The hassle-free way to integrate amplitude into any python application.
Project description
Amplitude Tracker library lets you record analytics data from your Python code to Amplitude
Getting Started
Install amplitude-tracker using pip:
pip install amplitude-tracker
Inside your app, you’ll want to set your write_key before making any analytics calls:
import amplitude_tracker as amplitude
amplitude.write_key = 'xxxxxxxxxxxxxxx'
Note: If you need to send data to multiple Segment sources, you can initialize a new Client for each write_key.
Development Settings
The default initialization settings are production-ready and queue messages to be processed by a background thread.
In development you might want to enable some settings to make it easier to spot problems. Enabling amplitude.debug will log debugging info to the Python logger. You can also add an on_error handler to specifically print out the response you’re seeing from the Amplitude’s API.
def on_error(error, items):
print("An error occurred:", error)
analytics.debug = True
analytics.on_error = on_error
Track
track lets you record the actions your users perform. Every action triggers what we call an “event”, which can also have associated properties.
import amplitude_tracker as amplitude
amplitude.write_key = 'xxxxxxxxxxxxxxx'
amplitude.track(
user_id="xxx",
event_type="xxx",
user_properties={"trait": "xxx"},
event_properties={"attribute": "xxx"})
Batching
This library is built to support high performance environments. That means it is safe to use amplitude-tracker on a web server that’s serving hundreds of requests per second.
Every call track method does not result in an HTTP request, but is queued in memory instead. Messages are flushed in batch in the background, which allows for much faster operation.
By default, this library will flush:
every 100 messages (control with upload_size)
if 0.5 seconds has passed since the last flush (control with upload_interval)
There is a maximum of 500KB per batch request and 32KB per call.
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