"""One-hot encoding functionality for categorical features."""

from typing import List, Optional, Union
import pandas as pd


def encode_categorical_features_with_one_hot(
    dataframe: pd.DataFrame,
    columns: List[str],
    *,
    prefix: Optional[str] = None,
    suffix: Optional[str] = None,
    delete_original_columns: bool = False,
    in_place: bool = False
) -> pd.DataFrame:
    """Encode categorical features using one-hot encoding with missing value handling.
    
    This function performs one-hot encoding on specified categorical columns,
    creating separate columns for missing values when they exist. The function
    provides flexible naming options and can operate in-place or return a copy.
    
    Args:
        dataframe: The input DataFrame containing categorical features to encode.
        columns: List of column names to apply one-hot encoding to.
        prefix: Optional prefix to add to all new column names.
        suffix: Optional suffix to add to all new column names.
        delete_original_columns: Whether to remove the original categorical columns
            after encoding. Defaults to False.
        in_place: Whether to modify the DataFrame in-place or return a copy.
            Defaults to False.
    
    Returns:
        pd.DataFrame: The DataFrame with one-hot encoded features. Returns the
            modified original DataFrame if in_place=True, otherwise returns a copy.
    
    Raises:
        TypeError: If dataframe is not a pandas DataFrame.
        TypeError: If columns is not a list.
        ValueError: If any column in the columns list doesn't exist in the DataFrame.
        TypeError: If prefix or suffix are provided but are not strings.
        TypeError: If delete_original_columns is not a boolean.
        TypeError: If in_place is not a boolean.
    
    Notes:
        - Missing values (NaN) get their own indicator columns only if they exist
        - Column naming follows the pattern: [prefix_]original_column_value[_suffix]
        - For missing values: [prefix_]original_column_missing[_suffix]
        - If no missing values exist for a column, no missing indicator is created
    """
    # TODO: Implement the actual one-hot encoding logic
    pass
