app.py

import os
import tempfile
import shutil
from zipfile import ZipFile
import logging
import psutil
from flask import Flask, request, jsonify, render_template, send_file
import multiprocessing
import subprocess

# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# Initialize Flask app
app = Flask(__name__)

connected_cpus = {"localhost": {"cpu_count": psutil.cpu_count(logical=False), "usage": 0.0}}

# Define the target function for multiprocessing
def target_function(script_path, folder_path):
    output_log = tempfile.TemporaryFile(mode='w+t')
    try:
        result = subprocess.run(['python', script_path], cwd=folder_path, stdout=output_log, stderr=subprocess.STDOUT)
        output_log.seek(0)
        log_output = output_log.read()
    except Exception as e:
        log_output = str(e)
    finally:
        output_log.close()
    return log_output

# Endpoint to handle file uploads and script execution
@app.route('/upload', methods=['POST'])
def handle_upload():
    try:
        if 'file' not in request.files or 'script_content' not in request.form:
            return jsonify({"status": "error", "message": "File or script content not provided"}), 400
        
        files = request.files.getlist('file')
        script_content = request.form['script_content']
        
        # Create a temporary directory to store uploaded files
        temp_dir = tempfile.mkdtemp()
        
        # Save the uploaded files to the temporary directory
        folder_path = os.path.join(temp_dir, 'uploaded_folder')
        os.makedirs(folder_path, exist_ok=True)
        for file_obj in files:
            file_path = os.path.join(folder_path, file_obj.filename)
            file_obj.save(file_path)
        
        # Save the script content to a file
        script_path = os.path.join(folder_path, 'user_script.py')
        with open(script_path, 'w') as script_file:
            script_file.write(script_content)
        
        # Run the script using multiprocessing
        log_output = run_script(script_path, folder_path)
        
        # Create a zip file of the entire folder
        zip_path = os.path.join(temp_dir, 'output_folder.zip')
        with ZipFile(zip_path, 'w') as zipf:
            for root, _, files in os.walk(folder_path):
                for file in files:
                    zipf.write(os.path.join(root, file), os.path.relpath(os.path.join(root, file), folder_path))
        
        return jsonify({"status": "success", "log_output": log_output, "download_url": f"/download/{os.path.basename(zip_path)}"})
    
    except Exception as e:
        logger.error(f"Error in handle_upload: {e}")
        return jsonify({"status": "error", "message": str(e)}), 500

@app.route('/download/<filename>')
def download_file(filename):
    try:
        return send_file(os.path.join(tempfile.gettempdir(), filename), as_attachment=True)
    except Exception as e:
        logger.error(f"Error in download_file: {e}")
        return jsonify({"status": "error", "message": str(e)}), 500

# Endpoint to get connected CPUs information
@app.route('/cpu_info', methods=['GET'])
def get_cpu_info():
    try:
        info = []
        for host, data in connected_cpus.items():
            info.append(f"{host}: {data['cpu_count']} CPUs, {data['usage']}% usage")
        return jsonify({"status": "success", "cpu_info": "\n".join(info)})
    except Exception as e:
        logger.error(f"Error in get_cpu_info: {e}")
        return jsonify({"status": "error", "message": str(e)}), 500

# Main interface
@app.route('/')
def index():
    return render_template('index.html')

def run_script(script_path, folder_path):
    # Collect all available CPUs including the local host CPU
    total_cpus = sum(cpu['cpu_count'] for cpu in connected_cpus.values()) + 1
    
    # Use multiprocessing to run the script
    with multiprocessing.Pool(total_cpus) as pool:
        log_outputs = pool.starmap(target_function, [(script_path, folder_path)] * total_cpus)

    return '\n'.join(log_outputs)

if __name__ == "__main__":
    app.run(host='0.0.0.0', port=7860, threaded=True)