awesome-quantified-self VS myinfra

This sounds like something Beeminder [1] is doing since 2011, have you heard of them?

They have a huge community and tools ecosystem.

You might also want to check the Awesome List "Quantified Self" [2] if you like these kind of tools.

[1] https://www.beeminder.com/overview

[2] https://github.com/woop/awesome-quantified-self

Sorry also to add, you might find something meeting your requirements here: https://github.com/woop/awesome-quantified-self

https://github.com/woop/awesome-quantified-self The Quantified Self is a movement to incorporate technology into data acquisition on aspects of a person's daily life in terms of inputs (e.g. food consumed, quality of surrounding air), states (e.g. mood, arousal, blood oxygen levels), and performance (mental and physical).

https://github.com/woop/awesome-quantified-self MIT's OCW https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-s897-machine-learning-for-healthcare-spring-2019/lecture-videos/lecture-1-what-makes-healthcare-unique/ https://github.com/ran88dom99/QS-data-flow-network-graph

Was it? Seems that it had some updates (maybe not as active as it used to https://github.com/woop/awesome-quantified-self/commits/mast... )

Either way don't think I've seen anything better, so the best way would be to suggest them updates or help maintaining :)

I wonder if you'd like this community: https://github.com/woop/awesome-quantified-self

It's similar to what you're describing and aligns well with the idea of using your personal data in a more open way.

There are many other apps/services too - a list can be found at Awesome Quantified Self. The idea of a centralized aggregator for personal data is really popular, and many people are trying to make them - including me! However, as far as I know, none of them have truly caught on/offered really deep insight into data yet.

My understanding so far is that if you have some programing background, the best workable solution today is to write little pieces of code that recover your data regularly from different APIs (store in csv). There are frequently such things already existing on github you can reuse like the Awesome QS project.

Graphviz is awesome!

Here are a couple of my diagrams:

https://beepb00p.xyz/blog-graph.html -- graph of my blog pages with tags/connections between posts, generated with a DSL-ish python script https://github.com/karlicoss/beepb00p/blob/master/misc/index...

https://beepb00p.xyz/myinfra.html -- map of my personal data & infrastructure (discussed a year ago https://news.ycombinator.com/item?id=26269832 ). Also a similar DSL https://github.com/karlicoss/myinfra/blob/master/generate.py

The main downside for me is that sometimes it gets the positioning wrong, and you can see how it can be easily fixed, but it's hard to convince graphviz to actually do so. Basically I'd love a tool where I can do 10% of positioning manually and let the rest be constraint based like in graphviz.

Not the first time, but possibly the biggest thing I've drawn in it...

There definitely are some weird things when you try to plot complicated things, fighting with weird placement, clusters etc. But not sure if it's me or Graphviz to blame for this. But I don't really know a better tool. If I knew how the diagram would look in hindsight I might have drawn in manually in inkscape or something, but when I started I didn't know what I would end up with, so needed to be an automatic tool :)

To minimize the manual work, I ended up with a mix of DSL in python and raw graphviz commands: https://github.com/karlicoss/myinfra/blob/fc6345c31c4e49b534...

Depending on the things you want to represent a better fit might be force layout, for example something like https://observablehq.com/@morvasaaty/d3-force-notes