Integrated Support to add custom features

[Hsankesara]

• Added mechanism to add custom features
• Added feature to return dict as a feature output
• Added tabularize custom feature which would read the data and save the tabularized version of them.
• Added a feature to run multiple feature libraries in a single run.
• Discontinued support for Python 3.8 and 3.9 due to newer dependencies not being compatible with older versions.
• Added support for Python 3.11 and 3.12
• Added Custom FeatureLoader Module which can be used for Loading feature and return them in pandas or spark dataframe

To run Feature Loader, you have to create a config dict and pass it to the Feature Loader doc. Here's an example.

from radarpipeline.features import FeatureLoader
config = {
    "input": {"config": {"source_path": PATH}},
"features": [
    {
        "location": 'https://github.com/RADAR-base-Analytics/mockfeatures',
        "feature_groups": ["MockFeatureGroup"],
        "feature_names": [["all"]]
     }
]
}

feature_loader = FeatureLoader(config)
cfeatures = feature_loader.load_features()

[afolarin]

This will be super useful, very nice @Hsankesara 👍 LGTM.