import json
import tempfile
import unittest
from pathlib import Path
from unittest.mock import patch

import pandas as pd

from cbpred.latest_predict import OUTPUT_COLUMNS, build_predictions, output_columns_for_timeframe


class LatestPredictTests(unittest.TestCase):
    def test_output_columns_are_stable(self):
        self.assertEqual(
            OUTPUT_COLUMNS,
            (
                "rank",
                "symbol",
                "latest_bar_start_utc",
                "close",
                "quote_volume_usdt_8h",
                "atr_rank_200_pct",
                "drawdown_point_pct",
                "drawdown_cap_80pct_pct",
                "price_level_reached_80pct",
                "price_level_cap_80pct",
            ),
        )

    def test_output_columns_follow_timeframe(self):
        self.assertEqual(output_columns_for_timeframe("1d")[4], "quote_volume_usdt_1d")

    def test_batch_skips_symbols_without_training_profiles(self):
        with tempfile.TemporaryDirectory() as directory:
            root = Path(directory)
            data_dir = root / "data"
            output_dir = root / "output"
            data_dir.mkdir()
            for symbol, filename in (
                ("TRAIN/USDT:USDT", "train.csv"),
                ("STALE/USDT:USDT", "stale.csv"),
            ):
                pd.DataFrame(
                    [{"timestamp": 1, "quote": 10.0, "close": 100.0}]
                ).to_csv(data_dir / filename, index=False)
            (data_dir / "manifest.json").write_text(
                json.dumps(
                    {
                        "symbols": [
                            {"symbol": "TRAIN/USDT:USDT", "path": "train.csv"},
                            {"symbol": "STALE/USDT:USDT", "path": "stale.csv"},
                        ]
                    }
                )
            )

            result = {
                "symbol": "TRAIN/USDT:USDT",
                "timestamp": 1,
                "close": 100.0,
                "volatility_rank_200": 0.5,
                "eligible_for_model": False,
            }
            with patch(
                "cbpred.latest_predict.joblib.load",
                return_value={"asset_profiles": {"TRAIN/USDT:USDT": {}}},
            ), patch(
                "cbpred.latest_predict.predict_from_csv", return_value=result
            ) as predict:
                summary = build_predictions(data_dir, root / "model.joblib", output_dir)

            predict.assert_called_once_with(
                root / "model.joblib", data_dir / "train.csv", symbol="TRAIN/USDT:USDT"
            )
            self.assertEqual(summary["symbols"], 1)
            self.assertEqual(summary["skipped_symbols"], ["STALE/USDT:USDT"])


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