Initial commit - Navi.FM v3
This commit is contained in:
Collin Kasbergen
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import time
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import os
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import threading
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import subprocess
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from database import SessionLocal, Track
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from navidrome import navidrome_client
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from analyzer import analyze_audio
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from queue_manager import get_active_profile, set_active_profile
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import json
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import datetime
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def sync_tracks_loop():
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while True:
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try:
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if not navidrome_client.url:
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time.sleep(10)
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continue
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print("Syncing tracks from Navidrome...")
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songs = navidrome_client.get_random_songs(count=200)
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db = SessionLocal()
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added = 0
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for song in songs:
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# Check if song exists
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existing = db.query(Track).filter(Track.id == song["id"]).first()
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if not existing:
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new_track = Track(
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id=song["id"],
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title=song.get("title", "Unknown"),
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artist=song.get("artist", "Unknown"),
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album=song.get("album", "Unknown"),
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duration=song.get("duration", 0),
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path=song.get("path", "")
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)
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db.add(new_track)
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added += 1
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if added > 0:
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db.commit()
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db.close()
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print(f"Sync complete. Added {added} new tracks.")
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except Exception as e:
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print(f"Error syncing tracks: {e}")
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# Run every hour
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time.sleep(3600)
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def analyze_tracks_loop():
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while True:
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try:
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if not navidrome_client.url:
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time.sleep(10)
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continue
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db = SessionLocal()
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# Find an un-analyzed track
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track = db.query(Track).filter(Track.analyzed == False).first()
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if track:
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print(f"Analyzing track: {track.artist} - {track.title}")
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temp_path = f"/tmp/{track.id}.audio"
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# Download
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if navidrome_client.download_song(track.id, temp_path):
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# Analyze
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metadata = analyze_audio(temp_path)
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if metadata:
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track.bpm = metadata["bpm"]
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track.key = metadata["key"]
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track.energy = metadata["energy"]
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track.spectral_centroid = metadata["spectral_centroid"]
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track.onset_density = metadata["onset_density"]
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track.lufs = metadata["lufs"]
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track.analyzed = True
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db.commit()
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print("Analysis successful.")
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else:
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# Mark as analyzed anyway so we don't get stuck in a loop, or maybe add an error flag
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track.analyzed = True
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db.commit()
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print("Analysis failed, marked as analyzed to skip.")
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# Cleanup
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if os.path.exists(temp_path):
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os.remove(temp_path)
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else:
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print("Download failed.")
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else:
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# No tracks to analyze, sleep for a while
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time.sleep(60)
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db.close()
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except Exception as e:
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print(f"Error in analysis loop: {e}")
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time.sleep(60)
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def scheduler_loop():
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"""
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Checks the auto_pilot_schedule every minute and changes the profile if it matches the current time.
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"""
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while True:
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try:
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# Wait until the start of the next minute
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now = datetime.datetime.now()
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sleep_seconds = 60 - now.second
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time.sleep(sleep_seconds)
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# Now it's a new minute
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now = datetime.datetime.now()
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current_time_str = now.strftime("%H:%M")
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db = SessionLocal()
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from database import get_setting
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schedule_str = get_setting(db, "auto_pilot_schedule", "[]")
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db.close()
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schedule = json.loads(schedule_str)
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for rule in schedule:
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if rule.get("time") == current_time_str:
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target_profile = rule.get("profile")
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if target_profile:
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print(f"[Scheduler] Time is {current_time_str}. Switching profile to: {target_profile}")
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set_active_profile(target_profile)
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except Exception as e:
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print(f"Error in scheduler loop: {e}")
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time.sleep(60)
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def startup_manager_loop():
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"""
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Waits until at least 10 tracks have been analyzed before starting Liquidsoap.
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This prevents Liquidsoap from rapidly requesting /next and queuing the exact same track
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repeatedly when the database is empty or only has 1 track during initial setup.
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"""
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while True:
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try:
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db = SessionLocal()
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count = db.query(Track).filter(Track.analyzed == True).count()
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db.close()
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if count >= 10:
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print(f"[Startup Manager] {count} tracks analyzed. Starting Liquidsoap...")
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# Run supervisorctl to start liquidsoap
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subprocess.run(["supervisorctl", "start", "liquidsoap"], check=False)
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break
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else:
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print(f"[Startup Manager] Waiting for initial analysis... ({count}/10 tracks analyzed)")
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time.sleep(10)
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except Exception as e:
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print(f"Error in startup manager: {e}")
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time.sleep(10)
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def start_workers():
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t1 = threading.Thread(target=sync_tracks_loop, daemon=True)
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t2 = threading.Thread(target=analyze_tracks_loop, daemon=True)
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t3 = threading.Thread(target=scheduler_loop, daemon=True)
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t4 = threading.Thread(target=startup_manager_loop, daemon=True)
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t1.start()
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t2.start()
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t3.start()
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t4.start()
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