Why do I want that?
Disk space is cheap. Your time is not.
Metadata is, by definition, required to interpret your data.
So if your program doesn’t record metadata for you, then you’ll have to do it manually.
- Sounds tedious. And I'm lazy!
- What if you forget to write something down?
- What if your experiment finds new variables you didn't know were important?
- Even if you're not lazy, this much is apparent:
And less metadata is actually bad for your scientific outcomes:
PyX saves you from trying to prioritize data collection before the experiment,
letting you do it after the fact.
That means:
The little things add up. This is a big deal.
Why?
PyX will lead you into a
"data-rich" mindset, which
people have high hopes for:
And, it sets you up for future machine learning
applications by
stockpiling complete, machine-interpretable datasets.
I'll leave you with some testimonials
users were not compensated for their
participation
"Newton couldn't invent calculus, much less without PyX!"
~ Gottfried Leibniz
"If you have a procedure with ten parameters, you probably missed some.
Thanks to PyX, you can record them all!"
~ Alan Perlis
"I'm being quoted to introduce something"
~ Randall Munroe
"PyX has made you less of a disappointment"
~ my mother
Your tools guide how you work. So get yourself a
giant chainsaw.
~ me
Created by Jonathan Okasinski, lead developer, PyX
