import time
import subprocess
import json
import os
from sqlalchemy.orm import Session
from . import models, database

# Base directory for data
BASE_DATA_DIR = "/home/asf/testarena"
if os.name == 'nt':
    BASE_DATA_DIR = "d:/ASF - course/ASF_01/ASF_tools/asf-pc-server/testarena_pc_backend/testarena_data"

def update_json_status(queue_id, task_id, status, result=None):
    queue_dir = os.path.join(BASE_DATA_DIR, queue_id)
    status_file = os.path.join(queue_dir, "queue_status.json")
    if os.path.exists(status_file):
        with open(status_file, 'r') as f:
            data = json.load(f)
        
        if task_id:
            data["tasks"][task_id] = status
        else:
            data["status"] = status
            
        if result:
            data["results"] = data.get("results", {})
            data["results"][task_id] = result
            
        with open(status_file, 'w') as f:
            json.dump(data, f, indent=4)

def run_command_with_logging(cmd, log_file, cwd=None, env=None):
    """Runs a command, logs output to file and stdout."""
    with open(log_file, "a") as f:
        process = subprocess.Popen(
            cmd,
            stdout=subprocess.PIPE,
            stderr=subprocess.STDOUT,
            shell=True,
            text=True,
            cwd=cwd,
            env=env
        )
        for line in process.stdout:
            print(line, end="")
            f.write(line)
            f.flush()
        process.wait()
        return process.returncode

def run_worker():
    print("Worker started...")
    while True:
        db = database.SessionLocal()
        try:
            # Get next waiting queue
            queue = db.query(models.Queue).filter(models.Queue.status == "Waiting").order_by(models.Queue.created_at).first()
            
            if queue:
                print(f"Processing queue: {queue.id} (Branch: {queue.source})")
                queue.status = "Running"
                update_json_status(queue.id, None, "Running")
                db.commit()
                
                queue_dir = os.path.join(BASE_DATA_DIR, queue.id)
                os.makedirs(queue_dir, exist_ok=True)
                queue_log = os.path.join(queue_dir, "queue_log.txt")
                
                # 0- Checkout branch
                print(f"Checking out branch: {queue.source}")
                checkout_cmd = f"./TPF/gitea_repo_controller.sh checkout {queue.source}"
                run_command_with_logging(checkout_cmd, queue_log)
                
                # 1-5 Build software
                print("Building software...")
                # We need to source the IDF export script and then build. 
                # Using a single shell command to maintain environment.
                build_cmd = f"bash -c 'source $HOME/esp/esp-idf/export.sh && cd TPF/Sensor_hub_repo && idf.py build && idf.py qemu'"
                run_command_with_logging(build_cmd, queue_log)
                
                # 9- Loop for each task
                tasks = db.query(models.Task).filter(models.Task.queue_id == queue.id, models.Task.status == "Waiting").all()
                
                for task in tasks:
                    # Check if queue was aborted mid-way
                    db.refresh(queue)
                    if queue.status == "Aborted":
                        break
                        
                    print(f"Running task: {task.id}")
                    task.status = "Running"
                    update_json_status(queue.id, task.id, "Running")
                    db.commit()
                    
                    try:
                        # Run scenario_execution.py queue_id scenario_path task_id
                        # The user said it's in TPF/scenario_execution.py
                        script_path = "./TPF/scenario_execution.py"
                        # Use the same python environment
                        cmd = f"python3 {script_path} {queue.id} {task.scenario_path} {task.id}"
                        
                        # We want to capture this in the task log too
                        task_dir = os.path.join(queue_dir, task.id)
                        os.makedirs(task_dir, exist_ok=True)
                        task_log = os.path.join(task_dir, f"{task.id}-logging.html")
                        
                        # For now, let's just log to stdout and the queue log
                        # scenario_execution.py already generates its own reports.
                        ret = run_command_with_logging(cmd, queue_log)
                        
                        if ret == 0:
                            task.status = "Finished"
                        else:
                            task.status = "Error"
                        
                        # Try to find the summary if it exists
                        summary_path = os.path.join(task_dir, "final_summary.json")
                        if os.path.exists(summary_path):
                            with open(summary_path, 'r') as f:
                                task.result = json.load(f)
                        
                        update_json_status(queue.id, task.id, task.status, task.result)
                        
                    except Exception as e:
                        print(f"Error running task {task.id}: {e}")
                        task.status = "Error"
                        update_json_status(queue.id, task.id, "Error")
                    
                    db.commit()
                
                if queue.status != "Aborted":
                    queue.status = "Finished"
                    update_json_status(queue.id, None, "Finished")
                    db.commit()
                    
            time.sleep(5) # Poll every 5 seconds
        except Exception as e:
            print(f"Worker error: {e}")
            time.sleep(10)
        finally:
            db.close()

if __name__ == "__main__":
    run_worker()