Contrib: added xgboost-optuna contrib

[zilto]

Flow that receives a set of X_train y_train X_test y_test and can train an XGBoost model with hyperparameter tuning

For new dataflows:

Do you have the following?

• Added a directory mapping to my github user name in the contrib/hamilton/contrib/user directory.
  • If my author names contains hyphens I have replaced them with underscores.
  • If my author name starts with a number, I have prefixed it with an underscore.
  • If your author name is a python reserved keyword. Reach out to the maintainers for help.
  • Added an author.md file under my username directory and is filled out.
  • Added an init.py file under my username directory.
• Added a new folder for my dataflow under my username directory.
  • Added a README.md file under my dataflow directory that follows the standard headings and is filled out.
  • Added a init.py file under my dataflow directory that contains the Hamilton code.
  • Added a requirements.txt under my dataflow directory that contains the required packages outside of Hamilton.
  • Added tags.json under my dataflow directory to curate my dataflow.
  • Added valid_configs.jsonl under my dataflow directory to specify the valid configurations.
  • Added a dag.png that shows one possible configuration of my dataflow.

For existing dataflows -- what has changed?

How I tested this

There is a notebook that loads data using sklearn. It should run successfully from start to finish

Notes

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)
• Dataflow documentation has been updated if adding/changing functionality.

[sweep-ai]

Apply Sweep Rules to your PR?

• Apply: Leftover TODOs in the code should be handled.
• Apply: All new business logic should have corresponding unit tests in the tests/ directory.
• Apply: Any clearly inefficient or repeated code should be optimized or refactored.