"""Malformed parquet/input tests for phase boundary contracts."""

from __future__ import annotations

import pandas as pd
import pytest

from pipeline.alpha.compute import compute_alpha
from pipeline.combo.combine import combine_alphas
from pipeline.derived.compute import validate_derived_frame
from pipeline.portfolio.construct import construct_positions
from pipeline.portfolio.simulator import ReferenceSimulator
from tests.helpers import make_generated_daily_bars


def test_alpha_compute_rejects_daily_data_without_close():
    daily = make_generated_daily_bars().drop(columns=["close"])

    with pytest.raises(KeyError, match="close"):
        compute_alpha(daily, "bad", "reversal", lookback=3)


def test_alpha_feature_path_rejects_duplicate_symbol_dates(tmp_path):
    daily = make_generated_daily_bars()
    feature = pd.DataFrame({
        "symbol_id": ["sh600000", "sh600000"],
        "date": ["2024-01-02 09:30:00", "2024-01-02 15:00:00"],
        "toy_feature": [1.0, 2.0],
    })
    feature_path = tmp_path / "duplicate_feature_keys.pq"
    feature.to_parquet(feature_path, index=False)

    with pytest.raises(ValueError, match="duplicate symbol_id,date"):
        compute_alpha(
            daily,
            "bad_features",
            "reversal",
            lookback=3,
            feature_paths=[str(feature_path)],
        )


def test_derived_validation_rejects_bool_value_columns():
    derived = pd.DataFrame({
        "symbol_id": ["sh600000"],
        "date": [pd.Timestamp("2024-01-02")],
        "is_good": [True],
    })

    with pytest.raises(ValueError, match="numeric"):
        validate_derived_frame(derived)


def test_combo_combine_rejects_missing_weight_column(tmp_path):
    bad_alpha = pd.DataFrame({
        "symbol_id": ["sh600000"],
        "date": [pd.Timestamp("2024-01-02")],
        "alpha_name": ["bad"],
    })
    bad_alpha_path = tmp_path / "bad_alpha.pq"
    bad_alpha.to_parquet(bad_alpha_path, index=False)

    with pytest.raises(KeyError, match="weight"):
        combine_alphas([str(bad_alpha_path)], "bad_combo")


def test_portfolio_build_rejects_weights_without_symbol_id():
    daily = make_generated_daily_bars()
    bad_weights = pd.DataFrame({
        "date": [pd.Timestamp("2024-01-02")],
        "combo_name": ["bad"],
        "weight": [1.0],
    })

    with pytest.raises(KeyError, match="symbol_id"):
        construct_positions(
            bad_weights,
            daily,
            booksize=1_000_000.0,
            portfolio_name="bad_portfolio",
        )


def test_portfolio_simulate_rejects_positions_without_position_shares():
    daily = make_generated_daily_bars()
    bad_positions = pd.DataFrame({
        "symbol_id": ["sh600000"],
        "date": [pd.Timestamp("2024-01-02")],
        "portfolio_name": ["bad"],
        "target_weight": [1.0],
        "target_value": [1000.0],
        "target_shares": [100.0],
        "position_value": [1000.0],
        "price": [10.0],
    })

    with pytest.raises(KeyError, match="position_shares"):
        ReferenceSimulator().run(bad_positions, daily)