Chilkat Online Tools

ListDocumentClassifiers Swift3 Example

Amazon Comprehend

func chilkatTest() {
    // This example requires the Chilkat API to have been previously unlocked.
    // See Global Unlock Sample for sample code.

    let rest = CkoRest()!
    var success: Bool

    let authAws = CkoAuthAws()!
    authAws.accessKey = "AWS_ACCESS_KEY"
    authAws.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.region = "us-west-2"
    authAws.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", port: 443, tls: true, autoReconnect: true)
    if success != true {
        print("ConnectFailReason: \(rest.connectFailReason.intValue)")
        print("\(rest.lastErrorText!)")
        return
    }

    // 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

    let json = CkoJsonObject()!
    json.update("Filter.DocumentClassifierName", value: "string")
    json.update("Filter.Status", value: "string")
    json.updateInt("Filter.SubmitTimeAfter", value: 123)
    json.updateInt("Filter.SubmitTimeBefore", value: 123)
    json.updateInt("MaxResults", value: 123)
    json.update("NextToken", value: "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", value: "application/x-amz-json-1.1")
    rest.addHeader("X-Amz-Target", value: "Comprehend_20171127.ListDocumentClassifiers")

    let sbRequestBody = CkoStringBuilder()!
    json.emitSb(sbRequestBody)
    let sbResponseBody = CkoStringBuilder()!
    success = rest.fullRequestSb("POST", uriPath: "/", requestBody: sbRequestBody, responseBody: sbResponseBody)
    if success != true {
        print("\(rest.lastErrorText!)")
        return
    }

    var respStatusCode: Int = rest.responseStatusCode.intValue
    print("response status code = \(respStatusCode)")
    if respStatusCode != 200 {
        print("Response Header:")
        print("\(rest.responseHeader!)")
        print("Response Body:")
        print("\(sbResponseBody.getAsString()!)")
        return
    }

    let jResp = CkoJsonObject()!
    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

    var Accuracy: Int
    var F1Score: Int
    var HammingLoss: Int
    var MicroF1Score: Int
    var MicroPrecision: Int
    var MicroRecall: Int
    var Precision: Int
    var Recall: Int
    var NumberOfLabels: Int
    var NumberOfTestDocuments: Int
    var NumberOfTrainedDocuments: Int
    var DataAccessRoleArn: String?
    var DocumentClassifierArn: String?
    var EndTime: Int
    var DataFormat: String?
    var LabelDelimiter: String?
    var S3Uri: String?
    var TestS3Uri: String?
    var LanguageCode: String?
    var Message: String?
    var Mode: String?
    var ModelKmsKeyId: String?
    var KmsKeyId: String?
    var OutputDataConfigS3Uri: String?
    var SourceModelArn: String?
    var Status: String?
    var SubmitTime: Int
    var TrainingEndTime: Int
    var TrainingStartTime: Int
    var VersionName: String?
    var VolumeKmsKeyId: String?
    var j: Int
    var count_j: Int
    var AnnotationDataS3Uri: String?
    var DocumentType: String?
    var SourceDocumentsS3Uri: String?
    var Split: String?
    var k: Int
    var count_k: Int
    var strVal: String?

    var NextToken: String? = jResp.string(of: "NextToken")
    var i: Int = 0
    var count_i: Int = jResp.size(ofArray: "DocumentClassifierPropertiesList").intValue
    while i < count_i {
        jResp.i = i
        Accuracy = jResp.int(of: "DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.Accuracy").intValue
        F1Score = jResp.int(of: "DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.F1Score").intValue
        HammingLoss = jResp.int(of: "DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.HammingLoss").intValue
        MicroF1Score = jResp.int(of: "DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.MicroF1Score").intValue
        MicroPrecision = jResp.int(of: "DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.MicroPrecision").intValue
        MicroRecall = jResp.int(of: "DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.MicroRecall").intValue
        Precision = jResp.int(of: "DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.Precision").intValue
        Recall = jResp.int(of: "DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.Recall").intValue
        NumberOfLabels = jResp.int(of: "DocumentClassifierPropertiesList[i].ClassifierMetadata.NumberOfLabels").intValue
        NumberOfTestDocuments = jResp.int(of: "DocumentClassifierPropertiesList[i].ClassifierMetadata.NumberOfTestDocuments").intValue
        NumberOfTrainedDocuments = jResp.int(of: "DocumentClassifierPropertiesList[i].ClassifierMetadata.NumberOfTrainedDocuments").intValue
        DataAccessRoleArn = jResp.string(of: "DocumentClassifierPropertiesList[i].DataAccessRoleArn")
        DocumentClassifierArn = jResp.string(of: "DocumentClassifierPropertiesList[i].DocumentClassifierArn")
        EndTime = jResp.int(of: "DocumentClassifierPropertiesList[i].EndTime").intValue
        DataFormat = jResp.string(of: "DocumentClassifierPropertiesList[i].InputDataConfig.DataFormat")
        LabelDelimiter = jResp.string(of: "DocumentClassifierPropertiesList[i].InputDataConfig.LabelDelimiter")
        S3Uri = jResp.string(of: "DocumentClassifierPropertiesList[i].InputDataConfig.S3Uri")
        TestS3Uri = jResp.string(of: "DocumentClassifierPropertiesList[i].InputDataConfig.TestS3Uri")
        LanguageCode = jResp.string(of: "DocumentClassifierPropertiesList[i].LanguageCode")
        Message = jResp.string(of: "DocumentClassifierPropertiesList[i].Message")
        Mode = jResp.string(of: "DocumentClassifierPropertiesList[i].Mode")
        ModelKmsKeyId = jResp.string(of: "DocumentClassifierPropertiesList[i].ModelKmsKeyId")
        KmsKeyId = jResp.string(of: "DocumentClassifierPropertiesList[i].OutputDataConfig.KmsKeyId")
        OutputDataConfigS3Uri = jResp.string(of: "DocumentClassifierPropertiesList[i].OutputDataConfig.S3Uri")
        SourceModelArn = jResp.string(of: "DocumentClassifierPropertiesList[i].SourceModelArn")
        Status = jResp.string(of: "DocumentClassifierPropertiesList[i].Status")
        SubmitTime = jResp.int(of: "DocumentClassifierPropertiesList[i].SubmitTime").intValue
        TrainingEndTime = jResp.int(of: "DocumentClassifierPropertiesList[i].TrainingEndTime").intValue
        TrainingStartTime = jResp.int(of: "DocumentClassifierPropertiesList[i].TrainingStartTime").intValue
        VersionName = jResp.string(of: "DocumentClassifierPropertiesList[i].VersionName")
        VolumeKmsKeyId = jResp.string(of: "DocumentClassifierPropertiesList[i].VolumeKmsKeyId")
        j = 0
        count_j = jResp.size(ofArray: "DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests").intValue
        while j < count_j {
            jResp.j = j
            AnnotationDataS3Uri = jResp.string(of: "DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].AnnotationDataS3Uri")
            DocumentType = jResp.string(of: "DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].DocumentType")
            S3Uri = jResp.string(of: "DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].S3Uri")
            SourceDocumentsS3Uri = jResp.string(of: "DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].SourceDocumentsS3Uri")
            Split = jResp.string(of: "DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].Split")
            k = 0
            count_k = jResp.size(ofArray: "DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].AttributeNames").intValue
            while k < count_k {
                jResp.k = k
                strVal = jResp.string(of: "DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].AttributeNames[k]")
                k = k + 1
            }

            j = j + 1
        }

        j = 0
        count_j = jResp.size(ofArray: "DocumentClassifierPropertiesList[i].VpcConfig.SecurityGroupIds").intValue
        while j < count_j {
            jResp.j = j
            strVal = jResp.string(of: "DocumentClassifierPropertiesList[i].VpcConfig.SecurityGroupIds[j]")
            j = j + 1
        }

        j = 0
        count_j = jResp.size(ofArray: "DocumentClassifierPropertiesList[i].VpcConfig.Subnets").intValue
        while j < count_j {
            jResp.j = j
            strVal = jResp.string(of: "DocumentClassifierPropertiesList[i].VpcConfig.Subnets[j]")
            j = j + 1
        }

        i = i + 1
    }

    // 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"
    // }

}