distilling-flask | Strava app for display and analysis of personal running data

distilling-flask is a Python library. distilling-flask has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install distilling-flask' or download it from GitHub, PyPI.

Given a valid strava access token, the Flask app talks to Strava's API and displays running activities in a dashboard using plotly Dash. I built this app so I could pick apart my raw Strava data, which includes data streams for elevation, grade, and moving/stopped periods. In short, I think Strava presents data in an unrealistically favorable way in its apps, and I wanted to work with the raw feeds. There is power in looking at the reality of things. Over time, I generalized the Dash app to accept pandas.DataFrame as input. This means you can view any activity data you want, as long as it is formatted correctly, using the create_dash_app function. If you have a valid Strava access token, you can view any of your Strava runs in a dashboard powered by Plotly Dash. From there, you can save each run to a local database, and view the long-term effects of training in a training log dashboard. See the Examples section below to see how everything works.