import pandas as pd
import os, sys, csv

def reduce_layer(layername):
    if 'top' in layername:
        return 'T'
    elif 'bottom' in layername:
        return 'B'
    else:
        return ''

def drop_columns_containing(df, substring):
    """
    Drops columns from a Pandas DataFrame if their name contains a specific substring.

    Args:
        df (pd.DataFrame): The DataFrame to modify.
        substring (str): The substring to search for in column names.

    Returns:
        pd.DataFrame: The modified DataFrame with the specified columns dropped.
    """
    columns_to_drop = [col for col in df.columns if substring in col]
    df = df.drop(columns=columns_to_drop, axis=1)
    return df

if __name__ == "__main__":
    cpl_file = pd.read_csv(sys.argv[1])

    # Remove header rows from table
    # cpl_file.drop([0,1,2,3,4,5])

    # Assign names and sort rows to match JLC format
    cpl_file.columns = ['Designator', 'Val', 'Package', 'Mid X', 'Mid Y', 'Rotation', 'Layer']

    # # Drop all comment rows
    cpl_file = drop_columns_containing(cpl_file, '#')

    cpl_file = cpl_file.reindex(columns=['Designator', 'Mid X', 'Mid Y', 'Layer', 'Rotation'])

    # Change top/bottom to T/B
    cpl_file['Layer'] = cpl_file['Layer'].apply(reduce_layer)

    # Write file to disk
    cpl_file.to_csv(sys.argv[2], index=False)