sharkpy.saving

Functions

save_model(self, model[, name, directory])	Save the trained model to a .joblib file with enhanced error handling.
load_model(self, model_path)	Load a saved SharkPy model from a .joblib file with enhanced error handling.

Module Contents

sharkpy.saving.save_model(self, model, name='shark_model', directory='models')

Save the trained model to a .joblib file with enhanced error handling.

Parameters:

• model (object) – Trained ML model object

• name (str, optional) – Filename without extension (default: “shark_model”)

• directory (str, optional) – Folder where the model will be saved (default: “models”)

Returns:

Path to the saved model if successful

Return type:

str

Raises:

• ValueError – If model is None or not trained

• OSError – If directory creation or file writing fails

sharkpy.saving.load_model(self, model_path)

Load a saved SharkPy model from a .joblib file with enhanced error handling.

Parameters:

model_path (str) – Path to the saved .joblib model file

Returns:

The loaded model object

Return type:

object

Raises:

• FileNotFoundError – If model file doesn’t exist

• ValueError – If file is not a valid model