kedro pipeline

pipeline.py

# in <root>/src/<project>/pipelines/data_science/pipeline.py
 
from kedro.pipeline import node, pipeline
from .nodes import split_data, fit_xgboost
 
def create_plot_roc_node():
    return node(
        func=plot_roc,
        inputs=["clf", "X_test", "y_test"],
        outputs="roc_graph",
        name="plot_roc",
    )
 
 
def create_split_node():
    return node(
        func=split_data,
        inputs=["model_input_table", "params:split_options"],
        outputs=["X_train", "X_test", "y_train", "y_test"],
        name="split_data_node",
    )
 
def create_xgb_pipeline(**kwargs):
    split_node = create_split_node()
    plot_node = create_plot_roc_node()
 
    xgb_pipe_instance = pipeline(
        [
            split_node,
            node(
                func=fit_xgboost,
                inputs=["X_train", "y_train", "X_test", "y_test",
                        "params:xgboost_params_full_feats"],
                outputs={"clf": "clf", "model_metrics": "model_metrics"},
                name="train_xgboost",
            ),
            plot_node
        ],
    )
 
    return pipeline(
        pipe=xgb_pipe_instance,
        inputs="model_input_table",
        namespace="xgboost_pipe",
        parameters={"params:xgboost_params_full_feats"})