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https://github.com/ChuckBuilds/LEDMatrix.git
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update leaderboard data sources for other sports and font sizes
This commit is contained in:
Chuck
@@ -7,9 +7,15 @@ from datetime import datetime, timedelta, timezone
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import os
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from PIL import Image, ImageDraw, ImageFont
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import pytz
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from .display_manager import DisplayManager
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from .cache_manager import CacheManager
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from .config_manager import ConfigManager
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try:
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from .display_manager import DisplayManager
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from .cache_manager import CacheManager
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from .config_manager import ConfigManager
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except ImportError:
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# Fallback for direct imports
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from display_manager import DisplayManager
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from cache_manager import CacheManager
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from config_manager import ConfigManager
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# Import the API counter function from web interface
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try:
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@@ -71,9 +77,12 @@ class LeaderboardManager:
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'league': 'nfl',
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'logo_dir': 'assets/sports/nfl_logos',
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'league_logo': 'assets/sports/nfl_logos/nfl.png',
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'teams_url': 'https://site.api.espn.com/apis/site/v2/sports/football/nfl/teams',
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'standings_url': 'https://site.api.espn.com/apis/v2/sports/football/nfl/standings',
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'enabled': self.enabled_sports.get('nfl', {}).get('enabled', False),
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'top_teams': self.enabled_sports.get('nfl', {}).get('top_teams', 10)
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'top_teams': self.enabled_sports.get('nfl', {}).get('top_teams', 10),
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'season': self.enabled_sports.get('nfl', {}).get('season', 2025),
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'level': self.enabled_sports.get('nfl', {}).get('level', 1),
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'sort': self.enabled_sports.get('nfl', {}).get('sort', 'winpercent:desc,gamesbehind:asc')
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},
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'nba': {
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'sport': 'basketball',
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@@ -89,9 +98,12 @@ class LeaderboardManager:
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'league': 'mlb',
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'logo_dir': 'assets/sports/mlb_logos',
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'league_logo': 'assets/sports/mlb_logos/mlb.png',
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'teams_url': 'https://site.api.espn.com/apis/site/v2/sports/baseball/mlb/teams',
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'standings_url': 'https://site.api.espn.com/apis/v2/sports/baseball/mlb/standings',
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'enabled': self.enabled_sports.get('mlb', {}).get('enabled', False),
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'top_teams': self.enabled_sports.get('mlb', {}).get('top_teams', 10)
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'top_teams': self.enabled_sports.get('mlb', {}).get('top_teams', 10),
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'season': self.enabled_sports.get('mlb', {}).get('season', 2025),
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'level': self.enabled_sports.get('mlb', {}).get('level', 1),
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'sort': self.enabled_sports.get('mlb', {}).get('sort', 'winpercent:desc,gamesbehind:asc')
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},
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'ncaa_fb': {
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'sport': 'football',
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@@ -108,9 +120,12 @@ class LeaderboardManager:
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'league': 'nhl',
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'logo_dir': 'assets/sports/nhl_logos',
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'league_logo': 'assets/sports/nhl_logos/nhl.png',
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'teams_url': 'https://site.api.espn.com/apis/site/v2/sports/hockey/nhl/teams',
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'standings_url': 'https://site.api.espn.com/apis/v2/sports/hockey/nhl/standings',
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'enabled': self.enabled_sports.get('nhl', {}).get('enabled', False),
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'top_teams': self.enabled_sports.get('nhl', {}).get('top_teams', 10)
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'top_teams': self.enabled_sports.get('nhl', {}).get('top_teams', 10),
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'season': self.enabled_sports.get('nhl', {}).get('season', 2025),
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'level': self.enabled_sports.get('nhl', {}).get('level', 1),
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'sort': self.enabled_sports.get('nhl', {}).get('sort', 'winpercent:desc,gamesbehind:asc')
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},
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'ncaam_basketball': {
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'sport': 'basketball',
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@@ -120,6 +135,19 @@ class LeaderboardManager:
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'teams_url': 'https://site.api.espn.com/apis/site/v2/sports/basketball/mens-college-basketball/teams',
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'enabled': self.enabled_sports.get('ncaam_basketball', {}).get('enabled', False),
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'top_teams': self.enabled_sports.get('ncaam_basketball', {}).get('top_teams', 25)
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},
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'ncaa_baseball': {
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'sport': 'baseball',
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'league': 'college-baseball',
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'logo_dir': 'assets/sports/ncaa_fbs_logos',
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'league_logo': 'assets/sports/ncaa_fbs_logos/ncaa_baseball.png',
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'standings_url': 'https://site.api.espn.com/apis/v2/sports/baseball/college-baseball/standings',
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'scoreboard_url': 'https://site.api.espn.com/apis/site/v2/sports/baseball/college-baseball/scoreboard',
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'enabled': self.enabled_sports.get('ncaa_baseball', {}).get('enabled', False),
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'top_teams': self.enabled_sports.get('ncaa_baseball', {}).get('top_teams', 25),
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'season': self.enabled_sports.get('ncaa_baseball', {}).get('season', 2025),
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'level': self.enabled_sports.get('ncaa_baseball', {}).get('level', 1),
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'sort': self.enabled_sports.get('ncaa_baseball', {}).get('sort', 'winpercent:desc,gamesbehind:asc')
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}
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}
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@@ -152,15 +180,17 @@ class LeaderboardManager:
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try:
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return {
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'small': ImageFont.truetype("assets/fonts/PressStart2P-Regular.ttf", 6),
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'medium': ImageFont.truetype("assets/fonts/PressStart2P-Regular.ttf", 8),
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'large': ImageFont.truetype("assets/fonts/PressStart2P-Regular.ttf", 10)
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'medium': ImageFont.truetype("assets/fonts/PressStart2P-Regular.ttf", 10), # Increased from 8 to 10
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'large': ImageFont.truetype("assets/fonts/PressStart2P-Regular.ttf", 12), # Increased from 10 to 12
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'xlarge': ImageFont.truetype("assets/fonts/PressStart2P-Regular.ttf", 14) # New extra-large font
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}
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except Exception as e:
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logger.error(f"Error loading fonts: {e}")
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return {
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'small': ImageFont.load_default(),
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'medium': ImageFont.load_default(),
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'large': ImageFont.load_default()
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'large': ImageFont.load_default(),
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'xlarge': ImageFont.load_default()
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}
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def _get_team_logo(self, team_abbr: str, logo_dir: str) -> Optional[Image.Image]:
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@@ -213,6 +243,10 @@ class LeaderboardManager:
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if league_key == 'college-football':
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return self._fetch_ncaa_fb_rankings(league_config)
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# Use standings endpoint for NFL, MLB, NHL, and NCAA Baseball
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if league_key in ['nfl', 'mlb', 'nhl', 'college-baseball']:
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return self._fetch_standings_data(league_config)
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try:
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logger.info(f"Fetching fresh leaderboard data for {league_key}")
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@@ -391,6 +425,189 @@ class LeaderboardManager:
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logger.error(f"Error fetching rankings for {league_key}: {e}")
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return []
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def _fetch_standings_data(self, league_config: Dict[str, Any]) -> List[Dict[str, Any]]:
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"""Fetch standings data from ESPN API using the standings endpoint."""
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league_key = league_config['league']
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cache_key = f"leaderboard_{league_key}_standings"
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# Try to get cached data first
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cached_data = self.cache_manager.get_cached_data_with_strategy(cache_key, 'leaderboard')
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if cached_data:
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logger.info(f"Using cached standings data for {league_key}")
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return cached_data.get('standings', [])
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try:
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logger.info(f"Fetching fresh standings data for {league_key}")
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# Build the standings URL with query parameters
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standings_url = league_config['standings_url']
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params = {
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'season': league_config.get('season', 2025),
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'level': league_config.get('level', 1),
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'sort': league_config.get('sort', 'winpercent:desc,gamesbehind:asc')
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}
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logger.info(f"Fetching standings from: {standings_url} with params: {params}")
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response = requests.get(standings_url, params=params, timeout=self.request_timeout)
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response.raise_for_status()
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data = response.json()
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# Increment API counter for sports data
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increment_api_counter('sports', 1)
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standings = []
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# Parse the standings data structure
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# Check if we have direct standings data or children (divisions/conferences)
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if 'standings' in data and 'entries' in data['standings']:
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# Direct standings data (e.g., NFL overall standings)
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standings_data = data['standings']['entries']
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logger.info(f"Processing direct standings data with {len(standings_data)} teams")
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for entry in standings_data:
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team_data = entry.get('team', {})
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stats = entry.get('stats', [])
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team_name = team_data.get('displayName', 'Unknown')
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team_abbr = team_data.get('abbreviation', 'Unknown')
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# Extract record from stats
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wins = 0
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losses = 0
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ties = 0
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win_percentage = 0.0
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# First pass: collect all stat values
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games_played = 0
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for stat in stats:
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stat_type = stat.get('type', '')
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stat_value = stat.get('value', 0)
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if stat_type == 'wins':
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wins = int(stat_value)
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elif stat_type == 'losses':
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losses = int(stat_value)
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elif stat_type == 'ties':
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ties = int(stat_value)
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elif stat_type == 'winpercent':
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win_percentage = float(stat_value)
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# NHL specific stats
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elif stat_type == 'overtimelosses' and league_key == 'nhl':
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ties = int(stat_value) # NHL uses overtime losses as ties
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elif stat_type == 'gamesplayed' and league_key == 'nhl':
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games_played = float(stat_value)
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# Second pass: calculate win percentage for NHL if not already set
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if league_key == 'nhl' and win_percentage == 0.0 and games_played > 0:
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win_percentage = wins / games_played
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# Create record summary
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if ties > 0:
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record_summary = f"{wins}-{losses}-{ties}"
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else:
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record_summary = f"{wins}-{losses}"
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standings.append({
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'name': team_name,
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'abbreviation': team_abbr,
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'wins': wins,
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'losses': losses,
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'ties': ties,
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'win_percentage': win_percentage,
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'record_summary': record_summary,
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'division': 'Overall'
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})
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elif 'children' in data:
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# Children structure (divisions/conferences)
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children = data.get('children', [])
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logger.info(f"Processing {len(children)} divisions/conferences")
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for child in children:
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child_name = child.get('displayName', 'Unknown')
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logger.info(f"Processing {child_name}")
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standings_data = child.get('standings', {}).get('entries', [])
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for entry in standings_data:
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team_data = entry.get('team', {})
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stats = entry.get('stats', [])
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team_name = team_data.get('displayName', 'Unknown')
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team_abbr = team_data.get('abbreviation', 'Unknown')
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# Extract record from stats
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wins = 0
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losses = 0
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ties = 0
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win_percentage = 0.0
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# First pass: collect all stat values
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games_played = 0
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for stat in stats:
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stat_type = stat.get('type', '')
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stat_value = stat.get('value', 0)
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if stat_type == 'wins':
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wins = int(stat_value)
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elif stat_type == 'losses':
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losses = int(stat_value)
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elif stat_type == 'ties':
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ties = int(stat_value)
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elif stat_type == 'winpercent':
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win_percentage = float(stat_value)
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# NHL specific stats
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elif stat_type == 'overtimelosses' and league_key == 'nhl':
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ties = int(stat_value) # NHL uses overtime losses as ties
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elif stat_type == 'gamesplayed' and league_key == 'nhl':
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games_played = float(stat_value)
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# Second pass: calculate win percentage for NHL if not already set
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if league_key == 'nhl' and win_percentage == 0.0 and games_played > 0:
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win_percentage = wins / games_played
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# Create record summary
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if ties > 0:
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record_summary = f"{wins}-{losses}-{ties}"
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else:
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record_summary = f"{wins}-{losses}"
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standings.append({
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'name': team_name,
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'abbreviation': team_abbr,
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'wins': wins,
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'losses': losses,
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'ties': ties,
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'win_percentage': win_percentage,
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'record_summary': record_summary,
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'division': child_name
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})
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else:
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logger.warning(f"No standings or children data found for {league_key}")
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return []
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# Sort by win percentage (descending) and limit to top teams
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standings.sort(key=lambda x: x['win_percentage'], reverse=True)
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top_teams = standings[:league_config['top_teams']]
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# Cache the results
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cache_data = {
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'standings': top_teams,
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'timestamp': time.time(),
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'league': league_key,
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'season': params['season'],
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'level': params['level']
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}
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self.cache_manager.save_cache(cache_key, cache_data)
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logger.info(f"Fetched and cached {len(top_teams)} teams for {league_key} standings")
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return top_teams
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except Exception as e:
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logger.error(f"Error fetching standings for {league_key}: {e}")
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return []
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def _fetch_team_record(self, team_abbr: str, league_config: Dict[str, Any]) -> Optional[Dict[str, Any]]:
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"""Fetch individual team record from ESPN API with caching."""
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league = league_config['league']
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@@ -592,11 +809,11 @@ class LeaderboardManager:
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# For other leagues, show position
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number_text = f"{i+1}."
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number_bbox = self.fonts['large'].getbbox(number_text)
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number_bbox = self.fonts['xlarge'].getbbox(number_text)
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number_width = number_bbox[2] - number_bbox[0]
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number_height = number_bbox[3] - number_bbox[1]
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number_y = (height - number_height) // 2
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draw.text((team_x, number_y), number_text, font=self.fonts['large'], fill=(255, 255, 0))
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draw.text((team_x, number_y), number_text, font=self.fonts['xlarge'], fill=(255, 255, 0))
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# Draw team logo (95% of display height, centered vertically)
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team_logo = self._get_team_logo(team['abbreviation'], league_config['logo_dir'])
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@@ -611,24 +828,24 @@ class LeaderboardManager:
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# Draw team abbreviation after the logo (centered vertically)
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team_text = team['abbreviation']
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text_bbox = self.fonts['medium'].getbbox(team_text)
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text_bbox = self.fonts['large'].getbbox(team_text)
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text_width = text_bbox[2] - text_bbox[0]
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text_height = text_bbox[3] - text_bbox[1]
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text_x = logo_x + logo_size + 4
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text_y = (height - text_height) // 2
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draw.text((text_x, text_y), team_text, font=self.fonts['medium'], fill=(255, 255, 255))
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draw.text((text_x, text_y), team_text, font=self.fonts['large'], fill=(255, 255, 255))
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# Calculate total width used by this team
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team_width = number_width + 4 + logo_size + 4 + text_width + 12 # 12px spacing to next team
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else:
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# Fallback if no logo - draw team abbreviation after bold number (centered vertically)
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team_text = team['abbreviation']
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text_bbox = self.fonts['medium'].getbbox(team_text)
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text_bbox = self.fonts['large'].getbbox(team_text)
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text_width = text_bbox[2] - text_bbox[0]
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text_height = text_bbox[3] - text_bbox[1]
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text_x = team_x + number_width + 4
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text_y = (height - text_height) // 2
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draw.text((text_x, text_y), team_text, font=self.fonts['medium'], fill=(255, 255, 255))
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draw.text((text_x, text_y), team_text, font=self.fonts['large'], fill=(255, 255, 255))
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# Calculate total width used by this team
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team_width = number_width + 4 + text_width + 12 # 12px spacing to next team
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@@ -640,37 +857,119 @@ class LeaderboardManager:
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current_x += teams_width + 20 # Teams width + spacing
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current_x += spacing # Add spacing between leagues
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# Calculate dynamic duration based on number of teams and content
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if self.dynamic_duration_enabled:
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# Count total teams across all leagues
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total_teams = sum(len(league_data['teams']) for league_data in self.leaderboard_data)
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total_leagues = len(self.leaderboard_data)
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# Use configurable time per team and league
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time_per_team = self.time_per_team
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time_per_league = self.time_per_league
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# Calculate base duration from teams and leagues
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base_duration = (total_teams * time_per_team) + (total_leagues * time_per_league)
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# Add scroll time based on content width
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scroll_time = (total_width / self.scroll_speed) * self.scroll_delay
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# Use the maximum of base duration and scroll time, with buffer
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calculated_duration = max(base_duration, scroll_time) + self.duration_buffer
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# Apply min/max constraints
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self.dynamic_duration = max(self.min_duration, min(self.max_duration, calculated_duration))
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logger.info(f"Calculated dynamic duration: {self.dynamic_duration:.1f}s for {total_teams} teams across {total_leagues} leagues (width: {total_width})")
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# Set total scroll width for dynamic duration calculation
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self.total_scroll_width = total_width
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# Calculate dynamic duration using proper scroll-based calculation
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if self.dynamic_duration_enabled:
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self.calculate_dynamic_duration()
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logger.info(f"Created leaderboard image with width {total_width}")
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except Exception as e:
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logger.error(f"Error creating leaderboard image: {e}")
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self.leaderboard_image = None
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def calculate_dynamic_duration(self):
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"""Calculate the exact time needed to display all leaderboard content"""
|
||||
logger.debug(f"calculate_dynamic_duration called - dynamic_duration_enabled: {self.dynamic_duration_enabled}, total_scroll_width: {self.total_scroll_width}")
|
||||
|
||||
# If dynamic duration is disabled, use fixed duration from config
|
||||
if not self.dynamic_duration_enabled:
|
||||
self.dynamic_duration = self.leaderboard_config.get('display_duration', 60)
|
||||
logger.debug(f"Dynamic duration disabled, using fixed duration: {self.dynamic_duration}s")
|
||||
return
|
||||
|
||||
if not self.total_scroll_width:
|
||||
self.dynamic_duration = self.min_duration # Use configured minimum
|
||||
logger.debug(f"total_scroll_width is 0, using minimum duration: {self.min_duration}s")
|
||||
return
|
||||
|
||||
try:
|
||||
# Get display width (assume full width of display)
|
||||
display_width = getattr(self.display_manager, 'matrix', None)
|
||||
if display_width:
|
||||
display_width = display_width.width
|
||||
else:
|
||||
display_width = 128 # Default to 128 if not available
|
||||
|
||||
# Calculate total scroll distance needed
|
||||
# For leaderboard, we need to scroll the entire content width plus display width
|
||||
# to ensure all content is visible from start to finish
|
||||
total_scroll_distance = display_width + self.total_scroll_width
|
||||
|
||||
# Calculate time based on scroll speed and delay
|
||||
# scroll_speed = pixels per frame, scroll_delay = seconds per frame
|
||||
frames_needed = total_scroll_distance / self.scroll_speed
|
||||
total_time = frames_needed * self.scroll_delay
|
||||
|
||||
# Add buffer time for smooth cycling (configurable %)
|
||||
buffer_time = total_time * self.duration_buffer
|
||||
|
||||
# If looping is enabled, ensure we complete at least one full cycle
|
||||
# and add extra time to ensure we don't cut off mid-scroll
|
||||
if self.loop:
|
||||
# Add extra buffer for looping to ensure smooth transition
|
||||
# Use a more reasonable buffer to prevent excessive looping
|
||||
loop_buffer = total_time * 0.15 # 15% extra for looping (reduced from 30%)
|
||||
calculated_duration = int(total_time + buffer_time + loop_buffer)
|
||||
logger.debug(f"Looping enabled, added {loop_buffer:.2f}s loop buffer")
|
||||
else:
|
||||
# Even without looping, add extra buffer to ensure complete display
|
||||
extra_buffer = total_time * 0.1 # 10% extra to ensure complete content display (reduced from 15%)
|
||||
calculated_duration = int(total_time + buffer_time + extra_buffer)
|
||||
logger.debug(f"No looping, added {extra_buffer:.2f}s extra buffer for complete display")
|
||||
|
||||
# Apply configured min/max limits
|
||||
if calculated_duration < self.min_duration:
|
||||
self.dynamic_duration = self.min_duration
|
||||
logger.debug(f"Duration capped to minimum: {self.min_duration}s")
|
||||
elif calculated_duration > self.max_duration:
|
||||
self.dynamic_duration = self.max_duration
|
||||
logger.debug(f"Duration capped to maximum: {self.max_duration}s")
|
||||
else:
|
||||
self.dynamic_duration = calculated_duration
|
||||
|
||||
# Additional safety check: if the calculated duration seems too short for the content,
|
||||
# ensure we have enough time to display all content properly
|
||||
if self.dynamic_duration < 30 and self.total_scroll_width > 800:
|
||||
# If we have a lot of content but short duration, increase it
|
||||
self.dynamic_duration = max(30, int(self.total_scroll_width / 30)) # At least 30s or 1s per 30px
|
||||
logger.debug(f"Adjusted duration for large content: {self.dynamic_duration}s")
|
||||
|
||||
logger.debug(f"Leaderboard dynamic duration calculation:")
|
||||
logger.debug(f" Display width: {display_width}px")
|
||||
logger.debug(f" Content width: {self.total_scroll_width}px")
|
||||
logger.debug(f" Total scroll distance: {total_scroll_distance}px")
|
||||
logger.debug(f" Scroll speed: {self.scroll_speed}px/frame")
|
||||
logger.debug(f" Scroll delay: {self.scroll_delay}s/frame")
|
||||
logger.debug(f" Frames needed: {frames_needed:.1f}")
|
||||
logger.debug(f" Base time: {total_time:.2f}s")
|
||||
logger.debug(f" Buffer time: {buffer_time:.2f}s ({self.duration_buffer*100}%)")
|
||||
logger.debug(f" Looping enabled: {self.loop}")
|
||||
logger.debug(f" Calculated duration: {calculated_duration}s")
|
||||
logger.debug(f" Final duration: {self.dynamic_duration}s")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error calculating dynamic duration: {e}")
|
||||
self.dynamic_duration = self.min_duration # Use configured minimum as fallback
|
||||
|
||||
def get_dynamic_duration(self) -> int:
|
||||
"""Get the calculated dynamic duration for display"""
|
||||
# If we don't have a valid dynamic duration yet (total_scroll_width is 0),
|
||||
# try to update the data first
|
||||
if self.total_scroll_width == 0 and self.is_enabled:
|
||||
logger.debug("get_dynamic_duration called but total_scroll_width is 0, attempting update...")
|
||||
try:
|
||||
# Force an update to get the data and calculate proper duration
|
||||
# Bypass the update interval check for duration calculation
|
||||
self.update()
|
||||
logger.debug(f"Force update completed, total_scroll_width: {self.total_scroll_width}px")
|
||||
except Exception as e:
|
||||
logger.error(f"Error updating leaderboard for dynamic duration: {e}")
|
||||
|
||||
logger.debug(f"get_dynamic_duration called, returning: {self.dynamic_duration}s")
|
||||
return self.dynamic_duration
|
||||
|
||||
def update(self) -> None:
|
||||
"""Update leaderboard data."""
|
||||
current_time = time.time()
|
||||
|
||||
@@ -1349,13 +1349,13 @@ class OddsTickerManager:
|
||||
# and add extra time to ensure we don't cut off mid-scroll
|
||||
if self.loop:
|
||||
# Add extra buffer for looping to ensure smooth transition
|
||||
# Use a larger buffer to ensure complete content display
|
||||
loop_buffer = total_time * 0.3 # 30% extra for looping (increased from 20%)
|
||||
# Use a more reasonable buffer to prevent excessive looping
|
||||
loop_buffer = total_time * 0.15 # 15% extra for looping (reduced from 30%)
|
||||
calculated_duration = int(total_time + buffer_time + loop_buffer)
|
||||
logger.debug(f"Looping enabled, added {loop_buffer:.2f}s loop buffer")
|
||||
else:
|
||||
# Even without looping, add extra buffer to ensure complete display
|
||||
extra_buffer = total_time * 0.15 # 15% extra to ensure complete content display
|
||||
extra_buffer = total_time * 0.1 # 10% extra to ensure complete content display (reduced from 15%)
|
||||
calculated_duration = int(total_time + buffer_time + extra_buffer)
|
||||
logger.debug(f"No looping, added {extra_buffer:.2f}s extra buffer for complete display")
|
||||
|
||||
@@ -1371,9 +1371,9 @@ class OddsTickerManager:
|
||||
|
||||
# Additional safety check: if the calculated duration seems too short for the content,
|
||||
# ensure we have enough time to display all content properly
|
||||
if self.dynamic_duration < 45 and self.total_scroll_width > 500:
|
||||
if self.dynamic_duration < 30 and self.total_scroll_width > 800:
|
||||
# If we have a lot of content but short duration, increase it
|
||||
self.dynamic_duration = max(45, int(self.total_scroll_width / 20)) # At least 45s or 1s per 20px
|
||||
self.dynamic_duration = max(30, int(self.total_scroll_width / 30)) # At least 30s or 1s per 30px
|
||||
logger.debug(f"Adjusted duration for large content: {self.dynamic_duration}s")
|
||||
|
||||
logger.debug(f"Odds ticker dynamic duration calculation:")
|
||||
|
||||
239
test/test_standings_fetch.py
Normal file
239
test/test_standings_fetch.py
Normal file
@@ -0,0 +1,239 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Test script to verify the standings fetching logic works correctly.
|
||||
This tests the core functionality without requiring the full LED matrix setup.
|
||||
"""
|
||||
|
||||
import requests
|
||||
import json
|
||||
import time
|
||||
from typing import Dict, Any, List
|
||||
|
||||
def fetch_standings_data(league_config: Dict[str, Any]) -> List[Dict[str, Any]]:
|
||||
"""Fetch standings data from ESPN API using the standings endpoint."""
|
||||
league_key = league_config['league']
|
||||
|
||||
try:
|
||||
print(f"Fetching fresh standings data for {league_key}")
|
||||
|
||||
# Build the standings URL with query parameters
|
||||
standings_url = league_config['standings_url']
|
||||
params = {
|
||||
'season': league_config.get('season', 2024),
|
||||
'level': league_config.get('level', 1),
|
||||
'sort': league_config.get('sort', 'winpercent:desc,gamesbehind:asc')
|
||||
}
|
||||
|
||||
print(f"Fetching standings from: {standings_url} with params: {params}")
|
||||
|
||||
response = requests.get(standings_url, params=params, timeout=30)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
|
||||
standings = []
|
||||
|
||||
# Parse the standings data structure
|
||||
# Check if we have direct standings data or children (divisions/conferences)
|
||||
if 'standings' in data and 'entries' in data['standings']:
|
||||
# Direct standings data (e.g., NFL overall standings)
|
||||
standings_data = data['standings']['entries']
|
||||
print(f"Processing direct standings data with {len(standings_data)} teams")
|
||||
|
||||
for entry in standings_data:
|
||||
team_data = entry.get('team', {})
|
||||
stats = entry.get('stats', [])
|
||||
|
||||
team_name = team_data.get('displayName', 'Unknown')
|
||||
team_abbr = team_data.get('abbreviation', 'Unknown')
|
||||
|
||||
# Extract record from stats
|
||||
wins = 0
|
||||
losses = 0
|
||||
ties = 0
|
||||
win_percentage = 0.0
|
||||
|
||||
for stat in stats:
|
||||
stat_type = stat.get('type', '')
|
||||
stat_value = stat.get('value', 0)
|
||||
|
||||
if stat_type == 'wins':
|
||||
wins = int(stat_value)
|
||||
elif stat_type == 'losses':
|
||||
losses = int(stat_value)
|
||||
elif stat_type == 'ties':
|
||||
ties = int(stat_value)
|
||||
elif stat_type == 'winpercent':
|
||||
win_percentage = float(stat_value)
|
||||
|
||||
# Create record summary
|
||||
if ties > 0:
|
||||
record_summary = f"{wins}-{losses}-{ties}"
|
||||
else:
|
||||
record_summary = f"{wins}-{losses}"
|
||||
|
||||
standings.append({
|
||||
'name': team_name,
|
||||
'abbreviation': team_abbr,
|
||||
'wins': wins,
|
||||
'losses': losses,
|
||||
'ties': ties,
|
||||
'win_percentage': win_percentage,
|
||||
'record_summary': record_summary,
|
||||
'division': 'Overall'
|
||||
})
|
||||
|
||||
elif 'children' in data:
|
||||
# Children structure (divisions/conferences)
|
||||
children = data.get('children', [])
|
||||
print(f"Processing {len(children)} divisions/conferences")
|
||||
|
||||
for child in children:
|
||||
child_name = child.get('displayName', 'Unknown')
|
||||
print(f"Processing {child_name}")
|
||||
|
||||
standings_data = child.get('standings', {}).get('entries', [])
|
||||
|
||||
for entry in standings_data:
|
||||
team_data = entry.get('team', {})
|
||||
stats = entry.get('stats', [])
|
||||
|
||||
team_name = team_data.get('displayName', 'Unknown')
|
||||
team_abbr = team_data.get('abbreviation', 'Unknown')
|
||||
|
||||
# Extract record from stats
|
||||
wins = 0
|
||||
losses = 0
|
||||
ties = 0
|
||||
win_percentage = 0.0
|
||||
|
||||
for stat in stats:
|
||||
stat_type = stat.get('type', '')
|
||||
stat_value = stat.get('value', 0)
|
||||
|
||||
if stat_type == 'wins':
|
||||
wins = int(stat_value)
|
||||
elif stat_type == 'losses':
|
||||
losses = int(stat_value)
|
||||
elif stat_type == 'ties':
|
||||
ties = int(stat_value)
|
||||
elif stat_type == 'winpercent':
|
||||
win_percentage = float(stat_value)
|
||||
|
||||
# Create record summary
|
||||
if ties > 0:
|
||||
record_summary = f"{wins}-{losses}-{ties}"
|
||||
else:
|
||||
record_summary = f"{wins}-{losses}"
|
||||
|
||||
standings.append({
|
||||
'name': team_name,
|
||||
'abbreviation': team_abbr,
|
||||
'wins': wins,
|
||||
'losses': losses,
|
||||
'ties': ties,
|
||||
'win_percentage': win_percentage,
|
||||
'record_summary': record_summary,
|
||||
'division': child_name
|
||||
})
|
||||
else:
|
||||
print(f"No standings or children data found for {league_key}")
|
||||
return []
|
||||
|
||||
# Sort by win percentage (descending) and limit to top teams
|
||||
standings.sort(key=lambda x: x['win_percentage'], reverse=True)
|
||||
top_teams = standings[:league_config['top_teams']]
|
||||
|
||||
print(f"Fetched and processed {len(top_teams)} teams for {league_key} standings")
|
||||
return top_teams
|
||||
|
||||
except Exception as e:
|
||||
print(f"Error fetching standings for {league_key}: {e}")
|
||||
return []
|
||||
|
||||
def test_standings_fetch():
|
||||
"""Test the standings fetching functionality."""
|
||||
print("Testing Standings Fetching Logic")
|
||||
print("=" * 50)
|
||||
|
||||
# Test configurations
|
||||
test_configs = [
|
||||
{
|
||||
'name': 'NFL',
|
||||
'config': {
|
||||
'league': 'nfl',
|
||||
'standings_url': 'https://site.api.espn.com/apis/v2/sports/football/nfl/standings',
|
||||
'top_teams': 5,
|
||||
'season': 2025,
|
||||
'level': 1,
|
||||
'sort': 'winpercent:desc,gamesbehind:asc'
|
||||
}
|
||||
},
|
||||
{
|
||||
'name': 'MLB',
|
||||
'config': {
|
||||
'league': 'mlb',
|
||||
'standings_url': 'https://site.api.espn.com/apis/v2/sports/baseball/mlb/standings',
|
||||
'top_teams': 5,
|
||||
'season': 2025,
|
||||
'level': 1,
|
||||
'sort': 'winpercent:desc,gamesbehind:asc'
|
||||
}
|
||||
},
|
||||
{
|
||||
'name': 'NHL',
|
||||
'config': {
|
||||
'league': 'nhl',
|
||||
'standings_url': 'https://site.api.espn.com/apis/v2/sports/hockey/nhl/standings',
|
||||
'top_teams': 5,
|
||||
'season': 2025,
|
||||
'level': 1,
|
||||
'sort': 'winpercent:desc,gamesbehind:asc'
|
||||
}
|
||||
},
|
||||
{
|
||||
'name': 'NCAA Baseball',
|
||||
'config': {
|
||||
'league': 'college-baseball',
|
||||
'standings_url': 'https://site.api.espn.com/apis/v2/sports/baseball/college-baseball/standings',
|
||||
'top_teams': 5,
|
||||
'season': 2025,
|
||||
'level': 1,
|
||||
'sort': 'winpercent:desc,gamesbehind:asc'
|
||||
}
|
||||
}
|
||||
]
|
||||
|
||||
results = []
|
||||
|
||||
for test_config in test_configs:
|
||||
print(f"\n--- Testing {test_config['name']} ---")
|
||||
|
||||
standings = fetch_standings_data(test_config['config'])
|
||||
|
||||
if standings:
|
||||
print(f"✓ Successfully fetched {len(standings)} teams")
|
||||
print(f"Top {len(standings)} teams:")
|
||||
for i, team in enumerate(standings):
|
||||
print(f" {i+1}. {team['name']} ({team['abbreviation']}): {team['record_summary']} ({team['win_percentage']:.3f})")
|
||||
results.append(True)
|
||||
else:
|
||||
print(f"✗ Failed to fetch standings for {test_config['name']}")
|
||||
results.append(False)
|
||||
|
||||
# Summary
|
||||
passed = sum(results)
|
||||
total = len(results)
|
||||
|
||||
print(f"\n=== Test Results ===")
|
||||
print(f"Passed: {passed}/{total}")
|
||||
|
||||
if passed == total:
|
||||
print("✓ All standings fetch tests passed!")
|
||||
return True
|
||||
else:
|
||||
print("✗ Some tests failed!")
|
||||
return False
|
||||
|
||||
if __name__ == "__main__":
|
||||
success = test_standings_fetch()
|
||||
exit(0 if success else 1)
|
||||
293
test/test_standings_simple.py
Normal file
293
test/test_standings_simple.py
Normal file
@@ -0,0 +1,293 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Simple test script to verify the ESPN standings endpoints work correctly.
|
||||
"""
|
||||
|
||||
import requests
|
||||
import json
|
||||
|
||||
def test_nfl_standings():
|
||||
"""Test NFL standings endpoint with corrected parsing."""
|
||||
print("\n=== Testing NFL Standings ===")
|
||||
|
||||
url = "https://site.api.espn.com/apis/v2/sports/football/nfl/standings"
|
||||
params = {
|
||||
'season': 2025,
|
||||
'level': 1,
|
||||
'sort': 'winpercent:desc,gamesbehind:asc'
|
||||
}
|
||||
|
||||
try:
|
||||
response = requests.get(url, params=params, timeout=30)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
|
||||
print(f"✓ Successfully fetched NFL standings")
|
||||
|
||||
# Check for direct standings data
|
||||
if 'standings' in data and 'entries' in data['standings']:
|
||||
standings_data = data['standings']['entries']
|
||||
print(f" Found {len(standings_data)} teams in direct standings")
|
||||
|
||||
# Show top 5 teams
|
||||
print(f" Top 5 teams:")
|
||||
for i, entry in enumerate(standings_data[:5]):
|
||||
team_data = entry.get('team', {})
|
||||
team_name = team_data.get('displayName', 'Unknown')
|
||||
team_abbr = team_data.get('abbreviation', 'Unknown')
|
||||
|
||||
# Get record
|
||||
wins = 0
|
||||
losses = 0
|
||||
ties = 0
|
||||
win_percentage = 0.0
|
||||
|
||||
for stat in entry.get('stats', []):
|
||||
stat_type = stat.get('type', '')
|
||||
stat_value = stat.get('value', 0)
|
||||
|
||||
if stat_type == 'wins':
|
||||
wins = int(stat_value)
|
||||
elif stat_type == 'losses':
|
||||
losses = int(stat_value)
|
||||
elif stat_type == 'ties':
|
||||
ties = int(stat_value)
|
||||
elif stat_type == 'winpercent':
|
||||
win_percentage = float(stat_value)
|
||||
|
||||
record = f"{wins}-{losses}" if ties == 0 else f"{wins}-{losses}-{ties}"
|
||||
print(f" {i+1}. {team_name} ({team_abbr}): {record} ({win_percentage:.3f})")
|
||||
|
||||
return True
|
||||
else:
|
||||
print(" ✗ No direct standings data found")
|
||||
return False
|
||||
|
||||
except Exception as e:
|
||||
print(f"✗ Error testing NFL standings: {e}")
|
||||
return False
|
||||
|
||||
def test_mlb_standings():
|
||||
"""Test MLB standings endpoint with corrected parsing."""
|
||||
print("\n=== Testing MLB Standings ===")
|
||||
|
||||
url = "https://site.api.espn.com/apis/v2/sports/baseball/mlb/standings"
|
||||
params = {
|
||||
'season': 2025,
|
||||
'level': 1,
|
||||
'sort': 'winpercent:desc,gamesbehind:asc'
|
||||
}
|
||||
|
||||
try:
|
||||
response = requests.get(url, params=params, timeout=30)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
|
||||
print(f"✓ Successfully fetched MLB standings")
|
||||
|
||||
# Check for direct standings data
|
||||
if 'standings' in data and 'entries' in data['standings']:
|
||||
standings_data = data['standings']['entries']
|
||||
print(f" Found {len(standings_data)} teams in direct standings")
|
||||
|
||||
# Show top 5 teams
|
||||
print(f" Top 5 teams:")
|
||||
for i, entry in enumerate(standings_data[:5]):
|
||||
team_data = entry.get('team', {})
|
||||
team_name = team_data.get('displayName', 'Unknown')
|
||||
team_abbr = team_data.get('abbreviation', 'Unknown')
|
||||
|
||||
# Get record
|
||||
wins = 0
|
||||
losses = 0
|
||||
ties = 0
|
||||
win_percentage = 0.0
|
||||
|
||||
for stat in entry.get('stats', []):
|
||||
stat_type = stat.get('type', '')
|
||||
stat_value = stat.get('value', 0)
|
||||
|
||||
if stat_type == 'wins':
|
||||
wins = int(stat_value)
|
||||
elif stat_type == 'losses':
|
||||
losses = int(stat_value)
|
||||
elif stat_type == 'ties':
|
||||
ties = int(stat_value)
|
||||
elif stat_type == 'winpercent':
|
||||
win_percentage = float(stat_value)
|
||||
|
||||
record = f"{wins}-{losses}" if ties == 0 else f"{wins}-{losses}-{ties}"
|
||||
print(f" {i+1}. {team_name} ({team_abbr}): {record} ({win_percentage:.3f})")
|
||||
|
||||
return True
|
||||
else:
|
||||
print(" ✗ No direct standings data found")
|
||||
return False
|
||||
|
||||
except Exception as e:
|
||||
print(f"✗ Error testing MLB standings: {e}")
|
||||
return False
|
||||
|
||||
def test_nhl_standings():
|
||||
"""Test NHL standings endpoint with corrected parsing."""
|
||||
print("\n=== Testing NHL Standings ===")
|
||||
|
||||
url = "https://site.api.espn.com/apis/v2/sports/hockey/nhl/standings"
|
||||
params = {
|
||||
'season': 2025,
|
||||
'level': 1,
|
||||
'sort': 'winpercent:desc,gamesbehind:asc'
|
||||
}
|
||||
|
||||
try:
|
||||
response = requests.get(url, params=params, timeout=30)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
|
||||
print(f"✓ Successfully fetched NHL standings")
|
||||
|
||||
# Check for direct standings data
|
||||
if 'standings' in data and 'entries' in data['standings']:
|
||||
standings_data = data['standings']['entries']
|
||||
print(f" Found {len(standings_data)} teams in direct standings")
|
||||
|
||||
# Show top 5 teams
|
||||
print(f" Top 5 teams:")
|
||||
for i, entry in enumerate(standings_data[:5]):
|
||||
team_data = entry.get('team', {})
|
||||
team_name = team_data.get('displayName', 'Unknown')
|
||||
team_abbr = team_data.get('abbreviation', 'Unknown')
|
||||
|
||||
# Get record with NHL-specific parsing
|
||||
wins = 0
|
||||
losses = 0
|
||||
ties = 0
|
||||
win_percentage = 0.0
|
||||
games_played = 0
|
||||
|
||||
# First pass: collect all stat values
|
||||
for stat in entry.get('stats', []):
|
||||
stat_type = stat.get('type', '')
|
||||
stat_value = stat.get('value', 0)
|
||||
|
||||
if stat_type == 'wins':
|
||||
wins = int(stat_value)
|
||||
elif stat_type == 'losses':
|
||||
losses = int(stat_value)
|
||||
elif stat_type == 'ties':
|
||||
ties = int(stat_value)
|
||||
elif stat_type == 'winpercent':
|
||||
win_percentage = float(stat_value)
|
||||
# NHL specific stats
|
||||
elif stat_type == 'overtimelosses':
|
||||
ties = int(stat_value) # NHL uses overtime losses as ties
|
||||
elif stat_type == 'gamesplayed':
|
||||
games_played = float(stat_value)
|
||||
|
||||
# Second pass: calculate win percentage for NHL if not already set
|
||||
if win_percentage == 0.0 and games_played > 0:
|
||||
win_percentage = wins / games_played
|
||||
|
||||
record = f"{wins}-{losses}" if ties == 0 else f"{wins}-{losses}-{ties}"
|
||||
print(f" {i+1}. {team_name} ({team_abbr}): {record} ({win_percentage:.3f})")
|
||||
|
||||
return True
|
||||
else:
|
||||
print(" ✗ No direct standings data found")
|
||||
return False
|
||||
|
||||
except Exception as e:
|
||||
print(f"✗ Error testing NHL standings: {e}")
|
||||
return False
|
||||
|
||||
def test_ncaa_baseball_standings():
|
||||
"""Test NCAA Baseball standings endpoint with corrected parsing."""
|
||||
print("\n=== Testing NCAA Baseball Standings ===")
|
||||
|
||||
url = "https://site.api.espn.com/apis/v2/sports/baseball/college-baseball/standings"
|
||||
params = {
|
||||
'season': 2025,
|
||||
'level': 1,
|
||||
'sort': 'winpercent:desc,gamesbehind:asc'
|
||||
}
|
||||
|
||||
try:
|
||||
response = requests.get(url, params=params, timeout=30)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
|
||||
print(f"✓ Successfully fetched NCAA Baseball standings")
|
||||
|
||||
# Check for direct standings data
|
||||
if 'standings' in data and 'entries' in data['standings']:
|
||||
standings_data = data['standings']['entries']
|
||||
print(f" Found {len(standings_data)} teams in direct standings")
|
||||
|
||||
# Show top 5 teams
|
||||
print(f" Top 5 teams:")
|
||||
for i, entry in enumerate(standings_data[:5]):
|
||||
team_data = entry.get('team', {})
|
||||
team_name = team_data.get('displayName', 'Unknown')
|
||||
team_abbr = team_data.get('abbreviation', 'Unknown')
|
||||
|
||||
# Get record
|
||||
wins = 0
|
||||
losses = 0
|
||||
ties = 0
|
||||
win_percentage = 0.0
|
||||
|
||||
for stat in entry.get('stats', []):
|
||||
stat_type = stat.get('type', '')
|
||||
stat_value = stat.get('value', 0)
|
||||
|
||||
if stat_type == 'wins':
|
||||
wins = int(stat_value)
|
||||
elif stat_type == 'losses':
|
||||
losses = int(stat_value)
|
||||
elif stat_type == 'ties':
|
||||
ties = int(stat_value)
|
||||
elif stat_type == 'winpercent':
|
||||
win_percentage = float(stat_value)
|
||||
|
||||
record = f"{wins}-{losses}" if ties == 0 else f"{wins}-{losses}-{ties}"
|
||||
print(f" {i+1}. {team_name} ({team_abbr}): {record} ({win_percentage:.3f})")
|
||||
|
||||
return True
|
||||
else:
|
||||
print(" ✗ No direct standings data found")
|
||||
return False
|
||||
|
||||
except Exception as e:
|
||||
print(f"✗ Error testing NCAA Baseball standings: {e}")
|
||||
return False
|
||||
|
||||
def main():
|
||||
"""Main function to run all tests."""
|
||||
print("ESPN Standings Endpoints Test (Corrected)")
|
||||
print("=" * 50)
|
||||
|
||||
results = []
|
||||
|
||||
# Test individual endpoints
|
||||
results.append(test_nfl_standings())
|
||||
results.append(test_mlb_standings())
|
||||
results.append(test_nhl_standings())
|
||||
results.append(test_ncaa_baseball_standings())
|
||||
|
||||
# Summary
|
||||
passed = sum(results)
|
||||
total = len(results)
|
||||
|
||||
print(f"\n=== Test Results ===")
|
||||
print(f"Passed: {passed}/{total}")
|
||||
|
||||
if passed == total:
|
||||
print("✓ All tests passed!")
|
||||
return True
|
||||
else:
|
||||
print("✗ Some tests failed!")
|
||||
return False
|
||||
|
||||
if __name__ == "__main__":
|
||||
success = main()
|
||||
exit(0 if success else 1)
|
||||
Reference in New Issue
Block a user