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Deploy Iddaai Backend / build-and-deploy (push) Failing after 18s

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"""
XGBoost Training Data Extraction (Advanced Basketball V21)
============================================================
Batch feature extraction for top-league basketball matches.
Extracts 60+ features per match including deep team stats (FG%, Rebounds, Qrt pacing).
Usage:
python3 scripts/extract_advanced_basketball_data.py
"""
import os
import sys
import json
import csv
import math
import time
from datetime import datetime
from collections import defaultdict
import psycopg2
from psycopg2.extras import RealDictCursor
from dotenv import load_dotenv
load_dotenv()
# =============================================================================
# CONFIG
# =============================================================================
AI_ENGINE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.insert(0, AI_ENGINE_DIR)
TOP_LEAGUES_PATH = os.path.join(AI_ENGINE_DIR, "..", "basketball_top_leagues.json")
OUTPUT_CSV = os.path.join(AI_ENGINE_DIR, "data", "advanced_basketball_training_data.csv")
os.makedirs(os.path.dirname(OUTPUT_CSV), exist_ok=True)
def get_conn():
db_url = os.getenv("DATABASE_URL", "").split("?schema=")[0]
return psycopg2.connect(db_url)
# =============================================================================
# FEATURE COLUMNS (ORDER MATTERS)
# =============================================================================
FEATURE_COLS = [
"match_id", "home_team_id", "away_team_id", "league_id", "mst_utc",
# Form & Winning
"home_winning_streak", "away_winning_streak",
"home_win_rate", "away_win_rate",
# Home Team Offense (Averages of last 5)
"home_pts_avg", "home_reb_avg", "home_ast_avg", "home_stl_avg", "home_blk_avg", "home_tov_avg",
"home_fg_pct", "home_3pt_pct", "home_ft_pct",
"home_q1_avg", "home_q2_avg", "home_q3_avg", "home_q4_avg",
# Home Team Defense (Averages of opponent stats in last 5)
"home_conc_pts", "home_conc_reb", "home_conc_ast", "home_conc_tov",
"home_conc_fg_pct", "home_conc_3pt_pct",
# Away Team Offense (Averages of last 5)
"away_pts_avg", "away_reb_avg", "away_ast_avg", "away_stl_avg", "away_blk_avg", "away_tov_avg",
"away_fg_pct", "away_3pt_pct", "away_ft_pct",
"away_q1_avg", "away_q2_avg", "away_q3_avg", "away_q4_avg",
# Away Team Defense (Averages of opponent stats in last 5)
"away_conc_pts", "away_conc_reb", "away_conc_ast", "away_conc_tov",
"away_conc_fg_pct", "away_conc_3pt_pct",
# H2H Features
"h2h_total_matches", "h2h_home_win_rate",
"h2h_avg_points", "h2h_over140_rate",
# Odds Features
"odds_ml_h", "odds_ml_a",
"odds_tot_o", "odds_tot_u", "odds_tot_line",
"odds_spread_h", "odds_spread_a", "odds_spread_line",
# Labels
"score_home", "score_away", "total_points",
"label_ml", # 0=Home, 1=Away
"label_tot", # 0=Under, 1=Over (dynamic line)
"label_spread", # 0=Away Cover, 1=Home Cover (dynamic line)
]
# =============================================================================
# BATCH LOADERS
# =============================================================================
class AdvancedDataLoader:
def __init__(self, conn, top_league_ids: list):
self.conn = conn
self.cur = conn.cursor(cursor_factory=RealDictCursor)
self.top_league_ids = top_league_ids
self.matches = []
self.odds_cache = {}
self.team_stats_cache = {} # (match_id, team_id) -> stats dict
self.form_cache = {}
self.h2h_cache = {}
def load_all(self):
t0 = time.time()
self._load_matches()
print(f" ✅ Matches: {len(self.matches)} ({time.time()-t0:.1f}s)", flush=True)
t1 = time.time()
self._load_team_stats()
print(f" ✅ Team Stats: {len(self.team_stats_cache)} records ({time.time()-t1:.1f}s)", flush=True)
t2 = time.time()
self._load_odds()
print(f" ✅ Odds: {len(self.odds_cache)} matches ({time.time()-t2:.1f}s)", flush=True)
t3 = time.time()
self._build_advanced_history()
print(f" ✅ Advanced History & Stats cache built ({time.time()-t3:.1f}s)", flush=True)
print(f" 📊 Total load time: {time.time()-t0:.1f}s", flush=True)
def _load_matches(self):
query = """
SELECT
id, mst_utc, league_id, home_team_id, away_team_id,
score_home, score_away
FROM matches
WHERE sport = 'basketball'
AND status = 'FT'
AND score_home IS NOT NULL
AND score_away IS NOT NULL
AND mst_utc > 1640995200000
"""
if self.top_league_ids:
format_strings = ",".join(["%s"] * len(self.top_league_ids))
query += f" AND league_id IN ({format_strings})"
self.cur.execute(query + " ORDER BY mst_utc ASC", tuple(self.top_league_ids))
else:
self.cur.execute(query + " ORDER BY mst_utc ASC")
self.matches = self.cur.fetchall()
def _load_team_stats(self):
query = """
SELECT
match_id, team_id,
points, rebounds, assists, steals, blocks, turnovers,
fg_made, fg_attempted,
three_pt_made, three_pt_attempted,
ft_made, ft_attempted,
q1_score, q2_score, q3_score, q4_score
FROM basketball_team_stats
WHERE match_id IN (
SELECT id FROM matches WHERE sport = 'basketball' AND status = 'FT'
)
"""
self.cur.execute(query)
rows = self.cur.fetchall()
for r in rows:
self.team_stats_cache[(str(r['match_id']), str(r['team_id']))] = r
def _load_odds(self):
# Using exact same odds parser as original script
query = """
SELECT match_id, name as category_name, db_id as category_id
FROM odd_categories
WHERE match_id IN (
SELECT id FROM matches WHERE sport = 'basketball' AND status = 'FT'
)
"""
self.cur.execute(query)
cats = self.cur.fetchall()
cat_to_match = {c['category_id']: c['match_id'] for c in cats}
cat_ids = tuple(cat_to_match.keys())
if not cat_ids: return
cat_id_to_name = {c['category_id']: c['category_name'] for c in cats}
chunk_size = 50000
cats_list = list(cat_ids)
total_chunks = len(cats_list) // chunk_size + 1
for idx, i in enumerate(range(0, len(cats_list), chunk_size)):
chunk = tuple(cats_list[i:i+chunk_size])
self.cur.execute("SELECT odd_category_db_id, name, odd_value FROM odd_selections WHERE odd_category_db_id IN %s", (chunk,))
rows = self.cur.fetchall()
for row in rows:
c_id = row['odd_category_db_id']
m_id = str(cat_to_match[c_id])
c_name = cat_id_to_name.get(c_id, "")
if m_id not in self.odds_cache:
self.odds_cache[m_id] = {}
self._parse_single_odd(m_id, c_name, str(row['name']), float(row['odd_value']))
def _parse_single_odd(self, match_id, category_name, sel_name, odd_value):
if odd_value <= 1.0: return
cat_lower = category_name.lower()
sel_lower = sel_name.lower()
target = self.odds_cache[match_id]
# ML
if cat_lower in ("maç sonucu (uzt. dahil)", "mac sonucu (uzt. dahil)", "maç sonucu", "mac sonucu"):
if sel_lower == "1": target["ml_h"] = odd_value
elif sel_lower == "2": target["ml_a"] = odd_value
# Totals
if "alt/üst" in cat_lower or "alt/ust" in cat_lower:
line = None
try:
left = cat_lower.find("(")
right = cat_lower.find(")", left + 1)
if left > -1 and right > -1:
line = float(cat_lower[left+1:right].replace(",", "."))
except: pass
if line and "tot_line" not in target: target["tot_line"] = line
if "üst" in sel_lower or "ust" in sel_lower or "over" in sel_lower:
target.setdefault("tot_o", odd_value)
elif "alt" in sel_lower or "under" in sel_lower:
target.setdefault("tot_u", odd_value)
# Spread
if "hnd. ms" in cat_lower or "hand. ms" in cat_lower or "hnd ms" in cat_lower:
line = None
try:
left = cat_lower.find("(")
right = cat_lower.find(")", left + 1)
if left > -1 and right > -1:
payload = cat_lower[left+1:right].replace(",", ".")
if ":" in payload:
home_hcp = float(payload.split(":")[0])
away_hcp = float(payload.split(":")[1])
if abs(home_hcp) < 1e-6 and away_hcp > 0: line = -away_hcp
elif home_hcp > 0 and abs(away_hcp) < 1e-6: line = home_hcp
elif abs(home_hcp - away_hcp) < 1e-6 and home_hcp > 0: line = 0.0
except: pass
if line is not None and "spread_line" not in target:
target["spread_line"] = line
if sel_lower == "1": target.setdefault("spread_h", odd_value)
elif sel_lower == "2": target.setdefault("spread_a", odd_value)
def _build_advanced_history(self):
team_matches = defaultdict(list)
for m in self.matches:
mid = str(m['id'])
hid = str(m['home_team_id'])
aid = str(m['away_team_id'])
# Fetch stats from cache
h_stat = self.team_stats_cache.get((mid, hid))
a_stat = self.team_stats_cache.get((mid, aid))
if h_stat and a_stat:
m_data = {
"utc": int(m['mst_utc']),
"mid": mid,
}
# For Home Team History (it stores what THEY did, and what Opp did)
team_matches[hid].append({
"utc": int(m['mst_utc']),
"scored": m['score_home'], "conceded": m['score_away'],
"offense": h_stat, "defense": a_stat
})
# For Away Team History
team_matches[aid].append({
"utc": int(m['mst_utc']),
"scored": m['score_away'], "conceded": m['score_home'],
"offense": a_stat, "defense": h_stat
})
else:
# If advanced stats are missing, we still push the scores to maintain streak tracking
team_matches[hid].append({
"utc": int(m['mst_utc']),
"scored": m['score_home'], "conceded": m['score_away'],
"offense": None, "defense": None
})
team_matches[aid].append({
"utc": int(m['mst_utc']),
"scored": m['score_away'], "conceded": m['score_home'],
"offense": None, "defense": None
})
for team_id, hist in team_matches.items():
hist.sort(key=lambda x: x["utc"])
for i, match_info in enumerate(hist):
mst_utc = match_info["utc"]
past = [x for x in hist[:i] if x["utc"] < mst_utc]
if not past:
self.form_cache[(team_id, mst_utc)] = self._empty_form()
continue
last_5 = past[-5:]
wins = sum(1 for x in past if x["scored"] > x["conceded"])
win_rate = wins / len(past) if len(past) > 0 else 0.5
streak = 0
for x in reversed(past):
if x["scored"] > x["conceded"]: streak += 1
else: break
# Averages
off_pts, off_reb, off_ast, off_stl, off_blk, off_tov = 0,0,0,0,0,0
off_fg_m, off_fg_a, off_3pt_m, off_3pt_a, off_ft_m, off_ft_a = 0,0,0,0,0,0
off_q1, off_q2, off_q3, off_q4 = 0,0,0,0
def_pts, def_reb, def_ast, def_tov = 0,0,0,0
def_fg_m, def_fg_a, def_3pt_m, def_3pt_a = 0,0,0,0
valid_stats_count = sum(1 for x in last_5 if x["offense"] is not None)
if valid_stats_count > 0:
for x in last_5:
o = x["offense"]
d = x["defense"]
if o and d:
off_pts += (o["points"] or 0)
off_reb += (o["rebounds"] or 0)
off_ast += (o["assists"] or 0)
off_stl += (o["steals"] or 0)
off_blk += (o["blocks"] or 0)
off_tov += (o["turnovers"] or 0)
off_fg_m += (o["fg_made"] or 0)
off_fg_a += (o["fg_attempted"] or 0)
off_3pt_m += (o["three_pt_made"] or 0)
off_3pt_a += (o["three_pt_attempted"] or 0)
off_ft_m += (o["ft_made"] or 0)
off_ft_a += (o["ft_attempted"] or 0)
off_q1 += (o["q1_score"] or 0)
off_q2 += (o["q2_score"] or 0)
off_q3 += (o["q3_score"] or 0)
off_q4 += (o["q4_score"] or 0)
def_pts += (d["points"] or 0) # Conceded points based on opponents "offense" data
def_reb += (d["rebounds"] or 0)
def_ast += (d["assists"] or 0)
def_tov += (d["turnovers"] or 0)
def_fg_m += (d["fg_made"] or 0)
def_fg_a += (d["fg_attempted"] or 0)
def_3pt_m += (d["three_pt_made"] or 0)
def_3pt_a += (d["three_pt_attempted"] or 0)
avg_c = float(valid_stats_count)
self.form_cache[(team_id, mst_utc)] = {
"winning_streak": streak, "win_rate": win_rate,
"pts_avg": off_pts/avg_c, "reb_avg": off_reb/avg_c,
"ast_avg": off_ast/avg_c, "stl_avg": off_stl/avg_c,
"blk_avg": off_blk/avg_c, "tov_avg": off_tov/avg_c,
"fg_pct": (off_fg_m / off_fg_a) if off_fg_a > 0 else 0.45,
"3pt_pct": (off_3pt_m / off_3pt_a) if off_3pt_a > 0 else 0.35,
"ft_pct": (off_ft_m / off_ft_a) if off_ft_a > 0 else 0.75,
"q1_avg": off_q1/avg_c, "q2_avg": off_q2/avg_c,
"q3_avg": off_q3/avg_c, "q4_avg": off_q4/avg_c,
"conc_pts": def_pts/avg_c, "conc_reb": def_reb/avg_c,
"conc_ast": def_ast/avg_c, "conc_tov": def_tov/avg_c,
"conc_fg_pct": (def_fg_m / def_fg_a) if def_fg_a > 0 else 0.45,
"conc_3pt_pct": (def_3pt_m / def_3pt_a) if def_3pt_a > 0 else 0.35,
}
else:
self.form_cache[(team_id, mst_utc)] = self._empty_form()
self.form_cache[(team_id, mst_utc)]["winning_streak"] = streak
self.form_cache[(team_id, mst_utc)]["win_rate"] = win_rate
# Build H2H similarly
h2h_map = defaultdict(list)
for m in self.matches:
directional_pair = (str(m['home_team_id']), str(m['away_team_id']))
h2h_map[directional_pair].append((m['mst_utc'], m['score_home'], m['score_away']))
for (h_id, a_id), hist in h2h_map.items():
hist.sort(key=lambda x: x[0])
for i, (mst_utc, sh, sa) in enumerate(hist):
past = [x for x in hist[:i] if x[0] < mst_utc]
if not past:
self.h2h_cache[(h_id, a_id, mst_utc)] = {
"total": 0, "home_win_rate": 0.5,
"avg_points": 160.0, "over140_rate": 0.5
}
else:
home_wins = sum(1 for x in past if x[1] > x[2])
total_pts = sum(x[1] + x[2] for x in past)
over140 = sum(1 for x in past if x[1] + x[2] > 140)
self.h2h_cache[(h_id, a_id, mst_utc)] = {
"total": len(past), "home_win_rate": home_wins / len(past),
"avg_points": total_pts / len(past), "over140_rate": over140 / len(past)
}
def _empty_form(self):
return {
"winning_streak": 0, "win_rate": 0.5,
"pts_avg": 80.0, "reb_avg": 35.0, "ast_avg": 20.0,
"stl_avg": 7.0, "blk_avg": 3.0, "tov_avg": 13.0,
"fg_pct": 0.45, "3pt_pct": 0.35, "ft_pct": 0.75,
"q1_avg": 20.0, "q2_avg": 20.0, "q3_avg": 20.0, "q4_avg": 20.0,
"conc_pts": 80.0, "conc_reb": 35.0, "conc_ast": 20.0, "conc_tov": 13.0,
"conc_fg_pct": 0.45, "conc_3pt_pct": 0.35,
}
# =============================================================================
# FEATURE EXTRACTION PIPELINE
# =============================================================================
def process_matches(loader: AdvancedDataLoader):
f = open(OUTPUT_CSV, "w", newline='')
writer = csv.writer(f)
writer.writerow(FEATURE_COLS)
extracted_count = 0
missing_odds_count = 0
for match in loader.matches:
mid = str(match['id'])
mst = int(match['mst_utc'])
hid = str(match['home_team_id'])
aid = str(match['away_team_id'])
s_home = int(match['score_home'])
s_away = int(match['score_away'])
total_pts = s_home + s_away
c_odds = loader.odds_cache.get(mid, {})
c_form_h = loader.form_cache.get((hid, mst), {})
c_form_a = loader.form_cache.get((aid, mst), {})
c_h2h = loader.h2h_cache.get((hid, aid, mst), {})
if "ml_h" not in c_odds or "ml_a" not in c_odds:
missing_odds_count += 1
continue
label_ml = 0 if s_home > s_away else 1
line_tot = c_odds.get("tot_line", 160.0)
label_tot = 1 if total_pts > line_tot else 0
line_spread = c_odds.get("spread_line", 0.0)
hc_score = float(s_home) + float(line_spread)
label_spread = 1 if hc_score > float(s_away) else 0
row = [
mid, hid, aid, match.get('league_id', ''), mst,
c_form_h.get("winning_streak", 0), c_form_a.get("winning_streak", 0),
c_form_h.get("win_rate", 0), c_form_a.get("win_rate", 0),
# Home Offense
c_form_h.get("pts_avg", 80), c_form_h.get("reb_avg", 35), c_form_h.get("ast_avg", 20),
c_form_h.get("stl_avg", 7), c_form_h.get("blk_avg", 3), c_form_h.get("tov_avg", 13),
c_form_h.get("fg_pct", 0.45), c_form_h.get("3pt_pct", 0.35), c_form_h.get("ft_pct", 0.75),
c_form_h.get("q1_avg", 20), c_form_h.get("q2_avg", 20), c_form_h.get("q3_avg", 20), c_form_h.get("q4_avg", 20),
# Home Defense
c_form_h.get("conc_pts", 80), c_form_h.get("conc_reb", 35), c_form_h.get("conc_ast", 20), c_form_h.get("conc_tov", 13),
c_form_h.get("conc_fg_pct", 0.45), c_form_h.get("conc_3pt_pct", 0.35),
# Away Offense
c_form_a.get("pts_avg", 80), c_form_a.get("reb_avg", 35), c_form_a.get("ast_avg", 20),
c_form_a.get("stl_avg", 7), c_form_a.get("blk_avg", 3), c_form_a.get("tov_avg", 13),
c_form_a.get("fg_pct", 0.45), c_form_a.get("3pt_pct", 0.35), c_form_a.get("ft_pct", 0.75),
c_form_a.get("q1_avg", 20), c_form_a.get("q2_avg", 20), c_form_a.get("q3_avg", 20), c_form_a.get("q4_avg", 20),
# Away Defense
c_form_a.get("conc_pts", 80), c_form_a.get("conc_reb", 35), c_form_a.get("conc_ast", 20), c_form_a.get("conc_tov", 13),
c_form_a.get("conc_fg_pct", 0.45), c_form_a.get("conc_3pt_pct", 0.35),
c_h2h.get("total", 0), c_h2h.get("home_win_rate", 0.5),
c_h2h.get("avg_points", 160.0), c_h2h.get("over140_rate", 0.5),
c_odds.get("ml_h", 1.9), c_odds.get("ml_a", 1.9),
c_odds.get("tot_o", 1.9), c_odds.get("tot_u", 1.9), line_tot,
c_odds.get("spread_h", 1.9), c_odds.get("spread_a", 1.9), line_spread,
s_home, s_away, total_pts,
label_ml, label_tot, label_spread,
]
if len(row) != len(FEATURE_COLS):
print(f"Error: Row length mismatch {len(row)} != {len(FEATURE_COLS)}")
sys.exit(1)
writer.writerow(row)
extracted_count += 1
f.close()
print("\nExtraction Summary")
print("=========================")
print(f"Total Matches in Scope: {len(loader.matches)}")
print(f"Filtered (Missing ML Odds): {missing_odds_count}")
print(f"✅ Successfully Extracted: {extracted_count}")
print(f"📂 Saved to: {OUTPUT_CSV}")
if __name__ == "__main__":
t_start = time.time()
if not os.path.exists(TOP_LEAGUES_PATH):
print(f"Error: file not found {TOP_LEAGUES_PATH}")
sys.exit(1)
with open(TOP_LEAGUES_PATH, "r") as f:
top_leagues = json.load(f)
print(f"🏀 Extracting Advanced Basketball Training Data (V21)")
print(f"=====================================================")
print(f"Loaded {len(top_leagues)} top leagues.")
conn = get_conn()
loader = AdvancedDataLoader(conn, top_leagues)
loader.load_all()
process_matches(loader)
conn.close()
print(f"Total Script Run Time: {time.time()-t_start:.1f}s")