358 karma · joined January 12, 2017
Movement Name:
10 12r
10 10r 2s
10 8rIn order for this to parse correctly, there needs to be an ' in front of "60m" like "'60m".
Thanks for finding this. I have updated that example on the site.
@ 2020/07/15; #r:hpu; #w:3; #c:3; #d:1; push: 14; 18; 14; 14; 14; 30
@ 2020/07/14; pull: 5; 5; 5; 5
...
Definitely not as human readable as yours for your use case. Thanks for sharing!I will do some noodling on this. If you have ideas, I’d love to dialog on them. I hadn’t implemented anything beyond the basics just because I hadn’t been doing them lately. I definitely want to support your use case as a first class language feature.
Squat:
# bands: 200lb
# box: 12 inches
# rest: 45 seconds
* wide and medium alternating
225 2r 10s Clean: 150 2r 5s
+ Jerk: 150 5sThanks for looking!
I use the metadata to capture partial ranges and accommodating resistance. For example
Bench:
# grip: index on smooth
# pin height: 16 inches off bench
# chains: 100lbs
135 5r
225 3r
...
And on and on. I have added pieces to the language over the two years I’ve been using it and I hope to write a better guide (maybe short book) on how you can capture different kinds of training.Thanks for looking!
For the question of the usefulness of portability, let’s imagine StrongLifts uses Traindown and you have the ability to access that data directly as Traindown files.
Now imagine someone has developed an analytics package that slurps your owned data and that allows you to easily spot patterns that can improve your results. You could use that immediately and find value. You would not need to export whatever mess and try to make it work assuming they even let you do that.
That’s the idea, anyhow. I feel very strongly that YOU should own YOUR DATA and applications should provide value ON TOP of your data. This provides you true freedom of choice.
I have a bit in the FAQ in the Guide that hand waves how you could model things like cardio. I personally model my intervals like an example from today
Squat: # bands: 200lb # box: 12 inches # rest: 45 seconds * wide and medium alternating 225 2r 10s
I love how you did your metadata in your example. I intend to leave the language VERY open ended and hope folks build tools for athletes that provide functionality that is spec compliant (thus portable!) but leverages nuances for the given sport. Thanks for taking a look!
I also have a background in Olympic weightlifting and know exactly how convoluted complexes can get.
Currently, I model those as either supersets (when it fits) or I name the complex as the movement and then use the metadata to get at a data shape that mostly fits.
Example of supersets would be something like
Clean: 150 2r 5s + Jerk: 150 5s
For a clean double, single jerk. The named complex just captures the reps and weights per submovment in the metadata.
The intent is to provide a common format for training data.
By training data, I mean data you'd commonly find in a workout app. Think "Squats at 500 for 10 reps" sorta thing.
Anyhow, thanks for looking!