Python RegEx with List as search variables

Question

I have a dataframe with a column email_adress_raw containing multiple email addresses in each row and I want to create a new column with the first email address that has an specific email ending listed in a long list.

email_endings = ['email_end1.com','email_end2.com','email_end3.com',...]

I created the following function, which is already working, but as the list is quite long and is constantly under construction, I would like to do an iteration over the list inside the code or something similiar. I already thought of a loop, but somehow I don't manage to do it...

def email_address_new(s):
    try:
        r = re.search("([\w.-]+@"+email_endings[0]+"|[\w.-]+@"+email_endings[1]+"|[\w.-]+@"+email_endings[2]+")", s).group()
    except AttributeError:
        print(s)
        return None
    except TypeError:
        print(s)
        return None
    return r

udf_email_address_new= F.udf(email_address_new, StringType())

df = df.withColumn("email", udf_email_address_new(F.col("email_adress_raw")))

Answer 1

You can use join to combine the email endings in the list to the regex pattern:

email_endings = ['email_end1.com','email_end2.com','email_end3.com']

def email_address_new(s):
    try:
        pattern = "([\w.-]+@" + "|[\w.-]+@".join(email_endings) + ")"
        r = re.search(pattern, s).group()
    except AttributeError:
        print(s)
        return None
    except TypeError:
        print(s)
        return None
    return r

udf_email_address_new= F.udf(email_address_new, StringType())

df2 = df.withColumn("email", udf_email_address_new(F.col("email_adress_raw")))

But you probably don't need a UDF for this purpose. You can just use regexp_extract , and replace the empty strings with null if there is no match ( regexp_extract returns an empty string if it cannot match)

import pyspark.sql.functions as F

email_endings = ['email_end1.com','email_end2.com','email_end3.com']
pattern = "([\w.-]+@" + "|[\w.-]+@".join(email_endings) + ")"

df2 = df.withColumn(
    "email", 
    F.when(
        F.regexp_extract(F.col("email_adress_raw"), pattern, 1) != "",
        F.regexp_extract(F.col("email_adress_raw"), pattern, 1)
    )
)