[Python] Replace words in a sentence with synonyms using Python

I have a dataset named news_collection.csv where that has news and what I was struggling to do is that to replace words of the data set with the synonyms from pre built collection called syno.txt . If a word in the data set has a synonyms from syno.txt I want to replace with the first value of that particular synonym line.

Below is the news_collection.csv

created_at,text
5/13/2021 3:27:55 PM,"my mom went with her mommy to bring the food for us"
5/13/2021 3:27:55 PM,"that is my dad and haven't your dada talk to my father"
​

Below is the syno.txt

mother, mommy, mom, ma
father, dad, daddy, dada
​

Below is the expected result

created_at,text
5/13/2021 3:27:55 PM,"my mother went with her mother to bring the food for us"
5/13/2021 3:27:55 PM,"that is my father and haven't your father talk to my father"
​

Below is what I have tried upto now

import pandas as pd
import re
from nltk.tokenize import word_tokenize


def similarity():
tweets = pd.read_csv(r'news_collection.csv')
df = pd.DataFrame(tweets, columns=['created_at', 'text'])
df['created_at'] = pd.to_datetime(df['created_at'])
df['text'] = df['text'].apply(lambda x: str(x))
df["text"] = df["text"].apply(lambda x: replacesynonyms(x))

return df

def replacesynonyms(text):
file = open('sino.txt', 'r', encoding="utf8")
//code to be added


Can someone help to solve this algorithm?

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