双十一企业身份数据治理推荐

# 示例代码：使用Python进行数据清洗和标准化
import pandas as pd

def clean_data(df):
    df['email'] = df['email'].str.lower().str.strip()
    df['phone'] = df['phone'].str.replace(r'\D+', '', regex=True)
    return df

data = pd.read_csv('user_data.csv')
cleaned_data = clean_data(data)
cleaned_data.to_csv('cleaned_user_data.csv', index=False)

# 示例代码：使用Flask框架实现基本的身份验证
from flask import Flask, request, jsonify
from functools import wraps

app = Flask(__name__)

def require_auth(f):
    @wraps(f)
    def decorated(*args, **kwargs):
        auth = request.authorization
        if not auth or auth.username != 'admin' or auth.password != 'secret':
            return jsonify({"message": "Authentication required"}), 401
        return f(*args, **kwargs)
    return decorated

@app.route('/data')
@require_auth
def get_data():
    return jsonify({"data": "sensitive information"})

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

# 示例代码：使用Kafka进行实时数据处理
from kafka import KafkaConsumer, KafkaProducer

consumer = KafkaConsumer('user_data', bootstrap_servers=['localhost:9092'])
producer = KafkaProducer(bootstrap_servers=['localhost:9092'])

for message in consumer:
    processed_data = process_message(message.value)
    producer.send('processed_user_data', value=processed_data)

def process_message(data):
    # 数据处理逻辑
    return processed_data