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| import pandas as pd | |
| from fpl_utils import fpl_utils | |
| import os | |
| def lambda_handler(event, context): | |
| try: | |
| pl_profile = event['pl_profile'] | |
| cookie = f"pl_profile={pl_profile};" | |
| calc_player_out(event['user_id'], cookie) | |
| return event | |
| except Exception as e: | |
| sns_topic = fpl_utils.get_parameter('failure_email_sns_key') | |
| error_message = f"Error in Lambda function getPlayerDetails: {str(e)}" | |
| fpl_utils.send_sns_notification(error_message, sns_topic) | |
| raise e # Re-raise the exception after sending the notification | |
| def calc_player_out(user_id, cookie): | |
| team = fpl_utils.get_team_auth(user_id, cookie) | |
| gameweek = fpl_utils.get_gameweek() | |
| bucket_name = fpl_utils.get_parameter('fpl_bucket_name') | |
| players_df = fpl_utils.get_csv_df(bucket_name, f'players-gameweek-{gameweek}.csv') | |
| players = [x['element'] for x in team['picks']] | |
| my_original_team = players_df.loc[players_df.id.isin(players)] | |
| my_original_team = calc_out_weight(my_original_team) | |
| player_out = my_original_team.sample(1, weights=my_original_team.out_weight) | |
| file_name = f'gameweek-{gameweek}/player_out.json' | |
| fpl_utils.upload_json_to_s3(bucket_name, file_name, player_out.to_dict(orient='records')) | |
| def calc_out_weight(players): | |
| players_copy = players.copy() | |
| players_copy['out_weight'] = 100 | |
| players_copy['out_weight'] -= players_copy['diff'] | |
| players_copy['out_weight'] -= players_copy['form'].astype("float") * 10 | |
| players_copy.loc[players_copy['element_type'] == 1, 'out_weight'] -= 10 | |
| players_copy.loc[players_copy['out_weight'] < 0, 'out_weight'] = 0 | |
| return players_copy.sort_values('out_weight', ascending=False) |
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