Universal analytics python library
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.
The easiest way to install universal-analytics is directly from PyPi using pip
by running the following command:
pip install universal-analytics-python3
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:
Additional tracking types supported with property dictionaries:
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")
This code is distributed under the terms of the MIT license.
A full changelog is maintained in the CHANGELOG file.
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.