[Proposal] - Add KedroPipelineError and provide better error message for invalid node/pipeline definition

[noklam]

NOTE: Kedro datasets are moving from kedro.extras.datasets to a separate kedro-datasets package in
kedro-plugins repository. Any changes to the dataset implementations
should be done by opening a pull request in that repository.

Description

fix #2733

It's easy if the value is int type, because we can do some simple type checking, but if user pass X_train:'50' it's harder to differentiate whether it's a valid dataset.

    for dataset_name in all_inputs_outputs:
        # Check if `dataset_name` is not `str`
        name = _strip_transcoding(dataset_name)
        if name != dataset_name and name in all_inputs_outputs:
            invalid.add(name)

Originally posted by @noklam in #2733 (comment)

Development notes

Checklist

• Read the contributing guidelines
• Opened this PR as a 'Draft Pull Request' if it is work-in-progress
• Updated the documentation to reflect the code changes
• Added a description of this change in the RELEASE.md file
• Added tests to cover my changes

[noklam]

In case user pass a string as value instead of a dataset, they will just get a ValueError because the dataset does not exist. It would be nice to provide the same error consistently, but I don't think it's easy to differentiate here.

I consider this is still a win because in this case the error message is clear enough

ValueError: Pipeline input(s) {'2', '3'} not found in the DataCatalog
DataCatalog

[merelcht]

Closed by accident, sorry!

[astrojuanlu]

#2733 was already closed in #3715, anything else to do here?

[noklam]

Closing in favor of #3715. I think the initial idea was mainly about the str problem though it's more generic than that.