#!/usr/bin/env python3
"""
hl_funding_arb.py — Hyperliquid vs Binance funding rate monitor

Compares 1-hour funding rates across matching perpetual pairs on Hyperliquid
and Binance USDT-margined futures. Ranks arb opportunities by annualized spread.
Separately analyzes HIP-3 equity perps that have no Binance equivalent.

Usage:
    python hl_funding_arb.py
    python hl_funding_arb.py --top 30
    python hl_funding_arb.py --min-oi 10  # only pairs with OI > $10M
"""

import argparse
import json
import sys
from datetime import datetime, timezone

import requests

HL_API = "https://api.hyperliquid.xyz/info"
BN_PERP_API = "https://fapi.binance.com/fapi/v1/premiumIndex"

# Taker fee assumptions — standard retail tier, no volume discounts.
# HL: 0.035% taker (drops to 0.010% at higher volume tiers; maker is rebated at -0.002%)
# Binance USDT perp: 0.050% taker (drops to 0.017% at VIP 6+)
# Adjust these constants to match your actual fee tier.
HL_TAKER_FEE = 0.00035
BN_TAKER_FEE = 0.0005
ROUNDTRIP_COST = (HL_TAKER_FEE + BN_TAKER_FEE) * 2  # open + close both legs

# Known HIP-3 equity perps on Hyperliquid (tokenized stock/index perps)
EQUITY_TICKERS = {
    "TSLA", "AAPL", "NVDA", "MSFT", "AMZN", "GOOGL", "GOOG", "META",
    "NFLX", "AMD", "INTC", "COIN", "MSTR", "BABA", "SPX", "QQQ",
    "GLD", "SLV", "PLTR", "UBER", "SNAP", "ARKK", "PYPL", "CRM",
    "AVGO", "TSM", "ASML", "SHOP", "SQ", "RBLX", "NET", "CRWD",
    "DDOG", "ZS", "PANW", "SMCI", "ARM", "HOOD", "RIVN", "LCID",
}


def fetch_hl_data() -> list[dict]:
    """Return all HL perp markets with funding, OI, and mark price."""
    resp = requests.post(
        HL_API,
        json={"type": "metaAndAssetCtxs"},
        timeout=15,
    )
    resp.raise_for_status()
    meta, ctxs = resp.json()

    results = []
    for coin_meta, ctx in zip(meta["universe"], ctxs):
        name = coin_meta["name"]
        try:
            funding_1h = float(ctx["funding"])
            mark_px = float(ctx["markPx"])
            oi_contracts = float(ctx["openInterest"])
        except (KeyError, ValueError, TypeError):
            continue

        oi_usd = oi_contracts * mark_px
        funding_annual = funding_1h * 24 * 365  # 1h rate × 8760

        results.append(
            {
                "symbol": name,
                "funding_1h": funding_1h,
                "funding_annual": funding_annual,
                "oi_usd": oi_usd,
                "mark_px": mark_px,
                "asset_type": "equity" if name in EQUITY_TICKERS else "crypto",
            }
        )

    return results


def fetch_binance_funding() -> dict[str, dict]:
    """Return mapping of base asset → Binance 1h equivalent funding rate."""
    resp = requests.get(BN_PERP_API, timeout=15)
    resp.raise_for_status()

    results = {}
    for item in resp.json():
        symbol: str = item["symbol"]
        if not symbol.endswith("USDT"):
            continue
        base = symbol[:-4]
        # Binance lastFundingRate is for the 8-hour settlement window
        rate_8h = float(item["lastFundingRate"])
        results[base] = {
            "funding_1h": rate_8h / 8,
            "funding_annual": rate_8h * 3 * 365,  # 3 settlements/day × 365
            "next_funding_time": item.get("nextFundingTime"),
        }

    return results


def breakeven_holding_days(spread_annual: float) -> float:
    """Minimum days the spread must persist to cover round-trip fees."""
    if spread_annual == 0:
        return float("inf")
    return ROUNDTRIP_COST / abs(spread_annual) * 365


def _pct(rate: float) -> str:
    return f"{rate * 100:+.4f}%"


def _pct2(rate: float) -> str:
    return f"{rate * 100:+.2f}%"


def print_table(rows: list[dict], columns: list[tuple], title: str):
    header = "  ".join(f"{name:>{width}}" for name, width, _ in columns)
    sep = "  ".join("-" * width for _, width, _ in columns)
    print(f"\n── {title} ──\n")
    print(header)
    print(sep)
    for row in rows:
        cells = []
        for name, width, key in columns:
            val = row.get(key, "")
            if callable(key):
                val = key(row)
            cells.append(f"{str(val):>{width}}")
        print("  ".join(cells))


def run(top: int = 25, min_oi_m: float = 0.0):
    ts = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M UTC")
    print(f"\n{'='*76}")
    print(f"  HYPERLIQUID vs BINANCE FUNDING RATE MONITOR — {ts}")
    print(f"{'='*76}")

    print("\nFetching Hyperliquid data...", end=" ", flush=True)
    hl_data = fetch_hl_data()
    print(f"{len(hl_data)} markets")

    print("Fetching Binance data...", end=" ", flush=True)
    bn_data = fetch_binance_funding()
    print(f"{len(bn_data)} markets")

    min_oi = min_oi_m * 1e6

    cross_venue = []
    equity_perps = []
    hl_only = []

    for item in hl_data:
        if item["oi_usd"] < min_oi:
            continue
        sym = item["symbol"]
        if item["asset_type"] == "equity":
            equity_perps.append(item)
        elif sym in bn_data:
            bn = bn_data[sym]
            spread = item["funding_annual"] - bn["funding_annual"]
            breakeven = breakeven_holding_days(spread)
            cross_venue.append(
                {
                    **item,
                    "bn_annual": bn["funding_annual"],
                    "spread_annual": spread,
                    "breakeven_days": breakeven,
                }
            )
        else:
            hl_only.append(item)

    cross_venue.sort(key=lambda x: abs(x["spread_annual"]), reverse=True)
    equity_perps.sort(key=lambda x: x["oi_usd"], reverse=True)

    # ── SECTION 1: Cross-venue arb ──────────────────────────────────────────
    print(f"\n\n{'─'*76}")
    print(f"  SECTION 1 — FUNDING ARB: HL vs BINANCE  (top {top} by |spread|)")
    print(f"  Round-trip fee cost: {ROUNDTRIP_COST*100:.3f}%  |  min OI filter: ${min_oi_m:.0f}M")
    print(f"{'─'*76}")

    header = (
        f"  {'Symbol':<10}"
        f"{'HL annual':>11}"
        f"{'BN annual':>11}"
        f"{'Spread':>10}"
        f"{'OI $M':>9}"
        f"{'B/E days':>9}"
        f"  Direction"
    )
    print(header)
    print("  " + "-" * 72)

    shown = 0
    for row in cross_venue:
        if shown >= top:
            break
        spread = row["spread_annual"]
        direction = "BN short / HL long" if spread > 0 else "HL short / BN long"
        covers_fees = "✓" if abs(spread) > ROUNDTRIP_COST * 2 else " "

        print(
            f"  {row['symbol']:<10}"
            f"{_pct2(row['funding_annual']):>11}"
            f"{_pct2(row['bn_annual']):>11}"
            f"{_pct2(spread):>10}"
            f"{row['oi_usd']/1e6:>8.1f}M"
            f"{row['breakeven_days']:>9.1f}"
            f"  {covers_fees} {direction}"
        )
        shown += 1

    # ── SECTION 2: Equity perps ─────────────────────────────────────────────
    print(f"\n\n{'─'*76}")
    print(f"  SECTION 2 — HIP-3 EQUITY PERPS on HYPERLIQUID (no Binance equivalent)")
    print(f"{'─'*76}")

    eq_header = (
        f"  {'Symbol':<10}"
        f"{'1h rate':>10}"
        f"{'Annual':>10}"
        f"{'OI $M':>9}"
        f"  Signal"
    )
    print(eq_header)
    print("  " + "-" * 55)

    for row in equity_perps[:20]:
        ann = row["funding_annual"]
        if ann > 0.50:
            signal = "↑ heavily long-biased"
        elif ann < -0.50:
            signal = "↓ heavily short-biased"
        elif abs(ann) < 0.05:
            signal = "  neutral"
        else:
            signal = ""

        print(
            f"  {row['symbol']:<10}"
            f"{_pct(row['funding_1h']):>10}"
            f"{_pct2(ann):>10}"
            f"{row['oi_usd']/1e6:>8.1f}M"
            f"  {signal}"
        )

    # ── SECTION 3: Platform summary ─────────────────────────────────────────
    total_oi = sum(x["oi_usd"] for x in hl_data if x["oi_usd"] >= min_oi)
    equity_oi = sum(x["oi_usd"] for x in equity_perps)
    crypto_oi = sum(x["oi_usd"] for x in cross_venue) + sum(x["oi_usd"] for x in hl_only)
    positive_spread = [x for x in cross_venue if x["spread_annual"] > ROUNDTRIP_COST * 2]
    negative_spread = [x for x in cross_venue if x["spread_annual"] < -ROUNDTRIP_COST * 2]

    print(f"\n\n{'─'*76}")
    print(f"  SECTION 3 — PLATFORM SUMMARY")
    print(f"{'─'*76}")
    print(f"  Total HL OI tracked:       ${total_oi/1e9:>7.2f}B")
    print(f"  Crypto perp OI:            ${crypto_oi/1e9:>7.2f}B  ({crypto_oi/total_oi*100:.1f}%)")
    print(f"  HIP-3 equity perp OI:      ${equity_oi/1e9:>7.2f}B  ({equity_oi/total_oi*100:.1f}%)")
    print(f"  Cross-venue pairs (HL+BN): {len(cross_venue):>4}")
    print(f"  HL-only crypto pairs:      {len(hl_only):>4}")
    print(f"  Equity-only pairs:         {len(equity_perps):>4}")
    print(f"  Pairs with +spread > fees: {len(positive_spread):>4}  (BN short / HL long bias)")
    print(f"  Pairs with -spread > fees: {len(negative_spread):>4}  (HL short / BN long bias)")

    avg_eq_funding = (
        sum(abs(x["funding_annual"]) for x in equity_perps) / len(equity_perps)
        if equity_perps
        else 0
    )
    avg_crypto_funding = (
        sum(abs(x["funding_annual"]) for x in cross_venue) / len(cross_venue)
        if cross_venue
        else 0
    )
    print(f"\n  Avg |annual funding| — equity perps:  {avg_eq_funding*100:.2f}%")
    print(f"  Avg |annual funding| — crypto perps:  {avg_crypto_funding*100:.2f}%")
    print()


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="HL vs Binance funding rate monitor")
    parser.add_argument("--top", type=int, default=25, help="Top N pairs to show (default: 25)")
    parser.add_argument(
        "--min-oi",
        type=float,
        default=0.0,
        metavar="M",
        help="Minimum OI in millions USD (default: 0)",
    )
    args = parser.parse_args()
    run(top=args.top, min_oi_m=args.min_oi)