import pandas as pd
from EncoderManager import EncoderManager


def main():
    # Define example data
    data = {
        'Color': ['Red', 'Blue', 'Green', 'Red', 'Green', 'Blue'],
        'Gender': ['Male', 'Female', 'Male', 'Female', 'Male', 'Male'],
        'Size': ['M', 'S', 'L', 'M', 'XL', 'M'],
        'Species': ['Dog', 'Cat', 'Bird', 'Dog', 'Bird', 'Cat'],
        'Count': [2, 1, 3, 4, 1, 2]
    }
    df = pd.DataFrame(data)

    # Define encoding parameters
    label_cols = ('Gender','Species')
    ordinal_cols = ('Size',)
    onehot_cols = ('Color',)

    # Create encoder manager
    encoder = EncoderManager(df, label_cols, ordinal_cols, onehot_cols)

    # Test encoding
    encoded_df = encoder.encode(inplace=False)
    print("Encoded DataFrame:")
    print(encoded_df)

    # Test decoding
    decoded_df = encoder.decode(inplace=False)
    print("Decoded DataFrame:")
    print(decoded_df)

    df_normalized = encoder.normalize('min-max', inplace=True).get_df()
    print("Normalized DataFrame:")
    print(df_normalized)


if __name__ == "__main__":
    main()