polkupy

Python package to analyse and visualise personal cycling activities. Loads GPX and FIT tracks into chainable pandas-backed objects, with built-in filtering, geography helpers, and rich Jupyter display.

Installation

For users, install from PyPI using:

pip install polkupy

To contribute to development, install with pixi using:

pixi install --all
pixi shell -e dev

Quick start

from polkupy import Ride, Trips

ride = Ride.from_gpx("path/to/ride.gpx")
ride  # -> route map + metadata in Jupyter

trips = Trips.from_gpx("data")  # one subfolder per bike
commutes = trips.between(start=(48.14, 11.56), end=(48.35, 11.79))

Structure

Ride/Trips wrap the underlying pandas DataFrame(s) in a chainable API.

src/polkupy/
├── __init__.py       # public API: Ride, Trips
├── core/
│   ├── ride.py       # Ride: one track
│   └── trips.py      # Trips: a collection of rides
├── io/
│   └── gpx.py
├── algorithms/
│   └── filters.py
├── clock.py
└── geo.py

Development

pixi run -e dev test         # pytest
pixi run -e dev check        # mypy + pylint
pixi run -e dev docs-build   # Sphinx HTML docs -> docs/_build/html

See CHANGELOG.md for release history.