"""Tests for marketing_intelligence.reporting.pdf_generator."""

from __future__ import annotations

from pathlib import Path
from typing import Any


from marketing_intelligence.core.models import TrendSignal
from marketing_intelligence.reporting.pdf_generator import (
    build_pdf,
    save_pdf_temp,
)

_MOD = "marketing_intelligence.reporting.pdf_generator"


# ──────────────────────────── fixtures ────────────────────────────────────────


def _minimal_sentiment(**overrides: object) -> dict[str, Any]:
    base: dict[str, Any] = dict(
        campaign_config_key="artist_track",
        run_id="run1",
        observed_at="2024-01-01T00:00:00Z",
        sentiment="positive",
        confidence=0.85,
        summary="Fans love it.",
        reasoning="High like rate.",
        how_sound_is_used="background melody",
        confidence_rationale="Multiple signals agree.",
    )
    base.update(overrides)
    # coerce TrendSignal objects to dicts so the generator receives plain dicts
    if "trend_signals" in base:
        base["trend_signals"] = [
            s.model_dump() if isinstance(s, TrendSignal) else s
            for s in base["trend_signals"]
        ]
    return base


# ──────────────────────────── build_pdf ───────────────────────────────────────


class TestBuildPdf:
    def test_creates_file(self, tmp_path: Path) -> None:
        out = tmp_path / "report.pdf"
        build_pdf(_minimal_sentiment(), out)
        assert out.exists()

    def test_pdf_starts_with_magic_bytes(self, tmp_path: Path) -> None:
        out = tmp_path / "report.pdf"
        build_pdf(_minimal_sentiment(), out)
        assert out.read_bytes()[:4] == b"%PDF"

    def test_non_empty_output(self, tmp_path: Path) -> None:
        out = tmp_path / "report.pdf"
        build_pdf(_minimal_sentiment(), out)
        assert out.stat().st_size > 1024

    def test_negative_sentiment(self, tmp_path: Path) -> None:
        out = tmp_path / "report.pdf"
        build_pdf(_minimal_sentiment(sentiment="negative", confidence=0.4), out)
        assert out.read_bytes()[:4] == b"%PDF"

    def test_neutral_sentiment(self, tmp_path: Path) -> None:
        out = tmp_path / "report.pdf"
        build_pdf(_minimal_sentiment(sentiment="neutral", confidence=0.6), out)
        assert out.read_bytes()[:4] == b"%PDF"

    def test_with_trend_signals(self, tmp_path: Path) -> None:
        signals = [
            TrendSignal(
                signal="Viral loop",
                evidence="10M views in 24h",
                supporting_video_ids=["v1", "v2", "v3"],
            )
        ]
        out = tmp_path / "report.pdf"
        build_pdf(_minimal_sentiment(trend_signals=signals), out)
        assert out.read_bytes()[:4] == b"%PDF"

    def test_with_many_trend_signals(self, tmp_path: Path) -> None:
        signals = [
            TrendSignal(signal=f"sig{i}", evidence="ev", supporting_video_ids=[f"v{i}"])
            for i in range(5)
        ]
        out = tmp_path / "report.pdf"
        build_pdf(_minimal_sentiment(trend_signals=signals), out)
        assert out.read_bytes()[:4] == b"%PDF"

    def test_with_hashtags(self, tmp_path: Path) -> None:
        out = tmp_path / "report.pdf"
        build_pdf(
            _minimal_sentiment(
                primary_hashtags=["dance", "viral", "fyp", "trending", "music"]
            ),
            out,
        )
        assert out.read_bytes()[:4] == b"%PDF"

    def test_with_detected_topics(self, tmp_path: Path) -> None:
        out = tmp_path / "report.pdf"
        build_pdf(
            _minimal_sentiment(detected_topics=["nostalgia", "summer", "party"]), out
        )
        assert out.read_bytes()[:4] == b"%PDF"

    def test_with_virality_factors(self, tmp_path: Path) -> None:
        out = tmp_path / "report.pdf"
        build_pdf(
            _minimal_sentiment(virality_factors=["fast tempo", "relatable lyrics"]), out
        )
        assert out.read_bytes()[:4] == b"%PDF"

    def test_empty_optional_lists(self, tmp_path: Path) -> None:
        out = tmp_path / "report.pdf"
        build_pdf(
            _minimal_sentiment(
                primary_hashtags=[],
                detected_topics=[],
                virality_factors=[],
                trend_signals=[],
            ),
            out,
        )
        assert out.read_bytes()[:4] == b"%PDF"

    def test_long_text_fields(self, tmp_path: Path) -> None:
        long_text = "word " * 200
        out = tmp_path / "report.pdf"
        build_pdf(
            _minimal_sentiment(
                summary=long_text,
                reasoning=long_text,
                how_sound_is_used=long_text,
                confidence_rationale=long_text,
            ),
            out,
        )
        assert out.read_bytes()[:4] == b"%PDF"

    def test_trend_signal_many_video_ids(self, tmp_path: Path) -> None:
        signals = [
            TrendSignal(
                signal="big",
                evidence="ev",
                supporting_video_ids=[f"v{i}" for i in range(20)],
            )
        ]
        out = tmp_path / "report.pdf"
        build_pdf(_minimal_sentiment(trend_signals=signals), out)
        assert out.read_bytes()[:4] == b"%PDF"


# ──────────────────────────── save_pdf_temp ──────────────────────────────────


class TestSavePdfTemp:
    def test_creates_temp_file(self) -> None:
        path = save_pdf_temp(_minimal_sentiment())
        p = Path(path)
        assert p.exists()
        p.unlink()

    def test_temp_file_is_valid_pdf(self) -> None:
        path = save_pdf_temp(_minimal_sentiment())
        p = Path(path)
        assert p.read_bytes()[:4] == b"%PDF"
        p.unlink()

    def test_temp_filename_has_prefix(self) -> None:
        path = save_pdf_temp(_minimal_sentiment())
        assert "artist_track" in Path(path).name
        Path(path).unlink()