Calculer des analyses de séries temporelles

// Compute timeseries analytics returns "OK" response

package main

import (
	"context"
	"encoding/json"
	"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.ProductAnalyticsAnalyticsRequest{
		Data: datadogV2.ProductAnalyticsAnalyticsRequestData{
			Attributes: datadogV2.ProductAnalyticsAnalyticsRequestAttributes{
				From: 1771232048460,
				Query: datadogV2.ProductAnalyticsAnalyticsQuery{
					Compute: datadogV2.ProductAnalyticsCompute{
						Aggregation: "count",
					},
					Query: datadogV2.ProductAnalyticsBaseQuery{
						ProductAnalyticsEventQuery: &datadogV2.ProductAnalyticsEventQuery{
							DataSource: datadogV2.PRODUCTANALYTICSEVENTQUERYDATASOURCE_PRODUCT_ANALYTICS,
							Search: datadogV2.ProductAnalyticsEventSearch{
								Query: datadog.PtrString("@type:view"),
							},
						}},
				},
				To: 1771836848262,
			},
			Type: datadogV2.PRODUCTANALYTICSANALYTICSREQUESTTYPE_FORMULA_ANALYTICS_EXTENDED_REQUEST,
		},
	}
	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.NewProductAnalyticsApi(apiClient)
	resp, r, err := api.QueryProductAnalyticsTimeseries(ctx, body)

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

	responseContent, _ := json.MarshalIndent(resp, "", "  ")
	fmt.Fprintf(os.Stdout, "Response from `ProductAnalyticsApi.QueryProductAnalyticsTimeseries`:\n%s\n", responseContent)
}

// Compute timeseries analytics returns "OK" response

import com.datadog.api.client.ApiClient;
import com.datadog.api.client.ApiException;
import com.datadog.api.client.v2.api.ProductAnalyticsApi;
import com.datadog.api.client.v2.model.ProductAnalyticsAnalyticsQuery;
import com.datadog.api.client.v2.model.ProductAnalyticsAnalyticsRequest;
import com.datadog.api.client.v2.model.ProductAnalyticsAnalyticsRequestAttributes;
import com.datadog.api.client.v2.model.ProductAnalyticsAnalyticsRequestData;
import com.datadog.api.client.v2.model.ProductAnalyticsAnalyticsRequestType;
import com.datadog.api.client.v2.model.ProductAnalyticsBaseQuery;
import com.datadog.api.client.v2.model.ProductAnalyticsCompute;
import com.datadog.api.client.v2.model.ProductAnalyticsEventQuery;
import com.datadog.api.client.v2.model.ProductAnalyticsEventQueryDataSource;
import com.datadog.api.client.v2.model.ProductAnalyticsEventSearch;
import com.datadog.api.client.v2.model.ProductAnalyticsTimeseriesResponse;

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

    ProductAnalyticsAnalyticsRequest body =
        new ProductAnalyticsAnalyticsRequest()
            .data(
                new ProductAnalyticsAnalyticsRequestData()
                    .attributes(
                        new ProductAnalyticsAnalyticsRequestAttributes()
                            .from(1771232048460L)
                            .query(
                                new ProductAnalyticsAnalyticsQuery()
                                    .compute(new ProductAnalyticsCompute().aggregation("count"))
                                    .query(
                                        new ProductAnalyticsBaseQuery(
                                            new ProductAnalyticsEventQuery()
                                                .dataSource(
                                                    ProductAnalyticsEventQueryDataSource
                                                        .PRODUCT_ANALYTICS)
                                                .search(
                                                    new ProductAnalyticsEventSearch()
                                                        .query("@type:view")))))
                            .to(1771836848262L))
                    .type(ProductAnalyticsAnalyticsRequestType.FORMULA_ANALYTICS_EXTENDED_REQUEST));

    try {
      ProductAnalyticsTimeseriesResponse result = apiInstance.queryProductAnalyticsTimeseries(body);
      System.out.println(result);
    } catch (ApiException e) {
      System.err.println(
          "Exception when calling ProductAnalyticsApi#queryProductAnalyticsTimeseries");
      System.err.println("Status code: " + e.getCode());
      System.err.println("Reason: " + e.getResponseBody());
      System.err.println("Response headers: " + e.getResponseHeaders());
      e.printStackTrace();
    }
  }
}

"""
Compute timeseries analytics returns "OK" response
"""

from os import environ
from datadog_api_client import ApiClient, Configuration
from datadog_api_client.v2.api.product_analytics_api import ProductAnalyticsApi
from datadog_api_client.v2.model.product_analytics_analytics_query import ProductAnalyticsAnalyticsQuery
from datadog_api_client.v2.model.product_analytics_analytics_request import ProductAnalyticsAnalyticsRequest
from datadog_api_client.v2.model.product_analytics_analytics_request_attributes import (
    ProductAnalyticsAnalyticsRequestAttributes,
)
from datadog_api_client.v2.model.product_analytics_analytics_request_data import ProductAnalyticsAnalyticsRequestData
from datadog_api_client.v2.model.product_analytics_analytics_request_type import ProductAnalyticsAnalyticsRequestType
from datadog_api_client.v2.model.product_analytics_compute import ProductAnalyticsCompute
from datadog_api_client.v2.model.product_analytics_event_query import ProductAnalyticsEventQuery
from datadog_api_client.v2.model.product_analytics_event_query_data_source import ProductAnalyticsEventQueryDataSource
from datadog_api_client.v2.model.product_analytics_event_search import ProductAnalyticsEventSearch

body = ProductAnalyticsAnalyticsRequest(
    data=ProductAnalyticsAnalyticsRequestData(
        attributes=ProductAnalyticsAnalyticsRequestAttributes(
            _from=1771232048460,
            query=ProductAnalyticsAnalyticsQuery(
                compute=ProductAnalyticsCompute(
                    aggregation="count",
                ),
                query=ProductAnalyticsEventQuery(
                    data_source=ProductAnalyticsEventQueryDataSource.PRODUCT_ANALYTICS,
                    search=ProductAnalyticsEventSearch(
                        query="@type:view",
                    ),
                ),
            ),
            to=1771836848262,
        ),
        type=ProductAnalyticsAnalyticsRequestType.FORMULA_ANALYTICS_EXTENDED_REQUEST,
    ),
)

configuration = Configuration()
configuration.access_token = environ["DD_BEARER_TOKEN"]
with ApiClient(configuration) as api_client:
    api_instance = ProductAnalyticsApi(api_client)
    response = api_instance.query_product_analytics_timeseries(body=body)

    print(response)

# Compute timeseries analytics returns "OK" response

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

body = DatadogAPIClient::V2::ProductAnalyticsAnalyticsRequest.new({
  data: DatadogAPIClient::V2::ProductAnalyticsAnalyticsRequestData.new({
    attributes: DatadogAPIClient::V2::ProductAnalyticsAnalyticsRequestAttributes.new({
      from: 1771232048460,
      query: DatadogAPIClient::V2::ProductAnalyticsAnalyticsQuery.new({
        compute: DatadogAPIClient::V2::ProductAnalyticsCompute.new({
          aggregation: "count",
        }),
        query: DatadogAPIClient::V2::ProductAnalyticsEventQuery.new({
          data_source: DatadogAPIClient::V2::ProductAnalyticsEventQueryDataSource::PRODUCT_ANALYTICS,
          search: DatadogAPIClient::V2::ProductAnalyticsEventSearch.new({
            query: "@type:view",
          }),
        }),
      }),
      to: 1771836848262,
    }),
    type: DatadogAPIClient::V2::ProductAnalyticsAnalyticsRequestType::FORMULA_ANALYTICS_EXTENDED_REQUEST,
  }),
})
p api_instance.query_product_analytics_timeseries(body)

// Compute timeseries analytics returns "OK" response
use datadog_api_client::datadog;
use datadog_api_client::datadogV2::api_product_analytics::ProductAnalyticsAPI;
use datadog_api_client::datadogV2::model::ProductAnalyticsAnalyticsQuery;
use datadog_api_client::datadogV2::model::ProductAnalyticsAnalyticsRequest;
use datadog_api_client::datadogV2::model::ProductAnalyticsAnalyticsRequestAttributes;
use datadog_api_client::datadogV2::model::ProductAnalyticsAnalyticsRequestData;
use datadog_api_client::datadogV2::model::ProductAnalyticsAnalyticsRequestType;
use datadog_api_client::datadogV2::model::ProductAnalyticsBaseQuery;
use datadog_api_client::datadogV2::model::ProductAnalyticsCompute;
use datadog_api_client::datadogV2::model::ProductAnalyticsEventQuery;
use datadog_api_client::datadogV2::model::ProductAnalyticsEventQueryDataSource;
use datadog_api_client::datadogV2::model::ProductAnalyticsEventSearch;

#[tokio::main]
async fn main() {
    let body = ProductAnalyticsAnalyticsRequest::new(ProductAnalyticsAnalyticsRequestData::new(
        ProductAnalyticsAnalyticsRequestAttributes::new(
            1771232048460,
            ProductAnalyticsAnalyticsQuery::new(
                ProductAnalyticsCompute::new("count".to_string()),
                ProductAnalyticsBaseQuery::ProductAnalyticsEventQuery(Box::new(
                    ProductAnalyticsEventQuery::new(
                        ProductAnalyticsEventQueryDataSource::PRODUCT_ANALYTICS,
                        ProductAnalyticsEventSearch::new().query("@type:view".to_string()),
                    ),
                )),
            ),
            1771836848262,
        ),
        ProductAnalyticsAnalyticsRequestType::FORMULA_ANALYTICS_EXTENDED_REQUEST,
    ));
    let configuration = datadog::Configuration::new();
    let api = ProductAnalyticsAPI::with_config(configuration);
    let resp = api.query_product_analytics_timeseries(body).await;
    if let Ok(value) = resp {
        println!("{:#?}", value);
    } else {
        println!("{:#?}", resp.unwrap_err());
    }
}

/**
 * Compute timeseries analytics returns "OK" 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.ProductAnalyticsApi(configuration);

const params: v2.ProductAnalyticsApiQueryProductAnalyticsTimeseriesRequest = {
  body: {
    data: {
      attributes: {
        from: 1771232048460,
        query: {
          compute: {
            aggregation: "count",
          },
          query: {
            dataSource: "product_analytics",
            search: {
              query: "@type:view",
            },
          },
        },
        to: 1771836848262,
      },
      type: "formula_analytics_extended_request",
    },
  },
};

apiInstance
  .queryProductAnalyticsTimeseries(params)
  .then((data: v2.ProductAnalyticsTimeseriesResponse) => {
    console.log(
      "API called successfully. Returned data: " + JSON.stringify(data)
    );
  })
  .catch((error: any) => console.error(error));