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Universal Analytics for Python

This library provides a Python interface to Google Analytics, supporting the Universal Analytics Measurement Protocol, with an interface modeled (loosely) after Google's analytics.js.

NOTE this project is reasonably feature-complete for most use-cases, covering all relevant features of the Measurement Protocol, however we still consider it beta. Please feel free to file issues for feature requests.

Contact

Email: [email protected]

Installation

The easiest way to install universal-analytics is directly from PyPi using pip by running the following command:

pip install universal-analytics-python

Or use latest code:

pip install -e git+https://github.com/analytics-pros/universal-analytics-python.git#egg=universal-analytics-python-dev

Otherwise you can download source code and install it directly:

python setup.py install

Usage

For the most accurate data in your reports, Analytics Pros recommends establishing a distinct ID for each of your users, and integrating that ID on your front-end web tracking, as well as back-end tracking calls. This provides for a consistent, correct representation of user engagement, without skewing overall visit metrics (and others).

A simple example:

from UniversalAnalytics import Tracker

tracker = Tracker.create('UA-XXXXX-Y', client_id = CUSTOMER_UNIQUE_ID)
tracker.send('event', 'Subscription', 'billing')

Please see the test/test_everything.py script for additional examples.

This library support the following tracking types, with corresponding (optional) arguments:

  • pageview: [ page path ]
  • event: category, action, [ label [, value ] ]
  • social: network, action [, target ]
  • timing: category, variable, time [, label ]

Additional tracking types supported with property dictionaries:

  • transaction
  • item
  • screenview
  • exception

Property dictionaries permit the same naming conventions given in the analytics.js Field Reference, with the addition of common spelling variations, abbreviations, and hyphenated names (rather than camel-case). These are also demonstrated in the tests/main.py file.

Further, the property dictionaries support names as per the Measurement Protocol Parameter Reference, and properties/parameters can be passed as named arguments.

Example:

  # as python named-arguments
  tracker.send('pageview', path = "/test", title = "Test page") 
  
  # as property dictionary 
  tracker.send('pageview', {
    'path': "/test",
    'title': "Test page"
  })

Features not implemented

  • Throttling

We're particularly interested in the scope of throttling for back-end tracking for users who have a defined use-case for it. Please contact us if you have such a use-case.

License

universal-analytics-python is licensed under the BSD license