559c8fd1d2
The format parameter allows to choose between JSON, FIT, TCX, PWX and CSV as the filetype to be used for the service instance. Default is JSON for backward compatibility and because it is the only format preserving all data. The use case is for coaches downloading FIT files from athletes Dropbox folders. Fixes #2710
GoldenCheetah
About
GoldenCheetah is a desktop application for cyclists and triathletes and coaches
- Analyse using summary metrics like BikeStress, TRIMP or RPE
- Extract insight via models like Critical Power and W'bal
- Track and predict performance using models like Banister and PMC
- Optimise aerodynamics using Virtual Elevation
- Train indoors with ANT and BTLE trainers
- Upload and Download with many cloud services including Strava, Withings and Todays Plan
- Import and export data to and from a wide range of bike computers and file formats
- Track body measures, equipment use and setup your own metadata to track
GoldenCheetah provides tools for users to develop their own own metrics, models and charts
- A high-performance and powerful built-in scripting language
- Local Python runtime or embedding a user installed runtime
- Embedded user installed R runtime
GoldenCheetah supports community sharing via the Cloud
- Upload and download user developed metrics
- Upload and download user, Python or R charts
- Import indoor workouts from the ErgDB
- Share anonymised data with researchers via the OpenData initiative
GoldenCheetah is free for everyone to use and modify, released under the GPL v2 open source license with pre-built binaries for Mac, Windows and Linux.
Installing
Golden Cheetah install and build instructions are documented for each platform;
INSTALL-WIN32 For building on Microsoft Windows
INSTALL-LINUX For building on Linux
INSTALL-MAC For building on Apple MacOS
macOS and Linux: 
Windows:
Official release builds, snapshots and development builds are all available from http://www.goldencheetah.org
NOTIO Fork
If you are looking for the NOTIO fork of GoldenCheetah it can be found here: https://github.com/notio-technologies/GCNotio