Use the number of active worker as a variable in a function

Question

I'm using ThreadPoolExecutor to create multiple worker in order to download simultaneously multiple table from database with an API. The API limitation is 200 request per minute (rate_limit=60/200), and as I'm trying to download 5 table i use 5 worker (num_worker=5 ). Then my time sleep is time_sleep=rate_limit*num_worker .

I would like to use a variable like active_num_workerto adapt the time sleep in order to increase the download speed of the remaining tables when other workers have finished their task.

Main code:

# create list of tables
list_of_travelperks_tables=['users','trips','invoices','bookings','suppliers']


# initialize empty list for dataframes
dfs = []
num_workers=5
rate_limit = 60/200   #rate limit is 200 requests per minute

def load_and_convert_table(i):
    # Load the JSON data
    data = load_travelperk_table(i, os.environ['TP_API_KEY'], rate_limit*num_workers)
    # Convert the list of dictionaries to a DataFrame
    df = pd.json_normalize(data)
    return i, df


# Create a dictionary to store the dataframes
dfs_dict = {}

with concurrent.futures.ThreadPoolExecutor(max_workers=num_workers) as executor:
    futures = executor.map(load_and_convert_table, list_of_travelperks_tables)
    for i, df in futures:
        df_name = f'df_{i}'
        dfs_dict[df_name] = df  # Store the dataframe in the dictionary
        dfs.append((df_name, df))

load_travelperk_table function:

def load_travelperk_table(table_name: str, ApiKey: str, time_sleep: int, parameters=None):

        #code to download
        time.sleep(time_sleep)

    return data

How should I proceed, once a worker finished its task the parameter in the other worker are changed?