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GoldenCheetah
GoldenCheetah OpenData Project compatibility
It would be nice if sweatpy supports working with data from the GoldenCheetah OpenData Project right out of the box. Probably could be a separate module in sweat.io, similar to sweat.io.strava, and sweat.io.fit.
Resources: https://osf.io/6hfpz/ https://github.com/GoldenCheetah/OpenData
There is a python lib for working with osf too https://github.com/osfclient/osfclient
Thanks for pointing to the osfclient, that could provide a really seamless experience without having to download any files manually. Will look into it.
I'd be really interested to get some thoughts on what kind of 'index' or 'metadata' we should generate to help folks navigate across what is likely to be a big bunch of zipfiles.
.. but perhaps some of this work belongs in the OpenData project not sweatpy, so will add you and Maksym to that project too.
I think there is already enough metadata: the name of the zip file matches the athlete id and the json contains enough information to do things like "get the latest activity" or "list the activities that contain power".
I started working on a POC that you can view here. For me it would make sense to let sweatpy handle opendata directly via osfclient.
But maybe you think this should be handled in https://github.com/GoldenCheetah/OpenData, possibly with a dependency on sweatpy? Can you explain the purpose of this OpenData repo?
OpenData repo is for tooling to work with the opendata files; python, R, js
When/if there are hundreds of zip files you won't want to download and unzup them all .. some kind of index will help id athlete files that are relevant to your analysis e.g. cycling, have power and cadence, multi years...
Clear.
True that. It might be useful to store a separate file with metadata in osf or somewhere else. Maybe even in the OpenData repo?
On 5 Apr 2018 at 21:17, Mark Liversedge [email protected] wrote:
OpenData repo is for tooling to work with the opendata files; python, R, js
When/if there are hundreds of zip files you won't want to download and unzup them all .. some kind of index will help id athlete files that are relevant to your analysis e.g. cycling, have power and cadence, multi years...
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