import json

import pytest

from app.db import altcoin_db
from app.db.paper_trading import get_paper_trading_summary, list_paper_trades, sync_recommendation


@pytest.fixture
def buy_now_rec(monkeypatch):
    monkeypatch.setenv("ALPHAX_PAPER_TRADING_ENABLED", "1")
    monkeypatch.setenv("ALPHAX_PAPER_TRADE_NOTIONAL_USDT", "100")
    monkeypatch.setenv("ALPHAX_PAPER_TRADE_FEE_RATE", "0")
    monkeypatch.setenv("ALPHAX_PAPER_TRADE_SLIPPAGE_PCT", "0")
    altcoin_db.init_db()
    rec_id = altcoin_db.create_recommendation(
        symbol="PAPER/USDT",
        rec_state="爆发",
        rec_score=28,
        entry_price=100,
        stop_loss=95,
        tp1=106,
        tp2=112,
        signals=["当前15min即刻入场信号"],
        entry_plan={
            "entry_action": "可即刻买入",
            "entry_price": 100,
            "stop_loss": 95,
            "tp1": 106,
            "tp2": 112,
            "risk_reward_ok": True,
            "rr1": 1.2,
            "entry_trigger_confirmed": True,
        },
    )
    rows = altcoin_db.get_active_recommendations_deduped(actionable_only=False)
    return next(r for r in rows if r["id"] == rec_id)


def test_buy_now_opens_paper_trade_once(buy_now_rec):
    first = sync_recommendation(buy_now_rec, 100, event_time="2026-05-16T10:00:00")
    second = sync_recommendation(buy_now_rec, 101, event_time="2026-05-16T10:01:00")

    assert first["opened"] is True
    assert second["updated"] is True

    trades = list_paper_trades()["items"]
    assert len(trades) == 1
    assert trades[0]["symbol"] == "PAPER/USDT"
    assert trades[0]["status"] == "open"
    assert trades[0]["pnl_pct"] == pytest.approx(1.0)


def test_default_paper_trade_uses_5000u_notional_5x_and_1000u_margin(monkeypatch):
    monkeypatch.setenv("ALPHAX_PAPER_TRADING_ENABLED", "1")
    monkeypatch.delenv("ALPHAX_PAPER_TRADE_NOTIONAL_USDT", raising=False)
    monkeypatch.delenv("ALPHAX_PAPER_TRADE_MARGIN_USDT", raising=False)
    monkeypatch.delenv("ALPHAX_PAPER_TRADE_LEVERAGE", raising=False)
    monkeypatch.delenv("ALPHAX_PAPER_ACCOUNT_EQUITY_USDT", raising=False)
    monkeypatch.setenv("ALPHAX_PAPER_TRADE_FEE_RATE", "0")
    monkeypatch.setenv("ALPHAX_PAPER_TRADE_SLIPPAGE_PCT", "0")
    altcoin_db.init_db()
    rec_id = altcoin_db.create_recommendation(
        symbol="DEFAULT/USDT",
        rec_state="爆发",
        rec_score=28,
        entry_price=100,
        stop_loss=95,
        tp1=106,
        tp2=112,
        signals=["当前15min即刻入场信号"],
        entry_plan={"entry_action": "可即刻买入", "entry_trigger_confirmed": True, "risk_reward_ok": True},
    )
    rec = next(r for r in altcoin_db.get_active_recommendations_deduped(actionable_only=False) if r["id"] == rec_id)

    sync_recommendation(rec, 100, event_time="2026-05-16T10:00:00")
    trade = list_paper_trades()["items"][0]
    summary = get_paper_trading_summary(days=30)

    assert trade["notional_usdt"] == pytest.approx(5000.0)
    assert trade["leverage"] == pytest.approx(5.0)
    assert trade["margin_usdt"] == pytest.approx(1000.0)
    assert summary["account_equity_usdt"] == pytest.approx(20000.0)
    assert summary["initial_equity_usdt"] == pytest.approx(20000.0)
    assert summary["current_balance_usdt"] == pytest.approx(20000.0)
    assert summary["open_position_value_usdt"] == pytest.approx(5000.0)
    assert summary["cumulative_leverage"] == pytest.approx(0.25)
    assert summary["notional_usdt"] == pytest.approx(5000.0)
    assert summary["margin_usdt"] == pytest.approx(1000.0)


def test_paper_margin_is_derived_from_notional_and_leverage(monkeypatch):
    monkeypatch.setenv("ALPHAX_PAPER_TRADE_NOTIONAL_USDT", "5000")
    monkeypatch.setenv("ALPHAX_PAPER_TRADE_LEVERAGE", "5")
    monkeypatch.setenv("ALPHAX_PAPER_TRADE_MARGIN_USDT", "5000")

    summary = get_paper_trading_summary(days=30)

    assert summary["notional_usdt"] == pytest.approx(5000.0)
    assert summary["leverage"] == pytest.approx(5.0)
    assert summary["margin_usdt"] == pytest.approx(1000.0)


def test_observation_does_not_open_paper_trade(monkeypatch):
    monkeypatch.setenv("ALPHAX_PAPER_TRADING_ENABLED", "1")
    altcoin_db.init_db()
    rec_id = altcoin_db.create_recommendation(
        symbol="OBS/USDT",
        rec_state="加速",
        rec_score=18,
        entry_price=100,
        stop_loss=95,
        tp1=106,
        signals=["历史放量"],
        entry_plan={"entry_action": "观察", "entry_price": 100, "stop_loss": 95, "tp1": 106},
    )
    rows = altcoin_db.get_active_recommendations_deduped(actionable_only=False)
    rec = next(r for r in rows if r["id"] == rec_id)

    result = sync_recommendation(rec, 100, event_time="2026-05-16T10:00:00")

    assert result["skipped"] is True
    assert result["reason"] == "not_buy_now"
    assert list_paper_trades()["total"] == 0


def test_open_paper_trade_closes_on_tp1_and_summary_counts_win(buy_now_rec):
    sync_recommendation(buy_now_rec, 100, event_time="2026-05-16T10:00:00")
    result = sync_recommendation(buy_now_rec, 106, event_time="2026-05-16T10:05:00")

    assert result["closed"] is True
    assert result["exit_reason"] == "tp1"
    assert result["pnl_pct"] == pytest.approx(6.0)

    summary = get_paper_trading_summary(days=30)
    assert summary["closed_count"] == 1
    assert summary["win_count"] == 1
    assert summary["win_rate"] == pytest.approx(100.0)


def test_closed_paper_trade_keeps_exit_price_and_shows_latest_market_price(buy_now_rec):
    sync_recommendation(buy_now_rec, 100, event_time="2026-05-16T10:00:00")
    sync_recommendation(buy_now_rec, 106, event_time="2026-05-16T10:05:00")
    altcoin_db.update_latest_price_cache("PAPER/USDT", 103.25, updated_at="2026-05-16T10:10:00", source="unit")

    trade = list_paper_trades()["items"][0]

    assert trade["status"] == "closed"
    assert trade["exit_price"] == pytest.approx(106.0)
    assert trade["current_price"] == pytest.approx(106.0)
    assert trade["latest_price"] == pytest.approx(103.25)
    assert trade["latest_price_updated_at"] == "2026-05-16T10:10:00"


def test_disabled_paper_trading_skips_without_writing(monkeypatch, buy_now_rec):
    monkeypatch.setenv("ALPHAX_PAPER_TRADING_ENABLED", "0")

    result = sync_recommendation(buy_now_rec, 100, event_time="2026-05-16T10:00:00")

    assert result["skipped"] is True
    assert result["reason"] == "disabled"
    assert list_paper_trades()["total"] == 0