ListDocumentClassifiers unicodeCpp Example
#include <CkRestW.h>
#include <CkAuthAwsW.h>
#include <CkJsonObjectW.h>
#include <CkStringBuilderW.h>
void ChilkatSample(void)
{
// This example requires the Chilkat API to have been previously unlocked.
// See Global Unlock Sample for sample code.
CkRestW rest;
bool success;
CkAuthAwsW authAws;
authAws.put_AccessKey(L"AWS_ACCESS_KEY");
authAws.put_SecretKey(L"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(L"us-west-2");
authAws.put_ServiceName(L"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(L"comprehend.us-west-2.amazonaws.com",443,true,true);
if (success != true) {
wprintf(L"ConnectFailReason: %d\n",rest.get_ConnectFailReason());
wprintf(L"%s\n",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
CkJsonObjectW json;
json.UpdateString(L"Filter.DocumentClassifierName",L"string");
json.UpdateString(L"Filter.Status",L"string");
json.UpdateInt(L"Filter.SubmitTimeAfter",123);
json.UpdateInt(L"Filter.SubmitTimeBefore",123);
json.UpdateInt(L"MaxResults",123);
json.UpdateString(L"NextToken",L"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(L"Content-Type",L"application/x-amz-json-1.1");
rest.AddHeader(L"X-Amz-Target",L"Comprehend_20171127.ListDocumentClassifiers");
CkStringBuilderW sbRequestBody;
json.EmitSb(sbRequestBody);
CkStringBuilderW sbResponseBody;
success = rest.FullRequestSb(L"POST",L"/",sbRequestBody,sbResponseBody);
if (success != true) {
wprintf(L"%s\n",rest.lastErrorText());
return;
}
int respStatusCode = rest.get_ResponseStatusCode();
wprintf(L"response status code = %d\n",respStatusCode);
if (respStatusCode != 200) {
wprintf(L"Response Header:\n");
wprintf(L"%s\n",rest.responseHeader());
wprintf(L"Response Body:\n");
wprintf(L"%s\n",sbResponseBody.getAsString());
return;
}
CkJsonObjectW jResp;
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
// Chilkat functions returning "const char *" return a pointer to temporary internal memory owned and managed by Chilkat.
// See this example explaining how this memory should be used: const char * functions.
int Accuracy;
int F1Score;
int HammingLoss;
int MicroF1Score;
int MicroPrecision;
int MicroRecall;
int Precision;
int Recall;
int NumberOfLabels;
int NumberOfTestDocuments;
int NumberOfTrainedDocuments;
const wchar_t *DataAccessRoleArn = 0;
const wchar_t *DocumentClassifierArn = 0;
int EndTime;
const wchar_t *DataFormat = 0;
const wchar_t *LabelDelimiter = 0;
const wchar_t *S3Uri = 0;
const wchar_t *TestS3Uri = 0;
const wchar_t *LanguageCode = 0;
const wchar_t *Message = 0;
const wchar_t *Mode = 0;
const wchar_t *ModelKmsKeyId = 0;
const wchar_t *KmsKeyId = 0;
const wchar_t *OutputDataConfigS3Uri = 0;
const wchar_t *SourceModelArn = 0;
const wchar_t *Status = 0;
int SubmitTime;
int TrainingEndTime;
int TrainingStartTime;
const wchar_t *VersionName = 0;
const wchar_t *VolumeKmsKeyId = 0;
int j;
int count_j;
const wchar_t *AnnotationDataS3Uri = 0;
const wchar_t *DocumentType = 0;
const wchar_t *SourceDocumentsS3Uri = 0;
const wchar_t *Split = 0;
int k;
int count_k;
const wchar_t *strVal = 0;
const wchar_t *NextToken = jResp.stringOf(L"NextToken");
int i = 0;
int count_i = jResp.SizeOfArray(L"DocumentClassifierPropertiesList");
while (i < count_i) {
jResp.put_I(i);
Accuracy = jResp.IntOf(L"DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.Accuracy");
F1Score = jResp.IntOf(L"DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.F1Score");
HammingLoss = jResp.IntOf(L"DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.HammingLoss");
MicroF1Score = jResp.IntOf(L"DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.MicroF1Score");
MicroPrecision = jResp.IntOf(L"DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.MicroPrecision");
MicroRecall = jResp.IntOf(L"DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.MicroRecall");
Precision = jResp.IntOf(L"DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.Precision");
Recall = jResp.IntOf(L"DocumentClassifierPropertiesList[i].ClassifierMetadata.EvaluationMetrics.Recall");
NumberOfLabels = jResp.IntOf(L"DocumentClassifierPropertiesList[i].ClassifierMetadata.NumberOfLabels");
NumberOfTestDocuments = jResp.IntOf(L"DocumentClassifierPropertiesList[i].ClassifierMetadata.NumberOfTestDocuments");
NumberOfTrainedDocuments = jResp.IntOf(L"DocumentClassifierPropertiesList[i].ClassifierMetadata.NumberOfTrainedDocuments");
DataAccessRoleArn = jResp.stringOf(L"DocumentClassifierPropertiesList[i].DataAccessRoleArn");
DocumentClassifierArn = jResp.stringOf(L"DocumentClassifierPropertiesList[i].DocumentClassifierArn");
EndTime = jResp.IntOf(L"DocumentClassifierPropertiesList[i].EndTime");
DataFormat = jResp.stringOf(L"DocumentClassifierPropertiesList[i].InputDataConfig.DataFormat");
LabelDelimiter = jResp.stringOf(L"DocumentClassifierPropertiesList[i].InputDataConfig.LabelDelimiter");
S3Uri = jResp.stringOf(L"DocumentClassifierPropertiesList[i].InputDataConfig.S3Uri");
TestS3Uri = jResp.stringOf(L"DocumentClassifierPropertiesList[i].InputDataConfig.TestS3Uri");
LanguageCode = jResp.stringOf(L"DocumentClassifierPropertiesList[i].LanguageCode");
Message = jResp.stringOf(L"DocumentClassifierPropertiesList[i].Message");
Mode = jResp.stringOf(L"DocumentClassifierPropertiesList[i].Mode");
ModelKmsKeyId = jResp.stringOf(L"DocumentClassifierPropertiesList[i].ModelKmsKeyId");
KmsKeyId = jResp.stringOf(L"DocumentClassifierPropertiesList[i].OutputDataConfig.KmsKeyId");
OutputDataConfigS3Uri = jResp.stringOf(L"DocumentClassifierPropertiesList[i].OutputDataConfig.S3Uri");
SourceModelArn = jResp.stringOf(L"DocumentClassifierPropertiesList[i].SourceModelArn");
Status = jResp.stringOf(L"DocumentClassifierPropertiesList[i].Status");
SubmitTime = jResp.IntOf(L"DocumentClassifierPropertiesList[i].SubmitTime");
TrainingEndTime = jResp.IntOf(L"DocumentClassifierPropertiesList[i].TrainingEndTime");
TrainingStartTime = jResp.IntOf(L"DocumentClassifierPropertiesList[i].TrainingStartTime");
VersionName = jResp.stringOf(L"DocumentClassifierPropertiesList[i].VersionName");
VolumeKmsKeyId = jResp.stringOf(L"DocumentClassifierPropertiesList[i].VolumeKmsKeyId");
j = 0;
count_j = jResp.SizeOfArray(L"DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests");
while (j < count_j) {
jResp.put_J(j);
AnnotationDataS3Uri = jResp.stringOf(L"DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].AnnotationDataS3Uri");
DocumentType = jResp.stringOf(L"DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].DocumentType");
S3Uri = jResp.stringOf(L"DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].S3Uri");
SourceDocumentsS3Uri = jResp.stringOf(L"DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].SourceDocumentsS3Uri");
Split = jResp.stringOf(L"DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].Split");
k = 0;
count_k = jResp.SizeOfArray(L"DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].AttributeNames");
while (k < count_k) {
jResp.put_K(k);
strVal = jResp.stringOf(L"DocumentClassifierPropertiesList[i].InputDataConfig.AugmentedManifests[j].AttributeNames[k]");
k = k + 1;
}
j = j + 1;
}
j = 0;
count_j = jResp.SizeOfArray(L"DocumentClassifierPropertiesList[i].VpcConfig.SecurityGroupIds");
while (j < count_j) {
jResp.put_J(j);
strVal = jResp.stringOf(L"DocumentClassifierPropertiesList[i].VpcConfig.SecurityGroupIds[j]");
j = j + 1;
}
j = 0;
count_j = jResp.SizeOfArray(L"DocumentClassifierPropertiesList[i].VpcConfig.Subnets");
while (j < count_j) {
jResp.put_J(j);
strVal = jResp.stringOf(L"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"
// }
}
