Adds ability to pass in a callable to get the function name from for …

[skrawcz]

…execute

I found myself wanting to click directly to outputs being created to inspect them. So to short cut that, directly referencing them is a way I can do that and have my IDE jump there when navigating code.

The downside is that this solution doesn't handle functions annotated with decorators that create nodes, e.g. @parameterize*, or @config* . I think that's okay, because it's probably clearer to have a "string" name here to indicate that something is changing/being produced at DAG creation time, and thus a reference to an exact function is likely a misnomer...

Adds unit test for this.

Example usage:

import data_loaders, transforms, model_pipeline
...
dr = driver.Driver(config, data_loaders, transforms, model_pipeline)  
dr.visualize_execution([model_pipeline.kaggle_submission_df], "./kaggle_submission_df.dot.png", {})
kaggle_submission_df: pd.DataFrame = dr.execute([model_pipeline.kaggle_submission_df])

The list can be a union of strings or callables. We right now just grab the name of the callable.

Changes

• execute can now take in a "callable" that we take the name from.
• adds unit test

How I tested this

• locally
• via unit tests

Notes

• this will also make it simpler for IDEs to find references and potentially rename things when function names change.

Checklist

• PR has an informative and human-readable title (this will be pulled into the release notes)
• Changes are limited to a single goal (no scope creep)
• Code passed the pre-commit check & code is left cleaner/nicer than when first encountered.
• Any change in functionality is tested
• New functions are documented (with a description, list of inputs, and expected output)
• Placeholder code is flagged / future TODOs are captured in comments
• Project documentation has been updated if adding/changing functionality.

[elijahbenizzy]

LGTM 🚢 🇮🇹