Find and replace for millions of rows with regex in Python

I have 2 set of data.

First one which serves as dictionary has two columns keyword and id and 180000 rows. Below is some sample data.

Also, note that some of the keyword are as small as 2 character and as big as 700 characters and there is no fixed length of the keywords. Although id has fixed pattern of 3 digit number with a hash symbol before and after the number.

keyword         id
salesman        #123#
painter         #486#
senior painter  #215#

Second file has one column which is corpus and it runs into 22 million records and length of each record varies between 10 to 1000. Below is sample data which can be considered as input.

corpus
I am working as a salesman. salesmanship is not my forte, however i have become a good at it
I have been a painter since i was 19
are you the salesman?

Output

corpus
I am working as a #123#. salesmanship is not my forte, however i have become a good at it
I have been a #486# since i was 19
are you the #123#?

Please note that i want to replace complete word and not overlapped words. so in the first sentence salesman was replaced with #123# where as salesmanship was not replaced with #123#ship. This requires me to add regular expression '\b' before and after the keyword. This is why Regex is important for the search function

So this is a search and replace operation for multi-million rows and has regex. I have read Mass string replace in python? and Speed up millions of regex replacements in Python 3, however it is taking me days to do this find and replace, which i can't afford as this is a weekly task. I want to be able to do this much faster. Below is my code

Id = df_dict.Id.tolist()
#convert to list with regex
keyword = [r'\b'+ x + r'\b' for x in df_dict.keyword]
#light on memory to clean file
del df_dict
#replace
df_corpus["corpus_text"].replace(keyword, Id, regex=False,inplace=True)