Read bytes file using pyspark

I have a file contains bytes information like below with delimiter : '#*'

b'\x00\x00V\x97'#*b'2%'#*b'\x00\x00'#*b'\xc5'#*b'\t'#*b'\xc0'

I want to read this data using Pyspark and each column has different conversion methods to convert into ascii.

I have read this file using String Type() but when I'm doing conversion it is throwing error

'Attribute Error: 'str' object has no attribute 'decode''

customSchema = StructType(
    [
        StructField("Col1", StringType(), True),
        StructField("Col2", StringType(), True),
        StructField("Col3", StringType(), True),
    ]
)

df = (
    spark.read.format("csv")
    .option("inferSchema", "true")
    .option("header", "true")
    .schema(customSchema)
    .option("sep", "#*")
    .load("/FileStore/tables/EbcdicTextData.txt")
)

df.show()

#  col1           col2      col3
# |b'\x00\x01d0'|b'I\x08'|b'\x00\x00'|


def unpack_ch_or_zd(bytes: bytearray) -> str:
    ascii_text = bytes.decode("cp037").replace("\x00", "").rstrip()
    return ascii_text if ascii_text.isascii() else "Non-ASCII"


def unpack_pd_or_pd_plus(bytes) -> str:
    ascii_text = (
        "" if bytes.hex()[-1:] != "d" and bytes.hex()[-1:] != "b" else "-"
    ) + bytes.hex()[:-1]
    return ascii_text if ascii_text.isascii() else "Non-ASCII"


def unpack_pd_or_pd_plus_dec(bytes, decimal: int) -> str:
    ascii_text = (
        "" if bytes.hex()[-1:] != "d" and bytes.hex()[-1:] != "b" else "-"
    ) + bytes.hex()[:-1]
    ascii_text = (
        ascii_text[:-decimal] + "." + ascii_text[-decimal:]
        if ascii_text.isascii()
        else "Non-ASCII"
    )
    return ascii_text


def unpack_bi_or_biplus_no_dec(bytes) -> str:
    # elif (type.lower() == "bi" or ( type.lower() == "bi+" and bytes.hex() <= HighestPositive[:len(bytes) * 2])) and decimal == 0:
    a = str(int("0x" + bytes.hex(), 0))
    return a if a.isascii() else "Non-ASCII"


unpack_ch_or_zd_UDF = udf(lambda x: unpack_ch_or_zd(x), StringType())
unpack_pd_or_pd_plus_UDF = udf(lambda x: unpack_pd_or_pd_plus(x), StringType())
unpack_pd_or_pd_plus_dec_UDF = udf(lambda x: unpack_pd_or_pd_plus_dec(x), StringType())

Layout_df is a dataframe that Contains column names and conversion Type of the particular column:

for row in layout_df.collect():
    column_name = row["Field_name"]
    conversion_type = row["Python_Data_type"]
    if conversion_type.lower() == "ch" or conversion_type.lower() == "zd":
        df = df.withColumn(column_name, unpack_ch_or_zd_UDF(col(column_name)))
    elif (
        conversion_type.lower() == "pd" or conversion_type.lower() == "pd+"
    ) and decimal == 0:
        df = df.withColumn(column_name, unpack_pd_or_pd_plus_UDF(col(column_name)))
    elif (
        conversion_type.lower() == "pd" or conversion_type.lower() == "pd+"
    ) and decimal > 0:
        df = df.withColumn(column_name, unpack_pd_or_pd_plus_dec_UDF(col(column_name)))