62 lines
1.8 KiB
Python
62 lines
1.8 KiB
Python
#!/usr/bin/env python3
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"""Check finished football matches with odds"""
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import sys
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sys.path.insert(0, 'ai-engine')
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import psycopg2
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from psycopg2.extras import RealDictCursor
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from datetime import datetime, timezone
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# Read .env file manually
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db_url = None
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with open('.env') as f:
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for line in f:
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if line.startswith('DATABASE_URL'):
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db_url = line.split('=', 1)[1].strip().strip('"').strip("'")
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break
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if '?schema=' in db_url:
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db_url = db_url.split('?schema=')[0]
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conn = psycopg2.connect(db_url)
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cur = conn.cursor(cursor_factory=RealDictCursor)
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# Get matches with odds data
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cur.execute('''
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SELECT
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m.id, m.score_home, m.score_away, m.ht_score_home, m.ht_score_away,
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m.mst_utc,
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ht.name as home_team_name,
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at.name as away_team_name,
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l.name as league_name,
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o.ms_h, o.ms_d, o.ms_a
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FROM matches m
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JOIN teams ht ON ht.id = m.home_team_id
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JOIN teams at ON at.id = m.away_team_id
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JOIN leagues l ON l.id = m.league_id
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LEFT JOIN odds o ON o.match_id = m.id
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WHERE l.sport = 'football'
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AND m.score_home IS NOT NULL
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AND o.ms_h IS NOT NULL
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ORDER BY m.mst_utc DESC
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LIMIT 30
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''')
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matches = cur.fetchall()
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print('Last 30 finished football matches with odds:')
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print()
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for m in matches:
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ts = m['mst_utc'] / 1000
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dt = datetime.fromtimestamp(ts, tz=timezone.utc)
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score = 'HT: {}-{}, FT: {}-{}'.format(m['ht_score_home'], m['ht_score_away'], m['score_home'], m['score_away'])
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odds = 'Odds: H={:.2f} D={:.2f} A={:.2f}'.format(float(m['ms_h'] or 0), float(m['ms_d'] or 0), float(m['ms_a'] or 0))
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league = (m['league_name'] or 'Unknown')[:15]
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home = (m['home_team_name'] or 'Unknown')[:15]
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away = (m['away_team_name'] or 'Unknown')[:15]
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print('{} | {:15} | {:15} vs {:15} | {} | {}'.format(dt.strftime('%Y-%m-%d %H:%M'), league, home, away, score, odds))
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cur.close()
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conn.close()
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