官方协议

import pandas as pd import numpy as np import requests def collect_data(api_url): response = requests.get(api_url) data = response.json() df = pd.DataFrame(data) return df # Example API URL for data collection api_url = "https://example.com/api/system_status" data = collect_data(api_url) from sklearn.ensemble import IsolationForest def detect_anomalies(data): model = IsolationForest(contamination=0.01) model.fit(data) data['anomaly'] = model.predict(data) anomalies = data[data['anomaly'] == -1] return anomalies anomalies = detect_anomalies(data) from twilio.rest import Client def send_alert(anomalies): if not anomalies.empty: account_sid = 'your_account_sid' auth_token = 'your_auth_token' client = Client(account_sid, auth_token) message = client.messages.create( body=f'Anomalies detected: {anomalies}', from_='+1234567890', to='+0987654321' ) print(message.sid) send_alert(anomalies) from flask import Flask, render_template import pandas as pd app = Flask(__name__) @app.route('/') def index(): data = collect_data(api_url) anomalies = detect_anomalies(data) return render_template('index.html', tables=[data.to_html(classes='data', header="true"), anomalies.to_html(classes='data', header="true")]) if __name__ == '__main__': app.run(debug=True) from apscheduler.schedulers.blocking import BlockingScheduler scheduler = BlockingScheduler() @scheduler.scheduled_job('interval', minutes=5) def scheduled_job(): data = collect_data(api_url) anomalies = detect_anomalies(data) send_alert(anomalies) scheduler.start() TechGuardian Dashboard

System Status

Collected Data

Detected Anomalies