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:
tracker.send("pageview", path="/test", title="Test page")
tracker.send("pageview", {"path": "/test", "title": "Test page"})
Server-side experiments:
tracker.set("exp", "$experimentId.$variationId")
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.