import os
import json
# import pytest  <-- Removed
from datetime import datetime, timedelta
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from backend.app.models import Base, PlayHistory, Track, Artist
from backend.app.services.stats_service import StatsService

# Setup Test Database
# @pytest.fixture <-- Removed
def db_session():
    engine = create_engine("sqlite:///:memory:")
    Base.metadata.create_all(engine)
    Session = sessionmaker(bind=engine)
    session = Session()
    yield session
    session.close()

def seed_data(db):
    """
    Seeds the database with specific patterns to verify metrics.
    Pattern:
    - High Energy/Happy Session (Morning)
    - Low Energy/Sad Session (Night)
    - Skips
    - Repeats
    """
    
    # 1. Create Artists
    a1 = Artist(id="a1", name="The Hype Men", genres=["pop", "dance"])
    a2 = Artist(id="a2", name="Sad Bois", genres=["indie", "folk"])
    a3 = Artist(id="a3", name="Mozart", genres=["classical"])
    db.add_all([a1, a2, a3])
    
    # 2. Create Tracks
    # High Energy, High Valence, Fast
    t1 = Track(
        id="t1", name="Party Anthem", album="Hype Vol 1", duration_ms=180000,
        popularity=80, energy=0.9, valence=0.9, danceability=0.8, tempo=140.0, acousticness=0.1, instrumentalness=0.0,
        key=0, mode=1 # C Major
    )
    t1.artists.append(a1)
    
    # Low Energy, Low Valence, Slow
    t2 = Track(
        id="t2", name="Rainy Day", album="Sad Vol 1", duration_ms=240000,
        popularity=20, energy=0.2, valence=0.1, danceability=0.3, tempo=80.0, acousticness=0.9, instrumentalness=0.0,
        key=9, mode=0 # A Minor
    )
    t2.artists.append(a2)
    
    # Classical (Instrumental)
    t3 = Track(
        id="t3", name="Symphony 40", album="Classics", duration_ms=300000,
        popularity=50, energy=0.4, valence=0.5, danceability=0.1, tempo=110.0, acousticness=0.8, instrumentalness=0.9,
        key=5, mode=0
    )
    t3.artists.append(a3)

    db.add_all([t1, t2, t3])
    db.commit()

    # 3. Create History
    base_time = datetime(2023, 11, 1, 8, 0, 0) # Morning
    
    plays = []
    
    # SESSION 1: Morning Hype (3 plays of t1)
    # 08:00
    plays.append(PlayHistory(track_id="t1", played_at=base_time, context_uri="spotify:playlist:morning"))
    # 08:04 (4 min gap)
    plays.append(PlayHistory(track_id="t1", played_at=base_time + timedelta(minutes=4), context_uri="spotify:playlist:morning"))
    # 08:08 
    plays.append(PlayHistory(track_id="t1", played_at=base_time + timedelta(minutes=8), context_uri="spotify:playlist:morning"))
    
    # GAP > 20 mins -> New Session
    
    # SESSION 2: Night Sadness (t2, t2, t3)
    # 22:00
    night_time = datetime(2023, 11, 1, 22, 0, 0)
    plays.append(PlayHistory(track_id="t2", played_at=night_time, context_uri="spotify:album:sad"))
    
    # SKIP SIMULATION: t2 played at 22:00, next play at 22:00:20 (20s later). 
    # Duration is 240s. 20s < 230s. This is a skip.
    # But wait, logic says "boredom skip". 
    # If I play t2 at 22:00.
    # And play t3 at 22:00:40. 
    # Diff = 40s. 40 < (240 - 10). Yes, Skip.
    plays.append(PlayHistory(track_id="t3", played_at=night_time + timedelta(seconds=40), context_uri="spotify:album:sad"))
    
    # Finish t3 (5 mins)
    plays.append(PlayHistory(track_id="t3", played_at=night_time + timedelta(seconds=40) + timedelta(minutes=5, seconds=10), context_uri="spotify:album:sad"))

    db.add_all(plays)
    db.commit()

def test_stats_generation(db_session):
    seed_data(db_session)
    stats_service = StatsService(db_session)
    
    start = datetime(2023, 11, 1, 0, 0, 0)
    end = datetime(2023, 11, 2, 0, 0, 0)
    
    report = stats_service.generate_full_report(start, end)
    
    print("\n--- GENERATED REPORT ---")
    print(json.dumps(report, indent=2, default=str))
    print("------------------------\n")
    
    # Assertions
    
    # 1. Volume
    assert report["volume"]["total_plays"] == 6
    assert report["volume"]["unique_tracks"] == 3
    # Top track should be t1 (3 plays)
    assert report["volume"]["top_tracks"][0]["name"] == "Party Anthem"
    
    # 2. Time
    # 3 plays in morning (8am), 3 plays at night (22pm)
    assert report["time_habits"]["part_of_day"]["morning"] == 3
    assert report["time_habits"]["part_of_day"]["night"] == 0 # 22:00 is "evening" in buckets (18-23)
    assert report["time_habits"]["part_of_day"]["evening"] == 3
    
    # 3. Sessions
    # Should be 2 sessions (gap between 08:08 and 22:00)
    assert report["sessions"]["count"] == 2
    
    # 4. Skips
    # 1 skip detected (t2 -> t3 gap was 40s vs 240s duration)
    assert report["skips"]["total_skips"] == 1
    
    # 5. Vibe & Clustering
    # Should have cluster info
    assert "clusters" in report["vibe"]
    # Check harmonic
    assert report["vibe"]["harmonic_profile"]["major_pct"] > 0
    # Check tempo zones (t1=140=Hype, t2=80=Chill, t3=110=Groove)
    # 3x t1 (Hype), 1x t2 (Chill), 2x t3 (Groove)
    # Total 6. Hype=0.5, Chill=0.17, Groove=0.33
    zones = report["vibe"]["tempo_zones"]
    assert zones["hype"] == 0.5
    
    # 6. Context
    # Morning = Playlist (3), Night = Album (3) -> 50/50
    assert report["context"]["type_breakdown"]["playlist"] == 0.5
    assert report["context"]["type_breakdown"]["album"] == 0.5

if __name__ == "__main__":
    # Manually run if executed as script
    engine = create_engine("sqlite:///:memory:")
    Base.metadata.create_all(engine)
    Session = sessionmaker(bind=engine)
    session = Session()
    test_stats_generation(session)