multiprocessing in python error using concurrent.futures AttributeError : Can't get attribute 'simulate_end_season' on <module '__main__' (built-in)>

Question

def simulate_end_season(Parameters, Team,response):
    
    # Update result data in dicts - faster than updating a DataFrame.
    points=defaultdict(int)
    wins=defaultdict(int)
    losses=defaultdict(int)
    draws=defaultdict(int)
    goals_for=defaultdict(int)
    goals_against=defaultdict(int)
    Max=10
    games_played = 0
    # Simulate all the games in a season
    for match in response["matches"]:
      home_team=match['homeTeam']['name']
      away_team=match['awayTeam']['name']
      if match['status']=='FINISHED':
       home_goals=match['score']['fullTime']['homeTeam']
       away_goals=match['score']['fullTime']['awayTeam']
      else :
        
        GameResult = SimulateMatch(home_team, away_team, Parameters, Team)
        home_goals = GameResult[0]
        away_goals =GameResult[1]

      # Update the points and win/draw/loss statistics.
      if home_goals > away_goals:
        points[home_team] += 3
        wins[home_team] += 1
        losses[away_team] += 1
      elif home_goals == away_goals:
        points[home_team] += 1
        points[away_team] += 1
        draws[home_team] += 1
        draws[away_team] += 1
      else:
        points[away_team] += 3
        wins[away_team] += 1
        losses[home_team] += 1

      # Update the goals.
      goals_for[home_team] += home_goals
      goals_against[home_team] += away_goals
            
      goals_for[away_team] += away_goals
      goals_against[away_team] += home_goals

    # Return the table as a DataFrame (needs to be sorted on points and goal diff).
    
    # Build the empty table
    empty_rows = np.zeros((len(Team),7), dtype=int)
    season_table = pd.DataFrame(empty_rows, index=Team,columns=['points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal diff'])
    
    # Fill in the table
    for team in Team:
        values_list = [points[team], wins[team], draws[team], losses[team], goals_for[team], goals_against[team]]
        season_table.loc[team, ['points', 'wins', 'draws', 'losses', 'goals for', 'goals against']] = values_list
    # Calculate the goal diff.
    season_table.loc[:, 'goal diff']= season_table.loc[:, 'goals for'] - season_table.loc[:, 'goals against']
    season_table=season_table.sort_values(['points', 'goal diff'], ascending=[False, False])
    rank=[k for k in range(1,len(Team)+1)]
    season_table.insert(1,"rank",rank,True)
    season_table=season_table.sort_index()
    return season_table

    def simulate_n_seasons(Team, Parameters, response,n,Max = 10):
    start = time.time()
    team_position=np.zeros((len(Team),n),dtype=int)
    GoalsFor =np.zeros((len(Team),n))
    GoalsAgainst= np.zeros((len(Team),n))
    Losses = np.zeros((len(Team),n))
    Wins = np.zeros((len(Team),n))
    Draws = np.zeros((len(Team),n))
    Points = np.zeros((len(Team),n))
    Name= Team.sort()
    with concurrent.futures.ProcessPoolExecutor() as executor:
      results= [executor.submit(simulate.simulate_end_season,Params, Team, response) for k in range(n)]
      i=0
      for f in concurrent.futures.as_completed(results):
        season_table = f.result()
        team_position[:,i]=list(season_table['rank'])
        GoalsFor[:,i]=list(season_table['goals for'])
        GoalsAgainst[:,i]=list(season_table['losses'])
        Losses[:,i]= list(season_table['losses'])
        Draws[:,i]= list(season_table['draws'])
        Wins[:,i]= list(season_table['wins'])
        Points[:,i]=list(season_table['points'])
        i+=1
    
      
    end = time.time()
    Name= sorted(Team)
    print(end - start)
    return Name,team_position,GoalsFor,GoalsAgainst,Points,Wins,Draws,Losses

Hello everyone, I am using concurrent.futures in order to do multiproscessing for my project in python. I have read that i need to import the function used for multiprocessing from another file, i can run the function simulate_n_seasons on Google colab but on Spyder or Pycharm, i got the following error message which is in the title. What should i do ? Thanks for your help.