"""Validate category decomposition data for Overton report."""
from __future__ import annotations

import duckdb
import pytest

DB_PATH = "data/motions.db"


@pytest.fixture(scope="module")
def con():
    c = duckdb.connect(DB_PATH)
    yield c
    c.close()


def test_category_distribution(con):
    """There are exactly 10 categories and all 3,030 motions are classified."""
    df = con.execute("""
        SELECT category, COUNT(*) as cnt
        FROM right_wing_motions
        WHERE classified = TRUE
        GROUP BY category
        ORDER BY cnt DESC
    """).fetchdf()
    assert len(df) == 10
    assert df["cnt"].sum() == 3030
    assert df[df["category"] == "overig"]["cnt"].values[0] >= 100


def test_category_deltas(con):
    """Pre/post CS deltas (2024 split) — ALL categories gained, energie/klimaat leads."""
    df = con.execute("""
        SELECT
          category,
          AVG(CASE WHEN year < 2024 THEN centrist_support_strict END) as pre_cs,
          AVG(CASE WHEN year >= 2024 THEN centrist_support_strict END) as post_cs,
          COUNT(*) as n
        FROM right_wing_motions
        WHERE classified = TRUE AND year >= 2017
        GROUP BY category
    """).fetchdf()

    assert len(df) == 10
    df = df.copy()
    df["delta"] = df["post_cs"] - df["pre_cs"]
    top = df.sort_values("delta", ascending=False)
    assert top.iloc[0]["category"] == "energie/klimaat"
    assert 0.35 < abs(top.iloc[0]["delta"]) < 0.45

    bottom = df.sort_values("delta", ascending=True)
    assert bottom.iloc[0]["category"] in ("veiligheid/justitie", "onderwijs/wetenschap")

    assert all(df["delta"] > 0)


def test_yearly_category_cs(con):
    """Yearly CS per category returns data for every year-category combo."""
    df = con.execute("""
        SELECT year, category, AVG(centrist_support_strict) as cs, COUNT(*) as n
        FROM right_wing_motions
        WHERE classified = TRUE AND year >= 2017
        GROUP BY year, category
        ORDER BY year, category
    """).fetchdf()
    assert len(df) >= 50
    assert df["category"].nunique() == 10
    assert df["year"].nunique() >= 8


def test_quarterly_category_data(con):
    """Quarterly CS per key categories returns expected shape."""
    key_cats = ["asiel/vreemdelingen", "energie/klimaat", "buitenland/europa",
                "landbouw/natuur", "economie"]
    df = con.execute("""
        SELECT
          EXTRACT(YEAR FROM m.date) AS y,
          CEIL(EXTRACT(MONTH FROM m.date) / 3.0) AS q,
          r.category,
          AVG(r.centrist_support_strict) AS cs,
          COUNT(*) AS n
        FROM right_wing_motions r
        JOIN motions m ON r.motion_id = m.id
        WHERE r.classified = TRUE AND m.date IS NOT NULL
          AND r.category IN ({})
        GROUP BY y, q, r.category
        ORDER BY y, q
    """.format(",".join(f"'{c}'" for c in key_cats))).fetchdf()

    assert df["category"].nunique() <= 5
    for cat in key_cats:
        assert cat in df["category"].values


def test_qmd_has_domain_decomposition_section():
    """QMD should have a Domain Decomposition heading after implementation."""
    qmd = open("reports/overton_window/overton_window.qmd").read()
    assert "## Domain Decomposition" in qmd


def test_qmd_has_category_delta_chart():
    """QMD should have a category delta bar chart cell."""
    qmd = open("reports/overton_window/overton_window.qmd").read()
    assert "chart-7-category-delta" in qmd


def test_qmd_has_category_filter_dropdown():
    """Chart 1 should have updatemenu for category filtering."""
    qmd = open("reports/overton_window/overton_window.qmd").read()
    assert "updatemenus" in qmd


def test_qmd_has_domain_trajectories():
    """Quarterly chart should have category trajectories."""
    qmd = open("reports/overton_window/overton_window.qmd").read()
    assert "chart-8-domain-trajectories" in qmd