汽车相关识别新年优惠活动

import pandas as pd
from sklearn.cluster import KMeans

# 假设我们有一个客户数据集
data = pd.read_csv('customer_data.csv')

# 使用KMeans算法进行客户分群
kmeans = KMeans(n_clusters=3)
data['cluster'] = kmeans.fit_predict(data[['age', 'income', 'purchase_history']])

# 根据分群结果推送个性化优惠
for cluster in data['cluster'].unique():
    cluster_data = data[data['cluster'] == cluster]
    # 推送相应的优惠信息

from flask import Flask, request, jsonify
import redis

app = Flask(__name__)
cache = redis.Redis(host='localhost', port=6379)

@app.route('/get_discount', methods=['GET'])
def get_discount():
    user_id = request.args.get('user_id')
    discount = cache.get(f'discount:{user_id}')
    if discount is None:
        # 从数据库中获取优惠信息
        discount = fetch_discount_from_db(user_id)
        cache.setex(f'discount:{user_id}', 3600, discount)  # 缓存1小时
    return jsonify({'discount': discount})

def fetch_discount_from_db(user_id):
    # 模拟从数据库中获取优惠信息
    return '10% off'

if __name__ == '__main__':
    app.run(debug=True)