ClientError: Failed to invoke sagemaker:CreateProcessingJob. Error Details: Input and Output names must be globally unique: [data]
when creating a pipeline in the last step in my pipeline since two inputs/outputs have the same name. -.-
Asserting this should also be possible and a meaningful usecase for your package? I was not sure if StepInputsAsExpected covered it already, since I am not familiar with the package. If needed, I can provide more context.
Merge to main will trigger additional steps / job to pip install python-semantic-release and execute semantic-release publish. This will create a new tag + GitHun release. python-semantic-release infers the next version from PR title or commit message using conventional commits scheme
Trigger Existing Release Workflow. The current version of the release can be fetched using
Target State
The overall objective is to make the implementation of new Validations as easy as possible by providing developers and users a robust and general functionality to search and filter for the desired attribute (value).
More concretely:
Generalized lookup functionality that can be used across Validations to find appropriate attributes of any object.
Should allow for filtering based on user input:
indices, e.g. if an attribute is a list and the user wants to fetch the first item of that attribute/list
value of attributes, e.g. if an attribute is a dict or other complex object
Problem Statement
At present, every Validation object's run method returns a dict of the form str: ValidationResult where str is the name of the Validation producing that result. See here, for example.
This is a remainder of a previous implementation where run returned a list of varying lenth of ValidationResult objects. Now, the cardinality of Validation:ValidationResult is 1:1, which is why simplifying to storing the value of Validation.name in an attribute of ValidationResult may make more sense. Besides simplification of the data structures, it'd also allow for simplifying the Report.to_df method.
Target State
A ValidationResult object stores the name of the Validation that it was generated by.
The Validation.run methods are updated accordingly.
Report.to_df is refactored to handle the different data structure appropriately.
I see you are already using pre-commit hooks in this repo, but you could also expose one. I could help with that (at least conceptually), I have contributed to pre-commit (top ten contributor) and maintain R hooks myself. The idea would be to run the validations on every commit. Folowing sagemaker projects, the user could supply a module that contains a functinon get_pipeline() that returns the pipeline.