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oscarwang2
commited on
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36ca81e
1
Parent(s):
1dcef25
Update app.py
Browse files
app.py
CHANGED
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import os
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import subprocess
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import tempfile
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import shutil
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from zipfile import ZipFile
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import logging
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import json
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import psutil
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import multiprocessing
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from flask import Flask, request, jsonify, render_template, send_file
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# Configure logging
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logging.basicConfig(level=logging.INFO)
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@@ -18,101 +17,94 @@ app = Flask(__name__)
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connected_cpus = {"localhost": {"cpu_count": psutil.cpu_count(logical=False), "usage": 0.0}}
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#
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def update_cpu_usage_handler():
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data = request.get_json()
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host = data['host']
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usage = data['usage']
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if host in connected_cpus:
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connected_cpus[host]['usage'] = usage
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logger.info(f"Updated CPU usage for {host}: {usage}%")
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return jsonify({"status": "success"})
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# Function to run the provided Python script using multiprocessing
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def run_script(script_content, folder_path):
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script_path = os.path.join(folder_path, 'user_script.py')
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with open(script_path, 'w') as script_file:
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script_file.write(script_content)
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def target_function(cpu_id):
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output_log = tempfile.TemporaryFile(mode='w+t')
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try:
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result = subprocess.run(['python', script_path], cwd=folder_path, stdout=output_log, stderr=subprocess.STDOUT)
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output_log.seek(0)
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log_output = output_log.read()
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except Exception as e:
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log_output = str(e)
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finally:
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output_log.close()
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return log_output
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# Collect all available CPUs including the local host CPU
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total_cpus = sum(cpu['cpu_count'] for cpu in connected_cpus.values())
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# Run the script using multiprocessing
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with multiprocessing.Pool(total_cpus) as pool:
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log_outputs = pool.map(target_function, range(total_cpus))
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return '\n'.join(log_outputs)
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#
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@app.route('/upload', methods=['POST'])
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def handle_upload():
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@app.route('/download/<filename>')
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def download_file(filename):
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# Endpoint to get connected CPUs information
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@app.route('/cpu_info', methods=['GET'])
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def get_cpu_info():
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# Main interface
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@app.route('/')
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def index():
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return render_template('index.html')
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if __name__ == "__main__":
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app.run(host='0.0.0.0', port=7860, threaded=True)
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import os
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import tempfile
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import shutil
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from zipfile import ZipFile
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import logging
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import psutil
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from flask import Flask, request, jsonify, render_template, send_file
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import multiprocessing
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import subprocess
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# Configure logging
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logging.basicConfig(level=logging.INFO)
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connected_cpus = {"localhost": {"cpu_count": psutil.cpu_count(logical=False), "usage": 0.0}}
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# Define the target function for multiprocessing
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def target_function(script_path, folder_path):
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output_log = tempfile.TemporaryFile(mode='w+t')
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try:
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result = subprocess.run(['python', script_path], cwd=folder_path, stdout=output_log, stderr=subprocess.STDOUT)
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output_log.seek(0)
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log_output = output_log.read()
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except Exception as e:
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log_output = str(e)
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finally:
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output_log.close()
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return log_output
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# Endpoint to handle file uploads and script execution
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@app.route('/upload', methods=['POST'])
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def handle_upload():
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try:
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if 'file' not in request.files or 'script_content' not in request.form:
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return jsonify({"status": "error", "message": "File or script content not provided"}), 400
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files = request.files.getlist('file')
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script_content = request.form['script_content']
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# Create a temporary directory to store uploaded files
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temp_dir = tempfile.mkdtemp()
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# Save the uploaded files to the temporary directory
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folder_path = os.path.join(temp_dir, 'uploaded_folder')
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os.makedirs(folder_path, exist_ok=True)
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for file_obj in files:
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file_path = os.path.join(folder_path, file_obj.filename)
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file_obj.save(file_path)
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# Save the script content to a file
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script_path = os.path.join(folder_path, 'user_script.py')
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with open(script_path, 'w') as script_file:
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script_file.write(script_content)
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# Run the script using multiprocessing
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log_output = run_script(script_path, folder_path)
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# Create a zip file of the entire folder
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zip_path = os.path.join(temp_dir, 'output_folder.zip')
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with ZipFile(zip_path, 'w') as zipf:
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for root, _, files in os.walk(folder_path):
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for file in files:
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zipf.write(os.path.join(root, file), os.path.relpath(os.path.join(root, file), folder_path))
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return jsonify({"status": "success", "log_output": log_output, "download_url": f"/download/{os.path.basename(zip_path)}"})
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except Exception as e:
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logger.error(f"Error in handle_upload: {e}")
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return jsonify({"status": "error", "message": str(e)}), 500
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@app.route('/download/<filename>')
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def download_file(filename):
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try:
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return send_file(os.path.join(tempfile.gettempdir(), filename), as_attachment=True)
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except Exception as e:
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logger.error(f"Error in download_file: {e}")
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return jsonify({"status": "error", "message": str(e)}), 500
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# Endpoint to get connected CPUs information
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@app.route('/cpu_info', methods=['GET'])
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def get_cpu_info():
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try:
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info = []
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for host, data in connected_cpus.items():
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info.append(f"{host}: {data['cpu_count']} CPUs, {data['usage']}% usage")
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return jsonify({"status": "success", "cpu_info": "\n".join(info)})
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except Exception as e:
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logger.error(f"Error in get_cpu_info: {e}")
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return jsonify({"status": "error", "message": str(e)}), 500
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# Main interface
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@app.route('/')
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def index():
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return render_template('index.html')
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def run_script(script_path, folder_path):
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# Collect all available CPUs including the local host CPU
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total_cpus = sum(cpu['cpu_count'] for cpu in connected_cpus.values()) + 1
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# Use multiprocessing to run the script
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with multiprocessing.Pool(total_cpus) as pool:
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log_outputs = pool.starmap(target_function, [(script_path, folder_path)] * total_cpus)
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return '\n'.join(log_outputs)
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if __name__ == "__main__":
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app.run(host='0.0.0.0', port=7860, threaded=True)
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