容器

查询容器实例列表

1.接口说明

接口路径:/ai/openapi/v2/instance-service/task

请求方式:GET

请求数据类型:

接口描述:查询容器实例列表

2.请求消息

请求参数:

Headers:

名称	类型	必填	描述	示例
token	string	是	接口凭证	eyJhbGciOiJIUzI1...

参数:

名称	类型	必填	描述	示例
instanceServiceName	array	否	容器实例名称
limit	int	是	限制数量	20
sort	string	是	排序方式	desc
start	int	否	起始值,默认为0	0
status	string	否	状态	Running | Deploying | Waiting | Terminated | Failed | Completed
taskType	string	否	任务类型	ssh | jupyter | codeserver | rstudio

3.请求示例

cURL请求示例

curl --location --request GET 'https://scnet-demo.accloud.cn/ai/openapi/v2/instance-service/task' \
--header 'token: <Token>' \
--header 'Content-Type: application/json' \
--data '{
  "status": null,
  "instanceServiceName": null,
  "taskType": "ssh",
  "start": 0,
  "limit": 20,
  "sort": "desc"
}'

Java请求示例

import org.apache.http.HttpEntity;
import org.apache.http.client.methods.CloseableHttpResponse;
import org.apache.http.client.methods.HttpEntityEnclosingRequestBase;
import org.apache.http.entity.ContentType;
import org.apache.http.entity.StringEntity;
import org.apache.http.impl.client.CloseableHttpClient;
import org.apache.http.impl.client.HttpClientBuilder;
import org.apache.http.util.EntityUtils;

import java.net.*;

public class QueryInstanceServiceDemo {

    public static class HttpGetWithEntity extends HttpEntityEnclosingRequestBase {
        
        public final static String METHOD_NAME = "GET";

        @Override
        public String getMethod() {
            return METHOD_NAME;
        }
    }

    public static void main(String[] args) throws Exception {
        String token = "<Token>";
        String url = "https://ai01.xxx.com:65011/ai/openapi/v2/instance-service/task";
        String params = "{\n    \"status\": null,\n    \"instanceServiceName\": null,\n    \"taskType\": \"ssh\",\n    \"start\": 0,\n    \"limit\": 20,\n    \"sort\": \"desc\"\n}";
        CloseableHttpClient httpClient = HttpClientBuilder.create().build();
        HttpGetWithEntity e = new HttpGetWithEntity();
        e.setURI(new URI(url));
        e.setHeader("token", token);
        e.setHeader("Content-Type", "application/json");
        HttpEntity yourEntity = new StringEntity(params, ContentType.APPLICATION_JSON);
        e.setEntity(yourEntity);
        CloseableHttpResponse response = httpClient.execute(e);
        HttpEntity entity = response.getEntity();
        String body = "";
        if (entity != null) {
            body = EntityUtils.toString(entity, "UTF-8");
        }
        System.out.println(body);
        response.close();
    }
}

Python请求示例

import requests
import json

url = "https://scnet-demo.accloud.cn/ai/openapi/v2/instance-service/task"
payload = json.dumps({
  "status": None,
  "instanceServiceName": None,
  "taskType": "ssh",
  "start": 0,
  "limit": 20,
  "sort": "desc"
})
headers = {
  "token": "<Token>",
  "Content-Type": "application/json"
}

response = requests.request("GET", url, headers=headers, data=payload)
print(response.text)

4.响应消息

返回参数:

名称	类型	描述	示例
msg	string	信息	操作成功
code	string	状态码	0
data	array	任务列表
acceleratorType	string	加速器类型
cpuNumber	int	CPU数量
createTime	string	创建时间
currentIndex	int	容器当前索引
description	string	描述信息
duration	string	持续时间
endTime	string	结束时间
gpuNumber	int	GPU数量
headerNotebookId	string	容器实例关联的首个notebook任务ID
headerNotebookIp	string	容器实例关联的首个notebook任务IP
id	string	容器实例ID
imagePath	string	镜像路径
instanceServiceName	string	名称
ramSize	int	内存
remainingTime	string	剩余时间
resourceGroup	string	资源分组
resourceSpec	string	资源配置
startScriptActionScope	string	启用脚本范围
startScriptPath	string	启动脚本路径
startScriptContent	string	启动脚本的内容
startTime	string	开始时间
status	string	状态
taskNumber	string	实例任务数量
taskType	string	任务类型
tensorboardId	string	TB-ID
tensorboardPath	string	TB路径
timeoutLimit	string	超时时间
useStartScript	boolean	启用脚本
userName	string	用户名
version	string	镜像名称
mountInfoList	array
containerPortInfoList	array

返回示例:

{
  "msg":"success",
  "total":4,
  "code":"0",
  "data":[
    {
      "id":"530491fa7c8e47348f01de73e627a6a7",
      "headerNotebookId":"b54439dc621a434a88e8ab37d1897241",
      "instanceServiceName":"Instances_2204208761",
      "currentIndex":1,
      "gpuNumber":2,
      "cpuNumber":6,
      "ramSize":30720,
      "acceleratorType":"gpu",
      "resourceGroup":"TeslaM40",
      "resourceSpec":"6 核心; 2 加速器; 30.0G 内存",
      "taskNumber":1,
      "timeoutLimit":"unlimited",
      "userName":"demo",
      "version":"pytorch:1.2-py3.6-CUDA10.0",
      "imagePath":"10.0.35.26:5000/gpu/admin/base/pytorch:1.2-py3.6-CUDA10.0",
      "status":"Waiting",
      "taskType":"ssh",
      "description":"",
      "createTime":"2022-04-20 16:16:14",
      "startTime":null,
      "endTime":null,
      "duration":"--",
      "remainingTime":"--",
      "tensorboardId":null,
      "tensorboardPath":null,
      "mountInfoList":null,
      "containerPortInfoList":null,
      "useStartScript":false,
      "startScriptContent":"",
      "startScriptPath":null,
      "startScriptActionScope":"all",
      "headerNotebookIp":null
    }
  ]
}

5.错误码

错误码	说明
0	成功
10001	内部异常（其他异常）
10003	参数不全
10004	参数无效
10007	用户已被冻结
10008	权限不足
10009	没有权限访问接口
10010	文件校验失败
10011	文件过大
10012	连接中断