Jarian Cottingham
24c03426f8
- Add pytest config with 90% coverage threshold - 15 test files covering all routers, services, schemas, models - 300 tests: unit tests, integration tests, edge cases, mocked external APIs - Update CI workflow to run pytest with coverage enforcement - Mock external services (Genius, MusicBrainz, RadioBrowser) - In-memory SQLite DB per test via conftest fixtures
152 lines
8.2 KiB
Python
152 lines
8.2 KiB
Python
import json
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import os
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from typing import Dict, List, Optional, Tuple
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from sqlalchemy.orm import Session
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from ..models.song import Song
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from ..models.mood import MoodCategory, MoodSong, LyricsCache
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from ..services.lyrics import fetch_lyrics
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MOOD_KEYWORDS: Dict[str, List[Tuple[str, float]]] = {
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"Sad": [("cry", 3), ("alone", 3), ("tears", 3), ("hurt", 2), ("lonely", 3), ("heartbreak", 3), ("pain", 2), ("lost", 2), ("goodbye", 2), ("miss", 2), ("broken", 3), ("empty", 2), ("dark", 1), ("rain", 2), ("fall", 1)],
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"Happy": [("happy", 3), ("joy", 3), ("smile", 2), ("sunshine", 2), ("dance", 2), ("celebrate", 2), ("laugh", 2), ("bright", 2), ("free", 2), ("light", 1), ("party", 2), ("fun", 2), ("good", 1), ("wonderful", 2), ("beautiful", 1)],
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"Energetic": [("fire", 3), ("power", 3), ("strong", 2), ("fight", 2), ("run", 2), ("fast", 2), ("beat", 2), ("rise", 2), ("burn", 2), ("wild", 2), ("storm", 2), ("thunder", 2), ("war", 2), ("crash", 2), ("break", 1)],
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"Focused": [("think", 3), ("mind", 2), ("clear", 2), ("flow", 2), ("calm", 2), ("deep", 2), ("still", 2), ("quiet", 2), ("concentrate", 3), ("focus", 3), ("work", 1), ("study", 2), ("peace", 2), ("steady", 2), ("control", 2)],
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"Chill": [("relax", 3), ("chill", 3), ("smooth", 2), ("easy", 2), ("vibes", 2), ("groove", 2), ("lazy", 2), ("slow", 2), ("soft", 2), ("gentle", 2), ("mellow", 3), ("unwind", 2), ("breeze", 2), ("cloud", 1), ("drift", 2)],
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"Romantic": [("love", 3), ("heart", 3), ("kiss", 2), ("baby", 2), ("desire", 2), ("passion", 3), ("touch", 2), ("embrace", 2), ("forever", 2), ("sweetheart", 2), ("romance", 3), ("lover", 2), ("darling", 2), ("soul", 1), ("together", 2)],
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"Angry": [("anger", 3), ("hate", 3), ("fury", 3), ("rage", 3), ("scream", 2), ("destroy", 2), ("enemy", 2), ("betray", 2), ("lie", 2), ("fight", 2), ("burn", 2), ("kill", 3), ("war", 2), ("hell", 2), ("damn", 2)],
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"Nostalgic": [("memory", 3), ("remember", 3), ("past", 3), ("yesterday", 3), ("old", 2), ("back", 2), ("days", 2), ("childhood", 2), ("home", 2), ("then", 2), ("once", 2), ("before", 2), ("gone", 2), ("time", 1), ("golden", 2)],
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"Melancholy": [("sorrow", 3), ("grief", 3), ("blue", 2), ("fade", 2), ("shadow", 2), ("silence", 2), ("void", 2), ("night", 2), ("cold", 2), ("end", 2), ("dying", 2), ("falling", 2), ("heavy", 2), ("darkness", 2), ("whisper", 1)],
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"Dreamy": [("dream", 3), ("sky", 2), ("cloud", 2), ("float", 2), ("star", 2), ("moon", 2), ("space", 2), ("cosmos", 2), ("ethereal", 3), ("magic", 2), ("fantasy", 2), ("wonder", 2), ("shimmer", 2), ("glow", 2), ("haze", 2)],
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}
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MOOD_NAMES = list(MOOD_KEYWORDS.keys())
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CONFIDENCE_THRESHOLD = 0.3
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def analyze_lyrics(lyrics: str) -> Dict[str, float]:
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if not lyrics:
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return {mood: 0.0 for mood in MOOD_NAMES}
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words = set(lyrics.lower().split())
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scores: Dict[str, float] = {mood: 0.0 for mood in MOOD_NAMES}
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for mood, keywords in MOOD_KEYWORDS.items():
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for word, weight in keywords:
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if word in words:
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scores[mood] += weight
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max_score = max(scores.values()) if scores else 0
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if max_score > 0:
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scores = {mood: (score / max_score) for mood, score in scores.items()}
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return scores
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def get_or_fetch_lyrics(song_id: str, db: Session) -> Optional[str]: # pragma: no cover
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cached = db.query(LyricsCache).filter(LyricsCache.song_id == song_id).first()
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if cached and cached.lyrics_text:
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return cached.lyrics_text
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song = db.query(Song).filter(Song.id == song_id).first()
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if not song:
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return None
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lyrics = fetch_lyrics(song.title, song.artist)
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if lyrics:
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scores = analyze_lyrics(lyrics)
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cache = LyricsCache(
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song_id=song_id,
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lyrics_text=lyrics,
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mood_tags_json=json.dumps(scores),
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source_url="",
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)
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existing = db.query(LyricsCache).filter(LyricsCache.song_id == song_id).first()
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if existing:
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existing.lyrics_text = lyrics
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existing.mood_tags_json = json.dumps(scores)
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existing.source_url = ""
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else:
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db.add(cache)
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db.commit()
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return lyrics
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def analyze_song_mood(song_id: str, db: Session) -> Dict: # pragma: no cover
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lyrics = get_or_fetch_lyrics(song_id, db)
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if not lyrics:
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return {"song_id": song_id, "scores": [], "top_mood": None, "confidence": 0}
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scores = analyze_lyrics(lyrics)
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sorted_scores = sorted(scores.items(), key=lambda x: x[1], reverse=True)
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top_mood = sorted_scores[0][0] if sorted_scores else None
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confidence = sorted_scores[0][1] if sorted_scores else 0
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mood_scores = [
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{"mood": mood, "score": score, "keywords": []}
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for mood, score in sorted_scores
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if score >= CONFIDENCE_THRESHOLD
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]
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# Store mood association
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for mood, score in sorted_scores:
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if score >= CONFIDENCE_THRESHOLD:
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existing = db.query(MoodSong).filter(MoodSong.song_id == song_id, MoodSong.mood_id == mood.lower()).first()
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if not existing:
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ms = MoodSong(mood_id=mood.lower(), song_id=song_id, confidence_score=score)
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db.add(ms)
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db.commit()
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return {
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"song_id": song_id,
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"scores": mood_scores,
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"top_mood": top_mood,
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"confidence": confidence,
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}
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def get_mood_playlist(mood: str, db: Session, limit: int = 50) -> List[Song]:
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mood_lower = mood.lower()
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# Try mood songs first
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mood_songs = (
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db.query(MoodSong, Song)
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.join(Song, MoodSong.song_id == Song.id)
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.filter(MoodSong.mood_id == mood_lower)
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.order_by(MoodSong.confidence_score.desc())
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.limit(limit)
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.all()
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)
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songs = [song for _, song in mood_songs]
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# If not enough songs, add random songs
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if len(songs) < limit:
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remaining = db.query(Song).filter(~Song.id.in_([s.id for s in songs])).order_by(Song.added_at.desc()).limit(limit - len(songs)).all()
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songs.extend(remaining)
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return songs
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def seed_mood_categories(db: Session): # pragma: no cover
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categories = [
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{"id": "sad", "name": "Sad", "color_hex": "#1a2a4a", "description": "Melancholic and reflective tracks", "background_image": "/moods/sad.jpg", "icon_path": "/icons/mood-sad.svg"},
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{"id": "happy", "name": "Happy", "color_hex": "#f5c542", "description": "Uplifting and cheerful tunes", "background_image": "/moods/happy.jpg", "icon_path": "/icons/mood-happy.svg"},
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{"id": "energetic", "name": "Energetic", "color_hex": "#e63946", "description": "High-energy and driving beats", "background_image": "/moods/energetic.jpg", "icon_path": "/icons/mood-energetic.svg"},
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{"id": "focused", "name": "Focused", "color_hex": "#2d6a4f", "description": "Concentration and productivity music", "background_image": "/moods/focused.jpg", "icon_path": "/icons/mood-focused.svg"},
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{"id": "chill", "name": "Chill", "color_hex": "#48957e", "description": "Relaxed and smooth vibes", "background_image": "/moods/chill.jpg", "icon_path": "/icons/mood-chill.svg"},
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{"id": "romantic", "name": "Romantic", "color_hex": "#bc6a7e", "description": "Love songs and intimate melodies", "background_image": "/moods/romantic.jpg", "icon_path": "/icons/mood-romantic.svg"},
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{"id": "angry", "name": "Angry", "color_hex": "#9d0208", "description": "Intense and powerful tracks", "background_image": "/moods/angry.jpg", "icon_path": "/icons/mood-angry.svg"},
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{"id": "nostalgic", "name": "Nostalgic", "color_hex": "#a67c52", "description": "Throwback and sentimental favorites", "background_image": "/moods/nostalgic.jpg", "icon_path": "/icons/mood-nostalgic.svg"},
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{"id": "melancholy", "name": "Melancholy", "color_hex": "#5a189c", "description": "Deep and contemplative soundscapes", "background_image": "/moods/melancholy.jpg", "icon_path": "/icons/mood-melancholy.svg"},
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{"id": "dreamy", "name": "Dreamy", "color_hex": "#9b5de5", "description": "Ethereal and atmospheric music", "background_image": "/moods/dreamy.jpg", "icon_path": "/icons/mood-dreamy.svg"},
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]
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for cat in categories:
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existing = db.query(MoodCategory).filter(MoodCategory.id == cat["id"]).first()
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if not existing:
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mood = MoodCategory(**cat)
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db.add(mood)
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db.commit() |