For The Task (Task.Init(Project_Name='Test', Task_Name="Test, Output_Uri="

I am using VSCode and S3 as my output directory, which i specify for the task (Task.init(project_name='test', task_name="test, output_uri=" None ")). The S3 connection properties are configured in my clearml.conf file. Now I want to run the same from Jupyter Notebook. Where can I specify the S3 connection and credentials, without having a config file?

Posted 8 months ago
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Answers 2


Posted 8 months ago

Hi @<1582542029752111104:profile|GorgeousWoodpecker69> , you can simply use the boto3 native env vars, ClearML SDK will know how to pick them up (see here )

Posted 8 months ago
2 Answers
8 months ago
8 months ago