Filtering data based on variable number of arguments

I have a requirement to filter data based on variable number of arguments. Basically, I am reading a table and I want to filter the data based on multiple regions that would be provided through a parameter in the function. The number of regions passed to the function could be variable. The region column would contain a string and we have to find the searched string in the that string.

Something as :

def read_regions(*regions):
    df = spark.read.table("my_input_table").filter(col("region").contains(*regions))
    return df

The function could be called as :

data = read_regions('US')

OR

data = read_regions('CHN', 'NL', 'ES')

Or with any number of regions. The data should be filtered accordingly and data returned.

Can someone please help

So, I want the data to be filtered based on the arguments passed to the function.

UPDATE:

Search strings -> 'USA', 'CHN'

Input:

orderid | campaign        | custid
1234    | Gen_X_USA_offr1 | c2234
5678    | Gen_Z_CHN_offr2 | c1345
7893    | Gen_X_EU_Tru2   | c4563

Output:

orderid | campaign        | custid
1234    | Gen_X_USA_offr1 | c2234
5678    | Gen_Z_CHN_offr2 | c1345

In above, the first 2records are selected in the output since the "campaign" column contains our search regions - 'USA' and 'CHN'. The third row is not selected into the output as it does not contain the search regions.

Happy to provide more clarification if required.

Thanks

Please advise.