import pandas as pd

from utils.convert_to_excel import convert_dfs
from utils.extract_code import extract_code_from_mrbts
from utils.utils_vars import UtilsVars


def process_mrbts_data(file_path: str) -> pd.DataFrame:
    """
    Process data from the specified file path.

    Args:
        file_path (str): The path to the file.
    """
    dfs = pd.read_excel(
        file_path,
        sheet_name=["MRBTS"],
        engine="calamine",
        skiprows=[0],
    )

    df_mrbts = dfs["MRBTS"]
    df_mrbts.columns = df_mrbts.columns.str.replace(r"[ ]", "", regex=True)

    # Create an explicit copy of the filtered DataFrame to avoid SettingWithCopyWarning
    df_mrbts = df_mrbts[df_mrbts["MRBTS"].apply(lambda x: str(x).isnumeric())].copy()

    # Now use .loc to set values in the DataFrame
    df_mrbts.loc[:, "code"] = df_mrbts["MRBTS"].apply(extract_code_from_mrbts)
    df_mrbts = df_mrbts[["MRBTS", "code", "name", "btsName"]]

    UtilsVars.all_db_dfs.append(df_mrbts)
    UtilsVars.all_db_dfs_names.append("MRBTS")
    return df_mrbts


def process_mrbts_data_to_excel(file_path: str) -> None:
    """
    Process data from the specified file path and save it to a excel file.

    Args:
        file_path (str): The path to the file.
    """
    mrbts_df = process_mrbts_data(file_path)
    UtilsVars.final_mrbts_database = convert_dfs([mrbts_df], ["MRBTS"])