智能动态编码双11优惠活动

import random
import string

def generate_discount_code(length=8):
    characters = string.ascii_uppercase + string.digits
    return ''.join(random.choice(characters) for _ in range(length))

def assign_discount_code(user_id):
    # 假设根据用户ID的奇偶性分配不同类型的优惠码
    if user_id % 2 == 0:
        return "EVEN" + generate_discount_code()
    else:
        return "ODD" + generate_discount_code()

# 示例调用
user_id = 12345
discount_code = assign_discount_code(user_id)
print(f"User {user_id} gets discount code: {discount_code}")

import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier

# 假设已有用户行为数据
data = pd.read_csv('user_behavior_data.csv')

# 数据预处理
X = data[['age', 'purchase_history', 'click_count']]
y = data['discount_preference']

# 划分训练集和测试集
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

# 训练模型
model = RandomForestClassifier()
model.fit(X_train, y_train)

# 预测并生成优惠码
def generate_optimal_discount_code(user_features):
    prediction = model.predict([user_features])
    if prediction == 'high':
        return "HIGHSALE" + generate_discount_code()
    else:
        return "REGULAR" + generate_discount_code()

# 示例调用
user_features = [25, 10, 50]  # 假设的用户特征
optimal_code = generate_optimal_discount_code(user_features)
print(f"Optimal discount code for user features {user_features}: {optimal_code}")