import xmltodict
import pandas as pd


def save_json_to_xml(json_data, filename="DB_Structure.xml"):
    """
    Convert JSON data to XML and save it to a file.
    """
    xml_data = xmltodict.unparse({"root": json_data}, pretty=True)
    with open(filename, "w") as xml_file:
        xml_file.write(xml_data)
    print(f"XML data saved to {filename}")


def save_dataframe_to_excel(df, filename="DB_Structure.xlsx"):
    """
    Save the provided DataFrame to an Excel file.
    """
    df.to_excel(filename, index=False)
    print(f"Data saved to {filename}")


def save_dataframe_to_file(df, filename="DB_Structure.csv"):
    """
    Save the provided DataFrame to a CSV file.
    """
    df.to_csv(filename, index=False)
    print(f"Data saved to {filename}")


def collect_data_for_table(db_struct, parent_prefix="", collected_data=[]):
    """
    Recursively collect data from the DB structure to display in a tabular format,
    omitting 'fields' and 'Struct' in the names.
    """
    is_array_element = False
    if isinstance(db_struct, dict):
        for key, value in db_struct.items():
            # Skip 'fields' and 'Struct' keys in the name path
            # 
            if key == "fields" or key == "Struct" or key == "Array":
                next_prefix = parent_prefix  # Continue with the current prefix
            else:
                if isinstance(value, dict):
                    is_array_element = value.get('is_array_element', False)
                if not is_array_element:
                    next_prefix = f"{parent_prefix}.{key}" if parent_prefix else key
                else:
                    next_prefix = f"{parent_prefix}{key}" if parent_prefix else key

            if (
                isinstance(value, dict) and "type" in value
            ):  # Directly a field with 'type'
                field_data = {
                    "Nombre": next_prefix,
                    "Tipo": value.get("type", "N/A"),
                    "Offset": value.get("offset", "N/A"),
                    "Dirección PLC": value.get("plc_address", "N/A"),
                    "Comentario": value.get("comment", "N/A"),
                }
                collected_data.append(field_data)

            # Recursively handle nested dictionaries and lists
            if isinstance(value, dict) or isinstance(value, list):
                collect_data_for_table(value, next_prefix, collected_data)
    elif isinstance(db_struct, list):
        for index, item in enumerate(db_struct):
            item_prefix = f"{parent_prefix}[{index}]" if parent_prefix else f"[{index}]"
            collect_data_for_table(item, item_prefix, collected_data)

    return collected_data


def display_as_table(dbs):
    """
    Convert collected DB data into a pandas DataFrame and display it.
    """
    all_data = []
    for db_name, db_content in dbs.items():
        print(f"Processing DB: {db_name}")
        db_data = collect_data_for_table(db_content)
        all_data.extend(db_data)

    df = pd.DataFrame(all_data)
    return df