from __future__ import annotations

import csv
import io
import json
from pathlib import Path

import pytest

from yt_scraper.store import Store, VideoRef
from yt_scraper.parse import Segment
from yt_scraper import segments, export, analysis
from yt_scraper.render import build_filename_stem


SAMPLE_MD = """---
video_id: abc123
title: "Vaporwave and nostalgia"
channel: Alpha
upload_date: 20240115
duration: 600
views: 1234
likes: 56
tags: ["vaporwave", "nostalgia"]
thumbnail: http://img.test/abc.jpg
---

# Vaporwave and nostalgia

> [Ver en YouTube](https://www.youtube.com/watch?v=abc123)

## Transcripcion

### Intro (00:00)

**00:15** · Bienvenidos al video sobre vaporwave.
**00:32** · El vaporwave es una estetica muy interesante.

### Historia (01:15)

**01:15** · El vaporwave nacio en los 2010s.
**02:40** · dragon ball es un anime clasico.
"""


@pytest.fixture()
def store(tmp_path):
    s = Store(tmp_path / "t.db")
    s.upsert_channel("UC1", "@alpha", "Alpha", 1)
    s.upsert_videos([VideoRef("abc123", "UC1", "Vaporwave and nostalgia", "https://y/watch?v=abc123", "20240115", 600)])
    s.mark_done("abc123", "data/markdown/Alpha/x.md", "es", "auto", True)
    return s


def test_parse_markdown_metadata():
    parsed = segments.parse_markdown(SAMPLE_MD)
    assert parsed.metadata["video_id"] == "abc123"
    assert parsed.metadata["title"] == "Vaporwave and nostalgia"
    assert parsed.metadata["channel"] == "Alpha"
    assert len(parsed.segments) == 4
    assert abs(parsed.segments[0].start - 15.0) < 0.01
    assert "vaporwave" in parsed.segments[0].text.lower()
    chapters = parsed.chapters
    assert chapters[0]["title"] == "Intro"
    assert chapters[1]["title"] == "Historia"


def test_backfill_from_markdown(store, tmp_path):
    md = tmp_path / "md" / "Alpha" / "vapor.md"
    md.parent.mkdir(parents=True)
    md.write_text(SAMPLE_MD, encoding="utf-8")
    n = segments.backfill_from_markdown(store, tmp_path / "md")
    assert n == 1
    v = store.get_video("abc123")
    assert v.view_count == 1234
    assert v.like_count == 56
    assert json.loads(v.tags) == ["vaporwave", "nostalgia"]
    assert v.thumbnail == "http://img.test/abc.jpg"
    assert v.segments_json is not None
    segs = store.get_segments("abc123")
    assert len(segs) == 4
    # search now works
    hits = store.search_segments("vaporwave")
    assert len(hits) >= 1
    # idempotent
    n2 = segments.backfill_from_markdown(store, tmp_path / "md")
    assert n2 == 0


def test_ts_helpers():
    assert segments.ts_to_seconds("01:30") == 90.0
    assert segments.ts_to_seconds("1:02:03") == 3723.0


def test_export_json_csv(store, tmp_path):
    store.store_segments("abc123", [Segment(0.0, 2.0, "hello vaporwave")])
    store.update_video_metadata("abc123", view_count=1234, tags=["vaporwave"])
    j = export.export_json(store, "UC1", tmp_path / "out.json")
    data = json.loads(j.read_text(encoding="utf-8"))
    assert len(data["videos"]) == 1
    assert data["videos"][0]["video_id"] == "abc123"

    c = export.export_csv(store, "UC1", tmp_path / "out.csv")
    with open(c, encoding="utf-8") as f:
        reader = csv.DictReader(f)
        rows = list(reader)
    assert rows[0]["video_id"] == "abc123"
    assert rows[0]["view_count"] == "1234"


def test_export_srt(store, tmp_path):
    segs = [Segment(1.5, 3.5, "first line"), Segment(5.0, 7.0, "second line")]
    store.store_segments("abc123", segs)
    out = export.export_srt_video(store, "abc123", tmp_path / "x.srt")
    assert out is not None
    text = out.read_text(encoding="utf-8")
    assert "1\n" in text
    assert "00:00:01,500 --> 00:00:03,500" in text
    assert "first line" in text
    assert "second line" in text


def test_export_html(store, tmp_path):
    store.update_video_metadata("abc123", thumbnail="http://t.test/x.jpg", tags=["vaporwave"])
    out = export.export_html(store, "UC1", tmp_path / "g.html")
    html = out.read_text(encoding="utf-8")
    assert "abc123" in html
    assert "Gallery" in html


def test_word_frequency(store):
    segs = [
        Segment(0, 1, "vaporwave vaporwave nostalgia nostalgia nostalgia"),
        Segment(2, 3, "dragon dragon anime"),
    ]
    store.store_segments("abc123", segs)
    freq = analysis.word_frequency(store, "UC1", top=5)
    assert freq["nostalgia"] == 3
    assert freq["vaporwave"] == 2
    assert freq["dragon"] == 2
    # stopwords filtered
    assert "y" not in freq
    assert "the" not in freq


def test_term_timeline(store):
    segs = [Segment(0, 1, "vaporwave mentioned here")]
    store.store_segments("abc123", segs)
    tl = analysis.term_timeline(store, "vaporwave", "UC1")
    assert len(tl) == 1
    assert tl[0][0] == "2024-01"


def test_build_filename_stem():
    # callers pass already-normalized dates; stem uses them verbatim
    stem = build_filename_stem("2024-01-01", "Hola Mundo!", "{upload_date}_{slug}")
    assert stem == "2024-01-01_hola-mundo"