[spark dataframe] extract date value using pyspark udf lambda

from pyspark.sql import SparkSession

import pyspark.sql.functions as func

import datetime

fnDataReplace = func.udf(lambda s : s.replace('\\',''))

fnGetBaseDate = func.udf(lambda value1, s1, s2, s3 : extractBaseDate(value1, s1, s2, s3))

def extractBaseDate(value1, dateCol1, dateCol2, timestampCol):

    if (dateCol1 is not None) and len(dateCol1) > 13:

        baseDate = datetime.datetime.strptime(dateCol1, "%Y%m%d%H%M%s%f").strftime("%Y-%m-%d")

    elif (dateCol2 is not None) and len(dateCol2) > 13:

        baseDate = datetime.datetime.strptime(dateCol1, "%Y%m%d %H:%M:%S").strftime("%Y-%m-%d")

    else:

        try :

            baseDate = datetime.datetime.strptime(value1[1:11], "%Y-%m-%d").strftime("%Y-%m-%d")

        except ValueError:

            try :

                baseDate = datetime.datetime.strptime(timestampCol[:10], "%Y-%m-%d").strftime("%Y-%m-%d")

            except ValueError:

                baseDate = "unusable"

    return baseDate

dfRaw = dfRaw.withColumn("value", fnDataReplace("value"))

dfRaw = dfRaw.withColumn("base_dt", fnGetBaseDate("value","c0","c1","tmp_timestamp"))

dfRaw = dfRaw.drop("c0","c1","tmp_timestamp")

dfRaw = dfRaw.filter(dfRaw["base_dt"] != "unusable")