函数计算产品使用问题之如何处理GE 和POST请求

response.setHeader('Access-Control-Allow-Origin', '*');
response.setHeader('Access-Control-Allow-Methods', 'POST, GET, OPTIONS');
response.setHeader('Access-Control-Allow-Headers', 'Content-Type');

exports.handler = async (event, context) => {
    const requestMethod = event.httpMethod; // 获取请求方法（GET 或 POST）
    if (requestMethod === 'GET') {
        // 处理 GET 请求的逻辑
        return {
            statusCode: 200,
            body: JSON.stringify({ message: 'Hello, this is a GET request!' }),
        };
    } else if (requestMethod === 'POST') {
        // 处理 POST 请求的逻辑
        const body = JSON.parse(event.body); // 解析请求体中的 JSON 数据
        // ...
        return {
            statusCode: 200,
            body: JSON.stringify({ message: 'Hello, this is a POST request!' }),
        };
    } else {
        // 如果请求方法既不是 GET 也不是 POST，返回错误响应
        return {
            statusCode: 405,
            body: JSON.stringify({ error: 'Invalid request method' }),
        };
    }
};

import hashlib
import hmac
import base64
def getSignature(api_key, secret_key, method, path, headers, body):
    # 将请求参数按照字典序排序
    sorted_params = sorted(headers.items(), key=lambda x: x[0].lower())
    # 构建待签名的字符串
    string_to_sign = method + "\n" + path + "\n" + "".join([f"{k}:{v}\n" for k, v in sorted_params])
    # 使用 HMAC-SHA256 算法计算签名
    signature = hmac.new(secret_key.encode(), string_to_sign.encode(), hashlib.sha256).digest()
    # 对签名进行 Base64 编码
    signature_base64 = base64.b64encode(signature).decode()
    return signature_base64
# 示例用法
api_key = 'xxxxxxx'
secret_key = 'yyyyy'
method = 'GET'
path = '/lf/sendsms'
myHeaders = {
    'Content-Type': 'application/json',
    'Accept': 'application/json',
    'User-Agent': 'MyApp/1.0',
}
body = ''
signature = getSignature(api_key, secret_key, method, path, myHeaders, body)
print("Signature:", signature)

import numpy as np
import matplotlib.pyplot as plt
# 生成随机数据
data = np.random.randn(100)
# 计算均值和标准差
mean = np.mean(data)
std_dev = np.std(data)
# 绘制标准差图
plt.figure(figsize=(8, 6))
plt.hist(data, bins=20, density=True, alpha=0.7)
plt.axvline(mean, color='red', linestyle='dashed', linewidth=2)
plt.axvline(mean + std_dev, color='green', linestyle='dashed', linewidth=2)
plt.axvline(mean - std_dev, color='green', linestyle='dashed', linewidth=2)
plt.xlabel('Value')
plt.ylabel('Frequency')
plt.title('Standard Deviation Plot')
plt.legend(['Mean', 'Mean + Std Dev', 'Mean - Std Dev'])
plt.show()