import pytest
import pandas as pd
from scipy.stats import mannwhitneyu

from src.artifact_1 import core

@pytest.fixture
def sample_run_data_valid():
    return {
        "timestamp": "2024-06-10T10:00:00Z",
        "pinned_flag": True,
        "runtime": 120.5,
        "seqcount_retry_count": 2,
        "mischfenster_dauer": 3.4
    }

@pytest.fixture
def sample_run_data_unpinned():
    return {
        "timestamp": "2024-06-10T10:02:00Z",
        "pinned_flag": False,
        "runtime": 122.0,
        "seqcount_retry_count": 5,
        "mischfenster_dauer": 7.2
    }

def test_calculate_metrics_basic(sample_run_data_valid):
    result = core.calculate_metrics(sample_run_data_valid)
    assert isinstance(result, dict)
    assert "retry_free_rate" in result
    assert "mischfenster_stats" in result
    assert "correlations" in result
    # retry free rate sanity
    assert 0.0 <= result["retry_free_rate"] <= 1.0
    # mischfenster_stats contains expected keys
    stats = result["mischfenster_stats"]
    for key in ("p50", "p95", "max"):
        assert key in stats
    # correlations sanity check
    assert isinstance(result["correlations"], dict)

def test_calculate_metrics_invalid_input():
    invalid_data = {
        "timestamp": "2024-06-10T10:00:00Z",
        # missing required fields
    }
    with pytest.raises((KeyError, ValueError, TypeError)):
        core.calculate_metrics(invalid_data)

def test_run_mann_whitney_test_basic():
    data1 = [1.2, 1.4, 1.6, 1.8, 2.0]
    data2 = [2.1, 2.3, 2.5, 2.7, 2.9]
    p_value = core.run_mann_whitney_test(data1, data2)
    assert isinstance(p_value, float)
    assert 0.0 <= p_value <= 1.0

def test_run_mann_whitney_test_identical_data():
    data = [1.0, 1.1, 1.2, 1.3]
    p_value = core.run_mann_whitney_test(data, data.copy())
    assert pytest.approx(p_value, rel=1e-6) == 1.0

@pytest.mark.parametrize(
    "data1,data2",
    [
        ([1, 2, 3], [4, 5, 6]),
        ([10.0, 10.5, 10.8], [9.7, 9.8, 9.9]),
    ]
)
def test_run_mann_whitney_test_symmetry(data1, data2):
    p1 = core.run_mann_whitney_test(data1, data2)
    p2 = core.run_mann_whitney_test(data2, data1)
    assert pytest.approx(p1, rel=1e-6) == p2

def test_run_mann_whitney_test_invalid_input():
    with pytest.raises((ValueError, TypeError)):
        core.run_mann_whitney_test([], [1, 2, 3])
    with pytest.raises((ValueError, TypeError)):
        core.run_mann_whitney_test([1, 2, 3], [None, 5])