77 lines
2.9 KiB
Python
77 lines
2.9 KiB
Python
import argparse
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import subprocess
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import concurrent.futures
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import os
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from pathlib import Path
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from datetime import datetime
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import time
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import tomllib
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from utils import DEFAULT_DL_DIR, DEFAULT_JELLYFIN_DIR
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def run_workflow(imdb_id: str, dl_dir: str, jellyfin_dir: str, logs_dir: Path, errors_dir: Path):
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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log_file = logs_dir / f"{imdb_id}_{timestamp}.log"
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cmd = [
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"uv", "run", "workflow.py",
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imdb_id,
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"--dl-dir", dl_dir,
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"--jellyfin-dir", jellyfin_dir
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]
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print(f"Starting workflow for {imdb_id}... (Logging to {log_file})")
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with open(log_file, "w", encoding="utf-8") as f:
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process = subprocess.Popen(
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cmd,
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stdout=f,
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stderr=subprocess.STDOUT,
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text=True
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)
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process.wait()
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status = "SUCCESS" if process.returncode == 0 else f"FAILED (code {process.returncode})"
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if process.returncode != 0:
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error_file = errors_dir / log_file.name
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log_file.rename(error_file)
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print(f"[{status}] Workflow for {imdb_id} failed. Check {error_file} for details.")
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else:
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print(f"[{status}] Workflow for {imdb_id} completed. Check {log_file} for details.")
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return imdb_id, process.returncode
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def main():
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parser = argparse.ArgumentParser(description="Multithreading launcher for IMDB workflow.")
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parser.add_argument("imdb_ids", nargs="+", help="The IMDb IDs to process (e.g., tt38872297 tt0903747)")
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parser.add_argument("--dl-dir", type=str, default=DEFAULT_DL_DIR, help="The qBittorrent download directory")
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parser.add_argument("--jellyfin-dir", type=str, default=DEFAULT_JELLYFIN_DIR, help="The base Jellyfin library directory")
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parser.add_argument("--workers", type=int, default=4, help="Number of concurrent workers")
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parser.add_argument("--delay", type=float, default=5.0, help="Delay in seconds between starting each workflow")
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args = parser.parse_args()
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logs_dir = Path("logs")
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logs_dir.mkdir(exist_ok=True)
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errors_dir = Path("errors")
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errors_dir.mkdir(exist_ok=True)
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print(f"Launching processing for {len(args.imdb_ids)} IMDB IDs across {args.workers} workers...")
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with concurrent.futures.ThreadPoolExecutor(max_workers=args.workers) as executor:
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futures = []
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for i, imdb_id in enumerate(args.imdb_ids):
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if i > 0:
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time.sleep(args.delay)
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futures.append(
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executor.submit(run_workflow, imdb_id, args.dl_dir, args.jellyfin_dir, logs_dir, errors_dir)
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)
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for future in concurrent.futures.as_completed(futures):
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try:
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future.result()
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except Exception as e:
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print(f"Worker generated an exception: {e}")
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print("All tasks finished.")
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if __name__ == "__main__":
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main()
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