Python调用阿里云接口，实现数据清洗与异常监控功能

import requests
import json

# 设置阿里云DataWorks API的URL和参数
url = 'https://api.dataworks.aliyuncs.com/'
headers = {'Content-Type': 'application/json'}

# 设置需要清洗的数据集的名称和ID
project_name = 'your_project_name'
project_id = 'your_project_id'
data_set_name = 'your_data_set_name'
data_set_id = 'your_data_set_id'

# 设置清洗规则，比如删除含有缺失值的行
cleaning_rule = {
    "action": "DELETE",
    "columnIndices": [1, 2],
    "condition": "$col2 == ''"
}

data = {
    "projectName": project_name,
    "projectIdentifier": project_id,
    "content": json.dumps({
        "action": "CreateOrUpdateCleaningRule",
        "parameters": {
            "projectName": project_name,
            "projectIdentifier": project_id,
            "nodeId": data_set_id,
            "cleaningRuleType": "ALL",
            "cleaningRuleName": "cleaning_rule",
            "cleaningRuleDescription": "Data Cleaning Rule",
            "cleaningRuleScriptContent": json.dumps(cleaning_rule)
        }
    })
}

# 调用阿里云DataWorks接口进行数据清洗
response = requests.post(url, headers=headers, data=json.dumps(data))
print(response.json())

import requests
import json

# 设置阿里云CloudMonitor API的URL和参数
url = 'http://metrics.aliyuncs.com/'
headers = {'Content-Type': 'application/json'}

# 设置需要监控的指标和阈值
metric = 'your_metric'
namespace = 'your_namespace'
dimensions = [{'instanceId': 'your_instance_id'}]
threshold = {
    "times": 1,
    "value": 100
}

data = {
    "Action": "CreateAlarm",
    "Product": "cms",
    "Version": "2019-01-01",
    "MetricList": [{
        "MetricName": metric,
        "Namespace": namespace,
        "Dimensions": dimensions
    }],
    "AlarmName": "alarm_name",
    "AlarmDesc": "Alarm Description",
    "AlarmActions": ["your_action"],
    "Thresholds": [threshold]
}

# 调用阿里云CloudMonitor接口进行异常监控
response = requests.post(url, headers=headers, data=json.dumps(data))
print(response.json())