Get Replies to a Tweet using Tweepy's (4.10.0) Tweet_id

I am trying to use the Tweepy python package to get the actual replies to a Tweet. I break down the process I have worked on so far:

I import my modules and configure authentication variables with tweepy:

client = tweepy.Client(bearer_token=bearer_token, wait_on_rate_limit=True)
covid_tweets = []

for mytweets in tweepy.Paginator(client.search_all_tweets, query = '#COVID lang:en', 
  user_fields=['username', 'public_metrics', 'description', 'location'], tweet_fields 
  = ['created_at', 'geo', 'public_metrics', 'text'], expansions = 'author_id', 
  start_time = '2019-12-30T00:00:00Z', end_time = '2020-01-15T00:00:00Z', 
  max_results=10):
  time.sleep(2)
  covid_tweets.append(mytweets)

I then search for the hashtags I want and the parameters of the Tweepy Paginator with a for loop and append unto an empty list:

client = tweepy.Client(bearer_token=bearer_token, wait_on_rate_limit=True)
covid_tweets = []

for mytweets in tweepy.Paginator(client.search_all_tweets, query = '#COVID lang:en', 
 user_fields=['username', 'public_metrics', 'description', 'location'], tweet_fields 
 = ['created_at', 'geo', 'public_metrics', 'text'], expansions = 'author_id', 
 start_time = '2019-12-30T00:00:00Z', end_time = '2020-01-15T00:00:00Z', 
 max_results=10):
    time.sleep(2)
    covid_tweets.append(mytweets)

Then I convert this list into a dataFrame by extracting certain key fields[a user dictionary, user_object]:

#Convert Covid-19 tweets to a DF
result = []
user_dict = {}

# Loop through each response object
for response in covid_tweets:

 for user in response.includes['users']:
   user_dict[user.id] = {'username': user.username,
                          'followers': user.public_metrics['followers_count'],
                          'tweets': user.public_metrics['tweet_count'],
                          'description': user.description,
                          'location': user.location
                         }
 for tweet in response.data:
   # For each tweet, find the author's information
   author_info = user_dict[tweet.author_id]
   #check for condition
   if ('RT @' not in tweet.text):
 # Put all information we want to keep in a single dictionary for each tweet
 result.append({'author_id': tweet.author_id,
                       'tweet_id': tweet.id,
                       'username': author_info['username'],
                       'author_followers': author_info['followers'],
                       'author_tweets': author_info['tweets'],
                       'author_description': author_info['description'],
                       'author_location': author_info['location'],
                       'text': tweet.text,
                       'created_at': tweet.created_at,
                       'retweets': tweet.public_metrics['retweet_count'],
                       'replies': tweet.public_metrics['reply_count'],
                       'likes': tweet.public_metrics['like_count'],
                       'quote_count': tweet.public_metrics['quote_count']
                      })

 # Change this list of dictionaries into a dataframe
 df_1 = pd.DataFrame(result)

4. Now my issue is, from the dataFrame, I get to see tweets and reply_count for tweets and a proof of the image is shown below:

And I checked how I can get the replies from the tweets. So I did some checks and wanted to follow this code flow function:

def get_all_replies(tweet, api, fout, depth=10, Verbose=False):
global rep
if depth < 1:
    if Verbose:
        print('Max depth reached')
    return
user = tweet.user.screen_name
tweet_id = tweet.id
search_query = '@' + user

# filter out retweets
retweet_filter = '-filter:retweets'

query = search_query + retweet_filter
try:
    myCursor = tweepy.Cursor(api.search_tweets, q=query,
                             since_id=tweet_id,
                             max_id=None,
                             tweet_mode='extended').items()
    rep = [reply for reply in myCursor if reply.in_reply_to_status_id == tweet_id]
except tweepy.TweepyException as e:
    sys.stderr.write(('Error get_all_replies: {}\n').format(e))
    time.sleep(60)

if len(rep) != 0:
    if Verbose:
        if hasattr(tweet, 'full_text'):
            print('Saving replies to: %s' % tweet.full_text)
        elif hasattr(tweet, 'text'):
            print('Saving replies to: %s' % tweet.text)
        print("Output path: %s" % fout)

    # save to file
    with open(fout, 'a+') as (f):
        for reply in rep:
            data_to_file = json.dumps(reply._json)
            f.write(data_to_file + '\n')

        # recursive call
        get_all_replies(reply, api, fout, depth=depth - 1, Verbose=False)

return

So basically, with this function, I loop through the dataframe and pick the "tweet_id" & "the screen_name" for the tweet, then design a search query but I realized at the section of the "rep" list returns an empty list, and debugging line by line, actually showed that the in_reply_to_status_id is different from the tweet_id and the cause for the empty list even though the reply count for the dataframe shows a non-zero.

I know this is long but I really wanted to show what I have done so far and explain each process. Thank you NB: I have access to Academic Research API