strava-gear
Strava-local-heatmap
| strava-gear | Strava-local-heatmap | |
|---|---|---|
| 3 | 1 | |
| 28 | 151 | |
| - | - | |
| 7.5 | 4.8 | |
| 11 days ago | 3 months ago | |
| Python | Python | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
strava-gear
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Strava finally allows users to add gear directly from the app
There's also https://github.com/liskin/strava-gear which I released this week. It's a command-line tool, so the audience is a bit limited, but it's way easier to add half a dozen bikes with dozens of components by editing a local text file than entering all that through a web interface that doesn't forgive mistakes.
- Show HN: Strava-gear – local-first rule-based component tracker for Strava
- strava-gear: Local rule-based tracker of gear and component wear for Strava
Strava-local-heatmap
What are some alternatives?
strava-offline - Keep a local mirror of Strava activities for further analysis/processing
fit2gpx - A simple Python library for converting .FIT files to .GPX files. It also includes tools to convert Strava data downloads in bulk to GPX.
gpxpy - gpx-py is a python GPX parser. GPX (GPS eXchange Format) is an XML based file format for GPS tracks.
plotly-calplot - The easiest and best looking Calendar Heatmap you'll find, made with Plotly.
pyheat - pprofile + matplotlib = Python program profiled as an awesome heatmap!
running_page - Make your own running home page
GpxTrackPoster - Create a visually appealing poster from your GPX tracks
zwift-workout-file-reference - Reference documentation for the Zwift workout file format
july - A small library for creating pretty heatmaps of daily data.
pyheatmagic - IPython magic command to profile and view your python code as a heat map.