Google Analytics API quickstart
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You can use the Data API or Admin API for this quickstart

Choose an API: Data API Admin API

You can authenticate with a user account or service account:

Choose an account type:

In this quickstart, you create and send a runReport request.

Here's a summary of the steps:

Set up tools and access.
Enable the API.
Install an SDK.
Make an API call.

Before you begin

Create a service account.
Create a Google Cloud VM instance.
Install and initialize the gcloud CLI.

To give your service account the necessary scopes and link it to your VM instance, run the following:

gcloud compute instances stop VM-INSTANCE-NAME

gcloud compute instances set-service-account VM-INSTANCE-NAME \
    --service-account SERVICE-ACCOUNT-EMAIL  \
    --scopes="https://www.googleapis.com/auth/cloud-platform,https://www.googleapis.com/auth/analytics.readonly"

In the Google Analytics UI, grant the service account access to a Google Analytics property.

Enable the Data API

To select or create a Google Cloud project, and enable the API, click Enable the Google Analytics Data API v1.

Install an SDK

Install the SDK for your programming language.

Go

go get google.golang.org/genproto/googleapis/analytics/data/v1beta

REST

Configure your environment variables by entering the following. Replace PROJECT_ID with the ID of your Google Cloud project and PROPERTY_ID with the ID of your Google Analytics property.

  export PROJECT_ID=PROJECT_ID
  export PROPERTY_ID=PROPERTY_ID

Make an API call

To verify your setup and make an API call, run the following sample.

This sample calls the runReport method. The response lists active users for your property.

To install all the Analytics API code samples, see our GitHub.

Java

google-analytics-data/src/main/java/com/google/analytics/data/samples/QuickstartSample.java

Open in Cloud Shell View on GitHub

import com.google.analytics.data.v1beta.BetaAnalyticsDataClient;
import com.google.analytics.data.v1beta.DateRange;
import com.google.analytics.data.v1beta.Dimension;
import com.google.analytics.data.v1beta.Metric;
import com.google.analytics.data.v1beta.Row;
import com.google.analytics.data.v1beta.RunReportRequest;
import com.google.analytics.data.v1beta.RunReportResponse;

/**
 * Google Analytics Data API sample quickstart application.
 *
 * <p>This application demonstrates the usage of the Analytics Data API using service account
 * credentials.
 *
 * <p>Before you start the application, please review the comments starting with "TODO(developer)"
 * and update the code to use correct values.
 *
 * <p>To run this sample using Maven:
 *
 * <pre>{@code
 * cd google-analytics-data
 * mvn compile exec:java -Dexec.mainClass="com.google.analytics.data.samples.QuickstartSample"
 * }</pre>
 */
public class QuickstartSample {

  public static void main(String... args) throws Exception {
    /**
     * TODO(developer): Replace this variable with your Google Analytics 4 property ID before
     * running the sample.
     */
    String propertyId = "YOUR-GA4-PROPERTY-ID";
    sampleRunReport(propertyId);
  }

  // This is an example snippet that calls the Google Analytics Data API and runs a simple report
  // on the provided GA4 property id.
  static void sampleRunReport(String propertyId) throws Exception {
    // Using a default constructor instructs the client to use the credentials
    // specified in GOOGLE_APPLICATION_CREDENTIALS environment variable.
    try (BetaAnalyticsDataClient analyticsData = BetaAnalyticsDataClient.create()) {

      RunReportRequest request =
          RunReportRequest.newBuilder()
              .setProperty("properties/" + propertyId)
              .addDimensions(Dimension.newBuilder().setName("city"))
              .addMetrics(Metric.newBuilder().setName("activeUsers"))
              .addDateRanges(DateRange.newBuilder().setStartDate("2020-03-31").setEndDate("today"))
              .build();

      // Make the request.
      RunReportResponse response = analyticsData.runReport(request);

      System.out.println("Report result:");
      // Iterate through every row of the API response.
      for (Row row : response.getRowsList()) {
        System.out.printf(
            "%s, %s%n", row.getDimensionValues(0).getValue(), row.getMetricValues(0).getValue());
      }
    }
  }
}QuickstartSample.java

PHP

google-analytics-data/quickstart.php

Open in Cloud Shell View on GitHub

require 'vendor/autoload.php';

use Google\Analytics\Data\V1beta\Client\BetaAnalyticsDataClient;
use Google\Analytics\Data\V1beta\DateRange;
use Google\Analytics\Data\V1beta\Dimension;
use Google\Analytics\Data\V1beta\Metric;
use Google\Analytics\Data\V1beta\RunReportRequest;

/**
 * TODO(developer): Replace this variable with your Google Analytics 4
 *   property ID before running the sample.
 */
$property_id = 'YOUR-GA4-PROPERTY-ID';

// Using a default constructor instructs the client to use the credentials
// specified in GOOGLE_APPLICATION_CREDENTIALS environment variable.
$client = new BetaAnalyticsDataClient();

// Make an API call.
$request = (new RunReportRequest())
    ->setProperty('properties/' . $property_id)
    ->setDateRanges([
        new DateRange([
            'start_date' => '2020-03-31',
            'end_date' => 'today',
        ]),
    ])
    ->setDimensions([new Dimension([
            'name' => 'city',
        ]),
    ])
    ->setMetrics([new Metric([
            'name' => 'activeUsers',
        ])
    ]);
$response = $client->runReport($request);

// Print results of an API call.
print 'Report result: ' . PHP_EOL;

foreach ($response->getRows() as $row) {
    print $row->getDimensionValues()[0]->getValue()
        . ' ' . $row->getMetricValues()[0]->getValue() . PHP_EOL;
}quickstart.php

Python

google-analytics-data/quickstart.py

Open in Cloud Shell View on GitHub

from google.analytics.data_v1beta import BetaAnalyticsDataClient
from google.analytics.data_v1beta.types import (
    DateRange,
    Dimension,
    Metric,
    RunReportRequest,
)


def sample_run_report(property_id="YOUR-GA4-PROPERTY-ID"):
    """Runs a simple report on a Google Analytics 4 property."""
    # TODO(developer): Uncomment this variable and replace with your
    #  Google Analytics 4 property ID before running the sample.
    # property_id = "YOUR-GA4-PROPERTY-ID"

    # Using a default constructor instructs the client to use the credentials
    # specified in GOOGLE_APPLICATION_CREDENTIALS environment variable.
    client = BetaAnalyticsDataClient()

    request = RunReportRequest(
        property=f"properties/{property_id}",
        dimensions=[Dimension(name="city")],
        metrics=[Metric(name="activeUsers")],
        date_ranges=[DateRange(start_date="2020-03-31", end_date="today")],
    )
    response = client.run_report(request)

    print("Report result:")
    for row in response.rows:
        print(row.dimension_values[0].value, row.metric_values[0].value)

quickstart.py

Node.js

google-analytics-data/quickstart.js

Open in Cloud Shell View on GitHub

  /**
   * TODO(developer): Uncomment this variable and replace with your
   *   Google Analytics 4 property ID before running the sample.
   */
  // propertyId = 'YOUR-GA4-PROPERTY-ID';

  // Imports the Google Analytics Data API client library.
  const {BetaAnalyticsDataClient} = require('@google-analytics/data');

  // Using a default constructor instructs the client to use the credentials
  // specified in GOOGLE_APPLICATION_CREDENTIALS environment variable.
  const analyticsDataClient = new BetaAnalyticsDataClient();

  // Runs a simple report.
  async function runReport() {
    const [response] = await analyticsDataClient.runReport({
      property: `properties/${propertyId}`,
      dateRanges: [
        {
          startDate: '2020-03-31',
          endDate: 'today',
        },
      ],
      dimensions: [
        {
          name: 'city',
        },
      ],
      metrics: [
        {
          name: 'activeUsers',
        },
      ],
    });

    console.log('Report result:');
    response.rows.forEach((row) => {
      console.log(row.dimensionValues[0], row.metricValues[0]);
    });
  }

  runReport();quickstart.js

.NET


 {         

  

       

 

                } style="float: left; padding-top: 3px; margin-left: 5px;"> /googleanalytics/dotnet-docs-samples/blob/main/analytics-data/QuickStart/QuickStart.cs" target="_blank" style="color: white;"> /QuickStart.cs style="text-align: right; float: right;"> this sample or repository in the Google Cloud Shell Editor" nsole.cloud.google.com/cloudshell/open?git_repo=https%3A%2F%2Fgithub.com%2Fgoogleanalytics%2Fdotnet-docs-samples&%3Bpage=editor&%3Bopen_in_editor=analytics-data%2FQuickStart%2FQuickStart.cs&authuser=0"> top">Open in Cloud Shell target="_blank" href="https://github.com/googleanalytics/dotnet-docs-samples/blob/main/analytics-data/QuickStart/QuickStart.cs" track-name="gitHubViewButton" tination="https://github.com/googleanalytics/dotnet-docs-samples/blob/main/analytics-data/QuickStart/QuickStart.cs">View on GitHub class="devsite-click-to-copy notranslate" suppresswarning="suppresswarning" dir="ltr" is-upgraded syntax="GDScript">using Google.Analytics.Data.V1Beta; using System; namespace AnalyticsSamples class QuickStart { static void SampleRunReport(string propertyId="YOUR-GA4-PROPERTY-ID") { /** * TODO(developer): Uncomment this variable and replace with your *  Google Analytics 4 property ID before running the sample. */ // propertyId = "YOUR-GA4-PROPERTY-ID"; // Using a default constructor instructs the client to use the credentials // specified in GOOGLE_APPLICATION_CREDENTIALS environment variable. BetaAnalyticsDataClient client = BetaAnalyticsDataClient.Create(); // Initialize request argument(s) RunReportRequest request = new RunReportRequest { Property = "properties/" + propertyId, Dimensions = { new Dimension{ Name="city"}, }, Metrics = { new Metric{ Name="activeUsers"}, }, DateRanges = { new DateRange{ StartDate="2020-03-31", EndDate="today"}, }, }; // Make the request RunReportResponse response = client.RunReport(request); Console.WriteLine("Report result:"); foreach(Row row in response.Rows) { Console.WriteLine("{0}, {1}", row.DimensionValues[0].Value, row.MetricValues[0].Value); } } static int Main(string[] args) { if (args.Length > 0) { SampleRunReport(args[0]); } else { SampleRunReport(); } return 0; } } class="devsite-github-link nocode no-select">QuickStart.cs

REST

To send this request, run the curl command from the command line or include the REST call in your application.

curl -X POST \
  -H "Authorization: Bearer $(gcloud auth application-default print-access-token)" \
  -H "x-goog-user-project: ${PROJECT_ID}" \
  -H "Content-Type: application/json" \
  -d '
  {
    "dateRanges": [
      {
        "startDate": "2025-01-01",
        "endDate": "2025-02-01"
      }
    ],
    "dimensions": [
      {
        "name": "country"
      }
    ],
    "metrics": [
      {
        "name": "activeUsers"
      }
    ]
  }'  https://analyticsdata.googleapis.com/v1beta/properties/${PROPERTY_ID}:runReport

Here's a sample response:

{
  "dimensionHeaders": [
    {
      "name": "country"
    }
  ],
  "metricHeaders": [
    {
      "name": "activeUsers",
      "type": "TYPE_INTEGER"
    }
  ],
  "rows": [
    {
      "dimensionValues": [
        {
          "value": "United States"
        }
      ],
      "metricValues": [
        {
          "value": "3242"
        }
      ]
    },
    {
      "dimensionValues": [
        {
          "value": "(not set)"
        }
      ],
      "metricValues": [
        {
          "value": "3015"
        }
      ]
    },
    {
      "dimensionValues": [
        {
          "value": "India"
        }
      ],
      "metricValues": [
        {
          "value": "805"
        }
      ]
    }
  ],
  "rowCount": 3,
  "metadata": {
    "currencyCode": "USD",
    "timeZone": "America/Los_Angeles"
  },
  "kind": "analyticsData#runReport"
}

Google Analytics API quickstart Stay organized with collections Save and categorize content based on your preferences.

Before you begin

Enable the Data API

Install an SDK

Java

PHP

Python

Node.js

.NET

Ruby

Go

REST

Make an API call

Java

PHP

Python

Node.js

.NET

REST

Google Analytics API quickstart
Stay organized with collections Save and categorize content based on your preferences.