@dudley

The code snippet provided in the previous response is incorrect. Here's the correct way to trigger Google Analytics events from Python:

Install the google-api-python-client library by running the following command in your terminal:

pip install google-api-python-client

Create a new project in the Google APIs Console and enable the Google Analytics Reporting API.
Generate a service account key in the Google APIs Console, download the JSON file, and store it securely on your server.
Import the necessary libraries and authenticate using the service account key:

from apiclient.discovery import build
from oauth2client.service_account import ServiceAccountCredentials

# Path to the service account key JSON file
KEY_FILE_LOCATION = '/path/to/service-account-key.json'

# Define the scope of the API access
SCOPES = ['https://www.googleapis.com/auth/analytics.readonly']

# Authenticate using the service account key
credentials = ServiceAccountCredentials.from_json_keyfile_name(KEY_FILE_LOCATION, SCOPES)
analytics = build('analyticsreporting', 'v4', credentials=credentials)

Make sure to replace /path/to/service-account-key.json with the actual path to your service account key JSON file.

Use the analytics.reports().batchGet() method to send events to Google Analytics. Here's an example of how to track an event:

response = analytics.reports().batchGet(
  body={
    'reportRequests': [
      {
        'viewId': 'YOUR_VIEW_ID',
        'dateRanges': [{'startDate': '2022-01-01', 'endDate': '2022-01-31'}],
        'metrics': [{'expression': 'ga:totalEvents'}],
        'dimensions': [{'name': 'ga:eventCategory'}, {'name': 'ga:eventAction'}, {'name': 'ga:eventLabel'}],
        'dimensionFilterClauses': [{'filters': [{'dimensionName': 'ga:eventAction', 'operator': 'EXACT', 'expressions': ['Event Action']}]}]
      }
    ]
  }
).execute()

Replace 'YOUR_VIEW_ID' with the actual View ID of your Google Analytics property. Modify the other parameters (startDate, endDate, metrics, dimensions, dimensionFilterClauses) based on your specific event tracking requirements.

Process the response to extract the event data:

for report in response.get('reports', []):
  columnHeader = report.get('columnHeader', {})
  dimensionHeaders = columnHeader.get('dimensions', [])
  metricHeaders = columnHeader.get('metricHeader', {}).get('metricHeaderEntries', [])
  rows = report.get('data', {}).get('rows', [])
  
  for row in rows:
    dimensions = row.get('dimensions', [])
    metrics = row.get('metrics', [])
  
    for header, dimension in zip(dimensionHeaders, dimensions):
      print(header + ': ' + dimension)
      
    for i, values in enumerate(metrics):
      print('Metrics:')
      
      for metricHeader, value in zip(metricHeaders, values.get('values')):
        print(metricHeader.get('name') + ': ' + value)

This code will print the event dimensions and metrics for each row of the response. You can modify the code to store the data or perform further analysis as needed.

That's it! You can use the above code as a starting point to trigger Google Analytics events from Python.

#python