"""Test deterministici dello SHADOW MODE di TP01 (src/live/deribit.py).

Coprono la logica a rischio zero che NON tocca la rete: quantizzazione notional->contratti, sizing
target, costruzione ordine di ribilancio (buy/sell/exit/None), e PARITA' col backtest (il target
live = ultimo target della serie causale). Il fill reale (slippage/fee) NON e' qui: si valida solo
col micro-test mainnet.
"""
import sys
from pathlib import Path

PROJECT_ROOT = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(PROJECT_ROOT))

from src.live.deribit import (build_rebalance_order, notional_to_amount, target_notional_usd)
from src.strategies.trend_portfolio import CANONICAL, TrendPortfolio, resample_1d


def test_notional_to_amount_step_and_min():
    # BTC step/min $10
    assert notional_to_amount("BTC-PERPETUAL", 1000) == 1000
    assert notional_to_amount("BTC-PERPETUAL", 1006) == 1010      # round allo step
    assert notional_to_amount("BTC-PERPETUAL", 7) == 10           # clamp al minimo (>= mezzo step)
    assert notional_to_amount("BTC-PERPETUAL", 3) == 0.0          # < mezzo step -> niente ordine
    # ETH step/min $1
    assert notional_to_amount("ETH-PERPETUAL", 33.7) == 34
    assert notional_to_amount("ETH-PERPETUAL", 0.4) == 0.0
    # usa il valore assoluto (il segno lo decide il delta a monte)
    assert notional_to_amount("BTC-PERPETUAL", -1000) == 1000


def test_no_float_artifacts():
    # _quantize_step usa Decimal: nessun 0.07200000000000001 & co.
    v = notional_to_amount("ETH-PERPETUAL", 72.0)
    assert v == 72 and float(v).is_integer()


def test_target_notional_5050_weight():
    # 50/50 book: notional asset = 0.5 * frazione * equity
    assert target_notional_usd(1.0, 0.5, 2000) == 1000
    assert target_notional_usd(2.0, 0.5, 2000) == 2000           # leva-cap 2x -> piena equity sull'asset
    assert target_notional_usd(0.0, 0.5, 2000) == 0.0


def test_build_order_entry():
    o = build_rebalance_order("BTC-PERPETUAL", target_fraction=1.0, weight=0.5,
                              equity_usd=2000, current_pos_usd=0.0)
    assert o["side"] == "buy" and o["amount"] == 1000 and o["reduce_only"] is False
    assert o["target_notional"] == 1000 and o["delta_notional"] == 1000


def test_build_order_exit_is_reduce_only():
    o = build_rebalance_order("ETH-PERPETUAL", target_fraction=0.0, weight=0.5,
                              equity_usd=2000, current_pos_usd=1000.0)
    assert o["side"] == "sell" and o["reduce_only"] is True and o["amount"] == 1000


def test_build_order_already_at_target_is_none():
    o = build_rebalance_order("BTC-PERPETUAL", 1.0, 0.5, 2000, current_pos_usd=1000.0)
    assert o is None                                              # delta 0 -> nessun ordine


def test_build_order_subthreshold_is_none():
    # delta $3 su BTC (< mezzo step $5) -> niente ordine
    o = build_rebalance_order("BTC-PERPETUAL", 0.5015, 0.5, 2000, current_pos_usd=498.5)
    assert o is None


def test_partial_rebalance_direction():
    # target $1000, ho $600 -> compro $400; ho $1400 -> vendo $400
    up = build_rebalance_order("BTC-PERPETUAL", 1.0, 0.5, 2000, 600.0)
    dn = build_rebalance_order("BTC-PERPETUAL", 1.0, 0.5, 2000, 1400.0)
    assert up["side"] == "buy" and up["amount"] == 400
    assert dn["side"] == "sell" and dn["amount"] == 400 and dn["reduce_only"] is False


def test_parity_live_target_equals_backtest():
    # il target live (current_target) DEVE essere l'ultimo della serie causale del backtest
    from src.backtest.harness import load
    tp = TrendPortfolio(**CANONICAL)
    df = resample_1d(load("BTC", "1h"))
    assert tp.current_target(df) == tp.target_series(df)[-1]