Chilkat Tools

ListDocumentClassifiers Ruby Example

Amazon Comprehend

require 'chilkat'

# This example requires the Chilkat API to have been previously unlocked.
# See Global Unlock Sample for sample code.

rest = Chilkat::CkRest.new()

authAws = Chilkat::CkAuthAws.new()
authAws.put_AccessKey("AWS_ACCESS_KEY")
authAws.put_SecretKey("AWS_SECRET_KEY")

# Don't forget to change the region to your particular region. (Also make the same change in the call to Connect below.)
authAws.put_Region("us-west-2")
authAws.put_ServiceName("comprehend")
# SetAuthAws causes Chilkat to automatically add the following headers: Authorization, X-Amz-Date
rest.SetAuthAws(authAws)

# URL: https://comprehend.us-west-2.amazonaws.com/
# Use the same region as specified above.
success = rest.Connect("comprehend.us-west-2.amazonaws.com",443,true,true)
if (success != true)
    print "ConnectFailReason: " + rest.get_ConnectFailReason().to_s() + "\n";
    print rest.lastErrorText() + "\n";
    exit
end

# The following code creates the JSON request body.
# The JSON created by this code is shown below.

# Use this online tool to generate code from sample JSON:
# Generate Code to Create JSON

json = Chilkat::CkJsonObject.new()
json.UpdateString("Filter.DocumentClassifierName","string")
json.UpdateString("Filter.Status","string")
json.UpdateInt("Filter.SubmitTimeAfter",123)
json.UpdateInt("Filter.SubmitTimeBefore",123)
json.UpdateInt("MaxResults",123)
json.UpdateString("NextToken","string")

# The JSON request body created by the above code:

# {
#   "Filter": {
#     "DocumentClassifierName": "string",
#     "Status": "string",
#     "SubmitTimeAfter": number,
#     "SubmitTimeBefore": number
#   },
#   "MaxResults": number,
#   "NextToken": "string"
# }

rest.AddHeader("Content-Type","application/x-amz-json-1.1")
rest.AddHeader("X-Amz-Target","Comprehend_20171127.ListDocumentClassifiers")

sbRequestBody = Chilkat::CkStringBuilder.new()
json.EmitSb(sbRequestBody)
sbResponseBody = Chilkat::CkStringBuilder.new()
success = rest.FullRequestSb("POST","/",sbRequestBody,sbResponseBody)
if (success != true)
    print rest.lastErrorText() + "\n";
    exit
end

respStatusCode = rest.get_ResponseStatusCode()
print "response status code = " + respStatusCode.to_s() + "\n";
if (respStatusCode != 200)
    print "Response Header:" + "\n";
    print rest.responseHeader() + "\n";
    print "Response Body:" + "\n";
    print sbResponseBody.getAsString() + "\n";
    exit
end

jResp = Chilkat::CkJsonObject.new()
jResp.LoadSb(sbResponseBody)

# The following code parses the JSON response.
# A sample JSON response is shown below the sample code.

# Use this online tool to generate parsing code from sample JSON:
# Generate Parsing Code from JSON

NextToken = jResp.stringOf("NextToken")
i = 0
count_i = jResp.SizeOfArray("DocumentClassifierPropertiesList")
while i < count_i
    jResp.put_I(i)
    Accuracy = jResp.IntOf("DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.Accuracy")
    F1Score = jResp.IntOf("DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.F1Score")
    HammingLoss = jResp.IntOf("DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.HammingLoss")
    MicroF1Score = jResp.IntOf("DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.MicroF1Score")
    MicroPrecision = jResp.IntOf("DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.MicroPrecision")
    MicroRecall = jResp.IntOf("DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.MicroRecall")
    Precision = jResp.IntOf("DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.Precision")
    Recall = jResp.IntOf("DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.Recall")
    NumberOfLabels = jResp.IntOf("DocumentClassifierPropertiesList[i].ClassifierMetadata.NumberOfLabels")
    NumberOfTestDocuments = jResp.IntOf("DocumentClassifierPropertiesList[i].ClassifierMetadata.NumberOfTestDocuments")
    NumberOfTrainedDocuments = jResp.IntOf("DocumentClassifierPropertiesList[i].ClassifierMetadata.NumberOfTrainedDocuments")
    DataAccessRoleArn = jResp.stringOf("DocumentClassifierPropertiesList[i].DataAccessRoleArn")
    DocumentClassifierArn = jResp.stringOf("DocumentClassifierPropertiesList[i].DocumentClassifierArn")
    EndTime = jResp.IntOf("DocumentClassifierPropertiesList[i].EndTime")
    DataFormat = jResp.stringOf("DocumentClassifierPropertiesList[i].InputDataConfig.DataFormat")
    LabelDelimiter = jResp.stringOf("DocumentClassifierPropertiesList[i].InputDataConfig.LabelDelimiter")
    S3Uri = jResp.stringOf("DocumentClassifierPropertiesList[i].InputDataConfig.S3Uri")
    TestS3Uri = jResp.stringOf("DocumentClassifierPropertiesList[i].InputDataConfig.TestS3Uri")
    LanguageCode = jResp.stringOf("DocumentClassifierPropertiesList[i].LanguageCode")
    Message = jResp.stringOf("DocumentClassifierPropertiesList[i].Message")
    Mode = jResp.stringOf("DocumentClassifierPropertiesList[i].Mode")
    ModelKmsKeyId = jResp.stringOf("DocumentClassifierPropertiesList[i].ModelKmsKeyId")
    KmsKeyId = jResp.stringOf("DocumentClassifierPropertiesList[i].OutputDataConfig.KmsKeyId")
    OutputDataConfigS3Uri = jResp.stringOf("DocumentClassifierPropertiesList[i].OutputDataConfig.S3Uri")
    SourceModelArn = jResp.stringOf("DocumentClassifierPropertiesList[i].SourceModelArn")
    Status = jResp.stringOf("DocumentClassifierPropertiesList[i].Status")
    SubmitTime = jResp.IntOf("DocumentClassifierPropertiesList[i].SubmitTime")
    TrainingEndTime = jResp.IntOf("DocumentClassifierPropertiesList[i].TrainingEndTime")
    TrainingStartTime = jResp.IntOf("DocumentClassifierPropertiesList[i].TrainingStartTime")
    VersionName = jResp.stringOf("DocumentClassifierPropertiesList[i].VersionName")
    VolumeKmsKeyId = jResp.stringOf("DocumentClassifierPropertiesList[i].VolumeKmsKeyId")
    j = 0
    count_j = jResp.SizeOfArray("DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests")
    while j < count_j
        jResp.put_J(j)
        AnnotationDataS3Uri = jResp.stringOf("DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].AnnotationDataS3Uri")
        DocumentType = jResp.stringOf("DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].DocumentType")
        S3Uri = jResp.stringOf("DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].S3Uri")
        SourceDocumentsS3Uri = jResp.stringOf("DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].SourceDocumentsS3Uri")
        Split = jResp.stringOf("DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].Split")
        k = 0
        count_k = jResp.SizeOfArray("DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].AttributeNames")
        while k < count_k
            jResp.put_K(k)
            strVal = jResp.stringOf("DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].AttributeNames[k]")
            k = k + 1
        end
        j = j + 1
    end
    j = 0
    count_j = jResp.SizeOfArray("DocumentClassifierPropertiesList[i].VpcConfig.SecurityGroupIds")
    while j < count_j
        jResp.put_J(j)
        strVal = jResp.stringOf("DocumentClassifierPropertiesList[i].VpcConfig.SecurityGroupIds[j]")
        j = j + 1
    end
    j = 0
    count_j = jResp.SizeOfArray("DocumentClassifierPropertiesList[i].VpcConfig.Subnets")
    while j < count_j
        jResp.put_J(j)
        strVal = jResp.stringOf("DocumentClassifierPropertiesList[i].VpcConfig.Subnets[j]")
        j = j + 1
    end
    i = i + 1
end

# A sample JSON response body parsed by the above code:

# {
#   "DocumentClassifierPropertiesList": [
#     {
#       "ClassifierMetadata": {
#         "EvaluationMetrics": {
#           "Accuracy": number,
#           "F1Score": number,
#           "HammingLoss": number,
#           "MicroF1Score": number,
#           "MicroPrecision": number,
#           "MicroRecall": number,
#           "Precision": number,
#           "Recall": number
#         },
#         "NumberOfLabels": number,
#         "NumberOfTestDocuments": number,
#         "NumberOfTrainedDocuments": number
#       },
#       "DataAccessRoleArn": "string",
#       "DocumentClassifierArn": "string",
#       "EndTime": number,
#       "InputDataConfig": {
#         "AugmentedManifests": [
#           {
#             "AnnotationDataS3Uri": "string",
#             "AttributeNames": [
#               "string"
#             ],
#             "DocumentType": "string",
#             "S3Uri": "string",
#             "SourceDocumentsS3Uri": "string",
#             "Split": "string"
#           }
#         ],
#         "DataFormat": "string",
#         "LabelDelimiter": "string",
#         "S3Uri": "string",
#         "TestS3Uri": "string"
#       },
#       "LanguageCode": "string",
#       "Message": "string",
#       "Mode": "string",
#       "ModelKmsKeyId": "string",
#       "OutputDataConfig": {
#         "KmsKeyId": "string",
#         "S3Uri": "string"
#       },
#       "SourceModelArn": "string",
#       "Status": "string",
#       "SubmitTime": number,
#       "TrainingEndTime": number,
#       "TrainingStartTime": number,
#       "VersionName": "string",
#       "VolumeKmsKeyId": "string",
#       "VpcConfig": {
#         "SecurityGroupIds": [
#           "string"
#         ],
#         "Subnets": [
#           "string"
#         ]
#       }
#     }
#   ],
#   "NextToken": "string"
# }
Chilkat Online Tools

ListDocumentClassifiers Ruby Example

Amazon Comprehend
