stokehook
running_page
stokehook | running_page | |
---|---|---|
1 | 3 | |
7 | 3,301 | |
- | - | |
0.0 | 9.0 | |
about 1 year ago | 10 days ago | |
Svelte | Python | |
- | 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.
stokehook
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Show: Sveltekit app using Firebase, Tailwind, Netlify
The source is at https://github.com/jpoehnelt/stokehook for those interested.
running_page
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Ask HN: Comment here about whatever you're passionate about at the moment
A resource recently shared in HN for running tech lovers https://github.com/yihong0618/running_page
- Running_page
What are some alternatives?
Hitrava - Convert your Huawei Health sport activities and import them in Strava.
Strava-local-heatmap - Python script to generate a high resolution heatmap from Strava GPX files
derive - Generate personal heatmap from GPX/TCX/FIT/IGC data
camp-viz - Camp Visualizer is a Python application that enables users to extract and store waypoint data from GPX files.
OctoPrint-GPX - An OctoPrint plug-in to use GPX as the protocol layer underneath rather than replacing g-code to talk to s3g/x3g machines, for example, a FlashForge.
Apache Superset - Apache Superset is a Data Visualization and Data Exploration Platform [Moved to: https://github.com/apache/superset]
strava-offline - Keep a local mirror of Strava activities for further analysis/processing
emurasoft.github.io - Sphinx project for https://www.emeditor.org/
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.
gpx-viz - Personal project to visualize gpx tracks
strava-uploader - utility to migrate Runkeeper data (GPX and CSV) to Strava
streamlit - Streamlit — A faster way to build and share data apps.