import re
from datetime import date
from pathlib import Path

import pandas as pd
import pytest

from pdf_export import (
    DAGOVERZICHT_MAX_DAYS,
    SECTION_AGP,
    SECTION_DAGOVERZICHT,
    SECTION_EVENTS,
    SECTION_INSULIN_PROFILE,
    SECTION_SUMMARY,
    _report_config,
    build_report_pdf,
)


def _page_count(pdf_bytes: bytes) -> int:
    """Grof-maar-betrouwbaar paginatelling op de ruwe PDF-bytes: elke
    paginaobject bevat een '/Type /Page' (zonder de 's' van '/Type /Pages')
    in zijn objectdictionary, wat altijd onleesbaar-platte tekst blijft ook
    al staat contentstream-compressie aan — geen losse PDF-parser nodig voor
    deze structurele check (zelfde black-box-filosofie als de rest van deze
    testset: geen pixel-vergelijkingen, wel structuur)."""
    return len(re.findall(rb"/Type\s*/Page[^s]", pdf_bytes))


def _sample_glucose():
    timestamps = pd.date_range("2026-01-01", periods=48, freq="30min")
    return pd.DataFrame({"timestamp": timestamps, "mmol": [6.0 + (i % 5) for i in range(48)]})


def _glucose_with_hypo_and_hyper_events():
    """3 dagen data met een echte hypo- (<3.9, >=15 min) en hyperepisode (>10.0)."""
    timestamps = pd.date_range("2026-01-01", periods=3 * 24 * 12, freq="5min")
    values = [7.0] * len(timestamps)
    values[10:15] = [3.0] * 5  # 25 min hypo
    values[100:106] = [12.0] * 6  # 30 min hyper
    return pd.DataFrame({"timestamp": timestamps, "mmol": values})


def test_build_report_pdf_produces_valid_pdf_bytes():
    glucose = _sample_glucose()
    events_summary = {
        "Hypo Level 1": {"count": 2, "avg_duration_minutes": 20.0, "events_per_week": 1.0},
    }
    pdf_bytes = build_report_pdf(
        [SECTION_SUMMARY, SECTION_AGP, SECTION_EVENTS],
        glucose,
        events_summary,
        date(2026, 1, 1),
        date(2026, 1, 2),
    )
    assert isinstance(pdf_bytes, bytes)
    assert pdf_bytes.startswith(b"%PDF")
    assert len(pdf_bytes) > 500


def test_build_report_pdf_handles_empty_glucose():
    empty = pd.DataFrame(columns=["timestamp", "mmol"])
    pdf_bytes = build_report_pdf(
        [SECTION_SUMMARY, SECTION_AGP], empty, {}, date(2026, 1, 1), date(2026, 1, 2)
    )
    assert pdf_bytes.startswith(b"%PDF")


def test_build_report_pdf_handles_no_sections_selected():
    glucose = _sample_glucose()
    pdf_bytes = build_report_pdf([], glucose, {}, date(2026, 1, 1), date(2026, 1, 2))
    assert pdf_bytes.startswith(b"%PDF")


def test_build_report_pdf_includes_dagoverzicht_section():
    glucose = _sample_glucose()
    pdf_bytes = build_report_pdf(
        [SECTION_DAGOVERZICHT], glucose, {}, date(2026, 1, 1), date(2026, 1, 2)
    )
    assert pdf_bytes.startswith(b"%PDF")
    assert len(pdf_bytes) > 500


def test_build_report_pdf_caps_dagoverzicht_at_max_days():
    timestamps = pd.date_range("2026-01-01", periods=(DAGOVERZICHT_MAX_DAYS + 10) * 24, freq="1h")
    glucose = pd.DataFrame({"timestamp": timestamps, "mmol": [7.0] * len(timestamps)})
    pdf_bytes = build_report_pdf(
        [SECTION_DAGOVERZICHT],
        glucose,
        {},
        timestamps[0].date(),
        timestamps[-1].date(),
    )
    assert pdf_bytes.startswith(b"%PDF")


def test_build_report_pdf_draws_hypo_and_hyper_charts_when_events_present():
    glucose = _glucose_with_hypo_and_hyper_events()
    events_summary = {
        "Hypo Level 1": {"count": 1, "avg_duration_minutes": 25.0, "events_per_week": 2.3},
        "Hyper Level 1": {"count": 1, "avg_duration_minutes": 30.0, "events_per_week": 2.3},
    }
    pdf_bytes = build_report_pdf(
        [SECTION_EVENTS], glucose, events_summary, date(2026, 1, 1), date(2026, 1, 4)
    )
    assert pdf_bytes.startswith(b"%PDF")
    assert len(pdf_bytes) > 500


def test_build_report_pdf_always_has_at_least_a_cover_page():
    empty = pd.DataFrame(columns=["timestamp", "mmol"])
    pdf_bytes = build_report_pdf([], empty, {}, date(2026, 1, 1), date(2026, 1, 2))
    assert _page_count(pdf_bytes) == 1


def test_build_report_pdf_one_page_per_single_page_section():
    glucose = _sample_glucose()
    pdf_bytes = build_report_pdf(
        [SECTION_SUMMARY, SECTION_AGP], glucose, {}, date(2026, 1, 1), date(2026, 1, 2)
    )
    # cover + summary + agp = 3
    assert _page_count(pdf_bytes) == 3


def test_build_report_pdf_one_page_per_day_for_dagoverzicht():
    timestamps = pd.date_range("2026-01-01", periods=3 * 24 * 12, freq="5min")  # 3 dagen
    glucose = pd.DataFrame({"timestamp": timestamps, "mmol": [7.0] * len(timestamps)})
    pdf_bytes = build_report_pdf(
        [SECTION_DAGOVERZICHT], glucose, {}, date(2026, 1, 1), date(2026, 1, 3)
    )
    # cover + 3 dagen
    assert _page_count(pdf_bytes) == 4


def test_build_report_pdf_caps_dagoverzicht_page_count_at_max_days():
    timestamps = pd.date_range("2026-01-01", periods=(DAGOVERZICHT_MAX_DAYS + 10) * 24, freq="1h")
    glucose = pd.DataFrame({"timestamp": timestamps, "mmol": [7.0] * len(timestamps)})
    pdf_bytes = build_report_pdf(
        [SECTION_DAGOVERZICHT], glucose, {}, timestamps[0].date(), timestamps[-1].date()
    )
    # cover + max. DAGOVERZICHT_MAX_DAYS dagpagina's, ondanks (DAGOVERZICHT_MAX_DAYS + 10) dagen aan data
    assert _page_count(pdf_bytes) == 1 + DAGOVERZICHT_MAX_DAYS


def test_build_report_pdf_includes_insulin_profile_section_page():
    glucose = _sample_glucose()
    profile = {
        "name": "Default",
        "dia": 5.0,
        "basal": [{"minutes": 0, "value": 0.8}, {"minutes": 720, "value": 1.1}],
        "sens": [{"minutes": 0, "value": 2.8}],
        "carbratio": [{"minutes": 0, "value": 10.0}],
        "target_low": [{"minutes": 0, "value": 4.5}],
        "target_high": [{"minutes": 0, "value": 8.0}],
    }
    pdf_bytes = build_report_pdf(
        [SECTION_INSULIN_PROFILE], glucose, {}, date(2026, 1, 1), date(2026, 1, 2), profile=profile
    )
    # cover + insulineprofiel
    assert _page_count(pdf_bytes) == 2
    assert pdf_bytes.startswith(b"%PDF")


def test_build_report_pdf_insulin_profile_section_handles_missing_profile():
    glucose = _sample_glucose()
    pdf_bytes = build_report_pdf(
        [SECTION_INSULIN_PROFILE], glucose, {}, date(2026, 1, 1), date(2026, 1, 2), profile=None
    )
    assert _page_count(pdf_bytes) == 2
    assert pdf_bytes.startswith(b"%PDF")


def test_build_report_pdf_insulin_profile_section_renders_without_glucose():
    """De Insulineprofiel-sectie gaat niet over glucosedata en moet dus ook
    renderen als er geen glucosemetingen zijn (in tegenstelling tot
    Samenvatting/AGP/Dagoverzicht, die wel glucosedata vereisen)."""
    empty = pd.DataFrame(columns=["timestamp", "mmol"])
    profile = {
        "name": "Default",
        "dia": 5.0,
        "basal": [{"minutes": 0, "value": 0.8}],
        "sens": [{"minutes": 0, "value": 2.8}],
        "carbratio": [{"minutes": 0, "value": 10.0}],
        "target_low": [],
        "target_high": [],
    }
    pdf_bytes = build_report_pdf(
        [SECTION_INSULIN_PROFILE], empty, {}, date(2026, 1, 1), date(2026, 1, 2), profile=profile
    )
    assert _page_count(pdf_bytes) == 2


def test_build_report_pdf_dagoverzicht_uses_treatments_and_profile_without_error():
    """Regressietest: de dagpagina moet basaal/bolus/koolhydraten/streefwaarde-
    overlays tekenen zonder te crashen als er echte treatments/profile worden
    meegegeven (in plaats van de lege defaults)."""
    timestamps = pd.date_range("2026-01-01", periods=24 * 12, freq="5min")  # 1 dag
    glucose = pd.DataFrame({"timestamp": timestamps, "mmol": [7.0] * len(timestamps)})
    treatments = pd.DataFrame(
        [
            {
                "timestamp": pd.Timestamp("2026-01-01 08:00"),
                "eventType": "Meal Bolus",
                "insulin": 4.0,
                "carbs": 40.0,
                "type": "",
                "absolute": None,
                "duration": None,
            },
            {
                "timestamp": pd.Timestamp("2026-01-01 12:00"),
                "eventType": "Correction Bolus",
                "insulin": 0.3,
                "carbs": None,
                "type": "SMB",
                "absolute": None,
                "duration": None,
            },
            {
                "timestamp": pd.Timestamp("2026-01-01 06:00"),
                "eventType": "Temp Basal",
                "insulin": None,
                "carbs": None,
                "type": "",
                "absolute": 2.0,
                "duration": 60,
            },
        ]
    )
    profile = {
        "name": "Default",
        "dia": 5.0,
        "basal": [{"minutes": 0, "value": 0.8}],
        "sens": [{"minutes": 0, "value": 2.8}],
        "carbratio": [{"minutes": 0, "value": 10.0}],
        "target_low": [{"minutes": 0, "value": 4.5}],
        "target_high": [{"minutes": 0, "value": 8.0}],
    }
    pdf_bytes = build_report_pdf(
        [SECTION_DAGOVERZICHT],
        glucose,
        {},
        date(2026, 1, 1),
        date(2026, 1, 1),
        treatments=treatments,
        profile=profile,
    )
    assert pdf_bytes.startswith(b"%PDF")
    assert _page_count(pdf_bytes) == 2  # cover + 1 dag


def test_report_config_uses_defaults_when_env_vars_unset(monkeypatch):
    for var in ("REPORT_INSULIN_TYPE", "REPORT_PUMP_TYPE", "REPORT_SENSOR_TYPE", "NIGHTSCOUT_URL"):
        monkeypatch.delenv(var, raising=False)
    config = _report_config()
    assert config["insulin_type"] == "Onbekend insulinetype"
    assert config["pump_type"] == "Onbekende pomp"
    assert config["sensor_type"] == "Onbekende sensor"
    assert config["nightscout_url"] == ""


def test_report_config_reads_env_vars_when_set(monkeypatch):
    monkeypatch.setenv("REPORT_INSULIN_TYPE", "Lyumjev 100U")
    monkeypatch.setenv("REPORT_PUMP_TYPE", "Omnipod DASH")
    monkeypatch.setenv("REPORT_SENSOR_TYPE", "Dexcom G7")
    monkeypatch.setenv("NIGHTSCOUT_URL", "https://example.com/")
    config = _report_config()
    assert config["insulin_type"] == "Lyumjev 100U"
    assert config["pump_type"] == "Omnipod DASH"
    assert config["sensor_type"] == "Dexcom G7"
    assert config["nightscout_url"] == "https://example.com"  # trailing slash gestript


def test_icon_asset_exists():
    icon_path = Path(__file__).parent.parent / "assets" / "icon.svg"
    assert icon_path.exists()
    assert icon_path.read_text(encoding="utf-8").strip().startswith("<svg")


@pytest.mark.parametrize("section", [SECTION_SUMMARY, SECTION_AGP, SECTION_DAGOVERZICHT, SECTION_EVENTS])
def test_all_sections_still_work_without_treatments_or_profile_args(section):
    """Achterwaartse compatibiliteit: treatments/profile zijn optioneel — een
    aanroep zoals vóór deze PR (zonder die argumenten) moet blijven werken."""
    glucose = _glucose_with_hypo_and_hyper_events() if section == SECTION_EVENTS else _sample_glucose()
    events_summary = {"Hypo Level 1": {"count": 1, "avg_duration_minutes": 25.0, "events_per_week": 2.3}}
    pdf_bytes = build_report_pdf(
        [section], glucose, events_summary if section == SECTION_EVENTS else {}, date(2026, 1, 1), date(2026, 1, 4)
    )
    assert pdf_bytes.startswith(b"%PDF")