Hopscotch

Tracking

hopscotch-analytics collects anonymous usage analytics to help improve the library. This page explains exactly what is tracked and how to opt out.

What we track

We track method calls and widget actions only:

  • Eventstream creation — dataset shape (number of rows and columns)
  • Data processor calls — which processors are used (e.g. filter_events, collapse_events)
  • Widget and headless method calls — which visualizations are used
  • Widget interactions — cloud save/load actions, authentication screen shown

Every event includes anonymous device metadata: OS, Python version, library version, and runtime environment (Jupyter, VS Code, Google Colab, or script).

What we do not track

We never collect any sensitive data from your eventstream — no event names, no user identifiers, no path contents, no segment values, and no business metrics. Your data stays entirely on your machine.

Opting out

Set the environment variable HOPSCOTCH_NO_TRACK=1 before starting your notebook kernel:

# In your shell profile (.zshrc, .bashrc)
export HOPSCOTCH_NO_TRACK=1

# Or at the top of a notebook cell
import os
os.environ["HOPSCOTCH_NO_TRACK"] = "1"

Google Colab

Add a secret named HOPSCOTCH_NO_TRACK with value 1 in Colab → Settings → Secrets, then enable notebook access for it. The secret persists across all Colab sessions automatically.