"""Opportunity historical evaluation tests."""

from __future__ import annotations

import json
import tempfile
import unittest
from pathlib import Path

from coinhunter.services import opportunity_evaluation_service


def _rows(start_ms: int, closes: list[float]) -> list[list[float]]:
    rows = []
    for index, close in enumerate(closes):
        open_time = start_ms + index * 3_600_000
        volume = 1_000 + index * 10
        rows.append(
            [
                float(open_time),
                close * 0.99,
                close * 1.02,
                close * 0.98,
                close,
                float(volume),
                float(open_time + 3_599_999),
                close * volume,
            ]
        )
    return rows


class OpportunityEvaluationServiceTestCase(unittest.TestCase):
    def test_evaluate_opportunity_dataset_scores_historical_samples(self):
        start_ms = 1_767_225_600_000
        dataset = {
            "metadata": {
                "plan": {
                    "intervals": ["1h"],
                    "simulation_start": "2026-01-01T04:00:00Z",
                    "simulation_end": "2026-01-01T07:00:00Z",
                    "simulate_days": 1,
                }
            },
            "klines": {
                "GOODUSDT": {"1h": _rows(start_ms, [100, 101, 102, 103, 104, 106, 108, 109, 110])},
                "BADUSDT": {"1h": _rows(start_ms, [100, 99, 98, 97, 96, 95, 94, 93, 92])},
            },
        }
        config = {
            "market": {"default_quote": "USDT"},
            "opportunity": {
                "entry_threshold": 1.5,
                "watch_threshold": 0.6,
                "evaluation_horizon_hours": 2.0,
                "evaluation_take_profit_pct": 1.0,
                "evaluation_stop_loss_pct": 2.0,
                "evaluation_setup_target_pct": 0.5,
                "evaluation_lookback": 4,
                "top_n": 2,
            },
        }

        with tempfile.TemporaryDirectory() as tmp_dir:
            dataset_path = Path(tmp_dir) / "opportunity-dataset.json"
            dataset_path.write_text(json.dumps(dataset), encoding="utf-8")

            payload = opportunity_evaluation_service.evaluate_opportunity_dataset(
                config,
                dataset_path=str(dataset_path),
                horizon_hours=2.0,
                take_profit=0.01,
                stop_loss=0.02,
                setup_target=0.005,
                lookback=4,
                top_n=2,
                max_examples=3,
            )

        self.assertEqual(payload["summary"]["symbols"], ["BADUSDT", "GOODUSDT"])
        self.assertEqual(payload["summary"]["interval"], "1h")
        self.assertGreater(payload["summary"]["count"], 0)
        self.assertIn("by_action", payload)
        self.assertIn("trade_simulation", payload)
        self.assertEqual(payload["rules"]["research_mode"], "disabled: dataset has no point-in-time research snapshots")
        self.assertLessEqual(len(payload["examples"]), 3)


if __name__ == "__main__":
    unittest.main()