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# 获取个性化排名 (AWS SDK)
<a name="get-personalized-rankings-sdk"></a>

以下代码示例显示了如何使用 AWS SDK 获得个性化排名的不同变体。

**Topics**
+ [获取个性化排名](#personalized-ranking-sdk-sample)
+ [在个性化排名中包含物品元数据](#getting-personalized-ranking-with-metadata-sdk)
+ [使用上下文元数据获得个性化排名](#personalized-ranking-contextual-metadata-example)

## 获取个性化排名
<a name="personalized-ranking-sdk-sample"></a>

以下代码展示了如何为用户获取个性化排名。指定用户的 ID 和要为用户排名的物品 ID 列表。物品 ID 必须位于您用于训练解决方案版本的数据中。这将返回已排名的建议列表。Amazon Personalize 会将列表中的第一个物品视为用户最感兴趣的物品。

------
#### [ SDK for Python (Boto3) ]

```
import boto3

personalizeRt = boto3.client('personalize-runtime')

response = personalizeRt.get_personalized_ranking(
    campaignArn = "Campaign arn",
    userId = "UserID",
    inputList = ['ItemID1','ItemID2']
)

print("Personalized Ranking")
for item in response['personalizedRanking']:
    print (item['itemId'])
```

------
#### [ SDK for Java 2.x ]

```
public static List<PredictedItem> getRankedRecs(PersonalizeRuntimeClient personalizeRuntimeClient,
                                                String campaignArn,
                                                String userId,
                                                ArrayList<String> items) {

    try {
        GetPersonalizedRankingRequest rankingRecommendationsRequest = GetPersonalizedRankingRequest.builder()
                .campaignArn(campaignArn)
                .userId(userId)
                .inputList(items)
                .build();
  
        GetPersonalizedRankingResponse recommendationsResponse =
                personalizeRuntimeClient.getPersonalizedRanking(rankingRecommendationsRequest);
        List<PredictedItem> rankedItems = recommendationsResponse.personalizedRanking();
        int rank = 1;
        for (PredictedItem item : rankedItems) {
            System.out.println("Item ranked at position " + rank + " details");
            System.out.println("Item Id is : " + item.itemId());
            System.out.println("Item score is : " + item.score());
            System.out.println("---------------------------------------------");
            rank++;
        }
        return rankedItems;
    } catch (PersonalizeRuntimeException e) {
        System.err.println(e.awsErrorDetails().errorMessage());
        System.exit(1);
    }
    return null;
}
```

------
#### [ SDK for JavaScript v3 ]

```
// Get service clients module and commands using ES6 syntax.
import { GetPersonalizedRankingCommand } from "@aws-sdk/client-personalize-runtime";
import { personalizeRuntimeClient } from "./libs/personalizeClients.js";
// Or, create the client here.
// const personalizeRuntimeClient = new PersonalizeRuntimeClient({ region: "REGION"});

// Set the ranking request parameters.
export const getPersonalizedRankingParam = {
  campaignArn: "CAMPAIGN_ARN" /* required */,
  userId: "USER_ID" /* required */,
  inputList: ["ITEM_ID_1", "ITEM_ID_2", "ITEM_ID_3", "ITEM_ID_4"],
};

export const run = async () => {
  try {
    const response = await personalizeRuntimeClient.send(
      new GetPersonalizedRankingCommand(getPersonalizedRankingParam),
    );
    console.log("Success!", response);
    return response; // For unit tests.
  } catch (err) {
    console.log("Error", err);
  }
};
run();
```

------

## 在个性化排名中包含物品元数据
<a name="getting-personalized-ranking-with-metadata-sdk"></a>

如果您在市场活动的建议中启用了元数据，则可以指定要包含在响应中的物品数据集元数据列。有关启用元数据的信息，请参阅[推荐中的物品元数据](campaigns.md#create-campaign-return-metadata)。

以下代码示例显示了如何在请求个性化排名时指定元数据列。

```
import boto3

personalizeRt = boto3.client('personalize-runtime')

response = personalizeRt.get_personalized_ranking(
    campaignArn = "Campaign arn",
    userId = "UserID",
    inputList = ['ItemID1','ItemID2'],
    metadataColumns = {
      "ITEMS": ['columnNameA','columnNameB']
    }
)

print("Personalized Ranking")
for item in response['personalizedRanking']:
    print (item['itemId'])
    print (item['metadata'])
```

## 使用上下文元数据获得个性化排名
<a name="personalized-ranking-contextual-metadata-example"></a>

使用以下代码，根据上下文元数据获取个性化排名。对于 `context`，对于每个键值对，提供元数据字段作为键，提供上下文数据作为值。在以下示例代码中，键为 `DEVICE`，值为 `mobile phone`。替换这些值，将 `Campaign ARN` 和 `User ID` 替换为您自己的值。此外，将 `inputList` 更改为用于训练解决方案的数据中的物品 ID 列表。Amazon Personalize 会将列表中的第一个物品视为用户最感兴趣的物品。

```
import boto3

personalizeRt = boto3.client('personalize-runtime')

response = personalizeRt.get_personalized_ranking(
    campaignArn = "Campaign ARN",
    userId = "User ID",
    inputList = ['ItemID1', 'ItemID2'],
    context = {
      'DEVICE': 'mobile phone'
    }
)

print("Personalized Ranking")
for item in response['personalizedRanking']:
  print(item['itemId'])
```