import os import json import time import logging import logging.config import urllib3 import argparse import datetime import platform import requests import numpy as np import pandas as pd from threading import Event, Thread from telegram_handler import TelegramHandler from concurrent.futures import ThreadPoolExecutor urllib3.disable_warnings() myhost = platform.node() VERSION = "v.1 (7) 12.12.2024" TAGS = [ {"tag": "vtb", "name": "Единая Лига ВТБ", "lang": "en"}, {"tag": "vtbyouth", "name": "Молодежка ВТБ", "lang": ""}, {"tag": "rfb-deti", "name": "Дети", "lang": ""}, {"tag": "rfb-silent", "name": "Тихий!баскетбол", "lang": ""}, {"tag": "orgRoot", "name": "Все соревнования", "lang": ""}, {"tag": "vtb-supercup", "name": "Супер-Кубок ЕЛ ВТБ", "lang": ""}, {"tag": "uba-leto", "name": "UBA лето", "lang": "ru"}, {"tag": "phygital-russia-cup-m", "name": "Фиджитал кубок", "lang": "ru"}, {"tag": "phygital", "name": "Фиджитал", "lang": "ru"}, {"tag": "3x3Root", "name": "3х3", "lang": "ru"}, {"tag": "LS3x3", "name": "Лига Сильных 3х3", "lang": "ru"}, {"tag": "uba", "name": "ЮБА", "lang": "ru"}, {"tag": "uba-main", "name": "ЮБА-маин", "lang": "ru"}, {"tag": "msl", "name": "Суперлига. Мужчины", "lang": ""}, {"tag": "mhl", "name": "Высшая лига. Мужчины", "lang": ""}, {"tag": "mcup", "name": "Кубок России. Мужчины", "lang": ""}, {"tag": "wpremier", "name": "Премьер-Лига. Женщины", "lang": ""}, {"tag": "wsl", "name": "Суперлига. Женщины", "lang": ""}, {"tag": "whl", "name": "Высшая лига. Женщины", "lang": ""}, {"tag": "wcup", "name": "Кубок России. Женщины", "lang": ""}, {"tag": "uba-summer", "name": "UBA Leto", "lang": "ru"}, {"tag": "unics", "name": "UNICS", "lang": "ru"}, ] TOKEN = "7639240596:AAH0YtdQoWZSC-_R_EW4wKAHHNLIA0F_ARY" GROUP_CHAT = 228977654 # Используем argparse для обработки аргументов командной строки parser = argparse.ArgumentParser(description="VTB Data Fetcher") parser.add_argument("--league", type=str, default="vtb", help="League tag") parser.add_argument("--lang", type=str, default="en", help="Language") parser.add_argument("--team", type=str, default=None, help="Team") args = parser.parse_args() LEAGUE = args.league LANG = args.lang TEAM = args.team # Глобальные параметры таймаута (в секундах) TIMEOUT_STANDINGS = 1 # Интервал для обновления турнирной таблицы TIMEOUT_GAME = 120 # Интервал для обновления расписания LOG_CONFIG = { "version": 1, "handlers": { "telegram": { "class": "telegram_handler.TelegramHandler", "level": "INFO", "token": TOKEN, "chat_id": GROUP_CHAT, "formatter": "telegram", }, "console": { "class": "logging.StreamHandler", "level": "DEBUG", "formatter": "simple", "stream": "ext://sys.stdout", }, "file": { "class": "logging.FileHandler", "level": "DEBUG", "formatter": "simple", "filename": f"logs/GFX_{myhost}.log", "encoding": "utf-8", }, }, "loggers": { __name__: {"handlers": ["console", "file", "telegram"], "level": "DEBUG"}, }, "formatters": { "telegram": { "class": "telegram_handler.HtmlFormatter", "format": "%(levelname)s %(message)s", "use_emoji": "True", }, "simple": { "class": "logging.Formatter", "format": "%(asctime)s %(levelname)-8s %(funcName)12s() - %(message)s", "datefmt": "%d.%m.%Y %H:%M:%S", }, }, } if not os.path.exists("logs"): os.makedirs("logs") if not os.path.exists("JSON"): os.makedirs("JSON") logging.config.dictConfig(LOG_CONFIG) logger = logging.getLogger(__name__) logger.handlers[2].formatter.use_emoji = True pd.set_option("display.max_rows", None) if TEAM is None: logger.critical(f"{myhost}\nКоманда не указана") time.sleep(3) exit(1) logger.info( f"{myhost}\n!!!!!!!!СТАРТ!!!!!!!!! \nHOST: {TEAM}\nTAG: {LEAGUE}" ) if LANG is None: LANG = next( (tag["lang"] for tag in TAGS if tag["tag"].lower() == LEAGUE.lower()), "" ) URL = ( "https://basket.sportoteka.org/" if "uba" in LEAGUE.lower() # else "https://deti.russiabasket.org/" else "https://pro.russiabasket.org/" ) stat_name_list = [ ("points", "Очки", "points"), ("pt-1", "Штрафные", "free throws"), ("pt-1_pro", "штрафные, процент", "free throws pro"), ("pt-2", "2-очковые", "2-points"), ("pt-2_pro", "2-очковые, процент", "2-points pro"), ("pt-3", "3-очковые", "3-points"), ("pt-3_pro", "3-очковые, процент", "3-points pro"), ("fg", "очки с игры", "field goals"), ("fg_pro", "Очки с игры, процент", "field goals pro"), ("assist", "Передачи", "assists"), ("pass", "", ""), ("defReb", "подборы в защите", ""), ("offReb", "подборы в нападении", ""), ("Reb", "Подборы", "rebounds"), ("steal", "Перехваты", "steals"), ("block", "Блокшоты", "blocks"), ("blocked", "", ""), ("turnover", "Потери", "turnovers"), ("foul", "Фолы", "fouls"), ("foulsOn", "", ""), ("foulT", "", ""), ("foulD", "", ""), ("foulC", "", ""), ("foulB", "", ""), ("second", "секунды", "seconds"), ("dunk", "данки", "dunks"), ("fastBreak", "", "fast breaks"), ("plusMinus", "+/-", "+/-"), ("avgAge", "", "avg Age"), ("ptsBench", "", "Bench PTS"), ("ptsBench_pro", "", "Bench PTS, %"), ("ptsStart", "", "Start PTS"), ("ptsStart_pro", "", "Start PTS, %"), ("avgHeight", "", "avg height"), ("timeout_left", "", "timeout left"), ("timeout_str", "", "timeout str"), ] def get_json(url): try: logger.debug(f"Пытаюсь получить данные: {url}") response = requests.get(url, verify=False, timeout=10) if response.status_code == 200: return response.json() except requests.RequestException as e: logger.warning(f"{myhost}\n{url}: {e}") return None def get_season_and_schedule(): try: url = f"{URL}api/abc/comps/seasons?Tag={LEAGUE}&Lang={LANG}" data = get_json(url) if data and "result" in data and data["result"]: season = data["result"][0]["season"] schedule_url = f"{URL}api/abc/comps/calendar?Tag={LEAGUE}&Season={season}&Lang={LANG}&MaxResultCount=1000" schedule = get_json(schedule_url) if schedule and "items" in schedule: df_schedule = pd.json_normalize(schedule["items"]) df_schedule["game.DateStr"] = df_schedule["game.localDate"] # Преобразование дат для корректного сравнения df_schedule["game.localDate"] = pd.to_datetime( df_schedule["game.localDate"], format="%d.%m.%Y" ) # print(f"befor pada{df_schedule['game.localDate']}") current_date = datetime.datetime.now().strftime("%d.%m.%Y") current_date = pd.to_datetime(current_date, format="%d.%m.%Y") df_schedule["team1.name"] = df_schedule["team1.name"].str.strip() # Фильтрация данных df_schedule = df_schedule[ (df_schedule["game.localDate"] <= current_date) & (df_schedule["team1.name"].str.lower() == TEAM.lower()) ].iloc[-1] data = { "season": season, "game_id": df_schedule["game.id"], "team1_id": df_schedule["team1.teamId"], "team2_id": df_schedule["team2.teamId"], "team1": df_schedule["team1.name"], "team2": df_schedule["team2.name"], "when": df_schedule["game.DateStr"], "time": df_schedule["game.localTime"], } return data else: logger.warning("Season or schedule data missing.") except Exception as e: logger.error(f"Error fetching season or schedule: {e}") def is_file_locked(filepath): try: # Попытаемся открыть файл в режиме записи (перезапись) with open(filepath, "w"): pass return False # Если получилось открыть, файл не заблокирован except IOError: return True # Если произошла ошибка, файл заблокирован def rewrite_file(filepath, data): filepath = f"JSON/{filepath}.json" with open(filepath, "w", encoding="utf-8") as data_file: json.dump(data, data_file, ensure_ascii=False, indent=4) logger.debug(f"Файл {filepath} успешно перезаписан.") def Team_Stat_Game(team_id, game_id): game = Game_Online(game_id) if game["result"]["teams"][1]["teamId"] == int(team_id): logger.debug(f"send {game['result']['team1']['name']}") result = game["result"]["teams"][1] else: logger.debug(f"send {game['result']['team2']['name']}") result = game["result"]["teams"][2] return result def Player_Stat_Game(player_id, game_id): pass def Team_Stat_Season(team_id, season): pass def Player_Stat_Season(player_id, season): url = f"{URL}api/abc/players/stats?teamId=0&Tag={LEAGUE}&season={season}&Id={player_id}" player_stat_season = requests.get(url) logger.debug(f"API response OK!!!") if player_stat_season.status_code == 200: player_stat_season = player_stat_season.json() if player_stat_season["items"]: player_stat_season = player_stat_season["items"][-2:] logger.debug(f"Данные на сезон для игрока: {player_id} получены!!!") return {player_id: player_stat_season} else: logger.debug( f"Не нашел на {player_id} данные. Скорее всего еще не играл в сезоне." ) return { player_id: [ { "team": None, "game": None, "stats": { "games": 0, "isStarts": "", "points": "", "goal2": "", "shot2": "", "goal3": "", "shot3": "", "goal1": "", "shot1": "", "goal23": "", "shot23": "", "shot2Percent": "", "shot3Percent": "", "shot23Percent": "", "shot1Percent": "", "assist": "", "pass": "", "steal": "", "blockShot": "", "blockedOwnShot": "", "defRebound": "", "offRebound": "", "rebound": "", "foulsOnPlayer": "", "turnover": "", "foul": "", "second": 0, "playedTime": "", "dunk": "", "fastBreak": "", "plusMinus": None, }, "class": "Sum", }, { "team": None, "game": None, "stats": { "games": 0, "isStarts": "", "points": "", "goal2": "", "shot2": "", "goal3": "", "shot3": "", "goal1": "", "shot1": "", "goal23": "", "shot23": "", "shot2Percent": "", "shot3Percent": "", "shot23Percent": "", "shot1Percent": "", "assist": "", "pass": "", "steal": "", "blockShot": "", "blockedOwnShot": "", "defRebound": "", "offRebound": "", "rebound": "", "foulsOnPlayer": "", "turnover": "", "foul": "", "second": 0, "playedTime": "", "dunk": "", "fastBreak": "", "plusMinus": None, }, "class": "Avg", }, ] } def Player_Stat_Career(player_id): url = f"{URL}api/abc/players/career?teamId=0&Tag={LEAGUE}&Id={player_id}" player_stat_career = requests.get(url) logger.debug(f"API response OK!!!") if player_stat_career.status_code == 200: player_stat_career = player_stat_career.json() if player_stat_career["items"]: logger.debug(f"Данные за карьеру на игрока: {player_id} получены!!!") player_stat_career = player_stat_career["items"][-2:] return {player_id: player_stat_career} else: logger.debug(f"Не нашел на {player_id} данные. Скорее всего новичок") return { player_id: [ { "season": None, "team": None, "stats": { "games": 0, "isStarts": "", "points": "", "goal2": "", "shot2": "", "goal3": "", "shot3": "", "goal1": "", "shot1": "", "goal23": "", "shot23": "", "shot2Percent": "", "shot3Percent": "", "shot23Percent": "", "shot1Percent": "", "assist": "", "pass": "", "steal": "", "blockShot": "", "blockedOwnShot": "", "defRebound": "", "offRebound": "", "rebound": "", "foulsOnPlayer": "", "turnover": "", "foul": "", "second": 0, "playedTime": "", "dunk": "", "fastBreak": "", "plusMinus": None, }, "class": "Sum", }, { "season": None, "team": None, "stats": { "games": 0, "isStarts": "", "points": "", "goal2": "", "shot2": "", "goal3": "", "shot3": "", "goal1": "", "shot1": "", "goal23": "", "shot23": "", "shot2Percent": "", "shot3Percent": "", "shot23Percent": "", "shot1Percent": "", "assist": "", "pass": "", "steal": "", "blockShot": "", "blockedOwnShot": "", "defRebound": "", "offRebound": "", "rebound": "", "foulsOnPlayer": "", "turnover": "", "foul": "", "second": 0, "playedTime": "", "dunk": "", "fastBreak": "", "plusMinus": None, }, "class": "Avg", }, ] } def format_time(seconds): minutes = int(seconds // 60) seconds = int(seconds % 60) return f"{minutes:01}:{seconds:02}" def Coach_Stat(coach_id, season, team_id): url = f"{URL}api/abc/coaches/career?teamId={team_id}&tag={LEAGUE}&season={season}&Id={coach_id}" coach_stat = requests.get(url) logger.debug(f"API response OK!!!") if coach_stat.status_code == 200: coach_stat = coach_stat.json() if coach_stat["items"]: logger.debug(f"Данные за карьеру на тренера: {coach_id} получены!!!") coach_stat = coach_stat["items"] return {coach_id: coach_stat} else: logger.debug(f"Не нашел на {coach_id} данные. Скорее всего новичок") return None def coach_team_stat(data, team_id): games = 0 wins = 0 loses = 0 gamesAsCoach = 0 winsAsCoach = 0 losesAsCoach = 0 season = 0 if data: for d in data: if d["team"] and d["team"]["id"] == team_id: season += 1 games += d["games"] wins += d["wins"] loses += d["loses"] gamesAsCoach += d["games"] winsAsCoach += d["wins"] losesAsCoach += d["loses"] team_stat = { "games": games, "wins": wins, "loses": loses, "gamesAsCoach": gamesAsCoach, "winsAsCoach": winsAsCoach, "losesAsCoach": losesAsCoach, "season": season, } return team_stat def safe_int(value, default=0): try: return int(value) except (ValueError, TypeError): return default def Json_Team_Generation(who, data, event): logger.info(f"START making json for {data[who]}, {data[f'{who}_id']}") payload = Team_Stat_Game(f'{data[f"{who}_id"]}', data["game_id"]) # print(payload) # получаю ID игроков player_ids = [ i["personId"] for i in payload["starts"] if i["startRole"] == "Player" ] print(player_ids) coach_ids = [i["personId"] for i in payload["starts"] if i["startRole"] == "Coach"] print(coach_ids) url = f"{URL}api/abc/games/live-status?id={data['game_id']}" # print(url) json_live_status = requests.get(url) json_live_status = json_live_status.json() online = ( True if "status" in json_live_status and json_live_status["status"] == "Ok" and json_live_status["result"]["gameStatus"] == "Online" else False ) online = True # получаю статистику на игроков по сезону и карьере player_season_stat = [] player_career_stat = [] coach_stat = [] with ThreadPoolExecutor() as pool: player_season_stat_temp = [ pool.submit(Player_Stat_Season, player_id, data["season"]) for player_id in player_ids ] player_career_stat_temp = [ pool.submit(Player_Stat_Career, player_id) for player_id in player_ids ] coach_stat_temp = [ pool.submit(Coach_Stat, coach_id, data["season"], data[f"{who}_id"]) for coach_id in coach_ids ] player_season_stat += [res.result() for res in player_season_stat_temp] player_career_stat += [res.result() for res in player_career_stat_temp] coach_stat += [res.result() for res in coach_stat_temp] while not event.is_set(): payload = Team_Stat_Game(f'{data[f"{who}_id"]}', data["game_id"]) role_list = [ ("Center", "C"), ("Guard", "G"), ("Forward", "F"), ("Power Forward", "PF"), ("Small Forward", "SF"), ("Shooting Guard", "SG"), ("Point Guard", "PG"), ("Forward-Center", "FC"), ] starts = payload["starts"] HeadCoachStatsCareer, HeadCoachStatsTeam = "", "" team = [] for item in starts: # print(player_season_stat) row_player_season = next( ( v for row in player_season_stat for k, v in row.items() if k == item["personId"] ), None, ) row_player_career = next( ( v for row in player_career_stat for k, v in row.items() if k == item["personId"] ), None, ) row_coach_stat = next( ( v for row in coach_stat for k, v in row.items() if k == item["personId"] ), None, ) row_player_season_avg, row_player_season_sum = ( ( next( (r["stats"] for r in row_player_season if r["class"] == "Avg"), None, ), next( (r["stats"] for r in row_player_season if r["class"] == "Sum"), None, ), ) if row_player_season else (None, None) ) row_player_career_avg, row_player_career_sum = ( ( next( (r["stats"] for r in row_player_career if r["class"] == "Avg"), None, ), next( (r["stats"] for r in row_player_career if r["class"] == "Sum"), None, ), ) if row_player_career else (None, None) ) if row_coach_stat: games_word = ( "game" if row_coach_stat[-1]["games"] in [0, 1] else "games" ) total_season = len(row_coach_stat) - 1 season_word = "season" if total_season == 1 else "seasons" procent = ( round( (row_coach_stat[-1]["wins"] * 100) / row_coach_stat[-1]["games"], 1, ) if row_coach_stat[-1]["games"] != 0 else "" ) # HeadCoachStatsCareer = ( # f'{row_s["total_seasons"]} {season_word} in The VTB United League career' # ) HeadCoachStatsCareer = "in The VTB United League career" if total_season == 0: HeadCoachStatsCareer = f'{row_coach_stat[-1]["games"] if row_coach_stat[-1]["games"] != 0 else "first"} {games_word} as {data[who]} head coach' HeadCoachStatsCareer += ( f'\n{row_coach_stat[-1]["games"] if row_coach_stat[-1]["games"] != 0 else "first"} {games_word}: {row_coach_stat[-1]["wins"]}-{row_coach_stat[-1]["loses"]} ({procent}% wins)' if row_coach_stat[-1]["games"] != 0 else "" ) coach_team_stat_temp = coach_team_stat( row_coach_stat, data[f"{who}_id"] ) games_word_team = ( "game" if coach_team_stat_temp["games"] in [0, 1] else "games" ) season_word_team = ( "season" if coach_team_stat_temp["season"] == 1 else "seasons" ) procent_team = ( round( (coach_team_stat_temp["wins"] * 100) / coach_team_stat_temp["games"], 1, ) if coach_team_stat_temp["games"] != 0 else "" ) # HeadCoachStatsTeam = ( # f'{coach_team_stat_temp["season"]} {season_word_team} as {data[f"{who}"]} head coach' # ) HeadCoachStatsTeam = f"{data[f'{who}']} head coach" if coach_team_stat_temp["season"] == 0: HeadCoachStatsTeam = f'{coach_team_stat_temp["games"] if coach_team_stat_temp["games"] != 0 else "first"} {games_word} as {data[f"{who}"]} head coach' HeadCoachStatsTeam += ( f'\n{coach_team_stat_temp["games"] if coach_team_stat_temp["games"] != 0 else "first"} {games_word}: {coach_team_stat_temp["wins"]}-{coach_team_stat_temp["loses"]} ({procent_team}% wins)' if coach_team_stat_temp["games"] != 0 else "" ) text = "" if row_player_season_avg: text = f"GAMES: {row_player_season_avg['games']} MINUTES: {row_player_season_avg['playedTime']} " text += ( f"PTS: {row_player_season_avg['points']} " if row_player_season_avg["points"] != "" else "" ) text += ( f"REB: {row_player_season_avg['rebound']} " if row_player_season_avg["rebound"] != "" and float(row_player_season_avg["rebound"]) >= 1.0 else "" ) text += ( f"AST: {row_player_season_avg['assist']} " if row_player_season_avg["assist"] != "" and float(row_player_season_avg["assist"]) >= 1.0 else "" ) text += ( f"STL: {row_player_season_avg['steal']} " if row_player_season_avg["steal"] != "" and float(row_player_season_avg["steal"]) >= 1.0 else "" ) text += ( f"BLK: {row_player_season_avg['blockShot']} " if row_player_season_avg["blockShot"] != "" and float(row_player_season_avg["blockShot"]) >= 1.0 else "" ) text = text.strip() # print(item) player = { "id": item["personId"], "num": item["displayNumber"], "startRole": item["startRole"], "role": item["positionName"], "roleShort": ( [ r[1] for r in role_list if r[0].lower() == item["positionName"].lower() ][0] if any( r[0].lower() == item["positionName"].lower() for r in role_list ) else "" ), "NameGFX": ( f"{item['firstName'].strip()} {item['lastName'].strip()}" if item["firstName"] is not None and item["lastName"] is not None else "Команда" ), "captain": item["isCapitan"], "age": item["age"] if item["age"] is not None else 0, "height": f'{item["height"]} cm' if item["height"] else 0, "weight": f'{item["weight"]} kg' if item["weight"] else 0, "isStart": (item["stats"]["isStart"] if item["stats"] else False), "isOn": ( "🏀" if item["stats"] and item["stats"]["isOnCourt"] is True else "" ), "flag": f"https://flagicons.lipis.dev/flags/4x3/{'ru' if item['countryId'] is None and item['countryName'] == 'Russia' else '' if item['countryId'] is None else item['countryId'].lower() if item['countryName'] is not None else ''}.svg", "pts": item["stats"]["points"] if item["stats"] else 0, "pt-2": ( f"{item['stats']['goal2']}/{item['stats']['shot2']}" if item["stats"] else 0 ), "pt-3": ( f"{item['stats']['goal3']}/{item['stats']['shot3']}" if item["stats"] else 0 ), "pt-1": ( f"{item['stats']['goal1']}/{item['stats']['shot1']}" if item["stats"] else 0 ), "fg": ( f"{item['stats']['goal2'] + item['stats']['goal3']}/{item['stats']['shot2'] + item['stats']['shot3']}" if item["stats"] else 0 ), "ast": item["stats"]["assist"] if item["stats"] else 0, "stl": item["stats"]["steal"] if item["stats"] else 0, "blk": item["stats"]["block"] if item["stats"] else 0, "blkVic": item["stats"]["blocked"] if item["stats"] else 0, "dreb": item["stats"]["defReb"] if item["stats"] else 0, "oreb": item["stats"]["offReb"] if item["stats"] else 0, "reb": ( item["stats"]["defReb"] + item["stats"]["offReb"] if item["stats"] else 0 ), "to": item["stats"]["turnover"] if item["stats"] else 0, "foul": item["stats"]["foul"] if item["stats"] else 0, "foulT": item["stats"]["foulT"] if item["stats"] else 0, "foulD": item["stats"]["foulD"] if item["stats"] else 0, "foulC": item["stats"]["foulC"] if item["stats"] else 0, "foulB": item["stats"]["foulB"] if item["stats"] else 0, "fouled": item["stats"]["foulsOn"] if item["stats"] else 0, "plusMinus": item["stats"]["plusMinus"] if item["stats"] else 0, "dunk": item["stats"]["dunk"] if item["stats"] else 0, "kpi": ( item["stats"]["points"] + item["stats"]["defReb"] + item["stats"]["offReb"] + item["stats"]["assist"] + item["stats"]["steal"] + item["stats"]["block"] + item["stats"]["foulsOn"] + (item["stats"]["goal1"] - item["stats"]["shot1"]) + (item["stats"]["goal2"] - item["stats"]["shot2"]) + (item["stats"]["goal3"] - item["stats"]["shot3"]) - item["stats"]["turnover"] - item["stats"]["foul"] if item["stats"] else 0 ), "time": ( format_time(item["stats"]["second"]) if item["stats"] else "0:00" ), "Name1GFX": item["firstName"].strip() if item["firstName"] else "", "Name2GFX": item["lastName"].strip() if item["lastName"] else "", "photoGFX": ( f"D:\Photos\{LEAGUE}\{data[who]}\{item['displayNumber']}.png" if item["startRole"] == "Player" else "" ), "season": text, "isOnCourt": (item["stats"]["isOnCourt"] if item["stats"] else False), "AvgPoints": ( row_player_season_avg["points"] if row_player_season_avg and row_player_season_avg["points"] != "" else "0.0" ), "AvgAssist": ( row_player_season_avg["assist"] if row_player_season_avg and row_player_season_avg["assist"] != "" else "0.0" ), "AvgBlocks": ( row_player_season_avg["blockShot"] if row_player_season_avg and row_player_season_avg["blockShot"] != "" else "0.0" ), "AvgDefRebound": ( row_player_season_avg["defRebound"] if row_player_season_avg and row_player_season_avg["defRebound"] != "" else "0.0" ), "AvgOffRebound": ( row_player_season_avg["offRebound"] if row_player_season_avg and row_player_season_avg["offRebound"] != "" else "0.0" ), "AvgRebound": ( row_player_season_avg["rebound"] if row_player_season_avg and row_player_season_avg["rebound"] != "" else "0.0" ), "AvgSteal": ( row_player_season_avg["steal"] if row_player_season_avg and row_player_season_avg["steal"] != "" else "0.0" ), "AvgTurnover": ( row_player_season_avg["turnover"] if row_player_season_avg and row_player_season_avg["turnover"] != "" else "0.0" ), "AvgFoul": ( row_player_season_avg["foul"] if row_player_season_avg and row_player_season_avg["foul"] != "" else "0.0" ), "AvgOpponentFoul": ( row_player_season_avg["foulsOnPlayer"] if row_player_season_avg and row_player_season_avg["foulsOnPlayer"] != "" else "0.0" ), "AvgPlusMinus": ( row_player_season_avg["plusMinus"] if row_player_season_avg and row_player_season_avg["plusMinus"] != "" else "0.0" ), "AvgKPI": "0.0", "AvgPlayedTime": ( row_player_season_avg["playedTime"] if row_player_season_avg and row_player_season_avg["playedTime"] != "" else "0:00" ), "Shot1Percent": ( f'{row_player_season_avg["shot1Percent"]}%' if row_player_season_avg and row_player_season_avg["shot1Percent"] != "" else "0.0%" ), "Shot2Percent": ( f'{row_player_season_avg["shot2Percent"]}%' if row_player_season_avg and row_player_season_avg["shot2Percent"] != "" else "0.0%" ), "Shot3Percent": ( f'{row_player_season_avg["shot3Percent"]}%' if row_player_season_avg and row_player_season_avg["shot3Percent"] != "" else "0.0%" ), "Shot23Percent": ( f'{row_player_season_avg["shot23Percent"]}%' if row_player_season_avg and row_player_season_avg["shot23Percent"] != "" else "0.0%" ), "TPoints": safe_int( row_player_season_sum.get("points") if row_player_season_sum else 0 ) + (0 if online is False else item["stats"]["points"]), "TShots1": ( f'{safe_int(row_player_season_sum.get("goal1")) + (0 if online is False else item["stats"]["goal1"] if item["stats"]["goal1"] != "" else 0)}/{safe_int(row_player_season_sum.get("shot1")) + (0 if online is False else item["stats"]["shot1"] if item["stats"]["shot1"] != "" else 0)}' if row_player_season_sum and row_player_season_sum["shot1"] != "" and item["stats"]["shot1"] != "" else "0/0" ), "TShots2": ( f'{safe_int(row_player_season_sum.get("goal2")) + (0 if online is False else item["stats"]["goal2"] if item["stats"]["goal2"] != "" else 0)}/{safe_int(row_player_season_sum.get("shot2")) + (0 if online is False else item["stats"]["shot2"] if item["stats"]["shot2"] != "" else 0)}' if row_player_season_sum and row_player_season_sum["shot2"] != "" and item["stats"]["shot2"] != "" else "0/0" ), "TShots3": ( f'{safe_int(row_player_season_sum.get("goal3")) + (0 if online is False else item["stats"]["goal3"] if item["stats"]["goal3"] != "" else 0)}/{safe_int(row_player_season_sum.get("shot3")) + (0 if online is False else item["stats"]["shot3"] if item["stats"]["shot3"] != "" else 0)}' if row_player_season_sum and row_player_season_sum["shot3"] != "" and item["stats"]["shot3"] != "" else "0/0" ), "TShots23": ( f'{safe_int(row_player_season_sum.get("goal2")) + safe_int(row_player_season_sum.get("goal3")) + (0 if online is False else item["stats"]["goal2"] if item["stats"]["goal2"] != "" else 0) + (0 if online is False else item["stats"]["goal3"] if item["stats"]["goal3"] != "" else 0)}/' f'{safe_int(row_player_season_sum.get("shot2")) + safe_int(row_player_season_sum.get("shot3")) + (0 if online is False else item["stats"]["shot2"] if item["stats"]["shot2"] != "" else 0) + (0 if online is False else item["stats"]["shot3"] if item["stats"]["shot3"] != "" else 0)}' if row_player_season_sum else "0/0" ), # "TShot1Percent": ( # f'{row_player_season_sum["shot1Percent"]}%' # if row_player_season_sum # and row_player_season_sum["shot1Percent"] != "" # else "0.0%" # ), "TShot1Percent": ( f'{round( ((int(row_player_season_sum["goal1"]) if row_player_season_sum["goal1"] != "" else 0) + (0 if online is False else item["stats"]["goal1"] if item["stats"]["goal1"] != "" else 0)) * 100 / ((int(row_player_season_sum["shot1"]) if row_player_season_sum["shot1"] != "" else 0) + (0 if online is False else item["stats"]["shot1"] if item["stats"]["shot1"] != "" else 0)), 1)}%' if row_player_season_sum and row_player_season_sum["shot1"] != "" and item["stats"]["shot1"] != "" else "0.0%" ), "TShot2Percent": ( f'{round( ((int(row_player_season_sum["goal2"]) if row_player_season_sum["goal2"] != "" else 0) + (0 if online is False else item["stats"]["goal2"] if item["stats"]["goal2"] != "" else 0)) * 100 / ((int(row_player_season_sum["shot2"]) if row_player_season_sum["shot2"] != "" else 0) + (0 if online is False else item["stats"]["shot2"] if item["stats"]["shot2"] != "" else 0)), 1)}%' if row_player_season_sum and row_player_season_sum["shot2"] != "" and item["stats"]["shot2"] != "" else "0.0%" # f'{row_player_season_sum["shot2Percent"]}%' # if row_player_season_sum # and row_player_season_sum["shot2Percent"] != "" # else "0.0%" ), "TShot3Percent": ( f'{round( ((int(row_player_season_sum["goal3"]) if row_player_season_sum["goal3"] != "" else 0) + (0 if online is False else item["stats"]["goal3"] if item["stats"]["goal3"] != "" else 0)) * 100 / ((int(row_player_season_sum["shot3"]) if row_player_season_sum["shot3"] != "" else 0) + (0 if online is False else item["stats"]["shot3"] if item["stats"]["shot3"] != "" else 0)), 1)}%' if row_player_season_sum and row_player_season_sum["shot3"] != "" and item["stats"]["shot3"] != "" else "0.0%" # f'{row_player_season_sum["shot3Percent"]}%' # if row_player_season_sum # and row_player_season_sum["shot3Percent"] != "" # else "0.0%" ), "TShot23Percent": ( f'{round( ((int(row_player_season_sum["goal2"]) if row_player_season_sum["goal2"] != "" else 0) + (0 if online is False else item["stats"]["goal2"] if item["stats"]["goal2"] != "" else 0) + (int(row_player_season_sum["goal3"]) if row_player_season_sum["goal3"] != "" else 0) + (0 if online is False else item["stats"]["goal3"] if item["stats"]["goal3"] != "" else 0)) * 100 / ((int(row_player_season_sum["shot2"]) if row_player_season_sum["shot2"] != "" else 0) + (0 if online is False else item["stats"]["shot2"] if item["stats"]["shot2"] != "" else 0) + ((int(row_player_season_sum["shot3"]) if row_player_season_sum["shot3"] != "" else 0) + (0 if online is False else item["stats"]["shot3"] if item["stats"]["shot3"] != "" else 0))), 1)}%' if row_player_season_sum and row_player_season_sum["shot2"] != "" and item["stats"]["shot2"] != "" else "0.0%" ), "TAssist": safe_int( row_player_season_sum.get("assist") if row_player_season_sum else 0 ) + (0 if online is False else item["stats"]["assist"]), "TBlocks": safe_int( row_player_season_sum.get("blockShot") if row_player_season_sum else 0 ) + (0 if online is False else item["stats"]["block"]), "TDefRebound": safe_int( row_player_season_sum.get("defRebound") if row_player_season_sum else 0 ) + (0 if online is False else item["stats"]["defReb"]), "TOffRebound": safe_int( row_player_season_sum.get("offRebound") if row_player_season_sum else 0 ) + (0 if online is False else item["stats"]["offReb"]), "TRebound": safe_int( row_player_season_sum.get("rebound") if row_player_season_sum else 0 ) + (0 if online is False else item["stats"]["defReb"]) + (0 if online is False else item["stats"]["offReb"]), "TSteal": safe_int( row_player_season_sum.get("steal") if row_player_season_sum else 0 ) + (0 if online is False else item["stats"]["steal"]), "TTurnover": safe_int( row_player_season_sum.get("turnover") if row_player_season_sum else 0 ) + (0 if online is False else item["stats"]["turnover"]), "TFoul": safe_int( row_player_season_sum.get("foul") if row_player_season_sum else 0 ) + (0 if online is False else item["stats"]["foul"]), "TOpponentFoul": safe_int( row_player_season_sum.get("foulsOnPlayer") if row_player_season_sum else 0 ) + (0 if online is False else item["stats"]["foulsOn"]), "TPlusMinus": 0, "TKPI": 0, "TPlayedTime": ( row_player_season_sum["playedTime"] if row_player_season_sum else "0:00" ), "TGameCount": safe_int( row_player_season_sum.get("games") if row_player_season_sum and row_player_season_sum["games"] != "" else 0 ) + (0 if online is False else 1), "TStartCount": safe_int( row_player_season_sum.get("isStarts") if row_player_season_sum and row_player_season_sum["isStarts"] != "" else 0 ), "CareerTPoints": safe_int( row_player_career_sum.get("points") if row_player_career_sum and row_player_career_sum["points"] != "" else 0 ) + (0 if online is False else item["stats"]["points"]), "CareerTShots1": ( f'{(int(row_player_career_sum["goal1"]) if row_player_career_sum["goal1"] != "" else 0) + (0 if online is False else item["stats"]["goal1"] if item["stats"]["goal1"] != "" else 0)}/{(int(row_player_career_sum["shot1"]) if row_player_career_sum["shot1"] != "" else 0) + (0 if online is False else item["stats"]["shot1"] if item["stats"]["shot1"] != "" else 0)}' if row_player_career_sum and row_player_career_sum["shot1"] != "" and item["stats"]["shot1"] != "" else "0/0" ), "CareerTShots2": ( f'{(int(row_player_career_sum["goal2"]) if row_player_career_sum["goal2"] != "" else 0) + (0 if online is False else item["stats"]["goal2"] if item["stats"]["goal2"] != "" else 0)}/{(int(row_player_career_sum["shot2"]) if row_player_career_sum["shot2"] != "" else 0) + (0 if online is False else item["stats"]["shot2"] if item["stats"]["shot2"] != "" else 0)}' if row_player_career_sum and row_player_career_sum["shot2"] != "" and item["stats"]["shot2"] != "" else "0/0" ), "CareerTShots3": ( f'{(int(row_player_career_sum["goal3"]) if row_player_career_sum["goal3"] != "" else 0) + (0 if online is False else item["stats"]["goal3"] if item["stats"]["goal3"] != "" else 0)}/{(int(row_player_career_sum["shot3"]) if row_player_career_sum["shot3"] != "" else 0) + (0 if online is False else item["stats"]["shot3"] if item["stats"]["shot3"] != "" else 0)}' if row_player_career_sum and row_player_career_sum["shot3"] != "" and item["stats"]["shot3"] != "" else "0/0" ), "CareerTShots23": ( f'{safe_int(row_player_career_sum.get("goal2")) + safe_int(row_player_career_sum.get("goal3")) + (0 if online is False else item["stats"]["goal2"] if item["stats"]["goal2"] != "" else 0) + (0 if online is False else item["stats"]["goal3"] if item["stats"]["goal3"] != "" else 0)}/' f'{safe_int(row_player_career_sum.get("shot2")) + safe_int(row_player_career_sum.get("shot3")) + (0 if online is False else item["stats"]["shot2"] if item["stats"]["shot2"] != "" else 0) + (0 if online is False else item["stats"]["shot3"] if item["stats"]["shot3"] != "" else 0)}' if row_player_career_sum else "0/0" ), "CareerTShot1Percent": ( f'{round( ((int(row_player_career_sum["goal1"]) if row_player_career_sum["goal1"] != "" else 0) + (0 if online is False else item["stats"]["goal1"] if item["stats"]["goal1"] != "" else 0)) * 100 / ((int(row_player_career_sum["shot1"]) if row_player_career_sum["shot1"] != "" else 0) + (0 if online is False else item["stats"]["shot1"] if item["stats"]["shot1"] != "" else 0)), 1)}%' if row_player_career_sum and row_player_career_sum["shot1"] != "" and item["stats"]["shot1"] != "" else "0.0%" ), "CareerTShot2Percent": ( f'{round( ((int(row_player_career_sum["goal2"]) if row_player_career_sum["goal2"] != "" else 0) + (0 if online is False else item["stats"]["goal2"] if item["stats"]["goal2"] != "" else 0)) * 100 / ((int(row_player_career_sum["shot2"]) if row_player_career_sum["shot2"] != "" else 0) + (0 if online is False else item["stats"]["shot2"] if item["stats"]["shot2"] != "" else 0)), 1)}%' if row_player_career_sum and row_player_career_sum["shot2"] != "" and item["stats"]["shot2"] != "" else "0.0%" ), "CareerTShot3Percent": ( f'{round( ((int(row_player_career_sum["goal3"]) if row_player_career_sum["goal3"] != "" else 0) + (0 if online is False else item["stats"]["goal3"] if item["stats"]["goal3"] != "" else 0)) * 100 / ((int(row_player_career_sum["shot3"]) if row_player_career_sum["shot3"] != "" else 0) + (0 if online is False else item["stats"]["shot3"] if item["stats"]["shot3"] != "" else 0)), 1)}%' if row_player_career_sum and row_player_career_sum["shot3"] != "" and item["stats"]["shot3"] != "" else "0.0%" ), "CareerTShot23Percent": ( f'{round( ((int(row_player_career_sum["goal2"]) if row_player_career_sum["goal2"] != "" else 0) + (0 if online is False else item["stats"]["goal2"] if item["stats"]["goal2"] != "" else 0) + (int(row_player_career_sum["goal3"]) if row_player_career_sum["goal3"] != "" else 0) + (0 if online is False else item["stats"]["goal3"] if item["stats"]["goal3"] != "" else 0)) * 100 / ((int(row_player_career_sum["shot2"]) if row_player_career_sum["shot2"] != "" else 0) + (0 if online is False else item["stats"]["shot2"] if item["stats"]["shot2"] != "" else 0) + ((int(row_player_career_sum["shot3"]) if row_player_career_sum["shot3"] != "" else 0) + (0 if online is False else item["stats"]["shot3"] if item["stats"]["shot3"] != "" else 0))), 1)}%' if row_player_career_sum and row_player_career_sum["shot2"] != "" and item["stats"]["shot2"] != "" else "0.0%" ), "CareerTAssist": safe_int( row_player_career_sum.get("assist") if row_player_career_sum else 0 ) + (0 if online is False else item["stats"]["assist"]), "CareerTBlocks": safe_int( row_player_career_sum.get("blockShot") if row_player_career_sum else 0 ) + (0 if online is False else item["stats"]["block"]), "CareerTDefRebound": safe_int( row_player_career_sum.get("defRebound") if row_player_career_sum else 0 ) + (0 if online is False else item["stats"]["defReb"]), "CareerTOffRebound": safe_int( row_player_career_sum.get("offRebound") if row_player_career_sum else 0 ) + (0 if online is False else item["stats"]["offReb"]), "CareerTRebound": safe_int( row_player_career_sum.get("rebound") if row_player_career_sum else 0 ) + (0 if online is False else item["stats"]["defReb"]) + (0 if online is False else item["stats"]["offReb"]), "CareerTSteal": safe_int( row_player_career_sum.get("steal") if row_player_career_sum else 0 ) + (0 if online is False else item["stats"]["steal"]), "CareerTTurnover": safe_int( row_player_career_sum.get("turnover") if row_player_career_sum else 0 ) + (0 if online is False else item["stats"]["turnover"]), "CareerTFoul": safe_int( row_player_career_sum.get("foul") if row_player_career_sum else 0 ) + (0 if online is False else item["stats"]["foul"]), "CareerTOpponentFoul": safe_int( row_player_career_sum.get("foulsOnPlayer") if row_player_career_sum else 0 ) + (0 if online is False else item["stats"]["foulsOn"]), "CareerTPlusMinus": 0, "CareerTPlayedTime": ( row_player_career_sum["playedTime"] if row_player_career_sum else "0:00" ), "CareerTGameCount": safe_int( row_player_career_sum.get("games") if row_player_career_sum else 0 ) + (0 if online is False else 1), "CareerTStartCount": safe_int( row_player_career_sum.get("isStarts") if row_player_career_sum else 0 ), "HeadCoachStatsCareer": HeadCoachStatsCareer, "HeadCoachStatsTeam": HeadCoachStatsTeam, } # print(row_player_career_avg) # print(row_player_career_sum) # print(item) # print(player) team.append(player) count_player = sum(1 for x in team if x["startRole"] == "Player") if count_player < 12: if team: # Check if team is not empty empty_rows = [ { key: ( False if key in ["captain", "isStart", "isOnCourt"] else ( 0 if key in [ "id", "pts", "weight", "height", "age", "ast", "stl", "blk", "blkVic", "dreb", "oreb", "reb", "to", "foul", "foulT", "foulD", "foulC", "foulB", "fouled", "plusMinus", "dunk", "kpi", ] else "" ) ) for key in team[0].keys() } for _ in range((4 if count_player <= 4 else 12) - count_player) ] team.extend(empty_rows) else: time.sleep(3) pass sorted_team = sorted( team, key=lambda x: ("Player", "", "Coach", "Team").index(x["startRole"]) ) rewrite_file(who, sorted_team) top_sorted_team = sorted( filter(lambda x: x["startRole"] in ["Player", ""], sorted_team), key=lambda x: ( x["pts"], x["dreb"] + x["oreb"], x["ast"], x["stl"], x["blk"], x["time"], ), reverse=True, ) for item in top_sorted_team: item["pts"] = "" if item["num"] == "" else item["pts"] item["foul"] = "" if item["num"] == "" else item["foul"] rewrite_file(f"top{who.replace('t','T')}", top_sorted_team) started_team = sorted( filter( lambda x: x["startRole"] == "Player" and x["isOnCourt"] is True, sorted_team, ), key=lambda x: int(x["num"]), reverse=False, ) rewrite_file(f"started_{who}", started_team) time.sleep(0.5) def add_new_team_stat(data, avg_age, points, avg_height, timeout_str, timeout_left): data["pt-1"] = f'{data["goal1"]}/{data["shot1"]}' data["pt-2"] = f'{data["goal2"]}/{data["shot2"]}' data["pt-3"] = f'{data["goal3"]}/{data["shot3"]}' data["fg"] = ( f'{int(data["goal2"]) + int(data["goal3"])}/{int(data["shot2"]) + int(data["shot3"])}' ) data["pt-1_pro"] = ( f'{round(int(data["goal1"]) / int(data["shot1"]) * 100)}%' if int(data["shot1"]) != 0 else "0%" ) data["pt-2_pro"] = ( f'{round(int(data["goal2"]) / int(data["shot2"]) * 100)}%' if int(data["shot2"]) != 0 else "0%" ) data["pt-3_pro"] = ( f'{round(int(data["goal3"]) / int(data["shot3"]) * 100)}%' if int(data["shot3"]) != 0 else "0%" ) data["fg_pro"] = ( f'{round((int(data["goal2"]) + int(data["goal3"])) / (int(data["shot2"]) + int(data["shot3"])) * 100)}%' if int(data["shot2"]) != 0 or int(data["shot3"]) != 0 else "0%" ) data["Reb"] = f'{int(data["defReb"]) + int(data["offReb"])}' data["avgAge"] = avg_age data["ptsStart"] = points[0] data["ptsStart_pro"] = points[1] data["ptsBench"] = points[2] data["ptsBench_pro"] = points[3] data["avgHeight"] = f"{avg_height} cm" data["timeout_left"] = timeout_left data["timeout_str"] = timeout_str for k, v in data.items(): data[k] = str(v) return data def add_data_for_teams(new_data): players = [item for item in new_data if item["startRole"] == "Player"] # for player in players: # print(player) points_start = sum( player["stats"]["points"] for player in players if player["stats"]["isStart"] is True ) points_bench = sum( player["stats"]["points"] for player in players if player["stats"]["isStart"] is False ) points_start_pro = ( (str(round(points_start / (points_start + points_bench) * 100)) + "%") if points_start != 0 or points_bench != 0 else "0%" ) points_bench_pro = ( (str(round(points_bench / (points_start + points_bench) * 100)) + "%") if points_start != 0 or points_bench != 0 else "0%" ) points = [points_start, points_start_pro, points_bench, points_bench_pro] try: total_age = sum(player["age"] for player in players) average_age = total_age / len(players) if len(players) > 0 else 0 average_age = round(average_age, 1) except TypeError: average_age = 0 try: total_height = sum(player["height"] for player in players) average_height = total_height / len(players) if len(players) > 0 else 0 average_height = round(average_height, 1) except TypeError: average_height = 0 return average_age, points, average_height def time_outs_func(data_pbp): timeout1 = [] timeout2 = [] for event in data_pbp: if event["play"] == 23: if event["startNum"] == 1: timeout1.append(event) elif event["startNum"] == 2: timeout2.append(event) def timeout_str(timeout): timeout_str = "" timeout_left = "" count_timeout = 0 if last_event["period"] < 3: timeout_max = 2 count_timeout = sum( 1 for t in timeout if t["period"] <= last_event["period"] ) timeout_left = timeout_max - count_timeout quarter = "1st half" elif last_event["period"] < 5: timeout_max = 3 count_timeout = sum( 1 for t in timeout if 2 < t["period"] <= last_event["period"] ) timeout_left = timeout_max - count_timeout quarter = "2nd half" if ( last_event["period"] == 4 and last_event["sec"] >= 4800 and count_timeout in (0, 1) ): timeout_max = 2 timeout_left = timeout_max - count_timeout quarter = "2nd half" else: ot = last_event["period"] - 4 timeout_max = 1 count_timeout = sum( 1 for t in timeout if t["period"] == last_event["period"] ) timeout_left = timeout_max - count_timeout quarter = f"OverTime {ot}" timeout_word = "Time-outs" if timeout_left != 1 else "Time-out" timeout_str = f"{timeout_left if timeout_left != 0 else 'No'} {timeout_word} left in {quarter}" return timeout_str, timeout_left timeout_str1 = "" timeout_left1 = "" timeout_str2 = "" timeout_left2 = "" if data_pbp != []: last_event = data_pbp[-1] timeout_str1, timeout_left1 = timeout_str(timeout1) timeout_str2, timeout_left2 = timeout_str(timeout2) return timeout_str1, timeout_left1, timeout_str2, timeout_left2 def Team_Both_Stat(data, event): logger.info("START making json for team statistics") while not event.is_set(): team_stat_1 = Team_Stat_Game(data["team1_id"], data["game_id"]) team_stat_2 = Team_Stat_Game(data["team2_id"], data["game_id"]) data_pbp = Game_Online(data["game_id"]) data_pbp = data_pbp["result"]["plays"] timeout_str1, timeout_left1, timeout_str2, timeout_left2 = time_outs_func( data_pbp ) avg_age_1, points_1, avg_height_1 = add_data_for_teams(team_stat_1["starts"]) avg_age_2, points_2, avg_height_2 = add_data_for_teams(team_stat_2["starts"]) # timeout_str1, timeout_left1 = "", "" # timeout_str2, timeout_left2 = "", "" team_stat_1 = add_new_team_stat( team_stat_1["total"], avg_age_1, points_1, avg_height_1, timeout_str1, timeout_left1, ) team_stat_2 = add_new_team_stat( team_stat_2["total"], avg_age_2, points_2, avg_height_2, timeout_str2, timeout_left2, ) result_json = [] for key in team_stat_1: val1 = ( team_stat_1[key] if type(team_stat_1[key]) is not float else int(team_stat_1[key]) ) val2 = ( team_stat_2[key] if type(team_stat_2[key]) is not float else int(team_stat_2[key]) ) new_stat_rus = "" new_stat_eng = "" for s in stat_name_list: if s[0] == key: new_stat_rus = s[1] new_stat_eng = s[2] result_json.append( { "name": key, "nameGFX_rus": new_stat_rus, "nameGFX_eng": new_stat_eng, "val1": val1, "val2": val2, } ) rewrite_file("team_stats", result_json) logger.debug("Успешно положенны данные в файл") time.sleep(0.5) def restartable_thread(target, args, event): while not event.is_set(): thread = Thread(target=target, args=args) thread.start() thread.join() if not event.is_set(): logger.warning(f"Поток {target.__name__} завершился. Перезапуск...") def Game_Online(game_id): box_score = requests.get(f"{URL}api/abc/games/box-score?Id={game_id}") # print(f"{URL}api/abc/games/box-score?Id={game_id}") # print(f"{URL}api/abc/games/game?Id={game_id}&Lang={LANG}") # print(f"{URL}api/abc/games/play-by-play?Id={game_id}") if box_score.status_code == 200: if box_score.json()["status"] != "Ok": game = requests.get(f"{URL}api/abc/games/game?Id={game_id}&Lang={LANG}") game = game.json() logger.debug("У нас получилось получить данные со старого матча") # print(game) else: # ОНЛАЙН game = requests.get(f"{URL}api/abc/games/game?Id={game_id}&Lang={LANG}") play_by_play = requests.get(f"{URL}api/abc/games/play-by-play?Id={game_id}") game = game.json() for index_team, i in enumerate(game["result"]["teams"][1:]): for s in i["starts"]: matching_stats = next( ( stat for stat in box_score.json()["result"]["teams"][index_team][ "starts" ] if stat["startNum"] == s["startNum"] ), None, # Значение по умолчанию, если не найдено совпадение ) if matching_stats: s["stats"] = matching_stats i["total"] = box_score.json()["result"]["teams"][index_team]["total"] game["result"]["plays"] = play_by_play.json()["result"] game["result"]["scoreByPeriods"] = box_score.json()["result"][ "scoreByPeriods" ] game["result"]["fullScore"] = box_score.json()["result"]["fullScore"] logger.debug("Склеил данные по онлайн матчу") return game else: logger.warning(f"{myhost}\nAPI responed {box_score['status']}") return None def Referee(data, event): logger.info("START making json for referee") while not event.is_set(): payload = Game_Online(data["game_id"]) referee = payload["result"]["teams"][0]["starts"] referee = [ { "displayNumber": r["displayNumber"], "positionName": r["positionName"], "lastNameGFX": f'{r["firstName"]} {r["lastName"]}', "secondName": r["secondName"], "birthday": r["birthday"], "age": r["age"], "flag": f"https://flagicons.lipis.dev/flags/4x3/{r['countryId'].lower() if r['countryName'] else ''}.svg", } for r in referee ] desired_order = [ "Crew chief", "Referee 1", "Referee 2", "Commissioner", "Ст.судья", "Судья 1", "Судья 2", "Комиссар", ] referee = sorted( referee, key=lambda x: ( desired_order.index(x["positionName"]) if x["positionName"] in desired_order else len(desired_order) ), ) rewrite_file("referee", referee) logger.debug("Успешно записаны судьи в файл") time.sleep(60) def Scores_Quarter(data, event): logger.info(f"START making json for scores quarter") while not event.is_set(): payload = Game_Online(data["game_id"]) rewrite_file("game_online", payload) quarters = ["Q1", "Q2", "Q3", "Q4", "OT1", "OT2", "OT3", "OT4"] score_by_quarter_new = [ {"Q": quarter, "score1": "", "score2": ""} for quarter in quarters ] if payload["result"]["game"]["fullScore"]: fullscore = payload["result"]["game"]["fullScore"].split(",") for index, score in enumerate(fullscore): score_by_quarter_new[index]["score1"] = score.split(":")[0] score_by_quarter_new[index]["score2"] = score.split(":")[1] rewrite_file("scores", score_by_quarter_new) logger.debug("Успешно положил данные о счете по четвертям в файл") time.sleep(0.5) elif ( "scoreByPeriods" in payload["result"] and payload["result"]["scoreByPeriods"] ): fullscore = payload["result"]["scoreByPeriods"] for index, score in enumerate(fullscore): score_by_quarter_new[index]["score1"] = score["score1"] score_by_quarter_new[index]["score2"] = score["score2"] rewrite_file("scores", score_by_quarter_new) logger.debug("Успешно положил данные о счете по четвертям в файл") time.sleep(0.5) else: for score in score_by_quarter_new: score["score1"] = "" score["score2"] = "" rewrite_file("scores", score_by_quarter_new) logger.debug("Данных нет, положил пустоту в счет по четвертям") time.sleep(10) def Standing_func(data, event): logger.info("START making json for standings") while not event.is_set(): try: season = data["season"] url = ( f"{URL}api/abc/comps/standings?tag={LEAGUE}&season={season}&lang={LANG}" ) data_standings = requests.get(url) data_standings = data_standings.json() if data_standings and "items" in data_standings and data_standings["items"]: standings_temp = data_standings["items"][0].get("standings") if standings_temp: df = pd.json_normalize(standings_temp) del df["scores"] if not df["totalWin"].isna().all(): df["w_l"] = ( df["totalWin"].astype(str) + " / " + df["totalDefeat"].astype(str) ) df["procent"] = df.apply( lambda row: ( 0 if row["w_l"] == "0 / 0" or row["totalGames"] == 0 or pd.isna(row["totalWin"]) else round( row["totalWin"] * 100 / row["totalGames"] + 0.000005 ) ), axis=1, ) df["name"] = df["name"].replace("PBC Uralmash", "Uralmash") df.to_json( f"JSON/standings_{LEAGUE}.json", orient="records", force_ascii=False, indent=4, ) logger.debug("Standings data saved successfully.") else: logger.warning("Турнирное положение пусто.") except Exception as e: logger.warning(f"Ошибка в турнирном положении: {e}") time.sleep(60) def status_online_func(data): url = f"{URL}api/abc/games/live-status?id={data['game_id']}" # print(url) json_live_status = requests.get(url) json_live_status = json_live_status.json() if json_live_status["status"] == "Ok": temp_live_status = json_live_status["result"] path_to_png = ( r"D:\ГРАФИКА\БАСКЕТБОЛ\ЕДИНАЯ ЛИГА ВТБ 2022-2023\Scorebug Indicators" ) fouls_1 = 5 if temp_live_status["foulsA"] >= 5 else temp_live_status["foulsA"] fouls_2 = 5 if temp_live_status["foulsB"] >= 5 else temp_live_status["foulsB"] temp_live_status["foulsA_png"] = f"{path_to_png}\\Home_{fouls_1}.png" temp_live_status["foulsB_png"] = f"{path_to_png}\\Away_{fouls_2}.png" return temp_live_status def Status_Online(data, event): logger.info(f"START making json for status online") while not event.is_set(): temp_live_status = status_online_func(data) rewrite_file("live_status", [temp_live_status]) logger.debug("успешно положил данные об онлайн статусе в файл") time.sleep(0.5) def Play_By_Play(data, event): logger.info("START making json for play-by-play") payload1 = Team_Stat_Game(f'{data["team1_id"]}', data["game_id"]) team1_startnum = [ i["startNum"] for i in payload1["starts"] if i["startRole"] == "Player" ] payload2 = Team_Stat_Game(f'{data["team2_id"]}', data["game_id"]) team2_startnum = [ i["startNum"] for i in payload2["starts"] if i["startRole"] == "Player" ] team1_name = data["team1"] team2_name = data["team2"] while not event.is_set(): data_pbp = Game_Online(data["game_id"]) url = f"{URL}api/abc/games/live-status?id={data['game_id']}" json_live_status = requests.get(url) json_live_status = json_live_status.json() data_pbp = data_pbp["result"]["plays"] if data_pbp: df_data_pbp = pd.DataFrame(data_pbp[::-1]) last_event = data_pbp[-1] if "play" in df_data_pbp: if json_live_status["status"] != "Not Found": json_quarter = json_live_status["result"]["period"] json_second = json_live_status["result"]["second"] else: json_quarter = last_event["period"] json_second = 0 timer_str = "" if "3x3" in LEAGUE: df_data_pbp["play"].replace({2: 1, 3: 2}, inplace=True) df_goals = df_data_pbp.loc[df_data_pbp["play"].isin([1, 2, 3])].copy() if not df_goals.empty: df_goals.loc[ df_goals["startNum"].isin(team1_startnum), "score1" ] = df_goals["play"] df_goals.loc[ df_goals["startNum"].isin(team2_startnum), "score2" ] = df_goals["play"] df_goals["score_sum1"] = df_goals["score1"].fillna(0).cumsum() df_goals["score_sum2"] = df_goals["score2"].fillna(0).cumsum() df_goals["new_sec"] = ( df_goals["sec"].astype(str).str.slice(0, -1).astype(int) ) df_goals["time_now"] = ( 600 if json_quarter < 5 else 300 ) - json_second df_goals["quar"] = json_quarter - df_goals["period"] df_goals["diff_time"] = np.where( df_goals["quar"] == 0, df_goals["time_now"] - df_goals["new_sec"], (600 * df_goals["quar"] - df_goals["new_sec"]) + (df_goals["time_now"]), ) df_goals["diff_time_str"] = df_goals["diff_time"].apply( lambda x: ( f"{x // 60}:{str(x % 60).zfill(2)}" if isinstance(x, int) else x ) ) df_goals["team"] = df_goals.apply( lambda row: ( team1_name if not pd.isna(row["score1"]) else team2_name ), axis=1, ) df_goals["text_rus"] = df_goals.apply( lambda row: ( f"рывок {int(row['score_sum1'])}-{int(row['score_sum2'])}" if not pd.isna(row["score1"]) else f"рывок {int(row['score_sum2'])}-{int(row['score_sum1'])}" ), axis=1, ) df_goals["text_time_rus"] = df_goals.apply( lambda row: ( f"рывок {int(row['score_sum1'])}-{int(row['score_sum2'])} за {row['diff_time_str']}" if not pd.isna(row["score1"]) else f"рывок {int(row['score_sum2'])}-{int(row['score_sum1'])} за {row['diff_time_str']}" ), axis=1, ) df_goals["text"] = df_goals.apply( lambda row: ( f"{team1_name} {int(row['score_sum1'])}-{int(row['score_sum2'])} run" if not pd.isna(row["score1"]) else f"{team2_name} {int(row['score_sum2'])}-{int(row['score_sum1'])} run" ), axis=1, ) df_goals["text_time"] = df_goals.apply( lambda row: ( f"{team1_name} {int(row['score_sum1'])}-{int(row['score_sum2'])} run in last {row['diff_time_str']}" if not pd.isna(row["score1"]) else f"{team2_name} {int(row['score_sum2'])}-{int(row['score_sum1'])} run in last {row['diff_time_str']}" ), axis=1, ) new_order = ["text", "text_time"] + [ col for col in df_goals.columns if col not in ["text", "text_time"] ] df_goals = df_goals[new_order] for _ in [ "children", "start", "stop", "hl", "sort", "startNum", "zone", "x", "y", ]: del df_goals[_] df_goals.to_json( "JSON/play_by_play", orient="records", force_ascii=False, indent=4, ) logger.debug("успешно положил данные об play-by-play в файл") time.sleep(0.5) else: logger.debug("нет данных в play-by-play") time.sleep(60) def How_To_Play_Quarter(data): game_id = data["game_id"] team1_id = data["team1_id"] team2_id = data["team2_id"] team1_name = data["team1"] team2_name = data["team2"] season = data["season"] url = f"{URL}api/abc/comps/calendar?Tag={LEAGUE}&Season={season}&Lang={LANG}&MaxResultCount=1000" schedule_data = get_json(url) df_schedule = pd.json_normalize(schedule_data["items"]) df_schedule_new = df_schedule[ [ "game.id", "ot", "game.gameStatus", "game.score1", "game.score2", "game.fullScore", "team1.teamId", "team1.name", "team2.teamId", "team2.name", ] ] def calculate_win(row, team_id): if ( row["team1.teamId"] == team_id and row["game.score1"] > row["game.score2"] ) or ( row["team2.teamId"] == team_id and row["game.score2"] > row["game.score1"] ): return 1 else: return 0 df_schedule_new_2 = df_schedule_new.loc[ (df_schedule_new["game.id"] < game_id) & ( (df_schedule_new["team1.teamId"].isin([team1_id, team2_id])) | (df_schedule_new["team2.teamId"].isin([team1_id, team2_id])) ) ] def win_lose_draw_quarter(teamid): df_schedule_quarter_team = df_schedule_new_2.loc[ ( (df_schedule_new_2["team1.teamId"] == teamid) | (df_schedule_new_2["team2.teamId"] == teamid) ) ] columns_to_clear = [ "Q1", "Q2", "Q3", "Q4", "OT1", "OT2", "OT3", "OT4", "wldQ1", "wldQ2", "wldQ3", "wldQ4", "wldOT1", "wldOT2", "wldOT3", "wldOT4", "winQ1", "winQ2", "winQ3", "winQ4", "winOT1", "winOT2", "winOT3", "winOT4", "loseQ1", "loseQ2", "loseQ3", "loseQ4", "loseOT1", "loseOT2", "loseOT3", "loseOT4", "drawQ1", "drawQ2", "drawQ3", "drawQ4", "drawOT1", "drawOT2", "drawOT3", "drawOT4", ] df_schedule_quarter_team.loc[:, columns_to_clear] = [""] * len(columns_to_clear) temp_score_quarter = df_schedule_quarter_team["game.fullScore"].str.split(",") df_schedule_quarter_team = df_schedule_quarter_team.copy() for q in range(1, 9): new_q = f"OT{q - 4}" if q > 4 else f"Q{q}" df_schedule_quarter_team[new_q] = temp_score_quarter.apply( lambda x: x[q - 1] if (x is not None and len(x) >= q) else None ) def calculate_quarter_result(row, teamid, quarter_name): if pd.notna(row[quarter_name]) and ":" in row[quarter_name]: score = row[quarter_name].split(":") if len(score) == 2: score1 = int(score[0]) score2 = int(score[1]) if (row["team1.teamId"] == teamid and score1 > score2) or ( row["team2.teamId"] == teamid and score2 > score1 ): return "win" elif (row["team1.teamId"] == teamid and score1 < score2) or ( row["team2.teamId"] == teamid and score2 < score1 ): return "lose" elif score1 == score2: return "draw" return "" quarters = ["Q1", "Q2", "Q3", "Q4", "OT1", "OT2", "OT3", "OT4"] for quarter in quarters: df_schedule_quarter_team.loc[:, f"wld{quarter}"] = ( df_schedule_quarter_team.apply( calculate_quarter_result, args=(teamid, quarter), axis=1 ) ) df_schedule_quarter_team.loc[:, f"win{quarter}"] = ( df_schedule_quarter_team[f"wld{quarter}"] == "win" ).astype(int) df_schedule_quarter_team.loc[:, f"lose{quarter}"] = ( df_schedule_quarter_team[f"wld{quarter}"] == "lose" ).astype(int) df_schedule_quarter_team.loc[:, f"draw{quarter}"] = ( df_schedule_quarter_team[f"wld{quarter}"] == "draw" ).astype(int) return df_schedule_quarter_team df_schedule_quarter_team1 = win_lose_draw_quarter(team1_id) df_schedule_quarter_team2 = win_lose_draw_quarter(team2_id) def score_quarter_team(teamid): df_schedule_quarter_team_new = df_schedule_new_2.loc[ ( (df_schedule_new_2["team1.teamId"] == teamid) | (df_schedule_new_2["team2.teamId"] == teamid) ) ] temp_score_quarter = df_schedule_quarter_team_new["game.fullScore"].str.split( "," ) df_schedule_quarter_team_new.loc[ :, ["Q1", "Q2", "Q3", "Q4", "OT1", "OT2", "OT3", "OT4"] ] = ("", "", "", "", "", "", "", "") df_schedule_quarter_team_new = df_schedule_quarter_team_new.copy() num_elements = temp_score_quarter.apply( lambda x: len(x) if x is not None else 0 ).astype(int) if not num_elements.empty: for q in range(1, num_elements.max() + 1): new_q = f"OT{q - 4}" if q > 4 else f"Q{q}" df_schedule_quarter_team_new.loc[:, new_q] = temp_score_quarter.apply( lambda x: (x[q - 1] if (x is not None and len(x) >= q) else None) ) def calculate_quarter_result(row2, team_id, quarter_name): if pd.notna(row2[quarter_name]) and ":" in row2[quarter_name]: score = row2[quarter_name].split(":") score1 = int(score[0]) score2 = int(score[1]) if row2["team1.teamId"] == team_id: return score1 elif row2["team2.teamId"] == team_id: return score2 elif score1 == score2: return score1 return None quarters = ["Q1", "Q2", "Q3", "Q4", "OT1", "OT2", "OT3", "OT4"] df_schedule_quarter_team_new = df_schedule_quarter_team_new.copy() for quarter in quarters: df_schedule_quarter_team_new.loc[:, f"score{quarter}"] = ( df_schedule_quarter_team_new.apply( calculate_quarter_result, args=(teamid, quarter), axis=1 ) ) return df_schedule_quarter_team_new df_schedule_quarter_team1_new = score_quarter_team(team1_id) df_schedule_quarter_team2_new = score_quarter_team(team2_id) schedule_json_quarter = [ { "team": team1_name, "winQ1": df_schedule_quarter_team1["winQ1"].sum(), "winQ2": df_schedule_quarter_team1["winQ2"].sum(), "winQ3": df_schedule_quarter_team1["winQ3"].sum(), "winQ4": df_schedule_quarter_team1["winQ4"].sum(), "winOT1": df_schedule_quarter_team1["winOT1"].sum(), "winOT2": df_schedule_quarter_team1["winOT2"].sum(), "winOT3": df_schedule_quarter_team1["winOT3"].sum(), "winOT4": df_schedule_quarter_team1["winOT4"].sum(), "loseQ1": df_schedule_quarter_team1["loseQ1"].sum(), "loseQ2": df_schedule_quarter_team1["loseQ2"].sum(), "loseQ3": df_schedule_quarter_team1["loseQ3"].sum(), "loseQ4": df_schedule_quarter_team1["loseQ4"].sum(), "loseOT1": df_schedule_quarter_team1["loseOT1"].sum(), "loseOT2": df_schedule_quarter_team1["loseOT2"].sum(), "loseOT3": df_schedule_quarter_team1["loseOT3"].sum(), "loseOT4": df_schedule_quarter_team1["loseOT4"].sum(), "drawQ1": df_schedule_quarter_team1["drawQ1"].sum(), "drawQ2": df_schedule_quarter_team1["drawQ2"].sum(), "drawQ3": df_schedule_quarter_team1["drawQ3"].sum(), "drawQ4": df_schedule_quarter_team1["drawQ4"].sum(), "drawOT1": df_schedule_quarter_team1["drawOT1"].sum(), "drawOT2": df_schedule_quarter_team1["drawOT2"].sum(), "drawOT3": df_schedule_quarter_team1["drawOT3"].sum(), "drawOT4": df_schedule_quarter_team1["drawOT4"].sum(), "scoreQ1": df_schedule_quarter_team1_new["scoreQ1"].sum(), "scoreQ2": df_schedule_quarter_team1_new["scoreQ2"].sum(), "scoreQ3": df_schedule_quarter_team1_new["scoreQ3"].sum(), "scoreQ4": df_schedule_quarter_team1_new["scoreQ4"].sum(), "scoreOT1": df_schedule_quarter_team1_new["scoreOT1"].sum(), "scoreOT2": df_schedule_quarter_team1_new["scoreOT2"].sum(), "scoreOT3": df_schedule_quarter_team1_new["scoreOT3"].sum(), "scoreOT4": df_schedule_quarter_team1_new["scoreOT4"].sum(), "score_avgQ1": df_schedule_quarter_team1_new["scoreQ1"].mean(), "score_avgQ2": df_schedule_quarter_team1_new["scoreQ2"].mean(), "score_avgQ3": df_schedule_quarter_team1_new["scoreQ3"].mean(), "score_avgQ4": df_schedule_quarter_team1_new["scoreQ4"].mean(), "score_avgOT1": df_schedule_quarter_team1_new["scoreOT1"].mean(), "score_avgOT2": df_schedule_quarter_team1_new["scoreOT2"].mean(), "score_avgOT3": df_schedule_quarter_team1_new["scoreOT3"].mean(), "score_avgOT4": df_schedule_quarter_team1_new["scoreOT4"].mean(), }, { "team": team2_name, "winQ1": df_schedule_quarter_team2["winQ1"].sum(), "winQ2": df_schedule_quarter_team2["winQ2"].sum(), "winQ3": df_schedule_quarter_team2["winQ3"].sum(), "winQ4": df_schedule_quarter_team2["winQ4"].sum(), "winOT1": df_schedule_quarter_team2["winOT1"].sum(), "winOT2": df_schedule_quarter_team2["winOT2"].sum(), "winOT3": df_schedule_quarter_team2["winOT3"].sum(), "winOT4": df_schedule_quarter_team2["winOT4"].sum(), "loseQ1": df_schedule_quarter_team2["loseQ1"].sum(), "loseQ2": df_schedule_quarter_team2["loseQ2"].sum(), "loseQ3": df_schedule_quarter_team2["loseQ3"].sum(), "loseQ4": df_schedule_quarter_team2["loseQ4"].sum(), "loseOT1": df_schedule_quarter_team2["loseOT1"].sum(), "loseOT2": df_schedule_quarter_team2["loseOT2"].sum(), "loseOT3": df_schedule_quarter_team2["loseOT3"].sum(), "loseOT4": df_schedule_quarter_team2["loseOT4"].sum(), "drawQ1": df_schedule_quarter_team2["drawQ1"].sum(), "drawQ2": df_schedule_quarter_team2["drawQ2"].sum(), "drawQ3": df_schedule_quarter_team2["drawQ3"].sum(), "drawQ4": df_schedule_quarter_team2["drawQ4"].sum(), "drawOT1": df_schedule_quarter_team2["drawOT1"].sum(), "drawOT2": df_schedule_quarter_team2["drawOT2"].sum(), "drawOT3": df_schedule_quarter_team2["drawOT3"].sum(), "drawOT4": df_schedule_quarter_team2["drawOT4"].sum(), "scoreQ1": df_schedule_quarter_team2_new["scoreQ1"].sum(), "scoreQ2": df_schedule_quarter_team2_new["scoreQ2"].sum(), "scoreQ3": df_schedule_quarter_team2_new["scoreQ3"].sum(), "scoreQ4": df_schedule_quarter_team2_new["scoreQ4"].sum(), "scoreOT1": df_schedule_quarter_team2_new["scoreOT1"].sum(), "scoreOT2": df_schedule_quarter_team2_new["scoreOT2"].sum(), "scoreOT3": df_schedule_quarter_team2_new["scoreOT3"].sum(), "scoreOT4": df_schedule_quarter_team2_new["scoreOT4"].sum(), "score_avgQ1": df_schedule_quarter_team2_new["scoreQ1"].mean(), "score_avgQ2": df_schedule_quarter_team2_new["scoreQ2"].mean(), "score_avgQ3": df_schedule_quarter_team2_new["scoreQ3"].mean(), "score_avgQ4": df_schedule_quarter_team2_new["scoreQ4"].mean(), "score_avgOT1": df_schedule_quarter_team2_new["scoreOT1"].mean(), "score_avgOT2": df_schedule_quarter_team2_new["scoreOT2"].mean(), "score_avgOT3": df_schedule_quarter_team2_new["scoreOT3"].mean(), "score_avgOT4": df_schedule_quarter_team2_new["scoreOT4"].mean(), }, ] for i in schedule_json_quarter: i["scoreQ1"] = int(i["scoreQ1"]) i["scoreQ2"] = int(i["scoreQ2"]) i["scoreQ3"] = int(i["scoreQ3"]) i["scoreQ4"] = int(i["scoreQ4"]) i["scoreOT1"] = int(i["scoreOT1"]) i["scoreOT2"] = int(i["scoreOT2"]) i["scoreOT3"] = int(i["scoreOT3"]) i["scoreOT4"] = int(i["scoreOT4"]) i["score_avgQ1"] = round(i["score_avgQ1"], 1) if i["score_avgQ1"] else None i["score_avgQ2"] = round(i["score_avgQ2"], 1) if i["score_avgQ2"] else None i["score_avgQ3"] = round(i["score_avgQ3"], 1) if i["score_avgQ3"] else None i["score_avgQ4"] = round(i["score_avgQ4"], 1) if i["score_avgQ4"] else None i["score_avgOT1"] = round(i["score_avgOT1"], 1) if i["score_avgOT1"] else None i["score_avgOT2"] = round(i["score_avgOT2"], 1) if i["score_avgOT2"] else None i["score_avgOT3"] = round(i["score_avgOT3"], 1) if i["score_avgOT3"] else None i["score_avgOT4"] = round(i["score_avgOT4"], 1) if i["score_avgOT4"] else None rewrite_file("scores_quarter", schedule_json_quarter) def Player_Stats_Online_Per_Quarter(data, event): logger.info("START making json for players_stats_per_quarter") payload1 = Team_Stat_Game(f'{data["team1_id"]}', data["game_id"]) team1_formatted = [i for i in payload1["starts"] if i["startRole"] == "Player"] team1_formatted = pd.DataFrame(team1_formatted) team1_formatted_json = team1_formatted.copy() payload2 = Team_Stat_Game(f'{data["team2_id"]}', data["game_id"]) team2_formatted = [i for i in payload2["starts"] if i["startRole"] == "Player"] team2_formatted = pd.DataFrame(team2_formatted) team2_formatted_json = team2_formatted.copy() while not event.is_set(): data_pbp = Game_Online(data["game_id"]) data_pbp = data_pbp["result"]["plays"] df_data_pbp_2 = pd.DataFrame(data_pbp) if "play" in df_data_pbp_2: period_max = df_data_pbp_2[::-1].iloc[0]["period"] childrens = [] for d in data_pbp: if d["children"] != []: for child in d["children"]: child["sec"] = d["sec"] child["period"] = d["period"] child["play_parent"] = d["play"] childrens.append(child) if childrens: df_childers = pd.DataFrame(childrens) df_data_pbp_2 = pd.concat( [df_data_pbp_2, df_childers], ignore_index=True ) temp_data_all = [] temp_data_all = pd.concat([team1_formatted_json, team2_formatted_json]) players_start_num_1 = list(team1_formatted_json["startNum"]) players_start_num_2 = list(team2_formatted_json["startNum"]) df_info_players = pd.DataFrame(temp_data_all) plays_uniq = [x for x in range(100)] # + ["q_ast_NO"] players_uniq = sorted(df_data_pbp_2["startNum"].unique())[3:] columns_temp_8 = [ f"Четверть {i}" if i < 5 else f"Овертайм {i-4}" for i in range(1, int(period_max) + 1) ] for i in range(1, int(period_max) + 1): df_sorted_period = df_data_pbp_2.loc[df_data_pbp_2["period"] == i] df_sorted_period_last = df_sorted_period[::-1].iloc[0]["sec"] time_8_1 = df_sorted_period.loc[(df_sorted_period["play"] == 8)] time_9_1 = df_sorted_period.loc[(df_sorted_period["play"] == 9)] time_8_1 = ( time_8_1[["sec", "period", "startNum", "play"]] .groupby(by="startNum") .sum() ) time_9_1 = ( time_9_1[["sec", "period", "startNum", "play"]] .groupby(by="startNum") .sum() ) time_new_1 = pd.merge( time_8_1, time_9_1, left_index=True, right_index=True, how="left", ) time_new_1["last_sec"] = df_sorted_period_last time_new_1["sec_y"] = time_new_1["sec_y"].fillna(0) time_new_1["sec_y"] = time_new_1.apply( lambda row: ( row["sec_y"] + row["last_sec"] if (row["sec_y"] - row["sec_x"] < 0) or row["sec_y"] == 0 else row["sec_y"] ), axis=1, ) time_new_1["q_time"] = "0:00" time_new_1["q_time"] = time_new_1.apply( lambda row: format_time((row["sec_y"] - row["sec_x"]) // 10), axis=1, ) df_person_2 = pd.DataFrame(index=players_uniq, columns=plays_uniq) # print(df_person_2) df_person = ( df_sorted_period.groupby(["startNum", "play"]) .size() .unstack(fill_value=0) ) for startNum in players_uniq: if startNum in df_person.index: for play in plays_uniq: if play in df_person.columns: df_person_2.loc[startNum, play] = df_person.loc[ startNum, play ] else: df_person_2.loc[startNum, play] = 0 else: for play in plays_uniq: df_person_2.loc[startNum, play] = 0 df_person_2 = pd.merge( df_person_2, df_info_players, how="left", left_index=True, right_on="startNum", ) df_person_2 = pd.merge( df_person_2, time_new_1["q_time"], how="left", left_on="startNum", right_on="startNum", ) df_fouls_on = ( df_sorted_period.loc[ (df_sorted_period["play"].isin([50, 51, 52, 53, 54])) ] .groupby(["startNum", "play"]) .size() .unstack(fill_value=0) ) df_fouls_on["q_f_on"] = df_fouls_on.sum(axis=1) df_assists_no_goal = ( df_sorted_period.loc[ (df_sorted_period["play"] == 25) & (df_sorted_period["play_parent"].isin([4, 5, 6, 27])) ] .groupby(["startNum", "play"]) .size() .unstack(fill_value=0) ) df_assists_no_goal["q_ast_NO"] = df_assists_no_goal.sum(axis=1) df_person_2 = pd.merge( df_person_2, df_assists_no_goal["q_ast_NO"], how="left", left_on="startNum", right_on="startNum", ).fillna(0) df_person_2 = pd.merge( df_person_2, df_fouls_on["q_f_on"], how="left", left_on="startNum", right_on="startNum", ).fillna(0) df_person_2_copy = df_person_2.copy() # Concatenate columns and calculate q_pts new_columns = { "q_pts": df_person_2_copy[1] + df_person_2_copy[2] * 2 + df_person_2_copy[3] * 3, "q_to": df_person_2[10] + df_person_2[11] + df_person_2[12] + df_person_2[13] + df_person_2[14] + df_person_2[15] + df_person_2[16] + df_person_2[17] + df_person_2[18] + df_person_2[19] + df_person_2[20], } df_person_2 = pd.concat( [df_person_2, pd.DataFrame(new_columns)], axis=1 ) df_person_2 = df_person_2.rename( columns={ 1: "q_ft", 2: "q_pt2", 3: "q_pt3", 4: "q_ft_t", 5: "q_pt2_t", 6: "q_pt3_t", 7: "q_ch", 8: "q_ch_in", 9: "q_ch_out", 10: "q_to_", 11: "q_to_pass", 12: "q_to_travel", 13: "q_to_out", 14: "q_to_zone", 15: "q_to_double_dribble", 16: "q_to_3_sec", 17: "q_to_5_sec", 18: "q_to_8_sec", 19: "q_to_24_sec", 20: "q_to_ball", 25: "q_ast", 26: "q_stl", 27: "q_blk", 28: "q_reb", 40: "q_f", 41: "q_foul_u", 42: "q_foul_t", 43: "q_foul_d", 44: "q_foul_c", 45: "q_foul_b", 47: "q_to_foul", 50: "q_to_foul_2", } ) df_person_2["q_ast"] = df_person_2["q_ast"] - df_person_2["q_ast_NO"] columns_to_sum = [ "q_pts", "q_ast", "q_stl", "q_blk", "q_reb", "q_f_on", ] columns_to_subtract = [ "q_ft_t", "q_pt2_t", "q_pt3_t", "q_f", "q_to", ] sum_df = df_person_2[columns_to_sum].sum(axis=1) subtract_df = -df_person_2[columns_to_subtract].sum(axis=1) df_person_2["q_rnk"] = pd.concat([sum_df, subtract_df], axis=1).sum( axis=1 ) df_person_2 = df_person_2.sort_values( ["q_pts", "q_rnk"], ascending=[False, False], ) df_person_2["q_ft"] = ( df_person_2["q_ft"].astype(str) + "/" + (df_person_2["q_ft_t"] + df_person_2["q_ft"]).astype(str) ) df_person_2["q_pt2"] = ( df_person_2["q_pt2"].astype(str) + "/" + (df_person_2["q_pt2_t"] + df_person_2["q_pt2"]).astype(str) ) df_person_2["q_pt3"] = ( df_person_2["q_pt3"].astype(str) + "/" + (df_person_2["q_pt3_t"] + df_person_2["q_pt3"]).astype(str) ) df_person_2["q_pt23"] = ( ( df_person_2["q_pt2"].apply(lambda x: int(x.split("/")[0])) + df_person_2["q_pt3"].apply(lambda x: int(x.split("/")[0])) ).astype(str) + "/" + ( df_person_2["q_pt2"].apply(lambda x: int(x.split("/")[1])) + df_person_2["q_pt3"].apply(lambda x: int(x.split("/")[1])) ).astype(str) ) df_person_2["num"] = df_person_2["playerNumber"] df_person_2["NameGFX"] = ( df_person_2["firstName"] + " " + df_person_2["lastName"] ) df_person_2["role"] = df_person_2["positionName"] df_person_2["teamName"] = df_person_2["teamNumber"].apply( lambda x: data["team1"] if x == 1 else data["team2"] ) role_list = [ ("Center", "C"), ("Guard", "G"), ("Forward", "F"), ("Power forward", "PF"), ("Small forward", "SF"), ("Shooting guard", "SG"), ("Point guard", "PG"), ("Forward-center", "FC"), ] role_dict = dict(role_list) df_person_2["roleShort"] = df_person_2["role"].map(role_dict) df_person_2["roleShort"] = df_person_2["roleShort"].fillna("") df_person_2["photoGFX"] = df_person_2.apply( lambda row: ( f"D:\\Photos\\{LEAGUE}\\{row['teamName']}\\{row['displayNumber']}.png" if row["startRole"] == "Player" else "" ), axis=1, ) df_person_2["Name1GFX"] = df_person_2["firstName"] df_person_2["Name2GFX"] = df_person_2["lastName"] columns_short = [ # "startNum", "num", "NameGFX", "q_time", "q_rnk", "q_pts", "q_reb", "q_ast", # "q_ast_NO", "q_stl", "q_blk", "q_f", "q_f_on", "q_to", "q_ft", "q_pt2", "q_pt3", "q_pt23", "age", "height", "weight", "role", "roleShort", "photoGFX", "Name1GFX", "Name2GFX", # "flag", ] columns_to_int = [ "q_rnk", "q_ast", "q_pts", "q_reb", "q_stl", "q_blk", "q_f", "q_f_on", "q_to", ] # print(list(df_person_2.columns)) df_person_2[columns_to_int] = df_person_2[columns_to_int].astype(int) df_person_2_team_1 = df_person_2[columns_short].loc[ (df_person_2["startNum"].isin(players_start_num_1)) & (df_person_2["role"] != "Coach") & (df_person_2["q_time"] != 0) ] df_person_2_team_2 = df_person_2[columns_short].loc[ (df_person_2["startNum"].isin(players_start_num_2)) & (df_person_2["role"] != "Coach") & (df_person_2["q_time"] != 0) ] df_person_2_team_1.to_json( f"JSON/team1_{i}.json", orient="records", force_ascii=False, indent=4, ) df_person_2_team_2.to_json( f"JSON/team2_{i}.json", orient="records", force_ascii=False, indent=4, ) logger.debug("успешная запись данных players_stats_per_quarter в файл") time.sleep(0.5) def main(): data = get_season_and_schedule() How_To_Play_Quarter(data) logger.info( f"{myhost}\n{data['team1']} VS {data['team2']}\n{data['when']} {data['time']}" ) logger.debug(data) team1_event = Event() team2_event = Event() teams_stat_event = Event() referee_event = Event() scores_quarter_event = Event() standings_event = Event() status_online_event = Event() play_by_play_event = Event() players_quarter_event = Event() team1_monitor_thread = Thread( target=restartable_thread, args=(Json_Team_Generation, ("team1", data, team1_event), team1_event), ) team2_monitor_thread = Thread( target=restartable_thread, args=(Json_Team_Generation, ("team2", data, team2_event), team2_event), ) teams_stat_monitor_thread = Thread( target=restartable_thread, args=(Team_Both_Stat, (data, teams_stat_event), teams_stat_event), ) referee_monitor_thread = Thread( target=restartable_thread, args=(Referee, (data, referee_event), referee_event), ) scores_quarter_monitor_thread = Thread( target=restartable_thread, args=(Scores_Quarter, (data, scores_quarter_event), scores_quarter_event), ) standings_monitor_thread = Thread( target=restartable_thread, args=(Standing_func, (data, standings_event), standings_event), ) status_online_monitor_thread = Thread( target=restartable_thread, args=(Status_Online, (data, status_online_event), status_online_event), ) play_by_play_monitor_thread = Thread( target=restartable_thread, args=(Play_By_Play, (data, play_by_play_event), play_by_play_event), ) players_quarter_monitor_thread = Thread( target=restartable_thread, args=( Player_Stats_Online_Per_Quarter, (data, players_quarter_event), players_quarter_event, ), ) try: team1_monitor_thread.start() team2_monitor_thread.start() teams_stat_monitor_thread.start() referee_monitor_thread.start() scores_quarter_monitor_thread.start() standings_monitor_thread.start() status_online_monitor_thread.start() play_by_play_monitor_thread.start() players_quarter_monitor_thread.start() while True: time.sleep(1) except KeyboardInterrupt: logger.info("Прерывание программы пользователем. Завершаем потоки...") team1_event.set() team2_event.set() teams_stat_event.set() referee_event.set() scores_quarter_event.set() standings_event.set() status_online_event.set() play_by_play_event.set() players_quarter_event.set() finally: team1_monitor_thread.join() team2_monitor_thread.join() teams_stat_monitor_thread.join() referee_monitor_thread.join() scores_quarter_monitor_thread.join() standings_monitor_thread.join() status_online_monitor_thread.join() play_by_play_monitor_thread.join() players_quarter_monitor_thread.join() logger.info("Все потоки завершены.") if __name__ == "__main__": start = time.perf_counter() main() end = time.perf_counter() delta = end - start print("=" * 20) print( f"выполнено за {delta:.2f} секунд = {int(end - start)//60}м{int(end - start)%60}с" )