Faire un upsert de lignes

// Upsert rows returns "Rows created or updated successfully" response

package main

import (
	"context"
	"fmt"
	"os"

	"github.com/DataDog/datadog-api-client-go/v2/api/datadog"
	"github.com/DataDog/datadog-api-client-go/v2/api/datadogV2"
)

func main() {
	body := datadogV2.BatchUpsertRowsRequestArray{
		Data: []datadogV2.BatchUpsertRowsRequestData{
			{
				Attributes: &datadogV2.BatchUpsertRowsRequestDataAttributes{
					Values: map[string]datadogV2.BatchUpsertRowsRequestDataAttributesValue{},
				},
				Id:   "primary_key_value",
				Type: datadogV2.TABLEROWRESOURCEDATATYPE_ROW,
			},
		},
	}
	ctx := datadog.NewDefaultContext(context.Background())
	ctx = context.WithValue(ctx, datadog.ContextAccessToken, os.Getenv("DD_BEARER_TOKEN"))
	configuration := datadog.NewConfiguration()
	apiClient := datadog.NewAPIClient(configuration)
	api := datadogV2.NewReferenceTablesApi(apiClient)
	r, err := api.UpsertRows(ctx, "id", body)

	if err != nil {
		fmt.Fprintf(os.Stderr, "Error when calling `ReferenceTablesApi.UpsertRows`: %v\n", err)
		fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
	}
}

// Upsert rows returns "Rows created or updated successfully" response

import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.ReferenceTablesApi;
import com.datadog.api.client.v2.model.BatchUpsertRowsRequestArray;
import com.datadog.api.client.v2.model.BatchUpsertRowsRequestData;
import com.datadog.api.client.v2.model.BatchUpsertRowsRequestDataAttributes;
import com.datadog.api.client.v2.model.TableRowResourceDataType;
import java.util.Collections;
import java.util.Map;

public class Example {
  public static void main(String[] args) {
    ApiClient defaultClient = ApiClient.getDefaultApiClient();
    defaultClient.setAccessToken(System.getenv("DD_BEARER_TOKEN"));
    ReferenceTablesApi apiInstance = new ReferenceTablesApi(defaultClient);

    BatchUpsertRowsRequestArray body =
        new BatchUpsertRowsRequestArray()
            .data(
                Collections.singletonList(
                    new BatchUpsertRowsRequestData()
                        .attributes(
                            new BatchUpsertRowsRequestDataAttributes().values(Map.ofEntries()))
                        .id("primary_key_value")
                        .type(TableRowResourceDataType.ROW)));

    try {
      apiInstance.upsertRows("id", body);
    } catch (ApiException e) {
      System.err.println("Exception when calling ReferenceTablesApi#upsertRows");
      System.err.println("Status code: " + e.getCode());
      System.err.println("Reason: " + e.getResponseBody());
      System.err.println("Response headers: " + e.getResponseHeaders());
      e.printStackTrace();
    }
  }
}

"""
Upsert rows returns "Rows created or updated successfully" response
"""

from os import environ
from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.reference_tables_api import ReferenceTablesApi
from datadog_api_client.v2.model.batch_upsert_rows_request_array import BatchUpsertRowsRequestArray
from datadog_api_client.v2.model.batch_upsert_rows_request_data import BatchUpsertRowsRequestData
from datadog_api_client.v2.model.batch_upsert_rows_request_data_attributes import BatchUpsertRowsRequestDataAttributes
from datadog_api_client.v2.model.table_row_resource_data_type import TableRowResourceDataType

body = BatchUpsertRowsRequestArray(
    data=[
        BatchUpsertRowsRequestData(
            attributes=BatchUpsertRowsRequestDataAttributes(
                values=dict(),
            ),
            id="primary_key_value",
            type=TableRowResourceDataType.ROW,
        ),
    ],
)

configuration = Configuration()
configuration.access_token = environ["DD_BEARER_TOKEN"]
with ApiClient(configuration) as api_client:
    api_instance = ReferenceTablesApi(api_client)
    api_instance.upsert_rows(id="id", body=body)

# Upsert rows returns "Rows created or updated successfully" response

require "datadog_api_client"
DatadogAPIClient.configure do |config|
  config.access_token = ENV["DD_BEARER_TOKEN"]
end
api_instance = DatadogAPIClient::V2::ReferenceTablesAPI.new

body = DatadogAPIClient::V2::BatchUpsertRowsRequestArray.new({
  data: [
    DatadogAPIClient::V2::BatchUpsertRowsRequestData.new({
      attributes: DatadogAPIClient::V2::BatchUpsertRowsRequestDataAttributes.new({
        values: {},
      }),
      id: "primary_key_value",
      type: DatadogAPIClient::V2::TableRowResourceDataType::ROW,
    }),
  ],
})
p api_instance.upsert_rows("id", body)

// Upsert rows returns "Rows created or updated successfully" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_reference_tables::ReferenceTablesAPI;
use datadog_api_client::datadogV2::model::BatchUpsertRowsRequestArray;
use datadog_api_client::datadogV2::model::BatchUpsertRowsRequestData;
use datadog_api_client::datadogV2::model::BatchUpsertRowsRequestDataAttributes;
use datadog_api_client::datadogV2::model::TableRowResourceDataType;
use std::collections::BTreeMap;

#[tokio::main]
async fn main() {
    let body = BatchUpsertRowsRequestArray::new(vec![BatchUpsertRowsRequestData::new(
        "primary_key_value".to_string(),
        TableRowResourceDataType::ROW,
    )
    .attributes(BatchUpsertRowsRequestDataAttributes::new(
        BTreeMap::from([]),
    ))]);
    let configuration = datadog::Configuration::new();
    let api = ReferenceTablesAPI::with_config(configuration);
    let resp = api.upsert_rows("id".to_string(), body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

/**
 * Upsert rows returns "Rows created or updated successfully" response
 */

import { client, v2 } from "@datadog/datadog-api-client";

const configuration = client.createConfiguration({
  authMethods: {
    AuthZ: {
      accessToken: process.env.DD_BEARER_TOKEN as string,
    },
  },
});
const apiInstance = new v2.ReferenceTablesApi(configuration);

const params: v2.ReferenceTablesApiUpsertRowsRequest = {
  body: {
    data: [
      {
        attributes: {
          values: {},
        },
        id: "primary_key_value",
        type: "row",
      },
    ],
  },
  id: "id",
};

apiInstance
  .upsertRows(params)
  .then((data: any) => {
    console.log(
      "API called successfully. Returned data: " + JSON.stringify(data)
    );
  })
  .catch((error: any) => console.error(error));