Universal Analytics for Python

It's a fork of universal-analytics-python whith support for Python 3, batch requests, synchronous and asynchronous API calls.

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.

Installation

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

pip install universal-analytics-python3

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 for synchronous usage:

from universal_analytics import Tracker, HTTPRequest, HTTPBatchRequest

with HTTPRequest() as http:
    tracker = Tracker("UA-XXXXX-Y", http, client_id="unique-id")
    tracker.send("event", "Subscription", "billing")

with HTTPBatchRequest() as http:
    tracker = Tracker("UA-XXXXX-Y", http, client_id="unique-id")
    tracker.send("event", "Subscription", "billing")

A simple example for asynchronous usage:

import asyncio
from universal_analytics import Tracker, AsyncHTTPRequest, AsyncHTTPBatchRequest

async def main():
    async with AsyncHTTPRequest() as http:
        tracker = Tracker("UA-XXXXX-Y", http, client_id="unique-id")
        await tracker.send("event", "Subscription", "billing")

    async with AsyncHTTPBatchRequest() as http:
        tracker = Tracker("UA-XXXXX-Y", http, client_id="unique-id")
        await tracker.send("event", "Subscription", "billing")

loop = asyncio.get_event_loop()
loop.run_until_complete(main())

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).

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"})

Server-side experiments:

# Set the experiment ID and variation ID
tracker.set("exp", "$experimentId.$variationId")

# Send a pageview hit to Google Analytics
tracker.send("pageview", path="/test", title="Test page")

License

This code is distributed under the terms of the MIT license.

Changes

A full changelog is maintained in the CHANGELOG file.

Contributing

universal-analytics-python3 is an open source project and contributions are welcome! Check out the Issues page to see if your idea for a contribution has already been mentioned, and feel free to raise an issue or submit a pull request.