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| import pandas as pd | |
| import os | |
| import requests | |
| import json | |
| from datetime import datetime | |
| from fpl_utils import fpl_utils | |
| def lambda_handler(event, context): | |
| try: | |
| players = fpl_utils.get('https://fantasy.premierleague.com/api/bootstrap-static/') | |
| players_df = pd.DataFrame(players['elements']) | |
| teams_df = pd.DataFrame(players['teams']) | |
| fixtures_df = pd.DataFrame(players['events']) | |
| today = datetime.now().timestamp() | |
| fixtures_df = fixtures_df.loc[fixtures_df.deadline_time_epoch>today] | |
| gameweek = fpl_utils.get_gameweek() | |
| teams = dict(zip(teams_df.id, teams_df.name)) | |
| players_df['team_name'] = players_df['team'].map(teams) | |
| api_key = fpl_utils.get_parameter('odds_data_api_key') | |
| odds_response = requests.get('https://api.the-odds-api.com/v3/odds/?apiKey='+api_key+'&sport=soccer_epl'+'®ion=uk'+'&mkt=h2h') | |
| odds_json = json.loads(odds_response.text) | |
| if odds_json['success'] == False: | |
| api_key = fpl_utils.get_parameter('odds_data_api_second_key') | |
| odds_response = requests.get('https://api.the-odds-api.com/v3/odds/?apiKey='+api_key+'&sport=soccer_epl'+'®ion=uk'+'&mkt=h2h') | |
| odds_json = json.loads(odds_response.text) | |
| sport = {} | |
| all_sports = [] | |
| this_deadline=fixtures_df.deadline_time_epoch.iat[0] | |
| next_deadline = fixtures_df.deadline_time_epoch.iat[1] | |
| if len(fixtures_df.id) == 1: | |
| next_deadline=fixtures_df.deadline_time_epoch.iat[1] + 5517900 | |
| for item in odds_json["data"]: | |
| if not (this_deadline < item['commence_time'] < next_deadline): | |
| continue | |
| sport['id'] =item['id'] | |
| sport['home_team'] = item['home_team'] | |
| sport['away_team'] = [team for team in item['teams'] if team != item['home_team']][0] | |
| sites = [x for x in item['sites'] if x['site_key'] == "paddypower"] | |
| if len(sites)==0: | |
| continue | |
| if item['home_team'] == item['teams'][0]: | |
| home_odds, away_odds, draw_odds = sites[0]['odds']['h2h'] | |
| else: | |
| away_odds, home_odds, draw_odds = sites[0]['odds']['h2h'] | |
| sport['home_odds'] = home_odds | |
| sport['draw_odds'] = draw_odds | |
| sport['away_odds'] = away_odds | |
| sport['commence_time'] = item['commence_time'] | |
| sport['home_chance'] = 100/sport['home_odds'] | |
| sport['away_chance'] = 100/sport['away_odds'] | |
| all_sports.append(sport.copy()) | |
| df = pd.DataFrame(all_sports) | |
| bucket_name = fpl_utils.get_parameter('fpl_bucket_name') | |
| key = "odds-gameweek-" +str(gameweek)+".csv" | |
| fpl_utils.upload_csv_to_s3(bucket_name, key, df) | |
| 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 |
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