strava_calendar's Introduction

Strava Calendar

A project to make beautiful visualizations from Strava data. Heavily inspired by the wonderful R library by Markus Volz.

Install

pip install git+git://github.com/colcarroll/strava_calendar.git

Use

First download your data from Strava (see below for how). The last step gives you a zip_path to the archive with all the data. This is quite slow the first time you run it for a zip file and year (~5mins), but quite fast after that (~5s).

from strava_calendar import plot_calendar

plot_calendar(zip_path=zip_path, year=2018)

You can control how many columns there are, the spacing between months and columns, and the label in the top left:

plot_calendar(zip_path=zip_path, year=2017, n_cols=6, month_gap=1.5, col_gap=1, label='')

You can also plot a single column of weeks, which is pleasant.

plot_calendar(zip_path=zip_path, year=2017, n_cols=1)

If you want to write more custom code, you can give that a shot, too:

import datetime

import matplotlib.pyplot as plt

from strava_calendar import Plotter, get_data

data = get_data(zip_path, 'running', datetime.datetime(2018, 1, 1), datetime.datetime(2019, 1, 1))

plotter = Plotter(data)

fig, ax = plt.subplots(figsize=(9, 6))

fig, ax, offset = plotter.plot_month(year=2018, month=6, fig=fig, ax=ax)
ax.text(0, offset + 4.2, 'Weeee!', fontdict={'fontsize': 32, 'fontweight': 'heavy'}, alpha=0.5)

Bulk export from Strava

The process for downloading data is also described on the Strava website:

After logging into Strava, select "Settings" from the main drop-down menu at top right of the screen.
Select "My Account" from the navigation menu to the left of the screen.
Under the "Download or Delete Your Account" heading, click the "Get Started" button.
Under the "Download Request", heading, click the "Request Your Archive" button. Be careful not to delete your account here!
The archive takes a while to be sent. Download the zipped file to a location whose path you know.

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