There are more AWS SDK examples available in the [AWS Doc SDK Examples](https://github.com/awsdocs/aws-doc-sdk-examples) GitHub repo.

# Use `DetectSentiment` with an AWS SDK or CLI
<a name="comprehend_example_comprehend_DetectSentiment_section"></a>

The following code examples show how to use `DetectSentiment`.

Action examples are code excerpts from larger programs and must be run in context. You can see this action in context in the following code example: 
+  [Detect document elements](comprehend_example_comprehend_Usage_DetectApis_section.md) 

------
#### [ .NET ]

**SDK for .NET**  
 There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/dotnetv3/Comprehend/#code-examples). 

```
    using System;
    using System.Threading.Tasks;
    using Amazon.Comprehend;
    using Amazon.Comprehend.Model;

    /// <summary>
    /// This example shows how to detect the overall sentiment of the supplied
    /// text using the Amazon Comprehend service.
    /// </summary>
    public static class DetectSentiment
    {
        /// <summary>
        /// This method calls the DetetectSentimentAsync method to analyze the
        /// supplied text and determine the overal sentiment.
        /// </summary>
        public static async Task Main()
        {
            string text = "It is raining today in Seattle";

            var comprehendClient = new AmazonComprehendClient(Amazon.RegionEndpoint.USWest2);

            // Call DetectKeyPhrases API
            Console.WriteLine("Calling DetectSentiment");
            var detectSentimentRequest = new DetectSentimentRequest()
            {
                Text = text,
                LanguageCode = "en",
            };
            var detectSentimentResponse = await comprehendClient.DetectSentimentAsync(detectSentimentRequest);
            Console.WriteLine($"Sentiment: {detectSentimentResponse.Sentiment}");
            Console.WriteLine("Done");
        }
    }
```
+  For API details, see [DetectSentiment](https://docs.aws.amazon.com/goto/DotNetSDKV3/comprehend-2017-11-27/DetectSentiment) in *AWS SDK for .NET API Reference*. 

------
#### [ CLI ]

**AWS CLI**  
**To detect the sentiment of an input text**  
The following `detect-sentiment` example analyzes the input text and returns an inference of the prevailing sentiment (`POSITIVE`, `NEUTRAL`, `MIXED`, or `NEGATIVE`).  

```
aws comprehend detect-sentiment \
    --language-code en \
    --text "It is a beautiful day in Seattle"
```
Output:  

```
{
    "Sentiment": "POSITIVE",
    "SentimentScore": {
        "Positive": 0.9976957440376282,
        "Negative": 9.653854067437351e-05,
        "Neutral": 0.002169104292988777,
        "Mixed": 3.857641786453314e-05
    }
}
```
For more information, see [Sentiment](https://docs.aws.amazon.com/comprehend/latest/dg/how-sentiment.html) in the *Amazon Comprehend Developer Guide*  
+  For API details, see [DetectSentiment](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehend/detect-sentiment.html) in *AWS CLI Command Reference*. 

------
#### [ Java ]

**SDK for Java 2.x**  
 There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/javav2/example_code/comprehend#code-examples). 

```
import software.amazon.awssdk.regions.Region;
import software.amazon.awssdk.services.comprehend.ComprehendClient;
import software.amazon.awssdk.services.comprehend.model.ComprehendException;
import software.amazon.awssdk.services.comprehend.model.DetectSentimentRequest;
import software.amazon.awssdk.services.comprehend.model.DetectSentimentResponse;

/**
 * Before running this Java V2 code example, set up your development
 * environment, including your credentials.
 *
 * For more information, see the following documentation topic:
 *
 * https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/get-started.html
 */
public class DetectSentiment {
    public static void main(String[] args) {
        String text = "Amazon.com, Inc. is located in Seattle, WA and was founded July 5th, 1994 by Jeff Bezos, allowing customers to buy everything from books to blenders. Seattle is north of Portland and south of Vancouver, BC. Other notable Seattle - based companies are Starbucks and Boeing.";
        Region region = Region.US_EAST_1;
        ComprehendClient comClient = ComprehendClient.builder()
                .region(region)
                .build();

        System.out.println("Calling DetectSentiment");
        detectSentiments(comClient, text);
        comClient.close();
    }

    public static void detectSentiments(ComprehendClient comClient, String text) {
        try {
            DetectSentimentRequest detectSentimentRequest = DetectSentimentRequest.builder()
                    .text(text)
                    .languageCode("en")
                    .build();

            DetectSentimentResponse detectSentimentResult = comClient.detectSentiment(detectSentimentRequest);
            System.out.println("The Neutral value is " + detectSentimentResult.sentimentScore().neutral());

        } catch (ComprehendException e) {
            System.err.println(e.awsErrorDetails().errorMessage());
            System.exit(1);
        }
    }
}
```
+  For API details, see [DetectSentiment](https://docs.aws.amazon.com/goto/SdkForJavaV2/comprehend-2017-11-27/DetectSentiment) in *AWS SDK for Java 2.x API Reference*. 

------
#### [ Python ]

**SDK for Python (Boto3)**  
 There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/comprehend#code-examples). 

```
class ComprehendDetect:
    """Encapsulates Comprehend detection functions."""

    def __init__(self, comprehend_client):
        """
        :param comprehend_client: A Boto3 Comprehend client.
        """
        self.comprehend_client = comprehend_client


    def detect_sentiment(self, text, language_code):
        """
        Detects the overall sentiment expressed in a document. Sentiment can
        be positive, negative, neutral, or a mixture.

        :param text: The document to inspect.
        :param language_code: The language of the document.
        :return: The sentiments along with their confidence scores.
        """
        try:
            response = self.comprehend_client.detect_sentiment(
                Text=text, LanguageCode=language_code
            )
            logger.info("Detected primary sentiment %s.", response["Sentiment"])
        except ClientError:
            logger.exception("Couldn't detect sentiment.")
            raise
        else:
            return response
```
+  For API details, see [DetectSentiment](https://docs.aws.amazon.com/goto/boto3/comprehend-2017-11-27/DetectSentiment) in *AWS SDK for Python (Boto3) API Reference*. 

------
#### [ SAP ABAP ]

**SDK for SAP ABAP**  
 There's more on GitHub. Find the complete example and learn how to set up and run in the [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/cpd#code-examples). 

```
    TRY.
        oo_result = lo_cpd->detectsentiment(
          iv_text = iv_text
          iv_languagecode = iv_language_code
        ).
        MESSAGE 'Sentiment detected.' TYPE 'I'.
      CATCH /aws1/cx_cpdtextsizelmtexcdex.
        MESSAGE 'Text size exceeds limit.' TYPE 'E'.
      CATCH /aws1/cx_cpdunsuppedlanguageex.
        MESSAGE 'Unsupported language.' TYPE 'E'.
      CATCH /aws1/cx_cpdinternalserverex.
        MESSAGE 'Internal server error occurred.' TYPE 'E'.
      CATCH /aws1/cx_cpdinvalidrequestex.
        MESSAGE 'Invalid request.' TYPE 'E'.
    ENDTRY.
```
+  For API details, see [DetectSentiment](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html) in *AWS SDK for SAP ABAP API reference*. 

------