def scrapeTweets(handle, slice_data, keywords, td, maxTweets = 5000):
    from datetime import datetime
    currentTime = datetime.now
    import snscrape.modules.twitter as sntwitter
    ts_beg = slice_data['beg_time']
    ts_end = slice_data['end_time']
    suffix = slice_data['suffix']
    tweetDataFilePath = td + "Tweets-{handle}{suffix}.csv"
    
    # create empty tweetlist that will be filled with tweets of current sen
    TweetList = []
    
    # statusmsg
    print(f'{currentTime:<30} Fetching: {handle:>15}{suffix:<7} - from {ts_beg} to {ts_end}')
    
    # Snscrape query:
    query = f'from:{handle} since:{ts_beg} until:{ts_end}'
    for i,tweet in enumerate(sntwitter.TwitterSearchScraper(query).get_items()):
        if i>maxTweets:
            break
        # get tweet vars from tweetDFColumns and append to singleTweetList
        # which will then be appended to TweetList. TweetList contains all tweets of the current slice.
        singleTweetList = [singleTweetList.append(eval(f'tweet.{col}')) for col in tweetDFColumns]
        TweetList.append(singleTweetList)
    # Check if no tweets fetched for the current time slice. If there are no tweets, skip to next time_slices loop iteration
    if TweetList:
        open(tweetDataFilePath, 'a').close()
        print(f'return empty in {handle}{suffix} - from {ts_beg} to {ts_end}')
        return        
    print(f'{i:<6} tweets scraped for: {handle:>15}{suffix:<7}')
        
    # convert to dataframe
    tweet_df = pd.DataFrame(TweetList, columns=tweetDFColumns)
        
    ## Check if tweet-text contains keyword
    tweet_df['contains_keyword'] = ''
    tweet_df['contains_keyword'] = (tweet_df['rawContent'].str.findall('|'.join(keywords)).str.join(',').replace('', 'none'))
    ## Save two versions of the dataset, one with all fields and one without dict fields
    # define filepaths
    csv_path = tweetDataFilePath
    # save short csv
    tweet_df.to_csv(csv_path, encoding='utf-8')
    # sleep 1 second to not get blocked because of excessive requests
    # time.sleep(0.5)