3pmonitor/analyze.py

#!/usr/bin/env python3
"""
Standalone CLI script for Teen Patti pattern analysis.

Usage:
    python analyze.py --host localhost --port 8123
"""

import argparse
import sys


def fmt_pct(n, total):
    return f"{n/total*100:.1f}%" if total else "0.0%"


def print_table(headers, rows, col_widths=None):
    """Print a simple formatted table."""
    if not col_widths:
        col_widths = [max(len(str(h)), *(len(str(r[i])) for r in rows))
                      for i, h in enumerate(headers)]
    # Header
    hdr = "  ".join(str(h).ljust(w) for h, w in zip(headers, col_widths))
    print(hdr)
    print("-" * len(hdr))
    for row in rows:
        print("  ".join(str(c).ljust(w) for c, w in zip(row, col_widths)))


def main():
    parser = argparse.ArgumentParser(description="Teen Patti Pattern Analysis CLI")
    parser.add_argument("--host", default="localhost", help="ClickHouse host")
    parser.add_argument("--port", type=int, default=8123, help="ClickHouse HTTP port")
    args = parser.parse_args()

    # Set config before importing db
    from app import config
    config.CLICKHOUSE_HOST = args.host
    config.CLICKHOUSE_PORT = args.port

    from app import db

    print(f"Connecting to ClickHouse at {args.host}:{args.port}...")
    try:
        data = db.get_pattern_analysis()
    except Exception as e:
        print(f"Error: {e}", file=sys.stderr)
        sys.exit(1)

    total = data["chair_bias"]["total_games"]
    print(f"\n{'='*60}")
    print(f"  TEEN PATTI PATTERN ANALYSIS  ({total:,} games)")
    print(f"{'='*60}\n")

    # 1. Chair Win Bias
    print("1. CHAIR WIN BIAS (expected 33.3%)")
    cb = data["chair_bias"]
    rows = []
    for ch in ("A", "B", "C"):
        d = cb[ch]
        diff = d["pct"] - 33.3
        sign = "+" if diff >= 0 else ""
        rows.append([ch, f"{d['wins']:,}", f"{d['pct']:.1f}%", f"{sign}{diff:.1f}%"])
    print_table(["Chair", "Wins", "Win %", "vs Expected"], rows)

    # 2. Bet Rank Analysis
    print("\n2. BET RANK ANALYSIS")
    br = data["bet_rank"]
    br_total = br["high"] + br["mid"] + br["low"]
    rows = []
    for rank in ("high", "mid", "low"):
        rows.append([rank.capitalize(), f"{br[rank]:,}", fmt_pct(br[rank], br_total)])
    print_table(["Rank", "Wins", "Win %"], rows)

    # 3. Per-Chair Bet Rank
    print("\n3. PER-CHAIR: HIGHEST BET WIN RATE")
    print("   When chair X has the highest bet, how often does X win?")
    pcr = data["per_chair_rank"]
    rows = []
    for ch in ("A", "B", "C"):
        d = pcr.get(ch, {})
        rows.append([ch, f"{d.get('has_highest', 0):,}",
                      f"{d.get('wins', 0):,}", f"{d.get('win_pct', 0):.1f}%"])
    print_table(["Chair", "Times Highest", "Wins", "Win %"], rows)

    # 4. Hand Type Distribution by Chair
    print("\n4. HAND TYPE DISTRIBUTION BY CHAIR")
    htbc = data["hand_types_by_chair"]
    hand_order = ["Trail", "Straight Flush", "Straight", "Flush", "Pair", "High Card"]
    rows = []
    for ht in hand_order:
        a = htbc["A"].get(ht, 0)
        b = htbc["B"].get(ht, 0)
        c = htbc["C"].get(ht, 0)
        if a + b + c == 0:
            continue
        rows.append([ht, f"{a:,}", f"{b:,}", f"{c:,}"])
    print_table(["Hand Type", "Chair A", "Chair B", "Chair C"], rows)

    # 5. Hand Type Win Rates
    print("\n5. HAND TYPE WIN RATES")
    htw = data["hand_type_wins"]
    htw_total = sum(htw.values())
    rows = []
    for ht in hand_order:
        v = htw.get(ht, 0)
        if v == 0:
            continue
        rows.append([ht, f"{v:,}", fmt_pct(v, htw_total)])
    print_table(["Hand Type", "Wins", "Win %"], rows)

    # 6. Pot Size Buckets
    print("\n6. WIN RATES BY POT SIZE")
    pb = data["pot_buckets"]
    ranges = pb.get("_ranges", {})
    rows = []
    for bucket in ("small", "medium", "large", "whale"):
        d = pb.get(bucket)
        if not d:
            continue
        t = d["total"] or 1
        rows.append([
            bucket.capitalize(), ranges.get(bucket, ""),
            f"{d['total']:,}",
            f"{d['A']/t*100:.1f}%", f"{d['B']/t*100:.1f}%", f"{d['C']/t*100:.1f}%",
        ])
    print_table(["Bucket", "Range", "Games", "A %", "B %", "C %"], rows)

    # 7. Streaks
    print("\n7. STREAK ANALYSIS")
    streaks = data["streaks"]
    rows = []
    for ch in ("A", "B", "C"):
        s = streaks[ch]
        rows.append([ch, str(s["max_streak"]), str(s["current_streak"])])
    print_table(["Chair", "Max Streak", "Current Streak"], rows)

    # 8. Hourly Patterns
    print("\n8. HOURLY PATTERNS (win % by hour)")
    hourly = data["hourly"]
    hours = sorted(hourly.keys(), key=lambda h: int(h))
    rows = []
    for h in hours:
        d = hourly[h]
        t = d["total"] or 1
        rows.append([
            f"{int(h):02d}:00", str(d["total"]),
            f"{d['A']/t*100:.1f}%", f"{d['B']/t*100:.1f}%", f"{d['C']/t*100:.1f}%",
        ])
    print_table(["Hour", "Games", "A %", "B %", "C %"], rows)

    # 9. Recent vs Overall
    print("\n9. RECENT (LAST 100) vs ALL-TIME")
    rva = data["recent_vs_all"]
    for label, section in [("All-Time", rva["all"]), ("Last 100", rva["recent"])]:
        t = section["total"] or 1
        d = section["dist"]
        parts = " | ".join(f"{ch}: {d[ch]:>4} ({d[ch]/t*100:.1f}%)" for ch in ("A", "B", "C"))
        print(f"  {label:>10}  [{t:>5} games]  {parts}")

    print(f"\n{'='*60}")
    print("  Done.")


if __name__ == "__main__":
    main()