google_analytics_graphql_mutation

"""Hello Analytics Reporting API V4."""
import pandas as pd
import matplotlib.pyplot as plt
from apiclient.discovery import build
from oauth2client.service_account import ServiceAccountCredentials
import requests, json
import dataframe_image as dfi
import cloudinary
import cloudinary.uploader
import cloudinary.api

SCOPES = ['https://www.googleapis.com/auth/analytics.readonly']
KEY_FILE_LOCATION = "PATH_TO_ANALYTICS_API_KEY_JSON_FILE"
VIEW_ID = 'VIEW_ID'
cloudinary.config( 
  cloud_name = "CLOUDINARY_LIBRARY_NAME", 
  api_key = "CLOUDINARY_API_KEY", 
  api_secret = "CLOUDINARY_API_SECRET_KEY" 
)

def ga_response_dataframe(response):
    row_list = []
    # Get each collected report
    for report in response.get('reports', []):
        # Set column headers
        column_header = report.get('columnHeader', {})
        dimension_headers = column_header.get('dimensions', [])
        metric_headers = column_header.get('metricHeader', {}).get('metricHeaderEntries', [])
    
        # Get each row in the report
        for row in report.get('data', {}).get('rows', []):
            # create dict for each row
            row_dict = {}
            dimensions = row.get('dimensions', [])
            date_range_values = row.get('metrics', [])

            # Fill dict with dimension header (key) and dimension value (value)
            for header, dimension in zip(dimension_headers, dimensions):
                row_dict[header] = dimension

            # Fill dict with metric header (key) and metric value (value)
            for i, values in enumerate(date_range_values):
                for metric, value in zip(metric_headers, values.get('values')):
                # Set int as int, float a float
                    if ',' in value or '.' in value:
                        row_dict[metric.get('name')] = float(value)
                    else:
                        row_dict[metric.get('name')] = int(value)

            row_list.append(row_dict)
    return pd.DataFrame(row_list)

def initialize_analyticsreporting():
  """Initializes an Analytics Reporting API V4 service object.

  Returns:
    An authorized Analytics Reporting API V4 service object.
  """
  credentials = ServiceAccountCredentials.from_json_keyfile_name(
      KEY_FILE_LOCATION, SCOPES)

  # Build the service object.
  analytics = build('analyticsreporting', 'v4', credentials=credentials)

  return analytics


def get_report(analytics):
  """Queries the Analytics Reporting API V4.

  Args:
    analytics: An authorized Analytics Reporting API V4 service object.
  Returns:
    The Analytics Reporting API V4 response.
  """
  return analytics.reports().batchGet(
      body={
        'reportRequests': [
        {
          'viewId': VIEW_ID,
          'dateRanges': [{'startDate': '7daysAgo', 'endDate': 'today'}],
          'metrics': [
            {"expression": "ga:sessions"},
        ], "dimensions": [
            {"name": "ga:browser"}
        ]
        }]
      }
  ).execute()


def print_response(response):
  """Parses and prints the Analytics Reporting API V4 response.

  Args:
    response: An Analytics Reporting API V4 response.
  """
  for report in response.get('reports', []):
    columnHeader = report.get('columnHeader', {})
    dimensionHeaders = columnHeader.get('dimensions', [])
    metricHeaders = columnHeader.get('metricHeader', {}).get('metricHeaderEntries', [])

    for row in report.get('data', {}).get('rows', []):
      dimensions = row.get('dimensions', [])
      dateRangeValues = row.get('metrics', [])

      for header, dimension in zip(dimensionHeaders, dimensions):
        print(header + ': ', dimension)

      for i, values in enumerate(dateRangeValues):
        print('Date range:', str(i))
        for metricHeader, value in zip(metricHeaders, values.get('values')):
          print(metricHeader.get('name') + ':', value)


def main():
  analytics = initialize_analyticsreporting()
  response = get_report(analytics)
  TOKEN = "WPGRAPHQL_AUTH_TOKEN"
  WPGRAPHQL_ENDPOINT = "WPGRAPHQL_ENDPOINT"

  content_data= str(response)
  plt.style.use('ggplot')

  df = ga_response_dataframe(response)

  # Pivot table to have browsers as columns
  df.set_index('ga:browser', inplace=True)
  axes = df.plot(kind='pie', figsize=(12.5, 6), subplots=True, legend=False)
  plt.savefig('df3.png')
  upload_result = cloudinary.uploader.upload("PATH_TO_LOCAL_IMAGE_FILE")
  upload_url = upload_result["secure_url"]
  headers = {
    "Content-Type": "application/json",
    "Authorization": 'Bearer ' + TOKEN
  }


  mutation = """
   mutation CreateIllustration {
  createMediaItem(
    input: {title: "Plot",
    filePath: %s,
    }
  ) {
    clientMutationId
  }
}
 """ % json.dumps(upload_url)



  data = (requests.post(WPGRAPHQL_ENDPOINT, json={'query': mutation}, headers=headers).json())

  print(data)
  print_response(response)
  

if __name__ == '__main__':
  main()